WorldWideScience

Sample records for anomalous network connectivity

  1. Connectivity of communication networks

    CERN Document Server

    Mao, Guoqiang

    2017-01-01

    This book introduces a number of recent developments on connectivity of communication networks, ranging from connectivity of large static networks and connectivity of highly dynamic networks to connectivity of small to medium sized networks. This book also introduces some applications of connectivity studies in network optimization, in network localization, and in estimating distances between nodes. The book starts with an overview of the fundamental concepts, models, tools, and methodologies used for connectivity studies. The rest of the chapters are divided into four parts: connectivity of large static networks, connectivity of highly dynamic networks, connectivity of small to medium sized networks, and applications of connectivity studies.

  2. Minimum cost connection networks

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Tvede, Mich

    . We use three axioms to characterize allocation rules that truthfully implement cost minimizing networks satisfying all connection demands in a game where: (1) a central planner announces an allocation rule and a cost estimation rule; (2) every agent reports her own connection demand as well as all...... connection costs; and, (3) the central planner selects a cost minimizing network satisfying reported connection demands based on estimated connection costs and allocates true connection costs of the selected network....

  3. Fluctuation-stabilized marginal networks and anomalous entropic elasticity.

    Science.gov (United States)

    Dennison, M; Sheinman, M; Storm, C; MacKintosh, F C

    2013-08-30

    We study the elastic properties of thermal networks of Hookean springs. In the purely mechanical limit, such systems are known to have a vanishing rigidity when their connectivity falls below a critical, isostatic value. In this work, we show that thermal networks exhibit a nonzero shear modulus G well below the isostatic point and that this modulus exhibits an anomalous, sublinear dependence on temperature T. At the isostatic point, G increases as the square root of T, while we find G∝Tα below the isostatic point, where α≃0.8. We show that this anomalous T dependence is entropic in origin.

  4. Anomalous diffusion on the Hanoi networks

    Science.gov (United States)

    Boettcher, S.; Gonçalves, B.

    2008-11-01

    Diffusion is modeled on the recently proposed Hanoi networks by studying the mean-square displacement of random walks with time, langr2rang~t2/dw. It is found that diffusion —the quintessential mode of transport throughout Nature— proceeds faster than ordinary, in one case with an exact, anomalous exponent dw=2- log2(phi)=1.30576... . It is an instance of a physical exponent containing the "golden ratio"\\phi=(1+\\sqrt{5})/2 that is intimately related to Fibonacci sequences and since Euclid's time has been found to be fundamental throughout geometry, architecture, art, and Nature itself. It originates from a singular renormalization group fixed point with a subtle boundary layer, for whose resolution phi is the main protagonist. The origin of this rare singularity is easily understood in terms of the physics of the process. Yet, the connection between network geometry and the emergence of phi in this context remains elusive. These results provide an accurate test of recently proposed universal scaling forms for first passage times.

  5. Handbook of networking & connectivity

    CERN Document Server

    McClain, Gary R

    1994-01-01

    Handbook of Networking & Connectivity focuses on connectivity standards in use, including hardware and software options. The book serves as a guide for solving specific problems that arise in designing and maintaining organizational networks.The selection first tackles open systems interconnection, guide to digital communications, and implementing TCP/IP in an SNA environment. Discussions focus on elimination of the SNA backbone, routing SNA over internets, connectionless versus connection-oriented networks, internet concepts, application program interfaces, basic principles of layering, proto

  6. Minimum cost connection networks

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Tvede, Mich

    2015-01-01

    demands. We use a few axioms to characterize allocation rules that truthfully implement cost minimizing networks satisfying all connection demands in a game where: (1) a central planner announces an allocation rule and a cost estimation rule; (2) every agent reports her own connection demand as well...... as all connection costs; (3) the central planner selects a cost minimizing network satisfying reported connection demands based on the estimated costs; and, (4) the planner allocates the true costs of the selected network. It turns out that an allocation rule satisfies the axioms if and only if relative...

  7. Quantifying bicycle network connectivity.

    Science.gov (United States)

    Lowry, Michael; Loh, Tracy Hadden

    2017-02-01

    The intent of this study was to compare bicycle network connectivity for different types of bicyclists and different neighborhoods. Connectivity was defined as the ability to reach important destinations, such as grocery stores, banks, and elementary schools, via pathways or roads with low vehicle volumes and low speed limits. The analysis was conducted for 28 neighborhoods in Seattle, Washington under existing conditions and for a proposed bicycle master plan, which when complete will provide over 700 new bicycle facilities, including protected bike lanes, neighborhood greenways, and multi-use trails. The results showed different levels of connectivity across neighborhoods and for different types of bicyclists. Certain projects were shown to improve connectivity differently for confident and non-confident bicyclists. The analysis showed a positive correlation between connectivity and observed utilitarian bicycle trips. To improve connectivity for the majority of bicyclists, planners and policy-makers should provide bicycle facilities that allow immediate, low-stress access to the street network, such as neighborhood greenways. The analysis also suggests that policies and programs that build confidence for bicycling could greatly increase connectivity.

  8. Anomalous brain functional connectivity contributing to poor adaptive behavior in Down syndrome.

    Science.gov (United States)

    Pujol, Jesus; del Hoyo, Laura; Blanco-Hinojo, Laura; de Sola, Susana; Macià, Dídac; Martínez-Vilavella, Gerard; Amor, Marta; Deus, Joan; Rodríguez, Joan; Farré, Magí; Dierssen, Mara; de la Torre, Rafael

    2015-03-01

    Research in Down syndrome has substantially progressed in the understanding of the effect of gene overexpression at the molecular level, but there is a paucity of information on the ultimate consequences on overall brain functional organization. We have assessed the brain functional status in Down syndrome using functional connectivity MRI. Resting-state whole-brain connectivity degree maps were generated in 20 Down syndrome individuals and 20 control subjects to identify sites showing anomalous synchrony with other areas. A subsequent region-of-interest mapping served to detail the anomalies and to assess their potential contribution to poor adaptive behavior. Down syndrome individuals showed higher regional connectivity in a ventral brain system involving the amygdala/anterior temporal region and the ventral aspect of both the anterior cingulate and frontal cortices. By contrast, lower functional connectivity was identified in dorsal executive networks involving dorsal prefrontal and anterior cingulate cortices and posterior insula. Both functional connectivity increases and decreases contributed to account for patient scoring on adaptive behavior related to communication skills. The data overall suggest a distinctive functional organization with system-specific anomalies associated with reduced adaptive efficiency. Opposite effects were identified on distinct frontal and anterior temporal structures and relative sparing of posterior brain areas, which is generally consistent with Down syndrome cognitive profile. Relevantly, measurable connectivity changes, as a marker of the brain functional anomaly, could have a role in the development of therapeutic strategies addressed to improve the quality of life in Down syndrome individuals.

  9. Navigation by anomalous random walks on complex networks

    Science.gov (United States)

    Weng, Tongfeng; Zhang, Jie; Khajehnejad, Moein; Small, Michael; Zheng, Rui; Hui, Pan

    2016-11-01

    Anomalous random walks having long-range jumps are a critical branch of dynamical processes on networks, which can model a number of search and transport processes. However, traditional measurements based on mean first passage time are not useful as they fail to characterize the cost associated with each jump. Here we introduce a new concept of mean first traverse distance (MFTD) to characterize anomalous random walks that represents the expected traverse distance taken by walkers searching from source node to target node, and we provide a procedure for calculating the MFTD between two nodes. We use Lévy walks on networks as an example, and demonstrate that the proposed approach can unravel the interplay between diffusion dynamics of Lévy walks and the underlying network structure. Moreover, applying our framework to the famous PageRank search, we show how to inform the optimality of the PageRank search. The framework for analyzing anomalous random walks on complex networks offers a useful new paradigm to understand the dynamics of anomalous diffusion processes, and provides a unified scheme to characterize search and transport processes on networks.

  10. Network Connection Management

    CERN Multimedia

    IT Department

    2005-01-01

    The CERN network database is a key element of the CERN network infrastructure. It is absolutely essential that its information is kept up-to-date for security reasons and to ensure smooth running of the network infrastructure. Over the years, some of the information in the database has become obsolete. The database therefore needs to be cleaned up, for which we are requesting your help. In the coming weeks, you may receive an electronic mail from Netops.database@cern.ch relating to the clean-up. If you receive such a message, it will be for one of the following reasons: You are the person responsible for or the main user of a system for which a problem has been detected, or You have been the supervisor of a person who has now left CERN (according to the HR database), or The problem has been passed up to you because someone under your supervision has not taken the necessary action within four weeks of notification. Just open the link that will be included in the message and follow the instructions. Thank ...

  11. Network Connection Management

    CERN Multimedia

    IT Department, Communication Systems and Network Group

    2005-01-01

    The CERN network database is a key element of the CERN network infrastructure. It is absolutely essential that its information is kept up-to-date for security reasons and to ensure a smooth running of the network infrastructure. Over the years, some of the information in the database has become obsolete. The database therefore needs to be cleaned up, for which we are requesting your help. In the coming weeks, you may receive an electronic mail from Netops.database@cern.ch relating to the clean-up. If you receive such a message, it will be for one of the following reasons: You are the person responsible for or the main user of a system for which a problem has been detected, or You have been the supervisor of a person who has now left CERN (according to the HR database), or The problem has been passed up to you because someone under your supervision has not taken the necessary action within four weeks of notification. Just open the link that will be included in the message and follow the instructions....

  12. The Connectivity Analysis of Intermittent Connected Wireless Network

    Institute of Scientific and Technical Information of China (English)

    Li Yun; Zhou Yahui; Liu Qilie; Wang Xiaoying

    2009-01-01

    The connectivity is a basic and important characteristic to the network, it expresses the situation of link connectivity directly, and provides important reference for the entire network plan. Using statistics and probability Theory, this article emphasizes the probability between any two nodes in the network which nodes are equally distributed and the connectivity of whole network. At last, this article has made verification through simulation and has made out a conclusion, the simulation result agrees with theoretical analysis.

  13. Navigation by anomalous random walks on complex networks

    CERN Document Server

    Weng, Tongfeng; Khajehnejad, Moein; Small, Michael; Zheng, Rui; Hui, Pan

    2016-01-01

    Anomalous random walks having long-range jumps are a critical branch of dynamical processes on networks, which can model a number of search and transport processes. However, traditional measurements based on mean first passage time are not useful as they fail to characterize the cost associated with each jump. Here we introduce a new concept of mean first traverse distance (MFTD) to characterize anomalous random walks that represents the expected traverse distance taken by walkers searching from source node to target node, and we provide a procedure for calculating the MFTD between two nodes. We use Levy walks on networks as an example, and demonstrate that the proposed approach can unravel the interplay between diffusion dynamics of Levy walks and the underlying network structure. Interestingly, applying our framework to the famous PageRank search, we can explain why its damping factor empirically chosen to be around 0.85. The framework for analyzing anomalous random walks on complex networks offers a new us...

  14. Isolated supra-cardiac partial anomalous pulmonary venous connection causing right heart failure

    Directory of Open Access Journals (Sweden)

    Robert Sogomonian

    2016-04-01

    Full Text Available Right heart failure (RHF has been overlooked as left heart failure has predominated. One of the many causes of RHF is partial anomalous pulmonary venous connection (PAPVC, an extremely rare entity in nature. Physicians should consider the unusual causes of RHF after ruling out the common causes.

  15. Neonatal repair of total anomalous pulmonary venous connection and lung agenesis.

    Science.gov (United States)

    Kaku, Yuji; Nagashima, Mitsugi; Matsumura, Goki; Yamazaki, Kenji

    2015-07-01

    Here we report a neonatal case of total anomalous pulmonary venous connection with left lung agenesis. Diagnostic imaging demonstrated that the left pulmonary veins were totally absent and the right pulmonary veins connected with the common pulmonary chamber. Drainage from the common pulmonary venous chamber entered the persistent left suerior vena cava. In addition, it revealed complete absence of the left main bronchus and left lung vessels. The neonate successfully underwent surgical repair 18 days after birth.

  16. On the Quality of Wireless Network Connectivity

    CERN Document Server

    Dasgupta, Soura

    2011-01-01

    Despite intensive research in the area of network connectivity, there is an important category of problems that remain unsolved: how to measure the quality of connectivity of a wireless multi-hop network which has a realistic number of nodes, not necessarily large enough to warrant the use of asymptotic analysis, and has unreliable connections, reflecting the inherent unreliable characteristics of wireless communications? The quality of connectivity measures how easily and reliably a packet sent by a node can reach another node. It complements the use of \\emph{capacity} to measure the quality of a network in saturated traffic scenarios and provides a native measure of the quality of (end-to-end) network connections. In this paper, we explore the use of probabilistic connectivity matrix as a possible tool to measure the quality of network connectivity. Some interesting properties of the probabilistic connectivity matrix and their connections to the quality of connectivity are demonstrated. We argue that the la...

  17. Local Natural Connectivity in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    SHANG Yi-Lun

    2011-01-01

    @@ In network theory, a complex network represents a system whose evolving structure and dynamic behavior contribute to its robustness.The natural connectivity is recently proposed as a spectral measure to characterize the robustness of complex networks.We decompose the natural connectivity of a network as local natural connectivity of its connected components and quantify their contributions to the network robustness.In addition, we compare the natural connectivity of a network with that of an induced subgraph of it based on interlacing theorems.As an application, we derive an inequality for eigenvalues of ErdSs-Renyi random graphs.%In network theory, a complex network represents a system whose evolving structure and dynamic behavior contribute to its robustness. The natural connectivity is recently proposed as a spectral measure to characterize the robustness of complex networks. We decompose the natural connectivity of a network as local naturai connectivity of its connected components and quantify their contributions to the network robustness. In addition, we compare the naturai connectivity of a network with that of an induced subgraph of it based on interlacing theorems. As an application, we derive an inequality for eigenvalues of Erdos-Renyi random graphs.

  18. Anomalous metapopulation dynamics on scale-free networks

    CERN Document Server

    Fedotov, Sergei

    2016-01-01

    We model transport of individuals across a heterogeneous scale-free network where a few weakly connected nodes exhibit heavy-tailed residence times. Such power laws are consistent with the Axiom of Cumulative Inertia, an empirical law stating that the rate at which people leave a place decreases with the associated residence time. We show numerically and analytically that "cumulative inertia" overpowers highly connected nodes in attracting network individuals. Our result, confirmed by empirical evidence, challenges the classical view that individuals will accumulate in highly connected nodes.

  19. Are we connected? : Ports in Global Networks

    NARCIS (Netherlands)

    R.A. Zuidwijk (Rob)

    2015-01-01

    markdownabstractAbstract Global supply chains are built on organizational, information, and logistics networks. Ports are connected via these networks and also need to connect these networks. Synchromodality is an innovative concept for container transportation, and the port plays an important ro

  20. Anesthetic implications of total anomalous systemic venous connection to left atrium with left isomerism

    Directory of Open Access Journals (Sweden)

    Parimala Prasanna Simha

    2012-01-01

    Full Text Available Total anomalous systemic venous connection (TASVC to the left atrium (LA is a rare congenital anomaly. An 11-year-old girl presented with complaints of palpitations and cyanosis. TASVC with left isomerism and noncompaction of LV was diagnosed after contrast echocardiogram and computed tomography angiogram. The knowledge of anatomy and pathophysiology is essential for the successful management of these cases. Anesthetic concerns in this case were polycythemia, paradoxical embolism and rhythm abnormalities. The patient was successfully operated by rerouting the systemic venous connection to the right atrium.

  1. Supracardiac type total anomalous pulmonary venous connection (TAPVC) with oesophageal varices

    Energy Technology Data Exchange (ETDEWEB)

    Park, Ji Ae; Lee, Hyoung Doo; Ban, Ji Eun; Jo, Min Jung [Pusan National University School of Medicine, Department of Paediatrics, Medical Research Institute, Pusan National University Hospital, Busan (Korea); Sung, Si Chan; Chang, Yun Hee [Pusan National University School of Medicine, Department of Thoracic and Cardiovascular Surgery, Medical Research Institute, Pusan National University Hospital, Busan (Korea); Choo, Ki Seok [Pusan National University School of Medicine, Department of Radiology, Medical Research Institute, Pusan National University Hospital, Busan (Korea)

    2008-10-15

    Oesophageal varices due to total anomalous pulmonary venous connection (TAPVC) is very rare. Additionally, the infradiaphragmatic type is the most common type of oesophageal varices due to TAPVC. Paraoesophageal varices due to stenosis of the vertical vein of supracardiac TAPVC has not previously been reported. We describe paraoesophageal varices developed as a result of a connection between the left lower pulmonary vein and the umbilicovitelline venous system because of stenosis of the proximal vertical vein in supracardiac type TAPVC in a 3-day-old female newborn who presented with general cyanosis, tachypnoea and dyspnoea. (orig.)

  2. Leadership Networking Connect, Collaborate, Create

    CERN Document Server

    (CCL), Center for Creative Leadership; Baldwin, David

    2011-01-01

    Networking is essential to effective leadership in today's organizations. Leaders who are skilled networkers have access to people, information, and resources to help solve problems and create opportunities. Leaders who neglect their networks are missing out on a critical component of their role as leaders. This book will help leaders take a new view of networking and provide insight into how to enhance their networks and become effective at leadership networking.

  3. Visualizing neuronal network connectivity with connectivity pattern tables

    Directory of Open Access Journals (Sweden)

    Eilen Nordlie

    2010-01-01

    Full Text Available Complex ideas are best conveyed through well-designed illustrations. Up to now, computational neuroscientists have mostly relied on box-and-arrow diagrams of even complex neuronal networks, often using ad hoc notations with conflicting use of symbols from paper to paper. This significantly impedes the communication of ideas in neuronal network modeling. We present here Connectivity Pattern Tables (CPTs as a clutter-free visualization of connectivity in large neuronal networks containing two-dimensional populations of neurons. CPTs can be generated automatically from the same script code used to create the actual network in the NEST simulator. Through aggregation, CPTs can be viewed at different levels, providing either full detail or summary information. We also provide the open source ConnPlotter tool as a means to create connectivity pattern tables.

  4. Connectivity of Random 1-Dimensional Networks

    OpenAIRE

    Kurlin, V.; Mihaylova, L.

    2007-01-01

    An important problem in wireless sensor networks is to find the minimal number of randomly deployed sensors making a network connected with a given probability. In practice sensors are often deployed one by one along a trajectory of a vehicle, so it is natural to assume that arbitrary probability density functions of distances between successive sensors in a segment are given. The paper computes the probability of connectivity and coverage of 1-dimensional networks and gives estimates for a m...

  5. Path scanning for the detection of anomalous subgraphs and use of DNS requests and host agents for anomaly/change detection and network situational awareness

    Energy Technology Data Exchange (ETDEWEB)

    Neil, Joshua Charles; Fisk, Michael Edward; Brugh, Alexander William; Hash, Jr., Curtis Lee; Storlie, Curtis Byron; Uphoff, Benjamin; Kent, Alexander

    2017-01-31

    A system, apparatus, computer-readable medium, and computer-implemented method are provided for detecting anomalous behavior in a network. Historical parameters of the network are determined in order to determine normal activity levels. A plurality of paths in the network are enumerated as part of a graph representing the network, where each computing system in the network may be a node in the graph and the sequence of connections between two computing systems may be a directed edge in the graph. A statistical model is applied to the plurality of paths in the graph on a sliding window basis to detect anomalous behavior. Data collected by a Unified Host Collection Agent ("UHCA") may also be used to detect anomalous behavior.

  6. Surgical Repair of Total Anomalous Pulmonary Venous Connection in a Neonate With Mosaic Trisomy 8.

    Science.gov (United States)

    Hasegawa, Tomomi; Oshima, Yoshihiro; Sato, Yumi; Tanaka, Akiko

    2016-03-01

    Trisomy 8 mosaicism is a relatively rare chromosomal abnormality and has extremely variable phenotype with a wide range of clinical manifestations. Although no well-defined criteria for cardiac surgical indications are available for patients with mosaic trisomy 8, we present a case of hypoplastic left heart syndrome with total anomalous pulmonary venous connection (TAPVC) in a neonate with mosaic trisomy 8. Although primary sutureless repair of TAPVC with concomitant bilateral pulmonary artery banding was performed successfully in this case, the indications for cardiac surgery in patients with mosaic trisomy 8 should be carefully individualized. The entire dialog with parents and family, including the process of informed consent, is of great importance.

  7. Application of Partially Connected Neural Network

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper focuses mainly on application of Partially Connected Backpropagation Neural Network (PCBP) instead of typical Fully Connected Neural Network (FCBP). The initial neural network is fully connected, after training with sample data using cross-entropy as error function, a clustering method is employed to cluster weights between inputs to hidden layer and from hidden to output layer, and connections that are relatively unnecessary are deleted, thus the initial network becomes a PCBP network.Then PCBP can be used in prediction or data mining by training PCBP with data that comes from database. At the end of this paper, several experiments are conducted to illustrate the effects of PCBP using Iris data set.

  8. Pulmonary artery catheter insertion in a patient of dextrocardia with anomalous venous connections

    Directory of Open Access Journals (Sweden)

    Tripathi Mukesh

    2004-08-01

    Full Text Available In a young adult patient having situs solitus with dextrocardia the attempted pulmonary artery catheter placement for emergency mitral valve replacement required an unduly long length (50cm of catheter insertion to get into right ventricle and then into pulmonary artery. Although catheter coiling was suspected initially, chest x-ray taken after successfully placement revealed an uncommon congenital anomalous venous connection i.e. right internal jugular opening into left sided superior vena cava then into inferior vena cava after running all along the left border of the heart. With the result, it required to pass 50cm of PA catheter to get into right ventricle in our patient. This emphasizes the need to look for abnormal venous connections during echocardiography and x-ray screening in congenital heart disease. Fluoroscopy is recommended when an unusual length of pulmonary artery catheter insertion is required to enter the pulmonary artery.

  9. Intermittently connected mobile ad hoc networks

    CERN Document Server

    Jamalipour, Abbas

    2011-01-01

    In the last few years, there has been extensive research activity in the emerging area of Intermittently Connected Mobile Ad Hoc Networks (ICMANs). By considering the nature of intermittent connectivity in most real word mobile environments without any restrictions placed on users' behavior, ICMANs are eventually formed without any assumption with regard to the existence of a end-to-end path between two nodes wishing to communicate. It is different from the conventional Mobile Ad Hoc Networks (MANETs), which have been implicitly viewed as a connected graph with established complete paths betwe

  10. Modifying network connectivity with a subgraph addition

    CERN Document Server

    Taylor, Dane

    2011-01-01

    The principal eigenvalue $\\lambda$ of a network's adjacency matrix often determines dynamics on the network (e.g., in synchronization and spreading processes) and some of its structural properties (e.g., robustness against failure or attack), and is therefore a good indicator for how "strongly" a network is connected. We study how $\\lambda$ is modified by the addition of a subgraph. This type of modification has broad applications, ranging from those involving a single modification (e.g., introduction of a drug into a biological process) to those involving repeated subnetwork additions (e.g., power-grid and transit development). We describe how to optimally connect the subgraph to the network to either maximize or minimize the shift in $\\lambda$, noting several applications.

  11. Total anomalous connection of pulmonary veins to the portal vein. Value of multislice angiotomography. Report on three cases

    Directory of Open Access Journals (Sweden)

    Sara Alejandra Solórzano-Morales

    2014-07-01

    15 and 26% if all its varieties. Multislice angiotomography allows us to view the blood vessels and adjacent organs under consideration and obtain high-definition anatomic information. In the patients in this study, total anomalous connection of pulmonary veins to the portal vein was viewed with three-dimensional volumetric tomographic reconstructions and their correlation with ultrasonography studies.

  12. Asymmetric network connectivity using weighted harmonic averages

    Science.gov (United States)

    Morrison, Greg; Mahadevan, L.

    2011-02-01

    We propose a non-metric measure of the "closeness" felt between two nodes in an undirected, weighted graph using a simple weighted harmonic average of connectivity, that is a real-valued Generalized Erdös Number (GEN). While our measure is developed with a collaborative network in mind, the approach can be of use in a variety of artificial and real-world networks. We are able to distinguish between network topologies that standard distance metrics view as identical, and use our measure to study some simple analytically tractable networks. We show how this might be used to look at asymmetry in authorship networks such as those that inspired the integer Erdös numbers in mathematical coauthorships. We also show the utility of our approach to devise a ratings scheme that we apply to the data from the NetFlix prize, and find a significant improvement using our method over a baseline.

  13. Connectivity, dynamics, and structure in a tetrahedral network liquid.

    Science.gov (United States)

    Roldán-Vargas, Sándalo; Rovigatti, Lorenzo; Sciortino, Francesco

    2017-01-04

    We report a detailed computational study by Brownian dynamics simulations of the structure and dynamics of a liquid of patchy particles which forms an amorphous tetrahedral network upon decreasing the temperature. The highly directional particle interactions allow us to investigate the system connectivity by discriminating the total set of particles into different populations according to a penta-modal distribution of bonds per particle. With this methodology we show how the particle bonding process is not randomly independent but it manifests clear bond correlations at low temperatures. We further explore the dynamics of the system in real space and establish a clear relation between particle mobility and particle connectivity. In particular, we provide evidence of anomalous diffusion at low temperatures and reveal how the dynamics is affected by the short-time hopping motion of the weakly bounded particles. Finally we widely investigate the dynamics and structure of the system in Fourier space and identify two quantitatively similar length scales, one dynamic and the other static, which increase upon cooling the system and reach distances of the order of few particle diameters. We summarize our findings in a qualitative picture where the low temperature regime of the viscoelastic liquid is understood in terms of an evolving network of long time metastable cooperative domains of particles.

  14. Multidetector CT evaluation of total anomalous pulmonary venous connections: comparison with echocardiography

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Ki Ho; Choo, Ki Seok [Pusan National University Hospital, Department of Radiology, Medical Institute, Pusan (Korea); Lim, Soo Jin [Kim Hae Joong Ang Hospital, Department of Cardiology, Kimhae (Korea); Lee, Hyoung Doo; Park, Ji Ae; Jo, Min Jung [Pusan National University Hospital, Department of Paediatrics, Pusan (Korea); Sung, Si Chan; Chang, Yun Hee [Pusan National University Hospital, Department of Thoracic and Cardiovascular Surgery, Pusan (Korea); Jeong, Dong Wook [Pusan National University Hospital, Department of Family Medicine, Pusan (Korea); Kim, Siho [Dong-A University Hospital, Department of Thoracic and Cardiovascular Surgery, Pusan (Korea)

    2009-09-15

    Although echocardiography is the first-line imaging modality in the diagnosis of total anomalous pulmonary venous connection (TAPVC), multidetector CT (MDCT) could have advantages in the diagnosis of TAPVC in certain cases. To compare MDCT with echocardiography in the evaluation of TAPVC. Enrolled in the study were 23 patients with surgically proven TAPVC. The echocardiography and MDCT findings were independently interpreted by a paediatric cardiologist and cardiac radiologist in terms of: (1) the drainage site of the common pulmonary vein, (2) stenosis of the vertical vein, and (3) the course of the atypical vessel into the systemic vein in the case of vertical vein stenosis. The findings from both modalities were correlated with the results obtained at surgery (n=22) or autopsy (n=1). In all patients, MDCT correctly depicted the drainage site of the common pulmonary vein, stenosis of the vertical vein and the course of the atypical vessel into the systemic vein (sensitivity 100%, specificity 100%). The specificity of echocardiography was 100% for the three defined findings. The sensitivity of echocardiography, however, was 87%, 71% and 0%, respectively. MDCT can facilitate the diagnosis of TAPVC in certain cases. (orig.)

  15. Partial Anomalous Pulmonary Venous Connection Coexisting with Lung Cancer: A Case Report and Review of Relevant Cases from the Literature.

    Science.gov (United States)

    Kawasaki, Hidenori; Oshiro, Yasuji; Taira, Naohiro; Furugen, Tomonori; Ichi, Takaharu; Yohena, Tomofumi; Kawabata, Tsutomu

    2017-02-20

    A 45-year-old man had an abnormal shadow in the right lung field on an annual screening chest X-ray. He was diagnosed with Stage IA (cT1bN0M0) lung cancer. Initially, we did not notice an anomalous vein on non-contrast computed tomography. However, we found that the right upper lobe bronchus branched from the lateral wall of the right main bronchial orifice, above the level of the common right upper lobe bronchus. Therefore, the bronchus was thought to be a tracheal bronchus. We carefully reevaluated the patient using three-dimensional computed tomography angiography. This technique showed that the anomalous right superior pulmonary vein drained into the azygos vein along the superior vena cava. These findings confirmed a partial anomalous pulmonary venous connection of the right upper lobe. We performed video-assisted thoracoscopic right upper lobectomy and mediastinal lymph node dissection for definitive treatment for lung cancer and partial anomalous pulmonary venous connection. No hemodynamic problems occurred in the postoperative course.

  16. Maximizing Algebraic Connectivity in Interconnected Networks

    CERN Document Server

    Shakeri, Heman; Sahneh, Faryad Darabi; Poggi-Corradini, Pietro; Scoglio, Caterina

    2015-01-01

    Algebraic connectivity, the second eigenvalue of the Laplacian matrix, is a measure of node and link connectivity on networks. When studying interconnected networks it is useful to consider a multiplex model, where the component networks operate together with inter-layer links among them. In order to have a well-connected multilayer structure, it is necessary to optimally design these inter-layer links considering realistic constraints. In this work, we solve the problem of finding an optimal weight distribution for one-to-one inter-layer links under budget constraint. We show that for the special multiplex configurations with identical layers, the uniform weight distribution is always optimal. On the other hand, when the two layers are arbitrary, increasing the budget reveals the existence of two different regimes. Up to a certain threshold budget, the second eigenvalue of the supra-Laplacian is simple, the optimal weight distribution is uniform, and the Fiedler vector is constant on each layer. Increasing t...

  17. Intelligent optical networking with photonic cross connections

    Science.gov (United States)

    Ceuppens, L.; Jerphagnon, Olivier L.; Lang, Jonathan; Banerjee, Ayan; Blumenthal, Daniel J.

    2002-09-01

    Optical amplification and dense wavelength division multiplexing (DWDM) have fundamentally changed optical transport networks. Now that these technologies are widely adopted, the bottleneck has moved from the outside line plant to nodal central offices, where electrical switching equipment has not kept pace. While OEO technology was (and still is) necessary for grooming and traffic aggregation, the transport network has dramatically changed, requiring a dramatic rethinking of how networks need to be designed and operated. While todays transport networks carry remarkable amounts of bandwidth, their optical layer is fundamentally static and provides for only simple point-to-point transport. Efficiently managing the growing number of wavelengths can only be achieved through a new breed of networking element. Photonic switching systems (PSS) can efficiently execute these functions because they are bit rate, wavelength, and protocol transparent. With their all-optical switch cores and interfaces, PSS can switch optical signals at various levels of granularity wavelength, sub band, and composite DWDM fiber levels. Though cross-connect systems with electrical switch cores are available, they perform these functions at very high capital costs and operational inefficiencies. This paper examines enabling technologies for deployment of intelligent optical transport networks (OTN), and takes a practical perspective on survivability architecture migration and implementation issues.

  18. Long-Range Connections in Transportation Networks

    CERN Document Server

    Viana, Matheus P

    2010-01-01

    Since its recent introduction, the small-world effect has been identified in several important real-world systems. Frequently, it is a consequence of the existence of a few long-range connections, which dominate the original regular structure of the systems and implies each node to become accessible from other nodes after a small number of steps, typically of order $\\ell \\propto \\log N$. However, this effect has been observed in pure-topological networks, where the nodes have no spatial coordinates. In this paper, we present an alalogue of small-world effect observed in real-world transportation networks, where the nodes are embeded in a hree-dimensional space. Using the multidimensional scaling method, we demonstrate how the addition of a few long-range connections can suubstantially reduce the travel time in transportation systems. Also, we investigated the importance of long-range connections when the systems are under an attack process. Our findings are illustrated for two real-world systems, namely the L...

  19. Routing of multimedia connections in hybrid networks

    Science.gov (United States)

    Koegel, John F.; Syta, Andrzej

    1993-02-01

    The prevailing vision for next generation multimedia communication systems is a digital one. However, we anticipate a transitional period in which hybrid networks involving both analog and digital technology will coexist. These analog facilities will include crossbar audio-video switches, CATV distribution systems, and dedicated lines. For some scale of use, these facilities may offer economies for connectivity to conventional analog video equipment. We are interested in connection routing that will be needed in such hybrid networks for services including video conferencing and broadcast results. The routing problem in such topologies resembles but is not identical to that found in telephone systems because of the presence of broadcast connections. We discuss representative topologies, review related work, and describe algorithms and simulation results. In addition we describe a hybrid system that we have implemented in our research lab which involves several A/V switches, CATV channels, digital video on a LAN, and a point-to-point link to an offsite conference area.

  20. Anomalous Contagion and Renormalization in Dynamical Networks with Nodal Mobility

    CERN Document Server

    Manrique, Pedro D; Zheng, Minzhang; Xu, Chen; Hui, Pak Ming; Johnson, Neil F

    2015-01-01

    The common real-world feature of individuals migrating through a network -- either in real space or online -- significantly complicates understanding of network processes. Here we show that even though a network may appear static on average, underlying nodal mobility can dramatically distort outbreak profiles. Highly nonlinear dynamical regimes emerge in which increasing mobility either amplifies or suppresses outbreak severity. Predicted profiles mimic recent outbreaks of real-space contagion (social unrest) and online contagion (pro-ISIS support). We show that this nodal mobility can be renormalized in a precise way for a particular class of dynamical networks.

  1. Synaptic connectivity in engineered neuronal networks.

    Science.gov (United States)

    Molnar, Peter; Kang, Jung-Fong; Bhargava, Neelima; Das, Mainak; Hickman, James J

    2014-01-01

    We have developed a method to organize cells in dissociated cultures using engineered chemical clues on a culture surface and determined their connectivity patterns. Although almost all elements of the synaptic transmission machinery can be studied separately in single cell models in dissociated cultures, the complex physiological interactions between these elements are usually lost. Thus, factors affecting synaptic transmission are generally studied in organotypic cultures, brain slices, or in vivo where the cellular architecture generally remains intact. However, by utilizing engineered neuronal networks complex phenomenon such as synaptic transmission or synaptic plasticity can be studied in a simple, functional, cell culture-based system. We have utilized self-assembled monolayers and photolithography to create the surface templates. Embryonic hippocampal cells, plated on the resultant patterns in serum-free medium, followed the surface clues and formed the engineered neuronal networks. Basic whole-cell patch-clamp electrophysiology was applied to characterize the synaptic connectivity in these engineered two-cell networks. The same technology has been used to pattern other cell types such as cardiomyocytes or skeletal muscle fibers.

  2. Anomalous motor mediated cargo transport in microtubule networks

    Science.gov (United States)

    Vandal, Steven; Macveigh-Fierro, Daniel; Shen, Zhiyuan; Lemoi, Kyle; Vidali, Luis; Ross, Jennifer; Tuzel, Erkan

    Cargo transport is an important biological mechanism by which cells locomote, self-organize, and actively transport organelles. This transport is mediated by the cytoskeletal network and molecular motors; however, it is not known how network self-organization and dynamics affect these transport processes. In order to develop a mechanistic understanding of cargo transport, we use a coarse-grained Brownian dynamics model that incorporates the dynamics of these networks, as well as experimentally determined motor properties. We will test these models with two experimental systems: (1) in vitro microtubule networks with kinesin-1 motors, and quantum dot cargos on recreated microtubule networks, and (2) an excellent model organism, the moss Physcomitrella patens, in which chloroplasts are transported via the microtubule network by means of kinesin-like proteins. Phenomenological network characterizations are made, both in vivo and in vitro, and cargo motility is characterized using Mean Squared Displacement (MSD) measurements. Our simulations shed light on the role of network density and motor properties on the observed transport behavior, and improve our understanding of cargo transport in cells.

  3. Social network models predict movement and connectivity in ecological landscapes

    Science.gov (United States)

    Fletcher, Robert J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.

    2011-01-01

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  4. Repaired tetralogy of Fallot with coexisting unrepaired partial anomalous pulmonary venous connection is associated with diminished right ventricular ejection fraction and more severe right ventricular dilation

    Energy Technology Data Exchange (ETDEWEB)

    Chan, Sherwin S. [Children' s Mercy Hospital and Clinics, Department of Radiology, Kansas City, MO (United States); Whitehead, Kevin K.; Kim, Timothy S.; Fu, Gregory L.; Fogel, Mark A.; Harris, Matthew A. [Children' s Hospital of Philadelphia, Department of Cardiology, Philadelphia, PA (United States); Keller, Marc S. [Children' s Hospital of Philadelphia, Department of Radiology, Philadelphia, PA (United States)

    2015-09-15

    There is an established association between tetralogy of Fallot and partial anomalous pulmonary venous connections. This association is important because surgically repaired tetralogy patients have increased risk of right heart failure. We hypothesize that partial anomalous venous connections increase right ventricular volumes and worsen right ventricular failure. We reviewed cardiac MRI exams performed at a tertiary pediatric hospital from January 2005 to January 2014. We identified patients with repaired tetralogy and unrepaired partial anomalous pulmonary venous connection. We used age- and gender-matched repaired tetralogy patients without partial anomalous pulmonary venous connection as controls. We analyzed the MRI results and surgical course and performed comparative statistics to identify group differences. There were eight patients with repaired tetralogy and unrepaired partial anomalous pulmonary venous connection and 16 controls. In all cases, the partial anomalous pulmonary venous connection was not detected on preoperative echocardiography. There were no significant differences in surgical course and body surface area between the two groups. Repaired tetralogy patients with unrepaired partial anomalous pulmonary venous connection showed significantly higher indexed right ventricular end diastolic volume (149 ± 33 mL/m{sup 2} vs. 118 ± 30 mL/m{sup 2}), right ventricle to left ventricle size ratios (3.1 ± 1.3 vs. 1.9 ± 0.5) and a higher incidence of reduced right ventricular ejection fraction compared to controls (3/8 vs. 0/16). Repaired tetralogy of Fallot with unrepaired partial anomalous pulmonary venous connection is associated with reduced right ventricular ejection fraction and more significant right ventricular dilation. (orig.)

  5. An anomalous behavior of trypsin immobilized in alginate network.

    Science.gov (United States)

    Ganachaud, Chrystelle; Bernin, Diana; Isaksson, Dan; Holmberg, Krister

    2013-05-01

    Alginate is a biopolymer used in drug formulations and for surgical purposes. In the presence of divalent cations, it forms solid gels, and such gels are of interest for immobilization of cells and enzymes. In this work, we entrapped trypsin in an alginate gel together with a known substrate, N α-benzoyl-L-arginine-4-nitroanilide hydrochloride (L-BAPNA), and in the presence or absence of D-BAPNA, which is known to be a competitive inhibitor. Interactions between alginate and the substrate as well as the enzyme were characterized with transmission electron microscopy, rheology, and nuclear magnetic resonance spectroscopy. The biocatalysis was monitored by spectrophotometry at temperatures ranging from 10 to 42 °C. It was found that at 37 and 42 °C a strong acceleration of the reaction was obtained, whereas at 10 °C and at room temperature, the presence of D-BAPNA leads to a retardation of the reaction rate. The same effect was found when the reaction was performed in a non-cross-linked alginate solution. In alginate-free buffer solution, as well as in a solution of carboxymethylcellulose, a biopolymer that resembles alginate, the normal behavior was obtained; however, with D-BAPNA acting as an inhibitor at all temperatures. A more detailed investigation of the reaction kinetics showed that at higher temperature and in the presence of alginate, the curve of initial reaction rate versus L-BAPNA concentration had a sigmoidal shape, indicating an allosteric behavior. We believe that the anomalous behavior of trypsin in the presence of alginate is due to conformational changes caused by interactions between the positively charged trypsin and the strongly negatively charged alginate.

  6. Anomalous Returns in a Neural Network Equity-Ranking Predictor

    CERN Document Server

    Satinover, J B

    2008-01-01

    Using an artificial neural network (ANN), a fixed universe of approximately 1500 equities from the Value Line index are rank-ordered by their predicted price changes over the next quarter. Inputs to the network consist only of the ten prior quarterly percentage changes in price and in earnings for each equity (by quarter, not accumulated), converted to a relative rank scaled around zero. Thirty simulated portfolios are constructed respectively of the 10, 20,..., and 100 top ranking equities (long portfolios), the 10, 20,..., 100 bottom ranking equities (short portfolios) and their hedged sets (long-short portfolios). In a 29-quarter simulation from the end of the third quarter of 1994 through the fourth quarter of 2001 that duplicates real-world trading of the same method employed during 2002, all portfolios are held fixed for one quarter. Results are compared to the S&P 500, the Value Line universe itself, trading the universe of equities using the proprietary ``Value Line Ranking System'' (to which this...

  7. Towards Designing PLC Networks for Ubiquitous Connectivity in Enterprises

    OpenAIRE

    Ali, Kamran; Pefkianakis, Ioannis; Liu, Alex X.; Kim, Kyu-Han

    2016-01-01

    Powerline communication (PLC) provides inexpensive, secure and high speed network connectivity, by leveraging the existing power distribution networks inside the buildings. While PLC technology has the potential to improve connectivity and is considered a key enabler for sensing, control, and automation applications in enterprises, it has been mainly deployed for improving connectivity in homes. Deploying PLCs in enterprises is more challenging since the power distribution network is more com...

  8. Connectivity analysis of one-dimensional ad-hoc networks

    DEFF Research Database (Denmark)

    Hansen, Martin Bøgsted; Rasmussen, Jakob Gulddahl; Schwefel, Hans-Peter

    Applications and communication protocols in dynamic ad-hoc networks are exposed to physical limitations imposed by the connectivity relations that result from mobility. Motivated by vehicular freeway scenarios, this paper analyzes a number of important connectivity metrics for instantaneous...... hop-count; (3) the connectivity distance, expressing the geographic distance that a message can be propagated in the network on multi-hop paths; (4) the connectivity hops, which corresponds to the number of hops that are necessary to reach all nodes in the connected network. The paper develops...

  9. Chaotic Griffiths Phase with Anomalous Lyapunov Spectra in Coupled Map Networks

    Science.gov (United States)

    Shinoda, Kenji; Kaneko, Kunihiko

    2016-12-01

    Dynamics of coupled chaotic oscillators on a network are studied using coupled maps. Within a broad range of parameter values representing the coupling strength or the degree of elements, the system repeats formation and split of coherent clusters. The distribution of the cluster size follows a power law with the exponent α , which changes with the parameter values. The number of positive Lyapunov exponents and their spectra are scaled anomalously with the power of the system size with the exponent β , which also changes with the parameters. The scaling relation α ˜2 (β +1 ) is uncovered, which is universal independent of parameters and among random networks.

  10. Connectivity in Sub-Poisson Networks

    CERN Document Server

    Blaszczyszyn, Bartlomiej

    2010-01-01

    We consider a class of point processes (pp), which we call {\\em sub-Poisson}; these are pp that can be directionally-convexly ($dcx$) dominated by some Poisson pp. The $dcx$ order has already been shown useful in comparing various point process characteristics, including Ripley's and correlation functions as well as shot-noise fields generated by pp, indicating in particular that smaller in the $dcx$ order processes exhibit more regularity (less clustering, less voids) in the repartition of their points. Using these results, in this paper we study the impact of the $dcx$ ordering of pp on the properties of two continuum percolation models, which have been proposed in the literature to address macroscopic connectivity properties of large wireless networks. As the first main result of this paper, we extend the classical result on the existence of phase transition in the percolation of the Gilbert's graph (called also the Boolean model), generated by a homogeneous Poisson pp, to the class of homogeneous sub-Pois...

  11. Changes in brain functional network connectivity after stroke

    Institute of Scientific and Technical Information of China (English)

    Wei Li; Yapeng Li; Wenzhen Zhu; Xi Chen

    2014-01-01

    Studies have shown that functional network connection models can be used to study brain net-work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their ifrst ever stroke. Using independent component analysis, six spatially independent components highly correlat-ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our ifndings suggest that functional network connectivity in stroke patients is more complex than that in hea-lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.

  12. Connected Dominating Set Based Topology Control in Wireless Sensor Networks

    Science.gov (United States)

    He, Jing

    2012-01-01

    Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…

  13. Effects of local and global network connectivity on synergistic epidemics

    CERN Document Server

    Broder-Rodgers, David; Taraskin, Sergei N

    2015-01-01

    The effects of local and global connectivity on the spread of synergistic susceptible-infected-removed epidemics were studied in lattice models with infinite- and finite-range rewiring (small-world and small-world-like models). Several effects were found numerically and supported analytically within a simple model: (i) rewiring enhanced resilience to epidemics with strong constructive synergy on networks with high local connectivity; (ii) rewiring enhanced spread of epidemics with destructive or weak constructive synergy on networks with arbitrary local connectivity; (iii) rewiring enhanced spread of epidemics, independent of synergy, in networks with low local connectivity.

  14. Multiple relaxation modes in associative polymer networks with varying connectivity

    Science.gov (United States)

    Bohdan, M.; Sprakel, J.; van der Gucht, J.

    2016-09-01

    The dynamics and mechanics of networks depend sensitively on their spatial connectivity. To explore the effect of connectivity on local network dynamics, we prepare transient polymer networks in which we systematically cut connecting bonds. We do this by creating networks formed from hydrophobically modified difunctionalized polyethylene glycol chains. These form physical gels, consisting of flowerlike micelles that are transiently cross-linked by connecting bridges. By introducing monofunctionalized chains, we can systematically reduce the number of bonds between micelles and thus lower the network connectivity, which strongly reduces the network elasticity and relaxation time. Dynamic light scattering reveals a complex relaxation dynamics that are not apparent in bulk rheology. We observe three distinct relaxation modes. First we find a fast diffusive mode that does not depend on the number of bridges and is attributed to the diffusion of micelles within a cage formed by neighboring micelles. A second, intermediate mode depends strongly on network connectivity but surprisingly is independent of the scattering vector q . We attribute this viscoelastic mode to fluctuations in local connectivity of the network. The third, slowest mode is also diffusive and is attributed to the diffusion of micelle clusters through the viscoelastic matrix. These results shed light on the microscopic dynamics in weakly interconnected transient networks.

  15. Modeling Terrain Impact on Mobile Ad Hoc Networks (MANET) Connectivity

    Science.gov (United States)

    2014-05-01

    Modeling Terrain Impact on Mobile Ad Hoc Networks ( MANET ) Connectivity Lance Joneckis Corinne Kramer David Sparrow David Tate I N S T I T U T E F...SUBTITLE Modeling Terrain Impact on Mobile Ad Hoc Networks ( MANET ) Connectivity 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...1882 ljonecki@ida.org Abstract—Terrain affects connectivity in mobile ad hoc net- works ( MANET ). Both average pairwise link closure and the rate

  16. Connectivity of Large Scale Networks: Distribution of Isolated Nodes

    CERN Document Server

    Mao, Guoqiang

    2011-01-01

    Connectivity is one of the most fundamental properties of wireless multi-hop networks. A network is said to be connected if there is a path between any pair of nodes. A convenient way to study the connectivity of a random network is by investigating the condition under which the network has no isolated node. The condition under which the network has no isolated node provides a necessary condition for a connected network. Further the condition for a network to have no isolated node and the condition for the network to be connected can often be shown to asymptotically converge to be the same as the number of nodes approaches infinity, given a suitably defined random network and connection model. Currently analytical results on the distribution of the number of isolated nodes only exist for the unit disk model. This study advances research in the area by providing the asymptotic distribution of the number of isolated nodes in random networks with nodes Poissonly distributed on a unit square under a generic rando...

  17. Making Connections for Success: A Networking Exercise

    Science.gov (United States)

    Friar, John H.; Eddleston, Kimberly A.

    2007-01-01

    Networking is important, and it is a skill. The authors have developed an exercise that provides students with a realistic networking experience within the safe environment of the classroom. The exercise provides a lead-in to the discussion of networking techniques, active listening, the cultivation of secondary networks, appropriate ways to…

  18. Infiltration experiments demonstrate an explicit connection between heterogeneity and anomalous diffusion behavior

    Science.gov (United States)

    Filipovitch, N.; Hill, K. M.; Longjas, A.; Voller, V. R.

    2016-07-01

    Transport in systems containing heterogeneity distributed over multiple length scales can exhibit anomalous diffusion behaviors, where the time exponent, determining the spreading length scale of the transported scalar, differs from the expected value of n=1/2. Here we present experimental measurements of the infiltration of glycerin, under a fixed pressure head, into a Hele-Shaw cell containing a 3-D printed distribution of flow obstacles; a system that is an analog for infiltration into a porous medium. In support of previously presented direct simulation results, we experimentally demonstrate that, when the obstacles are distributed as a fractal carpet with fractal dimension H < 2, the averaged progress of infiltration exhibits a subdiffusive behavior n<1/2. We further show that observed values of the subdiffusion time exponent appear to be quadratically related to the fractal dimension of the carpet.

  19. Evolution of Plastic Learning in Spiking Networks via Memristive Connections

    OpenAIRE

    Howard, Gerard; Gale, Ella; Bull, Larry; Costello, Ben de Lacy; Adamatzky, Andy

    2012-01-01

    This article presents a spiking neuroevolutionary system which implements memristors as plastic connections, i.e. whose weights can vary during a trial. The evolutionary design process exploits parameter self-adaptation and variable topologies, allowing the number of neurons, connection weights, and inter-neural connectivity pattern to emerge. By comparing two phenomenological real-world memristor implementations with networks comprised of (i) linear resistors (ii) constant-valued connections...

  20. Anomalous Power Law Dispersions in ac Conductivity and Permittivity Shown to be Characteristics of Microstructural Electrical Networks

    Science.gov (United States)

    Almond, D. P.; Bowen, C. R.

    2004-04-01

    The frequency dependent ac conductivity and permittivity of porous lead zirconate titanate ceramic with the pore volume filled with water are shown to match the simulated electrical response of a large network of randomly positioned resistors and capacitors. Anomalous power law dispersions in conductivity and permittivity are shown to be an electrical response characteristic of the microstructural network formed by the porous lead zirconate titanate pore structure. The anomalous power law dispersions of a wide range of materials are also suggested to be microstructural network characteristics.

  1. Multi-goal Control of Chaotic Connected Complex Networks

    Institute of Scientific and Technical Information of China (English)

    FANG Jin-Qing; LIU Qiang; LU Xin-Biao; WANG Xiao-Fan; LI Yong

    2008-01-01

    Beam transport network (BTN) with small world (SW) (so-called BTN-SW) and Lorenz chaotic connected network with scale-free (SF) are taken as two typical examples, we proposed a global linear coupling and combined with local error feedback methods in sub-networks to realize multi-goal control method of halo and chaos in two networks above. The simulation results show that the methods above is effective for any chaotic connected networks and has a potential of applications in based-halo-chaos secure communication.

  2. Connect the Dot: Computing Feed-links for Network Extension

    NARCIS (Netherlands)

    Aronov, Boris; Buchin, Kevin; Buchin, Maike; Jansen, Bart; Jong, Tom de; Kreveld, Marc van; Löffler, Maarten; Luo, Jun; Silveira, Rodrigo I.; Speckmann, Bettina

    2011-01-01

    Road network analysis can require distance from points that are not on the network themselves. We study the algorithmic problem of connecting a point inside a face (region) of the road network to its boundary while minimizing the detour factor of that point to any point on the boundary of the face.

  3. Connected and leading disconnected hadronic light-by-light contribution to the muon anomalous magnetic moment with physical pion mass

    CERN Document Server

    Blum, Thomas; Hayakawa, Masashi; Izubuchi, Taku; Jin, Luchang; Jung, Chulwoo; Lehner, Christoph

    2016-01-01

    We report a lattice QCD calculation of the hadronic light-by-light contribution to the muon anomalous magnetic moment at physical pion mass. The calculation includes the connected diagrams and the leading, quark-line-disconnected diagrams. We incorporate algorithmic improvements developed in our previous work. The calculation was performed on the $48^3 \\times 96$ ensemble generated with a physical-pion-mass and a 5.5 fm spatial extent by the RBC and UKQCD collaborations using the chiral, domain wall fermion (DWF) formulation. We find $a_\\mu^{\\text{HLbL}} = 5.35 (1.35) \\times 10^{- 10}$, where the error is statistical only. The finite-volume and finite lattice-spacing errors could be quite large and are the subject of on-going research. The omitted disconnected graphs, while expected to give a correction of order 10\\%, also need to be computed.

  4. Activating and inhibiting connections in biological network dynamics

    Directory of Open Access Journals (Sweden)

    Knight Rob

    2008-12-01

    Full Text Available Abstract Background Many studies of biochemical networks have analyzed network topology. Such work has suggested that specific types of network wiring may increase network robustness and therefore confer a selective advantage. However, knowledge of network topology does not allow one to predict network dynamical behavior – for example, whether deleting a protein from a signaling network would maintain the network's dynamical behavior, or induce oscillations or chaos. Results Here we report that the balance between activating and inhibiting connections is important in determining whether network dynamics reach steady state or oscillate. We use a simple dynamical model of a network of interacting genes or proteins. Using the model, we study random networks, networks selected for robust dynamics, and examples of biological network topologies. The fraction of activating connections influences whether the network dynamics reach steady state or oscillate. Conclusion The activating fraction may predispose a network to oscillate or reach steady state, and neutral evolution or selection of this parameter may affect the behavior of biological networks. This principle may unify the dynamics of a wide range of cellular networks. Reviewers Reviewed by Sergei Maslov, Eugene Koonin, and Yu (Brandon Xia (nominated by Mark Gerstein. For the full reviews, please go to the Reviewers' comments section.

  5. Estimating the epidemic threshold on networks by deterministic connections

    Energy Technology Data Exchange (ETDEWEB)

    Li, Kezan, E-mail: lkzzr@sohu.com; Zhu, Guanghu [School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004 (China); Fu, Xinchu [Department of Mathematics, Shanghai University, Shanghai 200444 (China); Small, Michael [School of Mathematics and Statistics, The University of Western Australia, Crawley, Western Australia 6009 (Australia)

    2014-12-15

    For many epidemic networks some connections between nodes are treated as deterministic, while the remainder are random and have different connection probabilities. By applying spectral analysis to several constructed models, we find that one can estimate the epidemic thresholds of these networks by investigating information from only the deterministic connections. Nonetheless, in these models, generic nonuniform stochastic connections and heterogeneous community structure are also considered. The estimation of epidemic thresholds is achieved via inequalities with upper and lower bounds, which are found to be in very good agreement with numerical simulations. Since these deterministic connections are easier to detect than those stochastic connections, this work provides a feasible and effective method to estimate the epidemic thresholds in real epidemic networks.

  6. Selectivity and sparseness in randomly connected balanced networks.

    Directory of Open Access Journals (Sweden)

    Cengiz Pehlevan

    Full Text Available Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected. This raises the question whether selectivity and sparseness can be generated and maintained in randomly connected networks. We consider a recurrent network of excitatory and inhibitory spiking neurons with random connectivity, driven by random projections from an input layer of stimulus selective neurons. In this architecture, the stimulus-to-stimulus and neuron-to-neuron modulation of total synaptic input is weak compared to the mean input. Surprisingly, we show that in the balanced state the network can still support high stimulus selectivity and sparse population response. In the balanced state, strong synapses amplify the variation in synaptic input and recurrent inhibition cancels the mean. Functional specificity in connectivity emerges due to the inhomogeneity caused by the generative statistical rule used to build the network. We further elucidate the mechanism behind and evaluate the effects of model parameters on population sparseness and stimulus selectivity. Network response to mixtures of stimuli is investigated. It is shown that a balanced state with unselective inhibition can be achieved with densely connected input to inhibitory population. Balanced networks exhibit the "paradoxical" effect: an increase in excitatory drive to inhibition leads to decreased inhibitory population firing rate. We compare and contrast selectivity and sparseness generated by the balanced network to randomly connected unbalanced networks. Finally, we discuss our results in light of experiments.

  7. Information Model for Connection Management in Automatic Switched Optical Network

    Institute of Scientific and Technical Information of China (English)

    Xu Yunbin(徐云斌); Song Hongsheng; Gui Xuan; Zhang Jie; Gu Wanyi

    2004-01-01

    The three types of connections (Permanent Connection, Soft Permanent Connection and Switched Connection) provided by ASON can adapt the requirement of different network services. Management and maintenance of these three connections are the most important aspect of ASON management. The information models proposed in this paper are used for the purpose of ASON connection management. Firstly a new information model is proposed to meet the requirement for the control plane introduced by ASON. In this model, a new class ControlNE is given, and the relationship between the ControlNE and the transport NE (network element) is also defined. Then this paper proposes information models for the three types of connections for the first time, and analyzes the relationship between the three kinds of connections and the basic network transport entities. Finally, the paper defines some CORBA interfaces for the management of the three connections. In these interfaces, some operations such as create or release a connection are defined, and some other operations can manage the performance of the three kinds of connections, which is necessary for a distributed management system.

  8. Network Size and Connectivity in Mobile and Stationary Ad Hoc Networks

    Science.gov (United States)

    2014-05-01

    mobile ad hoc networks ( MANETs ) is that routes consisting of multiple hops will be available to connect those nodes that lack line-of- sight connectivity...SUPPLEMENTARY NOTES 14. ABSTRACT One of the assumptions behind tactical mobile ad hoc networks ( MANETs ) is that routes consisting of multiple hops will be...Network Size and Connectivity in Mobile and Stationary Ad Hoc Networks Lance Joneckis Corinne Kramer David Sparrow David Tate I N S T I T U T E

  9. Revealing Hidden Connections in Recommendation Networks

    CERN Document Server

    Minhano, Rogerio; Kamienski, Carlos

    2016-01-01

    Companies have been increasingly seeking new mechanisms for making their electronic marketing campaigns to become viral, thus obtaining a cascading recommendation effect similar to word-of-mouth. We analysed a dataset of a magazine publisher that uses email as the main marketing strategy and found out that networks emerging from those campaigns form a very sparse graph. We show that online social networks can be effectively used as a means to expand recommendation networks. Starting from a set of users, called seeders, we crawled Google's Orkut and collected about 20 million users and 80 million relationships. Next, we extended the original recommendation network by adding new edges using Orkut relationships that built a much denser network. Therefore, we advocate that online social networks are much more effective than email-based marketing campaigns

  10. Robust Network Design - Connectivity and Beyond

    Science.gov (United States)

    2015-01-15

    On Shortest Single/Multiple Path Computation Problems in Fiber - Wireless (FiWi) Access Networks, 15th IEEE International Conference on High Performance...Deutsche Telekom in Berlin, Germany. V. PUBLICATION LIST 1. S. Shirazipourazad, A. Sen, S. Bandyopadhyay, Fault-tolerant Design of Wireless Sensor Networks...Shirazipourazad, A. Sen, S. Bandyopadhyay, Fault-tolerant Design of Wireless Sensor Networks with Directional Antennas, International Conference on

  11. Role of connectivity in congestion and decongestion in networks

    CERN Document Server

    Gupte, N; Gupte, Neelima; Singh, Brajendra K.

    2005-01-01

    We study network traffic dynamics in a two dimensional communication network with regular nodes and hubs. If the network experiences heavy message traffic, congestion occurs due to finite capacity of the nodes. We discuss strategies to manipulate hub capacity and hub connections to relieve congestion and define a coefficient of betweenness centrality (CBC), a direct measure of network traffic, which is useful for identifying hubs which are most likely to cause congestion. The addition of assortative connections to hubs of high CBC relieves congestion very efficiently.

  12. Brain network dynamics underlying visuospatial judgment: an FMRI connectivity study.

    Science.gov (United States)

    de Graaf, Tom A; Roebroeck, Alard; Goebel, Rainer; Sack, Alexander T

    2010-09-01

    Previous functional imaging research has consistently indicated involvement of bilateral fronto-parietal networks during the execution of visuospatial tasks. Studies with TMS have suggested that the right hemispheric network, but not the left, is functionally relevant for visuospatial judgments. However, very little is still known about the interactions within these fronto-parietal networks underlying visuospatial processing. In the current study, we investigated task modulation of functional connectivity (instantaneous correlations of regional time courses), and task-specific effective connectivity (direction of influences), within the right fronto-parietal network activated during visuospatial judgments. Ten healthy volunteers performed a behaviorally controlled visuospatial judgment task (ANGLE) or a control task (COLOR) in an fMRI experiment. Visuospatial task-specific activations were found in posterior parietal cortex (PPC) and middle/inferior frontal gyrus (MFG). Functional connectivity within this network was task-modulated, with significantly higher connectivity between PPC and MFG during ANGLE than during COLOR. Effective connectivity analysis for directed influence revealed that visuospatial task-specific projections within this network were predominantly in a frontal-to-parietal direction. Moreover, ANGLE-specific influences from thalamic nuclei to PPC were identified. Exploratory effective connectivity analysis revealed that closely neighboring clusters, within visuospatial regions, were differentially involved in the network. These neighboring clusters had opposite effective connectivity patterns to other nodes of the fronto-parietal network. Our data thus reveal that visuospatial judgments are supported by massive fronto-parietal backprojections, thalamo-parietal influence, and multiple stages, or loops, of information flow within the visuospatial network. We speculate on possible functional contributions of the various network nodes and

  13. Connecting to the Internet Securely; Protecting Home Networks CIAC-2324

    Energy Technology Data Exchange (ETDEWEB)

    Orvis, W J; Krystosek, P; Smith, J

    2002-11-27

    With more and more people working at home and connecting to company networks via the Internet, the risk to company networks to intrusion and theft of sensitive information is growing. Working from home has many positive advantages for both the home worker and the company they work for. However, as companies encourage people to work from home, they need to start considering the interaction of the employee's home network and the company network he connects to. This paper discusses problems and solutions related to protection of home computers from attacks on those computers via the network connection. It does not consider protection of those systems from people who have physical access to the computers nor does it consider company laptops taken on-the-road. Home networks are often targeted by intruders because they are plentiful and they are usually not well secured. While companies have departments of professionals to maintain and secure their networks, home networks are maintained by the employee who may be less knowledgeable about network security matters. The biggest problems with home networks are that: Home networks are not designed to be secure and may use technologies (wireless) that are not secure; The operating systems are not secured when they are installed; The operating systems and applications are not maintained (for security considerations) after they are installed; and The networks are often used for other activities that put them at risk for being compromised. Home networks that are going to be connected to company networks need to be cooperatively secured by the employee and the company so they do not open up the company network to intruders. Securing home networks involves many of the same operations as securing a company network: Patch and maintain systems; Securely configure systems; Eliminate unneeded services; Protect remote logins; Use good passwords; Use current antivirus software; and Moderate your Internet usage habits. Most of these

  14. Connectivity analysis of one-dimensional ad-hoc networks

    DEFF Research Database (Denmark)

    Bøgsted, Martin; Rasmussen, Jakob Gulddahl; Schwefel, Hans-Peter

    2011-01-01

    Application and communication protocols in dynamic ad-hoc networks are exposed to physical limitations imposed by the connectivity relations that result from mobility. Motivated by vehicular freeway scenarios, this paper analyzes a number of important connectivity metrics for instantaneous...... snapshots of stochastic geographic movement patterns: (1) The single-hop connectivity number, corresponding to the number of single-hop neighbors of a mobile node; (2) the multi-hop connectivity number, expressing the number of nodes reachable via multi-hop paths of arbitrary hop-count; (3) the connectivity...

