WorldWideScience

Sample records for anomalous network connectivity

  1. Evidence for anomalous network connectivity during working memory encoding in schizophrenia: an ICA based analysis.

    Directory of Open Access Journals (Sweden)

    Shashwath A Meda

    Full Text Available BACKGROUND: Numerous neuroimaging studies report abnormal regional brain activity during working memory performance in schizophrenia, but few have examined brain network integration as determined by "functional connectivity" analyses. METHODOLOGY/PRINCIPAL FINDINGS: We used independent component analysis (ICA to identify and characterize dysfunctional spatiotemporal networks in schizophrenia engaged during the different stages (encoding and recognition of a Sternberg working memory fMRI paradigm. 37 chronic schizophrenia and 54 healthy age/gender-matched participants performed a modified Sternberg Item Recognition fMRI task. Time series images preprocessed with SPM2 were analyzed using ICA. Schizophrenia patients showed relatively less engagement of several distinct "normal" encoding-related working memory networks compared to controls. These encoding networks comprised 1 left posterior parietal-left dorsal/ventrolateral prefrontal cortex, cingulate, basal ganglia, 2 right posterior parietal, right dorsolateral prefrontal cortex and 3 default mode network. In addition, the left fronto-parietal network demonstrated a load-dependent functional response during encoding. Network engagement that differed between groups during recognition comprised the posterior cingulate, cuneus and hippocampus/parahippocampus. As expected, working memory task accuracy differed between groups (p<0.0001 and was associated with degree of network engagement. Functional connectivity within all three encoding-associated functional networks correlated significantly with task accuracy, which further underscores the relevance of abnormal network integration to well-described schizophrenia working memory impairment. No network was significantly associated with task accuracy during the recognition phase. CONCLUSIONS/SIGNIFICANCE: This study extends the results of numerous previous schizophrenia studies that identified isolated dysfunctional brain regions by providing evidence

  2. Control Networks in Paediatric Tourette Syndrome Show Immature and Anomalous Patterns of Functional Connectivity

    Science.gov (United States)

    Church, Jessica A.; Fair, Damien A.; Dosenbach, Nico U. F.; Cohen, Alexander L.; Miezin, Francis M.; Petersen, Steven E.; Schlaggar, Bradley L.

    2009-01-01

    Tourette syndrome (TS) is a developmental disorder characterized by unwanted, repetitive behaviours that manifest as stereotyped movements and vocalizations called "tics". Operating under the hypothesis that the brain's control systems may be impaired in TS, we measured resting-state functional connectivity MRI (rs-fcMRI) between 39 previously…

  3. 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.......In the present paper we consider the allocation of cost in connection networks. Agents have connection demands in form of pairs of locations they want to be connected. Connections between locations are costly to build. The problem is to allocate costs of networks satisfying all connection demands...

  4. Anomalous Diffusion on the Percolating Networks

    Institute of Scientific and Technical Information of China (English)

    DeLIU; HouqiangLI; 等

    1997-01-01

    According to the standard diffusion equation,by introducing reasonably into a anomalous diffusion coefficient,the generalized diffusion equation,which describes anomalous diffusion on the percolating networks with a power-law distribution of waiting times,is derived in this paper.The solution of the generalized diffusion equation is obtained by using the method,which is used by Barta,The problems of anomaloous diffusion on percolating networks with a power-law distribution of waiting times,which aren't solved by Barta,are resolved.

  5. 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......In the present paper we consider the allocation of costs in connection networks. Agents have connection demands in form of pairs of locations they want to have connected. Connections between locations are costly to build. The problem is to allocate costs of networks satisfying all connection...

  6. Functional total anomalous pulmonary venous connection via levoatriocardinal vein.

    Science.gov (United States)

    Hayashi, Taiyu; Ozawa, Katsusuke; Sugibayashi, Rika; Wada, Seiji; Ono, Hiroshi

    2016-07-01

    We report a fetal case of double outlet right ventricle, mitral atresia, and intact atrial septum. Although the pulmonary veins were connected to the left atrium, pulmonary venous blood drained into the right superior vena cava via the stenotic levoatriocardinal vein (LACV), which resulted in a circulation resembling total anomalous pulmonary venous connection (TAPVC) with pulmonary venous obstruction. Since the pulmonary veins were connected to both the stenotic LACV and the "dead-end" left atrium, the pulmonary venous flow had a to-and-fro pattern along with atrial relaxation and contraction. Postnatal echocardiography and computed tomography confirmed the diagnosis of normally connected but anomalously draining pulmonary veins via the LACV. Surgical creation of an atrial septal defect on the day of birth successfully relieved pulmonary venous obstruction. Normally connected but anomalously draining pulmonary veins via the LACV should be considered for TAPVC differential diagnosis in fetuses with a left-side heart obstruction. PMID:27460400

  7. 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

  8. Diagnosing Anomalous Network Performance with Confidence

    Energy Technology Data Exchange (ETDEWEB)

    Settlemyer, Bradley W [ORNL; Hodson, Stephen W [ORNL; Kuehn, Jeffery A [ORNL; Poole, Stephen W [ORNL

    2011-04-01

    Variability in network performance is a major obstacle in effectively analyzing the throughput of modern high performance computer systems. High performance interconnec- tion networks offer excellent best-case network latencies; how- ever, highly parallel applications running on parallel machines typically require consistently high levels of performance to adequately leverage the massive amounts of available computing power. Performance analysts have usually quantified network performance using traditional summary statistics that assume the observational data is sampled from a normal distribution. In our examinations of network performance, we have found this method of analysis often provides too little data to under- stand anomalous network performance. Our tool, Confidence, instead uses an empirically derived probability distribution to characterize network performance. In this paper we describe several instances where the Confidence toolkit allowed us to understand and diagnose network performance anomalies that we could not adequately explore with the simple summary statis- tics provided by traditional measurement tools. In particular, we examine a multi-modal performance scenario encountered with an Infiniband interconnection network and we explore the performance repeatability on the custom Cray SeaStar2 interconnection network after a set of software and driver updates.

  9. Anomalous Diffusion on the Hanoi Networks

    OpenAIRE

    Boettcher, S.; B. Goncalves

    2008-01-01

    Diffusion is modeled on the recently proposed Hanoi networks by studying the mean- square displacement of random walks with time, ~t^{2/d_w}. 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-log_2(\\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 Eucli...

  10. Green Connections Network

    Data.gov (United States)

    City of San Francisco — Green Connections aims to increase access to parks, open spaces, and the waterfront by envisioning a network of ���green connectors�۪ ��� city streets that will be...