  15. The Connect Effect Building Strong Personal, Professional, and Virtual Networks

    CERN Document Server

    Dulworth, Michael

    2008-01-01

    Entrepreneur and executive development expert Mike Dulworth's THE CONNECT EFFECT provides readers with a simple framework and practical tools for developing that crucial competitive advantage: a high-quality personal, professional/organizational and virtual network.

  16. Modified DM Models for Aging Networks Based on Neighborhood Connectivity

    Institute of Scientific and Technical Information of China (English)

    WEI Du-Qu; LIN Min; LUO Xiao-Shu; WANG Gang; ZOU Yan-Li; CHEN Tian-Lun

    2008-01-01

    Two modified Dorogovtsev-Mendes (DM) models of aging networks based on the dynamics of connecting nearest-neighbors are introduced. One edge of the new site is connected to the old site with probabilityekt-αas in the DM's model, where the degree and age of the old site are k and t, respectively. We consider two eases, I.e. The other edges of the new site attaching to the nearest-neighbors of the old site with uniform and degree connectivity probability, respectively. The network structure changes with an increase of aging exponent α. It is found that the networks can produce scale-free degree distributions with small-world properties. And the different connectivity probabilities lead to the different properties of the networks.

  17. Effects of local and global network connectivity on synergistic epidemics

    Science.gov (United States)

    Broder-Rodgers, David; Pérez-Reche, Francisco J.; Taraskin, Sergei N.

    2015-12-01

    Epidemics in networks can be affected by cooperation in transmission of infection and also connectivity between nodes. An interplay between these two properties and their influence on epidemic spread are addressed in the paper. A particular type of cooperative effects (called synergy effects) is considered, where the transmission rate between a pair of nodes depends on the number of infected neighbors. The connectivity effects are studied by constructing networks of different topology, starting with lattices with only local connectivity and then with networks that have both local and global connectivity obtained by random bond-rewiring to nodes within a certain distance. The susceptible-infected-removed epidemics were found to exhibit several interesting effects: (i) for epidemics with strong constructive synergy spreading in networks with high local connectivity, the bond rewiring has a negative role in epidemic spread, i.e., it reduces invasion probability; (ii) in contrast, for epidemics with destructive or weak constructive synergy spreading on networks of arbitrary local connectivity, rewiring helps epidemics to spread; (iii) and, finally, rewiring always enhances the spread of epidemics, independent of synergy, if the local connectivity is low.

  18. Structural Connectivity Networks of Transgender People

    OpenAIRE

    Hahn, Andreas; Kranz, Georg S.; Küblböck, Martin; Kaufmann, Ulrike; Ganger, Sebastian; Hummer, Allan; Seiger, Rene; Spies, Marie; Winkler, Dietmar; Kasper, Siegfried; Windischberger, Christian; Swaab, Dick F.; Lanzenberger, Rupert

    2015-01-01

    Although previous investigations of transsexual people have focused on regional brain alterations, evaluations on a network level, especially those structural in nature, are largely missing. Therefore, we investigated the structural connectome of 23 female-to-male (FtM) and 21 male-to-female (MtF) transgender patients before hormone therapy as compared with 25 female and 25 male healthy controls. Graph theoretical analysis of whole-brain probabilistic tractography networks (adjusted for diffe...

  19. Structural Connectivity Networks of Transgender People

    OpenAIRE

    Hahn, Andreas; Kranz, Georg S.; Küblböck, Martin; Kaufmann, Ulrike; Ganger, Sebastian; Hummer, Allan; Seiger, Rene; Spies, Marie; Winkler, Dietmar; Kasper, Siegfried; Windischberger, Christian; Swaab, Dick F.; Lanzenberger, Rupert

    2014-01-01

    Although previous investigations of transsexual people have focused on regional brain alterations, evaluations on a network level, especially those structural in nature, are largely missing. Therefore, we investigated the structural connectome of 23 female-to-male (FtM) and 21 male-to-female (MtF) transgender patients before hormone therapy as compared with 25 female and 25 male healthy controls. Graph theoretical analysis of whole-brain probabilistic tractography networks (adjusted for diffe...

  20. Networks with fourfold connectivity in two dimensions

    Science.gov (United States)

    Tessier, Frédéric; Boal, David H.; Discher, Dennis E.

    2003-01-01

    The elastic properties of planar, C4-symmetric networks under stress and at nonzero temperature are determined by simulation and mean field approximations. Attached at fourfold coordinated junction vertices, the networks are self-avoiding in that their elements (or bonds) may not intersect each other. Two different models are considered for the potential energy of the elements: either Hooke’s law springs or flexible tethers (square well potential). For certain ranges of stress and temperature, the properties of the networks are captured by one of several models: at large tensions, the networks behave like a uniform system of square plaquettes, while at large compressions or high temperatures, they display many characteristics of an ideal gas. Under less severe conditions, mean field models with more general shapes (parallelograms) reproduce many essential features of both networks. Lastly, the spring network expands without limit at a two-dimensional tension equal to the force constant of the spring; however, it does not appear to collapse under compression, except at zero temperature.

  1. Telephone Networks Connect Caregiving Families of Alzheimer's Victims.

    Science.gov (United States)

    Goodman, Catherine Chase; Pynoos, Jon

    1988-01-01

    Describes telephone network bringing family caregivers of Alzheimer's victims together over telephone in rotating pattern of twosomes. Explains how five caregiving spouses and five adult children were matched and connected over three months. Describes program's 25 telephone-accessed audiotapes that guided networks and provided information on…

  2. A neutral network based technique for short-term forecasting of anomalous load periods

    Energy Technology Data Exchange (ETDEWEB)

    Sforna, M. [ENEL, s.p.a, Italian Power Company (Italy); Lamedica, R.; Prudenzi, A. [Rome Univ. `La Sapienza`, Rome (Italy); Caciotta, M.; Orsolini Cencelli, V. [Rome Univ. III, Rome (Italy)

    1995-01-01

    The paper illustrates a part of the research activity conducted by authors in the field of electric Short Term Load Forecasting (STLF) based on Artificial Neural Network (ANN) architectures. Previous experiences with basic ANN architectures have shown that, even though these architecture provide results comparable with those obtained by human operators for most normal days, they evidence some accuracy deficiencies when applied to `anomalous` load conditions occurring during holidays and long weekends. For these periods a specific procedure based upon a combined (unsupervised/supervised) approach has been proposed. The unsupervised stage provides a preventive classification of the historical load data by means of a Kohonen`s Self Organizing Map (SOM). The supervised stage, performing the proper forecasting activity, is obtained by using a multi-layer percept ron with a back propagation learning algorithm similar to the ones above mentioned. The unconventional use of information deriving from the classification stage permits the proposed procedure to obtain a relevant enhancement of the forecast accuracy for anomalous load situations.

  3. Aberrant cerebellar connectivity in motor and association networks in schizophrenia

    Directory of Open Access Journals (Sweden)

    Ann K. Shinn

    2015-03-01

    Full Text Available Schizophrenia is a devastating illness characterized by disturbances in multiple domains. The cerebellum is involved in both motor and non-motor functions, and the cognitive dysmetria and dysmetria of thought models propose that abnormalities of the cerebellum may contribute to schizophrenia signs and symptoms. The cerebellum and cerebral cortex are reciprocally connected via a modular, closed-loop network architecture, but few schizophrenia neuroimaging studies have taken into account the topographical and functional heterogeneity of the cerebellum. In this study, using a previously defined 17-network cerebral cortical parcellation system as the basis for our functional connectivity seeds, we systematically investigated connectivity abnormalities within the cerebellum of 44 schizophrenia patients and 28 healthy control participants. We found selective alterations in cerebro-cerebellar functional connectivity. Specifically, schizophrenia patients showed decreased cerebro-cerebellar functional connectivity in higher level association networks (ventral attention, salience, control, and default mode networks relative to healthy control participants. Schizophrenia patients also showed increased cerebro-cerebellar connectivity in somatomotor and default mode networks, with the latter showing no overlap with the regions found to be hypoconnected within the same default mode network. Finally, we found evidence to suggest that somatomotor and default mode networks may be inappropriately linked in schizophrenia. The relationship of these dysconnectivities to schizophrenia symptoms, such as neurological soft signs and altered sense of agency, is discussed. We conclude that the cerebellum ought to be considered for analysis in all future studies of network abnormalities in SZ, and further suggest the cerebellum as a potential target for further elucidation, and possibly treatment, of the underlying mechanisms and network abnormalities producing symptoms of

  4. BCR Routing for Intermittently Connected Mobile Ad hoc Networks

    Directory of Open Access Journals (Sweden)

    S. RAMESH

    2014-03-01

    Full Text Available The Wireless and the Mobile Networks appear to provide a wide range of applications. Following these, the Mobile Ad hoc Networks (MANET aid in wide development of many applications. The achievement of the real world applications are attained through effective routing. The Intermittently Connected Mobile Ad hoc Network (ICMANET is a sparse network where a full connectivity is never possible. ICMANET is a disconnected MANET and is also a Delay Tolerant Network (DTN that sustains for higher delays. The routing in a disseminated network is a difficult task. A new routing scheme called Bee Colony Routing (BCR is been proposed with a motto of achieving optimal result in delivering the data packet towards the destined node. BCR is proposed with the basis of Bee Colony Optimization technique (BCO. The routing in ICMNAET is done by means of Bee routing protocol. This paper enchants a novel routing methodology for data transmission in ICMANET.

  5. Muscle networks: Connectivity analysis of EMG activity during postural control

    Science.gov (United States)

    Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

    2015-12-01

    Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures.

  6. Altered resting-state network connectivity in congenital blind.

    Science.gov (United States)

    Wang, Dawei; Qin, Wen; Liu, Yong; Zhang, Yunting; Jiang, Tianzi; Yu, Chunshui

    2014-06-01

    The brain of congenital blind (CB) has experienced a series of structural and functional alterations, either undesirable outcomes such as atrophy of the visual pathway due to sight loss from birth, or compensatory plasticity to interact efficiently with the environment. However, little is known, so far, about alterations in the functional architecture of resting-state networks (RSNs) in CB. This study aimed to investigate intra- and internetwork connectivity differences between CB and sighted controls (SC), using independent component analysis (ICA) on resting state functional MRI data. Compared with SC, CB showed significantly increased network connectivity within the salience network (SN) and the occipital cortex. Moreover, CB exhibited enhanced internetwork connectivity between the SN and the frontoparietal network (FPN) and between the FPN and the occipital cortex; however, they showed decreased internetwork connectivity between the occipital cortex and the sensorimotor network. These findings suggest that CB experience large scale reorganization at the level of the functional network. More importantly, the enhanced intra- and internetwork connectivity of the SN, FPN, and occipital cortex in CB may improve their abilities to identify salient stimuli, to initiate the executive function, and to top-down control of attention, which are critical for the CB to guide appropriate behavior and to better adaption to the environment.

  7. Interference Alignment for Partially Connected MIMO Cellular Networks

    CERN Document Server

    Ruan, Liangzhong

    2012-01-01

    In this paper, we propose an iterative interference alignment (IA) algorithm for MIMO cellular networks with partial connectivity, which is induced by heterogeneous path losses and spatial correlation. Such systems impose several key technical challenges in the IA algorithm design, namely the overlapping between the direct and interfering links due to the MIMO cellular topology as well as how to exploit the partial connectivity. We shall address these challenges and propose a three stage IA algorithm. As illustration, we analyze the achievable degree of freedom (DoF) of the proposed algorithm for a symmetric partially connected MIMO cellular network. We show that there is significant DoF gain compared with conventional IA algorithms due to partial connectivity. The derived DoF bound is also backward compatible with that achieved on fully connected K-pair MIMO interference channels.

  8. On Connectivity of Wireless Sensor Networks with Directional Antennas

    Science.gov (United States)

    Wang, Qiu; Dai, Hong-Ning; Zheng, Zibin; Imran, Muhammad; Vasilakos, Athanasios V.

    2017-01-01

    In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models. PMID:28085081

  9. On Connectivity of Wireless Sensor Networks with Directional Antennas

    Directory of Open Access Journals (Sweden)

    Qiu Wang

    2017-01-01

    Full Text Available In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models.

  10. Connect the dot: Computing feed-links for network extension

    Directory of Open Access Journals (Sweden)

    Boris Aronov

    2011-12-01

    Full Text Available Road network analysis can require distance from points that are not on the network themselves. We study the algorithmic problem of connecting a point inside a face (region of the road network to its boundary while minimizing the detour factor of that point to any point on the boundary of the face. We show that the optimal single connection (feed-link can be computed in O(lambda_7(n log n time, where n is the number of vertices that bounds the face and lambda_7(n is the slightly superlinear maximum length of a Davenport-Schinzel sequence of order 7 on n symbols. We also present approximation results for placing more feed-links, deal with the case that there are obstacles in the face of the road network that contains the point to be connected, and present various related results.

  11. On Connectivity of Wireless Sensor Networks with Directional Antennas.

    Science.gov (United States)

    Wang, Qiu; Dai, Hong-Ning; Zheng, Zibin; Imran, Muhammad; Vasilakos, Athanasios V

    2017-01-12

    In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models.

  12. Structural Connectivity Networks of Transgender People

    NARCIS (Netherlands)

    Hahn, Andreas; Kranz, Georg S; Küblböck, Martin; Kaufmann, Ulrike; Ganger, Sebastian; Hummer, Allan; Seiger, Rene; Spies, Marie; Winkler, Dietmar; Kasper, Siegfried; Windischberger, Christian; Swaab, Dick F; Lanzenberger, Rupert

    2015-01-01

    Although previous investigations of transsexual people have focused on regional brain alterations, evaluations on a network level, especially those structural in nature, are largely missing. Therefore, we investigated the structural connectome of 23 female-to-male (FtM) and 21 male-to-female (MtF) t

  13. Inferring connectivity in networked dynamical systems: Challenges using Granger causality

    Science.gov (United States)

    Lusch, Bethany; Maia, Pedro D.; Kutz, J. Nathan

    2016-09-01

    Determining the interactions and causal relationships between nodes in an unknown networked dynamical system from measurement data alone is a challenging, contemporary task across the physical, biological, and engineering sciences. Statistical methods, such as the increasingly popular Granger causality, are being broadly applied for data-driven discovery of connectivity in fields from economics to neuroscience. A common version of the algorithm is called pairwise-conditional Granger causality, which we systematically test on data generated from a nonlinear model with known causal network structure. Specifically, we simulate networked systems of Kuramoto oscillators and use the Multivariate Granger Causality Toolbox to discover the underlying coupling structure of the system. We compare the inferred results to the original connectivity for a wide range of parameters such as initial conditions, connection strengths, community structures, and natural frequencies. Our results show a significant systematic disparity between the original and inferred network, unless the true structure is extremely sparse or dense. Specifically, the inferred networks have significant discrepancies in the number of edges and the eigenvalues of the connectivity matrix, demonstrating that they typically generate dynamics which are inconsistent with the ground truth. We provide a detailed account of the dynamics for the Erdős-Rényi network model due to its importance in random graph theory and network science. We conclude that Granger causal methods for inferring network structure are highly suspect and should always be checked against a ground truth model. The results also advocate the need to perform such comparisons with any network inference method since the inferred connectivity results appear to have very little to do with the ground truth system.

  14. Population Coding in Sparsely Connected Networks of Noisy Neurons

    Directory of Open Access Journals (Sweden)

    Bryan Patrick Tripp

    2012-05-01

    Full Text Available This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behaviour. However, population coding theory has often ignored network structure, or assumed discrete, fully-connected populations (in contrast with the sparsely connected, continuous sheet of the cortex. In this study, we model a sheet of cortical neurons with sparse, primarily local connections, and find that a network with this structure can encode multiple internal state variables with high signal-to-noise ratio. However, in our model, although connection probability varies with the distance between neurons, we find that the connections cannot be instantiated at random according to these probabilities, but must have additional structure if information is to be encoded with high fidelity.

  15. Functional Connectivity Hubs and Networks in the Awake Marmoset Brain

    Directory of Open Access Journals (Sweden)

    Annabelle Marie Belcher

    2016-03-01

    Full Text Available In combination with advances in analytical methods, resting-state fMRI is allowing unprecedented access to achieve a better understanding of the network organization of the brain. Increasing evidence suggests that this architecture may incorporate highly functionally connected nodes, or hubs, and we have recently proposed local functional connectivity density (lFCD mapping to identify highly-connected nodes in the human brain. Here we imaged awake nonhuman primates to test whether, like the human brain, the marmoset brain contains functional connectivity hubs. Ten adult common marmosets (Callithrix jacchus were acclimated to mild, comfortable restraint using individualized helmets. Following restraint training, resting BOLD data were acquired during eight consecutive 10 min scans for each subject. lFCD revealed prominent cortical and subcortical hubs of connectivity across the marmoset brain; specifically, in primary and secondary visual cortices (V1/V2, higher-order visual association areas (A19M/V6[DM], posterior parietal and posterior cingulate areas (PGM and A23b/A31, thalamus, dorsal and ventral striatal areas (caudate, putamen, lateral septal nucleus, and anterior cingulate cortex (A24a. lFCD hubs were highly connected to widespread areas of the brain, and further revealed significant network-network interactions. These data provide a baseline platform for future investigations in a nonhuman primate model of the brain’s network topology.

  16. Network screening in a connected vehicle environment

    OpenAIRE

    Kluger, Robert

    2013-01-01

    Transportation agencies are responsible for analyzing crash data to identify hot spots - locations that experience abnormally large numbers of crashes, pointing to potential geometric and or control problems. Current network screening practice involves using information from police reports to determine hot spot locations. There are numerous issues with current practice. First, police reports are often inaccurate with regards to exact location and the cause of the incident. Second, from a stat...

  17. Connecting Land-Based Networks to Ships

    Science.gov (United States)

    2013-06-01

    intranet browsing or video conferencing . To accomplish this, most ships use satellite communications, which is an expensive and slow method. When a...communicate and exchange information with a shore network for services such as file transfer, database access, e-mail, web/intranet browsing or video ... conferencing . To accomplish this, most ships use satellite communications, which is an expensive and slow method. When a ship is near shore, it can use

  18. Network robustness assessed within a dual connectivity perspective

    CERN Document Server

    Tejedor, Alejandro; Zaliapin, Ilya; Foufoula-Georgiou, Efi

    2014-01-01

    Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. Typically, in these studies, robustness is assessed only in terms of the connectivity of the nodes unaffected by the attack (the harder it is to destroy the connectivity of the 'healthy' nodes, the more robust the network is considered). However, in many systems, the connectivity of the affected nodes too may play a significant role in evaluating the overall network robustness. Here, we propose a dual perspective approach, wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and the efficiency of building-up the IN. We show that trade-offs between the efficiency of Active and Idle network dynamics give rise to surprising crossovers and ...

  19. Improving interdependent networks robustness by adding connectivity links

    Science.gov (United States)

    Ji, Xingpei; Wang, Bo; Liu, Dichen; Chen, Guo; Tang, Fei; Wei, Daqian; Tu, Lian

    2016-02-01

    Compared with a single and isolated network, interdependent networks have two types of links: connectivity link and dependency link. This paper aims to improve the robustness of interdependent networks by adding connectivity links. Firstly, interdependent networks failure model and four frequently used link addition strategies are briefly reviewed. Furthermore, by defining inter degree-degree difference, two novel link addition strategies are proposed. Finally, we verify the effectiveness of our proposed link addition strategies by comparing with the current link addition strategies in three different network models. The simulation results show that, given the number of added links, link allocation strategies have great effects on the robustness of interdependent networks, i.e., the double-network link allocation strategy is superior to single-network link allocation strategy. Link addition strategies proposed in this paper excel the current strategies, especially for BA interdependent networks. Moreover, our work can provide guidance on how to allocate limited resources to an existing interdependent networks system and optimize its topology to avoid the potential cascade failures.

  20. Balanced Networks of Spiking Neurons with Spatially Dependent Recurrent Connections

    Science.gov (United States)

    Rosenbaum, Robert; Doiron, Brent

    2014-04-01

    Networks of model neurons with balanced recurrent excitation and inhibition capture the irregular and asynchronous spiking activity reported in cortex. While mean-field theories of spatially homogeneous balanced networks are well understood, a mean-field analysis of spatially heterogeneous balanced networks has not been fully developed. We extend the analysis of balanced networks to include a connection probability that depends on the spatial separation between neurons. In the continuum limit, we derive that stable, balanced firing rate solutions require that the spatial spread of external inputs be broader than that of recurrent excitation, which in turn must be broader than or equal to that of recurrent inhibition. Notably, this implies that network models with broad recurrent inhibition are inconsistent with the balanced state. For finite size networks, we investigate the pattern-forming dynamics arising when balanced conditions are not satisfied. Our study highlights the new challenges that balanced networks pose for the spatiotemporal dynamics of complex systems.

  1. Networking in medical education: Creating and connecting

    Directory of Open Access Journals (Sweden)

    Supe Avinash

    2008-03-01

    Full Text Available Social networking is being increasingly used as a tool of choice for communications and collaborations in business and higher education. Learning and practice become inseparable when professionals work in communities of practice that create interpersonal bonds and promote collective learning. Individual learning that arises from the critical reconstruction of practice, in the presence of peers and other health professionals, enhances a physician′s capability of clinical judgment and evidence-based practice. As such, it would be wise for medical schools, whose responsibility it is to prepare students to make a transition to adult life with the skills they need to succeed in both arenas, to reckon with it.

  2. Temporal dynamics of connectivity and epidemic properties of growing networks

    Science.gov (United States)

    Fotouhi, Babak; Shirkoohi, Mehrdad Khani

    2016-01-01

    Traditional mathematical models of epidemic disease had for decades conventionally considered static structure for contacts. Recently, an upsurge of theoretical inquiry has strived towards rendering the models more realistic by incorporating the temporal aspects of networks of contacts, societal and online, that are of interest in the study of epidemics (and other similar diffusion processes). However, temporal dynamics have predominantly focused on link fluctuations and nodal activities, and less attention has been paid to the growth of the underlying network. Many real networks grow: Online networks are evidently in constant growth, and societal networks can grow due to migration flux and reproduction. The effect of network growth on the epidemic properties of networks is hitherto unknown, mainly due to the predominant focus of the network growth literature on the so-called steady state. This paper takes a step towards alleviating this gap. We analytically study the degree dynamics of a given arbitrary network that is subject to growth. We use the theoretical findings to predict the epidemic properties of the network as a function of time. We observe that the introduction of new individuals into the network can enhance or diminish its resilience against endemic outbreaks and investigate how this regime shift depends upon the connectivity of newcomers and on how they establish connections to existing nodes. Throughout, theoretical findings are corroborated with Monte Carlo simulations over synthetic and real networks. The results shed light on the effects of network growth on the future epidemic properties of networks and offers insights for devising a priori immunization strategies.

  3. Network Connection Games with Disconnected Equilibria

    CERN Document Server

    Brandes, Ulrik; Nick, Bobo

    2008-01-01

    In this paper we extend a popular non-cooperative network creation game (NCG) to allow for disconnected equilibrium networks. There are n players, each is a vertex in a graph, and a strategy is a subset of players to build edges to. For each edge a player must pay a cost, and the utility is a trade-off between edge costs and shortest path lengths to all other players. We extend the model to a penalized game (PCG), for which we reduce the penalty counted towards the utility for a pair of disconnected players to a finite value. Our analysis concentrates on existence, structure, and cost of disconnected regular and strong Nash equilibria. Although the PCG is not a potential game, pure Nash equilibria always and pure strong equilibria very often exist. We provide tight conditions under which disconnected (strong) Nash equilibria can evolve. Components of these equilibria must be (strong) Nash equilibria of a smaller NCG. However, in contrast to the NCG, for almost all parameter values no tree is a stable componen...

  4. ToolConnect: A Functional Connectivity Toolbox for In vitro Networks

    Science.gov (United States)

    Pastore, Vito Paolo; Poli, Daniele; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

    2016-01-01

    Nowadays, the use of in vitro reduced models of neuronal networks to investigate the interplay between structural-functional connectivity and the emerging collective dynamics is a widely accepted approach. In this respect, a relevant advance for this kind of studies has been given by the recent introduction of high-density large-scale Micro-Electrode Arrays (MEAs) which have favored the mapping of functional connections and the recordings of the neuronal electrical activity. Although, several toolboxes have been implemented to characterize network dynamics and derive functional links, no specifically dedicated software for the management of huge amount of data and direct estimation of functional connectivity maps has been developed. toolconnect offers the implementation of up to date algorithms and a user-friendly Graphical User Interface (GUI) to analyze recorded data from large scale networks. It has been specifically conceived as a computationally efficient open-source software tailored to infer functional connectivity by analyzing the spike trains acquired from in vitro networks coupled to MEAs. In the current version, toolconnect implements correlation- (cross-correlation, partial-correlation) and information theory (joint entropy, transfer entropy) based core algorithms, as well as useful and practical add-ons to visualize functional connectivity graphs and extract some topological features. In this work, we present the software, its main features and capabilities together with some demonstrative applications on hippocampal recordings. PMID:27065841

  5. ToolConnect: A Functional Connectivity Toolbox for In vitro Networks.

    Science.gov (United States)

    Pastore, Vito Paolo; Poli, Daniele; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

    2016-01-01

    Nowadays, the use of in vitro reduced models of neuronal networks to investigate the interplay between structural-functional connectivity and the emerging collective dynamics is a widely accepted approach. In this respect, a relevant advance for this kind of studies has been given by the recent introduction of high-density large-scale Micro-Electrode Arrays (MEAs) which have favored the mapping of functional connections and the recordings of the neuronal electrical activity. Although, several toolboxes have been implemented to characterize network dynamics and derive functional links, no specifically dedicated software for the management of huge amount of data and direct estimation of functional connectivity maps has been developed. toolconnect offers the implementation of up to date algorithms and a user-friendly Graphical User Interface (GUI) to analyze recorded data from large scale networks. It has been specifically conceived as a computationally efficient open-source software tailored to infer functional connectivity by analyzing the spike trains acquired from in vitro networks coupled to MEAs. In the current version, toolconnect implements correlation- (cross-correlation, partial-correlation) and information theory (joint entropy, transfer entropy) based core algorithms, as well as useful and practical add-ons to visualize functional connectivity graphs and extract some topological features. In this work, we present the software, its main features and capabilities together with some demonstrative applications on hippocampal recordings.

  6. ToolConnect: a functional connectivity toolbox for in vitro networks

    Directory of Open Access Journals (Sweden)

    Vito Paolo Pastore

    2016-03-01

    Full Text Available Nowadays, the use of in vitro reduced models of neuronal networks to investigate the interplay between structural-functional connectivity and the emerging collective dynamics is a widely accepted approach. In this respect, a relevant advance for this kind of studies has been given by the recent introduction of high-density large-scale Micro-Electrode Arrays (MEAs which have favored the mapping of functional connections and the recordings of the neuronal electrical activity. Although several toolboxes have been implemented to characterize network dynamics and derive functional links, no specifically dedicated software for the management of huge amount of data and direct estimation of functional connectivity maps has been developed. TOOLCONNECT offers the implementation of up to date algorithms and a user-friendly Graphical User Interface (GUI to analyze recorded data from large scale networks. It has been specifically conceived as a computationally efficient open-source software tailored to infer functional connectivity by analyzing the spike trains acquired from in vitro networks coupled to MEAs. In the current version, TOOLCONNECT implements correlation- (cross-correlation, partial-correlation and information theory (joint entropy, transfer entropy based core algorithms, as well as useful and practical add-ons to visualize functional connectivity graphs and extract some topological features. In this work, we present the software, its main features and capabilities together with some demonstrative applications on hippocampal recordings.

  7. Wave speed in excitable random networks with spatially constrained connections.

    Directory of Open Access Journals (Sweden)

    Nikita Vladimirov

    Full Text Available Very fast oscillations (VFO in neocortex are widely observed before epileptic seizures, and there is growing evidence that they are caused by networks of pyramidal neurons connected by gap junctions between their axons. We are motivated by the spatio-temporal waves of activity recorded using electrocorticography (ECoG, and study the speed of activity propagation through a network of neurons axonally coupled by gap junctions. We simulate wave propagation by excitable cellular automata (CA on random (Erdös-Rényi networks of special type, with spatially constrained connections. From the cellular automaton model, we derive a mean field theory to predict wave propagation. The governing equation resolved by the Fisher-Kolmogorov PDE fails to describe wave speed. A new (hyperbolic PDE is suggested, which provides adequate wave speed v( that saturates with network degree , in agreement with intuitive expectations and CA simulations. We further show that the maximum length of connection is a much better predictor of the wave speed than the mean length. When tested in networks with various degree distributions, wave speeds are found to strongly depend on the ratio of network moments / rather than on mean degree , which is explained by general network theory. The wave speeds are strikingly similar in a diverse set of networks, including regular, Poisson, exponential and power law distributions, supporting our theory for various network topologies. Our results suggest practical predictions for networks of electrically coupled neurons, and our mean field method can be readily applied for a wide class of similar problems, such as spread of epidemics through spatial networks.

  8. Periodic Hydraulic Testing for Discerning Fracture Network Connections

    Science.gov (United States)

    Becker, M.; Le Borgne, T.; Bour, O.; Guihéneuf, N.; Cole, M.

    2015-12-01

    Discrete fracture network (DFN) models often predict highly variable hydraulic connections between injection and pumping wells used for enhanced oil recovery, geothermal energy extraction, and groundwater remediation. Such connections can be difficult to verify in fractured rock systems because standard pumping or pulse interference tests interrogate too large a volume to pinpoint specific connections. Three field examples are presented in which periodic hydraulic tests were used to obtain information about hydraulic connectivity in fractured bedrock. The first site, a sandstone in New York State, involves only a single fracture at a scale of about 10 m. The second site, a granite in Brittany, France, involves a fracture network at about the same scale. The third site, a granite/schist in the U.S. State of New Hampshire, involves a complex network at scale of 30-60 m. In each case periodic testing provided an enhanced view of hydraulic connectivity over previous constant rate tests. Periodic testing is particularly adept at measuring hydraulic diffusivity, which is a more effective parameter than permeability for identify the complexity of flow pathways between measurement locations. Periodic tests were also conducted at multiple frequencies which provides a range in the radius of hydraulic penetration away from the oscillating well. By varying the radius of penetration, we attempt to interrogate the structure of the fracture network. Periodic tests, therefore, may be uniquely suited for verifying and/or calibrating DFN models.

  9. Monotone switching networks for directed connectivity are strictly more powerful than certain-knowledge switching networks

    CERN Document Server

    Potechin, Aaron

    2011-01-01

    L (Logarithmic space) versus NL (Non-deterministic logarithmic space) is one of the great open problems in computational complexity theory. In the paper "Bounds on monotone switching networks for directed connectivity", we separated monotone analogues of L and NL using a model called the switching network model. In particular, by considering inputs consisting of just a path and isolated vertices, we proved that any monotone switching network solving directed connectivity on $N$ vertices must have size at least $N^{\\Omega(\\lg(N))}$ and this bound is tight. If we could show a similar result for general switching networks solving directed connectivity, then this would prove that $L \

  10. Maximizing residual capacity in connection-oriented networks

    Directory of Open Access Journals (Sweden)

    Krzysztof Walkowiak

    2006-07-01

    Full Text Available The following problem arises in the study of survivable connection-oriented networks. Given a demand matrix to be routed between nodes, we want to route all demands, so that the residual capacity given by the difference between link capacity and link flow is maximized. Each demand can use only one path. Therefore, the flow is modeled as nonbifurcated multicommodity flow. We call the considered problem nonbifurcated congestion (NBC problem. Solving NBC problem enables robust restoration of failed connections in a case of network failure. We propose a new heuristic algorithm for NBC problem and compare its performance with existing algorithms.

  11. Neural connections foster social connections: a diffusion-weighted imaging study of social networks.

    Science.gov (United States)

    Hampton, William H; Unger, Ashley; Von Der Heide, Rebecca J; Olson, Ingrid R

    2016-05-01

    Although we know the transition from childhood to adulthood is marked by important social and neural development, little is known about how social network size might affect neurocognitive development or vice versa. Neuroimaging research has identified several brain regions, such as the amygdala, as key to this affiliative behavior. However, white matter connectivity among these regions, and its behavioral correlates, remain unclear. Here we tested two hypotheses: that an amygdalocentric structural white matter network governs social affiliative behavior and that this network changes during adolescence and young adulthood. We measured social network size behaviorally, and white matter microstructure using probabilistic diffusion tensor imaging in a sample of neurologically normal adolescents and young adults. Our results suggest amygdala white matter microstructure is key to understanding individual differences in social network size, with connectivity to other social brain regions such as the orbitofrontal cortex and anterior temporal lobe predicting much variation. In addition, participant age correlated with both network size and white matter variation in this network. These findings suggest the transition to adulthood may constitute a critical period for the optimization of structural brain networks underlying affiliative behavior.

  12. Connectivity within and among a network of temperate marine reserves.

    Directory of Open Access Journals (Sweden)

    Melinda A Coleman

    Full Text Available Networks of marine reserves are increasingly being promoted as a means of conserving marine biodiversity. One consideration in designing systems of marine reserves is the maintenance of connectivity to ensure the long-term persistence and resilience of populations. Knowledge of connectivity, however, is frequently lacking during marine reserve design and establishment. We characterise patterns of genetic connectivity of 3 key species of habitat-forming macroalgae across an established network of temperate marine reserves on the east coast of Australia and the implications for adaptive management and marine reserve design. Connectivity varied greatly among species. Connectivity was high for the subtidal macroalgae Ecklonia radiata and Phyllospora comosa and neither species showed any clear patterns of genetic structuring with geographic distance within or among marine parks. In contrast, connectivity was low for the intertidal, Hormosira banksii, and there was a strong pattern of isolation by distance. Coastal topography and latitude influenced small scale patterns of genetic structure. These results suggest that some species are well served by the current system of marine reserves in place along this temperate coast but it may be warranted to revisit protection of intertidal habitats to ensure the long-term persistence of important habitat-forming macroalgae. Adaptively managing marine reserve design to maintain connectivity may ensure the long-term persistence and resilience of marine habitats and the biodiversity they support.

  13. Connectivity within and among a network of temperate marine reserves.

    Science.gov (United States)

    Coleman, Melinda A; Chambers, Justine; Knott, Nathan A; Malcolm, Hamish A; Harasti, David; Jordan, Alan; Kelaher, Brendan P

    2011-01-01

    Networks of marine reserves are increasingly being promoted as a means of conserving marine biodiversity. One consideration in designing systems of marine reserves is the maintenance of connectivity to ensure the long-term persistence and resilience of populations. Knowledge of connectivity, however, is frequently lacking during marine reserve design and establishment. We characterise patterns of genetic connectivity of 3 key species of habitat-forming macroalgae across an established network of temperate marine reserves on the east coast of Australia and the implications for adaptive management and marine reserve design. Connectivity varied greatly among species. Connectivity was high for the subtidal macroalgae Ecklonia radiata and Phyllospora comosa and neither species showed any clear patterns of genetic structuring with geographic distance within or among marine parks. In contrast, connectivity was low for the intertidal, Hormosira banksii, and there was a strong pattern of isolation by distance. Coastal topography and latitude influenced small scale patterns of genetic structure. These results suggest that some species are well served by the current system of marine reserves in place along this temperate coast but it may be warranted to revisit protection of intertidal habitats to ensure the long-term persistence of important habitat-forming macroalgae. Adaptively managing marine reserve design to maintain connectivity may ensure the long-term persistence and resilience of marine habitats and the biodiversity they support.

  14. Complex networks: new trends for the analysis of brain connectivity

    CERN Document Server

    Chavez, Mario; Latora, Vito; Martinerie, Jacques

    2010-01-01

    Today, the human brain can be studied as a whole. Electroencephalography, magnetoencephalography, or functional magnetic resonance imaging techniques provide functional connectivity patterns between different brain areas, and during different pathological and cognitive neuro-dynamical states. In this Tutorial we review novel complex networks approaches to unveil how brain networks can efficiently manage local processing and global integration for the transfer of information, while being at the same time capable of adapting to satisfy changing neural demands.

  15. Coverage and Connectivity Issue in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Rachit Trivedi

    2013-04-01

    Full Text Available Wireless sensor networks (WSNs are an emerging area of interest in research and development. It finds use in military surveillance, health care, environmental monitoring, forest fire detection and smart environments. An important research issue in WSNs is the coverage since cost, area and lifetime are directly validated to it.In this paper we present an overview of WSNs and try to refine the coverage and connectivity issues in wireless sensor networks.

  16. Mild hypoxia affects synaptic connectivity in cultured neuronal networks.

    Science.gov (United States)

    Hofmeijer, Jeannette; Mulder, Alex T B; Farinha, Ana C; van Putten, Michel J A M; le Feber, Joost

    2014-04-01

    Eighty percent of patients with chronic mild cerebral ischemia/hypoxia resulting from chronic heart failure or pulmonary disease have cognitive impairment. Overt structural neuronal damage is lacking and the precise cause of neuronal damage is unclear. As almost half of the cerebral energy consumption is used for synaptic transmission, and synaptic failure is the first abrupt consequence of acute complete anoxia, synaptic dysfunction is a candidate mechanism for the cognitive deterioration in chronic mild ischemia/hypoxia. Because measurement of synaptic functioning in patients is problematic, we use cultured networks of cortical neurons from new born rats, grown over a multi-electrode array, as a model system. These were exposed to partial hypoxia (partial oxygen pressure of 150Torr lowered to 40-50Torr) during 3 (n=14) or 6 (n=8) hours. Synaptic functioning was assessed before, during, and after hypoxia by assessment of spontaneous network activity, functional connectivity, and synaptically driven network responses to electrical stimulation. Action potential heights and shapes and non-synaptic stimulus responses were used as measures of individual neuronal integrity. During hypoxia of 3 and 6h, there was a statistically significant decrease of spontaneous network activity, functional connectivity, and synaptically driven network responses, whereas direct responses and action potentials remained unchanged. These changes were largely reversible. Our results indicate that in cultured neuronal networks, partial hypoxia during 3 or 6h causes isolated disturbances of synaptic connectivity.

  17. Connectivity, excitability and activity patterns in neuronal networks

    Science.gov (United States)

    le Feber, Joost; Stoyanova, Irina I.; Chiappalone, Michela

    2014-06-01

    Extremely synchronized firing patterns such as those observed in brain diseases like epilepsy may result from excessive network excitability. Although network excitability is closely related to (excitatory) connectivity, a direct measure for network excitability remains unavailable. Several methods currently exist for estimating network connectivity, most of which are related to cross-correlation. An example is the conditional firing probability (CFP) analysis which calculates the pairwise probability (CFPi,j) that electrode j records an action potential at time t = τ, given that electrode i recorded a spike at t = 0. However, electrode i often records multiple spikes within the analysis interval, and CFP values are biased by the on-going dynamic state of the network. Here we show that in a linear approximation this bias may be removed by deconvoluting CFPi,j with the autocorrelation of i (i.e. CFPi,i), to obtain the single pulse response (SPRi,j)—the average response at electrode j to a single spike at electrode i. Thus, in a linear system SPRs would be independent of the dynamic network state. Nonlinear components of synaptic transmission, such as facilitation and short term depression, will however still affect SPRs. Therefore SPRs provide a clean measure of network excitability. We used carbachol and ghrelin to moderately activate cultured cortical networks to affect their dynamic state. Both neuromodulators transformed the bursting firing patterns of the isolated networks into more dispersed firing. We show that the influence of the dynamic state on SPRs is much smaller than the effect on CFPs, but not zero. The remaining difference reflects the alteration in network excitability. We conclude that SPRs are less contaminated by the dynamic network state and that mild excitation may decrease network excitability, possibly through short term synaptic depression.

  18. Connectivity, cycles, and persistence thresholds in metapopulation networks.

    Science.gov (United States)

    Artzy-Randrup, Yael; Stone, Lewi

    2010-08-05

    Synthesising the relationships between complexity, connectivity, and the stability of large biological systems has been a longstanding fundamental quest in theoretical biology and ecology. With the many exciting developments in modern network theory, interest in these issues has recently come to the forefront in a range of multidisciplinary areas. Here we outline a new theoretical analysis specifically relevant for the study of ecological metapopulations focusing primarily on marine systems, where subpopulations are generally connected via larval dispersal. Our work determines the qualitative and quantitative conditions by which dispersal and network structure control the persistence of a set of age-structured patch populations. Mathematical modelling combined with a graph theoretic analysis demonstrates that persistence depends crucially on the topology of cycles in the dispersal network which tend to enhance the effect of larvae "returning home." Our method clarifies the impact directly due to network structure, but this almost by definition can only be achieved by examining the simplified case in which patches are identical; an assumption that we later relax. The methodology identifies critical migration routes, whose presence are vital to overall stability, and therefore should have high conservation priority. In contrast, "lonely links," or links in the network that do not participate in a cyclical component, have no impact on persistence and thus have low conservation priority. A number of other intriguing criteria for persistence are derived. Our modelling framework reveals new insights regarding the determinants of persistence, stability, and thresholds in complex metapopulations. In particular, while theoretical arguments have, in the past, suggested that increasing connectivity is a destabilizing feature in complex systems, this is not evident in metapopulation networks where connectivity, cycles, coherency, and heterogeneity all tend to enhance

  19. Connectivity, cycles, and persistence thresholds in metapopulation networks.

    Directory of Open Access Journals (Sweden)

    Yael Artzy-Randrup

    Full Text Available Synthesising the relationships between complexity, connectivity, and the stability of large biological systems has been a longstanding fundamental quest in theoretical biology and ecology. With the many exciting developments in modern network theory, interest in these issues has recently come to the forefront in a range of multidisciplinary areas. Here we outline a new theoretical analysis specifically relevant for the study of ecological metapopulations focusing primarily on marine systems, where subpopulations are generally connected via larval dispersal. Our work determines the qualitative and quantitative conditions by which dispersal and network structure control the persistence of a set of age-structured patch populations. Mathematical modelling combined with a graph theoretic analysis demonstrates that persistence depends crucially on the topology of cycles in the dispersal network which tend to enhance the effect of larvae "returning home." Our method clarifies the impact directly due to network structure, but this almost by definition can only be achieved by examining the simplified case in which patches are identical; an assumption that we later relax. The methodology identifies critical migration routes, whose presence are vital to overall stability, and therefore should have high conservation priority. In contrast, "lonely links," or links in the network that do not participate in a cyclical component, have no impact on persistence and thus have low conservation priority. A number of other intriguing criteria for persistence are derived. Our modelling framework reveals new insights regarding the determinants of persistence, stability, and thresholds in complex metapopulations. In particular, while theoretical arguments have, in the past, suggested that increasing connectivity is a destabilizing feature in complex systems, this is not evident in metapopulation networks where connectivity, cycles, coherency, and heterogeneity all tend

  20. Dual connectivity for LTE-advanced heterogeneous networks

    DEFF Research Database (Denmark)

    Wang, Hua; Rosa, Claudio; Pedersen, Klaus I.

    2016-01-01

    Dual connectivity (DC) allows user equipments (UEs) to receive data simultaneously from different eNodeBs (eNBs) in order to boost the performance in a heterogeneous network with dedicated carrier deployment. Yet, how to efficiently operate with DC opens a number of research questions. In this pa...

  1. Hidden Connectivity in Networks with Vulnerable Classes of Nodes

    Science.gov (United States)

    Krause, Sebastian M.; Danziger, Michael M.; Zlatić, Vinko

    2016-10-01

    In many complex systems representable as networks, nodes can be separated into different classes. Often these classes can be linked to a mutually shared vulnerability. Shared vulnerabilities may be due to a shared eavesdropper or correlated failures. In this paper, we show the impact of shared vulnerabilities on robust connectivity and how the heterogeneity of node classes can be exploited to maintain functionality by utilizing multiple paths. Percolation is the field of statistical physics that is generally used to analyze connectivity in complex networks, but in its existing forms, it cannot treat the heterogeneity of multiple vulnerable classes. To analyze the connectivity under these constraints, we describe each class as a color and develop a "color-avoiding" percolation. We present an analytic theory for random networks and a numerical algorithm for all networks, with which we can determine which nodes are color-avoiding connected and whether the maximal set percolates in the system. We find that the interaction of topology and color distribution implies a rich critical behavior, with critical values and critical exponents depending both on the topology and on the color distribution. Applying our physics-based theory to the Internet, we show how color-avoiding percolation can be used as the basis for new topologically aware secure communication protocols. Beyond applications to cybersecurity, our framework reveals a new layer of hidden structure in a wide range of natural and technological systems.

  2. Real-time estimation of dynamic functional connectivity networks.

    Science.gov (United States)

    Monti, Ricardo Pio; Lorenz, Romy; Braga, Rodrigo M; Anagnostopoulos, Christoforos; Leech, Robert; Montana, Giovanni

    2017-01-01

    Two novel and exciting avenues of neuroscientific research involve the study of task-driven dynamic reconfigurations of functional connectivity networks and the study of functional connectivity in real-time. While the former is a well-established field within neuroscience and has received considerable attention in recent years, the latter remains in its infancy. To date, the vast majority of real-time fMRI studies have focused on a single brain region at a time. This is due in part to the many challenges faced when estimating dynamic functional connectivity networks in real-time. In this work, we propose a novel methodology with which to accurately track changes in time-varying functional connectivity networks in real-time. The proposed method is shown to perform competitively when compared to state-of-the-art offline algorithms using both synthetic as well as real-time fMRI data. The proposed method is applied to motor task data from the Human Connectome Project as well as to data obtained from a visuospatial attention task. We demonstrate that the algorithm is able to accurately estimate task-related changes in network structure in real-time. Hum Brain Mapp 38:202-220, 2017. © 2016 Wiley Periodicals, Inc.

  3. Connectivity network measures predict volumetric atrophy in mild cognitive impairment.

    Science.gov (United States)

    Nir, Talia M; Jahanshad, Neda; Toga, Arthur W; Bernstein, Matt A; Jack, Clifford R; Weiner, Michael W; Thompson, Paul M

    2015-01-01

    Alzheimer's disease (AD) is characterized by cortical atrophy and disrupted anatomic connectivity, and leads to abnormal interactions between neural systems. Diffusion-weighted imaging (DWI) and graph theory can be used to evaluate major brain networks and detect signs of a breakdown in network connectivity. In a longitudinal study using both DWI and standard magnetic resonance imaging (MRI), we assessed baseline white-matter connectivity patterns in 30 subjects with mild cognitive impairment (MCI, mean age 71.8 ± 7.5 years, 18 males and 12 females) from the Alzheimer's Disease Neuroimaging Initiative. Using both standard MRI-based cortical parcellations and whole-brain tractography, we computed baseline connectivity maps from which we calculated global "small-world" architecture measures, including mean clustering coefficient and characteristic path length. We evaluated whether these baseline network measures predicted future volumetric brain atrophy in MCI subjects, who are at risk for developing AD, as determined by 3-dimensional Jacobian "expansion factor maps" between baseline and 6-month follow-up anatomic scans. This study suggests that DWI-based network measures may be a novel predictor of AD progression.

  4. Abnormal connectivity between attentional, language and auditory networks in schizophrenia

    NARCIS (Netherlands)

    Liemburg, Edith J.; Vercammen, Ans; Ter Horst, Gert J.; Curcic-Blake, Branislava; Knegtering, Henderikus; Aleman, Andre

    2012-01-01

    Brain circuits involved in language processing have been suggested to be compromised in patients with schizophrenia. This does not only include regions subserving language production and perception, but also auditory processing and attention. We investigated resting state network connectivity of aud

  5. Virtual private networks can provide reliable IT connections.

    Science.gov (United States)

    Kabachinski, Jeff

    2006-01-01

    A VPN is a private network that uses a public network, such as the Internet, to connect remote sites and users together. Instead of using a dedicated hard-wired connection as in a trusted connection or leased lines, a VPN uses a virtual connection routed through the Internet from the organization's private network to the remote site or employee. Typical VPN services allow for security in terms of data encryption as well as means to authenticate, authorize, and account for all the traffic. VPN services allow the organization to use whatever network operating system they wish as it also encapsulate your data into the protocols needed to transport data across public lines. The intention of this IT World article was to give the reader an introduction to VPNs. Keep in mind that there are no standard models for a VPN. You're likely to come across many vendors presenting the virtues of their VPN applications and devices when you Google "VPN." However the general uses, concepts, and principles outlined here should give you a fighting chance to read through the marketing language in the online ads and "white papers."

  6. A Provisional Framework for Studying Information Connectivity in Food Networks

    OpenAIRE

    Engelseth, Per; Karlsen, Anniken

    2008-01-01

    Through a discussion of peculiarities of food supply, involving focus on information connectivity, a preliminary framework is sought that underlines joint responsibility in a complete supply chain of actors working in network context to achieve safe, quality and economic provision of products to end-use.

  7. Connectivity in Secure Wireless Sensor Networks under Transmission Constraints

    CERN Document Server

    Zhao, Jun; Gligor, Virgil

    2015-01-01

    In wireless sensor networks (WSNs), the Eschenauer-Gligor (EG) key pre-distribution scheme is a widely recognized way to secure communications. Although connectivity properties of secure WSNs with the EG scheme have been extensively investigated, few results address physical transmission constraints. These constraints reflect real-world implementations of WSNs in which two sensors have to be within a certain distance from each other to communicate. In this paper, we present zero-one laws for connectivity in WSNs employing the EG scheme under transmission constraints. These laws help specify the critical transmission ranges for connectivity. Our analytical findings are confirmed via numerical experiments. In addition to secure WSNs, our theoretical results are also applied to frequency hopping in wireless networks.

  8. Embedded generation connection incentives for distribution network operators

    Energy Technology Data Exchange (ETDEWEB)

    Williams, P.; Andrews, S.

    2002-07-01

    This is the final report with respect to work commissioned by the Department of Trade and Industry (DTI) as part of the New and Renewable Energy Programme into incentives for distribution network operators (DNOs) for the connection of embedded generation. This report, which incorporates the contents of the interim report submitted in February 2002, considers the implications of changes in the structure and regulation in the UK electricity industry on the successful technical and commercial integrated of embedded generation into distribution networks. The report examines: the obligations of public electricity suppliers (PESs); current DNO practices regarding the connection of embedded generation; the changes introduced by the Utilities Act 2000, including the impact of new obligations placed on DNOs on the connection of embedded generation and the requirements of the new Electricity Distribution Standard Licence conditions; and problems and prospects for DNO incentives.

  9. Two Dimensional Connectivity for Vehicular Ad-Hoc Networks

    CERN Document Server

    Farivar, Masoud; Ashtiani, Farid

    2008-01-01

    In this paper, we focus on two-dimensional connectivity in sparse vehicular ad hoc networks (VANETs). In this respect, we find thresholds for the arrival rates of vehicles at entrances of a block of streets such that the connectivity is guaranteed for any desired probability. To this end, we exploit a mobility model recently proposed for sparse VANETs, based on BCMP open queuing networks and solve the related traffic equations to find the traffic characteristics of each street and use the results to compute the exact probability of connectivity along these streets. Then, we use the results from percolation theory and the proposed fast algorithms for evaluation of bond percolation problem in a random graph corresponding to the block of the streets. We then find sufficiently accurate two dimensional connectivity-related parameters, such as the average number of intersections connected to each other and the size of the largest set of inter-connected intersections. We have also proposed lower bounds for the case ...

  10. Age-related changes in task related functional network connectivity.

    Directory of Open Access Journals (Sweden)

    Jason Steffener

    Full Text Available Aging has a multi-faceted impact on brain structure, brain function and cognitive task performance, but the interaction of these different age-related changes is largely unexplored. We hypothesize that age-related structural changes alter the functional connectivity within the brain, resulting in altered task performance during cognitive challenges. In this neuroimaging study, we used independent components analysis to identify spatial patterns of coordinated functional activity involved in the performance of a verbal delayed item recognition task from 75 healthy young and 37 healthy old adults. Strength of functional connectivity between spatial components was assessed for age group differences and related to speeded task performance. We then assessed whether age-related differences in global brain volume were associated with age-related differences in functional network connectivity. Both age groups used a series of spatial components during the verbal working memory task and the strength and distribution of functional network connectivity between these components differed across the age groups. Poorer task performance, i.e. slower speed with increasing memory load, in the old adults was associated with decreases in functional network connectivity between components comprised of the supplementary motor area and the middle cingulate and between the precuneus and the middle/superior frontal cortex. Advancing age also led to decreased brain volume; however, there was no evidence to support the hypothesis that age-related alterations in functional network connectivity were the result of global brain volume changes. These results suggest that age-related differences in the coordination of neural activity between brain regions partially underlie differences in cognitive performance.

  11. Brain extracellular matrix retains connectivity in neuronal networks.

    Science.gov (United States)

    Bikbaev, Arthur; Frischknecht, Renato; Heine, Martin

    2015-09-29

    The formation and maintenance of connectivity are critically important for the processing and storage of information in neuronal networks. The brain extracellular matrix (ECM) appears during postnatal development and surrounds most neurons in the adult mammalian brain. Importantly, the removal of the ECM was shown to improve plasticity and post-traumatic recovery in the CNS, but little is known about the mechanisms. Here, we investigated the role of the ECM in the regulation of the network activity in dissociated hippocampal cultures grown on microelectrode arrays (MEAs). We found that enzymatic removal of the ECM in mature cultures led to transient enhancement of neuronal activity, but prevented disinhibition-induced hyperexcitability that was evident in age-matched control cultures with intact ECM. Furthermore, the ECM degradation followed by disinhibition strongly affected the network interaction so that it strongly resembled the juvenile pattern seen in naïve developing cultures. Taken together, our results demonstrate that the ECM plays an important role in retention of existing connectivity in mature neuronal networks that can be exerted through synaptic confinement of glutamate. On the other hand, removal of the ECM can play a permissive role in modification of connectivity and adaptive exploration of novel network architecture.

  12. Connectivity and Nestedness in Bipartite Networks from Community Ecology

    Energy Technology Data Exchange (ETDEWEB)

    Corso, Gilberto [Departamento de Biofisica e Farmacologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil); De Araujo, A I Levartoski [Instituto Federal de Educacao, Ciencia e Tecnologia do Ceara Av. Treze de Maio, 2081 - Benfica CEP 60040-531 - Fortaleza, CE (Brazil); De Almeida, Adriana M, E-mail: corso@cb.ufrn.br [Departamento de Botanica, Ecologia e Zoologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil)

    2011-03-01

    Bipartite networks and the nestedness concept appear in two different contexts in theoretical ecology: community ecology and islands biogeography. From a mathematical perspective nestedness is a pattern in a bipartite network. There are several nestedness indices in the market, we used the index {nu}. The index {nu} is found using the relation {nu} = 1 - {tau} where {tau} is the temperature of the adjacency matrix of the bipartite network. By its turn {tau} is defined with help of the Manhattan distance of the occupied elements of the adjacency matrix of the bipartite network. We prove that the nestedness index {nu} is a function of the connectivities of the bipartite network. In addition we find a concise way to find {nu} which avoid cumbersome algorithm manupulation of the adjacency matrix.

  13. Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks

    Directory of Open Access Journals (Sweden)

    Lindsay eRutter

    2013-07-01

    Full Text Available Complex networks have been observed to comprise small-world properties, believed to represent an optimal organization of local specialization and global integration of information processing at reduced wiring cost. Here, we applied magnitude squared coherence to resting magnetoencephalographic time series in reconstructed source space, acquired from controls and patients with schizophrenia, and generated frequency-dependent adjacency matrices modeling functional connectivity between virtual channels. After configuring undirected binary and weighted graphs, we found that all human networks demonstrated highly localized clustering and short characteristic path lengths. The most conservatively thresholded networks showed efficient wiring, with topographical distance between connected vertices amounting to one-third as observed in surrogate randomized topologies. Nodal degrees of the human networks conformed to a heavy-tailed exponentially truncated power-law, compatible with the existence of hubs, which included theta and alpha bilateral cerebellar tonsil, beta and gamma bilateral posterior cingulate, and bilateral thalamus across all frequencies. We conclude that all networks showed small-worldness, minimal physical connection distance, and skewed degree distributions characteristic of physically-embedded networks, and that these calculations derived from graph theoretical mathematics did not quantifiably distinguish between subject populations, independent of bandwidth. However, post-hoc measurements of edge computations at the scale of the individual vertex revealed trends of reduced gamma connectivity across the posterior medial parietal cortex in patients, an observation consistent with our prior resting activation study that found significant reduction of synthetic aperture magnetometry gamma power across similar regions. The basis of these small differences remains unclear.

  14. Just in time connectivity for large spiking networks

    Science.gov (United States)

    Lytton, William W.; Omurtag, Ahmet; Neymotin, Samuel A; Hines, Michael L

    2008-01-01

    The scale of large neuronal network simulations is memory-limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically-relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed – just-in-time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities and weights, as well as run-time connectivity state: the event queue. Comparison of the JitCon implementation to NEURON’s standard NetCon connectivity method showed substantial space savings, with associated run-time penalty. Although JitCon saved space by eliminating connectivity parameters, larger simulations were still memory-limited due to growth of the synaptic event queue. We therefore designed a JitEvent algorithm that only added items to the queue when required: instead of alerting multiple postsynaptic cells, a spiking presynaptic cell posted a callback event at the shortest synaptic delay time. At the time of the callback, this same presynaptic cell directly notified the first postsynaptic cell and generated another self-callback for the next delay time. The JitEvent implementation yielded substantial additional time and space savings. We conclude that just-in-time strategies are necessary for very large network simulations but that a variety of alternative strategies should be considered whose optimality will depend on the characteristics of the simulation to be run. PMID:18533821

  15. Altered default mode network functional connectivity in schizotypal personality disorder.

    Science.gov (United States)

    Zhang, Qing; Shen, Jing; Wu, Jianlin; Yu, Xiao; Lou, Wutao; Fan, Hongyu; Shi, Lin; Wang, Defeng

    2014-12-01

    The default mode network (DMN) has been identified to play a critical role in many mental disorders, but such abnormalities have not yet been determined in patients with schizotypal personality disorder (SPD). The purpose of this study was to analyze the alteration of the DMN functional connectivity in subjects with (SPD) and compared it to healthy control subjects. Eighteen DSM-IV diagnosed SPD subjects (all male, average age: 19.7±0.9) from a pool of 3000 first year college students, and eighteen age and gender matched healthy control subjects were recruited (all male, average age: 20.3±0.9). Independent component analysis (ICA) was used to analyze the DMN functional connectivity alteration. Compared to the healthy control group, SPD subjects had significantly decreased functional connectivity in the frontal areas, including the superior and medial frontal gyrus, and greater functional connectivity in the bilateral superior temporal gyrus and sub-lobar regions, including the bilateral putamen and caudate. Compared to subjects with SPD, the healthy control group showed decreased functional connectivity in the bilateral posterior cingulate gyrus, but showed greater functional connectivity in the right transverse temporal gyrus and left middle temporal gyrus. The healthy control group also showed greater activation in the cerebellum compared to the SPD group. These findings suggest that DMN functional connectivity, particularly that involving cognitive or emotional regulation, is altered in SPD subjects, and thus may be helpful in studying schizophrenia.

  16. Pattern reverberation in networks of excitable systems with connection delays

    Science.gov (United States)

    Lücken, Leonhard; Rosin, David P.; Worlitzer, Vasco M.; Yanchuk, Serhiy

    2017-01-01

    We consider the recurrent pulse-coupled networks of excitable elements with delayed connections, which are inspired by the biological neural networks. If the delays are tuned appropriately, the network can either stay in the steady resting state, or alternatively, exhibit a desired spiking pattern. It is shown that such a network can be used as a pattern-recognition system. More specifically, the application of the correct pattern as an external input to the network leads to a self-sustained reverberation of the encoded pattern. In terms of the coupling structure, the tolerance and the refractory time of the individual systems, we determine the conditions for the uniqueness of the sustained activity, i.e., for the functionality of the network as an unambiguous pattern detector. We point out the relation of the considered systems with cyclic polychronous groups and show how the assumed delay configurations may arise in a self-organized manner when a spike-time dependent plasticity of the connection delays is assumed. As excitable elements, we employ the simplistic coincidence detector models as well as the Hodgkin-Huxley neuron models. Moreover, the system is implemented experimentally on a Field-Programmable Gate Array.

  17. Correlation of structural order, anomalous density, and hydrogen bonding network of liquid water.

    Science.gov (United States)

    Bandyopadhyay, Dibyendu; Mohan, S; Ghosh, S K; Choudhury, Niharendu

    2013-07-25

    We use extensive molecular dynamics simulations employing different state-of-the-art force fields to find a common framework for comparing structural orders and density anomalies as obtained from different water models. It is found that the average number of hydrogen bonds correlates well with various order parameters as well as the temperature of maximum densities across the different models, unifying apparently disparate results from different models and emphasizing the importance of hydrogen bonding in determining anomalous properties and the structure of water. A deeper insight into the hydrogen bond network of water reveals that the solvation shell of a water molecule can be defined by considering only those neighbors that are hydrogen-bonded to it. On the basis of this view, the origin of the appearance of a non-tetrahedral peak at a higher temperature in the distribution of tetrahedral order parameters has been explained. It is found that a neighbor that is hydrogen-bonded to the central molecule is tetrahedrally coordinated even at higher temperatures. The non-tetrahedral peak at a higher temperature arises due to the strained orientation of the neighbors that are non-hydrogen-bonded to the central molecule. With the new definition of the solvation shell, liquid water can be viewed as an instantaneously changing random hydrogen-bonded network consisting of differently coordinated hydrogen-bonded molecules with their distinct solvation shells. The variation of the composition of these hydrogen-bonded molecules against temperature accounts for the density anomaly without introducing the concept of large-scale structural polyamorphism in water.