  11. Algebraic Connectivity of Interdependent Networks

    NARCIS (Netherlands)

    Martin-Hernandez, J.; Wang, H.; Van Mieghem, P.; D'Agostino, G.

    2014-01-01

    The algebraic connectivity UN-1, i.e. the second smallest eigenvalue of the Laplacian matrix, plays a crucial role in dynamic phenomena such as diffusion processes, synchronization stability, and network robustness. In this work we study the algebraic connectivity in the general context of interdepe

  12. 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...

  13. 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 ...

  14. 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....

  15. Women's connectivity in extreme networks.

    Science.gov (United States)

    Manrique, Pedro; Cao, Zhenfeng; Gabriel, Andrew; Horgan, John; Gill, Paul; Qi, Hong; Restrepo, Elvira M; Johnson, Daniela; Wuchty, Stefan; Song, Chaoming; Johnson, Neil

    2016-06-01

    A popular stereotype is that women will play more minor roles than men as environments become more dangerous and aggressive. Our analysis of new longitudinal data sets from offline and online operational networks [for example, ISIS (Islamic State)] shows that although men dominate numerically, women emerge with superior network connectivity that can benefit the underlying system's robustness and survival. Our observations suggest new female-centric approaches that could be used to affect such networks. They also raise questions about how individual contributions in high-pressure systems are evaluated. PMID:27386564

  16. Gigabit Wireless for Network Connectivity

    Science.gov (United States)

    Schoedel, Eric

    2009-01-01

    Uninterrupted, high-bandwidth network connectivity is crucial for higher education. Colleges and universities increasingly adopt gigabit wireless solutions because of their fiber-equivalent performance, quick implementation, and significant return on investment. For just those reasons, Rush University Medical Center switched from free space optics…

  17. 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.

  18. 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.

  19. Branching vertical vein with multiple sites of obstruction in supracardiac total anomalous pulmonary venous connection

    Directory of Open Access Journals (Sweden)

    Navaneetha Sasikumar

    2014-01-01

    Full Text Available We present the case of an infant with total anomalous pulmonary venous connection and a branching vertical vein with multiple points of narrowing, draining the confluence into the innominate vein. The embryology and clinical relevance of this interesting anatomy is discussed.

  20. 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.

  1. IMPROVED NETWORK CONNECTIVITY IN MANETS

    Directory of Open Access Journals (Sweden)

    B R Sujatha

    2009-10-01

    Full Text Available The growth in wireless communication technologies has resulted in a considerable amount ofattention given to mobile adhoc networks. All mobile hosts in an adhoc network are embedded withpacket forwarding capabilities. It is decentralized and is independent of infrastructure. Since mobilehosts in an adhoc network usually move freely, the topology of the network changes dynamically anddisconnection occurs frequently. These characteristics require the routing protocols to find analternative path towards the destination for data transfer. The existing on-demand routing protocolsdoes the alternative path establishment only after the disconnection of links in the existing path. Thedata sent by the source during alternate path establishment period will be lost leading to incompletedata transfer. The network traffic will therefore increase considerably. This problem can be overcomeby establishing an alternative path when the existing path is more likely to be broken, by sending awarning message to the source indicating the likelihood of disconnection. In this paper an attempt hasbeen made to analyze a protocol that improves the network connectivity by preempting the alternativepath before the existing link gets failed by monitoring the signal strength and ‘age of the path’.

  2. 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.

  3. 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

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

    OpenAIRE

    Parimala Prasanna Simha; Muralidhara Danappa Patel; Jagadeesh, A. M.

    2012-01-01

    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...

  5. Stent implantation to relieve native obstructed left partial anomalous pulmonary venous connections.

    Science.gov (United States)

    A McCrossan, Brian; O'Callaghan, Barry; P Walsh, Kevin

    2016-09-01

    Obstructed partial anomalous pulmonary venous connections (APVC) are rare but may be associated with severe pulmonary hypertension (PHTN) and warrant urgent relief. There are a number of case reports of successful catheter intervention for obstructed total APVC. We present the first reported case of catheter intervention to relieve obstructed, left sided PAPVC in a neonate with Turner syndrome. © 2016 Wiley Periodicals, Inc. PMID:27192610

  6. Severe aortic regurgitation and partial anomalous pulmonary venous connection in a Turner syndrome patient.

    Science.gov (United States)

    Yin, Kanhua; Li, Jun; Zhu, Kai; Wang, Yulin; Lai, Hao; Wang, Chunsheng

    2015-11-01

    Turner syndrome (TS) is one of the most common sex chromosome diseases. Short stature (if untreated) and ovarian dysgenesis (streak ovary) are two typical clinical manifestations of these patients. A variety of cardiovascular abnormalities has been found associated with TS. We report a 29-year-old TS patient with severe aortic regurgitation, bicuspid aortic valve (BAV) and partial anomalous pulmonary venous connection (PAPVC). We discuss the diagnostic and surgical management of cardiovascular complications in TS patients. PMID:26716053

  7. 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.

  8. 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.)

  9. The Twisted-Cube Connected Networks

    Institute of Scientific and Technical Information of China (English)

    WANG Deqiang; ZHAO Lianchang

    1999-01-01

    This paper presents a newinterconnection network topology, called the twisted-cube connectednetwork, which is a generation of the twisted 3-cube. The twisted-cubeconnected network is a variant of the hypercube, and it has a betterrecursive structure. The regularity, connectivities, subgraphs of thetwisted-cube connected network are studied. The twisted-cube connectednetwork is proved to be a 3-cube-free network, which is the essentialdifference from the hypercube and variants of the hypercube. Anefficient routing algorithm is proposed, and the diameter ofn-dimensional twisted-cube connected network is proved to be just[n+1/2] which is less than that of the hypercube.

  10. 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.

  11. 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.

  12. Anomalous t-c-g coupling: The connection between single top production and top decay

    OpenAIRE

    Tait, Tim; Yuan, C. --P.

    1996-01-01

    Continuing earlier work, we examine the constraint on an anomalous t-c-g coupling from top quark decay. We find that from current CDF measurements of the branching ratio $t \\rightarrow W b$, the minimum scale at which new physics can strongly modify the t-c-g coupling is \\Ltcg $\\geq$ about 950 GeV. At the upgraded Tevatron, single top production can constrain \\Ltcg $\\geq$ 4.5 TeV. The connection between t-c production and the decay $t \\rightarrow c g$ is examined, showing how constraints on o...

  13. 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.