  18. Altered cerebellar functional connectivity with intrinsic connectivity networks in adults with major depressive disorder.

    Directory of Open Access Journals (Sweden)

    Li Liu

    Full Text Available BACKGROUND: Numerous studies have demonstrated the higher-order functions of the cerebellum, including emotion regulation and cognitive processing, and have indicated that the cerebellum should therefore be included in the pathophysiological models of major depressive disorder. The aim of this study was to compare the resting-state functional connectivity of the cerebellum in adults with major depression and healthy controls. METHODS: Twenty adults with major depression and 20 gender-, age-, and education-matched controls were investigated using seed-based resting-state functional connectivity magnetic resonance imaging. RESULTS: Compared with the controls, depressed patients showed significantly increased functional connectivity between the cerebellum and the temporal poles. However, significantly reduced cerebellar functional connectivity was observed in the patient group in relation to both the default-mode network, mainly including the ventromedial prefrontal cortex and the posterior cingulate cortex/precuneus, and the executive control network, mainly including the superior frontal cortex and orbitofrontal cortex. Moreover, the Hamilton Depression Rating Scale score was negatively correlated with the functional connectivity between the bilateral Lobule VIIb and the right superior frontal gyrus in depressed patients. CONCLUSIONS: This study demonstrated increased cerebellar coupling with the temporal poles and reduced coupling with the regions in the default-mode and executive control networks in adults with major depression. These differences between patients and controls could be associated with the emotional disturbances and cognitive control function deficits that accompany major depression. Aberrant cerebellar connectivity during major depression may also imply a substantial role for the cerebellum in the pathophysiological models of depression.

  19. Genes2FANs: connecting genes through functional association networks

    Directory of Open Access Journals (Sweden)

    Dannenfelser Ruth

    2012-07-01

    Full Text Available Abstract Background Protein-protein, cell signaling, metabolic, and transcriptional interaction networks are useful for identifying connections between lists of experimentally identified genes/proteins. However, besides physical or co-expression interactions there are many ways in which pairs of genes, or their protein products, can be associated. By systematically incorporating knowledge on shared properties of genes from diverse sources to build functional association networks (FANs, researchers may be able to identify additional functional interactions between groups of genes that are not readily apparent. Results Genes2FANs is a web based tool and a database that utilizes 14 carefully constructed FANs and a large-scale protein-protein interaction (PPI network to build subnetworks that connect lists of human and mouse genes. The FANs are created from mammalian gene set libraries where mouse genes are converted to their human orthologs. The tool takes as input a list of human or mouse Entrez gene symbols to produce a subnetwork and a ranked list of intermediate genes that are used to connect the query input list. In addition, users can enter any PubMed search term and then the system automatically converts the returned results to gene lists using GeneRIF. This gene list is then used as input to generate a subnetwork from the user’s PubMed query. As a case study, we applied Genes2FANs to connect disease genes from 90 well-studied disorders. We find an inverse correlation between the counts of links connecting disease genes through PPI and links connecting diseases genes through FANs, separating diseases into two categories. Conclusions Genes2FANs is a useful tool for interpreting the relationships between gene/protein lists in the context of their various functions and networks. Combining functional association interactions with physical PPIs can be useful for revealing new biology and help form hypotheses for further experimentation. Our

  20. Neural network connectivity and response latency modelled by stochastic processes

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano

    is connected to thousands of other neurons. The rst question is: how to model neural networks through stochastic processes? A multivariate Ornstein-Uhlenbeck process, obtained as a diffusion approximation of a jump process, is the proposed answer. Obviously, dependencies between neurons imply dependencies......Stochastic processes and their rst passage times have been widely used to describe the membrane potential dynamics of single neurons and to reproduce neuronal spikes, respectively.However, cerebral cortex in human brains is estimated to contain 10-20 billions of neurons and each of them...... between their spike times. Therefore, the second question is: how to detect neural network connectivity from simultaneously recorded spike trains? Answering this question corresponds to investigate the joint distribution of sequences of rst passage times. A non-parametric method based on copulas...

  1. Emergent classical geometries on boundaries of randomly connected tensor networks

    Science.gov (United States)

    Chen, Hua; Sasakura, Naoki; Sato, Yuki

    2016-03-01

    It is shown that classical spaces with geometries emerge on boundaries of randomly connected tensor networks with appropriately chosen tensors in the thermodynamic limit. With variation of the tensors the dimensions of the spaces can be freely chosen, and the geometries—which are curved in general—can be varied. We give the explicit solvable examples of emergent flat tori in arbitrary dimensions, and the correspondence from the tensors to the geometries for general curved cases. The perturbative dynamics in the emergent space is shown to be described by an effective action which is invariant under the spatial diffeomorphism due to the underlying orthogonal group symmetry of the randomly connected tensor network. It is also shown that there are various phase transitions among spaces, including extended and point-like ones, under continuous change of the tensors.

  2. Emergent classical geometries on boundaries of randomly connected tensor networks

    CERN Document Server

    Chen, Hua; Sato, Yuki

    2016-01-01

    It is shown that classical spaces with geometries emerge on boundaries of randomly connected tensor networks with appropriately chosen tensors in the thermodynamic limit. With variation of the tensors, the dimensions of the spaces can be freely chosen, and the geometries, which are curved in general, can be varied. We give the explicit solvable examples of emergent flat tori in arbitrary dimensions, and the correspondence from the tensors to the geometries for general curved cases. The perturbative dynamics in the emergent space is shown to be described by an effective action which is invariant under the spatial diffeomorphism due to the underlying orthogonal group symmetry of the randomly connected tensor network. It is also shown that there are various phase transitions among spaces, including extended and point-like ones, under continuous change of the tensors.

  3. Correlated multiplexity induces unusual connectivity in multiplex random networks

    CERN Document Server

    Lee, Kyu-Min; Cho, Won-kuk; Goh, K -I; Kim, I -M

    2011-01-01

    Nodes in a complex networked system often engage in more than one type of interactions among them; they form a multiplex network with multiple types of links. In real-world complex systems, a node's degree for one type of links and that for the other are not randomly distributed but correlated, which we term correlated multiplexity. In this paper we study a simple model of multiplex random networks and show that the correlated multiplexity can induce unusual properties of giant component in the network. Specifically, when the degrees of a node for different interactions in a duplex Erdos-Renyi network are maximally correlated, the network contains the giant component for any nonzero link densities. On the contrary, when the degrees of a node are maximally anti-correlated, the emergence of giant component is significantly delayed, yet the entire network becomes connected into a single component at a finite link density. We also discuss the mixing patterns and the cases with imperfect correlated multiplexity.

  4. Disrupted Ipsilateral Network Connectivity in Temporal Lobe Epilepsy.

    Directory of Open Access Journals (Sweden)

    Lorena Vega-Zelaya

    Full Text Available The current practice under which patients with refractory epilepsy are surgically treated is based mainly on the identification of specific cortical areas, mainly the epileptogenic zone, which is believed to be responsible for generation of seizures. A better understanding of the whole epileptic network and its components and properties is required before more effective and less invasive therapies can be developed. The aim of the present study was to partially characterize the evolution of the functional network during the preictal-ictal transition in partial seizures in patients with temporal lobe epilepsy (TLE.Scalp and foramen ovale (FOE recordings from twenty-two TLE patients were analyzed under the complex network perspective. The density of links, average path length, average clustering coefficient, and modularity were calculated during the preictal and the ictal stages. Both linear-Pearson correlation-and non-linear-phase synchronization-measures were used as proxies of functional connectivity between the electrode locations areas. The transition from one stage to the other was evaluated in the whole network and in the mesial sub-networks. The results were compared with a voltage-dependent measure, namely, the spectral entropy.Changes in the global functional network during the transition from the preictal to the ictal stage show, in the linear case, that in sixteen cases (72.7% the density of the links increased during the seizure, with a decrease in the average path length in fifteen cases (68.1%. There was also a preictal and ictal imbalance in functional connectivity during both stages (77.2% to 86.3%. The SE dropped during the seizure in 95.4% of the cases, but did not show any tendency towards lateralization. When using the nonlinear measure of functional connectivity, the phase synchronization, similar results were obtained.In TLE patients, the transition to the ictal stage is accompanied by increasing global synchronization and a

  5. Restoration of lost connectivity of partitioned wireless sensor networks

    Directory of Open Access Journals (Sweden)

    Virender Ranga

    2016-05-01

    Full Text Available The lost connectivity due to failure of large scale nodes plays major role to degrade the system performance by generating unnecessary overhead or sometimes totally collapse the active network. There are many issues and challenges to restore the lost connectivity in an unattended scenario, i.e. how many recovery nodes will be sufficient and on which locations these recovery nodes have to be placed. A very few centralized and distributed approaches have been proposed till now. The centralized approaches are good for a scenario where information about the disjoint network, i.e. number of disjoint segments and their locations are well known in advance. However, for a scenario where such information is unknown due to the unattended harsh environment, a distributed approach is a better solution to restore the partitioned network. In this paper, we have proposed and implemented a semi-distributed approach called Relay node Placement using Fermat Point (RPFP. The proposed approach is capable of restoring lost connectivity with small number of recovery relay nodes and it works for any number of disjoint segments. The simulation experiment results show effectiveness of our approach as compared to existing benchmark approaches.

  6. Facilitate generation connections on Orkney by automatic distribution network management

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2004-07-01

    This report summarises the results of a study assessing the capability and limitations of the Orkney Network under a variety of conditions of demand, generation connections, network configuration, and reactive compensation). A conceptual active management scheme (AMS) suitable for the conditions on Orkney is developed and evaluated. Details are given of a proposed framework for the design and evaluation of future active management schemes, logic control sequences for managed generation units, and a proposed evaluation method for the active management scheme. Implications of introducing the proposed AMS are examined, and the commercial aspects of an AMS and system security are considered. The existing Orkney network is described; and an overview of the SHEPDL (Scottish Hydro Electric Power Distribution Ltd.) SCADA system is presented with a discussion of AMS identification, selection, and development.

  7. Evolutionary Algorithm for Optimal Connection Weights in Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    G.V.R. Sagar, S. Venkata Chalam, Manoj Kumar Singh

    2011-12-01

    Full Text Available A neural network may be considered as an adaptive system that progressively self-organizes inorder to approximate the solution, making the problem solver free from the need to accuratelyand unambiguously specify the steps towards the solution. Moreover, Evolutionary computationcan be integrated with artificial Neural Network to increase the performance at various levels; inresult such neural network is called Evolutionary ANN. In this paper very important issue of neuralnetwork namely adjustment of connection weights for learning presented by Genetic algorithmover feed forward architecture. To see the performance of developed solution comparison hasgiven with respect to well established method of learning called gradient decent method. Abenchmark problem of classification, XOR, has taken to justify the experiment. Presented methodis not only having very probability to achieve the global minima but also having very fastconvergence.

  8. Attention reorganizes connectivity across networks in a frequency specific manner

    DEFF Research Database (Denmark)

    Kwon, Soyoung; Watanabe, Masataka; Fischer, Elvira

    2017-01-01

    Attention allows our brain to focus its limited resources on a given task. It does so by selective modulation of neural activity and of functional connectivity (FC) across brain-wide networks. While there is extensive literature on activity changes, surprisingly few studies examined brain-wide FC...... modulations that can be cleanly attributed to attention compared to matched visual processing. In contrast to prior approaches, we used an ultra-long trial design that avoided transients from trial onsets, included slow fluctuations (...-segregated analyses. We found that FC derived from long blocks had a nearly two-fold higher gain compared to FC derived from traditional (short) block designs. Second, attention enhanced intrinsic (negative or positive) correlations across networks, such as between the default-mode network (DMN), the dorsal attention...

  9. 47 CFR 68.201 - Connection to the public switched telephone network.

    Science.gov (United States)

    2010-10-01

    ... CARRIER SERVICES (CONTINUED) CONNECTION OF TERMINAL EQUIPMENT TO THE TELEPHONE NETWORK Terminal Equipment Approval Procedures § 68.201 Connection to the public switched telephone network. Terminal equipment may not be connected to the public switched telephone network unless it has either been certified by...

  10. Maturation of the language network: from inter- to intrahemispheric connectivities.

    Directory of Open Access Journals (Sweden)

    Angela D Friederici

    Full Text Available Language development must go hand-in-hand with brain maturation. Little is known about how the brain develops to serve language processing, in particular, the processing of complex syntax, a capacity unique to humans. Behavioral reports indicate that the ability to process complex syntax is not yet adult-like by the age of seven years. Here, we apply a novel method to demonstrate that the basic neural basis of language, as revealed by low frequency fluctuation stemming from functional MRI data, differs between six-year-old children and adults in crucial aspects. Although the classical language regions are actively in place by the age of six, the functional connectivity between these regions clearly is not. In contrast to adults who show strong connectivities between frontal and temporal language regions within the left hemisphere, children's default language network is characterized by a strong functional interhemispheric connectivity, mainly between the superior temporal regions. These data indicate a functional reorganization of the neural network underlying language development towards a system that allows a close interplay between frontal and temporal regions within the left hemisphere.

  11. Temporal derivative of Total Solar Irradiance and anomalous Indian summer monsoon: An empirical evidence for a Sun–climate connection

    Digital Repository Service at National Institute of Oceanography (India)

    Agnihotri, R.; Dutta, K.; Soon, W.

    causes adverse impacts, drought conditions with anomalously low rainfall are actually culpable for large hunger related deaths and diseases. Though often overall impacts of these dry periods are also man-made (mismanage- ment of resources, wrong economic... than 1 million deaths recorded) in the Indian subcontinent during the last three centuries (source: http://en.wikipedia.org, Timeline of major fam- ines in India during British rule). We have considered only those famines that were caused by crop...

  12. Connected or informed?: Local Twitter networking in a London neighbourhood

    Directory of Open Access Journals (Sweden)

    John Bingham-Hall

    2015-08-01

    Full Text Available This paper asks whether geographically localised, or ‘hyperlocal’, uses of Twitter succeed in creating peer-to-peer neighbourhood networks or simply act as broadcast media at a reduced scale. Literature drawn from the smart cities discourse and from a UK research project into hyperlocal media, respectively, take on these two opposing interpretations. Evidence gathered in the case study presented here is consistent with the latter, and on this basis we criticise the notion that hyperlocal social media can be seen as a community in itself. We demonstrate this by creating a network map of Twitter followers of a popular hyperlocal blog in Brockley, southeast London. We describe various attributes of this network including its average degree and clustering coefficient to suggest that a small and highly connected cluster of visible local entities such as businesses form a clique at the centre of this network, with individual residents following these but not one another. We then plot the locations of these entities and demonstrate that sub-communities in the network are formed due to close geographical proximity between smaller sets of businesses. These observations are illustrated with qualitative evidence from interviews with users who suggest instead that rather than being connected to one another they benefit from what has been described as ‘neighbourhood storytelling’. Despite the limitations of working with Twitter data, we propose that this multi-modal approach offers a valuable way to investigate the experience of using social media as a communication tool in urban neighbourhoods.

  13. Leveraging network connectivity for quality assurance of clinical display monitors.

    Science.gov (United States)

    Gersten, Jennifer

    2012-01-01

    The VA Midwest Health Care Network, VISN 23, is one of 21 veteran integrated health service networks (VISN) under the Department of Veterans Affairs. There are approximately 300,000 imaging studies generated per year and currently more than 14,000 picture archiving and communication system (PACS) users in VISN 23. Biomedical Engineering Services within VISN 23 coordinates the provision of medical technology support. One emerging technology leverages network connectivity as a method of calibrating and continuously monitoring clinical display monitors in support of PACS. Utilizing a continuous calibration monitoring system, clinical displays can be identified as out of Digital Imaging and Communications in Medicine (DICOM) compliance through a centralized server. The technical group can receive immediate notification via e-mail and respond proactively. Previously, this problem could go unnoticed until the next scheduled preventive maintenance was performed. This system utilizes simple network management protocols (SNMP) and simple mail transfer protocols (SMTP) across a wide area network for real-time alerts from a centralized location. This central server supports and monitors approximately 320 clinical displays deployed across five states. Over the past three years of implementation in VISN 23, the remote calibration and monitoring capability has allowed for more efficient support of clinical displays and has enhanced patient safety by ensuring a consistent display of images on these clinical displays.

  14. Tensor-Based Link Prediction in Intermittently Connected Wireless Networks

    CERN Document Server

    Zayani, Mohamed-Haykel; Slama, Ines; Zeghlache, Djamal

    2011-01-01

    Through several studies, it has been highlighted that mobility patterns in mobile networks are driven by human behaviors. This effect has been particularly observed in intermittently connected networks like DTN (Delay Tolerant Networks). Given that common social intentions generate similar human behavior, it is relevant to exploit this knowledge in the network protocols design, e.g. to identify the closeness degree between two nodes. In this paper, we propose a temporal link prediction technique for DTN which quantifies the behavior similarity between each pair of nodes and makes use of it to predict future links. Our prediction method keeps track of the spatio-temporal aspects of nodes behaviors organized as a third-order tensor that aims to records the evolution of the network topology. After collapsing the tensor information, we compute the degree of similarity for each pair of nodes using the Katz measure. This metric gives us an indication on the link occurrence between two nodes relying on their closene...

  15. Connectivity of Confined Dense Networks: Boundary Effects and Scaling Laws

    CERN Document Server

    Coon, Justin P; Georgiou, Orestis

    2012-01-01

    In this paper, we study the probability that a dense network confined within a given geometry is fully connected. We employ a cluster expansion approach often used in statistical physics to analyze the effects that the boundaries of the geometry have on connectivity. To maximize practicality and applicability, we adopt four important point-to-point link models based on outage probability in our analysis: single-input single-output (SISO), single-input multiple-output (SIMO), multiple-input single-output (MISO), and multiple-input multiple-output (MIMO). Furthermore, we derive diversity and power scaling laws that dictate how boundary effects can be mitigated (to leading order) in confined dense networks for each of these models. Finally, in order to demonstrate the versatility of our theory, we analyze boundary effects for dense networks comprising MIMO point-to-point links confined within a right prism, a polyhedron that accurately models many geometries that can be found in practice. We provide numerical re...

  16. Neural network connectivity differences in children who stutter.

    Science.gov (United States)

    Chang, Soo-Eun; Zhu, David C

    2013-12-01

    Affecting 1% of the general population, stuttering impairs the normally effortless process of speech production, which requires precise coordination of sequential movement occurring among the articulatory, respiratory, and resonance systems, all within millisecond time scales. Those afflicted experience frequent disfluencies during ongoing speech, often leading to negative psychosocial consequences. The aetiology of stuttering remains unclear; compared to other neurodevelopmental disorders, few studies to date have examined the neural bases of childhood stuttering. Here we report, for the first time, results from functional (resting state functional magnetic resonance imaging) and structural connectivity analyses (probabilistic tractography) of multimodal neuroimaging data examining neural networks in children who stutter. We examined how synchronized brain activity occurring among brain areas associated with speech production, and white matter tracts that interconnect them, differ in young children who stutter (aged 3-9 years) compared with age-matched peers. Results showed that children who stutter have attenuated connectivity in neural networks that support timing of self-paced movement control. The results suggest that auditory-motor and basal ganglia-thalamocortical networks develop differently in stuttering children, which may in turn affect speech planning and execution processes needed to achieve fluent speech motor control. These results provide important initial evidence of neurological differences in the early phases of symptom onset in children who stutter.

  17. Network connections that evolve to circumvent the inverse optics problem.

    Science.gov (United States)

    Ng, Cherlyn; Sundararajan, Janani; Hogan, Michael; Purves, Dale

    2013-01-01

    A fundamental problem in vision science is how useful perceptions and behaviors arise in the absence of information about the physical sources of retinal stimuli (the inverse optics problem). Psychophysical studies show that human observers contend with this problem by using the frequency of occurrence of stimulus patterns in cumulative experience to generate percepts. To begin to understand the neural mechanisms underlying this strategy, we examined the connectivity of simple neural networks evolved to respond according to the cumulative rank of stimulus luminance values. Evolved similarities with the connectivity of early level visual neurons suggests that biological visual circuitry uses the same mechanisms as a means of creating useful perceptions and behaviors without information about the real world.

  18. Network connections that evolve to circumvent the inverse optics problem.

    Directory of Open Access Journals (Sweden)

    Cherlyn Ng

    Full Text Available A fundamental problem in vision science is how useful perceptions and behaviors arise in the absence of information about the physical sources of retinal stimuli (the inverse optics problem. Psychophysical studies show that human observers contend with this problem by using the frequency of occurrence of stimulus patterns in cumulative experience to generate percepts. To begin to understand the neural mechanisms underlying this strategy, we examined the connectivity of simple neural networks evolved to respond according to the cumulative rank of stimulus luminance values. Evolved similarities with the connectivity of early level visual neurons suggests that biological visual circuitry uses the same mechanisms as a means of creating useful perceptions and behaviors without information about the real world.

  19. Reward networks in the brain as captured by connectivity measures

    Directory of Open Access Journals (Sweden)

    Estela Camara

    2009-12-01

    Full Text Available An assortment of human behaviors is thought to be driven by rewards including reinforcement learning, novelty processing, learning, decision making, economic choice, incentive motivation, and addiction. In each case the ventral tegmental area / ventral striatum (Nucleus accumbens system (VTA-VS has been implicated as a key structure by functional imaging studies, mostly on the basis of standard, univariate analyses. Here we propose that standard fMRI analysis needs to be complemented by methods that take into account the differential connectivity of the VTA-VS system in the different behavioral contexts in order to describe reward based processes more appropriately. We first consider the wider network for reward processing as it emerged from animal experimentation. Subsequently, an example for a method to assess functional connectivity is given. Finally, we illustrate the usefulness of such analyses by examples regarding reward valuation, reward expectation and the role of reward in addiction.

  20. Understanding magnetotransport signatures in networks of connected permalloy nanowires

    Science.gov (United States)

    Le, B. L.; Park, J.; Sklenar, J.; Chern, G.-W.; Nisoli, C.; Watts, J. D.; Manno, M.; Rench, D. W.; Samarth, N.; Leighton, C.; Schiffer, P.

    2017-02-01

    The change in electrical resistance associated with the application of an external magnetic field is known as the magnetoresistance (MR). The measured MR is quite complex in the class of connected networks of single-domain ferromagnetic nanowires, known as "artificial spin ice," due to the geometrically induced collective behavior of the nanowire moments. We have conducted a thorough experimental study of the MR of a connected honeycomb artificial spin ice, and we present a simulation methodology for understanding the detailed behavior of this complex correlated magnetic system. Our results demonstrate that the behavior, even at low magnetic fields, can be well described only by including significant contributions from the vertices at which the legs meet, opening the door to new geometrically induced MR phenomena.

  1. Small vessel disease and cognitive impairment : The relevance of central network connections

    NARCIS (Netherlands)

    Reijmer, Yael D.; Fotiadis, Panagiotis; Piantoni, Giovanni; Boulouis, Gregoire; Kelly, Kathleen E.; Gurol, Mahmut E.; Leemans, Alexander; O'Sullivan, Michael J.; Greenberg, Steven M.; Viswanathan, Anand

    2016-01-01

    Central brain network connections greatly contribute to overall network efficiency. Here we examined whether small vessel disease (SVD) related white matter alterations in central brain network connections have a greater impact on executive functioning than alterations in non-central brain network c

  2. Internet Connectivity using Vehicular Ad-Hoc Networks

    OpenAIRE

    Hashim Ali; Aamir Saeed; Syed Rohullah Jan; Asadullah; Ahsan Khawaja

    2012-01-01

    Although a mobile Ad-Hoc network (MANET) can be used in many cases but the most preferable is a MANET connected to the internet. This is achieved by using gateways which act as bridges between a MANET and the internet. To communicate in-between, a mobile node needs to find a valid route to the gateway which requires gateway discovery mechanism. In this paper Ad hoc On-Demand Distance Vector (AODV) is altered to achieve the interconnection between a MANET and the Internet. Furthermore, the pap...

  3. Evaluation of GPFS Connectivity Over High-Performance Networks

    Energy Technology Data Exchange (ETDEWEB)

    Srinivasan, Jay; Canon, Shane; Andrews, Matthew

    2009-02-17

    We present the results of an evaluation of new features of the latest release of IBM's GPFS filesystem (v3.2). We investigate different ways of connecting to a high-performance GPFS filesystem from a remote cluster using Infiniband (IB) and 10 Gigabit Ethernet. We also examine the performance of the GPFS filesystem with both serial and parallel I/O. Finally, we also present our recommendations for effective ways of utilizing high-bandwidth networks for high-performance I/O to parallel file systems.

  4. Quetiapine modulates functional connectivity in brain aggression networks.

    Science.gov (United States)

    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.

  5. Network Intelligence Based on Network State Information for Connected Vehicles Utilizing Fog Computing

    Directory of Open Access Journals (Sweden)

    Seongjin Park

    2017-01-01

    Full Text Available This paper proposes a method to take advantage of fog computing and SDN in the connected vehicle environment, where communication channels are unstable and the topology changes frequently. A controller knows the current state of the network by maintaining the most recent network topology. Of all the information collected by the controller in the mobile environment, node mobility information is particularly important. Thus, we divide nodes into three classes according to their mobility types and use their related attributes to efficiently manage the mobile connections. Our approach utilizes mobility information to reduce control message overhead by adjusting the period of beacon messages and to support efficient failure recovery. One is to recover the connection failures using only mobility information, and the other is to suggest a real-time scheduling algorithm to recover the services for the vehicles that lost connection in the case of a fog server failure. A real-time scheduling method is first described and then evaluated. The results show that our scheme is effective in the connected vehicle environment. We then demonstrate the reduction of control overhead and the connection recovery by using a network simulator. The simulation results show that control message overhead and failure recovery time are decreased by approximately 55% and 5%, respectively.

  6. Lattice Calculation of the Connected Hadronic Light-by-Light Contribution to the Muon Anomalous Magnetic Moment

    CERN Document Server

    Jin, Luchang; Christ, Norman; Hayakawa, Masashi; Izubuchi, Taku; Lehner, Christoph

    2015-01-01

    The anomalous magnetic moment of muon, $g-2$, is a very precisely measured quantity. However, the current measurement disagrees with standard model by about 3 standard deviations. Hadronic vacuum polarization and hadronic light by light are the two types of processes that contribute most to the theoretical uncertainty. I will describe how lattice methods are well-suited to provide a first-principle's result for the hadronic light by light contribution, the various numerical strategies that are presently being used to evaluate it, our current results and the important remaining challenges which must be overcome.

  7. Larval connectivity in an effective network of marine protected areas.

    Directory of Open Access Journals (Sweden)

    Mark R Christie

    Full Text Available Acceptance of marine protected areas (MPAs as fishery and conservation tools has been hampered by lack of direct evidence that MPAs successfully seed unprotected areas with larvae of targeted species. For the first time, we present direct evidence of large-scale population connectivity within an existing and effective network of MPAs. A new parentage analysis identified four parent-offspring pairs from a large, exploited population of the coral-reef fish Zebrasoma flavescens in Hawai'i, revealing larval dispersal distances ranging from 15 to 184 km. In two cases, successful dispersal was from an MPA to unprotected sites. Given high adult abundances, the documentation of any parent-offspring pairs demonstrates that ecologically-relevant larval connectivity between reefs is substantial. All offspring settled at sites to the north of where they were spawned. Satellite altimetry and oceanographic models from relevant time periods indicated a cyclonic eddy that created prevailing northward currents between sites where parents and offspring were found. These findings empirically demonstrate the effectiveness of MPAs as useful conservation and management tools and further highlight the importance of coupling oceanographic, genetic, and ecological data to predict, validate and quantify larval connectivity among marine populations.

  8. The Diversity of Anomalous HEDs: Isotopic Constraints on the Connection of EET 92023, GRA 98098, and Dhofar 700 With Vesta

    Science.gov (United States)

    Sanborn, M. E.; Yin, Q.-Z.; Mittlefehldt, D. W.

    2016-01-01

    The possibility for multiple parent bodies, instead of a common parent body of Vesta, for eucrites has been suggested based on the variable oxygen isotopic composition observed in some eucrites.. Recently, we added an extra dimension to the discussion based on the (epsilon)54Cr composition of the same eucrites with known (delta)17O to compare with the normal eucrites. The combined (delta)17O and (epsilon)54Cr isotope systematics for Pasamonte, PCA 91007, A-881394, and Ibitira indicate their likely origin from multiple different parent bodies than the normal eucrites. Often the qualifier anomalous is used to identify HEDs with (delta)17O values that deviate significantly (>3(sigma)) from the mean HED (delta)17O. However, variations in eucrites and diogenites also include unique geochemical characteristics such as bulk composition, trace element abundances, or volatile concentrations, in addition to (delta)17O. Here, we investigate three such geochemically anomalous HEDs: Elephant Moraine (EET) 92023, Graves Nunataks (GRA) 98098, and Dhofar 700. In addition, to verify the homogeneity of (epsilon)54Cr observed for normal HEDs thus far, a set of seven eucrites and diogenites considered normal samples were also investigated.

  9. k-CONNECTED HYBRID RELAY NODE PLACEMENT IN WIRELESS SENSOR NETWORK FOR RESTORING CONNECTIVITY

    Directory of Open Access Journals (Sweden)

    Vijayvignesh Selvaraj

    2014-06-01

    Full Text Available Wireless Sensor Network (WSN consists of a number of sensor nodes for monitoring the environment. Scenario like floods, volcanic eruptions, earthquakes, tsunamis, avalanches, hailstorms and blizzards causes the sensor nodes to be damaged. In such worst case scenario, the deployed nodes in the monitoring area may split up into several segments. As a result sensor nodes in the network cannot communicate with each other due to partitions. Our algorithm investigates a strategy for restoring such kind of damage through either placement of Relay Nodes (RN’s or repositioning the existing nodes in the network. Unlike traditional schemes like minimum spanning tree, our proposed approach generates a different topology called as spider web. In this approach, both stationary and mobile relay nodes are used. Thus we are making our topology as a hybrid one. Though the numbers of relay nodes are increased, the robust connectivity and the balanced traffic load can be ensured. The validation of the proposed approach has been simulated and verified by QualNet Developer 5.0.2.

  10. The connection-set algebra--a novel formalism for the representation of connectivity structure in neuronal network models.

    Science.gov (United States)

    Djurfeldt, Mikael

    2012-07-01

    The connection-set algebra (CSA) is a novel and general formalism for the description of connectivity in neuronal network models, from small-scale to large-scale structure. The algebra provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. CSA is expressive enough to describe a wide range of connection patterns, including multiple types of random and/or geometrically dependent connectivity, and can serve as a concise notation for network structure in scientific writing. CSA implementations allow for scalable and efficient representation of connectivity in parallel neuronal network simulators and could even allow for avoiding explicit representation of connections in computer memory. The expressiveness of CSA makes prototyping of network structure easy. A C+ + version of the algebra has been implemented and used in a large-scale neuronal network simulation (Djurfeldt et al., IBM J Res Dev 52(1/2):31-42, 2008b) and an implementation in Python has been publicly released.

  11. Partially observed bipartite network analysis to identify predictive connections in transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Woolf Peter J

    2011-05-01

    Full Text Available Abstract Background Messenger RNA expression is regulated by a complex interplay of different regulatory proteins. Unfortunately, directly measuring the individual activity of these regulatory proteins is difficult, leaving us with only the resulting gene expression pattern as a marker for the underlying regulatory network or regulator-gene associations. Furthermore, traditional methods to predict these regulator-gene associations do not define the relative importance of each association, leading to a large number of connections in the global regulatory network that, although true, are not useful. Results Here we present a Bayesian method that identifies which known transcriptional relationships in a regulatory network are consistent with a given body of static gene expression data by eliminating the non-relevant ones. The Partially Observed Bipartite Network (POBN approach developed here is tested using E. coli expression data and a transcriptional regulatory network derived from RegulonDB. When the regulatory network for E. coli was integrated with 266 E. coli gene chip observations, POBN identified 93 out of 570 connections that were either inconsistent or not adequately supported by the expression data. Conclusion POBN provides a systematic way to integrate known transcriptional networks with observed gene expression data to better identify which transcriptional pathways are likely responsible for the observed gene expression pattern.

  12. Catheter ablation of paroxysmal atrial fibrillation in a young patient with a partial anomalous pulmonary venous connection

    Institute of Scientific and Technical Information of China (English)

    HUANG He; YANG Bo; JIANG Hong; WU Gang; HUANG Cong-xin

    2010-01-01

    @@ It has been demonstrated that pulmonary veins (PV)play an important role in the initiation and perpetuation of paroxysmal atrial fibrillation (PAF).1-5 Therefore, PV isolation has become the cornerstone for catheter ablation in the majority of these AF patients.3-5 In addition, ectopic foci in the non-PVs areas, such as superior vena cava(SVC), inferior vena cava (IVC), coronary sinus (CS),ligament of Marshall, have also participated in the initiation of PAF.The ostium isolation or local ablation for these structures was feasible and safe for PAF therapy.6-9 In this report, we describe a young PAF patient with anomalous right superior PV (RSPV) inserting into the SVC-right atrium (RA) junction who underwent successful isolation of all PVs and SVC for PAF guided with the CARTO-Merge technique.

  13. Connected and Leading Disconnected Hadronic Light-by-Light Contribution to the Muon Anomalous Magnetic Moment with a Physical Pion Mass

    Science.gov (United States)

    Blum, Thomas; Christ, Norman; Hayakawa, Masashi; Izubuchi, Taku; Jin, Luchang; Jung, Chulwoo; Lehner, Christoph

    2017-01-01

    We report a lattice QCD calculation of the hadronic light-by-light contribution to the muon anomalous magnetic moment at a physical pion mass. The calculation includes the connected diagrams and the leading, quark-line-disconnected diagrams. We incorporate algorithmic improvements developed in our previous work. The calculation was performed on the 4 83×96 ensemble generated with a physical pion mass and a 5.5 fm spatial extent by the RBC and UKQCD Collaborations using the chiral, domain wall fermion formulation. We find aμHLbL=5.35 (1.35 )×10-10 , where the error is statistical only. The finite-volume and finite lattice-spacing errors could be quite large and are the subject of ongoing research. The omitted disconnected graphs, while expected to give a correction of order 10%, also need to be computed.

  14. Role of mitochondria and network connectivity in intercellular calcium oscillations

    CERN Document Server

    Dokukina, I V; Grachev, E A; Gunton, J D; Dokukina, Irina V.; Gracheva, Maria E.; Grachev, Eugene A.; Gunton, James D.

    2005-01-01

    Mitochondria are large-scale regulators of cytosolic calcium under normal cellular conditions. In this paper we model the complex behavior of mitochondrial calcium during the action of inositol 1,4,5-trisphosphate on a single cell and find results that are in good agreement with recent experimental studies. We also study the influence of the cellular network connectivity on intercellular signalling via gap junction diffusion. We include in our model the dependence of the junctional conductivity on the cytosolic calcium concentrations in adjacent cells. We consider three different mechanisms of calcium wave propagation through gap junctions: via calcium diffusion, inositol 1,4,5-trisphosphate diffusion, and both calcium and inositol 1,4,5-trisphosphate diffusion. We show that inositol 1,4,5-trisphosphate diffusion is the mechanism of calcium wave propagation and that calcium diffusion is the mechanism of synchronization of cytosolic calcium oscillations in adjacent cells. We also study the role of different to...

  15. Link prediction boosted psychiatry disorder classification for functional connectivity network

    Science.gov (United States)

    Li, Weiwei; Mei, Xue; Wang, Hao; Zhou, Yu; Huang, Jiashuang

    2017-02-01

    Functional connectivity network (FCN) is an effective tool in psychiatry disorders classification, and represents cross-correlation of the regional blood oxygenation level dependent signal. However, FCN is often incomplete for suffering from missing and spurious edges. To accurate classify psychiatry disorders and health control with the incomplete FCN, we first `repair' the FCN with link prediction, and then exact the clustering coefficients as features to build a weak classifier for every FCN. Finally, we apply a boosting algorithm to combine these weak classifiers for improving classification accuracy. Our method tested by three datasets of psychiatry disorder, including Alzheimer's Disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. The experimental results show our method not only significantly improves the classification accuracy, but also efficiently reconstructs the incomplete FCN.

  16. Small vessel disease and cognitive impairment: The relevance of central network connections.

    Science.gov (United States)

    Reijmer, Yael D; Fotiadis, Panagiotis; Piantoni, Giovanni; Boulouis, Gregoire; Kelly, Kathleen E; Gurol, Mahmut E; Leemans, Alexander; O'Sullivan, Michael J; Greenberg, Steven M; Viswanathan, Anand

    2016-07-01

    Central brain network connections greatly contribute to overall network efficiency. Here we examined whether small vessel disease (SVD) related white matter alterations in central brain network connections have a greater impact on executive functioning than alterations in non-central brain network connections. Brain networks were reconstructed from diffusion-weighted MRI scans in 72 individuals (75 ± 8 years) with cognitive impairment and SVD on MRI. The centrality of white matter connections in the network was defined using graph theory. The association between the fractional anisotropy (FA) of central versus non-central connections, executive functioning, and markers of SVD was evaluated with linear regression and mediation analysis. Lower FA in central network connections was more strongly associated with impairment in executive functioning than FA in non-central network connections (r = 0.41 vs. r = 0.27; P 50%-10% connections). Higher SVD burden was associated with lower FA in central as well as non-central network connections. However, only central network FA mediated the relationship between white matter hyperintensity volume and executive functioning [change in regression coefficient after mediation (95% CI): -0.15 (-0.35 to -0.02)]. The mediation effect was not observed for FA alterations in non-central network connections [-0.03 (-0.19 to 0.04)]. These findings suggest that the centrality of network connections, and thus their contribution to global network efficiency, appears to be relevant for understanding the relationship between SVD and cognitive impairment. Hum Brain Mapp 37:2446-2454, 2016. © 2016 Wiley Periodicals, Inc.

  17. Design and Implementation of Anycast Services in Ad Hoc Networks Connected to IPv6 Networks

    Directory of Open Access Journals (Sweden)

    Xiaonan Wang

    2010-04-01

    Full Text Available The paper proposes a communication model of implementing an Anycast service in an Ad Hoc network which is connected to IPv6 networks where IPv6 nodes can obtain the Anycast service provided by the Ad hoc network. In this model when an Anycast mobile member in an Ad hoc network moves it can keep the existing communications with its corresponding nodes to continue providing the Anycast services with good quality of service to IPv6 nodes. This model creates a new kind of IPv6 address auto-configuration scheme which does not need the address duplication detection. This paper deeply discusses and analyzes the model and the experimental data prove its validity and efficiency.

  18. Chaos in complex motor networks induced byNewman-Watts small-world connections

    Institute of Scientific and Technical Information of China (English)

    WeiDu-Qu; Luo Xiao-Shu; Zhang Bo

    2011-01-01

    We investigate how dynamical behaviours of complex motor networks depend on the Newman-Watts small-world (NWSW) connections.Network elements are described by the permanent magnet synchronous motor (PMSM) with the values of parameters at which each individual PMSM is stable.It is found that with the increase of connection probability p,the motor in networks becomes periodic and falls into chaotic motion as p further increases.These phenomena imply that NWSW connections can induce and enhance chaos in motor networks.The possible mechanism behind the action of NWSW connections is addressed based on stability theory.

  19. Altered functional and structural connectivity networks in psychogenic non-epileptic seizures.

    Directory of Open Access Journals (Sweden)

    Ju-Rong Ding

    Full Text Available Psychogenic non-epileptic seizures (PNES are paroxysmal behaviors that resemble epileptic seizures but lack abnormal electrical activity. Recent studies suggest aberrant functional connectivity involving specific brain regions in PNES. Little is known, however, about alterations of topological organization of whole-brain functional and structural connectivity networks in PNES. We constructed functional connectivity networks from resting-state functional MRI signal correlations and structural connectivity networks from diffusion tensor imaging tractography in 17 PNES patients and 20 healthy controls. Graph theoretical analysis was employed to compute network properties. Moreover, we investigated the relationship between functional and structural connectivity networks. We found that PNES patients exhibited altered small-worldness in both functional and structural networks and shifted towards a more regular (lattice-like organization, which could serve as a potential imaging biomarker for PNES. In addition, many regional characteristics were altered in structural connectivity network, involving attention, sensorimotor, subcortical and default-mode networks. These regions with altered nodal characteristics likely reflect disease-specific pathophysiology in PNES. Importantly, the coupling strength of functional-structural connectivity was decreased and exhibited high sensitivity and specificity to differentiate PNES patients from healthy controls, suggesting that the decoupling strength of functional-structural connectivity might be an important characteristic reflecting the mechanisms of PNES. This is the first study to explore the altered topological organization in PNES combining functional and structural connectivity networks, providing a new way to understand the pathophysiological mechanisms of PNES.

  20. Introspection-based periodicity awareness model for intermittently connected mobile networks

    NARCIS (Netherlands)

    Türkes, Okan; Scholten, Hans; Havinga, Paul

    2013-01-01

    Recently, context awareness in Intermittently Connected Mobile Networks (ICMNs) has gained popularity in order to discover social similarities among mobile entities. Nevertheless, most of the contextual methods depend on network knowledge obtained with unrealistic scenarios. Mobile entities should h

  1. Synchronous state in a fully connected phase-locked loop network

    Directory of Open Access Journals (Sweden)

    J. R. C. Piqueira

    2006-01-01

    work, an estimation is analytically obtained for the synchronous state in a generic N-node network. Numerical experiments complete the analysis of the fully connected network relating free-running frequencies, node gains, and propagation delays.

  2. Altered resting-state functional connectivity in cortical networks in psychopathy.

    Science.gov (United States)

    Philippi, Carissa L; Pujara, Maia S; Motzkin, Julian C; Newman, Joseph; Kiehl, Kent A; Koenigs, Michael

    2015-04-15

    Psychopathy is a personality disorder characterized by callous antisocial behavior and criminal recidivism. Here we examine whether psychopathy is associated with alterations in functional connectivity in three large-scale cortical networks. Using fMRI in 142 adult male prison inmates, we computed resting-state functional connectivity using seeds from the default mode network, frontoparietal network, and cingulo-opercular network. To determine the specificity of our findings to these cortical networks, we also calculated functional connectivity using seeds from two comparison primary sensory networks: visual and auditory networks. Regression analyses related network connectivity to overall psychopathy scores and to subscores for the "factors" and "facets" of psychopathy: Factor 1, interpersonal/affective traits; Factor 2, lifestyle/antisocial traits; Facet 1, interpersonal; Facet 2, affective; Facet 3, lifestyle; Facet 4, antisocial. Overall psychopathy severity was associated with reduced functional connectivity between lateral parietal cortex and dorsal anterior cingulate cortex. The two factor scores exhibited contrasting relationships with functional connectivity: Factor 1 scores were associated with reduced functional connectivity in the three cortical networks, whereas Factor 2 scores were associated with heightened connectivity in the same networks. This dissociation was evident particularly in the functional connectivity between anterior insula and dorsal anterior cingulate cortex. The facet scores also demonstrated distinct patterns of connectivity. We found no associations between psychopathy scores and functional connectivity within visual or auditory networks. These findings provide novel evidence on the neural correlates of psychopathy and suggest that connectivity between cortical association hubs, such as the dorsal anterior cingulate cortex, may be a neurobiological marker of the disorder.

  3. Predicting healthy older adult's brain age based on structural connectivity networks using artificial neural networks.

    Science.gov (United States)

    Lin, Lan; Jin, Cong; Fu, Zhenrong; Zhang, Baiwen; Bin, Guangyu; Wu, Shuicai

    2016-03-01

    Brain ageing is followed by changes of the connectivity of white matter (WM) and changes of the grey matter (GM) concentration. Neurodegenerative disease is more vulnerable to an accelerated brain ageing, which is associated with prospective cognitive decline and disease severity. Accurate detection of accelerated ageing based on brain network analysis has a great potential for early interventions designed to hinder atypical brain changes. To capture the brain ageing, we proposed a novel computational approach for modeling the 112 normal older subjects (aged 50-79 years) brain age by connectivity analyses of networks of the brain. Our proposed method applied principal component analysis (PCA) to reduce the redundancy in network topological parameters. Back propagation artificial neural network (BPANN) improved by hybrid genetic algorithm (GA) and Levenberg-Marquardt (LM) algorithm is established to model the relation among principal components (PCs) and brain age. The predicted brain age is strongly correlated with chronological age (r=0.8). The model has mean absolute error (MAE) of 4.29 years. Therefore, we believe the method can provide a possible way to quantitatively describe the typical and atypical network organization of human brain and serve as a biomarker for presymptomatic detection of neurodegenerative diseases in the future.

  4. Multimodal functional network connectivity: an EEG-fMRI fusion in network space.

    Directory of Open Access Journals (Sweden)

    Xu Lei

    Full Text Available EEG and fMRI recordings measure the functional activity of multiple coherent networks distributed in the cerebral cortex. Identifying network interaction from the complementary neuroelectric and hemodynamic signals may help to explain the complex relationships between different brain regions. In this paper, multimodal functional network connectivity (mFNC is proposed for the fusion of EEG and fMRI in network space. First, functional networks (FNs are extracted using spatial independent component analysis (ICA in each modality separately. Then the interactions among FNs in each modality are explored by Granger causality analysis (GCA. Finally, fMRI FNs are matched to EEG FNs in the spatial domain using network-based source imaging (NESOI. Investigations of both synthetic and real data demonstrate that mFNC has the potential to reveal the underlying neural networks of each modality separately and in their combination. With mFNC, comprehensive relationships among FNs might be unveiled for the deep exploration of neural activities and metabolic responses in a specific task or neurological state.

  5. Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

    Directory of Open Access Journals (Sweden)

    Christopher E Hart

    2006-12-01

    Full Text Available A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes are explicitly disfavored in one network module (G2, relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of

  6. Impaired default network functional connectivity in autosomal dominant Alzheimer disease

    Science.gov (United States)

    Chhatwal, Jasmeer P.; Schultz, Aaron P.; Johnson, Keith; Benzinger, Tammie L.S.; Jack, Clifford; Ances, Beau M.; Sullivan, Caroline A.; Salloway, Stephen P.; Ringman, John M.; Koeppe, Robert A.; Marcus, Daniel S.; Thompson, Paul; Saykin, Andrew J.; Correia, Stephen; Schofield, Peter R.; Rowe, Christopher C.; Fox, Nick C.; Brickman, Adam M.; Mayeux, Richard; McDade, Eric; Bateman, Randall; Fagan, Anne M.; Goate, Allison M.; Xiong, Chengjie; Buckles, Virginia D.; Morris, John C.

    2013-01-01

    Objective: To investigate default mode network (DMN) functional connectivity MRI (fcMRI) in a large cross-sectional cohort of subjects from families harboring pathogenic presenilin-1 (PSEN1), presenilin-2 (PSEN2), and amyloid precursor protein (APP) mutations participating in the Dominantly Inherited Alzheimer Network. Methods: Eighty-three mutation carriers and 37 asymptomatic noncarriers from the same families underwent fMRI during resting state at 8 centers in the United States, United Kingdom, and Australia. Using group-independent component analysis, fcMRI was compared using mutation status and Clinical Dementia Rating to stratify groups, and related to each participant's estimated years from expected symptom onset (eYO). Results: We observed significantly decreased DMN fcMRI in mutation carriers with increasing Clinical Dementia Rating, most evident in the precuneus/posterior cingulate and parietal cortices (p < 0.001). Comparison of asymptomatic mutation carriers with noncarriers demonstrated decreased fcMRI in the precuneus/posterior cingulate (p = 0.014) and right parietal cortex (p = 0.0016). We observed a significant interaction between mutation carrier status and eYO, with decreases in DMN fcMRI observed as mutation carriers approached and surpassed their eYO. Conclusion: Functional disruption of the DMN occurs early in the course of autosomal dominant Alzheimer disease, beginning before clinically evident symptoms, and worsening with increased impairment. These findings suggest that DMN fcMRI may prove useful as a biomarker across a wide spectrum of disease, and support the feasibility of DMN fcMRI as a secondary endpoint in upcoming multicenter clinical trials in Alzheimer disease. PMID:23884042

  7. Altered directional connectivity between emotion network and motor network in Parkinson's disease with depression.

    Science.gov (United States)

    Liang, Peipeng; Deshpande, Gopikrishna; Zhao, Sinan; Liu, Jiangtao; Hu, Xiaoping; Li, Kuncheng

    2016-07-01

    Depression is common in patients with Parkinson's disease (PD), which can make all the other symptoms of PD much worse. It is thus urgent to differentiate depressed PD (DPD) patients from non-depressed PD (NDPD).The purpose of the present study was to characterize alterations in directional brain connectivity unique to Parkinson's disease with depression, using resting state functional magnetic resonance imaging (rs-fMRI).Sixteen DPD patients, 20 NDPD patients, 17 patients with major depressive disorder (MDD) and 21 healthy control subjects (normal controls [NC]) underwent structural MRI and rs-fMRI scanning. Voxel-based morphometry and directional brain connectivity during resting-state were analyzed. Analysis of variance (ANOVA) and 2-sample t tests were used to compare each pair of groups, using sex, age, education level, structural atrophy, and/or HAMD, unified PD rating scale (UPDRS) as covariates.In contrast to NC, DPD showed significant gray matter (GM) volume abnormalities in some mid-line limbic regions including dorsomedial prefrontal cortex and precuneus, and sub-cortical regions including caudate and cerebellum. Relative to NC and MDD, both DPD and NDPD showed significantly increased directional connectivity from bilateral anterior insula and posterior orbitofrontal cortices to left inferior temporal cortex. As compared with NC, MDD and NDPD, alterations of directional connectivity in DPD were specifically observed in the pathway from bilateral anterior insula and posterior orbitofrontal cortices to right basal ganglia.Resting state directional connectivity alterations were observed between emotion network and motor network in DPD patients after controlling for age, sex, structural atrophy. Given that these alterations are unique to DPD, it may provide a potential differential biomarker for distinguishing DPD from NC, NDPD, and MDD.

  8. Compressive sensing reconstruction of feed-forward connectivity in pulse-coupled nonlinear networks

    Science.gov (United States)

    Barranca, Victor J.; Zhou, Douglas; Cai, David

    2016-06-01

    Utilizing the sparsity ubiquitous in real-world network connectivity, we develop a theoretical framework for efficiently reconstructing sparse feed-forward connections in a pulse-coupled nonlinear network through its output activities. Using only a small ensemble of random inputs, we solve this inverse problem through the compressive sensing theory based on a hidden linear structure intrinsic to the nonlinear network dynamics. The accuracy of the reconstruction is further verified by the fact that complex inputs can be well recovered using the reconstructed connectivity. We expect this Rapid Communication provides a new perspective for understanding the structure-function relationship as well as compressive sensing principle in nonlinear network dynamics.

  9. Compressive sensing reconstruction of feed-forward connectivity in pulse-coupled nonlinear networks.

    Science.gov (United States)

    Barranca, Victor J; Zhou, Douglas; Cai, David

    2016-06-01

    Utilizing the sparsity ubiquitous in real-world network connectivity, we develop a theoretical framework for efficiently reconstructing sparse feed-forward connections in a pulse-coupled nonlinear network through its output activities. Using only a small ensemble of random inputs, we solve this inverse problem through the compressive sensing theory based on a hidden linear structure intrinsic to the nonlinear network dynamics. The accuracy of the reconstruction is further verified by the fact that complex inputs can be well recovered using the reconstructed connectivity. We expect this Rapid Communication provides a new perspective for understanding the structure-function relationship as well as compressive sensing principle in nonlinear network dynamics.

  10. Developmental Changes in Brain Network Hub Connectivity in Late Adolescence.

    Science.gov (United States)

    Baker, Simon T E; Lubman, Dan I; Yücel, Murat; Allen, Nicholas B; Whittle, Sarah; Fulcher, Ben D; Zalesky, Andrew; Fornito, Alex

    2015-06-17

    The human brain undergoes substantial development throughout adolescence and into early adulthood. This maturational process is thought to include the refinement of connectivity between putative connectivity hub regions of the brain, which collectively form a dense core that enhances the functional integration of anatomically distributed, and functionally specialized, neural systems. Here, we used longitudinal diffusion magnetic resonance imaging to characterize changes in connectivity between 80 cortical and subcortical anatomical regions over a 2 year period in 31 adolescents between the ages of 15 and 19 years. Connectome-wide analysis indicated that only a small subset of connections showed evidence of statistically significant developmental change over the study period, with 8% and 6% of connections demonstrating decreased and increased structural connectivity, respectively. Nonetheless, these connections linked 93% and 90% of the 80 regions, respectively, pointing to a selective, yet anatomically distributed pattern of developmental changes that involves most of the brain. Hub regions showed a distinct tendency to be highly connected to each other, indicating robust "rich-club" organization. Moreover, connectivity between hubs was disproportionately influenced by development, such that connectivity between subcortical hubs decreased over time, whereas frontal-subcortical and frontal-parietal hub-hub connectivity increased over time. These findings suggest that late adolescence is characterized by selective, yet significant remodeling of hub-hub connectivity, with the topological organization of hubs shifting emphasis from subcortical hubs in favor of an increasingly prominent role for frontal hub regions.

  11. Photovoltaic power, lithium batteries and network connection; Energia fotovoltaica, baterias de litio e conexao a rede

    Energy Technology Data Exchange (ETDEWEB)

    Schmiegel, A.U.; Koch, K.; Meissner, A.; Knaup, P. [Voltwerk Electronics (Germany); Jehoulet, C.; Schuh, H. [Saft Batteries (France); Landau, M.; Braun, M.; Bundenbender, K.; Geipel, R.; Vachette, C. [Fraunhofer IWES (Germany); Sauer, D.-U.; Magnor, D. [RWTH Aachen University (Germany). Institute for Solar Energy Systems - ISEA; Marcel, J.-C. [Tenosol (France)

    2011-11-15

    The Sun-ion, the system described in this article, combines storage technology based on the lithium ions with the high efficiency photovoltaic inverters, and supports two philosophies for personal use: off-grid, where the loads are directly connected to the inverter; and connected to the network, which makes up their own consumption when the load balancing in the network connection is zero. Performance measurements demonstrate the feasibility of the concept.

  12. Network topology and functional connectivity disturbances precede the onset of Huntington's disease.

    Science.gov (United States)

    Harrington, Deborah L; Rubinov, Mikail; Durgerian, Sally; Mourany, Lyla; Reece, Christine; Koenig, Katherine; Bullmore, Ed; Long, Jeffrey D; Paulsen, Jane S; Rao, Stephen M

    2015-08-01

    Cognitive, motor and psychiatric changes in prodromal Huntington's disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington's disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls (n = 16) and prodromal Huntington's disease individuals (n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease

  13. The anatomical distance of functional connections predicts brain network topology in health and schizophrenia.

    Science.gov (United States)

    Alexander-Bloch, Aaron F; Vértes, Petra E; Stidd, Reva; Lalonde, François; Clasen, Liv; Rapoport, Judith; Giedd, Jay; Bullmore, Edward T; Gogtay, Nitin

    2013-01-01

    The human brain is a topologically complex network embedded in anatomical space. Here, we systematically explored relationships between functional connectivity, complex network topology, and anatomical (Euclidean) distance between connected brain regions, in the resting-state functional magnetic resonance imaging brain networks of 20 healthy volunteers and 19 patients with childhood-onset schizophrenia (COS). Normal between-subject differences in average distance of connected edges in brain graphs were strongly associated with variation in topological properties of functional networks. In addition, a club or subset of connector hubs was identified, in lateral temporal, parietal, dorsal prefrontal, and medial prefrontal/cingulate cortical regions. In COS, there was reduced strength of functional connectivity over short distances especially, and therefore, global mean connection distance of thresholded graphs was significantly greater than normal. As predicted from relationships between spatial and topological properties of normal networks, this disorder-related proportional increase in connection distance was associated with reduced clustering and modularity and increased global efficiency of COS networks. Between-group differences in connection distance were localized specifically to connector hubs of multimodal association cortex. In relation to the neurodevelopmental pathogenesis of schizophrenia, we argue that the data are consistent with the interpretation that spatial and topological disturbances of functional network organization could arise from excessive "pruning" of short-distance functional connections in schizophrenia.

  14. Impact of connected vehicle guidance information on network-wide average travel time

    Directory of Open Access Journals (Sweden)

    Jiangfeng Wang

    2016-12-01

    Full Text Available With the emergence of connected vehicle technologies, the potential positive impact of connected vehicle guidance on mobility has become a research hotspot by data exchange among vehicles, infrastructure, and mobile devices. This study is focused on micro-modeling and quantitatively evaluating the impact of connected vehicle guidance on network-wide travel time by introducing various affecting factors. To evaluate the benefits of connected vehicle guidance, a simulation architecture based on one engine is proposed representing the connected vehicle–enabled virtual world, and connected vehicle route guidance scenario is established through the development of communication agent and intelligent transportation systems agents using connected vehicle application programming interface considering the communication properties, such as path loss and transmission power. The impact of connected vehicle guidance on network-wide travel time is analyzed by comparing with non-connected vehicle guidance in response to different market penetration rate, following rate, and congestion level. The simulation results explore that average network-wide travel time in connected vehicle guidance shows a significant reduction versus that in non–connected vehicle guidance. Average network-wide travel time in connected vehicle guidance have an increase of 42.23% comparing to that in non-connected vehicle guidance, and average travel time variability (represented by the coefficient of variance increases as the travel time increases. Other vital findings include that higher penetration rate and following rate generate bigger savings of average network-wide travel time. The savings of average network-wide travel time increase from 17% to 38% according to different congestion levels, and savings of average travel time in more serious congestion have a more obvious improvement for the same penetration rate or following rate.

  15. The Complexity of Recognition in the Single-Layered PLN Network with Feedback Connections

    Institute of Scientific and Technical Information of China (English)

    1993-01-01

    Regarding a single-layered PLN network with feedback connections as an associative memory network,the complexity of recognitions is discussed.We have the main result:if the size of the network N is m,then the complexity of recognition is an exponential function of m.The necessary condition under which the complexity of recognition is polynomial is given.

  16. Making Connections: Using Social Network Analysis for Program Evaluation. Issue Brief. Number 1

    Science.gov (United States)

    Honeycutt, Todd

    2009-01-01

    Social network analysis (SNA) is a methodological approach to measuring and mapping relationships. It can be used to study whole networks, all of the ties within a defined group, or connections that individuals have in their personal communities. The resulting graph-based structures illustrate the composition and effectiveness of networks on a…

  17. Brain network analysis of EEG functional connectivity during imagery hand movements.

    Science.gov (United States)

    Demuru, Matteo; Fara, Francesca; Fraschini, Matteo

    2013-12-01

    The characterization of human neural activity during imaginary movement tasks represent an important challenge in order to develop effective applications that allow the control of a machine. Yet methods based on brain network analysis of functional connectivity have been scarcely investigated. As a result we use graph theoretic methods to investigate the functional connectivity and brain network measures in order to characterize imagery hand movements in a set of healthy subjects. The results of the present study show that functional connectivity analysis and minimum spanning tree (MST) parameters allow to successfully discriminate between imagery hand movements (both right and left) and resting state conditions. In conclusion, this paper shows that brain network analysis of EEG functional connectivity could represent an efficient alternative to more classical local activation based approaches. Furthermore, it also suggests the shift toward methods based on the characterization of a limited set of fundamental functional connections that disclose salient network topological features.

  18. Volitional regulation of emotions produces distributed alterations in connectivity between visual, attention control, and default networks.

    Science.gov (United States)

    Sripada, Chandra; Angstadt, Michael; Kessler, Daniel; Phan, K Luan; Liberzon, Israel; Evans, Gary W; Welsh, Robert C; Kim, Pilyoung; Swain, James E

    2014-04-01

    The ability to volitionally regulate emotions is critical to health and well-being. While patterns of neural activation during emotion regulation have been well characterized, patterns of connectivity between regions remain less explored. It is increasingly recognized that the human brain is organized into large-scale intrinsic connectivity networks (ICNs) whose interrelationships are altered in characteristic ways during psychological tasks. In this fMRI study of 54 healthy individuals, we investigated alterations in connectivity within and between ICNs produced by the emotion regulation strategy of reappraisal. In order to gain a comprehensive picture of connectivity changes, we utilized connectomic psychophysiological interactions (PPI), a whole-brain generalization of standard single-seed PPI methods. In particular, we quantified PPI connectivity pair-wise across 837 ROIs placed throughout the cortex. We found that compared to maintaining one's emotional responses, engaging in reappraisal produced robust and distributed alterations in functional connections involving visual, dorsal attention, frontoparietal, and default networks. Visual network in particular increased connectivity with multiple ICNs including dorsal attention and default networks. We interpret these findings in terms of the role of these networks in mediating critical constituent processes in emotion regulation, including visual processing, stimulus salience, attention control, and interpretation and contextualization of stimuli. Our results add a new network perspective to our understanding of the neural underpinnings of emotion regulation, and highlight that connectomic methods can play a valuable role in comprehensively investigating modulation of connectivity across task conditions.

  19. Optimal distribution of reliability for a large network based on connectivity

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    It is a non-polynomial complexity problem to calculate connectivity of the complex network. When the system reliability cannot be expressed as a function of el-ement reliability, we have to apply some heuristic methods for optimization based on connectivity of the network. The calculation structure of connectivity of complex net-work is analyzed in the paper. The coefficient matrixes of Taylor second order expansion of the system connectivity is generated based on the calculation structure of connectivity of complex network. An optimal schedule is achieved based on genetic algorithms (GA). Fitness of seeds is calculated using the Taylor expansion function of system connectiv-ity. Precise connectivity of the optimal schedule and the Taylor expansion function of system conncctivity can be achieved by the approved Minty method or the recursive de-composition algorithm. When error between approximate connectivity and the precise value exceeds the assigned value, the optimization process is continued using GA, and the Taylor function of system connectivity needs to be renewed. The optimization process is called iterative GA. Iterative GA can be used in the large network for optimal reliability attribution. One temporary optimal result will be generated every time in the iteration process. These temporary optimal results approach the real optimal results. They can be regarded as a group of approximate optimal results useful in the real project.

  20. Temporal Dynamics of Connectivity and Epidemic Properties of Growing Networks

    CERN Document Server

    Fotouhi, Babak

    2015-01-01

    Traditional mathematical models of epidemic disease had for decades conventionally considered static structure for contacts. Recently, an upsurge of theoretical inquiry has strived towards rendering the models more realistic by incorporating the temporal aspects of networks of contacts, societal and online, that are of interest in the study of epidemics (and other similar diffusion processes). However, temporal dynamics have predominantly focused on link fluctuations and nodal activities, and less attention has been paid to the growth of the underlying network. Many real networks grow: online networks are evidently in constant growth, and societal networks can grow due to migration flux and reproduction. The effect of network growth on the epidemic properties of networks is hitherto unknown---mainly due to the predominant focus of the network growth literature on the so-called steady-state. This paper takes a step towards alleviating this gap. We analytically study the degree dynamics of a given arbitrary net...

  1. How connected is the global sovereign credit risk network?

    OpenAIRE

    Bostancı, Görkem; Yılmaz, Kamil

    2015-01-01

    We apply the Diebold-Yilmaz connectedness index methodology on sovereign credit default swaps (SCDSs) to estimate the network structure of global sovereign credit risk. In particular, using the elastic net estimation method, we separately estimate networks of daily SCDS returns and volatilities for 38 countries between 2009 and 2014. Our results reveal striking differences be- tween the network structures of returns and volatilities. In SCDS return networks, developing and developed countries...

  2. Connection Management and Recovery Strategies under Epidemic Network Failures in Optical Transport Networks

    DEFF Research Database (Denmark)

    Fagertun, Anna Manolova; Ruepp, Sarah Renée

    2014-01-01

    The current trend in deploying automatic control plane solutions for increased flexibility in the optical transport layer leads to numerous advantages for both the operators and the customers, but also pose challenges related to the stability of the network and its ability to operate in a robust ...... of their transport infrastructures. Applying proactive methods for avoiding areas where epidemic failures spread results in 50% less connections requiring recovery, which translates in improved quality of service to customers.......The current trend in deploying automatic control plane solutions for increased flexibility in the optical transport layer leads to numerous advantages for both the operators and the customers, but also pose challenges related to the stability of the network and its ability to operate in a robust......-Infected-Disabled epidemic failure spreading model and look into possible tradeoffs between resiliency and resource efficiency. Via extensive simulations we show that there exist a clear tradeoff between policy performance and network resource consumption, which must be addressed by network operators for improved robustness...

  3. Local Area Networks: Vehicles for Connecting and Sharing Information.

    Science.gov (United States)

    Lipman, Art

    1993-01-01

    Describes local area networks (LANs) and discusses advantages of their use in schools for students and teachers, including networking in labs, media centers, and classrooms. Roles of the network supervisor and/or technician are explained, including making decisions about the rights of users and instruction and assistance. (LRW)

  4. Approximating natural connectivity of scale-free networks based on largest eigenvalue

    Science.gov (United States)

    Tan, S.-Y.; Wu, J.; Li, M.-J.; Lu, X.

    2016-06-01

    It has been recently proposed that natural connectivity can be used to efficiently characterize the robustness of complex networks. The natural connectivity has an intuitive physical meaning and a simple mathematical formulation, which corresponds to an average eigenvalue calculated from the graph spectrum. However, as a network model close to the real-world system that widely exists, the scale-free network is found difficult to obtain its spectrum analytically. In this article, we investigate the approximation of natural connectivity based on the largest eigenvalue in both random and correlated scale-free networks. It is demonstrated that the natural connectivity of scale-free networks can be dominated by the largest eigenvalue, which can be expressed asymptotically and analytically to approximate natural connectivity with small errors. Then we show that the natural connectivity of random scale-free networks increases linearly with the average degree given the scaling exponent and decreases monotonically with the scaling exponent given the average degree. Moreover, it is found that, given the degree distribution, the more assortative a scale-free network is, the more robust it is. Experiments in real networks validate our methods and results.

  5. A parsimonious statistical method to detect groupwise differentially expressed functional connectivity networks.

    Science.gov (United States)

    Chen, Shuo; Kang, Jian; Xing, Yishi; Wang, Guoqing

    2015-12-01

    Group-level functional connectivity analyses often aim to detect the altered connectivity patterns between subgroups with different clinical or psychological experimental conditions, for example, comparing cases and healthy controls. We present a new statistical method to detect differentially expressed connectivity networks with significantly improved power and lower false-positive rates. The goal of our method was to capture most differentially expressed connections within networks of constrained numbers of brain regions (by the rule of parsimony). By virtue of parsimony, the false-positive individual connectivity edges within a network are effectively reduced, whereas the informative (differentially expressed) edges are allowed to borrow strength from each other to increase the overall power of the network. We develop a test statistic for each network in light of combinatorics graph theory, and provide p-values for the networks (in the weak sense) by using permutation test with multiple-testing adjustment. We validate and compare this new approach with existing methods, including false discovery rate and network-based statistic, via simulation studies and a resting-state functional magnetic resonance imaging case-control study. The results indicate that our method can identify differentially expressed connectivity networks, whereas existing methods are limited.

  6. Single pulse responses in cultured neuronal networks to describe connectivity

    NARCIS (Netherlands)

    Feber, le Joost; Corner, Michael

    2011-01-01

    Synaptic connections between neurons play a crucial role in cognitive processes like learning and memory. In recent work we developed a method, using conditional firing probability (CFP analysis), to estimate functional connectivity in terms of strength and latency, and here we further explored on t

  7. Network burst dynamics under heterogeneous cholinergic modulation of neural firing properties and heterogeneous synaptic connectivity.

    Science.gov (United States)

    Knudstrup, Scott; Zochowski, Michal; Booth, Victoria

    2016-05-01

    The characteristics of neural network activity depend on intrinsic neural properties and synaptic connectivity in the network. In brain networks, both of these properties are critically affected by the type and levels of neuromodulators present. The expression of many of the most powerful neuromodulators, including acetylcholine (ACh), varies tonically and phasically with behavioural state, leading to dynamic, heterogeneous changes in intrinsic neural properties and synaptic connectivity properties. Namely, ACh significantly alters neural firing properties as measured by the phase response curve in a manner that has been shown to alter the propensity for network synchronization. The aim of this simulation study was to build an understanding of how heterogeneity in cholinergic modulation of neural firing properties and heterogeneity in synaptic connectivity affect the initiation and maintenance of synchronous network bursting in excitatory networks. We show that cells that display different levels of ACh modulation have differential roles in generating network activity: weakly modulated cells are necessary for burst initiation and provide synchronizing drive to the rest of the network, whereas strongly modulated cells provide the overall activity level necessary to sustain burst firing. By applying several quantitative measures of network activity, we further show that the existence of network bursting and its characteristics, such as burst duration and intraburst synchrony, are dependent on the fraction of cell types providing the synaptic connections in the network. These results suggest mechanisms underlying ACh modulation of brain oscillations and the modulation of seizure activity during sleep states.

  8. Transition to chaos in random networks with cell-type-specific connectivity

    Science.gov (United States)

    Aljadeff, Johnatan; Stern, Merav; Sharpee, Tatyana

    2015-01-01

    In neural circuits, statistical connectivity rules strongly depend on cell-type identity. We study dynamics of neural networks with cell-type specific connectivity by extending the dynamic mean field method, and find that these networks exhibit a phase transition between silent and chaotic activity. By analyzing the locus of this transition, we derive a new result in random matrix theory: the spectral radius of a random connectivity matrix with block-structured variances. We apply our results to show how a small group of hyper-excitable neurons within the network can significantly increase the network’s computational capacity by bringing it into the chaotic regime. PMID:25768781

  9. Using LSTM recurrent neural networks for detecting anomalous behavior of LHC superconducting magnets

    CERN Document Server

    Wielgosz, Maciej; Mertik, Matej

    2016-01-01

    The superconducting LHC magnets are coupled with an electronic monitoring system which records and analyses voltage time series reflecting their performance. A currently used system is based on a range of preprogrammed triggers which launches protection procedures when a misbehavior of the magnets is detected. All the procedures used in the protection equipment were designed and implemented according to known working scenarios of the system and are updated and monitored by human operators. This paper proposes a novel approach to monitoring and fault protection of the Large Hadron Collider (LHC) superconducting magnets which employs state-of-the-art Deep Learning algorithms. Consequently, the authors of the paper decided to examine the performance of LSTM recurrent neural networks for anomaly detection in voltage time series of the magnets. In order to address this challenging task different network architectures and hyper-parameters were used to achieve the best possible performance of the solution. The regre...

  10. Community detection in weighted brain connectivity networks beyond the resolution limit

    CERN Document Server

    Nicolini, Carlo; Bifone, Angelo

    2016-01-01

    Graph theory provides a powerful framework to investigate brain functional connectivity networks and their modular organization. However, most graph-based methods suffer from a fundamental resolution limit that may have affected previous studies and prevented detection of modules, or communities, that are smaller than a specific scale. Surprise, a resolution-limit-free function rooted in discrete probability theory, has been recently introduced and applied to brain networks, revealing a wide size-distribution of functional modules, in contrast with many previous reports. However, the use of Surprise is limited to binary networks, while brain networks are intrinsically weighted, reflecting a continuous distribution of connectivity strengths between different brain regions. Here, we propose Asymptotical Surprise, a continuous version of Surprise, for the study of weighted brain connectivity networks, and validate this approach in synthetic networks endowed with a ground-truth modular structure. We compare Asymp...

  11. Restorability on 3-connected WDM Networks Under Single and Dual Physical Link Failures

    DEFF Research Database (Denmark)

    Gutierrez Lopez, Jose Manuel; Jensen, Michael; Riaz, Tahir

    2013-01-01

    This work studies the influence the network interconnection has over restoration techniques. The way physical links are distributed to interconnect network nodes has a great impact on parameters such as path distances when failures occur and restoration is applied. The work focuses on single...... and dual physical link failures restorability on WDM transport networks. This failure scenarios are tested over several 3-connected topologies, and studied in graph theory and network planning terms. In connection with the graphs, the resulting hop path distances and lengths are evaluated. In relation...... to network planning, the trade-off network length vs. performance of the different topological options is studied. The results show how 3-connected graphs could provide a reasonable trade-off between costs, link failure rates, and restored path parameters....

  12. Age-Related Increases in Long-Range Connectivity in Fetal Functional Neural Connectivity Networks In Utero

    Science.gov (United States)

    Thomason, Moriah E.; Grove, Lauren E.; Lozon, Tim A.; Vila, Angela M.; Ye, Yongquan; Nye, Matthew J.; Manning, Janessa H.; Pappas, Athina; Hernandez-Andrade, Edgar; Yeo, Lami; Mody, Swati; Berman, Susan; Hassan, Sonia S.; Romero, Roberto

    2015-01-01

    Formation of operational neural networks is one of the most significant accomplishments of human fetal brain growth. Recent advances in functional magnetic resonance imaging (fMRI) have made it possible to obtain information about brain function during fetal development. Specifically, resting-state fMRI and novel signal covariation approaches have opened up a new avenue for non-invasive assessment of neural functional connectivity (FC) before birth. Early studies in this area have unearthed new insights about principles of prenatal brain function. However, very little is known about the emergence and maturation of neural networks during fetal life. Here, we obtained cross-sectional rs-fMRI data from 39 fetuses between 24 and 38 weeks postconceptual age to examine patterns of connectivity across ten neural FC networks. We identified primitive forms of motor, visual, default mode, thalamic, and temporal networks in the human fetal brain. We discovered the first evidence of increased long-range, cerebral-cerebellar, cortical-subcortical, and intra-hemispheric FC with advancing fetal age. Continued aggregation of data about fundamental neural connectivity systems in utero is essential to establishing principles of connectomics at the beginning of human life. Normative data provides a vital context against which to compare instances of abnormal neurobiological development. PMID:25284273

  13. Age-related increases in long-range connectivity in fetal functional neural connectivity networks in utero

    Directory of Open Access Journals (Sweden)

    Moriah E. Thomason

    2015-02-01

    Full Text Available Formation of operational neural networks is one of the most significant accomplishments of human fetal brain growth. Recent advances in functional magnetic resonance imaging (fMRI have made it possible to obtain information about brain function during fetal development. Specifically, resting-state fMRI and novel signal covariation approaches have opened up a new avenue for non-invasive assessment of neural functional connectivity (FC before birth. Early studies in this area have unearthed new insights about principles of prenatal brain function. However, very little is known about the emergence and maturation of neural networks during fetal life. Here, we obtained cross-sectional rs-fMRI data from 39 fetuses between 24 and 38 weeks postconceptual age to examine patterns of connectivity across ten neural FC networks. We identified primitive forms of motor, visual, default mode, thalamic, and temporal networks in the human fetal brain. We discovered the first evidence of increased long-range, cerebral-cerebellar, cortical-subcortical, and intra-hemispheric FC with advancing fetal age. Continued aggregation of data about fundamental neural connectivity systems in utero is essential to establishing principles of connectomics at the beginning of human life. Normative data provides a vital context against which to compare instances of abnormal neurobiological development.

  14. Genomic connectivity networks based on the BrainSpan atlas of the developing human brain

    Science.gov (United States)

    Mahfouz, Ahmed; Ziats, Mark N.; Rennert, Owen M.; Lelieveldt, Boudewijn P. F.; Reinders, Marcel J. T.

    2014-03-01

    The human brain comprises systems of networks that span the molecular, cellular, anatomic and functional levels. Molecular studies of the developing brain have focused on elucidating networks among gene products that may drive cellular brain development by functioning together in biological pathways. On the other hand, studies of the brain connectome attempt to determine how anatomically distinct brain regions are connected to each other, either anatomically (diffusion tensor imaging) or functionally (functional MRI and EEG), and how they change over development. A global examination of the relationship between gene expression and connectivity in the developing human brain is necessary to understand how the genetic signature of different brain regions instructs connections to other regions. Furthermore, analyzing the development of connectivity networks based on the spatio-temporal dynamics of gene expression provides a new insight into the effect of neurodevelopmental disease genes on brain networks. In this work, we construct connectivity networks between brain regions based on the similarity of their gene expression signature, termed "Genomic Connectivity Networks" (GCNs). Genomic connectivity networks were constructed using data from the BrainSpan Transcriptional Atlas of the Developing Human Brain. Our goal was to understand how the genetic signatures of anatomically distinct brain regions relate to each other across development. We assessed the neurodevelopmental changes in connectivity patterns of brain regions when networks were constructed with genes implicated in the neurodevelopmental disorder autism (autism spectrum disorder; ASD). Using graph theory metrics to characterize the GCNs, we show that ASD-GCNs are relatively less connected later in development with the cerebellum showing a very distinct expression of ASD-associated genes compared to other brain regions.

  15. 星型网络的额外连通度%Extra connectivity of star networks

    Institute of Scientific and Technical Information of China (English)

    谢春萍; 梁家荣

    2015-01-01

    The extra-connectivity is more accurate and more significative than the connectivity in measuring the reliability of interconnection networks. Star networks are regarded as one of important candidates of network models in large-scale processor systems. In this paper, the problem of 2-extra-connectivity on star networks is studied, the 2-extra vertex connectivity and 2-extra edge connectivity of star network are obtained, which are for . Analysis shows that 2-extra connectivity is much superior to the traditional connectivity in evaluating the reliability of star networks.%在评价网络可靠性方面,额外连通度比传统连通度更为精确、更具有实际意义.星型互连网络Sn是重要的大规模处理器系统网络模型之一.研究了星型互连网络Sn的2-额外连通度问题,证明了当n≥6时,κ2(Sn)=λ2(Sn)=3n-7.具体说明了对星型网络的可靠性评价时,2-额外连通度比传统连通度更具有优越性.

  16. Geometry of River Networks; 3, Characterization of Component Connectivity

    CERN Document Server

    Dodds, P S; Dodds, Peter Sheridan; Rothman, Daniel H.

    2000-01-01

    River networks serve as a paradigmatic example of all branching networks. Essential to understanding the overall structure of river networks is a knowledge of their detailed architecture. Here we show that sub-branches are distributed exponentially in size and that they are randomly distributed in space, thereby completely characterizing the most basic level of river network description. Specifically, an averaged view of network architecture is first provided by a proposed self-similarity statement about the scaling of drainage density, a local measure of stream concentration. This scaling of drainage density is shown to imply Tokunaga's law, a description of the scaling of side branch abundance along a given stream, as well as a scaling law for stream lengths. This establishes the scaling of the length scale associated with drainage density as the basic signature of self-similarity in river networks. We then consider fluctuations in drainage density and consequently the numbers of side branches. Data is anal...

  17. Effective connectivity of hippocampal neural network and its alteration in Mg2+-free epilepsy model.

    Science.gov (United States)

    Gong, Xin-Wei; Li, Jing-Bo; Lu, Qin-Chi; Liang, Pei-Ji; Zhang, Pu-Ming

    2014-01-01

    Understanding the connectivity of the brain neural network and its evolution in epileptiform discharges is meaningful in the epilepsy researches and treatments. In the present study, epileptiform discharges were induced in rat hippocampal slices perfused with Mg2+-free artificial cerebrospinal fluid. The effective connectivity of the hippocampal neural network was studied by comparing the normal and epileptiform discharges recorded by a microelectrode array. The neural network connectivity was constructed by using partial directed coherence and analyzed by graph theory. The transition of the hippocampal network topology from control to epileptiform discharges was demonstrated. Firstly, differences existed in both the averaged in- and out-degree between nodes in the pyramidal cell layer and the granule cell layer, which indicated an information flow from the pyramidal cell layer to the granule cell layer during epileptiform discharges, whereas no consistent information flow was observed in control. Secondly, the neural network showed different small-worldness in the early, middle and late stages of the epileptiform discharges, whereas the control network did not show the small-world property. Thirdly, the network connectivity began to change earlier than the appearance of epileptiform discharges and lasted several seconds after the epileptiform discharges disappeared. These results revealed the important network bases underlying the transition from normal to epileptiform discharges in hippocampal slices. Additionally, this work indicated that the network analysis might provide a useful tool to evaluate the neural network and help to improve the prediction of seizures.

  18. Effective Suppression of Pathological Synchronization in Cortical Networks by Highly Heterogeneous Distribution of Inhibitory Connections

    Science.gov (United States)

    Kada, Hisashi; Teramae, Jun-Nosuke; Tokuda, Isao T.

    2016-01-01

    Even without external random input, cortical networks in vivo sustain asynchronous irregular firing with low firing rate. In addition to detailed balance between excitatory and inhibitory activities, recent theoretical studies have revealed that another feature commonly observed in cortical networks, i.e., long-tailed distribution of excitatory synapses implying coexistence of many weak and a few extremely strong excitatory synapses, plays an essential role in realizing the self-sustained activity in recurrent networks of biologically plausible spiking neurons. The previous studies, however, have not considered highly non-random features of the synaptic connectivity, namely, bidirectional connections between cortical neurons are more common than expected by chance and strengths of synapses are positively correlated between pre- and postsynaptic neurons. The positive correlation of synaptic connections may destabilize asynchronous activity of networks with the long-tailed synaptic distribution and induce pathological synchronized firing among neurons. It remains unclear how the cortical network avoids such pathological synchronization. Here, we demonstrate that introduction of the correlated connections indeed gives rise to synchronized firings in a cortical network model with the long-tailed distribution. By using a simplified feed-forward network model of spiking neurons, we clarify the underlying mechanism of the synchronization. We then show that the synchronization can be efficiently suppressed by highly heterogeneous distribution, typically a lognormal distribution, of inhibitory-to-excitatory connection strengths in a recurrent network model of cortical neurons. PMID:27803659

  19. Knotty-centrality: finding the connective core of a complex network.

    Directory of Open Access Journals (Sweden)

    Murray Shanahan

    Full Text Available A network measure called knotty-centrality is defined that quantifies the extent to which a given subset of a graph's nodes constitutes a densely intra-connected topologically central connective core. Using this measure, the knotty centre of a network is defined as a sub-graph with maximal knotty-centrality. A heuristic algorithm for finding subsets of a network with high knotty-centrality is presented, and this is applied to previously published brain structural connectivity data for the cat and the human, as well as to a number of other networks. The cognitive implications of possessing a connective core with high knotty-centrality are briefly discussed.

  20. On the Connectivity of Wireless Network Systems and an Application in Teacher-Student Interactive Platforms

    Directory of Open Access Journals (Sweden)

    Xun Ge

    2014-01-01

    Full Text Available A wireless network system is a pair (U;B, where B is a family of some base stations and U is a set of their users. To investigate the connectivity of wireless network systems, this paper takes covering approximation spaces as mathematical models of wireless network systems. With the help of covering approximation operators, this paper characterizes the connectivity of covering approximation spaces by their definable subsets. Furthermore, it is obtained that a wireless network system is connected if and only if the relevant covering approximation space has no nonempty definable proper subset. As an application of this result, the connectivity of a teacher-student interactive platform is discussed, which is established in the School of Mathematical Sciences of Soochow University. This application further demonstrates the usefulness of rough set theory in pedagogy and makes it possible to research education by logical methods and mathematical methods.

  1. Pulmonary uptake of thallium-201 in patients with congenital heart disease; Comparison between total anomalous pulmonary venous connection and tetralogy of Fallot

    Energy Technology Data Exchange (ETDEWEB)

    Kohata, Tohru; Ono, Yasuo; Iwatani, Hajime; Fukushima, Hideki; Kamiya, Tetsuro; Yagihara, Toshikatsu; Nishimura, Tsunehiko; Takamiya, Makoto (National Cardiovascular Center, Suita, Osaka (Japan))

    1992-01-01

    To evaluate the pulmonary extravascular space in patients with congenital heart disease, lung uptake of Tl-201 was quantitatively studied. Patients' diseases consisted of total anomalous pulmonary venous connection (TAPVC)--supracardiac (I), paracardiac (II) and infracardiac (III) types--, tetralogy of Fallot (T/F), ventricular septal defect (VSD), and patent ductus arteriosus (PDA). Tl-201 imaging was performed before operation and in the early and late stages after operation. Twenty-five other patients with arrhythemias or a history of Kawasaki disease without perfusion defects served as controls. Lung uptake of Tl-201 was analyzed with a computer using the anterior image of the chest, and the averge count ratio of the right lung (P) to the left ventricular wall (LV) was calculated. P/LV values were compared between the patients before and after operation, and differences in anatomical types in TAPVC were also evaluated. In TAPVC, P/LV values decreased gradually after operation, but were significantly higher than those of controls even in the late stage. In the late stage after operation, type I TAPVC had significantly higher P/LV values than those of type-II. In T/F, the P/LV values were significantly higher after operation, even in the late stage, than before operation. In the VSD or PDA group, the P/LV value returned to normal after operation and was significantly lower than that before operation. In conclusion, TAPVC patients was considered to have a larger pulmonary extravascular space even in the late stage after operation, suggesting a sign of pulmonary congestion due to intrapulmonary vascular damage in utero. In T/F, scanty pulmonary vascular beds before operation were perfused with increased pulmonary blood flow after operation. Therefore, postoperative increases in pulmonary blood flow may be responsible for the increased pulmonary extravascular space. (N.K.).

  2. Connecting core percolation and controllability of complex networks.

    Science.gov (United States)

    Jia, Tao; Pósfai, Márton

    2014-06-20

    Core percolation is a fundamental structural transition in complex networks related to a wide range of important problems. Recent advances have provided us an analytical framework of core percolation in uncorrelated random networks with arbitrary degree distributions. Here we apply the tools in analysis of network controllability. We confirm analytically that the emergence of the bifurcation in control coincides with the formation of the core and the structure of the core determines the control mode of the network. We also derive the analytical expression related to the controllability robustness by extending the deduction in core percolation. These findings help us better understand the interesting interplay between the structural and dynamical properties of complex networks.

  3. MODELING OF SYMMETRIC THREE-PHASE ASYNCHRONOUS ELECTRIC MOTOR IN ASYMMETRIC CONNECTION TO NETWORK

    Directory of Open Access Journals (Sweden)

    V. I. Lukovnikov

    2005-01-01

    Full Text Available The paper shows how to solve the problem concerning reveal of changes in mathematical models and electric parameters of symmetric three-phase short-circuited asynchronous electric motors in case of their connection to single- or two-phase network in comparison with their connection to three-phase network. The uniform methodological approach permitting to generalize the known data and receive new results is offered in the paper.

  4. Network-based analysis reveals functional connectivity related to internet addiction tendency

    OpenAIRE

    Tanya eWen; Shulan eHsieh

    2016-01-01

    IntroductionPreoccupation and compulsive use of the internet can have negative psychological effects, such that it is increasingly being recognized as a mental disorder. The present study employed network-based statistics to explore how whole-brain functional connections at rest is related to the extent of individual’s level of internet addiction, indexed by a self-rated questionnaire. We identified two topologically significant networks, one with connections that are positively correlated wi...

  5. Heterogeneity of Global and Local Connectivity in Spatial Network Structures of World Migration

    OpenAIRE

    2016-01-01

    We examine world migration as a social-spatial network of countries connected via movements of people. We assess how multilateral migratory relationships at global, regional, and local scales coexist ("glocalization"), divide ("polarization"), or form an interconnected global system ("globalization"). To do this, we decompose the world migration network (WMN) into communities---sets of countries with denser than expected migration connections---and characterize their pattern of local (i.e., i...

  6. Abnormal Connectional Fingerprint in Schizophrenia: A Novel Network Analysis of Diffusion Tensor Imaging Data.

    Science.gov (United States)

    Edwin Thanarajah, Sharmili; Han, Cheol E; Rotarska-Jagiela, Anna; Singer, Wolf; Deichmann, Ralf; Maurer, Konrad; Kaiser, Marcus; Uhlhaas, Peter J

    2016-01-01

    The graph theoretical analysis of structural magnetic resonance imaging (MRI) data has received a great deal of interest in recent years to characterize the organizational principles of brain networks and their alterations in psychiatric disorders, such as schizophrenia. However, the characterization of networks in clinical populations can be challenging, since the comparison of connectivity between groups is influenced by several factors, such as the overall number of connections and the structural abnormalities of the seed regions. To overcome these limitations, the current study employed the whole-brain analysis of connectional fingerprints in diffusion tensor imaging data obtained at 3 T of chronic schizophrenia patients (n = 16) and healthy, age-matched control participants (n = 17). Probabilistic tractography was performed to quantify the connectivity of 110 brain areas. The connectional fingerprint of a brain area represents the set of relative connection probabilities to all its target areas and is, hence, less affected by overall white and gray matter changes than absolute connectivity measures. After detecting brain regions with abnormal connectional fingerprints through similarity measures, we tested each of its relative connection probability between groups. We found altered connectional fingerprints in schizophrenia patients consistent with a dysconnectivity syndrome. While the medial frontal gyrus showed only reduced connectivity, the connectional fingerprints of the inferior frontal gyrus and the putamen mainly contained relatively increased connection probabilities to areas in the frontal, limbic, and subcortical areas. These findings are in line with previous studies that reported abnormalities in striatal-frontal circuits in the pathophysiology of schizophrenia, highlighting the potential utility of connectional fingerprints for the analysis of anatomical networks in the disorder.

  7. Connectivity and Coverage in Hybrid Wireless Sensor Networks using Dynamic Random Geometric Graph Model

    Directory of Open Access Journals (Sweden)

    Jasmine Norman

    2011-10-01

    Full Text Available Random Geometric Graphs have been a very influential and well-studied model of large networks, such assensor networks, where the network nodes are represented by the vertices of the RGG, and the direct connectivity between nodes is represented by the edges. This assumes homogeneous wireless nodes with uniform transmission ranges. In real life, there exist heterogeneous wireless networks in which devices have dramatically different capabilities. The connectivity of a WSN is related to the positions of nodes, and those positions are heavily affected by the method of sensor deployment. As sensors may be spread in an arbitrary manner, one of the fundamental issues in a wireless sensor network is the coverage problem. In this paper, I study connectivity and coverage in hybrid WSN based on dynamic random geometric graph.

  8. Change in brain network connectivity during PACAP38-induced migraine attacks

    DEFF Research Database (Denmark)

    Amin, Faisal Mohammad; Hougaard, Anders; Magon, Stefano

    2016-01-01

    OBJECTIVE: To investigate resting-state functional connectivity in the salience network (SN), the sensorimotor network (SMN), and the default mode network (DMN) during migraine attacks induced by pituitary adenylate cyclase-activating polypeptide-38 (PACAP38). METHODS: In a double-blind, randomized......, and visual cortices) and decreased (right cerebellum and left frontal lobe) connectivity with DMN. We found no resting-state network changes after VIP (n = 15). CONCLUSIONS: PACAP38-induced migraine attack is associated with altered connectivity of several large-scale functional networks of the brain....... study, 24 female migraine patients without aura received IV PACAP38 or vasoactive intestinal polypeptide (VIP) over 20 minutes. Both peptides are closely related and cause vasodilation, but only PACAP38 induces migraine attacks. VIP was therefore used as active placebo. Resting-state functional MRI...

  9. Dynamics of organizational rumor communication on connecting multi-small-world networks

    Institute of Scientific and Technical Information of China (English)

    Xing Qi-Bin; Zhang Yuan-Biao; Liang Zhi-Ning; ZhangFan

    2011-01-01

    We study the dynamics of an epidemic-like model for the spread of a rumor on a connecting multi-small-world-network (CM-SWN) model,which represents organizational communication in the real world.It has been shown that this model exhibits a transition between regimes of localization and propagation at a finite value of network randomness.Here,by numerical means,we perform a quantitative characterization of the evolution in the three groups under two evolution rules,namely the conformity and obeying principles.The variant of a dynamic CM-SWN,where the quenched disorder of small-world networks is replaced by randomly changing connections between individuals in a single network and stable connection by star nodes between networks,is also analysed in detail and compared with a mean-field approximation.

  10. Default mode, executive function, and language functional connectivity networks are compromised in mild Alzheimer's disease.

    Science.gov (United States)

    Weiler, Marina; Fukuda, Aya; Massabki, Lilian H P; Lopes, Tatila M; Franco, Alexandre R; Damasceno, Benito P; Cendes, Fernando; Balthazar, Marcio L F

    2014-03-01

    Alzheimer's disease (AD) is characterized by mental and cognitive problems, particularly with memory, language, visuospatial skills (VS), and executive functions (EF). Advances in the neuroimaging of AD have highlighted dysfunctions in functional connectivity networks (FCNs), especially in the memory related default mode network (DMN). However, little is known about the integrity and clinical significance of FNCs that process other cognitive functions than memory. We evaluated 22 patients with mild AD and 26 healthy controls through a resting state functional MRI scan. We aimed to identify different FCNs: the DMN, language, EF, and VS. Seed-based functional connectivity was calculated by placing a seed in the DMN (posterior cingulate cortex), language (Broca's and Wernicke's areas), EF (right and left dorsolateral prefrontal cortex), and VS networks (right and left associative visual cortex). We also performed regression analyses between individual connectivity maps for the different FCNs and the scores on cognitive tests. We found areas with significant decreases in functional connectivity in patients with mild AD in the DMN and Wernicke's area compared with controls. Increased connectivity in patients was observed in the EF network. Regarding multiple linear regression analyses, a significant correlation was only observed between the connectivity of the DMN and episodic memory (delayed recall) scores. In conclusion, functional connectivity alterations in mild AD are not restricted to the DMN. Other FCNs related to language and EF may be altered. However, we only found significant correlations between cognition and functional connectivity in the DMN and episodic memory performance.

  11. Connection of OWPPs to HVDC networks using VSCs and Diode Rectifiers: an Overview

    DEFF Research Database (Denmark)

    Saborío-Romano, Oscar; Bidadfar, Ali; Göksu, Ömer;

    This paper provides an overview of two technologies for connecting offshore wind power plants (offshore WPPs, OWPPs) to high-voltage direct current (HVDC) networks: voltage source converters (VSCs) and diode rectifiers (DRs). Current grid code requirements for the connection of such power plants...

  12. Client-Based Control Channel Analysis for Connectivity Estimation in LTE Networks

    OpenAIRE

    Falkenberg, Robert; Ide, Christoph; Wietfeld, Christian

    2017-01-01

    Advanced Cyber-Physical Systems aim for the balancing of restricted local resources of deeply embedded systems with cloud-based resources depending on the availability of network connectivity: in case of excellent connectivity, the offloading of large amounts of data can be more efficient than the local processing on a resource-constraint platform, while this latter solution is preferred in case of limited connectivity. This paper proposes a Client-Based Control Channel Analysis for Connectiv...

  13. Functional connectivity analysis using whole brain and regional network metrics in MS patients.

    Science.gov (United States)

    Chirumamilla, V C; Fleischer, V; Droby, A; Anjum, T; Muthuraman, M; Zipp, F; Groppa, S

    2016-08-01

    In the present study we investigated brain network connectivity differences between patients with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC) as derived from functional resonance magnetic imaging (fMRI) using graph theory. Resting state fMRI data of 18 RRMS patients (12 female, mean age ± SD: 42 ± 12.06 years) and 25 HC (8 female, 29.2 ± 5.38 years) were analyzed. In order to obtain information of differences in entire brain network, we focused on both, local and global network connectivity parameters. And the regional connectivity differences were assessed using regional network parameters. RRMS patients presented a significant increase of modularity in comparison to HC, pointing towards a network structure with densely interconnected nodes within one module, while the number of connections with other modules outside decreases. This higher decomposable network favours cost-efficient local information processing and promotes long-range disconnection. In addition, at the regional anatomical level, the network parameters clustering coefficient and local efficiency were increased in the insula, the superior parietal gyrus and the temporal pole. Our study indicates that modularity as derived from fMRI can be seen as a characteristic connectivity feature that is increased in MS patients compared to HC. Furthermore, specific anatomical regions linked to perception, motor function and cognition were mainly involved in the enhanced local information processing.

  14. Attentional load modulates large-scale functional brain connectivity beyond the core attention networks.

    Science.gov (United States)

    Alnæs, Dag; Kaufmann, Tobias; Richard, Geneviève; Duff, Eugene P; Sneve, Markus H; Endestad, Tor; Nordvik, Jan Egil; Andreassen, Ole A; Smith, Stephen M; Westlye, Lars T

    2015-04-01

    In line with the notion of a continuously active and dynamic brain, functional networks identified during rest correspond with those revealed by task-fMRI. Characterizing the dynamic cross-talk between these network nodes is key to understanding the successful implementation of effortful cognitive processing in healthy individuals and its breakdown in a variety of conditions involving aberrant brain biology and cognitive dysfunction. We employed advanced network modeling on fMRI data collected during a task involving sustained attentive tracking of objects at two load levels and during rest. Using multivariate techniques, we demonstrate that attentional load levels can be significantly discriminated, and from a resting-state condition, the accuracy approaches 100%, by means of estimates of between-node functional connectivity. Several network edges were modulated during task engagement: The dorsal attention network increased connectivity with a visual node, while decreasing connectivity with motor and sensory nodes. Also, we observed a decoupling between left and right hemisphere dorsal visual streams. These results support the notion of dynamic network reconfigurations based on attentional effort. No simple correspondence between node signal amplitude change and node connectivity modulations was found, thus network modeling provides novel information beyond what is revealed by conventional task-fMRI analysis. The current decoding of attentional states confirms that edge connectivity contains highly predictive information about the mental state of the individual, and the approach shows promise for the utilization in clinical contexts.

  15. Functional Connectivity with the Default Mode Network Is Altered in Fibromyalgia Patients

    Science.gov (United States)

    Chiu, Yee; Nurmikko, Turo; Stancak, Andrej

    2016-01-01

    Fibromyalgia syndrome (FMS) patients show altered connectivity with the network maintaining ongoing resting brain activity, known as the default mode network (DMN). The connectivity patterns of DMN with the rest of the brain in FMS patients are poorly understood. This study employed seed-based functional connectivity analysis to investigate resting-state functional connectivity with DMN structures in FMS. Sixteen female FMS patients and 15 age-matched, healthy control subjects underwent T2-weighted resting-state MRI scanning and functional connectivity analyses using DMN network seed regions. FMS patients demonstrated alterations to connectivity between DMN structures and anterior midcingulate cortex, right parahippocampal gyrus, left superior parietal lobule and left inferior temporal gyrus. Correlation analysis showed that reduced functional connectivity between the DMN and the right parahippocampal gyrus was associated with longer duration of symptoms in FMS patients, whereas augmented connectivity between the anterior midcingulate and posterior cingulate cortices was associated with tenderness and depression scores. Our findings demonstrate alterations to functional connectivity between DMN regions and a variety of regions which are important for pain, cognitive and emotional processing in FMS patients, and which may contribute to the development or maintenance of chronic symptoms in FMS. PMID:27442504

  16. CONNECTIONS USING SOCIAL NETWORKS AND SOCIAL INTELLIGENCE OF STUDENTS

    Directory of Open Access Journals (Sweden)

    Belma Duvnjak

    2013-05-01

    Full Text Available Social intelligence is the ability and skills to cope with everyday life situations and how to cope with interpersonal relationships. Today's generation of relationships based, carried and nurtured through various social networks. The aim of the presented research is to identify the impact of social networks on the development of social intelligence. The study was done on a sample, which makes the 208 students from the Faculty of Education at the University "Džemal Bijedić" in Mostar. The results show that the impact of social networks on the development of positive social intelligence. Greater achievement on tests of social intelligence (SI were significantly correlated with the amount of time spent using different social networks.

  17. Schizophrenic patients and their unaffected siblings share increased resting-state connectivity in the task-negative network but not its anticorrelated task-positive network

    OpenAIRE

    Liu, Haihong; Kaneko, Yoshio; Ouyang, Xuan; Li, Li; Hao, Yihui; Chen, Eric Y. H.; Jiang, Tianzi; Zhou, Yuan; Liu, Zhening

    2010-01-01

    Background: Abnormal connectivity of the anticorrelated intrinsic networks, the task-negative network (TNN), and the task-positive network (TPN) is implicated in schizophrenia. Comparisons between schizophrenic patients and their unaffected siblings enable further understanding of illness susceptibility and pathophysiology. We examined the resting-state connectivity differences in the intrinsic networks between schizophrenic patients, their unaffected siblings, and healthy controls. Methods: ...

  18. Impact of Terrain Features for Tactical Network Connectivity

    Science.gov (United States)

    2013-09-01

    distributions of ?̅?, we also conclude that () ≅ ?̅? is a reasonable approximation for most internode distances, at least for Charlottesville and...single network with multiple pathways emerges. This example is a particular illustra- tion of how powerfully an ad hoc network can overcome open links...preserve paths reduce the contribution of long pathways . 3-5 The large n limit reduces to preserved ( ) → ?̅? 2(1 + �), (3-10) which

  19. Aberrant functional connectivity of resting state networks in transient ischemic attack.

    Directory of Open Access Journals (Sweden)

    Rong Li

    Full Text Available BACKGROUND: Transient ischemic attack (TIA is usually defined as a neurologic ischemic disorder without permanent cerebral infarction. Studies have showed that patients with TIA can have lasting cognitive functional impairment. Inherent brain activity in the resting state is spatially organized in a set of specific coherent patterns named resting state networks (RSNs, which epitomize the functional architecture of memory, language, attention, visual, auditory and somato-motor networks. Here, we aimed to detect differences in RSNs between TIA patients and healthy controls (HCs. METHODS: Twenty one TIA patients suffered an ischemic event and 21 matched HCs were enrolled in the study. All subjects were investigated using cognitive tests, psychiatric tests and functional magnetic resonance imaging (fMRI. Independent component analysis (ICA was adopted to acquire the eight brain RSNs. Then one-sample t-tests were calculated in each group to gather the spatial maps of each RSNs, followed by second level analysis to investigate statistical differences on RSNs between twenty one TIA patients and 21 controls. Furthermore, a correlation analysis was performed to explore the relationship between functional connectivity (FC and cognitive and psychiatric scales in TIA group. RESULTS: Compared with the controls, TIA patients exhibited both decreased and increased functional connectivity in default mode network (DMN and self-referential network (SRN, and decreased functional connectivity in dorsal attention network (DAN, central-executive network (CEN, core network (CN, somato-motor network (SMN, visual network (VN and auditory network (AN. There was no correlation between neuropsychological scores and functional connectivity in regions of RSNs. CONCLUSIONS: We observed selective impairments of RSN intrinsic FC in TIA patients, whose all eight RSNs had aberrant functional connectivity. These changes indicate that TIA is a disease with widely abnormal brain

  20. A New Method of Transmission Network Flexible Planning Using the Connection Number

    Institute of Scientific and Technical Information of China (English)

    JIN Hua-zheng; CHENG Hao-zhong

    2008-01-01

    Because connection number can express and process synthetic uncertainties caused by various uncertainties in the transmission network planning, a connection number model (CNM) was presented to compare the values of connection number logically. This paper proposed a novel model for transmission network flexible planning with uncertainty. In the proposed planning model both certainty and uncertainty information were included, and the cost-benefit analysis method was used to evaluate the candidate schemes in the objective function. Its good adaptability and flexibility were illustrated through two examples.

  1. Influence of Different Connectivity Topologies in Small World Networks Modeling Earthquakes

    Institute of Scientific and Technical Information of China (English)

    LIN Min; CHEN Tian-Lun

    2004-01-01

    We introduce the Olami-Feder-Christensen (OFC) model on a squarelattice with some "rewired" long-range connections having the properties of small world networks. We find that our model displays the power-law behavior,and connectivity topologies are very important to model's avalanche dynamical behaviors. Our model has some behaviorsdifferent from the OFC model on a small world network with "added" long-range connections in our previous work [LINMin, ZHAO Xiao-Wei, and CHEN Tian-Lun, Commun. Theor. Phys. (Beijing, China) 41 (2004) 557.].

  2. Influence of Different Connectivity Topologies in Small World Networks Modeling Earthquakes

    Institute of Scientific and Technical Information of China (English)

    LINMin; CHENTian-Lun

    2004-01-01

    We introduce the Olami-Feder-Christensen (OFC) model on a square lattice with some "rewired" longrange connections having the properties of small world networks. We find that our model displays the power-law behavior, and connectivity topologies are very important to model's avalanche dynamical behaviors. Our model has some behaviors different from the OFC model on a small world network with "added" long-range connections in our previous work [LIN Min, ZHAO Xiao-Wei, and CHEN Tian-Lun, Commun. Theor. Phys. (Beijing, China) 41 (2004) 557.].

  3. Cost and Availability Analysis of 2- and 3-Connected WDM Networks Physical Interconnection

    DEFF Research Database (Denmark)

    Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir; Pedersen, Jens Myrup

    2012-01-01

    for the best trade-off among the relevant parameters for the network. In this paper we analyze this trade-off by studying 2-and 3-connected graphs to be used as WDM (Wavelength Division Multiplexing) networks physical infrastructure. The experiments show how the way links are distributed to interconnect...

  4. Measurement campaign on connectivity of mesh networks formed by mobile devices

    DEFF Research Database (Denmark)

    Pietrarca, Beatrice; Sasso, Giovanni; Perrucci, Gian Paolo

    2007-01-01

    This paper reports the results of a measurement campaign on the connectivity level of mobile devices using Bluetooth (BT) to form cooperative mobile mesh networks. Such mobile mesh networks composed of mobile devices are the basis for any peer-to-peer communication like wireless grids or social...

  5. Locating Highly Connected Nodes in P2P Networks with Heterogeneous Structures

    Institute of Scientific and Technical Information of China (English)

    ZHANG Haoxiang; ZHANG Lin; SHAN Xiuming; Victor O. K. LI

    2009-01-01

    Peer-to-peer (P2P) networks aggregate enormous storage and processing resources while mini-mizing entry and scaling costs. Gnutella-like P2P networks are complex heterogeneous networks, in which the underlying overlay topology has a power-law node degree distribution. While scale-free networks have great robustness against random failures, they are vulnerable to deliberate attacks where highly connected nodes are eliminated. Since high degree nodes play an important role in maintaining the connectivity, this paper presents an algorithm based on random walks to locate high degree nodes in P2P networks. Simula-tions demonstrate that the algorithm performs well in various scenarios and that heterogeneous P2P net-works are very sensitive to deliberate attacks.

  6. Network-based analysis reveals functional connectivity related to internet addiction tendency

    Directory of Open Access Journals (Sweden)

    Tanya eWen

    2016-02-01

    Full Text Available IntroductionPreoccupation and compulsive use of the internet can have negative psychological effects, such that it is increasingly being recognized as a mental disorder. The present study employed network-based statistics to explore how whole-brain functional connections at rest is related to the extent of individual’s level of internet addiction, indexed by a self-rated questionnaire. We identified two topologically significant networks, one with connections that are positively correlated with internet addiction tendency, and one with connections negatively correlated with internet addiction tendency. The two networks are interconnected mostly at frontal regions, which might reflect alterations in the frontal region for different aspects of cognitive control (i.e., for control of internet usage and gaming skills. Next, we categorized the brain into several large regional subgroupings, and found that the majority of proportions of connections in the two networks correspond to the cerebellar model of addiction which encompasses the four-circuit model. Lastly, we observed that the brain regions with the most inter-regional connections associated with internet addiction tendency replicate those often seen in addiction literature, and is corroborated by our meta-analysis of internet addiction studies. This research provides a better understanding of large-scale networks involved in internet addiction tendency and shows that pre-clinical levels of internet addiction are associated with similar regions and connections as clinical cases of addiction.

  7. Network-Based Analysis Reveals Functional Connectivity Related to Internet Addiction Tendency.

    Science.gov (United States)

    Wen, Tanya; Hsieh, Shulan

    2016-01-01

    Preoccupation and compulsive use of the internet can have negative psychological effects, such that it is increasingly being recognized as a mental disorder. The present study employed network-based statistics to explore how whole-brain functional connections at rest is related to the extent of individual's level of internet addiction, indexed by a self-rated questionnaire. We identified two topologically significant networks, one with connections that are positively correlated with internet addiction tendency, and one with connections negatively correlated with internet addiction tendency. The two networks are interconnected mostly at frontal regions, which might reflect alterations in the frontal region for different aspects of cognitive control (i.e., for control of internet usage and gaming skills). Next, we categorized the brain into several large regional subgroupings, and found that the majority of proportions of connections in the two networks correspond to the cerebellar model of addiction which encompasses the four-circuit model. Lastly, we observed that the brain regions with the most inter-regional connections associated with internet addiction tendency replicate those often seen in addiction literature, and is corroborated by our meta-analysis of internet addiction studies. This research provides a better understanding of large-scale networks involved in internet addiction tendency and shows that pre-clinical levels of internet addiction are associated with similar regions and connections as clinical cases of addiction.

  8. Resting-state connectivity in the default mode network and insula during experimental low back pain

    Institute of Scientific and Technical Information of China (English)

    Shanshan Zhang; Wen Wu; Guozhi Huang; Ziping Liu; Shigui Guo; Jianming Yang; Kangling Wang

    2014-01-01

    Functional magnetic resonance imaging studies have shown that the insular cortex has a signif-icant role in pain identiifcation and information integration, while the default mode network is associated with cognitive and memory-related aspects of pain perception. However, changes in the functional connectivity between the default mode network and insula during pain remain unclear. This study used 3.0 T functional magnetic resonance imaging scans in 12 healthy sub-jects aged 24.8 ± 3.3 years to compare the differences in the functional activity and connectivity of the insula and default mode network between the baseline and pain condition induced by intramuscular injection of hypertonic saline. Compared with the baseline, the insula was more functionally connected with the medial prefrontal and lateral temporal cortices, whereas there was lower connectivity with the posterior cingulate cortex, precuneus and inferior parietal lobule in the pain condition. In addition, compared with baseline, the anterior cingulate cortex exhibited greater connectivity with the posterior insula, but lower connectivity with the anterior insula, during the pain condition. These data indicate that experimental low back pain led to dysfunction in the connectivity between the insula and default mode network resulting from an impairment of the regions of the brain related to cognition and emotion, suggesting the impor-tance of the interaction between these regions in pain processing.

  9. Social Networking for the Older and Wiser Connect with Family, and Friends Old and New

    CERN Document Server

    McManus, Sean

    2010-01-01

    Social networks enable anyone with a computer and Internet connection to stay in touch with friends and family across the globe, and rediscover old acquaintances.  Social Networking for the Older and Wiser starts with the basics of social networks, before moving onto intermediate topics, all whilst highlighting ways to protect your privacy and keep your details secure. The book is packed with step-by-step instructions on how to use Facebook, Twitter, Friends Reunited, Saga Zone, and other social networks to:Create an account on your chosen social networkReconnect and stay-in-touch with old fr

  10. Resting-state functional connectivity of orthographic networks in acquired dysgraphia

    Directory of Open Access Journals (Sweden)

    Gali Ellenblum

    2015-05-01

    The NTA findings indicate that the relationship between orthographic and default-mode networks is characterized by greater within- vs. across-network connectivity. Furthermore, we show for the first time a pattern of increasing within/across network “coherence normalization” following spelling rehabilitation. Additional dysgraphic participants and other networks (language, sensory-motor, etc. will be analyzed to develop a better understanding of the RS orthographic network and its response to damage and recovery. Acknowledgements. The work is part of a multi-site, NIDCD-supported project examining language recovery neurobiology in aphasia (DC006740. We thank Melissa Greenberger and Xiao-Wei Song.

  11. Hydrodynamic provinces and oceanic connectivity from a transport network help designing marine reserves

    Science.gov (United States)

    Rossi, Vincent; Ser-Giacomi, Enrico; López, Cristóbal; Hernández-García, Emilio

    2014-04-01

    Oceanic dispersal and connectivity have been identified as crucial factors for structuring marine populations and designing marine protected areas (MPAs). Focusing on larval dispersal by ocean currents, we propose an approach coupling Lagrangian transport and new tools from Network Theory to characterize marine connectivity in the Mediterranean basin. Larvae of different pelagic durations and seasons are modeled as passive tracers advected in a simulated oceanic surface flow from which a network of connected areas is constructed. Hydrodynamical provinces extracted from this network are delimited by frontiers which match multiscale oceanographic features. By examining the repeated occurrence of such boundaries, we identify the spatial scales and geographic structures that would control larval dispersal across the entire seascape. Based on these hydrodynamical units, we study novel connectivity metrics for existing reserves. Our results are discussed in the context of ocean biogeography and MPAs design, having ecological and managerial implications.

  12. Analysis of Push-type Epidemic Data Dissemination in Fully Connected Networks

    OpenAIRE

    Çağlar, Mine; Sezer, Ali Devin

    2014-01-01

    Analysis of Push-type Epidemic Data Dissemination in Fully Connected Networks Mine C¸ a˘glar Department of Mathematics, Ko¸c University, Istanbul, Turkey Ali Devin Sezer Universit´e d’Evry, Laboratoire Analyse et Probabilit´es and Middle East Technical University, Institute of Applied Mathematics Abstract Consider a fully connected network of nodes, some of which have a piece of data to be disseminated to the whole network. We analyze the following push-type epid...

  13. Locally oriented information, calculation and documentation of networks with process connection

    Energy Technology Data Exchange (ETDEWEB)

    Brauner, G.

    1988-10-24

    Modular LORIS systems (Locally Oriented Information System) execute supply network information, documentation, calculation and simulation tasks and include software and hardware as well as system consulting, training and service functions. Services can be ranging from the scanning and digitalization of planned systems to network consulting and data base design services. LORIS can be connected to AEG network control systems (EVU 800) substation control and protection system (ILS system) to fulfill background functions for production data acquisition and fault location.

  14. Cluster Head Selection in a Homogeneous Wireless Sensor Network Ensuring Full Connectivity with Minimum Isolated Nodes

    Directory of Open Access Journals (Sweden)

    Tapan Kumar Jain

    2014-01-01

    Full Text Available The research work proposes a cluster head selection algorithm for a wireless sensor network. A node can be a cluster head if it is connected to at least one unique neighbor node where the unique neighbor is the one that is not connected to any other node. If there is no connected unique node then the CH is selected on the basis of residual energy and the number of neighbor nodes. With the increase in number of clusters, the processing energy of the network increases; hence, this algorithm proposes minimum number of clusters which further leads to increased network lifetime. The major novel contribution of the proposed work is an algorithm that ensures a completely connected network with minimum number of isolated nodes. An isolated node will remain only if it is not within the transmission range of any other node. With the maximum connectivity, the coverage of the network is automatically maximized. The superiority of the proposed design is verified by simulation results done in MATLAB, where it clearly depicts that the total numbers of rounds before the network dies out are maximum compared to other existing protocols.

  15. Analyzing the scaling of connectivity in neuromorphic hardware and in models of neural networks.

    Science.gov (United States)

    Partzsch, Johannes; Schüffny, René

    2011-06-01

    In recent years, neuromorphic hardware systems have significantly grown in size. With more and more neurons and synapses integrated in such systems, the neural connectivity and its configurability have become crucial design constraints. To tackle this problem, we introduce a generic extended graph description of connection topologies that allows a systematical analysis of connectivity in both neuromorphic hardware and neural network models. The unifying nature of our approach enables a close exchange between hardware and models. For an existing hardware system, the optimally matched network model can be extracted. Inversely, a hardware architecture may be fitted to a particular model network topology with our description method. As a further strength, the extended graph can be used to quantify the amount of configurability for a certain network topology. This is a hardware design variable that has widely been neglected, mainly because of a missing analysis method. To condense our analysis results, we develop a classification for the scaling complexity of network models and neuromorphic hardware, based on the total number of connections and the configurability. We find a gap between several models and existing hardware, making these hardware systems either impossible or inefficient to use for scaled-up network models. In this respect, our analysis results suggest models with locality in their connections as promising approach for tackling this scaling gap.

  16. NetStat: A Probabilistic Network Connectivity Analysis Tool,

    Science.gov (United States)

    1993-02-01

    of Invulnerable Communication Nets . IEEE Trans. on Circuit TheoryMay 1970 [14] Ed. Boesch, F.,et. al., Networks, An International Journal . New York...Wiley Journals , Vol. 15, Num. 2, Summer 1985 [15] Ed. Boesch, F., Large Scale Networks, Theory and Design. New York: IEEE Press, 1976 APPENDIX A...Npd..Bpd: RNumloString(DEFNODE..PD. SirnStrArrii)); $pd. Opd: RNumToSIting(DEF...LINK_.PO. SimStrAnrfi)); ?tr. .Dst: csea ((ord(i) -ord(Npd)) mod 3

  17. Slow dynamics and high variability in balanced cortical networks with clustered connections.

    Science.gov (United States)

    Litwin-Kumar, Ashok; Doiron, Brent

    2012-11-01

    Anatomical studies demonstrate that excitatory connections in cortex are not uniformly distributed across a network but instead exhibit clustering into groups of highly connected neurons. The implications of clustering for cortical activity are unclear. We studied the effect of clustered excitatory connections on the dynamics of neuronal networks that exhibited high spike time variability owing to a balance between excitation and inhibition. Even modest clustering substantially changed the behavior of these networks, introducing slow dynamics during which clusters of neurons transiently increased or decreased their firing rate. Consequently, neurons exhibited both fast spiking variability and slow firing rate fluctuations. A simplified model shows how stimuli bias networks toward particular activity states, thereby reducing firing rate variability as observed experimentally in many cortical areas. Our model thus relates cortical architecture to the reported variability in spontaneous and evoked spiking activity.

  18. Magnetoencephalography Reveals a Widespread Increase in Network Connectivity in Idiopathic/Genetic Generalized Epilepsy.

    Science.gov (United States)

    Elshahabi, Adham; Klamer, Silke; Sahib, Ashish Kaul; Lerche, Holger; Braun, Christoph; Focke, Niels K

    2015-01-01

    Idiopathic/genetic generalized epilepsy (IGE/GGE) is characterized by seizures, which start and rapidly engage widely distributed networks, and result in symptoms such as absences, generalized myoclonic and primary generalized tonic-clonic seizures. Although routine magnetic resonance imaging is apparently normal, many studies have reported structural alterations in IGE/GGE patients using diffusion tensor imaging and voxel-based morphometry. Changes have also been reported in functional networks during generalized spike wave discharges. However, network function in the resting-state without epileptiforme discharges has been less well studied. We hypothesize that resting-state networks are more representative of the underlying pathophysiology and abnormal network synchrony. We studied functional network connectivity derived from whole-brain magnetoencephalography recordings in thirteen IGE/GGE and nineteen healthy controls. Using graph theoretical network analysis, we found a widespread increase in connectivity in patients compared to controls. These changes were most pronounced in the motor network, the mesio-frontal and temporal cortex. We did not, however, find any significant difference between the normalized clustering coefficients, indicating preserved gross network architecture. Our findings suggest that increased resting state connectivity could be an important factor for seizure spread and/or generation in IGE/GGE, and could serve as a biomarker for the disease.

  19. Magnetoencephalography Reveals a Widespread Increase in Network Connectivity in Idiopathic/Genetic Generalized Epilepsy.

    Directory of Open Access Journals (Sweden)

    Adham Elshahabi

    Full Text Available Idiopathic/genetic generalized epilepsy (IGE/GGE is characterized by seizures, which start and rapidly engage widely distributed networks, and result in symptoms such as absences, generalized myoclonic and primary generalized tonic-clonic seizures. Although routine magnetic resonance imaging is apparently normal, many studies have reported structural alterations in IGE/GGE patients using diffusion tensor imaging and voxel-based morphometry. Changes have also been reported in functional networks during generalized spike wave discharges. However, network function in the resting-state without epileptiforme discharges has been less well studied. We hypothesize that resting-state networks are more representative of the underlying pathophysiology and abnormal network synchrony. We studied functional network connectivity derived from whole-brain magnetoencephalography recordings in thirteen IGE/GGE and nineteen healthy controls. Using graph theoretical network analysis, we found a widespread increase in connectivity in patients compared to controls. These changes were most pronounced in the motor network, the mesio-frontal and temporal cortex. We did not, however, find any significant difference between the normalized clustering coefficients, indicating preserved gross network architecture. Our findings suggest that increased resting state connectivity could be an important factor for seizure spread and/or generation in IGE/GGE, and could serve as a biomarker for the disease.

  20. Social-ecology networks : building connections for sustainable landscapes

    NARCIS (Netherlands)

    Opdam, P.F.M.

    2014-01-01

    Humans adapt their landscapes, their living environment. Sustainable use of the various landscape benefits requires that land owners and users collaborate in managing ecological networks. Because the government is stepping back as the organizer of coordinated landscape adaptation, we need new landsc

  1. Writingmatrix: Connecting Students with Blogs, Tags, and Social Networking

    Science.gov (United States)

    Stevens, Vance; Quintana, Nelba; Zeinstejer, Rita; Sirk, Sasa; Molero, Doris; Arena, Carla

    2008-01-01

    This paper describes an extensive online project, Writingmatrix [http://writingmatrix.wikispaces.com], involving several key elements essential to collaboration in Web 2.0, such as aggregation, tagging, and social networking. Participant teachers in several different countries--Argentina, Venezuela, and Slovenia--had their adult students at…

  2. The Unexpected Connection: Serendipity and Human Mediation in Networked Learning

    Science.gov (United States)

    Kop, Rita

    2012-01-01

    Major changes on the Web in recent years have contributed to an abundance of information for people to harness in their learning. Emerging technologies have instigated the need for critical literacies to support learners on open online networks in the mastering of critical information gathering during their learning journeys. This paper will argue…

  3. Predicting the connectivity of primate cortical networks from topological and spatial node properties

    Directory of Open Access Journals (Sweden)

    Kaiser Marcus

    2007-03-01

    Full Text Available Abstract Background The organization of the connectivity between mammalian cortical areas has become a major subject of study, because of its important role in scaffolding the macroscopic aspects of animal behavior and intelligence. In this study we present a computational reconstruction approach to the problem of network organization, by considering the topological and spatial features of each area in the primate cerebral cortex as subsidy for the reconstruction of the global cortical network connectivity. Starting with all areas being disconnected, pairs of areas with similar sets of features are linked together, in an attempt to recover the original network structure. Results Inferring primate cortical connectivity from the properties of the nodes, remarkably good reconstructions of the global network organization could be obtained, with the topological features allowing slightly superior accuracy to the spatial ones. Analogous reconstruction attempts for the C. elegans neuronal network resulted in substantially poorer recovery, indicating that cortical area interconnections are relatively stronger related to the considered topological and spatial properties than neuronal projections in the nematode. Conclusion The close relationship between area-based features and global connectivity may hint on developmental rules and constraints for cortical networks. Particularly, differences between the predictions from topological and spatial properties, together with the poorer recovery resulting from spatial properties, indicate that the organization of cortical networks is not entirely determined by spatial constraints.

  4. Initialization and self-organized optimization of recurrent neural network connectivity.

    Science.gov (United States)

    Boedecker, Joschka; Obst, Oliver; Mayer, N Michael; Asada, Minoru

    2009-10-01

    Reservoir computing (RC) is a recent paradigm in the field of recurrent neural networks. Networks in RC have a sparsely and randomly connected fixed hidden layer, and only output connections are trained. RC networks have recently received increased attention as a mathematical model for generic neural microcircuits to investigate and explain computations in neocortical columns. Applied to specific tasks, their fixed random connectivity, however, leads to significant variation in performance. Few problem-specific optimization procedures are known, which would be important for engineering applications, but also in order to understand how networks in biology are shaped to be optimally adapted to requirements of their environment. We study a general network initialization method using permutation matrices and derive a new unsupervised learning rule based on intrinsic plasticity (IP). The IP-based learning uses only local learning, and its aim is to improve network performance in a self-organized way. Using three different benchmarks, we show that networks with permutation matrices for the reservoir connectivity have much more persistent memory than the other methods but are also able to perform highly nonlinear mappings. We also show that IP-based on sigmoid transfer functions is limited concerning the output distributions that can be achieved.

  5. Shifted intrinsic connectivity of central executive and salience network in borderline personality disorder

    Directory of Open Access Journals (Sweden)

    Anselm eDoll

    2013-10-01

    Full Text Available Borderline personality disorder (BPD is characterized by stable instability of emotions and behavior and their regulation. This emotional and behavioral instability corresponds with a neurocognitive triple network model of psychopathology, which suggests that aberrant emotional saliency and cognitive control is associated with aberrant interaction across three intrinsic connectivity networks (ICN (i.e. the salience, default mode, and central executive network, SN, DMN, CEN. The objective of the current study was to investigate whether and how such triple network intrinsic functional connectivity (iFC is changed in patients with BPD. We acquired resting-state functional magnetic resonance imaging (rs-fMRI data from fourteen patients with BPD and sixteen healthy controls (HC. High-model order independent component analysis (ICA was used to extract spatiotemporal patterns of ongoing, coherent blood-oxygen-level-dependent (BOLD signal fluctuations from rs-fMRI data. Main outcome measures were iFC within networks (intra-iFC and between networks (i.e. network time course correlation inter-iFC.Aberrant intra-iFC was found in patients’ DMN, SN, and CEN, consistent with previous findings. While patients’ inter-iFC of the CEN was decreased, inter-iFC of the SN was increased. In particular, a balance index reflecting the relationship of CEN-and SN-inter-iFC across networks was strongly shifted from CEN to SN connectivity in patients. Results provide first preliminary evidence for aberrant triple network intrinsic functional connectivity in BPD. Our data suggest a shift of inter-network iFC from networks involved in cognitive control to those of emotion-related activity in BPD, potentially reflecting the persistent instability of emotion regulation in patients.