  14. Cortical attractor network dynamics with diluted connectivity.

    Science.gov (United States)

    Rolls, Edmund T; Webb, Tristan J

    2012-01-24

    The connectivity of the cerebral cortex is diluted, with the probability of excitatory connections between even nearby pyramidal cells rarely more than 0.1, and in the hippocampus 0.04. To investigate the extent to which this diluted connectivity affects the dynamics of attractor networks in the cerebral cortex, we simulated an integrate-and-fire attractor network taking decisions between competing inputs with diluted connectivity of 0.25 or 0.1, and with the same number of synaptic connections per neuron for the recurrent collateral synapses within an attractor population as for full connectivity. The results indicated that there was less spiking-related noise with the diluted connectivity in that the stability of the network when in the spontaneous state of firing increased, and the accuracy of the correct decisions increased. The decision times were a little slower with diluted than with complete connectivity. Given that the capacity of the network is set by the number of recurrent collateral synaptic connections per neuron, on which there is a biological limit, the findings indicate that the stability of cortical networks, and the accuracy of their correct decisions or memory recall operations, can be increased by utilizing diluted connectivity and correspondingly increasing the number of neurons in the network, with little impact on the speed of processing of the cortex. Thus diluted connectivity can decrease cortical spiking-related noise. In addition, we show that the Fano factor for the trial-to-trial variability of the neuronal firing decreases from the spontaneous firing state value when the attractor network makes a decision. This article is part of a Special Issue entitled "Neural Coding". PMID:21875702

  15. Connecting network properties of rapidly disseminating epizoonotics.

    Directory of Open Access Journals (Sweden)

    Ariel L Rivas

    Full Text Available To effectively control the geographical dissemination of infectious diseases, their properties need to be determined. To test that rapid microbial dispersal requires not only susceptible hosts but also a pre-existing, connecting network, we explored constructs meant to reveal the network properties associated with disease spread, which included the road structure.Using geo-temporal data collected from epizoonotics in which all hosts were susceptible (mammals infected by Foot-and-mouth disease virus, Uruguay, 2001; birds infected by Avian Influenza virus H5N1, Nigeria, 2006, two models were compared: 1 'connectivity', a model that integrated bio-physical concepts (the agent's transmission cycle, road topology into indicators designed to measure networks ('nodes' or infected sites with short- and long-range links, and 2 'contacts', which focused on infected individuals but did not assess connectivity.THE CONNECTIVITY MODEL SHOWED FIVE NETWORK PROPERTIES: 1 spatial aggregation of cases (disease clusters, 2 links among similar 'nodes' (assortativity, 3 simultaneous activation of similar nodes (synchronicity, 4 disease flows moving from highly to poorly connected nodes (directionality, and 5 a few nodes accounting for most cases (a "20:80" pattern. In both epizoonotics, 1 not all primary cases were connected but at least one primary case was connected, 2 highly connected, small areas (nodes accounted for most cases, 3 several classes of nodes were distinguished, and 4 the contact model, which assumed all primary cases were identical, captured half the number of cases identified by the connectivity model. When assessed together, the synchronicity and directionality properties explained when and where an infectious disease spreads.Geo-temporal constructs of Network Theory's nodes and links were retrospectively validated in rapidly disseminating infectious diseases. They distinguished classes of cases, nodes, and networks, generating information usable

  16. 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.

  17. Autaptic Connections Shift Network Excitability and Bursting

    OpenAIRE

    Wiles, Laura; Gu, Shi; Pasqualetti, Fabio; Bassett, Danielle S.; Meaney, David F.

    2016-01-01

    Network architecture forms a critical constraint on neuronal function. Here we examine the role of structural autapses, when a neuron synapses onto itself, in driving network-wide bursting behavior. Using a simple spiking model of neuronal activity, we study how autaptic connections affect activity patterns, and evaluate if neuronal degree or controllability are significant factors that affect changes in bursting from these autaptic connections. We observed that adding increasing numbers of a...

  18. Connectivity in finite ad-hoc networks

    Institute of Scientific and Technical Information of China (English)

    WANG HanXing; LU GuiLin; JIA WeiJia; ZHAO Wei

    2008-01-01

    Research on ad-hoc network connectivity has mainly focused on asymptotic results In the number of nodes in the network. For a one-dimensional ad-hoc network G1, assuming all the nodes are Independently uniform distributed in a closed Interval [O, Z](z ∈ R+), we derive a generic formula for the probability that the network is connected. The finite connected ad-hoc networks is analyzed. And we separately suggest necessary conditions to make the ad-hoc network to be connected in one and two dimensional cases, facing possible failed nodes (f-nodes). Based on the necessary condition and unit-disk assumption for the node transmission, we prove that the nodes of the connected two-dimensional ad-hoc networks (G2) can be di-vided into at most five different groups. For an f-node n0 in either of the five groups, we derive a close formula for the probability that there is at least one route between a pair of nodes in G2 - {no}.

  19. 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

  20. Connecting Dream Networks Across Cultures

    OpenAIRE

    Varol, Onur; Menczer, Filippo

    2014-01-01

    Many species dream, yet there remain many open research questions in the study of dreams. The symbolism of dreams and their interpretation is present in cultures throughout history. Analysis of online data sources for dream interpretation using network science leads to understanding symbolism in dreams and their associated meaning. In this study, we introduce dream interpretation networks for English, Chinese and Arabic that represent different cultures from various parts of the world. We ana...

  1. Maximizing algebraic connectivity in air transportation networks

    Science.gov (United States)

    Wei, Peng

    In air transportation networks the robustness of a network regarding node and link failures is a key factor for its design. An experiment based on the real air transportation network is performed to show that the algebraic connectivity is a good measure for network robustness. Three optimization problems of algebraic connectivity maximization are then formulated in order to find the most robust network design under different constraints. The algebraic connectivity maximization problem with flight routes addition or deletion is first formulated. Three methods to optimize and analyze the network algebraic connectivity are proposed. The Modified Greedy Perturbation Algorithm (MGP) provides a sub-optimal solution in a fast iterative manner. The Weighted Tabu Search (WTS) is designed to offer a near optimal solution with longer running time. The relaxed semi-definite programming (SDP) is used to set a performance upper bound and three rounding techniques are discussed to find the feasible solution. The simulation results present the trade-off among the three methods. The case study on two air transportation networks of Virgin America and Southwest Airlines show that the developed methods can be applied in real world large scale networks. The algebraic connectivity maximization problem is extended by adding the leg number constraint, which considers the traveler's tolerance for the total connecting stops. The Binary Semi-Definite Programming (BSDP) with cutting plane method provides the optimal solution. The tabu search and 2-opt search heuristics can find the optimal solution in small scale networks and the near optimal solution in large scale networks. The third algebraic connectivity maximization problem with operating cost constraint is formulated. When the total operating cost budget is given, the number of the edges to be added is not fixed. Each edge weight needs to be calculated instead of being pre-determined. It is illustrated that the edge addition and the

  2. 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.

  3. 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.

  4. 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.

  5. Fiber-connected position localization sensor networks

    Science.gov (United States)

    Pan, Shilong; Zhu, Dan; Fu, Jianbin; Yao, Tingfeng

    2014-11-01

    Position localization has drawn great attention due to its wide applications in radars, sonars, electronic warfare, wireless communications and so on. Photonic approaches to realize position localization can achieve high-resolution, which also provides the possibility to move the signal processing from each sensor node to the central station, thanks to the low loss, immunity to electromagnetic interference (EMI) and broad bandwidth brought by the photonic technologies. In this paper, we present a review on the recent works of position localization based on photonic technologies. A fiber-connected ultra-wideband (UWB) sensor network using optical time-division multiplexing (OTDM) is proposed to realize high-resolution localization and moving the signal processing to the central station. A 3.9-cm high spatial resolution is achieved. A wavelength-division multiplexed (WDM) fiber-connected sensor network is also demonstrated to realize location which is independent of the received signal format.

  6. Maximizing algebraic connectivity in interconnected networks.

    Science.gov (United States)

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

    2016-03-01

    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 interlayer links among them. In order to have a well-connected multilayer structure, it is necessary to optimally design these interlayer links considering realistic constraints. In this work, we solve the problem of finding an optimal weight distribution for one-to-one interlayer 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 the budget past the threshold, the optimal weight distribution can be nonuniform. The interesting consequence of this result is that there is no need to solve the optimization problem when the available budget is less than the threshold, which can be easily found analytically. PMID:27078276

  7. 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...

  8. 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...

  9. 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.

  10. 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...

  11. 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.

  12. 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.)

  13. 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

    International Nuclear Information System (INIS)

    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/m2 vs. 118 ± 30 mL/m2), 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.)

  14. 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.

  15. 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.

  16. Distinction and connection between contact network, social network, and disease transmission network.

    Science.gov (United States)

    Chen, Shi; Lanzas, Cristina

    2016-09-01

    In this paper we discuss the distinction and connection between three closely related networks in animal ecology and epidemiology studies: the contact, social, and disease transmission networks. We provide a robust theoretical definition and interpretation of these three networks, demonstrate that social and disease transmission networks can be derived as spanning subgraphs of contact network, and show examples based on real-world high-resolution cattle contact structure data. Furthermore, we establish a modeling framework to track potential disease transmission dynamics and construct transmission network based on the observed animal contact network.

  17. Distinction and connection between contact network, social network, and disease transmission network.

    Science.gov (United States)

    Chen, Shi; Lanzas, Cristina

    2016-09-01

    In this paper we discuss the distinction and connection between three closely related networks in animal ecology and epidemiology studies: the contact, social, and disease transmission networks. We provide a robust theoretical definition and interpretation of these three networks, demonstrate that social and disease transmission networks can be derived as spanning subgraphs of contact network, and show examples based on real-world high-resolution cattle contact structure data. Furthermore, we establish a modeling framework to track potential disease transmission dynamics and construct transmission network based on the observed animal contact network. PMID:27544246

  18. Availability analysis of GMPLS connections based on physical network topology

    OpenAIRE

    Segovia Silvero, Juan; Calle Ortega, Eusebi; Vilà Talleda, Pere

    2008-01-01

    This paper presents a study of connection availability in GMPLS over optical transport networks (OTN) taking into account different network topologies. Two basic path protection schemes are considered and compared with the no protection case. The selected topologies are heterogeneous in geographic coverage, network diameter, link lengths, and average node degree. Connection availability is also computed considering the reliability data of physical components and a well-known network availabil...

  19. A multi-layer network approach to MEG connectivity analysis.

    Science.gov (United States)

    Brookes, Matthew J; Tewarie, Prejaas K; Hunt, Benjamin A E; Robson, Sian E; Gascoyne, Lauren E; Liddle, Elizabeth B; Liddle, Peter F; Morris, Peter G

    2016-05-15

    Recent years have shown the critical importance of inter-regional neural network connectivity in supporting healthy brain function. Such connectivity is measurable using neuroimaging techniques such as MEG, however the richness of the electrophysiological signal makes gaining a complete picture challenging. Specifically, connectivity can be calculated as statistical interdependencies between neural oscillations within a large range of different frequency bands. Further, connectivity can be computed between frequency bands. This pan-spectral network hierarchy likely helps to mediate simultaneous formation of multiple brain networks, which support ongoing task demand. However, to date it has been largely overlooked, with many electrophysiological functional connectivity studies treating individual frequency bands in isolation. Here, we combine oscillatory envelope based functional connectivity metrics with a multi-layer network framework in order to derive a more complete picture of connectivity within and between frequencies. We test this methodology using MEG data recorded during a visuomotor task, highlighting simultaneous and transient formation of motor networks in the beta band, visual networks in the gamma band and a beta to gamma interaction. Having tested our method, we use it to demonstrate differences in occipital alpha band connectivity in patients with schizophrenia compared to healthy controls. We further show that these connectivity differences are predictive of the severity of persistent symptoms of the disease, highlighting their clinical relevance. Our findings demonstrate the unique potential of MEG to characterise neural network formation and dissolution. Further, we add weight to the argument that dysconnectivity is a core feature of the neuropathology underlying schizophrenia. PMID:26908313

  20. 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.

  1. 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.…

  2. 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.

  3. 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...