  6. On Connected Target k-Coverage in Heterogeneous Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jiguo Yu

    2016-01-01

    Full Text Available Coverage and connectivity are two important performance evaluation indices for wireless sensor networks (WSNs. In this paper, we focus on the connected target k-coverage (CTC k problem in heterogeneous wireless sensor networks (HWSNs. A centralized connected target k-coverage algorithm (CCTC k and a distributed connected target k-coverage algorithm (DCTC k are proposed so as to generate connected cover sets for energy-efficient connectivity and coverage maintenance. To be specific, our proposed algorithms aim at achieving minimum connected target k-coverage, where each target in the monitored region is covered by at least k active sensor nodes. In addition, these two algorithms strive to minimize the total number of active sensor nodes and guarantee that each sensor node is connected to a sink, such that the sensed data can be forwarded to the sink. Our theoretical analysis and simulation results show that our proposed algorithms outperform a state-of-art connected k-coverage protocol for HWSNs.

  7. On Connected Target k-Coverage in Heterogeneous Wireless Sensor Networks.

    Science.gov (United States)

    Yu, Jiguo; Chen, Ying; Ma, Liran; Huang, Baogui; Cheng, Xiuzhen

    2016-01-15

    Coverage and connectivity are two important performance evaluation indices for wireless sensor networks (WSNs). In this paper, we focus on the connected target k-coverage (CTC k) problem in heterogeneous wireless sensor networks (HWSNs). A centralized connected target k-coverage algorithm (CCTC k) and a distributed connected target k-coverage algorithm (DCTC k) are proposed so as to generate connected cover sets for energy-efficient connectivity and coverage maintenance. To be specific, our proposed algorithms aim at achieving minimum connected target k-coverage, where each target in the monitored region is covered by at least k active sensor nodes. In addition, these two algorithms strive to minimize the total number of active sensor nodes and guarantee that each sensor node is connected to a sink, such that the sensed data can be forwarded to the sink. Our theoretical analysis and simulation results show that our proposed algorithms outperform a state-of-art connected k-coverage protocol for HWSNs.

  8. Age Differences in the Intrinsic Functional Connectivity of Default Network Subsystems

    Directory of Open Access Journals (Sweden)

    Karen eCampbell

    2013-11-01

    Full Text Available Recent work suggests that the default mode network (DMN includes two core regions, the ventromedial prefrontal cortex (vmPFC and posterior cingulate cortex (PCC, and several unique subsystems that are functionally distinct. These include a medial temporal lobe (MTL subsystem, active during remembering and future projection, and a dorsomedial PFC (dmPFC subsystem, active during self-reference. The PCC has been further subdivided into ventral (vPCC and dorsal (dPCC regions that are more strongly connected with the DMN and cognitive control networks, respectively. The goal of this study was to examine age differences in resting state functional connectivity within these subsystems. After applying a rigorous procedure to reduce the effects of head motion, we used a multivariate technique to identify both common and unique patterns of functional connectivity in the MTL vs. the dmPFC, and in vPCC vs. dPCC. All four areas had robust functional connectivity with other DMN regions, and each also showed distinct connectivity patterns in both age groups. Young and older adults had equivalent functional connectivity in the MTL subsystem. Older adults showed weaker connectivity in the vPCC and dmPFC subsystems, particularly with other DMN areas, but stronger connectivity than younger adults in the dPCC subsystem, which included areas involved in cognitive control. Our data provide evidence for distinct subsystems involving DMN nodes, which are maintained with age. Nevertheless, there are age differences in the strength of functional connectivity within these subsystems, supporting prior evidence that DMN connectivity is particularly vulnerable to age, whereas connectivity involving cognitive control regions is relatively maintained. These results suggest an age difference in the integrated activity among brain networks that can have implications for cognition in older adults.

  9. A Space Operations Network Alternative: Using the Globally Connected Research and Education Networks for Space-based Science Operations

    Science.gov (United States)

    Bradford, Robert N.

    2006-01-01

    Earth based networking in support of various space agency projects has been based on leased service/circuits which has a high associated cost. This cost is almost always taken from the science side resulting in less science. This is a proposal to use Research and Education Networks (RENs) worldwide to support space flight operations in general and space-based science operations in particular. The RENs were developed to support scientific and educational endeavors. They do not provide support for general Internet traffic. The connectivity and performance of the research and education networks is superb. The connectivity at Layer 3 (IP) virtually encompasses the globe. Most third world countries and all developed countries have their own research and education networks, which are connected globally. Performance of the RENs especially in the developed countries is exceptional. Bandwidth capacity currently exists and future expansion promises that this capacity will continue. REN performance statistics has always exceeded minimum requirements for spaceflight support. Research and Education networks are more loosely managed than a corporate network but are highly managed when compared to the commodity Internet. Management of RENs on an international level is accomplished by the International Network Operations Center at Indiana University at Indianapolis. With few exceptions, each regional and national REN has its own network ops center. The acceptable use policies (AUP), although differing by country, allows any scientific program or project the use of their networks. Once in compliance with the first RENs AUP, all others will accept that specific traffic including regional and transoceanic networks. RENs can support spaceflight related scientific programs and projects. Getting the science to the researcher is obviously key to any scientific project. RENs provide a pathway to virtually any college or university in the world, as well as many governmental institutes and

  10. Inferring Neuronal Network Connectivity using Time-constrained Episodes

    CERN Document Server

    Patnaik, Debprakash; Unnikrishnan, K P

    2007-01-01

    Discovering frequent episodes in event sequences is an interesting data mining task. In this paper, we argue that this framework is very effective for analyzing multi-neuronal spike train data. Analyzing spike train data is an important problem in neuroscience though there are no data mining approaches reported for this. Motivated by this application, we introduce different temporal constraints on the occurrences of episodes. We present algorithms for discovering frequent episodes under temporal constraints. Through simulations, we show that our method is very effective for analyzing spike train data for unearthing underlying connectivity patterns.

  11. Contention aware mobility prediction routing for intermittently connected mobile networks

    KAUST Repository

    Elwhishi, Ahmed

    2013-04-26

    This paper introduces a novel multi-copy routing protocol, called predict and forward (PF), for delay tolerant networks, which aims to explore the possibility of using mobile nodes as message carriers for end-to-end delivery of the messages. With PF, the message forwarding decision is made by manipulating the probability distribution of future inter-contact and contact durations based on the network status, including wireless link condition and nodal buffer availability. In particular, PF is based on the observations that the node mobility behavior is semi-deterministic and could be predicted once there is sufficient mobility history information. We implemented the proposed protocol and compared it with a number of existing encounter-based routing approaches in terms of delivery delay, delivery ratio, and the number of transmissions required for message delivery. The simulation results show that PF outperforms all the counterpart multi-copy encounter-based routing protocols considered in the study.

  12. Convergence and divergence are mostly reciprocated properties of the connections in the network of cortical areas.

    Science.gov (United States)

    Négyessy, László; Nepusz, Tamás; Zalányi, László; Bazsó, Fülöp

    2008-10-22

    Cognition is based on the integrated functioning of hierarchically organized cortical processing streams in a manner yet to be clarified. Because integration fundamentally depends on convergence and the complementary notion of divergence of the neuronal connections, we analysed integration by measuring the degree of convergence/divergence through the connections in the network of cortical areas. By introducing a new index, we explored the complementary convergent and divergent nature of connectional reciprocity and delineated the backward and forward cortical sub-networks for the first time. Integrative properties of the areas defined by the degree of convergence/divergence through their afferents and efferents exhibited distinctive characteristics at different levels of the cortical hierarchy. Areas previously identified as hubs exhibit information bottleneck properties. Cortical networks largely deviate from random graphs where convergence and divergence are balanced at low reciprocity level. In the cortex, which is dominated by reciprocal connections, balance appears only by further increasing the number of reciprocal connections. The results point to the decisive role of the optimal number and placement of reciprocal connections in large-scale cortical integration. Our findings also facilitate understanding of the functional interactions between the cortical areas and the information flow or its equivalents in highly recurrent natural and artificial networks.

  13. Multiple resting state network functional connectivity abnormalities in mild traumatic brain injury.

    Science.gov (United States)

    Stevens, Michael C; Lovejoy, David; Kim, Jinsuh; Oakes, Howard; Kureshi, Inam; Witt, Suzanne T

    2012-06-01

    Several reports show that traumatic brain injury (TBI) results in abnormalities in the coordinated activation among brain regions. Because most previous studies examined moderate/severe TBI, the extensiveness of functional connectivity abnormalities and their relationship to postconcussive complaints or white matter microstructural damage are unclear in mild TBI. This study characterized widespread injury effects on multiple integrated neural networks typically observed during a task-unconstrained "resting state" in mild TBI patients. Whole brain functional connectivity for twelve separate networks was identified using independent component analysis (ICA) of fMRI data collected from thirty mild TBI patients mostly free of macroscopic intracerebral injury and thirty demographically-matched healthy control participants. Voxelwise group comparisons found abnormal mild TBI functional connectivity in every brain network identified by ICA, including visual processing, motor, limbic, and numerous circuits believed to underlie executive cognition. Abnormalities not only included functional connectivity deficits, but also enhancements possibly reflecting compensatory neural processes. Postconcussive symptom severity was linked to abnormal regional connectivity within nearly every brain network identified, particularly anterior cingulate. A recently developed multivariate technique that identifies links between whole brain profiles of functional and anatomical connectivity identified several novel mild TBI abnormalities, and represents a potentially important new tool in the study of the complex neurobiological sequelae of TBI.

  14. Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity

    OpenAIRE

    Bassett, Danielle S.; Ankit N Khambhati; Grafton, Scott T.

    2016-01-01

    Neuroengineering is faced with unique challenges in repairing or replacing complex neural systems that are composed of many interacting parts. These interactions form intricate patterns over large spatiotemporal scales, and produce emergent behaviors that are difficult to predict from individual elements. Network science provides a particularly appropriate framework in which to study and intervene in such systems, by treating neural elements (cells, volumes) as nodes in a graph and neural int...

  15. An Entity Maintenance and Connection Service for Sensor Networks

    Science.gov (United States)

    2006-01-01

    Demultiplexing - Message Buffering - Leader Election - Persistent State Messages Data Messages Entity Control Network and MAC Layer (Location-based...Node Receive Heartbeat Entity Timeout Node Member Election Leader Leader Lose Event Sense Event Lose Event Leader Election Figure 3. Node state...the case where the old leader simply dies in which case a timeout must elapse before the new leader election starts. Figures 6 and 7 compare the av

  16. Relay movement control for maintaining connectivity in aeronautical ad hoc networks

    Institute of Scientific and Technical Information of China (English)

    李杰; 孙志强; 师博浩; 宫二玲; 谢红卫

    2016-01-01

    As a new sort of mobile ad hoc network (MANET), aeronautical ad hoc network (AANET) has fleet-moving airborne nodes (ANs) and suffers from frequent network partitioning due to the rapid-changing topology. In this work, the additional relay nodes (RNs) is employed to repair the network and maintain connectivity in AANET. As ANs move, RNs need to move as well in order to re-establish the topology as quickly as possible. The network model and problem definition are firstly given, and then an online approach for RNs’ movement control is presented to make ANs achieve certain connectivity requirement during run time. By defining the minimum cost feasible moving matrix (MCFM), a fast algorithm is proposed for RNs’ movement control problem. Simulations demonstrate that the proposed algorithm outperforms other control approaches in the highly-dynamic environment and is of great potential to be applied in AANET.

  17. Connected Key No de Set-Based Skyline Query Pro cessing over Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    XIE Zhijun; YE Hongwu

    2015-01-01

    Skyline query has been applied widely in sensor networks. We propose a connected key node set-based skyline Efficient skyline query processing (EffiSky) algorithm to minimize communication traffic for resources-limited sensor networks. In the EffiSky algorithm, we dis-cover a Connected key node set (CKNS) used to trans-mit and collect queries and results among the sensor nodes, which can reduce the average communication cost of the networks significantly. We set up a two-level fil-tering scheme that prunes many useless dominated tu-ples. Both the theoretical analysis and experiment results demonstrate that EffiSky excels the existing work in terms of network traffic, scalability in network expansion, node density, and dimension change.

  18. Data for default network reduced functional connectivity in meditators, negatively correlated with meditation expertise

    Directory of Open Access Journals (Sweden)

    Aviva Berkovich-Ohana

    2016-09-01

    Full Text Available FMRI data described here was recorded during resting-state in Mindfulness Meditators (MM and control participants (see “Task-induced activity and resting-state fluctuations undergo similar alterations in visual and DMN areas of long-term meditators” Berkovich-Ohana et al. (2016 [1] for details. MM participants were also scanned during meditation. Analyses focused on functional connectivity within and between the default mode network (DMN and visual network (Vis. Here we show data demonstrating that: 1 Functional connectivity within the DMN and the Visual networks were higher in the control group than in the meditators; 2 Data show an increase for the functional connectivity between the DMN and the Visual networks in the meditators compared to controls; 3 Data demonstrate that functional connectivity both within and between networks reduces during meditation, compared to the resting-state; and 4 A significant negative correlation was found between DMN functional connectivity and meditation expertise. The reader is referred to Berkovich-Ohana et al. (2016 [1] for further interpretation and discussion.

  19. Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.

    Directory of Open Access Journals (Sweden)

    Peng Fang

    Full Text Available Magnetic resonance imaging studies have reported significant functional and structural differences between depressed patients and controls. Little attention has been given, however, to the abnormalities in anatomical connectivity in depressed patients. In the present study, we aim to investigate the alterations in connectivity of whole-brain anatomical networks in those suffering from major depression by using machine learning approaches. Brain anatomical networks were extracted from diffusion magnetic resonance images obtained from both 22 first-episode, treatment-naive adults with major depressive disorder and 26 matched healthy controls. Using machine learning approaches, we differentiated depressed patients from healthy controls based on their whole-brain anatomical connectivity patterns and identified the most discriminating features that represent between-group differences. Classification results showed that 91.7% (patients=86.4%, controls=96.2%; permutation test, p<0.0001 of subjects were correctly classified via leave-one-out cross-validation. Moreover, the strengths of all the most discriminating connections were increased in depressed patients relative to the controls, and these connections were primarily located within the cortical-limbic network, especially the frontal-limbic network. These results not only provide initial steps toward the development of neurobiological diagnostic markers for major depressive disorder, but also suggest that abnormal cortical-limbic anatomical networks may contribute to the anatomical basis of emotional dysregulation and cognitive impairments associated with this disease.

  20. Resting-brain functional connectivity predicted by analytic measures of network communication

    Science.gov (United States)

    Goñi, Joaquín; van den Heuvel, Martijn P.; Avena-Koenigsberger, Andrea; Velez de Mendizabal, Nieves; Betzel, Richard F.; Griffa, Alessandra; Hagmann, Patric; Corominas-Murtra, Bernat; Thiran, Jean-Philippe; Sporns, Olaf

    2014-01-01

    The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structural connectivity of the human brain and explore the capacity of these measures to predict resting-state functional connectivity across three independently acquired datasets. We focus on the layout of shortest paths across the network and on two communication measures—search information and path transitivity—which account for how these paths are embedded in the rest of the network. Search information is an existing measure of information needed to access or trace shortest paths; we introduce path transitivity to measure the density of local detours along the shortest path. We find that both search information and path transitivity predict the strength of functional connectivity among both connected and unconnected node pairs. They do so at levels that match or significantly exceed path length measures, Euclidean distance, as well as computational models of neural dynamics. This capacity suggests that dynamic couplings due to interactions among neural elements in brain networks are substantially influenced by the broader network context adjacent to the shortest communication pathways. PMID:24379387

  1. Connectivity and dynamics of neuronal networks as defined by the shape of individual neurons

    Energy Technology Data Exchange (ETDEWEB)

    Ahnert, Sebastian E [Theory of Condensed Matter, Cavendish Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE (United Kingdom); A N Travencolo, Bruno; Costa, Luciano da Fontoura [Instituto de FIsica de Sao Carlos, Universidade de Sao Paulo, Av. Trabalhador Sao Carlense 400, Caixa Postal 369, CEP 13560-970, Sao Carlos, Sao Paulo (Brazil)], E-mail: luciano@if.sc.usp.br

    2009-10-15

    Biological neuronal networks constitute a special class of dynamical systems, as they are formed by individual geometrical components, namely the neurons. In the existing literature, relatively little attention has been given to the influence of neuron shape on the overall connectivity and dynamics of the emerging networks. The current work addresses this issue by considering simplified neuronal shapes consisting of circular regions (soma/axons) with spokes (dendrites). Networks are grown by placing these patterns randomly in the two-dimensional (2D) plane and establishing connections whenever a piece of dendrite falls inside an axon. Several topological and dynamical properties of the resulting graph are measured, including the degree distribution, clustering coefficients, symmetry of connections, size of the largest connected component, as well as three hierarchical measurements of the local topology. By varying the number of processes of the individual basic patterns, we can quantify relationships between the individual neuronal shape and the topological and dynamical features of the networks. Integrate-and-fire dynamics on these networks is also investigated with respect to transient activation from a source node, indicating that long-range connections play an important role in the propagation of avalanches.

  2. Aberrant functional connectivity of default-mode network in type 2 diabetes patients

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Ying; Jiao, Yun; Chen, Hua-Jun; Ding, Jie; Luo, Bing; Peng, Cheng-Yu; Ju, Sheng-Hong; Teng, Gao-Jun [Medical School of Southeast University, Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Nanjing, Jiangsu (China)

    2015-11-15

    Type 2 diabetes mellitus is associated with increased risk for dementia. Patients with impaired cognition often show default-mode network disruption. We aimed to investigate the integrity of a default-mode network in diabetic patients by using independent component analysis, and to explore the relationship between network abnormalities, neurocognitive performance and diabetic variables. Forty-two patients with type 2 diabetes and 42 well-matched healthy controls were included and underwent resting-state functional MRI in a 3 Tesla unit. Independent component analysis was adopted to extract the default-mode network, including its anterior and posterior components. Z-maps of both sub-networks were compared between the two groups and correlated with each clinical variable. Patients showed increased connectivity around the medial prefrontal cortex in the anterior sub-network, but decreased connectivity around the posterior cingulate cortex in the posterior sub-network. The decreased connectivity in the posterior part was significantly correlated with the score on Complex Figure Test-delay recall test (r = 0.359, p = 0.020), the time spent on Trail-Making Test-part B (r = -0.346, p = 0.025) and the insulin resistance level (r = -0.404, p = 0.024). Dissociation pattern in the default-mode network was found in diabetic patients, which might provide powerful new insights into the neural mechanisms that underlie the diabetes-related cognitive decline. (orig.)

  3. Resting state functional MRI reveals abnormal network connectivity in orthostatic tremor.

    Science.gov (United States)

    Benito-León, Julián; Louis, Elan D; Manzanedo, Eva; Hernández-Tamames, Juan Antonio; Álvarez-Linera, Juan; Molina-Arjona, José Antonio; Matarazzo, Michele; Romero, Juan Pablo; Domínguez-González, Cristina; Domingo-Santos, Ángela; Sánchez-Ferro, Álvaro

    2016-07-01

    Very little is known about the pathogenesis of orthostatic tremor (OT). We have observed that OT patients might have deficits in specific aspects of neuropsychological function, particularly those thought to rely on the integrity of the prefrontal cortex, which suggests a possible involvement of frontocerebellar circuits. We examined whether resting-state functional magnetic resonance imaging (fMRI) might provide further insights into the pathogenesis on OT. Resting-state fMRI data in 13 OT patients (11 women and 2 men) and 13 matched healthy controls were analyzed using independent component analysis, in combination with a "dual-regression" technique, to identify group differences in several resting-state networks (RSNs). All participants also underwent neuropsychological testing during the same session. Relative to healthy controls, OT patients showed increased connectivity in RSNs involved in cognitive processes (default mode network [DMN] and frontoparietal networks), and decreased connectivity in the cerebellum and sensorimotor networks. Changes in network integrity were associated not only with duration (DMN and medial visual network), but also with cognitive function. Moreover, in at least 2 networks (DMN and medial visual network), increased connectivity was associated with worse performance on different cognitive domains (attention, executive function, visuospatial ability, visual memory, and language). In this exploratory study, we observed selective impairments of RSNs in OT patients. This and other future resting-state fMRI studies might provide a novel method to understand the pathophysiological mechanisms of motor and nonmotor features of OT.

  4. Middleware-based connection management for QoS-enabled networks

    Science.gov (United States)

    Fulp, Errin W.

    2004-10-01

    Many applications require network performance bounds, or Quality of Service (QoS), for their proper operation. This is achieved through the appropriate allocation of network resources; however, providing end-to-end QoS is becoming more complex, due to the increasing heterogeneity of networks. For example, end-to-end QoS can be provided through the concatenation of services across multiple networks (domains), but each domain may employ different network technologies as well as different QoS methodologies. As a result, management strategies are needed to provide QoS across multiple domains in a scalable and economically feasible manner. This paper describes a microeconomic-based middleware architecture that allows the specification and acquisition of QoS and resource policies. The architecture consists of users, bandwidth brokers, and network domains. Executing applications, users require network QoS obtained via middleware from a bandwidth broker. Bandwidth brokers then interact with one another to provide end-to-end QoS connections across multiple domains. This is done in a BGP manner which recursively provides end-to-end services in a scalable fashion. Using this framework, this paper describes management strategies to optimally provision and allocate end-to-end connections. The methods maintain a low blocking probability, and maximize utility and profit, which are increasingly important as network connectivity evolves as an industry.

  5. Protein intrinsic disorder and network connectivity. The case of 14-3-3 proteins.

    Directory of Open Access Journals (Sweden)

    Marina eUhart

    2014-02-01

    Full Text Available The understanding of networks is a common goal of an unprecedented array oftraditional disciplines. One of the network properties most influenced by thestructural contents of its nodes is the inter-connectivity. Recent studies in whichstructural information was included into the topological analysis of proteinnetworks revealed that the content of intrinsic disorder in the nodes couldmodulate the network topology, rewire networks and change their inter-connectivity, which is defined by its clustering coefficient. Here, we review therole of intrinsic disorder present in the partners of the highly conserved 14-3-3protein family on its interaction networks. The 14-3-3s are phospho-serine/threonine binding proteins that have strong influence in the regulation ofmetabolism and signal transduction networks. Intrinsic disorder increases theclustering coefficients, namely the inter-connectivity of the nodes within each14-3-3 paralog networks. We also review two new ideas to measure intrinsicdisorder independently of the primary sequence of proteins, a thermodynamicmodel and a method that uses protein structures and their solventenvironment. This new methods could be useful to explain unsolved questionsabout versatility and fixation of intrinsic disorder through evolution. Therelation between the intrinsic disorder and network topologies could be aninteresting model to investigate new implicitness of the graph theory intobiology.

  6. ON THE PROBABILITY OF K-CONNECTIVITY IN WIRELESS AD HOC NETWORKS UNDER DIFFERENT MOBILITY MODELS

    Directory of Open Access Journals (Sweden)

    Natarajan Meghanathan

    2010-09-01

    Full Text Available We compare the probability of k-Connectivity of an ad hoc network under Random Way Point (RWP,City Section and Manhattan mobility models. A Network is said to be k-Connected if there exists at least kedge disjoint paths between any pair of nodes in that network at any given time and velocity. Initially, foreach of the three mobility models, the movement of the each node in the ad hoc network at a givenvelocity and time are captured and stored in the Node Movement Database (NMDB. Using themovements in the NMDB, the location of the node at a given time is computed and stored in the NodeLocation Database (NLDB. A weighted graph is created using the location of the nodes from NLDB,which is converted into a residual graph. The k-Connectivity of this residual graph is obtained by runningFord-Fulkerson’s algorithm on it. Ford Fulkerson’s algorithm computes the maximum flow of a networkby recording the flows assigned to different routes from each node to all the other nodes in the network.When run for a particular source-destination pair (s, d pair on a residual network graph with unit edgeweights as capacity, the maximum flow determined by Ford-Fulkerson’ algorithm is the number of edgedisjoint s-d paths on the network graph. Simulations show that the RWP model yields the highestprobability of k-Connectivity compared to City Section and Manhattan mobility models for a majority ofdifferent node densities and velocities considered. Simulation results also show that, for all the threemobility models, as the k value increases, the probability of k-Connectivity decreases for a given densityand velocity and as the density increases the probability of k-Connectivity increases.

  7. Exercise-related changes in between-network connectivity in overweight/obese adults.

    Science.gov (United States)

    Legget, Kristina T; Wylie, Korey P; Cornier, Marc-Andre; Melanson, Edward L; Paschall, Courtnie J; Tregellas, Jason R

    2016-05-01

    Understanding how exercise affects communication across the brain in overweight/obese individuals may provide insight into mechanisms of weight loss and maintenance. In the current study, we examined the effects of a 6-month exercise program in 11 overweight/obese individuals (mean BMI: 33.6±1.4mg/kg(2); mean age: 38.2±3.2years) on integrative brain "hubs," which are areas with high levels of connectivity to multiple large-scale networks thought to play an important role in multimodal integration among brain regions. These integrative hubs were identified with a recently developed between-network connectivity (BNC) metric, using functional magnetic resonance imaging (fMRI). BNC utilizes a multiple regression analysis approach to assess relationships between the time series of large-scale functionally-connected brain networks (identified using independent components analysis) and the time series of each individual voxel in the brain. This approach identifies brain regions with high between-network interaction, i.e., areas with high levels of connectivity to many large-scale networks. Changes in BNC following exercise were determined using paired t-tests, with results considered significant at a whole-brain level if they exceeded a voxel-wise threshold of pexercise on communication between large-scale networks may contribute to individual responsivity to exercise.

  8. A fractal growth model: Exploring the connection pattern of hubs in complex networks

    Science.gov (United States)

    Li, Dongyan; Wang, Xingyuan; Huang, Penghe

    2017-04-01

    Fractal is ubiquitous in many real-world networks. Previous researches showed that the strong disassortativity between the hub-nodes on all length scales was the key principle that gave rise to the fractal architecture of networks. Although fractal property emerged in some models, there were few researches about the fractal growth model and quantitative analyses about the strength of the disassortativity for fractal model. In this paper, we proposed a novel inverse renormalization method, named Box-based Preferential Attachment (BPA), to build the fractal growth models in which the Preferential Attachment was performed at box level. The proposed models provided a new framework that demonstrated small-world-fractal transition. Also, we firstly demonstrated the statistical characteristic of connection patterns of the hubs in fractal networks. The experimental results showed that, given proper growing scale and added edges, the proposed models could clearly show pure small-world or pure fractal or both of them. It also showed that the hub connection ratio showed normal distribution in many real-world networks. At last, the comparisons of connection pattern between the proposed models and the biological and technical networks were performed. The results gave useful reference for exploring the growth principle and for modeling the connection patterns for real-world networks.

  9. The structural connectivity pattern of the default mode network and its association with memory and anxiety

    Directory of Open Access Journals (Sweden)

    Yan eTao

    2015-11-01

    Full Text Available The default mode network (DMN is one of the most widely studied resting state functional networks. The structural basis for the DMN is of particular interest and has been studied by several researchers using diffusion tensor imaging (DTI. Most of these previous studies focused on a few regions or white matter tracts of the DMN so that the global structural connectivity pattern and network properties of the DMN remain unclear. Moreover, evidences indicate that the DMN is involved in both memory and emotion, but how the DMN regulates memory and anxiety from the perspective of the whole DMN structural network remains unknown. We used multimodal neuroimaging methods to investigate the structural connectivity pattern of the DMN and the association of its network properties with memory and anxiety in 205 young healthy subjects. Using a probabilistic fiber tractography technique based on DTI data and graph theory methods, we constructed the global structural connectivity pattern of the DMN and found that memory quotient (MQ score was significantly positively correlated with the global and local efficiency of the DMN whereas anxiety was found to be negatively correlated with the efficiency. The strong structural connectivity between multiple brain regions within DMN may reflect that the DMN has certain structural basis. Meanwhile, we found the network efficiency of the DMN were related to memory and anxiety measures, which indicated that the DMN may play a role in the memory and anxiety.

  10. Evaluation and calibration of functional network modeling methods based on known anatomical connections.

    Science.gov (United States)

    Dawson, Debra Ann; Cha, Kuwook; Lewis, Lindsay B; Mendola, Janine D; Shmuel, Amir

    2013-02-15

    Recent studies have identified large scale brain networks based on the spatio-temporal structure of spontaneous fluctuations in resting-state fMRI data. It is expected that functional connectivity based on resting-state data is reflective of - but not identical to - the underlying anatomical connectivity. However, which functional connectivity analysis methods reliably predict the network structure remains unclear. Here we tested and compared network connectivity analysis methods by applying them to fMRI resting-state time-series obtained from the human visual cortex. The methods evaluated here are those previously tested against simulated data in Smith et al. (Neuroimage, 2011). To this end, we defined regions within retinotopic visual areas V1, V2, and V3 according to their eccentricity in the visual field, delineating central, intermediate, and peripheral eccentricity regions of interest (ROIs). These ROIs served as nodes in the models we study. We based our evaluation on the "ground-truth", thoroughly studied retinotopically-organized anatomical connectivity in the monkey visual cortex. For each evaluated method, we computed the fractional rate of detecting connections known to exist ("c-sensitivity"), while using a threshold of the 95th percentile of the distribution of interaction magnitudes of those connections not expected to exist. Under optimal conditions - including session duration of 68min, a relatively small network consisting of 9 nodes and artifact-free regression of the global effect - each of the top methods predicted the expected connections with 67-85% c-sensitivity. Correlation methods, including Correlation (Corr; 85%), Regularized Inverse Covariance (ICOV; 84%) and Partial Correlation (PCorr; 81%) performed best, followed by Patel's Kappa (80%), Bayesian Network method PC (BayesNet; 77%), General Synchronization measures (67-77%), and Coherence (CohB; 74%). With decreased session duration, these top methods saw decreases in c

  11. Efficient generation of connectivity in neuronal networks from simulator-independent descriptions

    Directory of Open Access Journals (Sweden)

    Mikael eDjurfeldt

    2014-04-01

    Full Text Available Simulator-independent descriptions of connectivity in neuronal networks promise greater ease of model sharing, improved reproducibility of simulation results, and reduced programming effort for computational neuroscientists. However, until now, enabling the use of such descriptions in a given simulator in a computationally efficient way has entailed considerable work for simulator developers, which must be repeated for each new connectivity-generating library that is developed.We have developed a generic connection generator interface that provides a standard way to connect a connectivity-generating library to a simulator, such that one library can easily be replaced by another, according to the modeller's needs. We have used the connection generator interface to connect C++ and Python implementations of the connection-set algebra to the NEST simulator. We also demonstrate how the simulator-independent modelling framework PyNN can transparently take advantage of this, passing a connection description through to the simulator layer for rapid processing in C++ where a simulator supports the connection generator interface and falling-back to slower iteration in Python otherwise. A set of benchmarks demonstrates the good performance of the interface.

  12. Efficient generation of connectivity in neuronal networks from simulator-independent descriptions.

    Science.gov (United States)

    Djurfeldt, Mikael; Davison, Andrew P; Eppler, Jochen M

    2014-01-01

    Simulator-independent descriptions of connectivity in neuronal networks promise greater ease of model sharing, improved reproducibility of simulation results, and reduced programming effort for computational neuroscientists. However, until now, enabling the use of such descriptions in a given simulator in a computationally efficient way has entailed considerable work for simulator developers, which must be repeated for each new connectivity-generating library that is developed. We have developed a generic connection generator interface that provides a standard way to connect a connectivity-generating library to a simulator, such that one library can easily be replaced by another, according to the modeler's needs. We have used the connection generator interface to connect C++ and Python implementations of the previously described connection-set algebra to the NEST simulator. We also demonstrate how the simulator-independent modeling framework PyNN can transparently take advantage of this, passing a connection description through to the simulator layer for rapid processing in C++ where a simulator supports the connection generator interface and falling-back to slower iteration in Python otherwise. A set of benchmarks demonstrates the good performance of the interface.

  13. Traffic dynamics on dynamical networks: The connection between network lifetime and traffic congestion

    CERN Document Server

    Yang, Xianxia; Yan, Meichen; Sharafat, Rajput Ramiz; Yang, Jian

    2016-01-01

    For many power-limited networks, such as wireless sensor networks and mobile ad hoc networks, maximizing the network lifetime is the first concern in the related designing and maintaining activities. We study the network lifetime from the perspective of network science. In our dynamic network, nodes are assigned a fixed amount of energy initially and consume the energy in the delivery of packets. We divided the network traffic flow into four states: no, slow, fast, and absolute congestion states. We derive the network lifetime by considering the state of the traffic flow. We find that the network lifetime is generally opposite to traffic congestion in that the more congested traffic, the less network lifetime. We also find the impacts of factors such as packet generation rate, communication radius, node moving speed, etc., on network lifetime and traffic congestion.

  14. Cooperative Adaptive Output Regulation for Second-Order Nonlinear Multiagent Systems With Jointly Connected Switching Networks.

    Science.gov (United States)

    Liu, Wei; Huang, Jie

    2017-01-11

    This paper studies the cooperative global robust output regulation problem for a class of heterogeneous second-order nonlinear uncertain multiagent systems with jointly connected switching networks. The main contributions consist of the following three aspects. First, we generalize the result of the adaptive distributed observer from undirected jointly connected switching networks to directed jointly connected switching networks. Second, by performing a new coordinate and input transformation, we convert our problem into the cooperative global robust stabilization problem of a more complex augmented system via the distributed internal model principle. Third, we solve the stabilization problem by a distributed state feedback control law. Our result is illustrated by the leader-following consensus problem for a group of Van der Pol oscillators.

  15. GENERAL: Connectivity correlations in three topological spaces of urban bus-transport networks in China

    Science.gov (United States)

    Chen, Yong-Zhou; Fu, Chun-Hua; Chang, Hui; Li, Nan; He, Da-Ren

    2008-10-01

    In this paper, an empirical investigation is presented, which focuses on unveiling the universality of connectivity correlations in three spaces (the route space, the stop geographical space and bus-transferring space) of urban bus-transport networks (BTNs) in four major cities of China. The underlying features of the connectivity correlations are shown in two statistical ways. One is the correlation between the (weighted) average degree of all the nearest neighbouring vertices with degree k, (Knnw (k)) Knn(k), and k, and the other is the correlations between the assortativity coefficient r and, respectively, the network size N, the network diameter D, the averaged clustering coefficient C, and the averaged distance . The obtained results show qualitatively the same connectivity correlations of all the considered cities under all the three spaces.

  16. Heterogeneity of Global and Local Connectivity in Spatial Network Structures of World Migration

    CERN Document Server

    Danchev, Valentin

    2016-01-01

    We examine world migration as a social-spatial network of countries connected via movements of people. We assess how multilateral migratory relationships at global, regional, and local scales coexist ("glocalization"), divide ("polarization"), or form an interconnected global system ("globalization"). To do this, we decompose the world migration network (WMN) into communities---sets of countries with denser than expected migration connections---and characterize their pattern of local (i.e., intracommunity) and global (i.e., intercommunity) connectivity. We distinguish community signatures---"cave", "biregional", and "bridging"---with distinct migration patterns, spatial network structures, temporal dynamics, and underlying antecedents. Cave communities are tightly-knit, enduring structures that tend to channel local migration between contiguous countries; biregional communities are likely to merge migration between two distinct geographic regions (e.g., North Africa and Europe); and bridging communities have ...

  17. TCP INCAST AVOIDANCE BASED ON CONNECTION SERIALIZATION IN DATA CENTER NETWORKS

    Directory of Open Access Journals (Sweden)

    Shigeyuki Osada

    2016-07-01

    Full Text Available In distributed file systems, a well-known congestion collapse called TCP incast (Incast briefly occurs because many servers almost simultaneously send data to the same client and then many packets overflow the port buffer of the link connecting to the client. Incast leads to throughput degradation in the network. In this paper, we propose three methods to avoid Incast based on the fact that the bandwidth-delay product is small in current data center networks. The first method is a method which completely serializes connection establishments. By the serialization, the number of packets in the port buffer becomes very small, which leads to Incast avoidance. The second and third methods are methods which overlap the slow start period of the next connection with the current established connection to improve throughput in the first method. Numerical results from extensive simulation runs show the effectiveness of our three proposed methods.

  18. Contention Aware Routing for Intermittently Connected Mobile Networks

    KAUST Repository

    Elwhishi, Ahmed

    2011-08-21

    This paper introduces a novel multi-copy routing protocol, called Self Adaptive Utility-based Routing Protocol (SAURP), for Delay Tolerant Networks (DTNs) that are possibly composed of a vast number of miniature devices such as smart phones, hand-held devices, and sensors mounted in fixed or mobile objects. SAURP aims to explore the possibility of taking mobile nodes as message carriers in order for end-to-end delivery of the messages. The best carrier for a message is determined by the prediction result using a novel contact model, where the network status, including wireless link condition and nodal buffer availability, are jointly considered. The paper argues and proves that the nodal movement and the predicted collocation with the message recipient can serve as meaningful information to achieve an intelligent message forwarding decision at each node. The proposed protocol has been implemented and compared with a number of existing encounter-based routing approaches in terms of delivery delay, and the number of transmissions required for message delivery. The simulation results show that the proposed SAURP outperforms all the counterpart multi-copy encounter-based routing protocols considered in the study.

  19. How plants connect pollination and herbivory networks and their contribution to community stability.

    Science.gov (United States)

    Sauve, Alix M C; Thébault, Elisa; Pocock, Michael J O; Fontaine, Colin

    2016-04-01

    Pollination and herbivory networks have mainly been studied separately, highlighting their distinct structural characteristics and the related processes and dynamics. However, most plants interact with both pollinators and herbivores, and there is evidence that both types of interaction affect each other. Here we investigated the way plants connect these mutualistic and antagonistic networks together, and the consequences for community stability. Using an empirical data set, we show that the way plants connect pollination and herbivory networks is not random and promotes community stability. Analyses of the structure of binary and quantitative networks show different results: the plants' generalism with regard to pollinators is positively correlated to their generalism with regard to herbivores when considering binary interactions, but not when considering quantitative interactions. We also show that plants that share the same pollinators do not share the same herbivores. However, the way plants connect pollination and herbivory networks promotes stability for both binary and quantitative networks. Our results highlight the relevance of considering the diversity of interaction types in ecological communities, and stress the need to better quantify the costs and benefits of interactions, as well as to develop new metrics characterizing the way different interaction types are combined within ecological networks.

  20. An application of higher order connection to inverse function delayed network

    Science.gov (United States)

    Sota, Takahiro; Hayakawa, Yoshihiro; Sato, Shigeo; Nakajima, Koji

    The Inverse function Delayed model (ID model) is a neuron model with negative resistance dynamics. The negative resistance can destabilize local minimum states, which are undesirable network responses. The ID network can remove these states. Actually, we have demonstrated that the ID network can perfectly remove all local minima with N-Queen problems or 4-Color problems, where stationary stable states always give correct answers. However this method cannot apply to Traveling Salesman Problems (TSPs) or Quadratic Assignment Problems (QAPs). Meanwhile, it is proposed that the TSPs are able to be represented in terms of the quartic form energy function. In this representation, the global minimum states that represent correct answers and the local minimum states are separable clearly, thus if it is applied to the ID network, it ensures that only the local minimum states are destabilized by the negative resistance. In this paper, we aim to introduce higher order connections to the ID network to apply the quartic form energy function. We apply the ID network with higher order connections to the TSPs or QAPs, and show that the higher order connection ID network can destabilize only the local minimum states by the negative resistance effect, so that it obtains only correct answers found at stationary stable states. Moreover, we obtain minimum parameter region analytically to destabilize every local minimum state.

  1. Alterations of Functional Connectivity Among Resting-State Networks in Hypothyroidism.

    Science.gov (United States)

    Singh, S; Kumar, M; Modi, S; Kaur, P; Shankar, L R; Khushu, S

    2015-07-01

    Hypothyroidism affects brain functioning as suggested by various neuroimaging studies. The primary focus of the present study was to examine whether hypothyroidism would impact connectivity among resting-state networks (RSNs) using resting-state functional magnetic resonance imaging (rsfMRI). Twenty-two patients with hypothyroidism and 22 healthy controls were recruited and scanned using rsfMRI. The data were analysed using independent component analysis and a dual regression approach that was applied on five RSNs that were identified using fsl software (http://fsl.fmrib.ox.ac.uk). Hypothyroid patients showed significantly decreased functional connectivity in the regions of the right frontoparietal network (frontal pole), the medial visual network (lateral occipital gyrus, precuneus cortex and cuneus) and the motor network (precentral gyrus, postcentral gyrus, precuneus cortex, paracingulate gyrus, cingulate gyrus and supramarginal gyrus) compared to healthy controls. The reduced functional connectivity in the right frontoparietal network, the medial visual network and the motor network suggests neurocognitive alterations in hypothyroid patients in the corresponding functions. However, the study would be further continued to investigate the effects of thyroxine treatment and correlation with neurocognitive scores. The findings of the present study provide further interesting insights into our understanding of the action of thyroid hormone on the adult human brain.

  2. Functional connectivity and information flow of the respiratory neural network in chronic obstructive pulmonary disease.

    Science.gov (United States)

    Yu, Lianchun; De Mazancourt, Marine; Hess, Agathe; Ashadi, Fakhrul R; Klein, Isabelle; Mal, Hervé; Courbage, Maurice; Mangin, Laurence

    2016-08-01

    Breathing involves a complex interplay between the brainstem automatic network and cortical voluntary command. How these brain regions communicate at rest or during inspiratory loading is unknown. This issue is crucial for several reasons: (i) increased respiratory loading is a major feature of several respiratory diseases, (ii) failure of the voluntary motor and cortical sensory processing drives is among the mechanisms that precede acute respiratory failure, (iii) several cerebral structures involved in responding to inspiratory loading participate in the perception of dyspnea, a distressing symptom in many disease. We studied functional connectivity and Granger causality of the respiratory network in controls and patients with chronic obstructive pulmonary disease (COPD), at rest and during inspiratory loading. Compared with those of controls, the motor cortex area of patients exhibited decreased connectivity with their contralateral counterparts and no connectivity with the brainstem. In the patients, the information flow was reversed at rest with the source of the network shifted from the medulla towards the motor cortex. During inspiratory loading, the system was overwhelmed and the motor cortex became the sink of the network. This major finding may help to understand why some patients with COPD are prone to acute respiratory failure. Network connectivity and causality were related to lung function and illness severity. We validated our connectivity and causality results with a mathematical model of neural network. Our findings suggest a new therapeutic strategy involving the modulation of brain activity to increase motor cortex functional connectivity and improve respiratory muscles performance in patients. Hum Brain Mapp 37:2736-2754, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  3. Increased functional connectivity with puberty in the mentalising network involved in social emotion processing

    OpenAIRE

    Klapwijk, Eduard T.; Goddings, Anne-Lise; Heyes, Stephanie Burnett; Bird, Geoffrey; Viner, Russell M; Blakemore, Sarah-Jayne

    2013-01-01

    There is increasing evidence that puberty plays an important role in the structural and functional brain development seen in adolescence, but little is known of the pubertal influence on changes in functional connectivity. We explored how pubertal indicators (salivary concentrations of testosterone, oestradiol and DHEA; pubertal stage; menarcheal status) relate to functional connectivity between components of a mentalising network identified to be engaged in social emotion processing by our p...

  4. Node Deployment Algorithm Based on Connected Tree for Underwater Sensor Networks.

    Science.gov (United States)

    Jiang, Peng; Wang, Xingmin; Jiang, Lurong

    2015-01-01

    Designing an efficient deployment method to guarantee optimal monitoring quality is one of the key topics in underwater sensor networks. At present, a realistic approach of deployment involves adjusting the depths of nodes in water. One of the typical algorithms used in such process is the self-deployment depth adjustment algorithm (SDDA). This algorithm mainly focuses on maximizing network coverage by constantly adjusting node depths to reduce coverage overlaps between two neighboring nodes, and thus, achieves good performance. However, the connectivity performance of SDDA is irresolute. In this paper, we propose a depth adjustment algorithm based on connected tree (CTDA). In CTDA, the sink node is used as the first root node to start building a connected tree. Finally, the network can be organized as a forest to maintain network connectivity. Coverage overlaps between the parent node and the child node are then reduced within each sub-tree to optimize coverage. The hierarchical strategy is used to adjust the distance between the parent node and the child node to reduce node movement. Furthermore, the silent mode is adopted to reduce communication cost. Simulations show that compared with SDDA, CTDA can achieve high connectivity with various communication ranges and different numbers of nodes. Moreover, it can realize coverage as high as that of SDDA with various sensing ranges and numbers of nodes but with less energy consumption. Simulations under sparse environments show that the connectivity and energy consumption performances of CTDA are considerably better than those of SDDA. Meanwhile, the connectivity and coverage performances of CTDA are close to those depth adjustment algorithms base on connected dominating set (CDA), which is an algorithm similar to CTDA. However, the energy consumption of CTDA is less than that of CDA, particularly in sparse underwater environments.

  5. Node Deployment Algorithm Based on Connected Tree for Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Peng Jiang

    2015-07-01

    Full Text Available Designing an efficient deployment method to guarantee optimal monitoring quality is one of the key topics in underwater sensor networks. At present, a realistic approach of deployment involves adjusting the depths of nodes in water. One of the typical algorithms used in such process is the self-deployment depth adjustment algorithm (SDDA. This algorithm mainly focuses on maximizing network coverage by constantly adjusting node depths to reduce coverage overlaps between two neighboring nodes, and thus, achieves good performance. However, the connectivity performance of SDDA is irresolute. In this paper, we propose a depth adjustment algorithm based on connected tree (CTDA. In CTDA, the sink node is used as the first root node to start building a connected tree. Finally, the network can be organized as a forest to maintain network connectivity. Coverage overlaps between the parent node and the child node are then reduced within each sub-tree to optimize coverage. The hierarchical strategy is used to adjust the distance between the parent node and the child node to reduce node movement. Furthermore, the silent mode is adopted to reduce communication cost. Simulations show that compared with SDDA, CTDA can achieve high connectivity with various communication ranges and different numbers of nodes. Moreover, it can realize coverage as high as that of SDDA with various sensing ranges and numbers of nodes but with less energy consumption. Simulations under sparse environments show that the connectivity and energy consumption performances of CTDA are considerably better than those of SDDA. Meanwhile, the connectivity and coverage performances of CTDA are close to those depth adjustment algorithms base on connected dominating set (CDA, which is an algorithm similar to CTDA. However, the energy consumption of CTDA is less than that of CDA, particularly in sparse underwater environments.

  6. Inferring the physical connectivity of complex networks from their functional dynamics

    Directory of Open Access Journals (Sweden)

    Holm Liisa

    2010-05-01

    Full Text Available Abstract Background Biological networks, such as protein-protein interactions, metabolic, signalling, transcription-regulatory networks and neural synapses, are representations of large-scale dynamic systems. The relationship between the network structure and functions remains one of the central problems in current multidisciplinary research. Significant progress has been made toward understanding the implication of topological features for the network dynamics and functions, especially in biological networks. Given observations of a network system's behaviours or measurements of its functional dynamics, what can we conclude of the details of physical connectivity of the underlying structure? Results We modelled the network system by employing a scale-free network of coupled phase oscillators. Pairwise phase coherence (PPC was calculated for all the pairs of oscillators to present functional dynamics induced by the system. At the regime of global incoherence, we observed a Significant pairwise synchronization only between two nodes that are physically connected. Right after the onset of global synchronization, disconnected nodes begin to oscillate in a correlated fashion and the PPC of two nodes, either connected or disconnected, depends on their degrees. Based on the observation of PPCs, we built a weighted network of synchronization (WNS, an all-to-all functionally connected network where each link is weighted by the PPC of two oscillators at the ends of the link. In the regime of strong coupling, we observed a Significant similarity in the organization of WNSs induced by systems sharing the same substrate network but different configurations of initial phases and intrinsic frequencies of oscillators. We reconstruct physical network from the WNS by choosing the links whose weights are higher than a given threshold. We observed an optimal reconstruction just before the onset of global synchronization. Finally, we correlated the topology of the

  7. Creativity and the default network: A functional connectivity analysis of the creative brain at rest☆

    Science.gov (United States)

    Beaty, Roger E.; Benedek, Mathias; Wilkins, Robin W.; Jauk, Emanuel; Fink, Andreas; Silvia, Paul J.; Hodges, Donald A.; Koschutnig, Karl; Neubauer, Aljoscha C.

    2014-01-01

    The present research used resting-state functional magnetic resonance imaging (fMRI) to examine whether the ability to generate creative ideas corresponds to differences in the intrinsic organization of functional networks in the brain. We examined the functional connectivity between regions commonly implicated in neuroimaging studies of divergent thinking, including the inferior prefrontal cortex and the core hubs of the default network. Participants were prescreened on a battery of divergent thinking tests and assigned to high- and low-creative groups based on task performance. Seed-based functional connectivity analysis revealed greater connectivity between the left inferior frontal gyrus (IFG) and the entire default mode network in the high-creative group. The right IFG also showed greater functional connectivity with bilateral inferior parietal cortex and the left dorsolateral prefrontal cortex in the high-creative group. The results suggest that the ability to generate creative ideas is characterized by increased functional connectivity between the inferior prefrontal cortex and the default network, pointing to a greater cooperation between brain regions associated with cognitive control and low-level imaginative processes. PMID:25245940

  8. A Layered Zone Routing Algorithm in Ad Hoc Network Based on Matrix of Adjacency Connection

    Institute of Scientific and Technical Information of China (English)

    XU Guang-wei; LI Feng; SHI Xiu-jin; HUO Jia-zhen

    2007-01-01

    The hybrid routing protocol has received more attention recently than the proactive and the reactive, especially for large-scale and highly dynamic connection, in mobile ad hoc network. A crucial reason is that zone-layered is being utilized in the complex systems. A hybrid routing algorithm which is layered zone based on adjacency connection(LZBAC) is put forward under the background of a few members in network with steady position and link. The algorithm modifies storage structure of nodes and improves routing mechanism. The theoretical analysis and simulation testing testify that the algorithm costs shorter time of route finding and less delay than others.

  9. Optical-network-connected multi-channel 96-GHz-band distributed radar system

    Science.gov (United States)

    Kanno, Atsushi; Kuri, Toshiaki; Kawanishi, Tetsuya

    2015-05-01

    The millimeter-wave (MMW) radar is a promising candidate for high-precision imaging because of its short wavelength and broad range of available bandwidths. In particular in the frequency range of 92-100 GHz, which is regulated for radiolocation, an atmospheric attenuation coefficient less than 1 dB/km limits the imaging range. Therefore, a combination of MMW radar and distributed antenna system directly connected to optical fiber networks can realize both high-precision imaging and large-area surveillance. In this paper, we demonstrate a multi-channel MMW frequency-modulated continuous-wave distributed radar system connected to an analog radio-over-fiber network.

  10. Self-Organization of Weighted Networks in Connection with the Misanthrope Process

    Institute of Scientific and Technical Information of China (English)

    MENG Qing-Kuan; ZHU Jian-Yang

    2009-01-01

    From an undirected random graph,by the weight redistribution of the edges,we obtain a weighted network.The weight redistribution of the edges can be connected to the well-known Misanthrope process,in which distinguishable particles hop among different urns.Under specific conditions,the condensation phenomena can be observed,i.e.,nearly all the edges connect to one vertex in the network.When there is no condensation,by adjusting the parameters,the strength distribution can be scale-free or exponentially decreasing.The numerical results fit well with the analytical ones.

  11. Preclinical cerebral network connectivity evidence of deficits in mild white matter lesions

    Directory of Open Access Journals (Sweden)

    Ying eLiang

    2016-02-01

    Full Text Available White matter lesions (WMLs are notable for their high prevalence and have been demonstrated to be a potential neuroimaging biomarker of early diagnosis of Alzheimer’s disease. This study aimed to identify the brain functional and structural mechanisms underlying cognitive decline observed in mild WMLs. Multi-domain cognitive tests, as well as resting-state, diffusion tensor and structural images were obtained on 42 mild WMLs and 42 age/sex-matched healthy controls. For each participant, we examined the functional connectivity of three resting-state networks related to the changed cognitive domains: the default mode network (DMN and the bilateral fronto-parietal network (FPN. We also performed voxel-based morphometry analysis to compare whole-brain gray matter volume, atlas-based quantification of the white matter tracts interconnecting the RSNs, and the relationship between functional connectivity and structural connectivity. We observed functional connectivity alterations in the DMN and the right FPN combined with related white matter integrity disruption in mild WMLs. However, no significant gray matter atrophy difference was found. Furthermore, the right precuneus functional connectivity in the DMN exhibited a significantly negative correlation with the memory test scores. Our study suggests that in mild WMLs, dysfunction of RSNs might be a consequence of decreased white matter structural connectivity, which further affects cognitive performance.

  12. Early Age-Related Functional Connectivity Decline in High-Order Cognitive Networks

    Science.gov (United States)

    Siman-Tov, Tali; Bosak, Noam; Sprecher, Elliot; Paz, Rotem; Eran, Ayelet; Aharon-Peretz, Judith; Kahn, Itamar

    2017-01-01

    As the world ages, it becomes urgent to unravel the mechanisms underlying brain aging and find ways of intervening with them. While for decades cognitive aging has been related to localized brain changes, growing attention is now being paid to alterations in distributed brain networks. Functional connectivity magnetic resonance imaging (fcMRI) has become a particularly useful tool to explore large-scale brain networks; yet, the temporal course of connectivity lifetime changes has not been established. Here, an extensive cross-sectional sample (21–85 years old, N = 887) from a public fcMRI database was used to characterize adult lifespan connectivity dynamics within and between seven brain networks: the default mode, salience, dorsal attention, fronto-parietal control, auditory, visual and motor networks. The entire cohort was divided into young (21–40 years, mean ± SD: 25.5 ± 4.8, n = 543); middle-aged (41–60 years, 50.6 ± 5.4, n = 238); and old (61 years and above, 69.0 ± 6.3, n = 106) subgroups. Correlation matrices as well as a mixed model analysis of covariance indicated that within high-order cognitive networks a considerable connectivity decline is already evident by middle adulthood. In contrast, a motor network shows increased connectivity in middle adulthood and a subsequent decline. Additionally, alterations in inter-network interactions are noticeable primarily in the transition between young and middle adulthood. These results provide evidence that aging-related neural changes start early in adult life. PMID:28119599

  13. Synaptic Dynamics and Neuronal Network Connectivity are reflected in the Distribution of Times in Up states

    Directory of Open Access Journals (Sweden)

    Khanh eDao Duc

    2015-07-01

    Full Text Available The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence times of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states.

  14. Independent functional connectivity networks underpin food and monetary reward sensitivity in excess weight.

    Science.gov (United States)

    Verdejo-Román, Juan; Fornito, Alex; Soriano-Mas, Carles; Vilar-López, Raquel; Verdejo-García, Antonio

    2017-02-01

    Overvaluation of palatable food is a primary driver of obesity, and is associated with brain regions of the reward system. However, it remains unclear if this network is specialized in food reward, or generally involved in reward processing. We used functional magnetic resonance imaging (fMRI) to characterize functional connectivity during processing of food and monetary rewards. Thirty-nine adults with excess weight and 37 adults with normal weight performed the Willingness to Pay for Food task and the Monetary Incentive Delay task in the fMRI scanner. A data-driven graph approach was applied to compare whole-brain, task-related functional connectivity between groups. Excess weight was associated with decreased functional connectivity during the processing of food rewards in a network involving primarily frontal and striatal areas, and increased functional connectivity during the processing of monetary rewards in a network involving principally frontal and parietal areas. These two networks were topologically and anatomically distinct, and were independently associated with BMI. The processing of food and monetary rewards involve segregated neural networks, and both are altered in individuals with excess weight.

  15. Application of feedback connection artificial neural network to seismic data filtering

    CERN Document Server

    Djarfour, Noureddine; Baddari, Kamel; Mihoubi, Abdelhafid; Ferahtia, Jalal; 10.1016/j.crte.2008.03.003

    2008-01-01

    The Elman artificial neural network (ANN) (feedback connection) was used for seismic data filtering. The recurrent connection that characterizes this network offers the advantage of storing values from the previous time step to be used in the current time step. The proposed structure has the advantage of training simplicity by a back-propagation algorithm (steepest descent). Several trials were addressed on synthetic (with 10% and 50% of random and Gaussian noise) and real seismic data using respectively 10 to 30 neurons and a minimum of 60 neurons in the hidden layer. Both an iteration number up to 4000 and arrest criteria were used to obtain satisfactory performances. Application of such networks on real data shows that the filtered seismic section was efficient. Adequate cross-validation test is done to ensure the performance of network on new data sets.

  16. Connecting Harbours. A comparison of traffic networks across ancient and medieval Europe

    CERN Document Server

    Preiser-Kapeller, Johannes

    2016-01-01

    Ancient and medieval harbours connected via navigable and terrestrial routes could be interpreted as elements of complex traffic networks. Based on evidence from three projects in Priority Programme 1630 (Fossa Carolina, Inland harbours in Central Europe and Byzantine harbours on the Balkan coasts) we present a pioneer study to apply concepts and tools of network theory on archaeological and on written evidence as well as to integrate this data into different network models. Our diachronic approach allows for an analysis of the temporal and spatial dynamics of webs of connectivity with a focus on the 1st millennium AD. The combination of case studies on various spatial scales as well as from regions of inland and maritime navigation (Central Europe respectively the Seas around the Balkans) allows for the identification of structural similarities respectively difference between pre-modern traffic systems across Europe. The contribution is a first step towards further adaptions of tools of network analysis as a...

  17. Impact of Beamforming on the Path Connectivity in Cognitive Radio Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Le The Dung

    2017-03-01

    Full Text Available This paper investigates the impact of using directional antennas and beamforming schemes on the connectivity of cognitive radio ad hoc networks (CRAHNs. Specifically, considering that secondary users use two kinds of directional antennas, i.e., uniform linear array (ULA and uniform circular array (UCA antennas, and two different beamforming schemes, i.e., randomized beamforming and center-directed to communicate with each other, we study the connectivity of all combination pairs of directional antennas and beamforming schemes and compare their performances to those of omnidirectional antennas. The results obtained in this paper show that, compared with omnidirectional transmission, beamforming transmission only benefits the connectivity when the density of secondary user is moderate. Moreover, the combination of UCA and randomized beamforming scheme gives the highest path connectivity in all evaluating scenarios. Finally, the number of antenna elements and degree of path loss greatly affect path connectivity in CRAHNs.

  18. Anomalous diffusion of epicentres

    CERN Document Server

    Sotolongo-Costa, Oscar; Posadas, A; Luzon, F

    2007-01-01

    The classification of earthquakes in main shocks and aftershocks by a method recently proposed by M. Baiesi and M. Paczuski allows to the generation of a complex network composed of clusters that group the most correlated events. The spatial distribution of epicentres inside these structures corresponding to the catalogue of earthquakes in the eastern region of Cuba shows anomalous anti-diffusive behaviour evidencing the attractive nature of the main shock and the possible description in terms of fractional kinetics.

  19. 婴儿完全性肺静脉异位连接的外科治疗%Surgical therapy of infants with total anomalous pulmonary venous connection

    Institute of Scientific and Technical Information of China (English)

    彭帮田; 张岩伟; 艾峰; 程兆云; 范太兵

    2014-01-01

    Objective To retrospectively summarize the strategies and effects of surgical therapy on infants with total anomalous pulmonary venous connection (TAPVC).Methods From January 2007 to April 2012,41 cases of infants with TAPVC were chosen.They were performed with surgical repairing with general anesthesia by hypothermic cardiopulmonary bypass.Twenty seven cases were treated by supracardiac anastomosis and 3 cases were treated by intracardiac anastomosis,among which 11 cases were treated by autologous pericardical expand anastomosis.As for intracardiac type,7 cases were cured by means of connecting pulmonary vein to coronary sinus,and then by cutting arterial septum and coronary sinus upper wall in the mouth of pulmonary vein,and finally using artificial materials to reconstruct interatrial septum to expand the left artrium; 1 case by linking pulmonary vein to right atrium roof,then the patients were remedied by expanding the interatrial septum defect and giving intracardiac patch.In terms of infracardiac type,2 cases were treated by cutting the pulmonary vein behind the right atrium in lengthways,and connecting the pulmonary vein to the left artrium by longitudinal anastomosis.Results Thirty-nine cases survived the operations,of whom the clinical symptoms disappeared and their physical growth improved obviously without cardiac dysfunction.Only 2 cases died in the early period (mortality rate 4.8%),1 of which died from sudden cardiac arrest as the result of pulmonary arterial hypertension crisis and 1 from low cardiac output as the result of left heart maldevelopment.The outpatient follow-up found no death case,but one case was operated twice,with no short and medium-term anastomosis stricture.Conclusions TAPVC,as an independant abnormality located in a normal heart,can be cured in babyhood with ideal effects and perfect prognosis.%目的 回顾性总结婴儿完全性肺静脉异位连接外科治疗的策略和效果.方法 2007年1月至2012年4月共收治婴

  20. Complex network analysis of brain functional connectivity under a multi-step cognitive task

    Science.gov (United States)

    Cai, Shi-Min; Chen, Wei; Liu, Dong-Bai; Tang, Ming; Chen, Xun

    2017-01-01

    Functional brain network has been widely studied to understand the relationship between brain organization and behavior. In this paper, we aim to explore the functional connectivity of brain network under a multi-step cognitive task involving consecutive behaviors, and further understand the effect of behaviors on the brain organization. The functional brain networks are constructed based on a high spatial and temporal resolution fMRI dataset and analyzed via complex network based approach. We find that at voxel level the functional brain network shows robust small-worldness and scale-free characteristics, while its assortativity and rich-club organization are slightly restricted to the order of behaviors performed. More interestingly, the functional connectivity of brain network in activated ROIs strongly correlates with behaviors and is obviously restricted to the order of behaviors performed. These empirical results suggest that the brain organization has the generic properties of small-worldness and scale-free characteristics, and its diverse functional connectivity emerging from activated ROIs is strongly driven by these behavioral activities via the plasticity of brain.