  4. 肺静脉连接异常的双源CT诊断%DSCT Diagnosis of Anomalous Pulmonary Venous Connections

    Institute of Scientific and Technical Information of China (English)

    金彪; 李惠民; 虞岐崴; 薛建平

    2011-01-01

    目的:探讨肺静脉连接异常的双源CT(DSCT)诊断及应用价值.方法:12例经手术和(或)X线心血管造影证实的肺静脉连接异常患者纳入研究,男女各半,年龄10个月~23岁,平均龄6.9岁;采用双源CT(Siemens,Definition)进行CT血管造影(DSCTA)检查,扫描参数:80~120kV,60~100mAs,重建函数B31f,层厚1.0mm,间隔0.4~0.8mm;全部患者同期完成心脏超声检查.结果:12例患者中完全性肺静脉连接异常8例(心上型6例,心内型2例),部分性肺静脉连接异常4例.DSCTA全部准确诊断,心脏超声的诊断准确率75%(9/12).结论:对于肺静脉连接异常,双源CT是可靠的无创诊断方法,优于心脏超声检查.%Purpose: To discuss the value of DSCT in diagnosis of anomalous pulmonary venous connections(APVC). Methods: Twelve patients with anomalous pulmonary venous connections confirmed by operation and / or catheter angiography were enrolled in our study. The CT angiography was undergone with a Dual -source CT scanner (Siemens, Definition). The parameters were 80- 120 kV, 60- 100mAs,B31f, slice thickness lmm, and interval 0.4- 0. 8mm. All patients were underwent echocardiography before CT scanning. Results: Eight total APVC (supracardiac 6, intracardiac 2) and four partial APVC were correctly diagnosed with DSCTA and verified by surgery and/ or catheter angiography. Nine patients (9/ 12, 75%) were correctly diagnosed with echocardiography. Conclusion: DSCT is a reliable modality in diagnosis of anomalous pulmonary venous connections and is superior to echocardiography.

  5. 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.

  6. Highly connected neurons spike less frequently in balanced networks

    Science.gov (United States)

    Pyle, Ryan; Rosenbaum, Robert

    2016-04-01

    Biological neuronal networks exhibit highly variable spiking activity. Balanced networks offer a parsimonious model of this variability in which strong excitatory synaptic inputs are canceled by strong inhibitory inputs on average, and irregular spiking activity is driven by fluctuating synaptic currents. Most previous studies of balanced networks assume a homogeneous or distance-dependent connectivity structure, but connectivity in biological cortical networks is more intricate. We use a heterogeneous mean-field theory of balanced networks to show that heterogeneous in-degrees can break balance. Moreover, heterogeneous architectures that achieve balance promote lower firing rates in neurons with larger in-degrees, consistent with some recent experimental observations.

  7. 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…

  8. 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.

  9. 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.

  10. 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.

  11. From sensor networks to connected analysis tools

    Science.gov (United States)

    Dawes, N.; Bavay, M.; Egger, T.; Sarni, S.; Salehi, A.; Davison, A.; Jeung, H.; Aberer, K.; Lehning, M.

    2012-04-01

    Multi-disciplinary data systems provide excellent tools for locating data, but most eventually provide a series of local files for further processing, providing marginal advantages for the regular user. The Swiss Experiment Platform (SwissEx) was built with the primary goal of enabling high density measurements, integrating them with lower density existing measurements and encouraging cross/inter-disciplinary collaborations. Nearing the end of the project, we have exceeded these goals, also providing connected tools for direct data access from analysis applications. SwissEx (www.swiss-experiment.ch) provides self-organising networks for rapid deployment and integrates these data with existing measurements from across environmental research. The data are categorised and documented according to their originating experiments and fieldsites as well as being searchable globally. Data from SwissEx are available for download, but we also provide tools to directly access data from within common scientific applications (Matlab, LabView, R) and numerical models such as Alpine3D (using a data acquisition plugin and preprocessing library, MeteoIO). The continuation project (the Swiss Environmental Data and Knowledge Platform) will aim to continue the ideas developed within SwissEx and (alongside cloud enablement and standardisation) work on the development of these tools for application specific tasks. We will work alongside several projects from a wide range of disciplines to help them to develop tools which either require real-time data, or large data samples. As well as developing domain specific tools, we will also be working on tools for the utilisation of the latest knowledge in data control, trend analysis, spatio-temporal statistics and downscaling (developed within the CCES Extremes project), which will be a particularly interesting application when combined with the large range of measurements already held in the system. This presentation will look at the

  12. 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.

  13. 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.

  14. Connectivity-driven Attachment in Mobile Cellular Ad Hoc Networks

    OpenAIRE

    Boite, Julien; Leguay, Jérémie

    2014-01-01

    International audience Cellular wireless technologies (e.g. LTE) can be used to build cellular ad hoc networks. In this new class of ad hoc networks, nodes are equipped with two radio interfaces: one being a terminal, the other one being an access point. In this context, attachment decisions based on traditional criteria (e.g. signal quality) may lead to network partitions or suboptimal path lengths, thus making access point selection critical to ensure efficient network connectivity. This...

  15. Graph analysis of spontaneous brain network using EEG source connectivity

    OpenAIRE

    Kabbara, Aya; Falou, Wassim El; Khalil, Mohamad; Wendling, Fabrice; Hassan, Mahmoud

    2016-01-01

    Exploring the human brain networks during rest is a topic of great interest. Several structural and functional studies have previously been conducted to study the intrinsic brain networks. In this paper, we focus on investigating the human brain network topology using dense Electroencephalography (EEG) source connectivity approach. We applied graph theoretical methods on functional networks reconstructed from resting state data acquired using EEG in 14 healthy subjects. Our findings confirmed...

  16. 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.

  17. 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

  18. Discriminating direct and indirect connectivities in biological networks.

    Science.gov (United States)

    Kang, Taek; Moore, Richard; Li, Yi; Sontag, Eduardo; Bleris, Leonidas

    2015-10-13

    Reverse engineering of biological pathways involves an iterative process between experiments, data processing, and theoretical analysis. Despite concurrent advances in quality and quantity of data as well as computing resources and algorithms, difficulties in deciphering direct and indirect network connections are prevalent. Here, we adopt the notions of abstraction, emulation, benchmarking, and validation in the context of discovering features specific to this family of connectivities. After subjecting benchmark synthetic circuits to perturbations, we inferred the network connections using a combination of nonparametric single-cell data resampling and modular response analysis. Intriguingly, we discovered that recovered weights of specific network edges undergo divergent shifts under differential perturbations, and that the particular behavior is markedly different between topologies. Our results point to a conceptual advance for reverse engineering beyond weight inference. Investigating topological changes under differential perturbations may address the longstanding problem of discriminating direct and indirect connectivities in biological networks. PMID:26420864

  19. 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.

  20. Social network of an internationally connected nurse leader.

    Science.gov (United States)

    Benton, David

    2016-03-01

    Over the past decade, there has been a proliferation of social media sites offering the opportunity for colleagues to connect with each other locally, nationally and internationally. Meanwhile, nurses have been increasingly using social network analytical techniques to look at team functioning and communication pathways. This article uses the author's LinkedIn social network to illustrate how analysis can offer insights into the connections, and how the results can be used to professional advantage. PMID:26927791

  1. 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

  2. Revealing Hidden Connections in Recommendation Networks

    OpenAIRE

    Minhano, Rogerio; Fernandes, Stenio; 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 se...