  1. The network of web 2.0 connections among state health departments: new pathways for dissemination.

    Science.gov (United States)

    Harris, Jenine K

    2013-01-01

    Most state health departments (SHDs) have adopted and are using Facebook and/or Twitter. Among the friends and followers of SHD Facebook and Twitter pages are other SHDs. These connections form networks with the potential to facilitate dissemination of evidence around effective public health practice among health departments nationwide. To better understand the composition and structure of these networks, Facebook and Twitter connections between SHDs were collected and examined. More SHDs were connected to each other on Twitter (n = 37) than on Facebook (n = 24). The Twitter network was denser (dTwitter = 0.06; dFacebook = 0.01) with more clustering (CTwitter = 0.06; CFacebook = 0.01). Larger health departments were more central in the Facebook network, whereas health departments with a longer social media presence were central on Twitter. Health departments on Twitter were also more likely to be following other health departments in the same geographic region, whereas the same was not true on Facebook. California and Florida were central in the Facebook network, whereas Minnesota, Missouri, Louisiana, and Rhode Island were central on Twitter. Overall, the Twitter network demonstrated greater potential to disseminate information quickly to a larger group of SHDs. More information is needed on the feasibility and effectiveness of using Web 2.0 for dissemination and other public health activities.

  2. An optimally evolved connective ratio of neural networks that maximizes the occurrence of synchronized bursting behavior

    Directory of Open Access Journals (Sweden)

    Dong Chao-Yi

    2012-03-01

    Full Text Available Abstract Background Synchronized bursting activity (SBA is a remarkable dynamical behavior in both ex vivo and in vivo neural networks. Investigations of the underlying structural characteristics associated with SBA are crucial to understanding the system-level regulatory mechanism of neural network behaviors. Results In this study, artificial pulsed neural networks were established using spike response models to capture fundamental dynamics of large scale ex vivo cortical networks. Network simulations with synaptic parameter perturbations showed the following two findings. (i In a network with an excitatory ratio (ER of 80-90%, its connective ratio (CR was within a range of 10-30% when the occurrence of SBA reached the highest expectation. This result was consistent with the experimental observation in ex vivo neuronal networks, which were reported to possess a matured inhibitory synaptic ratio of 10-20% and a CR of 10-30%. (ii No SBA occurred when a network does not contain any all-positive-interaction feedback loop (APFL motif. In a neural network containing APFLs, the number of APFLs presented an optimal range corresponding to the maximal occurrence of SBA, which was very similar to the optimal CR. Conclusions In a neural network, the evolutionarily selected CR (10-30% optimizes the occurrence of SBA, and APFL serves a pivotal network motif required to maximize the occurrence of SBA.

  3. Power Quality Improvement Using an Enhanced Network-Side-Shunt-Connected Dynamic Voltage Restorer

    Science.gov (United States)

    Fereidouni, Alireza; Masoum, Mohammad A. S.; Moghbel, Moayed

    2015-10-01

    Among the four basic dynamic voltage restorer (DVR) topologies, the network-side shunt-connected DVR (NSSC-DVR) has a relatively poor performance and is investigated in this paper. A new configuration is proposed and implemented for NSSC-DVR to enhance its performance in compensating (un)symmetrical deep and long voltage sags and mitigate voltage harmonics. The enhanced NSSC-DVR model includes a three-phase half-bridge semi-controlled network-side-shunt-connected rectifier and a three-phase full-bridge series-connected inverter implemented with a back-to-back configuration through a bidirectional buck-boost converter. The network-side-shunt-connected rectifier is employed to inject/draw the required energy by NSSC-DVR to restore the load voltage to its pre-fault value under sag/swell conditions. The buck-boost converter is responsible for maintaining the DC-link voltage of the series-connected inverter at its designated value in order to improve the NSSC-DVR capability in compensating deep and long voltage sags/swells. The full-bridge series-connected inverter permits to compensate unbalance voltage sags containing zero-sequence component. The harmonic compensation of the load voltage is achieved by extracting harmonics from the distorted network voltage using an artificial neural network (ANN) method called adaptive linear neuron (Adaline) strategy. Detailed simulations are performed by SIMULINK/MATLAB software for six case studies to verify the highly robustness of the proposed NSSC-DVR model under various conditions.

  4. Age-related Changes in Inter-Network Connectivity by Component Analysis

    Directory of Open Access Journals (Sweden)

    Christian eLa

    2015-12-01

    Full Text Available Healthy aging is associated with brain changes that reflect an alteration to a functional unit in response to the available resources and architecture. Even before the onset of noticeable cognitive decline, the neural scaffolds underlying cognitive function undergo considerable change. Prior studies have suggested a disruption of the connectivity pattern within the default-mode network (DMN, and more specifically a disruption of the anterio-posterior connectivity. In this study, we explored the effects of aging on within-network connectivity of three DMN subnetworks: a posterior DMN (pDMN, an anterior DMN (aDMN, and a ventral DMN (vDMN; as well as between-network connectivity during resting-state. Using groupICA on 43 young and 43 older healthy adults, we showed a reduction of network co-activation in two of the DMN subnetworks (pDMN and aDMN and demonstrated a difference in between-component connectivity levels. The older group exhibited more numerous high-correlation pairs (Pearson’s rho>0.3, # of comp-pairs = 46 in comparison to the young group (# of comp-pairs = 34, suggesting a more connected/less segregated cortical system. Moreover, three component-pairs exhibited statistically significant differences between the two populations. Visual areas V2-V1 and V2-V4 were more correlated in the older adults, while aDMN-pDMN correlation decreased with aging. The increase in the number of high-correlation component-pairs and the elevated correlation in the visual areas are consistent with the prior hypothesis that aging is associated with a reduction of functional segregation. However, the aDMN-pDMN dis-connectivity may be occurring under a different mechanism, a mechanism more related to a breakdown of structural integrity along the anterio-posterior axis.

  5. Effects of meditation experience on functional connectivity of distributed brain networks

    Directory of Open Access Journals (Sweden)

    Wendy eHasenkamp

    2012-03-01

    Full Text Available This study sought to examine the effect of meditation experience on brain networks underlying cognitive actions employed during contemplative practice. In a previous study, we proposed a basic model of naturalistic cognitive fluctuations that occur during the practice of focused attention meditation. This model specifies four intervals in a cognitive cycle: mind wandering, awareness of mind wandering, shifting of attention, and sustained attention. Using subjective input from experienced practitioners during meditation, we identified activity in salience network regions during awareness of mind wandering and executive network regions during shifting and sustained attention. Brain regions associated with the default mode were active during mind wandering. In the present study, we reasoned that repeated activation of attentional brain networks over years of practice may induce lasting functional connectivity changes within relevant circuits. To investigate this possibility, we created seeds representing the networks that were active during the four phases of the earlier study, and examined functional connectivity during the resting state in the same participants. Connectivity maps were then contrasted between participants with high vs. low meditation experience. Participants with more meditation experience exhibited increased connectivity within attentional networks, as well as between attentional regions and medial frontal regions. These neural relationships may be involved in the development of cognitive skills, such as maintaining attention and disengaging from distraction, that are often reported with meditation practice. Furthermore, because altered connectivity of brain regions in experienced meditators was observed in a non-meditative (resting state, this may represent a transference of cognitive abilities off the cushion into daily life.

  6. Obesity is marked by distinct functional connectivity in brain networks involved in food reward and salience.

    Science.gov (United States)

    Wijngaarden, M A; Veer, I M; Rombouts, S A R B; van Buchem, M A; Willems van Dijk, K; Pijl, H; van der Grond, J

    2015-01-01

    We hypothesized that brain circuits involved in reward and salience respond differently to fasting in obese versus lean individuals. We compared functional connectivity networks related to food reward and saliency after an overnight fast (baseline) and after a prolonged fast of 48 h in lean versus obese subjects. We included 13 obese (2 males, 11 females, BMI 35.4 ± 1.2 kg/m(2), age 31 ± 3 years) and 11 lean subjects (2 males, 9 females, BMI 23.2 ± 0.5 kg/m(2), age 28 ± 3 years). Resting-state functional magnetic resonance imaging scans were made after an overnight fast (baseline) and after a prolonged 48 h fast. Functional connectivity of the amygdala, hypothalamus and posterior cingulate cortex (default-mode) networks was assessed using seed-based correlations. At baseline, we found a stronger connectivity between hypothalamus and left insula in the obese subjects. This effect diminished upon the prolonged fast. After prolonged fasting, connectivity of the hypothalamus with the dorsal anterior cingulate cortex (dACC) increased in lean subjects and decreased in obese subjects. Amygdala connectivity with the ventromedial prefrontal cortex was stronger in lean subjects at baseline, which did not change upon the prolonged fast. No differences in posterior cingulate cortex connectivity were observed. In conclusion, obesity is marked by alterations in functional connectivity networks involved in food reward and salience. Prolonged fasting differentially affected hypothalamic connections with the dACC and the insula between obese and lean subjects. Our data support the idea that food reward and nutrient deprivation are differently perceived and/or processed in obesity.

  7. Non-harmful insertion of data mimicking computer network attacks

    Energy Technology Data Exchange (ETDEWEB)

    Neil, Joshua Charles; Kent, Alexander; Hash, Jr, Curtis Lee

    2016-06-21

    Non-harmful data mimicking computer network attacks may be inserted in a computer network. Anomalous real network connections may be generated between a plurality of computing systems in the network. Data mimicking an attack may also be generated. The generated data may be transmitted between the plurality of computing systems using the real network connections and measured to determine whether an attack is detected.

  8. Pentalogy of Cantrell with ectopia cordis totalis, total anomalous pulmonary venous connection, and tetralogy of Fallot: a case report and review of the literature.

    Science.gov (United States)

    Restrepo, M Santiago; Cerqua, Amanda; Turek, Joseph W

    2014-01-01

    Pentalogy of Cantrell is a rare condition with a varied expression and a high mortality. We present a patient with the classic pentad (type 1), but with a previously undescribed constellation of cardiac manifestations including ectopia cordis totalis, total anomalous pulmonary venous return, and tetralogy of Fallot. This case reminds us of the challenges associated with the management of various forms of this condition. We discuss the prenatal diagnosis, genetic basis, postnatal evaluation, and management of this entity.

  9. Reduced connectivity in the self-processing network of schizophrenia patients with poor insight.

    Directory of Open Access Journals (Sweden)

    Edith J Liemburg

    Full Text Available Lack of insight (unawareness of illness is a common and clinically relevant feature of schizophrenia. Reduced levels of self-referential processing have been proposed as a mechanism underlying poor insight. The default mode network (DMN has been implicated as a key node in the circuit for self-referential processing. We hypothesized that during resting state the DMN network would show decreased connectivity in schizophrenia patients with poor insight compared to patients with good insight. Patients with schizophrenia were recruited from mental health care centers in the north of the Netherlands and categorized in groups having good insight (n= 25 or poor insight (n = 19. All subjects underwent a resting state fMRI scan. A healthy control group (n = 30 was used as a reference. Functional connectivity of the anterior and posterior part of the DMN, identified using Independent Component Analysis, was compared between groups. Patients with poor insight showed lower connectivity of the ACC within the anterior DMN component and precuneus within the posterior DMN component compared to patients with good insight. Connectivity between the anterior and posterior part of the DMN was lower in patients than controls, and qualitatively different between the good and poor insight patient groups. As predicted, subjects with poor insight in psychosis showed decreased connectivity in DMN regions implicated in self-referential processing, although this concerned only part of the network. This finding is compatible with theories implying a role of reduced self-referential processing as a mechanism contributing to poor insight.

  10. Solution to avoid unwanted trips for PV systems connected to LV network facing voltage sags

    Energy Technology Data Exchange (ETDEWEB)

    Le Thi Minh, Chau; Tran-Quoc, Tuan; Kieny, Christophe [IDEA, Saint-Martin-d' Heres (France); Bacha, Seddik [Grenoble Electric Engineering Laboratory, Saint-Martin-d' Heres (France); Cabanac, Philippe; Grenard, Sebastien [Electricite de France, Clamart (France). Direction des Etudes et Recherches; Goulielmakis, David [Schneider Electric, Grenoble (France). Projects and Engineering Center

    2011-07-01

    Most of photovoltaic (PV) systems connected to low voltage (LV) distribution networks have a single-phase connection. The analysis of the behavior of these single-phase connection. The analysis of the behavior of these single-phase PV inverters facing voltage sags caused by short circuits is of major concern. These behaviors depend on fault types, fault location, types of grid architecture, grid protection systems (with or without auto-recloser system) and PV protection types. Therefore, the first investigation of this work is to study comprehensively the behaviors of PV systems connected to real LV networks facing voltage sags in different scenarios by taking into account the real network protection. Furthermore, future power systems with a large share of PV systems connected could be severely affected if several of the PV systems are tripping at the same instant. From these results of simulation, unwanted trip cases, due to the disconnection protection of PV systems are identified. Finally, a simple efficient solution by using the voltage-time characteristic for PV system is proposed. The validation by simulations shows the efficiency of the proposed solution. (orig.)

  11. Transient dynamics of sparsely connected Hopfield neural networks with arbitrary degree distributions

    Science.gov (United States)

    Zhang, Pan; Chen, Yong

    2008-02-01

    Using probabilistic approach, the transient dynamics of sparsely connected Hopfield neural networks is studied for arbitrary degree distributions. A recursive scheme is developed to determine the time evolution of overlap parameters. As illustrative examples, the explicit calculations of dynamics for networks with binomial, power-law, and uniform degree distribution are performed. The results are good agreement with the extensive numerical simulations. It indicates that with the same average degree, there is a gradual improvement of network performance with increasing sharpness of its degree distribution, and the most efficient degree distribution for global storage of patterns is the delta function.

  12. Adaptive Voltage Control Strategy for Variable-Speed Wind Turbine Connected to a Weak Network

    DEFF Research Database (Denmark)

    Abulanwar, Elsayed; Hu, Weihao; Chen, Zhe;

    2016-01-01

    Significant voltage fluctuations and power quality issues pose considerable constraints on the efficient integration of remotely located wind turbines into weak networks. Besides, 3p oscillations arising from the wind shear and tower shadow effects induce further voltage perturbations during...... and smoothness at the point of connection (POC) in order to maximise the wind power penetration into such networks. Intensive simulation case studies under different network topology and wind speed ranges reveal the effectiveness of the AVC scheme to effectively suppress the POC voltage variations particularly...

  13. Data-Intensive Cloud Service Provision for Research Institutes: the Network Connectivity Problem

    CERN Document Server

    Cass, Tony; CERN. Geneva. IT Department

    2016-01-01

    Much effort (and money) has been invested in recent years to ensure that academic and research sites are well interconnected with high-capacity networks that, in most cases, span national and continental boundaries. However, these dedicated research and education networks, whether national (NRENs) or trans-continental (RENs), frequently have Acceptable Use Policies (AUPs) that restrict their use by commercial entities, notably Cloud Service Providers (CSPs). After a brief summary of the issues involved, we describe three approaches to removing the network connectivity barrier that threatens to limit the ability of academic and research institutions to profit effectively from services offered by CSPs.

  14. Ad-hoc transient communities in Learning Networks Connecting and supporting the learner

    NARCIS (Netherlands)

    Brouns, Francis

    2009-01-01

    Brouns, F. (2009). Ad-hoc transient communities in Learning Networks Connecting and supporting the learner. Presentation given for Korean delegation of Chonnam National University and Dankook University (researchers dr. Jeeheon Ryu and dr. Minjeong Kim and a Group of PhD and Master students). August

  15. A geometric network model of intrinsic grey-matter connectivity of the human brain

    Science.gov (United States)

    Lo, Yi-Ping; O'Dea, Reuben; Crofts, Jonathan J.; Han, Cheol E.; Kaiser, Marcus

    2015-10-01

    Network science provides a general framework for analysing the large-scale brain networks that naturally arise from modern neuroimaging studies, and a key goal in theoretical neuroscience is to understand the extent to which these neural architectures influence the dynamical processes they sustain. To date, brain network modelling has largely been conducted at the macroscale level (i.e. white-matter tracts), despite growing evidence of the role that local grey matter architecture plays in a variety of brain disorders. Here, we present a new model of intrinsic grey matter connectivity of the human connectome. Importantly, the new model incorporates detailed information on cortical geometry to construct ‘shortcuts’ through the thickness of the cortex, thus enabling spatially distant brain regions, as measured along the cortical surface, to communicate. Our study indicates that structures based on human brain surface information differ significantly, both in terms of their topological network characteristics and activity propagation properties, when compared against a variety of alternative geometries and generative algorithms. In particular, this might help explain histological patterns of grey matter connectivity, highlighting that observed connection distances may have arisen to maximise information processing ability, and that such gains are consistent with (and enhanced by) the presence of short-cut connections.

  16. The National Broadband Network and the Challenges of Creating Connectivity in Education: The Case of Tasmania

    Science.gov (United States)

    Stack, Sue; Watson, Jane; Abbott-Chapman, Joan

    2013-01-01

    Tasmania, one of the first locations to have communities connected to the national broadband network (NBN), provided the context within which to ask significant questions about the implications of the NBN for all levels and sectors of education. This paper reports findings from a research project that developed innovative methodology to explore…

  17. Connectivity Analysis of Millimeter-Wave Device-to-Device Networks with Blockage

    Directory of Open Access Journals (Sweden)

    Haejoon Jung

    2016-01-01

    Full Text Available We consider device-to-device (D2D communications in millimeter-wave (mm Wave for the future fifth generation (5G cellular networks. While the mm Wave systems can support multiple D2D pairs simultaneously through beamforming with highly directional antenna arrays, the mm Wave channel is significantly more susceptible to blockage compared to microwave; mm Wave channel studies indicate that if line-of-sight (LoS paths are blocked, reliable mm Wave communications may not be achieved for high data-rate applications. Therefore, assuming that an outage occurs in the absence of the LoS path between two wireless devices by obstructions, we focus on connectivity of the mm Wave D2D networks. We consider two types of D2D communications: direct and indirect schemes. The connectivity performances of the two schemes are investigated in terms of (i the probability to achieve a fully connected network PFC and (ii the average number of reliably connected devices γ. Through analysis and simulation, we show that, as the network size increases, PFC and γ decrease. Also, PFC and γ decrease, when the blockage parameter increases. Moreover, simulation results indicate that the hybrid direct and indirect scheme can improve both PFC and γ up to about 35% compared to the nonhybrid scheme.

  18. Default-Mode Network Functional Connectivity in Aphasia: Therapy-Induced Neuroplasticity

    Science.gov (United States)

    Marcotte, Karine; Perlbarg, Vincent; Marrelec, Guillaume; Benali, Habib; Ansaldo, Ana Ines

    2013-01-01

    Previous research on participants with aphasia has mainly been based on standard functional neuroimaging analysis. Recent studies have shown that functional connectivity analysis can detect compensatory activity, not revealed by standard analysis. Little is known, however, about the default-mode network in aphasia. In the current study, we studied…

  19. Structural and effective connectivity reveals potential network-based influences on category-sensitive visual areas

    Directory of Open Access Journals (Sweden)

    Nicholas eFurl

    2015-05-01

    Full Text Available Visual category perception is thought to depend on brain areas that respond specifically when certain categories are viewed. These category-sensitive areas are often assumed to be modules (with some degree of processing autonomy and to act predominantly on feedforward visual input. This modular view can be complemented by a view that treats brain areas as elements within more complex networks and as influenced by network properties. This network-oriented viewpoint is emerging from studies using either diffusion tensor imaging to map structural connections or effective connectivity analyses to measure how their functional responses influence each other. This literature motivates several hypotheses that predict category-sensitive activity based on network properties. Large, long-range fiber bundles such as inferior fronto-occipital, arcuate and inferior longitudinal fasciculi are associated with behavioural recognition and could play crucial roles in conveying backward influences on visual cortex from anterior temporal and frontal areas. Such backward influences could support top-down functions such as visual search and emotion-based visual modulation. Within visual cortex itself, areas sensitive to different categories appear well-connected (e.g., face areas connect to object- and motion sensitive areas and their responses can be predicted by backward modulation. Evidence supporting these propositions remains incomplete and underscores the need for better integration of DTI and functional imaging.

  20. Public Libraries and the Internet, 2002: Internet Connectivity and Networked Services.

    Science.gov (United States)

    Bertot, John Carlo; McClure, Charles R.

    This study updated statistics about public library outlet and system Internet connectivity and network services using the 1997 public library dataset produced by the National Center for Education Statistics through the Federal-State Cooperative System. Using geographic information system-based techniques, a research team at the Florida State…

  1. Dynamics of delayed-coupled chaotic logistic maps: Influence of network topology, connectivity and delay times

    Indian Academy of Sciences (India)

    Arturo C Martí; Marcelo Ponce; Cristina Masoller

    2008-06-01

    We review our recent work on the synchronization of a network of delay-coupled maps, focusing on the interplay of the network topology and the delay times that take into account the finite velocity of propagation of interactions. We assume that the elements of the network are identical ( logistic maps in the regime where the individual maps, without coupling, evolve in a chaotic orbit) and that the coupling strengths are uniform throughout the network. We show that if the delay times are su±ciently heterogeneous, for adequate coupling strength the network synchronizes in a spatially homogeneous steady state, which is unstable for the individual maps without coupling. This synchronization behavior is referred to as `suppression of chaos by random delays' and is in contrast with the synchronization when all the interaction delay times are homogeneous, because with homogeneous delays the network synchronizes in a state where the elements display in-phase time-periodic or chaotic oscillations. We analyze the influence of the network topology considering four different types of networks: two regular (a ring-type and a ring-type with a central node) and two random (free-scale Barabasi-Albert and small-world Newman-Watts). We find that when the delay times are sufficiently heterogeneous the synchronization behavior is largely independent of the network topology but depends on the network's connectivity, i.e., on the average number of neighbors per node.

  2. Recovery schemes for different distributed connection management in generalized multi-protocol label switching networks

    Institute of Scientific and Technical Information of China (English)

    Can Wang; Yuefeng Ji

    2007-01-01

    As the wavelength division multiplexing (WDM) technology matures and the demands for bandwidth increase, survivability becomes more and more important in generalized multi-protocol label switching (GMPLS) controlled intelligent optical networks (IONs). There are great interests to study the performance of restorability under one certain connection management strategy. And studies in the problem of providing recovery from link failures under two different resource reservation schemes, forward reservation protocols (FRPs) and backward reservation protocols (BRPs), are presented. They are examined from the point of view of connection blocking probability, restorability and average recovery time. The two different connection management schemes and the survey of different recovery schemes are first presented. The performance of these recovery strategies is analyzed and compared both through theoretical analysis and simulation results. The main stressed idea is that using BRPs gives the best performance in terms of restorability and blocking probability in restorable GMPLS networks.

  3. Fatigue damage of steam turbine shaft at asynchronous connections of turbine generator to electrical network

    Science.gov (United States)

    Bovsunovsky, A. P.

    2015-07-01

    The investigations of cracks growth in the fractured turbine rotors point out at theirs fatigue nature. The main reason of turbine shafts fatigue damage is theirs periodical startups which are typical for steam turbines. Each startup of a turbine is accompanied by the connection of turbine generator to electrical network. During the connection because of the phase shift between the vector of electromotive force of turbine generator and the vector of supply-line voltage the short-term but powerful reactive shaft torque arises. This torque causes torsional vibrations and fatigue damage of turbine shafts of different intensity. Based on the 3D finite element model of turbine shaft of the steam turbine K-200-130 and the mechanical properties of rotor steel there was estimated the fatigue damage of the shaft at its torsional vibrations arising as a result of connection of turbine generator to electric network.

  4. Trusted Anonymous Authentication Scheme for Trusted Network Connection in Mobile Environment

    Directory of Open Access Journals (Sweden)

    Jun-jun Wu

    2012-09-01

    Full Text Available Technologies make the mobile terminals such as smart phones, PDAs and handsets much more powerful to access mobile network in recent years. Especially with the widely use of mobile terminals, mobile network now becomes a primary tool for daily and business interactions. However, the proliferation of mobile terminals also draws mobile malware’s attention which will do damage to the mobile terminal and further affect the security of mobile network. But the traditional access control and authentication mechanism cannot resolve such security issues. On the basis of trusted computing technology, we proposed a mobile trusted network architecture by extending the trusted network connection in mobile environment. And an improvement EAP-EHash method is used in the proposed architecture to implement authentication. We defined two service scenarios in the authentication scheme, home network authentication and roaming network authentication. The process of each scenario is described in detail. By introducing the pseudonym mechanism, our scheme can protect user identity. And the connection status not only depends on the identification process, but also the trust status of the platform. The analysis shows that our scheme benefits the properties of user identity anonymity, mutual authentication, fake agent resistance, platform integrity verification, EAP and TNC Compatible. And the ciphersuite negotiation makes our scheme more suitable for resource limited mobile terminals.

  5. Identification of MCI using optimal sparse MAR modeled effective connectivity networks.

    Science.gov (United States)

    Wee, Chong-Yaw; Li, Yang; Jie, Biao; Peng, Zi-Wen; Shen, Dinggang

    2013-01-01

    Capability of detecting causal or effective connectivity from resting-state functional magnetic resonance imaging (R-fMRI) is highly desirable for better understanding the cooperative nature of the brain. Effective connectivity provides specific dynamic temporal information of R-fMRI time series and reflects the directional causal influence of one brain region over another. These causal influences among brain regions are normally extracted based on the concept of Granger causality. Conventionally, the effective connectivity is inferred using multivariate autoregressive (MAR) modeling with default model order q = 1, considering low frequency fluctuation of R-fMRI time series. This assumption, although reduces the modeling complexity, does not guarantee the best fitting of R-fMRI time series at different brain regions. Instead of using the default model order, we propose to estimate the optimal model order based upon MAR order distribution to better characterize these causal influences at each brain region. Due to sparse nature of brain connectivity networks, an orthogonal least square (OLS) regression algorithm is incorporated to MAR modeling to minimize spurious effective connectivity. Effective connectivity networks inferred using the proposed optimal sparse MAR modeling are applied to Mild Cognitive Impairment (MCI) identification and obtained promising results, demonstrating the importance of using optimal causal relationships between brain regions for neurodegeneration disorder identification.

  6. Connectivity strategies for higher-order neural networks applied to pattern recognition

    Science.gov (United States)

    Spirkovska, Lilly; Reid, Max B.

    1990-01-01

    Different strategies for non-fully connected HONNs (higher-order neural networks) are discussed, showing that by using such strategies an input field of 128 x 128 pixels can be attained while still achieving in-plane rotation and translation-invariant recognition. These techniques allow HONNs to be used with the larger input scenes required for practical pattern-recognition applications. The number of interconnections that must be stored has been reduced by a factor of approximately 200,000 in a T/C case and about 2000 in a Space Shuttle/F-18 case by using regional connectivity. Third-order networks have been simulated using several connection strategies. The method found to work best is regional connectivity. The main advantages of this strategy are the following: (1) it considers features of various scales within the image and thus gets a better sample of what the image looks like; (2) it is invariant to shape-preserving geometric transformations, such as translation and rotation; (3) the connections are predetermined so that no extra computations are necessary during run time; and (4) it does not require any extra storage for recording which connections were formed.

  7. Optimization of Reliability of Network of Given Connectivity using Genetic Algorithm

    CERN Document Server

    Lam, Ho Tat

    2014-01-01

    Reliability is one of the important measures of how well the system meets its design objective, and mathematically is the probability that a system will perform satisfactorily for at least a given period of time. When the system is described by a connected network of N components (nodes) and their L connection (links), the reliability of the system becomes a difficult network design problem which solutions are of great practical interest in science and engineering. This paper discusses the numerical method of finding the most reliable network for a given N and L using genetic algorithm. For a given topology of the network, the reliability is numerically computed using adjacency matrix. For a search in the space of all possible topologies of the connected network with N nodes and L links, genetic operators such as mutation and crossover are applied to the adjacency matrix through a string representation. In the context of graphs, the mutation of strings in genetic algorithm corresponds to the rewiring of graph...

  8. Linear Approach for Synchronous State Stability in Fully Connected PLL Networks

    Directory of Open Access Journals (Sweden)

    Luiz H. A. Monteiro

    2008-03-01

    Full Text Available Synchronization is an essential feature for the use of digital systems in telecommunication networks, integrated circuits, and manufacturing automation. Formerly, master-slave (MS architectures, with precise master clock generators sending signals to phase-locked loops (PLLs working as slave oscillators, were considered the best solution. Nowadays, the development of wireless networks with dynamical connectivity and the increase of the size and the operation frequency of integrated circuits suggest that the distribution of clock signals could be more efficient if distributed solutions with fully connected oscillators are used. Here, fully connected networks with second-order PLLs as nodes are considered. In previous work, how the synchronous state frequency for this type of network depends on the node parameters and delays was studied and an expression for the long-term frequency was derived (Piqueira, 2006. Here, by taking the first term of the Taylor series expansion for the dynamical system description, it is shown that for a generic network with N nodes, the synchronous state is locally asymptotically stable.

  9. Optimal Operation of Network-Connected Combined Heat and Powers for Customer Profit Maximization

    Directory of Open Access Journals (Sweden)

    Da Xie

    2016-06-01

    Full Text Available Network-connected combined heat and powers (CHPs, owned by a community, can export surplus heat and electricity to corresponding heat and electric networks after community loads are satisfied. This paper proposes a new optimization model for network-connected CHP operation. Both CHPs’ overall efficiency and heat to electricity ratio (HTER are assumed to vary with loading levels. Based on different energy flow scenarios where heat and electricity are exported to the network from the community or imported, four profit models are established accordingly. They reflect the different relationships between CHP energy supply and community load demand across time. A discrete optimization model is then developed to maximize the profit for the community. The models are derived from the intervals determined by the daily operation modes of CHP and real-time buying and selling prices of heat, electricity and natural gas. By demonstrating the proposed models on a 1 MW network-connected CHP, results show that the community profits are maximized in energy markets. Thus, the proposed optimization approach can help customers to devise optimal CHP operating strategies for maximizing benefits.

  10. Lagrangian Flow networks: a new way to characterize transport and connectivity in geophysical flows

    Science.gov (United States)

    Ser-Giacomi, Enrico; Hernandez-Garcia, Emilio; Lopez, Cristobal; Rossi, Vincent; Vasile, Ruggero

    2015-04-01

    Water and air transport are among the basic processes shaping the climate of our planet. Heat and salinity fluxes change sea water density, and thus drive the global thermohaline circulation. Atmospheric winds force the ocean motion, and also transport moisture, heat or chemicals, impacting the regional climate. We describe transport among different regions of the ocean or the atmosphere by flow networks, giving a discrete and robust representation of the fluid advection dynamics. We use network-theory tools to gain insights into transport problem. Local and global features of the networks are extracted from many numerical experiments to give a time averaged description of the system. Classical concepts like dispersion, mixing and connectivity are finally related to a set of network-like objects contributing to build a "dictionary" between network measures and physical quantities in geophysical flows.

  11. Change in network connectivity during fictive-gasping generation in hypoxia: Prevention by a metabolic intermediate

    Directory of Open Access Journals (Sweden)

    Andrés eNieto-Posadas

    2014-07-01

    Full Text Available The neuronal circuit in charge of generating the respiratory rhythms, localized in the pre-Bötzinger complex (preBötC, is configured to produce fictive-eupnea during normoxia and reconfigures to produce fictive-gasping during hypoxic conditions in vitro. The mechanisms involved in such reconfiguration have been extensively investigated by cell-focused studies, but the actual changes at the network level remain elusive. Since a failure to generate gasping has been linked to Sudden Infant Death Syndrome, the study of gasping generation and pharmacological approaches to promote it may have clinical relevance. Here, we study the changes in network dynamics and circuit reconfiguration that occur during the transition to fictive-gasping generation in the brainstem slice preparation by recording the preBötC with multi-electrode arrays and assessing correlated firing among respiratory neurons or clusters of respiratory neurons (multiunits. We studied whether the respiratory network reconfiguration in hypoxia involves changes in either the number of active respiratory elements, the number of functional connections among elements, or the strength of these connections. Moreover, we tested the influence of isocitrate, a Krebs cycle intermediate that has recently been shown to promote breathing, on the configuration of the preBötC circuit during normoxia and on its reconfiguration during hypoxia. We found that, in contrast to previous suggestions based on cell-focused studies, the number and the overall activity of respiratory neurons change only slightly during hypoxia. However, hypoxia induces a reduction in the strength of functional connectivity within the circuit without reducing the number of connections. Isocitrate prevented this reduction during hypoxia while increasing the strength of network connectivity. In conclusion, we provide an overview of the configuration of the respiratory network under control conditions and how it is reconfigured

  12. Adaptive Connectivity Restoration from Node Failure(s) in Wireless Sensor Networks.

    Science.gov (United States)

    Wang, Huaiyuan; Ding, Xu; Huang, Cheng; Wu, Xiaobei

    2016-09-28

    Recently, there is a growing interest in the applications of wireless sensor networks (WSNs). A set of sensor nodes is deployed in order to collectively survey an area of interest and/or perform specific surveillance tasks in some of the applications, such as battlefield reconnaissance. Due to the harsh deployment environments and limited energy supply, nodes may fail, which impacts the connectivity of the whole network. Since a single node failure (cut-vertex) will destroy the connectivity and divide the network into disjoint blocks, most of the existing studies focus on the problem of single node failure. However, the failure of multiple nodes would be a disaster to the whole network and must be repaired effectively. Only few studies are proposed to handle the problem of multiple cut-vertex failures, which is a special case of multiple node failures. Therefore, this paper proposes a comprehensive solution to address the problems of node failure (single and multiple). Collaborative Single Node Failure Restoration algorithm (CSFR) is presented to solve the problem of single node failure only with cooperative communication, but CSFR-M, which is the extension of CSFR, handles the single node failure problem more effectively with node motion. Moreover, Collaborative Connectivity Restoration Algorithm (CCRA) is proposed on the basis of cooperative communication and node maneuverability to restore network connectivity after multiple nodes fail. CSFR-M and CCRA are reactive methods that initiate the connectivity restoration after detecting the node failure(s). In order to further minimize the energy dissipation, CCRA opts to simplify the recovery process by gridding. Moreover, the distance that an individual node needs to travel during recovery is reduced by choosing the nearest suitable candidates. Finally, extensive simulations validate the performance of CSFR, CSFR-M and CCRA.

  13. Altered causal connectivity of resting state brain networks in amnesic MCI.

    Directory of Open Access Journals (Sweden)

    Peipeng Liang

    Full Text Available Most neuroimaging studies of resting state networks in amnesic mild cognitive impairment (aMCI have concentrated on functional connectivity (FC based on instantaneous correlation in a single network. The purpose of the current study was to investigate effective connectivity in aMCI patients based on Granger causality of four important networks at resting state derived from functional magnetic resonance imaging data--default mode network (DMN, hippocampal cortical memory network (HCMN, dorsal attention network (DAN and fronto-parietal control network (FPCN. Structural and functional MRI data were collected from 16 aMCI patients and 16 age, gender-matched healthy controls. Correlation-purged Granger causality analysis was used, taking gray matter atrophy as covariates, to compare the group difference between aMCI patients and healthy controls. We found that the causal connectivity between networks in aMCI patients was significantly altered with both increases and decreases in the aMCI group as compared to healthy controls. Some alterations were significantly correlated with the disease severity as measured by mini-mental state examination (MMSE, and California verbal learning test (CVLT scores. When the whole-brain signal averaged over the entire brain was used as a nuisance co-variate, the within-group maps were significantly altered while the between-group difference maps did not. These results suggest that the alterations in causal influences may be one of the possible underlying substrates of cognitive impairments in aMCI. The present study extends and complements previous FC studies and demonstrates the coexistence of causal disconnection and compensation in aMCI patients, and thus might provide insights into biological mechanism of the disease.

  14. Local topological modeling of glass structure and radiation-induced rearrangements in connected networks

    Energy Technology Data Exchange (ETDEWEB)

    Hobbs, L.W. [Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, Cambridge, MA (United States); Jesurum, C.E. [Massachusetts Institute of Technology, Dept. of Mathematics, Cambridge, MA (United States); Pulim, V. [Massachusetts Institute of Technology, Lab. for Computer Science, Cambridge, MA (United States)

    1997-07-01

    Topology is shown to govern the arrangement of connected structural elements in network glasses such as silica and related radiation-amorphized network compounds: A topological description of such topologically-disordered arrangements is possible which utilizes a characteristic unit of structure--the local cluster--not far in scale from the unit cells in crystalline arrangements. Construction of credible glass network structures and their aberration during cascade disordering events during irradiation can be effected using local assembly rules based on modification of connectivity-based assembly rules derived for crystalline analogues. These topological approaches may provide useful complementary information to that supplied by molecular dynamics about re-ordering routes and final configurations in irradiated glasses. (authors)

  15. A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks.

    Science.gov (United States)

    Lee, JongHyup; Pak, Dohyun

    2016-08-29

    For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections.

  16. A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    JongHyup Lee

    2016-08-01

    Full Text Available For practical deployment of wireless sensor networks (WSN, WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections.

  17. Construction of Pipelined Strategic Connected Dominating Set for Mobile Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Ceronmani Sharmila

    2016-06-01

    Full Text Available Efficient routing between nodes is the most important challenge in a Mobile Ad Hoc Network (MANET. A Connected Dominating Set (CDS acts as a virtual backbone for routing in a MANET. Hence, the construction of CDS based on the need and its application plays a vital role in the applications of MANET. The PipeLined Strategic CDS (PLS-CDS is constructed based on strategy, dynamic diameter and transmission range. The strategy used for selecting the starting node is, any source node in the network, which has its entire destination within a virtual pipelined coverage, instead of the node with maximum connectivity. The other nodes are then selected based on density and velocity. The proposed CDS also utilizes the energy of the nodes in the network in an optimized manner. Simulation results showed that the proposed algorithm is better in terms of size of the CDS and average hop per path length.

  18. The Role of Delay and Connectivity in Throughput Reduction of Cooperative Decentralized Wireless Networks

    Directory of Open Access Journals (Sweden)

    Ahmed Alkhayyat

    2015-01-01

    Full Text Available We proposed a multiple relay selection protocol for decentralized wireless networks. The proposed relays selection protocol aims to address three issues: (1 selecting relays within the coverage area of the source and destination to ensure that the relays are positioned one hop away from the destination, (2 ensuring that the best node (best relays with less distance and attenuation from the destination access the channel first, and (3 ensuring that the proposed relays selection is collision-free. Our analysis also considers three important characteristics of decentralized wireless networks that are directly affected by cooperation: delay, connectivity, and throughput. The main goal of this paper is to demonstrate that improving connectivity and increasing number of relays reduce the throughput of cooperative decentralized wireless networks; consequently, a trade-off equation has been derived.

  19. Alteration of long-distance functional connectivity and network topology in patients with supratentorial gliomas

    Energy Technology Data Exchange (ETDEWEB)

    Park, Ji Eun; Kim, Ho Sung; Kim, Sang Joon; Shim, Woo Hyun [University of Ulsan College of Medicine, Department of Radiology and Research Institute of Radiology, Asan Medical Center, Songpa-Gu, Seoul (Korea, Republic of); Kim, Jeong Hoon [University of Ulsan College of Medicine, Department of Neurosurgery, Asan Medical Center, Seoul (Korea, Republic of)

    2016-03-15

    The need for information regarding functional alterations in patients with brain gliomas is increasing, but little is known about the functional consequences of focal brain tumors throughout the entire brain. Using resting-state functional MR imaging (rs-fMRI), this study assessed functional connectivity in patients with supratentorial brain gliomas with possible alterations in long-distance connectivity and network topology. Data from 36 patients with supratentorial brain gliomas and 12 healthy subjects were acquired using rs-fMRI. The functional connectivity matrix (FCM) was created using 32 pairs of cortical seeds on Talairach coordinates in each individual subject. Local and distant connectivity were calculated using z-scores in the individual patient's FCM, and the averaged FCM of patients was compared with that of healthy subjects. Weighted network analysis was performed by calculating local efficiency, global efficiency, clustering coefficient, and small-world topology, and compared between patients and healthy controls. When comparing the averaged FCM of patients with that of healthy controls, the patients showed decreased long-distance, inter-hemispheric connectivity (0.32 ± 0.16 in patients vs. 0. 42 ± 0.15 in healthy controls, p = 0.04). In network analysis, patients showed increased local efficiency (p < 0.05), but global efficiency, clustering coefficient, and small-world topology were relatively preserved compared to healthy subjects. Patients with supratentorial brain gliomas showed decreased long-distance connectivity while increased local efficiency and preserved small-world topology. The results of this small case series may provide a better understanding of the alterations of functional connectivity in patients with brain gliomas across the whole brain scale. (orig.)

  20. Disruption of functional networks in dyslexia: A whole-brain, data-driven analysis of connectivity

    Science.gov (United States)

    Finn, Emily S.; Shen, Xilin; Holahan, John M.; Scheinost, Dustin; Lacadie, Cheryl; Papademetris, Xenophon; Shaywitz, Sally E.; Shaywitz, Bennett A.; Constable, R. Todd

    2013-01-01

    Background Functional connectivity analyses of fMRI data are a powerful tool for characterizing brain networks and how they are disrupted in neural disorders. However, many such analyses examine only one or a small number of a priori seed regions. Studies that consider the whole brain frequently rely on anatomic atlases to define network nodes, which may result in mixing distinct activation timecourses within a single node. Here, we improve upon previous methods by using a data-driven brain parcellation to compare connectivity profiles of dyslexic (DYS) versus non-impaired (NI) readers in the first whole-brain functional connectivity analysis of dyslexia. Methods Whole-brain connectivity was assessed in children (n = 75; 43 NI, 32 DYS) and adult (n = 104; 64 NI, 40 DYS) readers. Results Compared to NI readers, DYS readers showed divergent connectivity within the visual pathway and between visual association areas and prefrontal attention areas; increased right-hemisphere connectivity; reduced connectivity in the visual word-form area (part of the left fusiform gyrus specialized for printed words); and persistent connectivity to anterior language regions around the inferior frontal gyrus. Conclusions Together, findings suggest that NI readers are better able to integrate visual information and modulate their attention to visual stimuli, allowing them to recognize words based on their visual properties, while DYS readers recruit altered reading circuits and rely on laborious phonology-based “sounding out” strategies into adulthood. These results deepen our understanding of the neural basis of dyslexia and highlight the importance of synchrony between diverse brain regions for successful reading. PMID:24124929

  1. Hyperthermia-induced disruption of functional connectivity in the human brain network.

    Directory of Open Access Journals (Sweden)

    Gang Sun

    Full Text Available BACKGROUND: Passive hyperthermia is a potential risk factor to human cognitive performance and work behavior in many extreme work environments. Previous studies have demonstrated significant effects of passive hyperthermia on human cognitive performance and work behavior. However, there is a lack of a clear understanding of the exact affected brain regions and inter-regional connectivities. METHODOLOGY AND PRINCIPAL FINDINGS: We simulated 1 hour environmental heat exposure to thirty-six participants under two environmental temperature conditions (25 °C and 50 °C, and collected resting-state functional brain activity. The functional connectivities with a preselected region of interest (ROI in the posterior cingulate cortex and precuneus (PCC/PCu, furthermore, inter-regional connectivities throughout the entire brain using a prior Anatomical Automatic Labeling (AAL atlas were calculated. We identified decreased correlations of a set of regions with the PCC/PCu, including the medial orbitofrontal cortex (mOFC and bilateral medial temporal cortex, as well as increased correlations with the partial orbitofrontal cortex particularly in the bilateral orbital superior frontal gyrus. Compared with the normal control (NC group, the hyperthermia (HT group showed 65 disturbed functional connectivities with 50 of them being decreased and 15 of them being increased. While the decreased correlations mainly involved with the mOFC, temporal lobe and occipital lobe, increased correlations were mainly located within the limbic system. In consideration of physiological system changes, we explored the correlations of the number of significantly altered inter-regional connectivities with differential rectal temperatures and weight loss, but failed to obtain significant correlations. More importantly, during the attention network test (ANT we found that the number of significantly altered functional connectivities was positively correlated with an increase in

  2. System Architecture of HatterHealthConnect: An Integration of Body Sensor Networks and Social Networks to Improve Health Awareness

    Directory of Open Access Journals (Sweden)

    Hala ElAarag

    2013-04-01

    Full Text Available Over the last decade, the demand for efficient healthcare monitoring has increased and forced the healthand wellness industry to embrace modern technological advances. Body Sensor Networks, or BSNs, canremotely collect users data and upload vital statistics to servers over the Internet. Advances in wirelesstechnologies such as cellular devices and Bluetooth increase the mobility users experience while wearing abody sensor network. When connected by the proper framework, BSNs can efficiently monitor and recorddata while minimizing the energy expenditure of nodes in the BSN. Social networking sites play a large rolein the aggregation and sharing of data between many users. Connecting a BSN to a social network createsthe unique ability to share health related data with other users through social interaction. In this research,we present an integration of BSNs and social networks to establish a community promoting well being andgreat social awareness. We present the system architecture; both hardware and software, of a prototypeimplementation using Zephyr HxM heart monitor, Intel-Shimmer EMG senor and a Samsung Captivatesmart phone. We provide implementation details for the design on the base station, the database server andthe Facebook application. We illustrate how the Android application was designed with both functionalityand user perspective in mind that resulted in an easy to use system. This prototype can be used in multiplehealth related applications based on the type of sensors used.

  3. The contribution of reserves and anthropogenic habitat for functional connectivity and resilience of ephemeral wetland networks

    Science.gov (United States)

    Allen, C. R.; Uden, D.; Angeler, D.; Hellman, M.

    2015-12-01

    Functional connectivity of reserves and other suitable habitat patches is crucial for persistence of spatially structured populations, and therefore for resilience. To maintain or increase connectivity at spatial scales larger than individual patches, conservation actions may focus on creating and maintaining reserves or influencing management actions taken on non-reserves. We assess functional connectivity of isolated wetlands within an intensively managed agricultural matrix. Using a graph-theoretic approach, we assessed the functional connectivity and spatial distribution of wetlands in the Rainwater Basins, Nebraska, U.S.A. at four assumed anuran dispersal distances. We compare the contemporary wetlands landscape to the historical landscape and putative future landscapes and evaluate the importance of individual and aggregated reserve and non-reserve wetlands for maintaining connectivity. Connectivity was greatest in the historical landscape, where wetlands were also the most densely distributed. The construction of irrigation reuse pits for water storage has substantially increased connectivity in the current landscape, but because their distribution is more uniform than historical wetlands, larger and longer-dispersing species may be favored over smaller, shorter-dispersing species. Because of their relatively low number, wetland reserves did not affect connectivity as greatly as non-reserve wetlands or irrigation reuse pits; however, they provide the highest-quality anuran habitat. Future levels of connectivity in the region will be directly impacted by the planned removal of irrigation reuse pits, and on non-reserve wetlands. Multi-scale spatial and temporal assessments of the effects of landuse change and conservation actions on landscape connectivity may be used to direct and prioritize conservation actions, and should also be useful for reserve network and landscape resilience assessments.

  4. Altered functional connectivity of the language network in ASD: Role of classical language areas and cerebellum

    Directory of Open Access Journals (Sweden)

    Marjolein Verly

    2014-01-01

    Full Text Available The development of language, social interaction and communicative skills is remarkably different in the child with autism spectrum disorder (ASD. Atypical brain connectivity has frequently been reported in this patient population. However, the neural correlates underlying their disrupted language development and functioning are still poorly understood. Using resting state fMRI, we investigated the functional connectivity properties of the language network in a group of ASD patients with clear comorbid language impairment (ASD-LI; N = 19 and compared them to the language related connectivity properties of 23 age-matched typically developing children. A verb generation task was used to determine language components commonly active in both groups. Eight joint language components were identified and subsequently used as seeds in a resting state analysis. Interestingly, both the interregional and the seed-based whole brain connectivity analysis showed preserved connectivity between the classical intrahemispheric language centers, Wernicke's and Broca's areas. In contrast however, a marked loss of functional connectivity was found between the right cerebellar region and the supratentorial regulatory language areas. Also, the connectivity between the interhemispheric Broca regions and modulatory control dorsolateral prefrontal region was found to be decreased. This disruption of normal modulatory control and automation function by the cerebellum may underlie the abnormal language function in children with ASD-LI.

  5. Escitalopram Decreases Cross-Regional Functional Connectivity within the Default-Mode Network.

    Directory of Open Access Journals (Sweden)

    Vincent van de Ven

    Full Text Available The default-mode network (DMN, which comprises medial frontal, temporal and parietal regions, is part of the brain's intrinsic organization. The serotonergic (5-HT neurotransmitter system projects to DMN regions from midbrain efferents, and manipulation of this system could thus reveal insights into the neurobiological mechanisms of DMN functioning. Here, we investigate intrinsic functional connectivity of the DMN as a function of activity of the serotonergic system, through the administration of the selective serotonin reuptake inhibitor (SSRI escitalopram. We quantified DMN functional connectivity using an approach based on dual-regression. Specifically, we decomposed group data of a subset of the functional time series using spatial independent component analysis, and projected the group spatial modes to the same and an independent resting state time series of individual participants. We found no effects of escitalopram on global functional connectivity of the DMN at the map-level; that is, escitalopram did not alter the global functional architecture of the DMN. However, we found that escitalopram decreased DMN regional pairwise connectivity, which included anterior and posterior cingulate cortex, hippocampal complex and lateral parietal regions. Further, regional DMN connectivity covaried with alertness ratings across participants. Our findings show that escitalopram altered intrinsic regional DMN connectivity, which suggests that the serotonergic system plays an important role in DMN connectivity and its contribution to cognition. Pharmacological challenge designs may be a useful addition to resting-state functional MRI to investigate intrinsic brain functional organization.

  6. Who Is the Best Connected Scientist?A Study of Scientific Coauthorship Networks

    Science.gov (United States)

    Newman, Mark E. J.

    Using data from computer databases of scientific papers in physics, biomedical research, and computer science, we have constructed networks of collaboration between scientists in each of these disciplines. In these networks two scientists are considered connected if they have coauthored one or more papers together. We have studied many statistical properties of our networks, including numbers of papers written by authors, numbers of authors per paper, numbers of collaborators that scientists have, typical distance through the network from one scientist to another, and a variety of measures of connectedness within a network, such as closeness and betweenness. We further argue that simple networks such as these cannot capture the variation in the strength of collaborative ties and propose a measure of this strength based on the number of papers coauthored by pairs of scientists, and the number of other scientists with whom they worked on those papers. Using a selection of our results, we suggest a variety of possible ways to answer the question Who is the best connected scientist?

  7. A Secure 3-Way Routing Protocols for Intermittently Connected Mobile Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Ramesh Sekaran

    2014-01-01

    Full Text Available The mobile ad hoc network may be partially connected or it may be disconnected in nature and these forms of networks are termed intermittently connected mobile ad hoc network (ICMANET. The routing in such disconnected network is commonly an arduous task. Many routing protocols have been proposed for routing in ICMANET since decades. The routing techniques in existence for ICMANET are, namely, flooding, epidemic, probabilistic, copy case, spray and wait, and so forth. These techniques achieve an effective routing with minimum latency, higher delivery ratio, lesser overhead, and so forth. Though these techniques generate effective results, in this paper, we propose novel routing algorithms grounded on agent and cryptographic techniques, namely, location dissemination service (LoDiS routing with agent AES, A-LoDiS with agent AES routing, and B-LoDiS with agent AES routing, ensuring optimal results with respect to various network routing parameters. The algorithm along with efficient routing ensures higher degree of security. The security level is cited testing with respect to possibility of malicious nodes into the network. This paper also aids, with the comparative results of proposed algorithms, for secure routing in ICMANET.

  8. A secure 3-way routing protocols for intermittently connected mobile ad hoc networks.

    Science.gov (United States)

    Sekaran, Ramesh; Parasuraman, Ganesh Kumar

    2014-01-01

    The mobile ad hoc network may be partially connected or it may be disconnected in nature and these forms of networks are termed intermittently connected mobile ad hoc network (ICMANET). The routing in such disconnected network is commonly an arduous task. Many routing protocols have been proposed for routing in ICMANET since decades. The routing techniques in existence for ICMANET are, namely, flooding, epidemic, probabilistic, copy case, spray and wait, and so forth. These techniques achieve an effective routing with minimum latency, higher delivery ratio, lesser overhead, and so forth. Though these techniques generate effective results, in this paper, we propose novel routing algorithms grounded on agent and cryptographic techniques, namely, location dissemination service (LoDiS) routing with agent AES, A-LoDiS with agent AES routing, and B-LoDiS with agent AES routing, ensuring optimal results with respect to various network routing parameters. The algorithm along with efficient routing ensures higher degree of security. The security level is cited testing with respect to possibility of malicious nodes into the network. This paper also aids, with the comparative results of proposed algorithms, for secure routing in ICMANET.

  9. Torus–Connected Cycles: A Simple and Scalable Topology for Interconnection Networks

    Directory of Open Access Journals (Sweden)

    Bossard Antoine

    2015-12-01

    Full Text Available Supercomputers are today made up of hundreds of thousands of nodes. The interconnection network is responsible for connecting all these nodes to each other. Different interconnection networks have been proposed; high performance topologies have been introduced as a replacement for the conventional topologies of recent decades. A high order, a low degree and a small diameter are the usual properties aimed for by such topologies. However, this is not sufficient to lead to actual hardware implementations. Network scalability and topology simplicity are two critical parameters, and they are two of the reasons why modern supercomputers are often based on torus interconnection networks (e.g., Fujitsu K, IBM Sequoia. In this paper we first describe a new topology, torus-connected cycles (TCCs, realizing a combination of a torus and a ring, thus retaining interesting properties of torus networks in addition to those of hierarchical interconnection networks (HINs. Then, we formally establish the diameter of a TCC, and deduce a point-to-point routing algorithm. Next, we propose routing algorithms solving the Hamiltonian cycle problem, and, in a two dimensional TCC, the Hamiltonian path one. Correctness and complexities are formally proved. The proposed algorithms are time-optimal.

  10. Simulation of Two High Pressure Distribution Network Operation in one-Network Connection

    Directory of Open Access Journals (Sweden)

    Perju Sorin

    2014-09-01

    Full Text Available The programs developed by the water supply system operators in view of metering the branches and reducing the potable water losses from the distribution network pipes lead to the performance reassessment of these networks. As a result the energetic consumption of the pumping stations should meet the accepted limits. An essential role in the evaluation of the operation parameters of the network performance is played by hydraulic modeling, by means of which the network performance simulation can be done in different scenarios. The present article describes the concept of two high-pressure network coupling. These networks are supplied by two repumping stations, in which the water flows were drastically reduced due to the present situation

  11. Global terrestrial water storage connectivity revealed using complex climate network analyses

    Directory of Open Access Journals (Sweden)

    A. Y. Sun

    2015-04-01

    Full Text Available Terrestrial water storage (TWS exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationships exist between precipitation and TWS, the latter also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and hydrologic cycle, but also provide new model calibration constraints for improving the current land surface models. In this work, the connectivity of TWS is quantified using the climate network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS datasets, a remote-sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE satellite mission, and a model-generated dataset from the global land data assimilation system's NOAH model (GLDAS-NOAH. Both datasets have 1 ° × 1 ° resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a statistical cutoff threshold to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show TWS hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two datasets indicate that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide important insights for constraining land surface models, especially in data sparse regions.

  12. Dual Connectivity in Heterogeneous Small Cell Networks with mmWave Backhauls

    Directory of Open Access Journals (Sweden)

    Wooseong Kim

    2016-01-01

    Full Text Available Ultradense Network (UDN with small cells is a key feature to begin a new era of 5G communication, which provides higher data rate, and accommodate explosive mobile traffic. Recently, mmWave-based wireless backhauls accelerate deployment of the UDN by reducing cost of fiber-optic cabling to small cells. The small cells can deliver user data to macro enhanced NodeBs (eNBs using multihop relay in wireless backhaul mesh that consists of small and macro cell eNBs connected by the mmWave links. For such a heterogeneous small cell network (HetNet, 3GPP introduced dual connectivity (i.e., dual connections to macro and small cell eNBs, which is an attractive standard feature to manage user mobility and network access in the small cells. In this paper, we exploit dual connectivity scheme in a HetNet with the mmWave-based backhaul mesh which introduces two main challenges for throughput maximization, multihop routing from small to macro cell, and selection of a small cell eNB for user equipment (UE. We establish an optimization model and find an optimal solution in terms of throughput and fairness using an IBM CPLEX solver. Additionally, we propose a heuristic algorithm for complexity reduction and compare it with the optimal results in evaluation.

  13. A new approach for effectively determining fracture network connections in fractured rocks using R tree indexing

    Institute of Scientific and Technical Information of China (English)

    LIU Hua-mei; WANG Ming-yu; SONG Xian-feng

    2011-01-01

    Determinations of fracture network connections would help the investigators remove those “meaningless” no-flow-passing fractures,providing an updated and more effective fracture network that could considerably improve the computation efficiency in the pertinent numerical simulations of fluid flow and solute transport.The effective algorithms with higher computational efficiency are needed to accomplish this task in large-scale fractured rock masses.A new approach using R tree indexing was proposed for determining fracture connection in 3D stochastically distributed fracture network.By comparing with the traditional exhaustion algorithm,it was observed that from the simulation results,this approach was much more effective; and the more the fractures were investigated,the more obvious the advantages of the approach were.Furthermore,it was indicated that the runtime used for creating the R tree indexing has a major part in the total of the runtime used for calculating Minimum Bounding Rectangles(MBRs),creating the R tree indexing,precisely finding out fracture intersections,and identifying flow paths,which are four important steps to determine fracture connections.This proposed approach for the determination of fracture connections in three-dimensional fractured rocks are expected to provide efficient preprocessing and critical database for practically accomplishing numerical computation of fluid flow and solute transport in large-scale fractured rock masses.

  14. Functional connectivity in task-negative network of the Deaf: effects of sign language experience.

    Science.gov (United States)

    Malaia, Evie; Talavage, Thomas M; Wilbur, Ronnie B

    2014-01-01

    Prior studies investigating cortical processing in Deaf signers suggest that life-long experience with sign language and/or auditory deprivation may alter the brain's anatomical structure and the function of brain regions typically recruited for auditory processing (Emmorey et al., 2010; Pénicaud et al., 2013 inter alia). We report the first investigation of the task-negative network in Deaf signers and its functional connectivity-the temporal correlations among spatially remote neurophysiological events. We show that Deaf signers manifest increased functional connectivity between posterior cingulate/precuneus and left medial temporal gyrus (MTG), but also inferior parietal lobe and medial temporal gyrus in the right hemisphere- areas that have been found to show functional recruitment specifically during sign language processing. These findings suggest that the organization of the brain at the level of inter-network connectivity is likely affected by experience with processing visual language, although sensory deprivation could be another source of the difference. We hypothesize that connectivity alterations in the task negative network reflect predictive/automatized processing of the visual signal.

  15. A mixed connection recovery strategy for surviving dual link failure in WDM networks

    Science.gov (United States)

    Yadav, Dharmendra Singh; Rana, Santosh; Prakash, Shashi

    2013-03-01

    As the size and complexity of a network increases, the probability of a dual link failure also increases. For recovering the dual link failures, two strategies have been presented in past. As per the first strategy, SPP-MAS (Shared Path Protection-Maximum Allowable Sharing), the sharing of backup lightpaths in SPP (Shared Path Protection) has been reduced, and in the second strategy TBPS (Two Backup Path Shared), the reservation of two backup lightpaths for each primary lightpath has been undertaken. The main flaw of these strategies is the requirement of redundant network resources towards the establishment of backup lightpaths, and the occurrence of trap problem after the second link fails. To minimize the redundant backup resources and the trap problem, a mixed connection recovery algorithm namely Adaptive Backup Routing over Reserved Resources (ABRRR) has been proposed. The design of ABRRR takes leverage of both, the pre-planned, and the post-failure connection recovery mechanisms. In ABRRR, the failed connections are re-provisioned adaptively over the pre-allocated backup network resources. Adaptive re-provisioning of the failed connection minimizes the trap problem. Using simulation experiments, we undertake a comparative study of the proposed strategy with the existing strategies (i.e. SPP-MAS and TBPS) under the network parameters of Blocking Probability, Dual Restorability, and Resource Utilization Ratio (RUR). Detailed investigations establish that the use of ABRRR leads to lower Blocking Probability, higher Dual Restorability, and minimized RUR compared to the existing strategies. Results also show that the proposed strategy not only survives more connections but also utilizes fewer numbers of resources compared to the existing strategies.

  16. Patients with fibromyalgia display less functional connectivity in the brain’s pain inhibitory network

    Directory of Open Access Journals (Sweden)

    Jensen Karin B

    2012-04-01

    Full Text Available Abstract Background There is evidence for augmented processing of pain and impaired endogenous pain inhibition in Fibromyalgia syndrome (FM. In order to fully understand the mechanisms involved in FM pathology, there is a need for closer investigation of endogenous pain modulation. In the present study, we compared the functional connectivity of the descending pain inhibitory network in age-matched FM patients and healthy controls (HC. We performed functional magnetic resonance imaging (fMRI in 42 subjects; 14 healthy and 28 age-matched FM patients (2 patients per HC, during randomly presented, subjectively calibrated pressure pain stimuli. A seed-based functional connectivity analysis of brain activity was performed. The seed coordinates were based on the findings from our previous study, comparing the fMRI signal during calibrated pressure pain in FM and HC: the rostral anterior cingulate cortex (rACC and thalamus. Results FM patients required significantly less pressure (kPa to reach calibrated pain at 50 mm on a 0–100 visual analogue scale (p  Conclusion Patients with FM displayed less connectivity within the brain’s pain inhibitory network during calibrated pressure pain, compared to healthy controls. The present study provides brain-imaging evidence on how brain regions involved in homeostatic control of pain are less connected in FM patients. It is possible that the dysfunction of the descending pain modulatory network plays an important role in maintenance of FM pain and our results may translate into clinical implications by using the functional connectivity of the pain modulatory network as an objective measure of pain dysregulation.