  3. 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.

  4. An Empirical Evaluation of the Performance of Mobile Network Connections

    OpenAIRE

    Bylund, Markus

    2003-01-01

    We present the results of an empirical evaluation of the performance of some network connections available for mobile terminals. General Packet Radio Service (GPRS) is compared with Bluetooth and a USB wired connection from a Sony Ericsson P800 smart phone.

  5. Brain Connectivity Plasticity in the Motor Network after Ischemic Stroke

    OpenAIRE

    Lin Jiang; Huijuan Xu; Chunshui Yu

    2013-01-01

    The motor function is controlled by the motor system that comprises a series of cortical and subcortical areas interacting via anatomical connections. The motor function will be disturbed when the stroke lesion impairs either any of these areas or their connections. More and more evidence indicates that the reorganization of the motor network including both areas and their anatomical and functional connectivity might contribute to the motor recovery after stroke. Here, we review recent studie...

  6. High Resolution Modelling of Anomalous Transport of Carbon Dioxide in Fracture Networks

    Science.gov (United States)

    Annewandter, R.; Main, I. G.; Geiger, S.

    2012-12-01

    Currently, large-scale modelling for Geological Carbon Storage (GCS) focuses mainly on carbon dioxide plume migration in porous media and do not account for sub-grid heterogeneities. A prevailing assumption therefore is that component transport and chemical reaction happens under well-mixed conditions. However, it has been shown that spreading of a dispersed plume and mixing of its components with the moving fluid is being affected by spatial changes in hydraulic and chemical properties. This leads to incomplete mixing as relevant processes at scales considered are not in local equilibrium resulting in anomalous transport. Anomalous transport is characterized by early or late component arrival and non-linear growth of the second moment of phase distributions and displacing saturation front. Incomplete mixing affects the amount of carbon dioxide in storage repositories. Using classical means to compute effective transport properties by averaging permeabilities and porosities, and assuming well-mixed carbon dioxide concentrations, may lead to significantly different patterns for large-scale flow and transport. Subsequent trapping processes such as capillary, solubility and mineral trapping therefore overpredicts the amount of supercritical carbon dioxide in storage repositories as as only a fraction of the rock volume will be exposed to it. We study the impact of variable length correlated apertures of fracture networks on breakthrough curves and on upscaled effective properties for carbon dioxide transport. We use an advection-dispersion equation which accounts for capillarity and gravity effects. Chemical reactions are not considered. Simulations are carried out using a general purpose reservoir simulator, the 'Complex System Modelling Platform (CSMP)'. It has been purposefully designed to solve compositional and compressible multi-phase flow and transport problems for fractured porous media in complex geological settings. It uses a Godunov operator

  7. 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…

  8. 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

  9. 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.

  10. 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.

  11. A connective differentiation of textual production in interaction networks

    OpenAIRE

    Fabbri, Renato

    2014-01-01

    This paper explores textual production in interaction networks, with special emphasis on its relation to topological measures. Four email lists were selected, in which measures were taken from the texts participants wrote. Peripheral, intermediary and hub sectors of these networks were observed to have discrepant linguistic elaborations. For completeness of exposition, correlation of textual and topological measures were observed for the entire network and for each connective sector. The form...

  12. Teletraffic Models for Mobile Network Connectivity.

    OpenAIRE

    Venigalla, Thejaswi; Akkapaka, Raj Kiran

    2013-01-01

    We are in an era marked by tremendous global growth in mobile traffic and subscribers due to change in the mobile communication technology from second generation to third and fourth generations. Especially usage of packet-data applications has recorded remarkable growth. The need for mobile communication networks capable of providing an ever increasing spectrum of services calls for efficient techniques for the analysis, monitoring and design of networks. To meet the ever increasing demands o...

  13. 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.

  14. 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.

  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 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 ...

  17. Emerging connections in the ethylene signaling network

    OpenAIRE

    Yoo, Sang-Dong; Cho, Younghee; Sheen, Jen

    2009-01-01

    The gaseous plant hormone ethylene acts as a pivotal mediator to respond to and coordinate internal and external cues in modulating plant growth dynamics and developmental programs. Genetic analysis of Arabidopsis thaliana has been used to identify key components and to build a linear ethylene-signaling pathway from the receptors through to the nuclear transcription factors. Studies applying integrative approaches have revealed new regulators, molecular connections and mechanisms in ethylene ...

  18. Connection cube modules for optical backplanes and fiber networks.

    Science.gov (United States)

    Kostuk, R K; Ramsey, D L; Kim, T J

    1997-07-10

    A modular free-space optical system, called the connection cube, for connecting arrays of electro-optic transceivers and fiber-array connectors is presented. The connection cube module provides bidirectional data transfer between four processing nodes on a cube face and can be used as a basic building block for optical backplanes and interconnect networks. An experimental system for connecting four processing nodes is presented and used to examine alignment and packaging issues. An analysis of the dimensional requirements and scaling capability for systems based on this module is conducted. This analysis shows that, when the connection cube module is adapted to vertical-cavity surface-emitting-laser-based point-to-point fiber-array links currently under development, it can connect up to 14 processing nodes with an aggregate data transfer capacity of 112 Gbits/s with 19.6-W power consumption. PMID:18259270

  19. 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 \

  20. 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

  1. Network connection of distributed electricity production - a preliminary study

    International Nuclear Information System (INIS)

    It will be necessary to lower the barriers for utilisation of distributed energy sources in order to increase the use of such sources in Norway. A relatively extensive R and D activity would be required for reaching this goal. Available Norwegian and international guidelines and technical requirements with respect to network connection of the distributed energy sources are studied with the aim of exposing needs for further R and D initiatives. A limited monitor is also carried out among the Norwegian network businesses with distributed units in their networks. The results show that the main focus in the R and D activities has drifted away from establishing guidelines for technical requirements for network coupling. Some verification work remains in investigating the usefulness of the existing international and the specific commercial network guidelines. For the network industry the main focus must be on the two following areas: 1) How will large concentrations of distributed production units connected to the same network influence the voltage quality and the delivery reliability in the networks. 2) How can the network businesses employ the distributed production units in their networks. A Nordic project (Finland, Sweden, Norway) which will study these problems is being established. Large national scientific institutions will be involved. The executive committee will consist of representatives from Finenergy, Elforsk and EBL Kompetanse and other financing institutions and industries. A Finnish business Merinova, is to be appointed to the project leadership

  2. 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.

  3. 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.

  4. 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. PMID:26871086

  5. 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.

  6. 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 snaps...... analytic expressions for the distributions and moments of these random variables for general stationary MAP processes on a one dimensional space. The numerical results compares bursty vehicular traffic with independent movement scenarios described by a Poisson process....

  7. Atypical Network Connectivity for Imitation in Autism Spectrum Disorder

    OpenAIRE

    Shih, Patricia; Shen, Mark; Öttl, Birgit; Keehn, Brandon; Gaffrey, Michael S.; Müller, Ralph-Axel

    2010-01-01

    Imitation has been considered as one of the precursors for sociocommunicative development. Impairments of imitation in autism spectrum disorder (ASD) could be indicative of dysfunctional underlying neural processes. Neuroimaging studies have found reduced activation in areas associated with imitation, but a functional connectivity MRI network perspective of these regions in autism is unavailable. Functional and effective connectivity was examined in 14 male participants with ASD and 14 matche...

  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. 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.

  10. Dual connectivity for LTE-advanced heterogeneous networks

    DEFF Research Database (Denmark)

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

    2016-01-01

    paper we focus on the case where a macro and a small cell eNBs are inter-connected with traditional backhaul links characterized by certain latency, assuming independent radio resource management (RRM) functionalities residing in each eNB. In order to fully harvest the gain provided by DC, an efficient...... aggregation (CA) and virtually zerolatency fronthaul connections, and in any case it is significantly higher compared to the case without DC. Keywords: Dual connectivity Heterogeneous network LTE-advanced Radio resource management Performance evaluation...

  11. 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...

  12. Connectivity of neutral networks and structural conservation in protein evolution

    OpenAIRE

    Bastolla, Ugo; Porto, Markus; Roman, H. Eduardo; Vendruscolo, Michele

    2001-01-01

    Protein structures are much more conserved than sequences during evolution. Based on this observation, we investigate the consequences of structural conservation on protein evolution. We study seven of the most studied protein folds, finding out that an extended neutral network in sequence space is associated to each of them. Within our model, neutral evolution leads to a non-Poissonian substitution process, due to the broad distribution of connectivities in neutral networks. The observation ...

  13. A trusted connection framework for multilevel secure Local Area Networks

    OpenAIRE

    Wilson, Jeffery Dwane.

    2000-01-01

    The Naval Postgraduate School is developing a Multilevel Secure Local Area Network (MLS LAN) that incorporates commercial-off-the-shelf client workstations to provide multiple users with simultaneous secure access to stored data of different sensitivity levels. The MLS LAN uses a Trusted Computing Base Extension (TCBE) in the LAN's client workstations to extend the TCB from the trusted server across the network to these workstations. Connections between elements of the LAN are under TCB contr...

  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. Brain Connectivity Plasticity in the Motor Network after Ischemic Stroke

    Directory of Open Access Journals (Sweden)

    Lin Jiang

    2013-01-01

    Full Text Available The motor function is controlled by the motor system that comprises a series of cortical and subcortical areas interacting via anatomical connections. The motor function will be disturbed when the stroke lesion impairs either any of these areas or their connections. More and more evidence indicates that the reorganization of the motor network including both areas and their anatomical and functional connectivity might contribute to the motor recovery after stroke. Here, we review recent studies employing models of anatomical, functional, and effective connectivity on neuroimaging data to investigate how ischemic stroke influences the connectivity of motor areas and how changes in connectivity relate to impaired function and functional recovery. We suggest that connectivity changes constitute an important pathophysiological aspect of motor impairment after stroke and important mechanisms of motor recovery. We also demonstrate that therapeutic interventions may facilitate motor recovery after stroke by modulating the connectivity among the motor areas. In conclusion, connectivity analyses improved our understanding of the mechanisms of motor recovery after stroke and may help to design hypothesis-driven treatment strategies and sensitive measures for outcome prediction in stroke patients.

  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. Selectively disrupted functional connectivity networks in type 2 diabetes mellitus

    Directory of Open Access Journals (Sweden)

    Yaojing eChen

    2015-12-01

    Full Text Available Background: The high prevalence of type 2 diabetes mellitus (T2DM in individuals over 65 years old and cognitive deficits caused by T2DM have attracted broad attention. The pathophysiological mechanism of T2DM induced cognitive impairments, however, remains poorly understood. Previous studies have suggested that the cognitive impairments can be attributed not merely to local functional and structural abnormalities but also to specific brain networks. Thus, we aimed to investigate the changes of global networks selectively affected by T2DM. Methods: A resting state functional network analysis was conducted to investigate the intrinsic functional connectivity in 37 patients with diabetes and 40 healthy controls which were recruited from local communities in Beijing, China. Results: We found that patients with T2DM exhibited cognitive function declines and functional connectivity disruptions within the default mode network, left frontal parietal network, and sensorimotor network. More importantly, the fasting glucose level was correlated with abnormal functional connectivity.Conclusions: These findings could help to understand the neural mechanisms of cognitive impairments in T2DM and provide potential neuroimaging biomarkers that may be used for early diagnosis and intervention in cognitive decline.

  19. 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.

  20. Quantifying the connectivity of a network: The network correlation function method

    CERN Document Server

    Barzel, Baruch; 10.1103/PhysRevE.80.046104

    2009-01-01

    Networks are useful for describing systems of interacting objects, where the nodes represent the objects and the edges represent the interactions between them. The applications include chemical and metabolic systems, food webs as well as social networks. Lately, it was found that many of these networks display some common topological features, such as high clustering, small average path length (small world networks) and a power-law degree distribution (scale free networks). The topological features of a network are commonly related to the network's functionality. However, the topology alone does not account for the nature of the interactions in the network and their strength. Here we introduce a method for evaluating the correlations between pairs of nodes in the network. These correlations depend both on the topology and on the functionality of the network. A network with high connectivity displays strong correlations between its interacting nodes and thus features small-world functionality. We quantify the ...

  1. 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

  2. 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

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

    Science.gov (United States)

    Artzy-Randrup, Yael; Stone, Lewi

    2010-01-01

    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

  4. 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."