  17. The brain network reflecting bodily self-consciousness: a functional connectivity study.

    Science.gov (United States)

    Ionta, Silvio; Martuzzi, Roberto; Salomon, Roy; Blanke, Olaf

    2014-12-01

    Several brain regions are important for processing self-location and first-person perspective, two important aspects of bodily self-consciousness. However, the interplay between these regions has not been clarified. In addition, while self-location and first-person perspective in healthy subjects are associated with bilateral activity in temporoparietal junction (TPJ), disturbed self-location and first-person perspective result from damage of only the right TPJ. Identifying the involved brain network and understanding the role of hemispheric specializations in encoding self-location and first-person perspective, will provide important information on system-level interactions neurally mediating bodily self-consciousness. Here, we used functional connectivity and showed that right and left TPJ are bilaterally connected to supplementary motor area, ventral premotor cortex, insula, intraparietal sulcus and occipitotemporal cortex. Furthermore, the functional connectivity between right TPJ and right insula had the highest selectivity for changes in self-location and first-person perspective. Finally, functional connectivity revealed hemispheric differences showing that self-location and first-person perspective modulated the connectivity between right TPJ, right posterior insula, and right supplementary motor area, and between left TPJ and right anterior insula. The present data extend previous evidence on healthy populations and clinical observations in neurological deficits, supporting a bilateral, but right-hemispheric dominant, network for bodily self-consciousness.

  18. Friends of friends: are indirect connections in social networks important to animal behaviour?

    Science.gov (United States)

    Brent, Lauren J N

    2015-05-01

    Friend of a friend relationships, or the indirect connections between people, influence our health, well-being, financial success and reproductive output. As with humans, social behaviours in other animals often occur within a broad interconnected network of social ties. Yet studies of animal social behaviour tend to focus on associations between pairs of individuals. With the increase in popularity of social network analysis, researchers have started to look beyond the dyad to examine the role of indirect connections in animal societies. Here, I provide an overview of the new knowledge that has been uncovered by these studies. I focus on research that has addressed both the causes of social behaviours, i.e. the cognitive and genetic basis of indirect connections, as well as their consequences, i.e. the impact of indirect connections on social cohesion, information transfer, cultural practices and fitness. From these studies, it is apparent that indirect connections play an important role in animal behaviour, although future research is needed to clarify their contribution.

  19. A network of amygdala connections predict individual differences in trait anxiety.

    Science.gov (United States)

    Greening, Steven G; Mitchell, Derek G V

    2015-12-01

    In this study we demonstrate that the pattern of an amygdala-centric network contributes to individual differences in trait anxiety. Individual differences in trait anxiety were predicted using maximum likelihood estimates of amygdala structural connectivity to multiple brain targets derived from diffusion-tensor imaging (DTI) and probabilistic tractography on 72 participants. The prediction was performed using a stratified sixfold cross validation procedure using a regularized least square regression model. The analysis revealed a reliable network of regions predicting individual differences in trait anxiety. Higher trait anxiety was associated with stronger connections between the amygdala and dorsal anterior cingulate cortex, an area implicated in the generation of emotional reactions, and inferior temporal gyrus and paracentral lobule, areas associated with perceptual and sensory processing. In contrast, higher trait anxiety was associated with weaker connections between amygdala and regions implicated in extinction learning such as medial orbitofrontal cortex, and memory encoding and environmental context recognition, including posterior cingulate cortex and parahippocampal gyrus. Thus, trait anxiety is not only associated with reduced amygdala connectivity with prefrontal areas associated with emotion modulation, but also enhanced connectivity with sensory areas. This work provides novel anatomical insight into potential mechanisms behind information processing biases observed in disorders of emotion.

  20. Altered Effective Connectivity of Hippocampus-Dependent Episodic Memory Network in mTBI Survivors

    Science.gov (United States)

    2016-01-01

    Traumatic brain injuries (TBIs) are generally recognized to affect episodic memory. However, less is known regarding how external force altered the way functionally connected brain structures of the episodic memory system interact. To address this issue, we adopted an effective connectivity based analysis, namely, multivariate Granger causality approach, to explore causal interactions within the brain network of interest. Results presented that TBI induced increased bilateral and decreased ipsilateral effective connectivity in the episodic memory network in comparison with that of normal controls. Moreover, the left anterior superior temporal gyrus (aSTG, the concept forming hub), left hippocampus (the personal experience binding hub), and left parahippocampal gyrus (the contextual association hub) were no longer network hubs in TBI survivors, who compensated for hippocampal deficits by relying more on the right hippocampus (underlying perceptual memory) and the right medial frontal gyrus (MeFG) in the anterior prefrontal cortex (PFC). We postulated that the overrecruitment of the right anterior PFC caused dysfunction of the strategic component of episodic memory, which caused deteriorating episodic memory in mTBI survivors. Our findings also suggested that the pattern of brain network changes in TBI survivors presented similar functional consequences to normal aging. PMID:28074162

  1. Altered Effective Connectivity of Hippocampus-Dependent Episodic Memory Network in mTBI Survivors

    Directory of Open Access Journals (Sweden)

    Hao Yan

    2016-01-01

    Full Text Available Traumatic brain injuries (TBIs are generally recognized to affect episodic memory. However, less is known regarding how external force altered the way functionally connected brain structures of the episodic memory system interact. To address this issue, we adopted an effective connectivity based analysis, namely, multivariate Granger causality approach, to explore causal interactions within the brain network of interest. Results presented that TBI induced increased bilateral and decreased ipsilateral effective connectivity in the episodic memory network in comparison with that of normal controls. Moreover, the left anterior superior temporal gyrus (aSTG, the concept forming hub, left hippocampus (the personal experience binding hub, and left parahippocampal gyrus (the contextual association hub were no longer network hubs in TBI survivors, who compensated for hippocampal deficits by relying more on the right hippocampus (underlying perceptual memory and the right medial frontal gyrus (MeFG in the anterior prefrontal cortex (PFC. We postulated that the overrecruitment of the right anterior PFC caused dysfunction of the strategic component of episodic memory, which caused deteriorating episodic memory in mTBI survivors. Our findings also suggested that the pattern of brain network changes in TBI survivors presented similar functional consequences to normal aging.

  2. A variance components model for statistical inference on functional connectivity networks.

    Science.gov (United States)

    Fiecas, Mark; Cribben, Ivor; Bahktiari, Reyhaneh; Cummine, Jacqueline

    2017-01-24

    We propose a variance components linear modeling framework to conduct statistical inference on functional connectivity networks that directly accounts for the temporal autocorrelation inherent in functional magnetic resonance imaging (fMRI) time series data and for the heterogeneity across subjects in the study. The novel method estimates the autocorrelation structure in a nonparametric and subject-specific manner, and estimates the variance due to the heterogeneity using iterative least squares. We apply the new model to a resting-state fMRI study to compare the functional connectivity networks in both typical and reading impaired young adults in order to characterize the resting state networks that are related to reading processes. We also compare the performance of our model to other methods of statistical inference on functional connectivity networks that do not account for the temporal autocorrelation or heterogeneity across the subjects using simulated data, and show that by accounting for these sources of variation and covariation results in more powerful tests for statistical inference.

  3. Impact of acoustic coordinated reset neuromodulation on effective connectivity in a neural network of phantom sound.

    Science.gov (United States)

    Silchenko, Alexander N; Adamchic, Ilya; Hauptmann, Christian; Tass, Peter A

    2013-08-15

    Chronic subjective tinnitus is an auditory phantom phenomenon characterized by abnormal neuronal synchrony in the central auditory system. As recently shown in a proof of concept clinical trial, acoustic coordinated reset (CR) neuromodulation causes a significant relief of tinnitus symptoms combined with a significant decrease of pathological oscillatory activity in a network comprising auditory and non-auditory brain areas. The objective of the present study was to analyze whether CR therapy caused an alteration of the effective connectivity in a tinnitus related network of localized EEG brain sources. To determine which connections matter, in a first step, we considered a larger network of brain sources previously associated with tinnitus. To that network we applied a data-driven approach, combining empirical mode decomposition and partial directed coherence analysis, in patients with bilateral tinnitus before and after 12 weeks of CR therapy as well as in healthy controls. To increase the signal-to-noise ratio, we focused on the good responders, classified by a reliable-change-index (RCI). Prior to CR therapy and compared to the healthy controls, the good responders showed a significantly increased connectivity between the left primary cortex auditory cortex and the posterior cingulate cortex in the gamma and delta bands together with a significantly decreased effective connectivity between the right primary auditory cortex and the dorsolateral prefrontal cortex in the alpha band. Intriguingly, after 12 weeks of CR therapy most of the pathological interactions were gone, so that the connectivity patterns of good responders and healthy controls became statistically indistinguishable. In addition, we used dynamic causal modeling (DCM) to examine the types of interactions which were altered by CR therapy. Our DCM results show that CR therapy specifically counteracted the imbalance of excitation and inhibition. CR significantly weakened the excitatory connection

  4. Effects of Different Connectivity Topologies in Small World Networks on EEG-Like Activities

    Science.gov (United States)

    Lin, Min; Zhang, Gui-Qing; Chen, Tian-Lun

    2006-02-01

    Based on our previously pulse-coupled integrate-and-fire neuron model in small world networks, we investigate the effects of different connectivity topologies on complex behavior of electroencephalographic-like signals produced by this model. We show that several times series analysis methods that are often used for analyzing complex behavior of electroencephalographic-like signals, such as reconstruction of the phase space, correlation dimension, fractal dimension, and the Hurst exponent within the rescaled range analysis (R/S). We find that the different connectivity topologies lead to different dynamical behaviors in models of integrate-and-fire neurons.

  5. Effects of Different Connectivity Topologies in Small World Networks on EEG-Like Activities

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Based on our previously pulse-coupled integrate-and-fire neuron model in small world networks, we investi gate the effects of different connectivity topologies on complex behavior of electroencephalographic-like signals produced by this model. We show that several times series analysis methods that are often used for analyzing complex behavior of electroencephalographic-like signals, such as reconstruction of the phase space, correlation dimension, fractal dimension,and the Hurst exponent within the rescaled range analysis (R/S). We find that the different connectivity topologies lead to different dynamical behaviors in models of integrate-and-fire neurons.

  6. Topology-selective jamming of fully-connected, code-division random-access networks

    Science.gov (United States)

    Polydoros, Andreas; Cheng, Unjeng

    1990-01-01

    The purpose is to introduce certain models of topology selective stochastic jamming and examine its impact on a class of fully-connected, spread-spectrum, slotted ALOHA-type random access networks. The theory covers dedicated as well as half-duplex units. The dominant role of the spatial duty factor is established, and connections with the dual concept of time selective jamming are discussed. The optimal choices of coding rate and link access parameters (from the users' side) and the jamming spatial fraction are numerically established for DS and FH spreading.

  7. Binary synaptic connections based on memory switching in a-Si:H for artificial neural networks

    Science.gov (United States)

    Thakoor, A. P.; Lamb, J. L.; Moopenn, A.; Khanna, S. K.

    1987-01-01

    A scheme for nonvolatile associative electronic memory storage with high information storage density is proposed which is based on neural network models and which uses a matrix of two-terminal passive interconnections (synapses). It is noted that the massive parallelism in the architecture would require the ON state of a synaptic connection to be unusually weak (highly resistive). Memory switching using a-Si:H along with ballast resistors patterned from amorphous Ge-metal alloys is investigated for a binary programmable read only memory matrix. The fabrication of a 1600 synapse test array of uniform connection strengths and a-Si:H switching elements is discussed.

  8. A Virtual Private Local PCN Ring Network Based on ATM VP Cross—Connection

    Institute of Scientific and Technical Information of China (English)

    LinBin; MaYingjun; 等

    1995-01-01

    Avirtual private local PCNring network (VPLPR)is proposed .VPLPR is a virtual logic ring seuved for digital cordless telephone system and it works on ATM VP cross-connection mechanism.Full-distributed data bases are organized for visitor location registers(VLR)and home location register(HLR).The signaling protocols are compatible upward to B-ISDN. The architecture and some of the main characteristics of VPLPR are given.How to configure the ATM VP cross-connection ring is described.And then a protocol conversion between STM frames and ATMcells in base station controller(BSC)is presented.

  9. Analytical estimates of efficiency of attractor neural networks with inborn connections

    Directory of Open Access Journals (Sweden)

    Solovyeva Ksenia

    2016-01-01

    Full Text Available The analysis is restricted to the features of neural networks endowed to the latter by the inborn (not learned connections. We study attractor neural networks in which for almost all operation time the activity resides in close vicinity of a relatively small number of attractor states. The number of the latter, M, is proportional to the number of neurons in the neural network, N, while the total number of the states in it is 2N. The unified procedure of growth/fabrication of neural networks with sets of all attractor states with dimensionality d=0 and d=1, based on model molecular markers, is studied in detail. The specificity of the networks (d=0 or d=1 depends on topology (i.e., the set of distances between elements which can be provided to the set of molecular markers by their physical nature. The neural networks parameters estimates and trade-offs for them in attractor neural networks are calculated analytically. The proposed mechanisms reveal simple and efficient ways of implementation in artificial as well as in natural neural networks of multiplexity, i.e. of using activity of single neurons in representation of multiple values of the variables, which are operated by the neural systems. It is discussed how the neuronal multiplexity provides efficient and reliable ways of performing functional operations in the neural systems.

  10. Reliability Analysis of Distributed Grid-connected Photovoltaic System Monitoring Network

    Directory of Open Access Journals (Sweden)

    Fu Zhixin

    2016-01-01

    Full Text Available A large amount of distributed grid-connected Photovoltaic systems have brought new challenges to the dispatching of power network. Real-time monitoring the PV system can efficiently help improve the ability of power network to accept and control the distributed PV systems, and thus mitigate the impulse on the power network imposed by the uncertainty of its power output. To study the reliability of distributed PV monitoring network, it is of great significance to look for a method to build a highly reliable monitoring system, analyze the weak links and key nodes of its monitoring performance in improving the performance of the monitoring network. Firstly a reliability model of PV system was constructed based on WSN technology. Then, in view of the dynamic characteristics of the network’s reliability, fault tree analysis was used to judge any possible reasons that cause the failure of the network and logical relationship between them. Finally, the reliability of the monitoring network was analyzed to figure out the weak links and key nodes. This paper provides guidance to build a stable and reliable monitoring network of a distributed PV system.

  11. Connecting every bit of knowledge: The structure of Wikipedia's First Link Network

    CERN Document Server

    Ibrahim, Mark; Dodds, Peter Sheridan

    2016-01-01

    Apples, porcupines, and the most obscure Bob Dylan song--is every topic a few clicks from Philosophy? Within Wikipedia, the surprising answer is yes: nearly all paths lead to Philosophy. Wikipedia is the largest, most meticulously indexed collection of human knowledge ever amassed. More than information about a topic, Wikipedia is a web of naturally emerging relationships. By following the first link in each article, we algorithmically construct a directed network of all 4.7 million articles: Wikipedia's First Link Network. Here, we study the English edition of Wikipedia's First Link Network for insight into how the many articles on inventions, places, people, objects, and events are related and organized. By traversing every path, we measure the accumulation of first links, path lengths, groups of path-connected articles, cycles, and the influence each article exerts in shaping the network. We find scale-free distributions describe path length, accumulation, and influence. Far from dispersed, first links dis...

  12. Persistence of self-recruitment and patterns of larval connectivity in a marine protected area network

    KAUST Repository

    Berumen, Michael L.

    2012-02-01

    The use of marine protected area (MPA) networks to sustain fisheries and conserve biodiversity is predicated on two critical yet rarely tested assumptions. Individual MPAs must produce sufficient larvae that settle within that reserve\\'s boundaries to maintain local populations while simultaneously supplying larvae to other MPA nodes in the network that might otherwise suffer local extinction. Here, we use genetic parentage analysis to demonstrate that patterns of self-recruitment of two reef fishes (Amphiprion percula and Chaetodon vagabundus) in an MPA in Kimbe Bay, Papua New Guinea, were remarkably consistent over several years. However, dispersal from this reserve to two other nodes in an MPA network varied between species and through time. The stability of our estimates of self-recruitment suggests that even small MPAs may be self-sustaining. However, our results caution against applying optimization strategies to MPA network design without accounting for variable connectivity among species and over time. 2012 The Authors.

  13. Persistence of self-recruitment and patterns of larval connectivity in a marine protected area network.

    Science.gov (United States)

    Berumen, Michael L; Almany, Glenn R; Planes, Serge; Jones, Geoffrey P; Saenz-Agudelo, Pablo; Thorrold, Simon R

    2012-02-01

    The use of marine protected area (MPA) networks to sustain fisheries and conserve biodiversity is predicated on two critical yet rarely tested assumptions. Individual MPAs must produce sufficient larvae that settle within that reserve's boundaries to maintain local populations while simultaneously supplying larvae to other MPA nodes in the network that might otherwise suffer local extinction. Here, we use genetic parentage analysis to demonstrate that patterns of self-recruitment of two reef fishes (Amphiprion percula and Chaetodon vagabundus) in an MPA in Kimbe Bay, Papua New Guinea, were remarkably consistent over several years. However, dispersal from this reserve to two other nodes in an MPA network varied between species and through time. The stability of our estimates of self-recruitment suggests that even small MPAs may be self-sustaining. However, our results caution against applying optimization strategies to MPA network design without accounting for variable connectivity among species and over time.

  14. Connectivity, biodiversity conservation and the design of marine reserve networks for coral reefs

    Science.gov (United States)

    Almany, G. R.; Connolly, S. R.; Heath, D. D.; Hogan, J. D.; Jones, G. P.; McCook, L. J.; Mills, M.; Pressey, R. L.; Williamson, D. H.

    2009-06-01

    Networks of no-take reserves are important for protecting coral reef biodiversity from climate change and other human impacts. Ensuring that reserve populations are connected to each other and non-reserve populations by larval dispersal allows for recovery from disturbance and is a key aspect of resilience. In general, connectivity between reserves should increase as the distance between them decreases. However, enhancing connectivity may often tradeoff against a network’s ability to representatively sample the system’s natural variability. This “representation” objective is typically measured in terms of species richness or diversity of habitats, but has other important elements (e.g., minimizing the risk that multiple reserves will be impacted by catastrophic events). Such representation objectives tend to be better achieved as reserves become more widely spaced. Thus, optimizing the location, size and spacing of reserves requires both an understanding of larval dispersal and explicit consideration of how well the network represents the broader system; indeed the lack of an integrated theory for optimizing tradeoffs between connectivity and representation objectives has inhibited the incorporation of connectivity into reserve selection algorithms. This article addresses these issues by (1) updating general recommendations for the location, size and spacing of reserves based on emerging data on larval dispersal in corals and reef fishes, and on considerations for maintaining genetic diversity; (2) using a spatial analysis of the Great Barrier Reef Marine Park to examine potential tradeoffs between connectivity and representation of biodiversity and (3) describing a framework for incorporating environmental fluctuations into the conceptualization of the tradeoff between connectivity and representation, and that expresses both in a common, demographically meaningful currency, thus making optimization possible.

  15. A Multimodal Approach for Determining Brain Networks by Jointly Modeling Functional and Structural Connectivity

    Directory of Open Access Journals (Sweden)

    Wenqiong eXue

    2015-02-01

    Full Text Available Recent innovations in neuroimaging technology have provided opportunities for researchers to investigate connectivity in the human brain by examining the anatomical circuitry as well as functional relationships between brain regions. Existing statistical approaches for connectivity generally examine resting-state or task-related functional connectivity (FC between brain regions or separately examine structural linkages. As a means to determine brain networks, we present a unified Bayesian framework for analyzing FC utilizing the knowledge of associated structural connections, which extends an approach by Patel et al.(2006a that considers only functional data. We introduce an FC measure that rests upon assessments of functional coherence between regional brain activity identified from functional magnetic resonance imaging (fMRI data. Our structural connectivity (SC information is drawn from diffusion tensor imaging (DTI data, which is used to quantify probabilities of SC between brain regions. We formulate a prior distribution for FC that depends upon the probability of SC between brain regions, with this dependence adhering to structural-functional links revealed by our fMRI and DTI data. We further characterize the functional hierarchy of functionally connected brain regions by defining an ascendancy measure that compares the marginal probabilities of elevated activity between regions. In addition, we describe topological properties of the network, which is composed of connected region pairs, by performing graph theoretic analyses. We demonstrate the use of our Bayesian model using fMRI and DTI data from a study of auditory processing. We further illustrate the advantages of our method by comparisons to methods that only incorporate functional information.

  16. Connection errors in networks of linear features and the application of geometrical reduction in spatial data algorithms

    CERN Document Server

    Rodis, Panteleimon

    2011-01-01

    The topic of this paper is to present a study of the connection errors in networks of linear features that are mapped in Geographical Information Systems (GIS), as well as algorithms that detect them and the notion of geometrical reduction and its use in spatial data algorithms. In datasets of networks usually there can be found errors, when a number of elements of the network are not connected according to the specifications of the network. This can occur due to errors in the digitization process of the network or because these elements are connected in reality in a not legal way. These errors can be topological, when the network elements are not correctly connected, or errors that violate the specifications of the network. Examples of specifications that their violation can result this situation is when in a telecommunication network there is the restriction that channels of high capacity should not be connected directly to home networks but only through local sub-networks, or when in a road network there i...

  17. Connecting primary care clinics and community pharmacies through a nationwide electronic prescribing network: A qualitative study

    Directory of Open Access Journals (Sweden)

    Marie-Pierre Gagnon

    2015-10-01

    Full Text Available Background The use of medication is at the heart of primary care, but is also the cause for major health concerns. It is therefore important to examine the prescription of medication process.Objective This study identifies the barriers and facilitators perceived by community pharmacists and primary care physicians concerning the adoption of a nationwide electronic prescribing (e-prescribing network in the province of Quebec, Canada.Methods We used purposive sampling to identify the most intensive users of the e-prescribing network. We conducted phone and in-person interviews. Interviews were transcribed, and we analysed their content with NVivo, using the clinical adoption framework (CAF for the codification of the data.Results We interviewed 33 pharmacists, 2 pharmacy technicians, 11 physicians and 3 clinic managers. Adoption of the e-prescribing network was fairly low. The respondents underlined adaptation of their work environment, openness to change and perception of benefits as facilitators to the adoption of the network. However, important barriers were perceived, including system quality issues and paper prescriptions being the only legal document in the prescribing process. Even if respondents recognised that the e-prescribing network can offer substantial benefits to the prescribing process, issues still persisted and raised barriers to the full use of such a network, especially in a context where different local information systems are connected within a nationwide e-prescribing network.Conclusion This study, based on the CAF, provides a better understanding of the factors related to the adoption of a nationwide e-prescribing network connecting primary care clinics and community pharmacies. 

  18. Abnormal structural connectivity in the brain networks of children with hydrocephalus.

    Science.gov (United States)

    Yuan, Weihong; Holland, Scott K; Shimony, Joshua S; Altaye, Mekibib; Mangano, Francesco T; Limbrick, David D; Jones, Blaise V; Nash, Tiffany; Rajagopal, Akila; Simpson, Sarah; Ragan, Dustin; McKinstry, Robert C

    2015-01-01

    Increased intracranial pressure and ventriculomegaly in children with hydrocephalus are known to have adverse effects on white matter structure. This study seeks to investigate the impact of hydrocephalus on topological features of brain networks in children. The goal was to investigate structural network connectivity, at both global and regional levels, in the brains in children with hydrocephalus using graph theory analysis and diffusion tensor tractography. Three groups of children were included in the study (29 normally developing controls, 9 preoperative hydrocephalus patients, and 17 postoperative hydrocephalus patients). Graph theory analysis was applied to calculate the global network measures including small-worldness, normalized clustering coefficients, normalized characteristic path length, global efficiency, and modularity. Abnormalities in regional network parameters, including nodal degree, local efficiency, clustering coefficient, and betweenness centrality, were also compared between the two patients groups (separately) and the controls using two tailed t-test at significance level of p hydrocephalus in both the preoperative and postoperative groups were found to have significantly lower small-worldness and lower normalized clustering coefficient than controls. Children with hydrocephalus in the postoperative group were also found to have significantly lower normalized characteristic path length and lower modularity. At regional level, significant group differences (or differences at trend level) in regional network measures were found between hydrocephalus patients and the controls in a series of brain regions including the medial occipital gyrus, medial frontal gyrus, thalamus, cingulate gyrus, lingual gyrus, rectal gyrus, caudate, cuneus, and insular. Our data showed that structural connectivity analysis using graph theory and diffusion tensor tractography is sensitive to detect abnormalities of brain network connectivity associated with

  19. Cortical EEG oscillations and network connectivity as efficacy indices for assessing drugs with cognition enhancing potential.

    Science.gov (United States)

    Ahnaou, A; Huysmans, H; Jacobs, T; Drinkenburg, W H I M

    2014-11-01

    Synchronization of electroencephalographic (EEG) oscillations represents a core mechanism for cortical and subcortical networks, and disturbance in neural synchrony underlies cognitive processing deficits in neurological and neuropsychiatric disorders. Here, we investigated the effects of cognition enhancers (donepezil, rivastigmine, tacrine, galantamine and memantine), which are approved for symptomatic treatment of dementia, on EEG oscillations and network connectivity in conscious rats chronically instrumented with epidural electrodes in different cortical areas. Next, EEG network indices of cognitive impairments with the muscarinic receptor antagonist scopolamine were modeled. Lastly, we examined the efficacy of cognition enhancers to normalize those aberrant oscillations. Cognition enhancers elicited systematic ("fingerprint") enhancement of cortical slow theta (4.5-6 Hz) and gamma (30.5-50 Hz) oscillations correlated with lower activity levels. Principal component analysis (PCA) revealed a compact cluster that corresponds to shared underlying mechanisms as compared to different drug classes. Functional network connectivity revealed consistent elevated coherent slow theta activity in parieto-occipital and between interhemispheric cortical areas. In rats instrumented with depth hippocampal CA1-CA3 electrodes, donepezil elicited similar oscillatory and coherent activities in cortico-hippocampal networks. When combined with scopolamine, the cognition enhancers attenuated the leftward shift in coherent slow delta activity. Such a consistent shift in EEG coherence into slow oscillations associated with altered slow theta and gamma oscillations may underlie cognitive deficits in scopolamine-treated animals, whereas enhanced coherent slow theta and gamma activity may be a relevant mechanism by which cognition enhancers exert their beneficial effect on plasticity and cognitive processes. The findings underscore that PCA and network connectivity are valuable tools to

  20. Abnormal structural connectivity in the brain networks of children with hydrocephalus

    Directory of Open Access Journals (Sweden)

    Weihong Yuan

    2015-01-01

    Full Text Available Increased intracranial pressure and ventriculomegaly in children with hydrocephalus are known to have adverse effects on white matter structure. This study seeks to investigate the impact of hydrocephalus on topological features of brain networks in children. The goal was to investigate structural network connectivity, at both global and regional levels, in the brains in children with hydrocephalus using graph theory analysis and diffusion tensor tractography. Three groups of children were included in the study (29 normally developing controls, 9 preoperative hydrocephalus patients, and 17 postoperative hydrocephalus patients. Graph theory analysis was applied to calculate the global network measures including small-worldness, normalized clustering coefficients, normalized characteristic path length, global efficiency, and modularity. Abnormalities in regional network parameters, including nodal degree, local efficiency, clustering coefficient, and betweenness centrality, were also compared between the two patients groups (separately and the controls using two tailed t-test at significance level of p < 0.05 (corrected for multiple comparison. Children with hydrocephalus in both the preoperative and postoperative groups were found to have significantly lower small-worldness and lower normalized clustering coefficient than controls. Children with hydrocephalus in the postoperative group were also found to have significantly lower normalized characteristic path length and lower modularity. At regional level, significant group differences (or differences at trend level in regional network measures were found between hydrocephalus patients and the controls in a series of brain regions including the medial occipital gyrus, medial frontal gyrus, thalamus, cingulate gyrus, lingual gyrus, rectal gyrus, caudate, cuneus, and insular. Our data showed that structural connectivity analysis using graph theory and diffusion tensor tractography is sensitive to

  1. Pharmacological characterization of cultivated neuronal networks: relevance to synaptogenesis and synaptic connectivity.

    Science.gov (United States)

    Verstraelen, Peter; Pintelon, Isabel; Nuydens, Rony; Cornelissen, Frans; Meert, Theo; Timmermans, Jean-Pierre

    2014-07-01

    Mental disorders, such as schizophrenia or Alzheimer's disease, are associated with impaired synaptogenesis and/or synaptic communication. During development, neurons assemble into neuronal networks, the primary supracellular mediators of information processing. In addition to the orchestrated activation of genetic programs, spontaneous electrical activity and associated calcium signaling have been shown to be critically involved in the maturation of such neuronal networks. We established an in vitro model that recapitulates the maturation of neuronal networks, including spontaneous electrical activity. Upon plating, mouse primary hippocampal neurons grow neurites and interconnect via synapses to form a dish-wide neuronal network. Via live cell calcium imaging, we identified a limited period of time in which the spontaneous activity synchronizes across neurons, indicative of the formation of a functional network. After establishment of network activity, the neurons grow dendritic spines, the density of which was used as a morphological readout for neuronal maturity and connectivity. Hence, quantification of neurite outgrowth, synapse density, spontaneous neuronal activity, and dendritic spine density allowed to study neuronal network maturation from the day of plating until the presence of mature neuronal networks. Via acute pharmacological intervention, we show that synchronized network activity is mediated by the NMDA-R. The balance between kynurenic and quinolinic acid, both neuro-active intermediates in the tryptophan/kynurenine pathway, was shown to be decisive for the maintenance of network activity. Chronic modulation of the neurotrophic support influenced the network formation and revealed the extreme sensitivity of calcium imaging to detect subtle alterations in neuronal physiology. Given the reproducible cultivation in a 96-well setup in combination with fully automated analysis of the calcium recordings, this approach can be used to build a high

  2. Dynamic Network Connectivity Analysis to Identify Epileptogenic Zones Based on Stereo-Electroencephalography

    Science.gov (United States)

    Mao, Jun-Wei; Ye, Xiao-Lai; Li, Yong-Hua; Liang, Pei-Ji; Xu, Ji-Wen; Zhang, Pu-Ming

    2016-01-01

    Objectives: Accurate localization of epileptogenic zones (EZs) is essential for successful surgical treatment of refractory focal epilepsy. The aim of the present study is to investigate whether a dynamic network connectivity analysis based on stereo-electroencephalography (SEEG) signals is effective in localizing EZs. Methods: SEEG data were recorded from seven patients who underwent presurgical evaluation for the treatment of refractory focal epilepsy and for whom the subsequent resective surgery gave a good outcome. A time-variant multivariate autoregressive model was constructed using a Kalman filter, and the time-variant partial directed coherence was computed. This was then used to construct a dynamic directed network model of the epileptic brain. Three graph measures (in-degree, out-degree, and betweenness centrality) were used to analyze the characteristics of the dynamic network and to find the important nodes in it. Results: In all seven patients, the indicative EZs localized by the in-degree and the betweenness centrality were highly consistent with the clinically diagnosed EZs. However, the out-degree did not indicate any significant differences between nodes in the network. Conclusions: In this work, a method based on ictal SEEG signals and effective connectivity analysis localized EZs accurately. The results suggest that the in-degree and betweenness centrality may be better network characteristics to localize EZs than the out-degree. PMID:27833545

  3. Analyzing Social Media Networks with NodeXL Insights from a Connected World

    CERN Document Server

    Hansen, Derek; Smith, Marc A

    2010-01-01

    Businesses, entrepreneurs, individuals, and government agencies alike are looking to social network analysis (SNA) tools for insight into trends, connections, and fluctuations in social media. Microsoft's NodeXL is a free, open-source SNA plug-in for use with Excel. It provides instant graphical representation of relationships of complex networked data. But it goes further than other SNA tools -- NodeXL was developed by a multidisciplinary team of experts that bring together information studies, computer science, sociology, human-computer interaction, and over 20 years of visual analytic theor

  4. Characterization and assessment of voltage and power constraints of DFIG WT connected to a weak network

    DEFF Research Database (Denmark)

    Abulanwar, Elsayed; Hu, Weihao; Iov, Florin;

    2014-01-01

    This article thoroughly investigates the challenges and constraints raised by the integration of a Doubly-fed Induction generator wind turbine, DFIG WT, into an ac network of extensively varying parameters and very weak conditions. The objective is to mitigate the voltage variations at the point...... of common coupling, PCC, and maximize the wind power penetration into weak networks. As a basis of investigation, a simplified system model is utilized and the respective PCC voltage, active and reactive power stability issues are identified. Besides, a steady-state study for DFIG WT connected to a weak...

  5. Network Garment Style Design System with Remote Information Access and Auto-Connecting Technology

    Institute of Scientific and Technical Information of China (English)

    QIAN Su-qin; DONG Ai-hua

    2007-01-01

    A Network Garment Style Design System (NGSDS) is proposed to enable the remote style structure drawing design of garment. After the development of the system structure based on network that consists of client end and server end at two remote places, a multi-layer part database based on Oracle platform is presented to store information of different parts of garment style. With the acquirement of remote design data at server end using Http technology, the style design is ultimately implemented at the client end using Auto-connecting algorithms. One empirical example is given to show the implementation of the NGSDS.

  6. Altered topological properties of functional network connectivity in schizophrenia during resting state: a small-world brain network study.

    Science.gov (United States)

    Yu, Qingbao; Sui, Jing; Rachakonda, Srinivas; He, Hao; Gruner, William; Pearlson, Godfrey; Kiehl, Kent A; Calhoun, Vince D

    2011-01-01

    Aberrant topological properties of small-world human brain networks in patients with schizophrenia (SZ) have been documented in previous neuroimaging studies. Aberrant functional network connectivity (FNC, temporal relationships among independent component time courses) has also been found in SZ by a previous resting state functional magnetic resonance imaging (fMRI) study. However, no study has yet determined if topological properties of FNC are also altered in SZ. In this study, small-world network metrics of FNC during the resting state were examined in both healthy controls (HCs) and SZ subjects. FMRI data were obtained from 19 HCs and 19 SZ. Brain images were decomposed into independent components (ICs) by group independent component analysis (ICA). FNC maps were constructed via a partial correlation analysis of ICA time courses. A set of undirected graphs were built by thresholding the FNC maps and the small-world network metrics of these maps were evaluated. Our results demonstrated significantly altered topological properties of FNC in SZ relative to controls. In addition, topological measures of many ICs involving frontal, parietal, occipital and cerebellar areas were altered in SZ relative to controls. Specifically, topological measures of whole network and specific components in SZ were correlated with scores on the negative symptom scale of the Positive and Negative Symptom Scale (PANSS). These findings suggest that aberrant architecture of small-world brain topology in SZ consists of ICA temporally coherent brain networks.

  7. Replicated landscape genetic and network analyses reveal wide variation in functional connectivity for American pikas.

    Science.gov (United States)

    Castillo, Jessica A; Epps, Clinton W; Jeffress, Mackenzie R; Ray, Chris; Rodhouse, Thomas J; Schwalm, Donelle

    2016-09-01

    Landscape connectivity is essential for maintaining viable populations, particularly for species restricted to fragmented habitats or naturally arrayed in metapopulations and facing rapid climate change. The importance of assessing both structural connectivity (physical distribution of favorable habitat patches) and functional connectivity (how species move among habitat patches) for managing such species is well understood. However, the degree to which functional connectivity for a species varies among landscapes, and the resulting implications for conservation, have rarely been assessed. We used a landscape genetics approach to evaluate resistance to gene flow and, thus, to determine how landscape and climate-related variables influence gene flow for American pikas (Ochotona princeps) in eight federally managed sites in the western United States. We used empirically derived, individual-based landscape resistance models in conjunction with predictive occupancy models to generate patch-based network models describing functional landscape connectivity. Metareplication across landscapes enabled identification of limiting factors for dispersal that would not otherwise have been apparent. Despite the cool microclimates characteristic of pika habitat, south-facing aspects consistently represented higher resistance to movement, supporting the previous hypothesis that exposure to relatively high temperatures may limit dispersal in American pikas. We found that other barriers to dispersal included areas with a high degree of topographic relief, such as cliffs and ravines, as well as streams and distances greater than 1-4 km depending on the site. Using the empirically derived network models of habitat patch connectivity, we identified habitat patches that were likely disproportionately important for maintaining functional connectivity, areas in which habitat appeared fragmented, and locations that could be targeted for management actions to improve functional connectivity

  8. Network modularity reveals critical scales for connectivity in ecology and evolution.

    Science.gov (United States)

    Fletcher, Robert J; Revell, Andre; Reichert, Brian E; Kitchens, Wiley M; Dixon, Jeremy D; Austin, James D

    2013-01-01

    For nearly a century, biologists have emphasized the profound importance of spatial scale for ecology, evolution and conservation. Nonetheless, objectively identifying critical scales has proven incredibly challenging. Here we extend new techniques from physics and social sciences that estimate modularity on networks to identify critical scales for movement and gene flow in animals. Using four species that vary widely in dispersal ability and include both mark-recapture and population genetic data, we identify significant modularity in three species, two of which cannot be explained by geographic distance alone. Importantly, the inclusion of modularity in connectivity and population viability assessments alters conclusions regarding patch importance to connectivity and suggests higher metapopulation viability than when ignoring this hidden spatial scale. We argue that network modularity reveals critical meso-scales that are probably common in populations, providing a powerful means of identifying fundamental scales for biology and for conservation strategies aimed at recovering imperilled species.

  9. Childhood poverty and stress reactivity are associated with aberrant functional connectivity in default mode network.

    Science.gov (United States)

    Sripada, Rebecca K; Swain, James E; Evans, Gary W; Welsh, Robert C; Liberzon, Israel

    2014-08-01

    Convergent research suggests that childhood poverty is associated with perturbation in the stress response system. This might extend to aberrations in the connectivity of large-scale brain networks, which subserve key cognitive and emotional functions. Resting-state brain activity was measured in adults with a documented history of childhood poverty (n=26) and matched controls from middle-income families (n=26). Participants also underwent a standard laboratory social stress test and provided saliva samples for cortisol assay. Childhood poverty was associated with reduced default mode network (DMN) connectivity. This, in turn, was associated with higher cortisol levels in anticipation of social stress. These results suggest a possible brain basis for exaggerated stress sensitivity in low-income individuals. Alterations in DMN may be associated with less efficient cognitive processing or greater risk for development of stress-related psychopathology among individuals who experienced the adversity of chronic childhood poverty.

  10. "Improved Geometric Network Model" (IGNM): a novel approach for deriving Connectivity Graphs for Indoor Navigation

    Science.gov (United States)

    Mortari, F.; Zlatanova, S.; Liu, L.; Clementini, E.

    2014-04-01

    Over the past few years Personal Navigation Systems have become an established tool for route planning, but they are mainly designed for outdoor environments. Indoor navigation is still a challenging research area for several reasons: positioning is not very accurate, users can freely move between the interior boundaries of buildings, path network construction process may not be easy and straightforward due to complexity of indoor space configurations. Therefore the creation of a good network is essential for deriving overall connectivity of a building and for representing position of objects within the environment. This paper reviews current approaches to automatic derivation of route graphs for indoor navigation and discusses some of their limitations. Then, it introduces a novel algorithmic strategy for extracting a 3D connectivity graph for indoor navigation based on 2D floor plans.

  11. Stimulus number, duration and intensity encoding in randomly connected attractor networks with synaptic depression

    Directory of Open Access Journals (Sweden)

    Paul eMiller

    2013-05-01

    Full Text Available Randomly connected recurrent networks of excitatory groups of neurons can possess a multitude of attractor states. When the internal excitatory synapses of these networks are depressing, the attractor states can be destabilized with increasing input. This leads to an itinerancy, where with either repeated transient stimuli, or increasing duration of a single stimulus, the network activity advances through sequences of attractor states. We find that the resulting network state, which persists beyond stimulus offset, can encode the number of stimuli presented via a distributed representation of neural activity with non-monotonic tuning curves for most neurons. Increased duration of a single stimulus is encoded via different distributed representations, so unlike an integrator, the network distinguishes separate successive presentations of a short stimulus from a single presentation of a longer stimulus with equal total duration. Moreover, different amplitudes of stimulus cause new, distinct activity patterns, such that changes in stimulus number, duration and amplitude can be distinguished from each other. These properties of the network depend on dynamic depressing synapses, as they disappear if synapses are static. Thus short-term synaptic depression allows a network to store separately the different dynamic properties of a spatially constant stimulus.

  12. Understanding Stability of Noisy Networks through Centrality Measures and Local Connections

    CERN Document Server

    Ufimtsev, Vladimir; Mukherjee, Animesh; Bhowmick, Sanjukta

    2016-01-01

    Networks created from real-world data contain some inaccuracies or noise, manifested as small changes in the network structure. An important question is whether these small changes can significantly affect the analysis results. In this paper, we study the effect of noise in changing ranks of the high centrality vertices. We compare, using the Jaccard Index (JI), how many of the top-k high centrality nodes from the original network are also part of the top-k ranked nodes from the noisy network. We deem a network as stable if the JI value is high. We observe two features that affect the stability. First, the stability is dependent on the number of top-ranked vertices considered. When the vertices are ordered according to their centrality values, they group into clusters. Perturbations to the network can change the relative ranking within the cluster, but vertices rarely move from one cluster to another. Second, the stability is dependent on the local connections of the high ranking vertices. The network is high...

  13. Oscillatory network with self-organized dynamical connections for synchronization-based image segmentation.

    Science.gov (United States)

    Kuzmina, Margarita; Manykin, Eduard; Surina, Irina

    2004-01-01

    An oscillatory network of columnar architecture located in 3D spatial lattice was recently designed by the authors as oscillatory model of the brain visual cortex. Single network oscillator is a relaxational neural oscillator with internal dynamics tunable by visual image characteristics - local brightness and elementary bar orientation. It is able to demonstrate either activity state (stable undamped oscillations) or "silence" (quickly damped oscillations). Self-organized nonlocal dynamical connections of oscillators depend on oscillator activity levels and orientations of cortical receptive fields. Network performance consists in transfer into a state of clusterized synchronization. At current stage grey-level image segmentation tasks are carried out by 2D oscillatory network, obtained as a limit version of the source model. Due to supplemented network coupling strength control the 2D reduced network provides synchronization-based image segmentation. New results on segmentation of brightness and texture images presented in the paper demonstrate accurate network performance and informative visualization of segmentation results, inherent in the model.

  14. Compact Graph Representations and Parallel Connectivity Algorithms for Massive Dynamic Network Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Madduri, Kamesh; Bader, David A.

    2009-02-15

    Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication traffic, and scientific computing can be intuitively modeled as graphs. We present the first study of novel high-performance combinatorial techniques for analyzing large-scale information networks, encapsulating dynamic interaction data in the order of billions of entities. We present new data structures to represent dynamic interaction networks, and discuss algorithms for processing parallel insertions and deletions of edges in small-world networks. With these new approaches, we achieve an average performance rate of 25 million structural updates per second and a parallel speedup of nearly28 on a 64-way Sun UltraSPARC T2 multicore processor, for insertions and deletions to a small-world network of 33.5 million vertices and 268 million edges. We also design parallel implementations of fundamental dynamic graph kernels related to connectivity and centrality queries. Our implementations are freely distributed as part of the open-source SNAP (Small-world Network Analysis and Partitioning) complex network analysis framework.

  15. Globs in the Primordial Soup: The Emergence of Connected Crowds in Mobile Wireless Networks

    OpenAIRE

    Heimlicher, Simon; Salamatian, Kavé

    2010-01-01

    MobiHoc 2010 Conference Best Paper Award; International audience; In many practical scenarios, nodes gathering at points of interest yield sizable connected components (clusters), which sometimes comprise the majority of nodes. While recent analysis of mobile networks focused on the process governing node encounters ("contacts"), this model is not particularly suitable for gathering behavior. In this paper, we propose a model of stochastic coalescence (merge) and fragmentation (split) of clus...

  16. Ketamine decreases resting state functional network connectivity in healthy subjects: implications for antidepressant drug action.

    Directory of Open Access Journals (Sweden)

    Milan Scheidegger

    Full Text Available Increasing preclinical and clinical evidence underscores the strong and rapid antidepressant properties of the glutamate-modulating NMDA receptor antagonist ketamine. Targeting the glutamatergic system might thus provide a novel molecular strategy for antidepressant treatment. Since glutamate is the most abundant and major excitatory neurotransmitter in the brain, pathophysiological changes in glutamatergic signaling are likely to affect neurobehavioral plasticity, information processing and large-scale changes in functional brain connectivity underlying certain symptoms of major depressive disorder. Using resting state functional magnetic resonance imaging (rsfMRI, the "dorsal nexus "(DN was recently identified as a bilateral dorsal medial prefrontal cortex region showing dramatically increased depression-associated functional connectivity with large portions of a cognitive control network (CCN, the default mode network (DMN, and a rostral affective network (AN. Hence, Sheline and colleagues (2010 proposed that reducing increased connectivity of the DN might play a critical role in reducing depression symptomatology and thus represent a potential therapy target for affective disorders. Here, using a randomized, placebo-controlled, double-blind, crossover rsfMRI challenge in healthy subjects we demonstrate that ketamine decreases functional connectivity of the DMN to the DN and to the pregenual anterior cingulate (PACC and medioprefrontal cortex (MPFC via its representative hub, the posterior cingulate cortex (PCC. These findings in healthy subjects may serve as a model to elucidate potential biomechanisms that are addressed by successful treatment of major depression. This notion is further supported by the temporal overlap of our observation of subacute functional network modulation after 24 hours with the peak of efficacy following an intravenous ketamine administration in treatment-resistant depression.

  17. Ketamine Decreases Resting State Functional Network Connectivity in Healthy Subjects: Implications for Antidepressant Drug Action

    Science.gov (United States)

    Walter, Martin; Lehmann, Mick; Metzger, Coraline; Grimm, Simone; Boeker, Heinz; Boesiger, Peter; Henning, Anke; Seifritz, Erich

    2012-01-01

    Increasing preclinical and clinical evidence underscores the strong and rapid antidepressant properties of the glutamate-modulating NMDA receptor antagonist ketamine. Targeting the glutamatergic system might thus provide a novel molecular strategy for antidepressant treatment. Since glutamate is the most abundant and major excitatory neurotransmitter in the brain, pathophysiological changes in glutamatergic signaling are likely to affect neurobehavioral plasticity, information processing and large-scale changes in functional brain connectivity underlying certain symptoms of major depressive disorder. Using resting state functional magnetic resonance imaging (rsfMRI), the „dorsal nexus “(DN) was recently identified as a bilateral dorsal medial prefrontal cortex region showing dramatically increased depression-associated functional connectivity with large portions of a cognitive control network (CCN), the default mode network (DMN), and a rostral affective network (AN). Hence, Sheline and colleagues (2010) proposed that reducing increased connectivity of the DN might play a critical role in reducing depression symptomatology and thus represent a potential therapy target for affective disorders. Here, using a randomized, placebo-controlled, double-blind, crossover rsfMRI challenge in healthy subjects we demonstrate that ketamine decreases functional connectivity of the DMN to the DN and to the pregenual anterior cingulate (PACC) and medioprefrontal cortex (MPFC) via its representative hub, the posterior cingulate cortex (PCC). These findings in healthy subjects may serve as a model to elucidate potential biomechanisms that are addressed by successful treatment of major depression. This notion is further supported by the temporal overlap of our observation of subacute functional network modulation after 24 hours with the peak of efficacy following an intravenous ketamine administration in treatment-resistant depression. PMID:23049758

  18. Fitting VFC's Output Using Functionally Connected High-Order Neural Networks

    Institute of Scientific and Technical Information of China (English)

    CHENG Chun-ling; ZHOU Jie

    2004-01-01

    A new method is presented in this paper for fitting Voltage-to-Frequency Converter (VFC's) output functions by using Functionally Connected High-order Neural Networks (FCHNN). The nonlinear estimation is implemented when the VFC110 is used at a full-scale output frequency of 4 MHz. Two kinds of on-line dynamic calibrating circuits are designed to improve the sampling precision. This method can also be applied to different industrial areas.

  19. A Triple Network Connectivity Study of Large-Scale Brain Systems in Cognitively Normal APOE4 Carriers

    Science.gov (United States)

    Wu, Xia; Li, Qing; Yu, Xinyu; Chen, Kewei; Fleisher, Adam S.; Guo, Xiaojuan; Zhang, Jiacai; Reiman, Eric M.; Yao, Li; Li, Rui

    2016-01-01

    The triple network model, consisting of the central executive network (CEN), salience network (SN) and default mode network (DMN), has been recently employed to understand dysfunction in core networks across various disorders. Here we used the triple network model to investigate the large-scale brain networks in cognitively normal apolipoprotein e4 (APOE4) carriers who are at risk of Alzheimer’s disease (AD). To explore the functional connectivity for each of the three networks and the effective connectivity among them, we evaluated 17 cognitively normal individuals with a family history of AD and at least one copy of the APOE4 allele and compared the findings to those of 12 individuals who did not carry the APOE4 gene or have a family history of AD, using independent component analysis (ICA) and Bayesian network (BN) approach. Our findings indicated altered within-network connectivity that suggests future cognitive decline risk, and preserved between-network connectivity that may support their current preserved cognition in the cognitively normal APOE4 allele carriers. The study provides novel sights into our understanding of the risk factors for AD and their influence on the triple network model of major psychopathology. PMID:27733827

  20. Storage of phase-coded patterns via STDP in fully-connected and sparse network: a study of the network capacity

    Directory of Open Access Journals (Sweden)

    Silvia Scarpetta

    2010-08-01

    Full Text Available We study the storage and retrieval of phase-coded patterns as stable dynamical attractors in recurrent neural networks, for both an analog and a integrate-and-fire spiking model. The synaptic strength is determined by a learning rule based on spike-time-dependent plasticity, with an asymmetric time window depending on the relative timing between pre- and post-synaptic activity. We store multiple patterns and study the network capacity. For the analog model, we find that the network capacity scales linearly with the network size, and that both capacity and the oscillation frequency of the retrieval state depend on the asymmetry of the learning time window. In addition to fully-connected networks, we study sparse networks, where each neuron is connected only to a small number $zll N$ of other neurons. Connections can be short range, between neighboring neurons placed on a regular lattice, or long range, between randomly chosen pairs of neurons. We find that a small fraction of long range connections is able to amplify the capacity of the network. This imply that a small-world-network topology is optimal, as a compromise between the cost of long range connections and the capacity increase. Also in the spiking integrate and fire model the crucial result of storing and retrieval of multiple phase-coded patterns is observed. The capacity of the fully-connected spiking network is investigated, together with the relation between oscillation frequency of retrieval state and window asymmetry.

  1. Resting-state network disruption and APOE genotype in Alzheimer's disease: a lagged functional connectivity study.

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    Leonides Canuet

    Full Text Available BACKGROUND: The apolipoprotein E epsilon 4 (APOE-4 is associated with a genetic vulnerability to Alzheimer's disease (AD and with AD-related abnormalities in cortical rhythms. However, it is unclear whether APOE-4 is linked to a specific pattern of intrinsic functional disintegration of the brain after the development of the disease or during its different stages. This study aimed at identifying spatial patterns and effects of APOE genotype on resting-state oscillations and functional connectivity in patients with AD, using a physiological connectivity index called "lagged phase synchronization". METHODOLOGY/PRINCIPAL FINDINGS: Resting EEG was recorded during awake, eyes-closed state in 125 patients with AD and 60 elderly controls. Source current density and functional connectivity were determined using eLORETA. Patients with AD exhibited reduced parieto-occipital alpha oscillations compared with controls, and those carrying the APOE-4 allele had reduced alpha activity in the left inferior parietal and temporo-occipital cortex relative to noncarriers. There was a decreased alpha2 connectivity pattern in AD, involving the left temporal and bilateral parietal cortex. Several brain regions exhibited increased lagged phase synchronization in low frequencies, specifically in the theta band, across and within hemispheres, where temporal lobe connections were particularly compromised. Areas with abnormal theta connectivity correlated with cognitive scores. In patients with early AD, we found an APOE-4-related decrease in interhemispheric alpha connectivity in frontal and parieto-temporal regions. CONCLUSIONS/SIGNIFICANCE: In addition to regional cortical dysfunction, as indicated by abnormal alpha oscillations, there are patterns of functional network disruption affecting theta and alpha bands in AD that associate with the level of cognitive disturbance or with the APOE genotype. These functional patterns of nonlinear connectivity may potentially

  2. A depression network of functionally connected regions discovered via multi-attribute canonical correlation graphs.

    Science.gov (United States)

    Kang, Jian; Bowman, F DuBois; Mayberg, Helen; Liu, Han

    2016-11-01

    To establish brain network properties associated with major depressive disorder (MDD) using resting-state functional magnetic resonance imaging (Rs-fMRI) data, we develop a multi-attribute graph model to construct a region-level functional connectivity network that uses all voxel level information. For each region pair, we define the strength of the connectivity as the kernel canonical correlation coefficient between voxels in the two regions; and we develop a permutation test to assess the statistical significance. We also construct a network based classifier for making predictions on the risk of MDD. We apply our method to Rs-fMRI data from 20 MDD patients and 20 healthy control subjects in the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study. Using this method, MDD patients can be distinguished from healthy control subjects based on significant differences in the strength of regional connectivity. We also demonstrate the performance of the proposed method using simulationstudies.

  3. Functional connectivity in task-negative network of the Deaf: effects of sign language experience

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    Evie Malaia

    2014-06-01

    Full Text Available Prior studies investigating cortical processing in Deaf signers suggest that life-long experience with sign language and/or auditory deprivation may alter the brain’s anatomical structure and the function of brain regions typically recruited for auditory processing (Emmorey et al., 2010; Pénicaud et al., 2013 inter alia. We report the first investigation of the task-negative network in Deaf signers and its functional connectivity—the temporal correlations among spatially remote neurophysiological events. We show that Deaf signers manifest increased functional connectivity between posterior cingulate/precuneus and left medial temporal gyrus (MTG, but also inferior parietal lobe and medial temporal gyrus in the right hemisphere- areas that have been found to show functional recruitment specifically during sign language processing. These findings suggest that the organization of the brain at the level of inter-network connectivity is likely affected by experience with processing visual language, although sensory deprivation could be another source of the difference. We hypothesize that connectivity alterations in the task negative network reflect predictive/automatized processing of the visual signal.

  4. Protein complex prediction based on k-connected subgraphs in protein interaction network

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    Habibi Mahnaz

    2010-09-01

    Full Text Available Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on connectivity number on subgraphs. We evaluate CFA using several protein interaction networks on reference protein complexes in two benchmark data sets (MIPS and Aloy, containing 1142 and 61 known complexes respectively. We compare CFA to some existing protein complex prediction methods (CMC, MCL, PCP and RNSC in terms of recall and precision. We show that CFA predicts more complexes correctly at a competitive level of precision. Conclusions Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number. Our CFA program and results are freely available from http://www.bioinf.cs.ipm.ir/softwares/cfa/CFA.rar.

  5. Early math achievement and functional connectivity in the fronto-parietal network.

    Science.gov (United States)

    Emerson, Robert W; Cantlon, Jessica F

    2012-02-15

    In this study we test the hypothesis that the functional connectivity of the frontal and parietal regions that children recruit during a basic numerical task (matching Arabic numerals to arrays of dots) is predictive of their math test scores (TEMA-3; Ginsburg, 2003). Specifically, we tested 4-11-year-old children on a matching task during fMRI to localize a fronto-parietal network that responds more strongly during numerical matching than matching faces, words, or shapes. We then tested the functional connectivity between those regions during an independent task: natural viewing of an educational video that included math topics. Using this novel natural viewing method, we found that the connectivity between frontal and parietal regions during task-independent free-viewing of educational material is correlated with children's basic number matching ability, as well as their scores on the standardized test of mathematical ability (the TEMA). The correlation between children's mathematics scores and fronto-parietal connectivity is math-specific in the sense that it is independent of children's verbal IQ scores. Moreover, a control network, selective for faces, showed no correlation with mathematics performance. Finally, brain regions that correlate with subjects' overall response times in the matching task do not account for our number- and math-related effects. We suggest that the functional intersection of number-related frontal and parietal regions is math-specific.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  8. Cognitive stimulation of the default-mode network modulates functional connectivity in healthy aging.

    Science.gov (United States)

    De Marco, Matteo; Meneghello, Francesca; Duzzi, Davide; Rigon, Jessica; Pilosio, Cristina; Venneri, Annalena

    2016-03-01

    A cognitive-stimulation tool was created to regulate functional connectivity within the brain Default-Mode Network (DMN). Computerized exercises were designed based on the hypothesis that repeated task-dependent coactivation of multiple DMN regions would translate into regulation of resting-state network connectivity. Forty seniors (mean age: 65.90 years; SD: 8.53) were recruited and assigned either to an experimental group (n=21) who received one month of intensive cognitive stimulation, or to a control group (n=19) who maintained a regime of daily-life activities explicitly focused on social interactions. An MRI protocol and a battery of neuropsychological tests were administered at baseline and at the end of the study. Changes in the DMN (measured via functional connectivity of posterior-cingulate seeds), in brain volumes, and in cognitive performance were measured with mixed models assessing group-by-timepoint interactions. Moreover, regression models were run to test gray-matter correlates of the various stimulation tasks. Significant associations were found between task performance and gray-matter volume of multiple DMN core regions. Training-dependent up-regulation of functional connectivity was found in the posterior DMN component. This interaction was driven by a pattern of increased connectivity in the training group, while little or no up-regulation was seen in the control group. Minimal changes in brain volumes were found, but there was no change in cognitive performance. The training-dependent regulation of functional connectivity within the posterior DMN component suggests that this stimulation program might exert a beneficial impact in the prevention and treatment of early AD neurodegeneration, in which this neurofunctional pathway is progressively affected by the disease.

  9. Changes in intrinsic connectivity of the brain's reading network following intervention in children with autism.

    Science.gov (United States)

    Murdaugh, Donna L; Maximo, Jose O; Kana, Rajesh K

    2015-08-01

    While task-based neuroimaging studies have identified alterations in neural circuitry underlying language processing in children with autism spectrum disorders [ASD], resting state functional magnetic resonance imaging [rsfMRI] is a promising alternative to the constraints posed by task-based fMRI. This study used rsfMRI, in a longitudinal design, to study the impact of a reading intervention on connectivity of the brain regions involved in reading comprehension in children with ASD. Functional connectivity was examined using group independent component analysis (GICA) and seed-based correlation analysis of Broca's and Wernicke's areas, in three groups of participants: an experimental group of ASD children (ASD-EXP), a wait list control group of ASD children (ASD-WLC), and a group of typically developing (TD) control children. Both GICA and seed-based analyses revealed stronger functional connectivity of Broca's and Wernicke's areas in the ASD-EXP group postintervention. Additionally, improvement in reading comprehension in the ASD-EXP group was correlated with greater connectivity in both Broca's and Wernicke's area in the GICA identified reading network component. In addition, increased connectivity between the Broca's area and right postcentral and right STG, and the Wernicke's area and LIFG, were also correlated with greater improvement in reading comprehension. Overall, this study revealed widespread changes in functional connectivity of the brain's reading network as a result of intervention in children with ASD. These novel findings provide valuable insights into the neuroplasticity of brain areas underlying reading and the impact of intensive intervention in modifying them in children with ASD.

  10. Dynamic modulation of rTMS on functional connectivity and functional network connectivity to children with cerebral palsy: a case report.

    Science.gov (United States)

    Guo, Zhiwei; Xing, Guoqiang; He, Bin; Chen, Huaping; Ou, Jun; McClure, Morgan A; Liu, Hua; Wang, Yunfeng; Mu, Qiwen

    2016-03-02

    Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive treatment tool for the recovery of cerebral palsy (CP). This report describes the modulation effect of rTMS to functional connectivity, functional network connectivity, motor, and cognitive ability following treatment in a child with mild ataxia CP. After receiving 8 months of 0.5 Hz rTMS treatment over the right dorsolateral prefrontal cortex, the child showed a gradual improvement in motor and cognitive-related functional connectivity and functional network connectivity following treatment as well as improved motor, cognitive functions. These pilot results provide the first evidence of the efficiency of 0.5 Hz of rTMS on a child with CP. Further large sample studies are needed to verify and expand the present findings.

  11. Women Connected to at Risk Indian Men Who Have Sex with Men: An Unexplored Network.

    Science.gov (United States)

    Satyanarayan, Sammita; Kapur, Abhinav; Azhar, Sameena; Yeldandi, Vijay; Schneider, John A

    2015-06-01

    Little is known about the women connected to Indian MSM and their impact on HIV risk. We surveyed 240 Indian MSM, who identified their social networks (n = 7,092). Women (n = 1,321) comprised 16.7 % of the network, with 94.7 % representing non-sexual connections. MSM were classified as having low, moderate, or high female network proportion. MSM with moderate female network proportion (8-24 % total network) had significantly lowered odds of HIV seropositivity (AOR = 0.24, 95 % CI = 0.1-0.6). This suggests moderate proportions of female connections could mediate HIV risk. HIV prevention interventions in India could consider the greater involvement of women among their target audiences. Se sabe poco sobre las mujeres conectadas a HSH en India y su impacto en el riesgo de VIH. Se encuestó a 240 HSH indios, quienes identificaron sus redes sociales (n = 7,092). Las mujeres (n = 1,321) formaron al 16.7 % de la red, del cual el 94.7 % representa conexiones no sexuales. Los HSH se clasificaron como baja, moderada o alta proporción de red femenina. HSH con proporción moderada de red femenina (8-24 % del red total) tuvieron un riesgo significativamente reducido de seropositividad de VIH (AOR = 0,24; IC 95 % = 0,1-0,6). Esto sugiere que tener una proporción moderada de contactos femeninos podría atenuar el riesgo de VIH. Las intervenciones de prevención del VIH en India podrían considerar una mayor participación de las mujeres en su público objetivo.

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

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    Recep Colak

    Full Text Available BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSION/SIGNIFICANCE: 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

  13. Assessing the congruence between perceived connectivity and network centrality measures specific to pandemic influenza preparedness in Alberta

    Directory of Open Access Journals (Sweden)

    Shiell Alan

    2010-03-01

    Full Text Available Abstract Background Recent research has suggested that perceived organizational connectivity may serve as an important measure of public health preparedness. Presumably, organizations with higher perceived connectivity also have a greater number of actual organizational ties. Using network analysis, we evaluate this presumption by assessing the correlation between perceived organizational connectivity and reported inter-organizational connections. Methods During late 2007-early 2008, representatives from organizations involved in the delivery of public health systems in Alberta were asked to complete an online questionnaire on public health preparedness. Organizational jurisdictional information was collected. Items from Dorn and colleagues connectivity scale (2007 were used to measure perceived organizational connectivity. Inter-organizational network data on formal connections in the area of pandemic influenza preparedness were collected using a roster approach. These data were imported into UCINET to calculate in- and out-degree centrality scores for each organization. One-way ANOVA tests assessed if perceived connectivity and in- and out-degree centrality varied among jurisdictions. Pearson correlation coefficients were used to assess the correlation of perceived connectivity and in- and out-degree centrality. Results Significant mean differences among jurisdictions were observed for in-degree (F(3,116 = 26.60, p F(3,116 = 5.24, p r(123 = 0.22, p r(123 = -0.07, p > 0.05. Conclusions The results suggest in terms of pandemic preparedness that perceived connectivity may serve as a partial proxy measure of formal out-degree network connectivity.

  14. Intrinsic default mode network connectivity predicts spontaneous verbal descriptions of autobiographical memories during social processing

    Directory of Open Access Journals (Sweden)

    Xiao-Fei eYang

    2013-01-01

    Full Text Available Neural systems activated in a coordinated way during rest, known as the default mode network (DMN, also support autobiographical memory (AM retrieval and social processing/mentalizing. However, little is known about how individual variability in reliance on personal memories during social processing relates to individual differences in DMN functioning during rest (intrinsic functional connectivity. Here we examined 18 participants’ spontaneous descriptions of autobiographical memories during a two-hour, private, open-ended interview in which they reacted to a series of true stories about real people’s social situations and responded to the prompt, how does this person’s story make you feel? We classified these descriptions as either containing factual information (semantic AMs or more elaborate descriptions of emotionally meaningful events (episodic AMs. We also collected resting state fMRI scans from the participants and related individual differences in frequency of described AMs to participants’ intrinsic functional connectivity within regions of the DMN. We found that producing more descriptions of either memory type correlated with stronger intrinsic connectivity in the parahippocampal and middle temporal gyri. Additionally, episodic AM descriptions correlated with connectivity in the bilateral hippocampi and medial prefrontal cortex, and semantic memory descriptions correlated with connectivity in right inferior lateral parietal cortex. These findings suggest that in individuals who naturally invoke more memories during social processing, brain regions involved in memory retrieval and self/social processing are more strongly coupled to the DMN during rest.

  15. Decreased connectivity of the default mode network in pathological gambling: a resting state functional MRI study.

    Science.gov (United States)

    Jung, Myung Hun; Kim, Jae-Hun; Shin, Young-Chul; Jung, Wi Hoon; Jang, Joon Hwan; Choi, Jung-Seok; Kang, Do-Hyung; Yi, Jung-Seo; Choi, Chi-Hoon; Kwon, Jun Soo

    2014-11-01

    The default mode network (DMN) represents neuronal activity that is intrinsically generated during a resting state. The present study used resting-state fMRI to investigate whether functional connectivity is altered in pathological gambling (PG). Fifteen drug-naive male patients with PG and 15 age-matched male control subjects participated in the present study. The pathological gambling modification of the Yale-Brown Obsessive Compulsive Scale (PG-YBOCS), the Beck Depression Inventory, and the Beck Anxiety Inventory were used to determine symptom severity in all participants. Participants were instructed to keep their eyes closed and not to focus on any particular thoughts during the 4.68-min resting-state functional scan. The patients with PG displayed decreased default mode connectivity in the left superior frontal gyrus, right middle temporal gyrus, and precuneus compared with healthy controls. The severity of PG symptoms in patients with PG was negatively associated with connectivity between the posterior cingulate cortex seed region and the precuneus (r=-0.599, p=0.018). Decreased functional connectivity within DMN suggests that PG may share similar neurobiological abnormalities with other addictive disorders. Moreover, the severity of PG symptoms was correlated with decreased connectivity in the precuneus, which may be important in the response to treatment in patients with PG.

  16. Altered effective connectivity within default mode network in major depression disorder

    Science.gov (United States)

    Li, Liang; Li, Baojuan; Bai, Yuanhan; Wang, Huaning; Zhang, Linchuan; Cui, Longbiao; Lu, Hongbing

    2016-03-01

    Understanding the neural basis of Major Depressive Disorder (MDD) is important for the diagnosis and treatment of this mental disorder. The default mode network (DMN) is considered to be highly involved in the MDD. To find directed interaction between DMN regions associated with the development of MDD, the effective connectivity within the DMN of the MDD patients and matched healthy controls was estimated by using a recently developed spectral dynamic causal modeling. Sixteen patients with MDD and sixteen matched healthy control subjects were included in this study. While the control group underwent the resting state fMRI scan just once, all patients underwent resting state fMRI scans before and after two months' treatment. The spectral dynamic causal modeling was used to estimate directed connections between four DMN nodes. Statistical analysis on connection strengths indicated that efferent connections from the medial frontal cortex (MFC) to posterior cingulate cortex (PCC) and to right parietal cortex (RPC) were significant higher in pretreatment MDD patients than those of the control group. After two-month treatment, the efferent connections from the MFC decreased significantly, while those from the left parietal cortex (LPC) to MFC, PCC and RPC showed a significant increase. These findings suggest that the MFC may play an important role for inhibitory conditioning of the DMN, which was disrupted in MDD patients. It also indicates that disrupted suppressive function of the MFC could be effectively restored after two-month treatment.

  17. Bifurcations in time-delay fully-connected networks with symmetry

    Directory of Open Access Journals (Sweden)

    Ferruzzo Correa Diego Paolo

    2014-01-01

    Full Text Available In this work a brief method for finding steady-state and Hopf bifurcations in a (R + 1-th order N-node time-delay fully-connected network with symmetry is explored. A self-sustained Phase-Locked Loop is used as node. The irreducible representations found due to the network symmetry are used to find regions of time-delay independent stability/instability in the parameter space. Symmetry-preserving and symmetry-breaking bifurcations can be computed numerically using the Sn map proposed in [1]. The analytic results show the existence of symmetry-breaking bifurcations with multiplicity N − 1. A second-order N-node network is used as application example. This work is a generalization of some results presented in [2].

  18. Constrained Synaptic Connectivity in Functional Mammalian Neuronal Networks Grown on Patterned Surfaces

    Science.gov (United States)

    Bourdieu, Laurent; Wyart, Claire; Ybert, Christophe; Herr, Catherine; Chatenay, Didier

    2002-03-01

    The use of ordered neuronal networks in vitro is a promising approach to study the development and the activity of neuronal assemblies. However in previous attempts, sufficient growth control and physiological maturation of neurons could not be achieved. We describe an original protocol in which polylysine patterns confine the adhesion of cellular bodies to prescribed spots and the neuritic growth to thin lines. Hippocampal neurons are maintained healthy in serum free medium up to five weeks in vitro. Electrophysiology and immunochemistry show that neurons exhibit mature excitatory and inhibitory synapses and calcium imaging reveals spontaneous bursting activity of neurons in isolated networks. Neurons in these geometrical networks form functional synapses preferentially to their first neighbors. We have therefore established a simple and robust protocol to constrain both the location of neuronal cell bodies and their pattern of connectivity.

  19. Brain Network Connectivity During Language Comprehension: Interacting Linguistic and Perceptual Subsystems.

    Science.gov (United States)

    Fonteneau, Elisabeth; Bozic, Mirjana; Marslen-Wilson, William D

    2015-10-01

    The dynamic neural processes underlying spoken language comprehension require the real-time integration of general perceptual and specialized linguistic information. We recorded combined electro- and magnetoencephalographic measurements of participants listening to spoken words varying in perceptual and linguistic complexity. Combinatorial linguistic complexity processing was consistently localized to left perisylvian cortices, whereas competition-based perceptual complexity triggered distributed activity over both hemispheres. Functional connectivity showed that linguistically complex words engaged a distributed network of oscillations in the gamma band (20-60 Hz), which only partially overlapped with the network supporting perceptual analysis. Both processes enhanced cross-talk between left temporal regions and bilateral pars orbitalis (BA47). The left-lateralized synchrony between temporal regions and pars opercularis (BA44) was specific to the linguistically complex words, suggesting a specific role of left frontotemporal cross-cortical interactions in morphosyntactic computations. Synchronizations in oscillatory dynamics reveal the transient coupling of functional networks that support specific computational processes in language comprehension.

  20. Small-World Connections to Induce Firing Activity and Phase Synchronization in Neural Networks

    Institute of Scientific and Technical Information of China (English)

    QIN Ying-Hua; LUO Xiao-Shu

    2009-01-01

    We investigate how the firing activity and the subsequent phase synchronization of neural networks with small-world topological connections depend on the probability p of adding-links. Network elements are described by two-dimensional map neurons (2DMNs) in a quiescent original state. Neurons burst for a given coupling strength when the topological randomness p increases, which is absent in a regular-lattice neural network. The bursting activity becomes frequent and synchronization of neurons emerges as topological randomness further increases.The maximal firing frequency and phase synchronization appear at a particular value of p. However, if the randomness p further increases, the firing frequency decreases and synchronization is apparently destroyed.

  1. RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks

    Energy Technology Data Exchange (ETDEWEB)

    Balasundaram, Balabhaskar [Oklahoma State Univ., Stillwater, OK (United States); Butenko, Sergiy [Texas A & M Univ., College Station, TX (United States); Boginski, Vladimir [Univ. of Florida, Gainesville, FL (United States); Uryasev, Stan [Univ. of Florida, Gainesville, FL (United States)

    2013-12-25

    The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need

  2. Deficits in episodic memory retrieval reveal impaired default mode network connectivity in amnestic mild cognitive impairment

    Directory of Open Access Journals (Sweden)

    Cameron J. Dunn

    2014-01-01

    Full Text Available Amnestic mild cognitive impairment (aMCI is believed to represent a transitional stage between normal healthy ageing and the development of dementia. In particular, aMCI patients have been shown to have higher annual transition rates to Alzheimer's Disease (AD than individuals without cognitive impairment. Despite intensifying interest investigating the neuroanatomical basis of this transition, there remain a number of questions regarding the pathophysiological process underlying aMCI itself. A number of recent studies in aMCI have shown specific impairments in connectivity within the default mode network (DMN, which is a group of regions strongly related to episodic memory capacities. However to date, no study has investigated the integrity of the DMN between patients with aMCI and those with a non-amnestic pattern of MCI (naMCI, who have cognitive impairment, but intact memory storage systems. In this study, we contrasted the DMN connectivity in 24 aMCI and 33 naMCI patients using seed-based resting state fMRI. The two groups showed no statistical difference in their DMN intra-connectivity. However when connectivity was analysed according to performance on measures of episodic memory retrieval, the two groups were separable, with aMCI patients demonstrating impaired functional connectivity between the hippocampal formation and the posterior cingulate cortex. We provide evidence that this lack of connectivity is driven by impaired communication from the posterior cingulate hub and does not simply represent hippocampal atrophy, suggesting that posterior cingulate degeneration is the driving force behind impaired DMN connectivity in aMCI.

  3. Deficits in episodic memory retrieval reveal impaired default mode network connectivity in amnestic mild cognitive impairment

    Science.gov (United States)

    Dunn, Cameron J.; Duffy, Shantel L; Hickie, Ian B; Lagopoulos, Jim; Lewis, Simon J.G.; Naismith, Sharon L.; Shine, James M.

    2014-01-01

    Amnestic mild cognitive impairment (aMCI) is believed to represent a transitional stage between normal healthy ageing and the development of dementia. In particular, aMCI patients have been shown to have higher annual transition rates to Alzheimer's Disease (AD) than individuals without cognitive impairment. Despite intensifying interest investigating the neuroanatomical basis of this transition, there remain a number of questions regarding the pathophysiological process underlying aMCI itself. A number of recent studies in aMCI have shown specific impairments in connectivity within the default mode network (DMN), which is a group of regions strongly related to episodic memory capacities. However to date, no study has investigated the integrity of the DMN between patients with aMCI and those with a non-amnestic pattern of MCI (naMCI), who have cognitive impairment, but intact memory storage systems. In this study, we contrasted the DMN connectivity in 24 aMCI and 33 naMCI patients using seed-based resting state fMRI. The two groups showed no statistical difference in their DMN intra-connectivity. However when connectivity was analysed according to performance on measures of episodic memory retrieval, the two groups were separable, with aMCI patients demonstrating impaired functional connectivity between the hippocampal formation and the posterior cingulate cortex. We provide evidence that this lack of connectivity is driven by impaired communication from the posterior cingulate hub and does not simply represent hippocampal atrophy, suggesting that posterior cingulate degeneration is the driving force behind impaired DMN connectivity in aMCI. PMID:24634833

  4. Evaluation of a Cyber Security System for Hospital Network.

    Science.gov (United States)

    Faysel, Mohammad A

    2015-01-01

    Most of the cyber security systems use simulated data in evaluating their detection capabilities. The proposed cyber security system utilizes real hospital network connections. It uses a probabilistic data mining algorithm to detect anomalous events and takes appropriate response in real-time. On an evaluation using real-world hospital network data consisting of incoming network connections collected for a 24-hour period, the proposed system detected 15 unusual connections which were undetected by a commercial intrusion prevention system for the same network connections. Evaluation of the proposed system shows a potential to secure protected patient health information on a hospital network.

  5. Does landscape connectivity shape local and global social network structure in white-tailed deer?

    Science.gov (United States)

    Koen, Erin L; Tosa, Marie I; Nielsen, Clayton K; Schauber, Eric M

    2017-01-01

    Intraspecific social behavior can be influenced by both intrinsic and extrinsic factors. While much research has focused on how characteristics of individuals influence their roles in social networks, we were interested in the role that landscape structure plays in animal sociality at both individual (local) and population (global) levels. We used female white-tailed deer (Odocoileus virginianus) in Illinois, USA, to investigate the potential effect of landscape on social network structure by weighting the edges of seasonal social networks with association rate (based on proximity inferred from GPS collar data). At the local level, we found that sociality among female deer in neighboring social groups (n = 36) was mainly explained by their home range overlap, with two exceptions: 1) during fawning in an area of mixed forest and grassland, deer whose home ranges had low forest connectivity were more social than expected; and 2) during the rut in an area of intensive agriculture, deer inhabiting home ranges with high amount and connectedness of agriculture were more social than expected. At the global scale, we found that deer populations (n = 7) in areas with highly connected forest-agriculture edge, a high proportion of agriculture, and a low proportion of forest tended to have higher weighted network closeness, although low sample size precluded statistical significance. This result implies that infectious disease could spread faster in deer populations inhabiting such landscapes. Our work advances the general understanding of animal social networks, demonstrating how landscape features can underlie differences in social behavior both within and among wildlife social networks.

  6. Impact of Radio Link Unreliability on the Connectivity of Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jean-Marie Gorce

    2007-06-01

    Full Text Available Many works have been devoted to connectivity of ad hoc networks. This is an important feature for wireless sensor networks (WSNs to provide the nodes with the capability of communicating with one or several sinks. In most of these works, radio links are assumed ideal, that is, with no transmission errors. To fulfil this assumption, the reception threshold should be high enough to guarantee that radio links have a low transmission error probability. As a consequence, all unreliable links are dismissed. This approach is suboptimal concerning energy consumption because unreliable links should permit to reduce either the transmission power or the number of active nodes. The aim of this paper is to quantify the contribution of unreliable long hops to an increase of the connectivity of WSNs. In our model, each node is assumed to be connected to each other node in a probabilistic manner. Such a network is modeled as a complete random graph, that is, all edges exist. The instantaneous node degree is then defined as the number of simultaneous valid single-hop receptions of the same message, and finally the mean node degree is computed analytically in both AWGN and block-fading channels. We show the impact on connectivity of two MACs and routing parameters. The first one is the energy detection level such as the one used in carrier sense mechanisms. The second one is the reliability threshold used by the routing layer to select stable links only. Both analytic and simulation results show that using opportunistic protocols is challenging.

  7. Network-based characterization of brain functional connectivity in Zen practitioners.

    Science.gov (United States)

    Kemmer, Phebe B; Guo, Ying; Wang, Yikai; Pagnoni, Giuseppe

    2015-01-01

    In the last decade, a number of neuroimaging studies have investigated the neurophysiological effects associated with contemplative practices. Meditation-related changes in resting state functional connectivity (rsFC) have been previously reported, particularly in the default mode network, frontoparietal attentional circuits, saliency-related regions, and primary sensory cortices. We collected functional magnetic resonance imaging data from a sample of 12 experienced Zen meditators and 12 meditation-naïve matched controls during a basic attention-to-breathing protocol, together with behavioral performance outside the scanner on a set of computerized neuropsychological tests. We adopted a network system of 209 nodes, classified into nine functional modules, and a multi-stage approach to identify rsFC differences in meditators and controls. Between-group comparisons of modulewise FC, summarized by the first principal component of the relevant set of edges, revealed important connections of frontoparietal circuits with early visual and executive control areas. We also identified several group differences in positive and negative edgewise FC, often involving the visual, or frontoparietal regions. Multivariate pattern analysis of modulewise FC, using support vector machine (SVM), classified meditators, and controls with 79% accuracy and selected 10 modulewise connections that were jointly prominent in distinguishing meditators and controls; a similar SVM procedure based on the subjects' scores on the neuropsychological battery yielded a slightly weaker accuracy (75%). Finally, we observed a good correlation between the across-subject variation in strength of modulewise connections among frontoparietal, executive, and visual circuits, on the one hand, and in the performance on a rapid visual information processing test of sustained attention, on the other. Taken together, these findings highlight the usefulness of employing network analysis techniques in investigating

  8. Network-based characterization of brain functional connectivity in Zen practitioners

    Directory of Open Access Journals (Sweden)

    Phebe Brenne Kemmer

    2015-05-01

    Full Text Available In the last decade, a number of neuroimaging studies have investigated the neurophysiological effects associated with contemplative practices. Meditation-related changes in resting state functional connectivity (rsFC have been previously reported, particularly in the default mode network, frontoparietal (FP attentional circuits, saliency-related regions, and primary sensory cortices. We collected fMRI data from a sample of 12 experienced Zen meditators and 12 meditation-naïve matched controls during a basic attention-to-breathing protocol, together with behavioral performance outside the scanner on a set of computerized neuropsychological tests. We adopted a network system of 209 nodes, classified into 9 functional modules, and a multi-stage approach to identify rsFC differences in meditators and controls. Between-group comparisons of modulewise FC, summarized by the first principal component of the relevant set of edges, revealed important connections of FP circuits with early visual and executive control areas. We also identified several group differences in positive and negative edgewise FC, often involving the visual or FP regions. Multivariate pattern analysis of modulewise FC, using Support Vector Machine (SVM, classified meditators and controls with 79% accuracy and selected 10 modulewise connections that were jointly prominent in distinguishing meditators and controls; a similar SVM procedure based on the subjects' scores on the neuropsychological battery yielded a slightly weaker accuracy (75%. Finally, we observed a good correlation between the across-subject variation in strength of modulewise connections among FP, executive, and visual circuits, on the one hand, and in the performance on a rapid visual information processing (RVIP test of sustained attention, on the other. Taken together, these findings highlight the usefulness of employing network analysis techniques in investigating the neural correlates of contemplative practices.

  9. Impact of Radio Link Unreliability on the Connectivity of Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Gorce Jean-Marie

    2007-01-01

    Full Text Available Many works have been devoted to connectivity of ad hoc networks. This is an important feature for wireless sensor networks (WSNs to provide the nodes with the capability of communicating with one or several sinks. In most of these works, radio links are assumed ideal, that is, with no transmission errors. To fulfil this assumption, the reception threshold should be high enough to guarantee that radio links have a low transmission error probability. As a consequence, all unreliable links are dismissed. This approach is suboptimal concerning energy consumption because unreliable links should permit to reduce either the transmission power or the number of active nodes. The aim of this paper is to quantify the contribution of unreliable long hops to an increase of the connectivity of WSNs. In our model, each node is assumed to be connected to each other node in a probabilistic manner. Such a network is modeled as a complete random graph, that is, all edges exist. The instantaneous node degree is then defined as the number of simultaneous valid single-hop receptions of the same message, and finally the mean node degree is computed analytically in both AWGN and block-fading channels. We show the impact on connectivity of two MACs and routing parameters. The first one is the energy detection level such as the one used in carrier sense mechanisms. The second one is the reliability threshold used by the routing layer to select stable links only. Both analytic and simulation results show that using opportunistic protocols is challenging.

  10. Nonlinear Dynamical Behavior in BS Evolution Model Based on Small-World Network Added with Mechanism of Preferential Connection

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    In this paper, we introduce a modified small-world network added with new links with preferential connection instead of adding randomly, then we apply Bak-Sneppen (BS) evolution model on this network. Several dynamical character of the model such as the evolution graph, fo avalanche, the critical exponent D and τ, and the distribution of mutation times of all the nodes, show particular behaviors different from those of the model based on the regular network and the small-world network.

  11. Increased functional connectivity with puberty in the mentalising network involved in social emotion processing.

    Science.gov (United States)

    Klapwijk, Eduard T; Goddings, Anne-Lise; Burnett Heyes, Stephanie; Bird, Geoffrey; Viner, Russell M; Blakemore, Sarah-Jayne

    2013-07-01

    This article is part of a Special Issue "Puberty and Adolescence". There is increasing evidence that puberty plays an important role in the structural and functional brain development seen in adolescence, but little is known of the pubertal influence on changes in functional connectivity. We explored how pubertal indicators (salivary concentrations of testosterone, oestradiol and DHEA; pubertal stage; menarcheal status) relate to functional connectivity between components of a mentalising network identified to be engaged in social emotion processing by our prior work, using psychophysiological interaction (PPI) analysis. Female adolescents aged 11 to 13years were scanned whilst silently reading scenarios designed to evoke either social emotions (guilt and embarrassment) or basic emotions (disgust and fear), of which only social compared to basic emotions require the representation of another person's mental states. Pubertal stage and menarcheal status were used to assign participants to pre/early or mid/late puberty groups. We found increased functional connectivity between the dorsomedial prefrontal cortex (DMPFC) and the right posterior superior temporal sulcus (pSTS) and right temporo-parietal junction (TPJ) during social relative to basic emotion processing. Moreover, increasing oestradiol concentrations were associated with increased functional connectivity between the DMPFC and the right TPJ during social relative to basic emotion processing, independent of age. Our analysis of the PPI data by phenotypic pubertal status showed that more advanced puberty stage was associated with enhanced functional connectivity between the DMPFC and the left anterior temporal cortex (ATC) during social relative to basic emotion processing, also independent of age. Our results suggest increased functional maturation of the social brain network with the advancement of puberty in girls.

  12. Interplay between functional connectivity and scale-free dynamics in intrinsic fMRI networks.

    Science.gov (United States)

    Ciuciu, Philippe; Abry, Patrice; He, Biyu J

    2014-07-15

    Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra - a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework - a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and while performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately - resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well.

  13. Bipolar and borderline patients display differential patterns of functional connectivity among resting state networks.

    Science.gov (United States)

    Das, Pritha; Calhoun, Vince; Malhi, Gin S

    2014-09-01

    Bipolar disorder (BD) and borderline personality (BPD) disorder share clinical features such as emotional lability and poor interpersonal functioning but the course of illness and treatment differs in these groups, which suggests that the underlying neurobiology of BD and BPD is likely to be different. Understanding the neural mechanisms behind the pathophysiology of BD and BPD will facilitate accurate diagnosis and inform the administration of targeted treatment. Since deficits in social cognition or emotion regulation or in the self-referential processing system can give rise to these clinical features, and impairment in these domains have been observed in both patient groups, functional connectivity within and between networks subserving these processes during resting was investigated using functional magnetic resonance imaging. Data were acquired from 16 patients with BD, 14 patients with BPD, and 13 healthy controls (HC) and functional connectivity strength was correlated with scores using the Difficulties in Emotion Regulation Scale. Functional network connectivity (FNC) patterns differentiated BD and BPD patients from HC. In BD, FNC was increased while in BPD it was decreased. In BD impaired FNC was evident primarily among networks involved in self-referential processing while in BPD it also involved the emotion regulatory network. Impaired FNC displayed an association with impulsivity in BPD and emotional clarity and emotional awareness in BD. This study shows that BD and BPD can perhaps be differentiated using resting state FNC approach and that the neural mechanisms underpinning overlapping symptoms discernibly differ between the groups. These findings provide a potential platform for elucidating the targeted effects of psychological interventions in both disorders.

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

    Science.gov (United States)

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

    2008-10-01

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

  15. Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

    Directory of Open Access Journals (Sweden)

    E. M. A. Perrier

    2010-04-01

    Full Text Available Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a Critical Filtration Size (CFS delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009. Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

  16. Percolation properties of 3-D multiscale pore networks: how connectivity controls soil filtration processes

    Directory of Open Access Journals (Sweden)

    E. M. A. Perrier

    2010-10-01

    Full Text Available Quantifying the connectivity of pore networks is a key issue not only for modelling fluid flow and solute transport in porous media but also for assessing the ability of soil ecosystems to filter bacteria, viruses and any type of living microorganisms as well inert particles which pose a contamination risk. Straining is the main mechanical component of filtration processes: it is due to size effects, when a given soil retains a conveyed entity larger than the pores through which it is attempting to pass. We postulate that the range of sizes of entities which can be trapped inside soils has to be associated with the large range of scales involved in natural soil structures and that information on the pore size distribution has to be complemented by information on a critical filtration size (CFS delimiting the transition between percolating and non percolating regimes in multiscale pore networks. We show that the mass fractal dimensions which are classically used in soil science to quantify scaling laws in observed pore size distributions can also be used to build 3-D multiscale models of pore networks exhibiting such a critical transition. We extend to the 3-D case a new theoretical approach recently developed to address the connectivity of 2-D fractal networks (Bird and Perrier, 2009. Theoretical arguments based on renormalisation functions provide insight into multi-scale connectivity and a first estimation of CFS. Numerical experiments on 3-D prefractal media confirm the qualitative theory. These results open the way towards a new methodology to estimate soil filtration efficiency from the construction of soil structural models to be calibrated on available multiscale data.

  17. Investigating changes in brain network properties in HIV-associated neurocognitive disease (HAND) using mutual connectivity analysis (MCA)

    Science.gov (United States)

    Abidin, Anas Zainul; D'Souza, Adora M.; Nagarajan, Mahesh B.; Wismüller, Axel

    2016-03-01

    About 50% of subjects infected with HIV present deficits in cognitive domains, which are known collectively as HIV associated neurocognitive disorder (HAND). The underlying synaptodendritic damage can be captured using resting state functional MRI, as has been demonstrated by a few earlier studies. Such damage may induce topological changes of brain connectivity networks. We test this hypothesis by capturing the functional interdependence of 90 brain network nodes using a Mutual Connectivity Analysis (MCA) framework with non-linear time series modeling based on Generalized Radial Basis function (GRBF) neural networks. The network nodes are selected based on the regions defined in the Automated Anatomic Labeling (AAL) atlas. Each node is represented by the average time series of the voxels of that region. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We tested for differences in these properties in network graphs obtained for 10 subjects (6 male and 4 female, 5 HIV+ and 5 HIV-). Global network properties captured some differences between these subject cohorts, though significant differences were seen only with the clustering coefficient measure. Local network properties, such as local efficiency and the degree of connections, captured significant differences in regions of the frontal lobe, precentral and cingulate cortex amongst a few others. These results suggest that our method can be used to effectively capture differences occurring in brain network connectivity properties revealed by resting-state functional MRI in neurological disease states, such as HAND.

  18. Perturbed connectivity of the amygdala and its subregions with the central executive and default mode networks in chronic pain.

    Science.gov (United States)

    Jiang, Ying; Oathes, Desmond; Hush, Julia; Darnall, Beth; Charvat, Mylea; Mackey, Sean; Etkin, Amit

    2016-09-01

    Maladaptive responses to pain-related distress, such as pain catastrophizing, amplify the impairments associated with chronic pain. Many of these aspects of chronic pain are similar to affective distress in clinical anxiety disorders. In light of the role of the amygdala in pain and affective distress, disruption of amygdalar functional connectivity in anxiety states, and its implication in the response to noxious stimuli, we investigated amygdala functional connectivity in 17 patients with chronic low back pain and 17 healthy comparison subjects, with respect to normal targets of amygdala subregions (basolateral vs centromedial nuclei), and connectivity to large-scale cognitive-emotional networks, including the default mode network, central executive network, and salience network. We found that patients with chronic pain had exaggerated and abnormal amygdala connectivity with central executive network, which was most exaggerated in patients with the greatest pain catastrophizing. We also found that the normally basolateral-predominant amygdala connectivity to the default mode network was blunted in patients with chronic pain. Our results therefore highlight the importance of the amygdala and its network-level interaction with large-scale cognitive/affective cortical networks in chronic pain, and help link the neurobiological mechanisms of cognitive theories for pain with other clinical states of affective distress.

  19. Demand-Supply Optimization with Risk Management for a Multi-Connection Water Reservoir Network

    CERN Document Server

    Chatpatanasiri, Ratthachat

    2009-01-01

    In this paper, we propose a framework to solve a demand-supply optimization problem of long-term water resource allocation on a multi-connection reservoir network which, in two aspects, is different to the problem considered in previous works. First, while all previous works consider a problem where each reservoir can transfer water to only one fixed reservoir, we consider a multi-connection network being constructed in Thailand in which each reservoir can transfer water to many reservoirs in one period of time. Second, a demand-supply plan considered here is static, in contrast to a dynamic policy considered in previous works. Moreover, in order to efficiently develop a long-term static plan, a severe loss (a risk) is taken into account, i.e. a risk occurs if the real amount of water stored in each reservoir in each time period is less than what planned by the optimizer. The multi-connection function and the risk make the problem rather complex such that traditional stochastic dynamic programming and determi...

  20. Dynamic morphometric characterization of local connective tissue network structure in humans using ultrasound

    Directory of Open Access Journals (Sweden)

    Konofagou Elisa E

    2007-06-01

    Full Text Available Abstract Background In humans, connective tissue forms a complex, interconnected network throughout the body that may have mechanosensory, regulatory and signaling functions. Understanding these potentially important phenomena requires non-invasive measurements of collagen network structure that can be performed in live animals or humans. The goal of this study was to show that ultrasound can be used to quantify dynamic changes in local connective tissue structure in vivo. We first performed combined ultrasound and histology examinations of the same tissue in two subjects undergoing surgery: in one subject, we examined the relationship of ultrasound to histological images in three dimensions; in the other, we examined the effect of a localized tissue perturbation using a previously developed robotic acupuncture needling technique. In ten additional non-surgical subjects, we quantified changes in tissue spatial organization over time during needle rotation vs. no rotation using ultrasound and semi-variogram analyses. Results 3-D renditions of ultrasound images showed longitudinal echogenic sheets that matched with collagenous sheets seen in histological preparations. Rank correlations between serial 2-D ultrasound and corresponding histology images resulted in high positive correlations for semi-variogram ranges computed parallel (r = 0.79, p Conclusion The combination of ultrasound and semi-variogram analyses allows quantitative assessment of dynamic changes in the structure of human connective tissue in vivo.

  1. Dynamical scalability and control of totally connected spin networks across quantum phase transitions

    Science.gov (United States)

    Acevedo, Óscar L.; Quiroga, Luis; Rodríguez, Ferney J.; Johnson, Neil F.

    2014-03-01

    Dynamical quantum phase crossings of spin networks have recently received increased attention thanks to their relation to adiabatic quantum computing, and their feasible realizations using ultra-cold atomic and molecular systems with a highly tunable degree of connectivity. Dynamical scaling of spatially distributed systems like Ising models have been widely studied, and successfully related to well-known theories like the Kibble-Zurek mechanism. The case of totally connected networks such as the Dicke Model and Lipkin-Meshkov-Glick Model, however, is known to exhibit a breakdown of these frameworks. Our analysis overcomes the lack of spatial correlation structure by developing a general approach which (i) is valid regardless the connectivity of the system, (ii) goes beyond critical exponents, and (iii) provides a time-resolved picture of dynamical scaling. By treating these models as a method for macroscopic quantum control of their subsystems, we have found microscopic signatures of the dynamical scaling as well as instances of dynamical enhancement of distinctive quantum properties such as entanglement and coherence. Our results yield novel prescriptions for the fields of quantum simulations and quantum control, and deepen our fundamental understanding of phase transitions.

  2. Network science and the effects of music preference on functional brain connectivity: from Beethoven to Eminem.

    Science.gov (United States)

    Wilkins, R W; Hodges, D A; Laurienti, P J; Steen, M; Burdette, J H

    2014-08-28

    Most people choose to listen to music that they prefer or 'like' such as classical, country or rock. Previous research has focused on how different characteristics of music (i.e., classical versus country) affect the brain. Yet, when listening to preferred music--regardless of the type--people report they often experience personal thoughts and memories. To date, understanding how this occurs in the brain has remained elusive. Using network science methods, we evaluated differences in functional brain connectivity when individuals listened to complete songs. We show that a circuit important for internally-focused thoughts, known as the default mode network, was most connected when listening to preferred music. We also show that listening to a favorite song alters the connectivity between auditory brain areas and the hippocampus, a region responsible for memory and social emotion consolidation. Given that musical preferences are uniquely individualized phenomena and that music can vary in acoustic complexity and the presence or absence of lyrics, the consistency of our results was unexpected. These findings may explain why comparable emotional and mental states can be experienced by people listening to music that differs as widely as Beethoven and Eminem. The neurobiological and neurorehabilitation implications of these results are discussed.

  3. Fully Connected Neural Networks Ensemble with Signal Strength Clustering for Indoor Localization in Wireless Sensor Networks

    OpenAIRE

    2015-01-01

    The paper introduces a method which improves localization accuracy of the signal strength fingerprinting approach. According to the proposed method, entire localization area is divided into regions by clustering the fingerprint database. For each region a prototype of the received signal strength is determined and a dedicated artificial neural network (ANN) is trained by using only those fingerprints that belong to this region (cluster). Final estimation of the location is obtained by fusion ...

  4. Connect and win: The role of social networks in political elections

    CERN Document Server

    Halu, Arda; Baronchelli, Andrea; Bianconi, Ginestra

    2012-01-01

    Many networks do not live in isolation but are strongly interacting, with profound consequences on their dynamics. Here, we consider the case of two interacting social networks and, in the context of a simple model, we address the case of political elections. Each network represents a competing party and every agent on the election day can choose to be either active in one of the two networks (vote for the corresponding party) or to be inactive in both (not vote). The opinion dynamics during the election campaign is described through a simulated annealing algorithm. We find that for a large region of the parameter space the result of the competition between the two parties allows for the existence of pluralism in the society, where both parties have a finite share of the votes. The central result is that a densely connected social network is key for the final victory of a party. However, small committed minorities can play a crucial role, and even reverse the election outcome.

  5. Fault Location Identification for Localized Intermittent Connection Problems on CAN Networks

    Institute of Scientific and Technical Information of China (English)

    LEI Yong; YUAN Yong; SUN Yichao

    2014-01-01

    The intermittent connection(IC) of the field-bus in networked manufacturing systems is a common but hard troubleshooting network problem, which may result in system level failures or safety issues. However, there is no online IC location identification method available to detect and locate the position of the problem. To tackle this problem, a novel model based online fault location identification method for localized IC problem is proposed. First, the error event patterns are identified and classified according to different node sources in each error frame. Then generalized zero inflated Poisson process(GZIP) model for each node is established by using time stamped error event sequence. Finally, the location of the IC fault is determined by testing whether the parameters of the fitted stochastic model is statistically significant or not using the confident intervals of the estimated parameters. To illustrate the proposed method, case studies are conducted on a 3-node controller area network(CAN) test-bed, in which IC induced faults are imposed on a network drop cable using computer controlled on-off switches. The experimental results show the parameters of the GZIP model for the problematic node are statistically significant(larger than 0), and the patterns of the confident intervals of the estimated parameters are directly linked to the problematic node, which agrees with the experimental setup. The proposed online IC location identification method can successfully identify the location of the drop cable on which IC faults occurs on the CAN network.

  6. Connect and win: The role of social networks in political elections

    Science.gov (United States)

    Halu, Arda; Zhao, Kun; Baronchelli, Andrea; Bianconi, Ginestra

    2013-04-01

    Many real systems are made of strongly interacting networks, with profound consequences on their dynamics. Here, we consider the case of two interacting social networks and, in the context of a simple model, we address the case of political elections. Each network represents a competing party and every agent, on the election day, can choose to be either active in one of the two networks (vote for the corresponding party) or to be inactive in both (not vote). The opinion dynamics during the election campaign is described through a simulated annealing algorithm. We find that for a large region of the parameter space the result of the competition between the two parties allows for the existence of pluralism in the society, where both parties have a finite share of the votes. The central result is that a densely connected social network is key for the final victory of a party. However, small committed minorities can play a crucial role, and even reverse the election outcome.

  7. Advancing the boundaries of high-connectivity network simulation with distributed computing.

    Science.gov (United States)

    Morrison, Abigail; Mehring, Carsten; Geisel, Theo; Aertsen, A D; Diesmann, Markus

    2005-08-01

    The availability of efficient and reliable simulation tools is one of the mission-critical technologies in the fast-moving field of computational neuroscience. Research indicates that higher brain functions emerge from large and complex cortical networks and their interactions. The large number of elements (neurons) combined with the high connectivity (synapses) of the biological network and the specific type of interactions impose severe constraints on the explorable system size that previously have been hard to overcome. Here we present a collection of new techniques combined to a coherent simulation tool removing the fundamental obstacle in the computational study of biological neural networks: the enormous number of synaptic contacts per neuron. Distributing an individual simulation over multiple computers enables the investigation of networks orders of magnitude larger than previously possible. The software scales excellently on a wide range of tested hardware, so it can be used in an interactive and iterative fashion for the development of ideas, and results can be produced quickly even for very large networks. In contrast to earlier approaches, a wide class of neuron models and synaptic dynamics can be represented.

  8. Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring

    Directory of Open Access Journals (Sweden)

    Naisen Liu

    2016-12-01

    Full Text Available Wireless sensor networks (WSNs are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA. In order to realize full coverage and k-connectivity WSN deployment for monitoring crop growth information of farmland on a large scale and to ensure the accuracy of the monitored data, a new WSN deployment method using a genetic algorithm (GA is here proposed. The fitness function of GA was constructed based on the following WSN deployment criteria: (1 nodes must be located in the corresponding plots; (2 WSN must have k-connectivity; (3 WSN must have no communication silos; (4 the minimum distance between node and plot boundary must be greater than a specific value to prevent each node from being affected by the farmland edge effect. The deployment experiments were performed on natural farmland and on irregular farmland divided based on spatial differences of soil nutrients. Results showed that both WSNs gave full coverage, there were no communication silos, and the minimum connectivity of nodes was equal to k. The deployment was tested for different values of k and transmission distance (d to the node. The results showed that, when d was set to 200 m, as k increased from 2 to 4 the minimum connectivity of nodes increases and is equal to k. When k was set to 2, the average connectivity of all nodes increased in a linear manner with the increase of d from 140 m to 250 m, and the minimum connectivity does not change.

  9. Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring

    Science.gov (United States)

    Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

    2016-01-01

    Wireless sensor networks (WSNs) are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA). In order to realize full coverage and k-connectivity WSN deployment for monitoring crop growth information of farmland on a large scale and to ensure the accuracy of the monitored data, a new WSN deployment method using a genetic algorithm (GA) is here proposed. The fitness function of GA was constructed based on the following WSN deployment criteria: (1) nodes must be located in the corresponding plots; (2) WSN must have k-connectivity; (3) WSN must have no communication silos; (4) the minimum distance between node and plot boundary must be greater than a specific value to prevent each node from being affected by the farmland edge effect. The deployment experiments were performed on natural farmland and on irregular farmland divided based on spatial differences of soil nutrients. Results showed that both WSNs gave full coverage, there were no communication silos, and the minimum connectivity of nodes was equal to k. The deployment was tested for different values of k and transmission distance (d) to the node. The results showed that, when d was set to 200 m, as k increased from 2 to 4 the minimum connectivity of nodes increases and is equal to k. When k was set to 2, the average connectivity of all nodes increased in a linear manner with the increase of d from 140 m to 250 m, and the minimum connectivity does not change. PMID:27941704

  10. Increased resting state functional connectivity in the default mode network in recovered anorexia nervosa.

    Science.gov (United States)

    Cowdrey, Felicity A; Filippini, Nicola; Park, Rebecca J; Smith, Stephen M; McCabe, Ciara

    2014-02-01

    Functional brain imaging studies have shown abnormal neural activity in individuals recovered from anorexia nervosa (AN) during both cognitive and emotional task paradigms. It has been suggested that this abnormal activity which persists into recovery might underpin the neurobiology of the disorder and constitute a neural biomarker for AN. However, no study to date has assessed functional changes in neural networks in the absence of task-induced activity in those recovered from AN. Therefore, the aim of this study was to investigate whole brain resting state functional connectivity in nonmedicated women recovered from anorexia nervosa. Functional magnetic resonance imaging scans were obtained from 16 nonmedicated participants recovered from anorexia nervosa and 15 healthy control participants. Independent component analysis revealed functionally relevant resting state networks. Dual regression analysis revealed increased temporal correlation (coherence) in the default mode network (DMN) which is thought to be involved in self-referential processing. Specifically, compared to healthy control participants the recovered anorexia nervosa participants showed increased temporal coherence between the DMN and the precuneus and the dorsolateral prefrontal cortex/inferior frontal gyrus. The findings support the view that dysfunction in resting state functional connectivity in regions involved in self-referential processing and cognitive control might be a vulnerability marker for the development of anorexia nervosa.

  11. Interference-Aware Scheduling for Connectivity in MIMO Ad Hoc Multicast Networks

    CERN Document Server

    Jiang, Feng; Swindlehurst, A Lee

    2012-01-01

    We consider a multicast scenario involving an ad hoc network of co-channel MIMO nodes in which a source node attempts to share a streaming message with all nodes in the network via some pre-defined multi-hop routing tree. The message is assumed to be broken down into packets, and the transmission is conducted over multiple frames. Each frame is divided into time slots, and each link in the routing tree is assigned one time slot in which to transmit its current packet. We present an algorithm for determining the number of time slots and the scheduling of the links in these time slots in order to optimize the connectivity of the network, which we define to be the probability that all links can achieve the required throughput. In addition to time multiplexing, the MIMO nodes also employ beamforming to manage interference when links are simultaneously active, and the beamformers are designed with the maximum connectivity metric in mind. The effects of outdated channel state information (CSI) are taken into accoun...

  12. Probability of islanding in utility networks due to grid connected photovoltaic power systems

    Energy Technology Data Exchange (ETDEWEB)

    Verhoeven, B.

    2002-09-15

    This report for the International Energy Agency (IEA) made by Task 5 of the Photovoltaic Power Systems (PVPS) programme takes a look at the probability of islanding in utility networks due to grid-connected photovoltaic power systems. The mission of the Photovoltaic Power Systems Programme is to enhance the international collaboration efforts which accelerate the development and deployment of photovoltaic solar energy. Task 5 deals with issues concerning grid-interconnection and distributed PV power systems. This report summarises the results on a study on the probability of islanding in power networks with a high penetration level of grid connected PV-systems. The results are based on measurements performed during one year in a Dutch utility network. The measurements of active and reactive power were taken every second for two years and stored in a computer for off-line analysis. The area examined and its characteristics are described, as are the test set-up and the equipment used. The ratios between load and PV-power are discussed. The general conclusion is that the probability of islanding is virtually zero for low, medium and high penetration levels of PV-systems.

  13. Increased resting state functional connectivity in the fronto-parietal and default mode network in anorexia nervosa

    Directory of Open Access Journals (Sweden)

    Ilka eBoehm

    2014-10-01

    Full Text Available The etiology of anorexia nervosa (AN is poorly understood. Results from functional brain imaging studies investigating the neural profile of AN using cognitive and emotional task paradigms are difficult to reconcile. Task-related imaging studies often require a high level of compliance and can only partially explore the distributed nature and complexity of brain function. In this study, resting state functional connectivity imaging was used to investigate well-characterized brain networks potentially relevant to understand the neural mechanisms underlying the symptomatology and etiology of AN. Resting state functional magnetic resonance imaging data was obtained from 35 unmedicated female acute AN patients and 35 closely matched healthy female participants (HC and decomposed using spatial group independent component analyses. Using validated templates, we identified components covering the fronto-parietal control network, the default mode network (DMN, the salience network, the visual and the sensory-motor network. Group comparison revealed an increased functional connectivity between the angular gyrus and the other parts of the fronto-parietal network in patients with AN in comparison to HC. Connectivity of the angular gyrus was positively associated with self-reported persistence in HC. In the DMN, AN patients also showed an increased functional connectivity strength in the anterior insula in comparison to HC. Anterior insula connectivity was associated with self-reported problems with interoceptive awareness. This study, with one of the largest sample to date, shows that acute AN is associated with abnormal brain connectivity in two major resting state networks. The finding of an increased functional connectivity in the fronto-parietal network adds novel support for the notion of AN as a disorder of excessive cognitive control, whereas the elevated functional connectivity of the anterior insula with the DMN may reflect the high levels of self

  14. Resting-state functional connectivity of the default mode network associated with happiness.

    Science.gov (United States)

    Luo, Yangmei; Kong, Feng; Qi, Senqing; You, Xuqun; Huang, Xiting

    2016-03-01

    Happiness refers to people's cognitive and affective evaluation of their life. Why are some people happier than others? One reason might be that unhappy people are prone to ruminate more than happy people. The default mode network (DMN) is normally active during rest and is implicated in rumination. We hypothesized that unhappiness may be associated with increased default-mode functional connectivity during rest, including the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC) and inferior parietal lobule (IPL). The hyperconnectivity of these areas may be associated with higher levels of rumination. One hundred forty-eight healthy participants underwent a resting-state fMRI scan. A group-independent component analysis identified the DMNs. Results indicated increased functional connectivity in the DMN was associated with lower levels of happiness. Specifically, relative to happy people, unhappy people exhibited greater functional connectivity in the anterior medial cortex (bilateral MPFC), posterior medial cortex regions (bilateral PCC) and posterior parietal cortex (left IPL). Moreover, the increased functional connectivity of the MPFC, PCC and IPL, correlated positively with the inclination to ruminate. These results highlight the important role of the DMN in the neural correlates of happiness, and suggest that rumination may play an important role in people's perceived happiness.

  15. Altered Resting-State Connectivity within Executive Networks after Aneurysmal Subarachnoid Hemorrhage.

    Directory of Open Access Journals (Sweden)

    Monica Maher

    Full Text Available Aneurysmal subarachnoid hemorrhage (aSAH is associated with significant mortality rates, and most survivors experience significant cognitive deficits across multiple domains, including executive function. It is critical to determine the neural basis for executive deficits in aSAH, in order to better understand and improve patient outcomes. This study is the first examination of resting-state functional Magnetic Resonance Imaging in a group of aSAH patients, used to characterize changes in functional connectivity of the frontoparietal network. We scanned 14 aSAH patients and 14 healthy controls, and divided patients into "impaired" and "unimpaired" groups based on a composite executive function score. Impaired patients exhibited significantly lower quality of life and neuropsychological impairment relative to controls, across multiple domains. Seed-based functional connectivity analysis demonstrated that unimpaired patients were not significantly different from controls, but impaired patients had increased frontoparietal connectivity. Patients evidenced increased frontoparietal connectivity as a function of decreased executive function and decreased mood (i.e. quality of life. In addition, T1 morphometric analysis demonstrated that these changes are not attributable to local cortical atrophy among aSAH patients. These results establish significant, reliable changes in the endogenous brain dynamics of aSAH patients, that are related to cognitive and mood outcomes.

  16. Large-Scale Network Organisation in the Avian Forebrain: A Connectivity Matrix and Theoretical Analysis

    Directory of Open Access Journals (Sweden)

    Murray eShanahan

    2013-07-01

    Full Text Available Many species of birds, including pigeons, possess demonstrable cognitive capacities, and some are capable of cognitive feats matching those of apes. Since mammalian cortex is laminar while the avian telencephalon is nucleated, it is natural to ask whether the brains of these two cognitively capable taxa, despite their apparent anatomical dissimilarities, might exhibit common principles of organisation on some level. Complementing recent investigations of macro-scale brain connectivity in mammals, including humans and macaques, we here present the first large-scale wiring diagram for the forebrain of a bird. Using graph theory, we show that the pigeon telencephalon is organised along similar lines to that of a mammal. Both are modular, small-world networks with a connective core of hub nodes that includes prefrontal-like and hippocampal structures. These hub nodes are, topologically speaking, the most central regions of the pigeon's brain, as well as being the most richly connected, implying a crucial role in information flow. Overall, our analysis suggests that indeed, despite the absence of cortical layers and close to 300 million years of separate evolution, the connectivity of the avian brain conforms to the same organisational principles as the mammalian brain.

  17. Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging.

    Science.gov (United States)

    Robinson, Jennifer L; Baxi, Madhura; Katz, Jeffrey S; Waggoner, Paul; Beyers, Ronald; Morrison, Edward; Salibi, Nouha; Denney, Thomas S; Vodyanoy, Vitaly; Deshpande, Gopikrishna

    2016-11-25

    Diffusion tensor imaging (DTI) provides us an insight into the micro-architecture of white-matter tracts in the brain. This method has proved promising in understanding and investigating the neuronal tracts and structural connectivity between the brain regions in primates as well as rodents. The close evolutionary relationship between canines and humans may have spawned a unique bond in regard to social cognition rendering them useful as an animal model in translational research. In this study, we acquired diffusion data from anaesthetized dogs and created a DTI-based atlas for a canine model which could be used to investigate various white matter diseases. We illustrate the application of this atlas by calculating DTI tractography based structural connectivity between the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) regions of the default mode network (DMN) in dogs. White matter connectivity was investigated to provide structural basis for the functional dissociation observed between the anterior and posterior parts of DMN. A comparison of the integrity of long range structural connections (such as in the DMN) between dogs and humans is likely to provide us with new perspectives on the neural basis of the evolution of cognitive functions.

  18. Serotonergic modulation of resting state default mode network connectivity in healthy women.

    Science.gov (United States)

    Helmbold, K; Zvyagintsev, M; Dahmen, B; Biskup, C S; Bubenzer-Busch, S; Gaber, T J; Klasen, M; Eisert, A; Konrad, K; Habel, U; Herpertz-Dahlmann, B; Zepf, F D

    2016-04-01

    The default mode network (DMN) plays a central role in intrinsic thought processes. Altered DMN connectivity has been linked to diminished cerebral serotonin synthesis. Diminished brain serotonin synthesis is further associated with a lack of impulse control and various psychiatric disorders. Here, we investigated the serotonergic modulation of intrinsic functional connectivity (FC) within the DMN in healthy adult females, controlling for the menstrual cycle phase. Eighteen healthy women in the follicular phase (aged 20-31 years) participated in a double-blind controlled cross-over study of serotonin depletion. Acute tryptophan depletion (ATD) and a balanced amino acid load (BAL), used as the control condition, were applied on two separate days of assessment. Neural resting state data using functional magnetic resonance imaging (fMRI) and individual trait impulsivity scores were obtained. ATD compared with BAL significantly reduced FC with the DMN in the precuneus (associated with self-referential thinking) and enhanced FC with the DMN in the frontal cortex (associated with cognitive reasoning). Connectivity differences with the DMN between BAL and ATD in the precentral gyrus were significantly correlated with the magnitude of serotonin depletion. Right medial frontal gyrus and left superior frontal gyrus connectivity differences with the DMN were inversely correlated with trait impulsivity. These findings partially deviate from previous findings obtained in males and underline the importance of gender-specific studies and controlling for menstrual cycle to further elucidate the mechanism of ATD-induced changes within intrinsic thought processes.

  19. Decreased functional connectivity of insula-based network in young adults with internet gaming disorder.

    Science.gov (United States)

    Zhang, Yanzhen; Mei, Wei; Zhang, John X; Wu, Qiulin; Zhang, Wei

    2016-09-01

    The insula is a region that integrates interoception and drug urges, but little is known about its role in behavioral addiction such as internet addiction. We investigated insula-based functional connectivity in participants with internet gaming disorder (IGD) and healthy controls (HC) using resting-state functional MRI. The right and left insula subregions (posterior, ventroanterior, and dorsoanterior) were used as seed regions in a connectivity analysis. Compared with the HC group, the IGD group showed decreased functional connectivity between left posterior insula and bilateral supplementary motor area and middle cingulated cortex, between right posterior insula and right superior frontal gyrus, and decreased functional integration between insular subregions. The finding of reduced functional connectivity between the interoception and the motor/executive control regions is interpreted to reflect reduced ability to inhibit motor responses to internet gaming or diminished executive control over craving for internet gaming in IGD. The results support the hypothesis that IGD is associated with altered insula-based network, similar to substance addiction such as smoking.

  20. Altered resting-state network connectivity in stroke patients with and without apraxia of speech

    Directory of Open Access Journals (Sweden)

    Anneliese B. New

    2015-01-01

    Full Text Available Motor speech disorders, including apraxia of speech (AOS, account for over 50% of the communication disorders following stroke. Given its prevalence and impact, and the need to understand its neural mechanisms, we used resting state functional MRI to examine functional connectivity within a network of regions previously hypothesized as being associated with AOS (bilateral anterior insula (aINS, inferior frontal gyrus (IFG, and ventral premotor cortex (PM in a group of 32 left hemisphere stroke patients and 18 healthy, age-matched controls. Two expert clinicians rated severity of AOS, dysarthria and nonverbal oral apraxia of the patients. Fifteen individuals were categorized as AOS and 17 were AOS-absent. Comparison of connectivity in patients with and without AOS demonstrated that AOS patients had reduced connectivity between bilateral PM, and this reduction correlated with the severity of AOS impairment. In addition, AOS patients had negative connectivity between the left PM and right aINS and this effect decreased with increasing severity of non-verbal oral apraxia. These results highlight left PM involvement in AOS, begin to differentiate its neural mechanisms from those of other motor impairments following stroke, and help inform us of the neural mechanisms driving differences in speech motor planning and programming impairment following stroke.

  1. Altered resting-state network connectivity in stroke patients with and without apraxia of speech.

    Science.gov (United States)

    New, Anneliese B; Robin, Donald A; Parkinson, Amy L; Duffy, Joseph R; McNeil, Malcom R; Piguet, Olivier; Hornberger, Michael; Price, Cathy J; Eickhoff, Simon B; Ballard, Kirrie J

    2015-01-01

    Motor speech disorders, including apraxia of speech (AOS), account for over 50% of the communication disorders following stroke. Given its prevalence and impact, and the need to understand its neural mechanisms, we used resting state functional MRI to examine functional connectivity within a network of regions previously hypothesized as being associated with AOS (bilateral anterior insula (aINS), inferior frontal gyrus (IFG), and ventral premotor cortex (PM)) in a group of 32 left hemisphere stroke patients and 18 healthy, age-matched controls. Two expert clinicians rated severity of AOS, dysarthria and nonverbal oral apraxia of the patients. Fifteen individuals were categorized as AOS and 17 were AOS-absent. Comparison of connectivity in patients with and without AOS demonstrated that AOS patients had reduced connectivity between bilateral PM, and this reduction correlated with the severity of AOS impairment. In addition, AOS patients had negative connectivity between the left PM and right aINS and this effect decreased with increasing severity of non-verbal oral apraxia. These results highlight left PM involvement in AOS, begin to differentiate its neural mechanisms from those of other motor impairments following stroke, and help inform us of the neural mechanisms driving differences in speech motor planning and programming impairment following stroke.

  2. An Adaptive Connectivity-based Centroid Algorithm for Node Positioning in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Aries Pratiarso

    2015-06-01

    Full Text Available In wireless sensor network applications, the position of nodes is randomly distributed following the contour of the observation area. A simple solution without any measurement tools is provided by range-free method. However, this method yields the coarse estimating position of the nodes. In this paper, we propose Adaptive Connectivity-based (ACC algorithm. This algorithm is a combination of Centroid as range-free based algorithm, and hop-based connectivity algorithm. Nodes have a possibility to estimate their own position based on the connectivity level between them and their reference nodes. Each node divides its communication range into several regions where each of them has a certain weight depends on the received signal strength. The weighted value is used to obtain the estimated position of nodes. Simulation result shows that the proposed algorithm has up to 3 meter error of estimated position on 100x100 square meter observation area, and up to 3 hop counts for 80 meters' communication range. The proposed algorithm performs an average error positioning up to 10 meters better than Weighted Centroid algorithm. Keywords: adaptive, connectivity, centroid, range-free.

  3. 'Connecting tracks': exploring the roles of an Aboriginal women's cancer support network.

    Science.gov (United States)

    Cuesta-Briand, Beatriz; Bessarab, Dawn; Shahid, Shaouli; Thompson, Sandra C

    2016-11-01

    Aboriginal Australians are at higher risk of developing certain types of cancer and, once diagnosed, they have poorer outcomes than their non-Aboriginal counterparts. Lower access to cancer screening programmes, deficiencies in treatment and cultural barriers contribute to poor outcomes. Additional logistical factors affecting those living in rural areas compound these barriers. Cancer support groups have positive effects on people affected by cancer; however, there is limited evidence on peer-support programmes for Aboriginal cancer patients in Australia. This paper explores the roles played by an Aboriginal women's cancer support network operating in a regional town in Western Australia. Data were collected through semi-structured interviews with 24 participants including Aboriginal and mainstream healthcare service providers, and network members and clients. Interviews were audiotaped and transcribed verbatim. Transcripts were subjected to inductive thematic analysis. Connecting and linking people and services was perceived as the main role of the network. This role had four distinct domains: (i) facilitating access to cancer services; (ii) fostering social interaction; (iii) providing a culturally safe space; and (iv) building relationships with other agencies. Other network roles included providing emotional and practical support, delivering health education and facilitating engagement in cancer screening initiatives. Despite the network's achievements, unresolved tensions around role definition negatively impacted on the working relationship between the network and mainstream service providers, and posed a threat to the network's sustainability. Different perspectives need to be acknowledged and addressed in order to build strong, effective partnerships between service providers and Aboriginal communities. Valuing and honouring the Aboriginal approaches and expertise, and adopting an intercultural approach are suggested as necessary to the way forward.

  4. Networks of connected Pt nanoparticles supported on carbon nanotubes as superior catalysts for methanol electrooxidation

    Science.gov (United States)

    Huang, Meihua; Zhang, Jianshuo; Wu, Chuxin; Guan, Lunhui

    2017-02-01

    The high cost and short lifetime of the Pt-based anode catalyst for methanol oxidation reaction (MOR) hamper the widespread commercialization of direct methanol fuel cell (DMFC). Therefore, improving the activity of Pt-based catalysts is necessary for their practical application. For the first time, we prepared networks of connected Pt nanoparticles supported on multi-walled carbon nanotubes with loading ratio as high as 91 wt% (Pt/MWCNTs). Thanks for the unique connected structure, the Pt mass activity of Pt/MWCNTs for methanol oxidation reaction is 4.4 times as active as that of the commercial Pt/C (20 wt%). When carbon support is considered, the total mass activity of Pt/MWCNTs is 20 times as active as that of the commercial Pt/C. The durability and anti-poisoning ability are also improved greatly.

  5. Temporal metastates are associated with differential patterns of time-resolved connectivity, network topology, and attention.

    Science.gov (United States)

    Shine, James M; Koyejo, Oluwasanmi; Poldrack, Russell A

    2016-08-30

    Little is currently known about the coordination of neural activity over longitudinal timescales and how these changes relate to behavior. To investigate this issue, we used resting-state fMRI data from a single individual to identify the presence of two distinct temporal states that fluctuated over the course of 18 mo. These temporal states were associated with distinct patterns of time-resolved blood oxygen level dependent (BOLD) connectivity within individual scanning sessions and also related to significant alterations in global efficiency of brain connectivity as well as differences in self-reported attention. These patterns were replicated in a separate longitudinal dataset, providing additional supportive evidence for the presence of fluctuations in functional network topology over time. Together, our results underscore the importance of longitudinal phenotyping in cognitive neuroscience.

  6. Functional connectivity in cortico-subcortical brain networks underlying reward processing in attention-deficit/hyperactivity disorder

    Directory of Open Access Journals (Sweden)

    Marianne Oldehinkel

    2016-01-01

    Conclusions: The present study does not corroborate previous childhood evidence for functional connectivity alterations between key reward processing regions in adolescents and young adults with ADHD. Our findings could point to developmental normalization or indicate that reward-processing deficits result from functional connectivity alterations in general task-related networks.

  7. Connectivity levels and the competitive position of Spanish airports and Iberia's network rationalization strategy, 2001-2007

    NARCIS (Netherlands)

    P. Suau-Sanchez; G. Burghouwt

    2012-01-01

    This paper examines the connectivity of the Spanish airport system between 2001 and 2007. Over the period, network carriers considerably strengthened the connectivity between Spanish airports and major European hubs. Although OneWorld is still the dominant alliance in Spain, SkyTeam and Star achieve

  8. Individual Variability in Sensorimotor Network Functional Connectivity Correlates With the Rate of Early Visuomotor Adaptation

    Science.gov (United States)

    Cassady, K.; Ruitenberg, M.; Koppelmans, V.; DeDios, Y.; Gadd, N.; Wood, S.; Reuter-Lorenz, P.; Riascos, R.; Kofman, I.; Bloomberg, J.; Mulavara, A.; Seidler, R.

    2016-01-01

    Sensorimotor adaptation is a type of procedural motor learning that enables individuals to preserve accurate movements in the presence of external or internal perturbations. Adaptation learning can be divided into an early, more cognitively demanding stage, and a later, more automatic stage. In recent years, several investigations have identified significant associations between sensorimotor adaptation and brain structure and function. However, the question of whether individual variability in functional connectivity strength is predictive of sensorimotor adaptation performance has been largely unaddressed. In the present study, we investigate whether such variability in early sensorimotor adaptation is associated with individual differences in resting-state functional connectivity. We used resting state functional magnetic resonance imaging (rs-fMRI) to estimate functional connectivity strength using hypothesis-driven (seed-to-voxel) and hypothesis-free (voxel-to-voxel) approaches. For the hypothesis-driven analysis, we selected several regions of interest (ROIs) from sensorimotor and default mode networks of the brain. We then correlated these connectivity measures with the rate of early learning during a visuomotor adaptation task in 16 healthy participants. For this task, participants lay supine in the MRI scanner and moved an MRI-compatible dual axis joystick with their right hand to hit targets presented on a screen. Each movement was initiated from the central position on the display screen. Participants were instructed to move the cursor to the target as quickly as possible by moving the joystick, and to hold the cursor within the target until it disappeared. They we