  5. Predicting fate from early connectivity in a social network.

    Science.gov (United States)

    McDonald, David B

    2007-06-26

    In the long-tailed manakin (Chiroxiphia linearis), a long-lived tropical bird, early connectivity within a social network predicts male success an average of 4.8 years later. Long-tailed manakins have an unusual lek mating system in which pairs of unrelated males, at the top of complex overlapping teams of as many as 15 males, cooperate for obligate dual-male song and dance courtship displays. For as long as 8 years before forming stable "alpha-beta" partnerships, males interact with many other males in complex, temporally dynamic social networks. "Information centrality" is a network connectivity metric that accounts for indirect as well as shortest (geodesic) paths among interactors. The odds that males would rise socially rose by a factor of five for each one-unit increase in their early information centrality. Connectivity of males destined to rise did not change over time but increased in males that failed to rise socially. The results suggest that network connectivity is important for young males (ages 1-6) but less so for older males of high status (ages 10-15) and that it is difficult to explain present success without reference to social history. PMID:17576933

  6. Scaling of critical connectivity of mobile ad hoc networks.

    Science.gov (United States)

    Wang, Li; Zhu, Chen-Ping; Gu, Zhi-Ming

    2008-12-01

    In this paper, critical global connectivity of mobile ad hoc networks (MANETs) is investigated. We model the two-dimensional plane on which nodes move randomly with a triangular lattice. Demanding the best communication of the network, we account the global connectivity eta as a function of occupancy sigma of sites in the lattice by mobile nodes. Critical phenomena of the connectivity for different transmission ranges r are revealed by numerical simulations, and these results fit well to the analysis based on the assumption of homogeneous mixing. Scaling behavior of the connectivity is found as eta approximately f(R;{beta}sigma) , where R=(r-r_{0})r_{0} , r_{0} is the length unit of the triangular lattice, and beta is the scaling index in the universal function f(x) . The model serves as a sort of geometric distance-dependent site percolation on dynamic complex networks. Moreover, near each critical sigma_{c}(r) corresponding to certain transmission range r , there exists a cutoff degree k_{c} below which the clustering coefficient of such self-organized networks keeps a constant while the averaged nearest-neighbor degree exhibits a unique linear variation with the degree k , which may be useful to the designation of real MANETs. PMID:19256905

  7. 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.

  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. 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.

  10. 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 ...

  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. The Network Observability Problem: Detecting nodes and connections

    CERN Document Server

    Rios, Dionicio F

    2013-01-01

    Reconstructing the connections between the nodes of a network is a problem of fundamental importance in the study of neuronal and genetic networks. An underlying related problem is that of observability, i.e., identifying the conditions under which such a reconstruction is possible. In this paper we consider observability of complex dynamical networks, for which we aim at identifying both node and edge states. We use a graphical approach, which we apply to both the Node Inference Diagram (NID) and the Node Edge Inference Diagram (NEID) of the network. We investigate the relationship between the observability of the NID and that of the NEID network representations and conclude that the latter can be derived from the former, under general assumptions. We further consider the effects of graph symmetries on observability and we show how a minimal set of outputs can be selected to obtain observability in the presence of symmetries.

  14. 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.

  15. 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.

  16. 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.

  17. Alternatives for Monitoring and Limiting Network Access to Students in Network-Connected Classrooms

    Science.gov (United States)

    Almeroth, Kevin; Zhang, Hangjin

    2013-01-01

    With the advent of laptop computers and network technology, many classrooms are now being equipped with Internet connections, either through wired connections or wireless infrastructure. Internet access provides students an additional source from which to obtain course-related information. However, constant access to the Internet can be a…

  18. Image Informatics Strategies for Deciphering Neuronal Network Connectivity.

    Science.gov (United States)

    Detrez, Jan R; Verstraelen, Peter; Gebuis, Titia; Verschuuren, Marlies; Kuijlaars, Jacobine; Langlois, Xavier; Nuydens, Rony; Timmermans, Jean-Pierre; De Vos, Winnok H

    2016-01-01

    Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Amongst the neuronal structures that show morphological plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular communication and the associated calcium bursting behaviour. In vitro cultured neuronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardization of both image acquisition and image analysis, it has become possible to extract statistically relevant readouts from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies. PMID:27207365

  19. Connecting the dots: network data and models in HIV epidemiology.

    Science.gov (United States)

    Delva, Wim; Leventhal, Gabriel E; Helleringer, Stéphane

    2016-08-24

    Effective HIV prevention requires knowledge of the structure and dynamics of the social networks across which infections are transmitted. These networks most commonly comprise chains of sexual relationships, but in some populations, sharing of contaminated needles is also an important, or even the main mechanism that connects people in the network. Whereas network data have long been collected during survey interviews, new data sources have become increasingly common in recent years, because of advances in molecular biology and the use of partner notification services in HIV prevention and treatment programmes. We review current and emerging methods for collecting HIV-related network data, as well as modelling frameworks commonly used to infer network parameters and map potential HIV transmission pathways within the network. We discuss the relative strengths and weaknesses of existing methods and models, and we propose a research agenda for advancing network analysis in HIV epidemiology. We make the case for a combination approach that integrates multiple data sources into a coherent statistical framework. PMID:27314176

  20. 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

  1. Targeted attack on networks coupled by connectivity and dependency links

    Science.gov (United States)

    Du, Ruijin; Dong, Gaogao; Tian, Lixin; Liu, Runran

    2016-05-01

    Coupled systems used to increase capacity were shown beneficial as long as it does not open pathways to cascades. Previous studies on the robustness of coupled networks except for interdependent networks are almost the cases of random attack. Many challenges remain exist in targeted-attack problem of coupled networks. Since nodes within coupled networks show different functions for each network, this paper both analytically and numerically analyzed the robustness of coupled networks under three types of targeted attacking strategies, including attacking on nodes by considering internal and external degree, internal degree only, and external degree only. For coupled network with both interdependent and interconnected links, all degree distributions of intra- and inter-connectivity links are Poissonian, we find the system undergoes from second to first order phase transition as coupling strength q increases. The fraction of nodes in the giant component P∞ at stable state, the critical phase transition threshold pc (first order threshold pcI and second order threshold pcII), and the critical point (pc ,qc) separating the first and second order phase transitions are analytically obtained for three types of attacking strategies with attacking probability parameter α = 0 , 1. We also find the system becomes more vulnerable as the average degree of intra-links k ¯ or inter-links K ¯ decreases. Therefore, the minimum average degrees k¯min and K¯min to maintain the system stable are obtained for the case of α = 0 , 1. Moreover, we discussed three typical cases of coupled networks, interdependent networks (K ¯ = 0), interacting networks (q = 0) and bipartite network (k = 0, q = 0), the analytical expressions of P∞, pc and (pc ,qc) (only for interdependent) are given respectively. Besides, we study the equivalence relations between interdependent networks and coupled networks with connectivity and dependency links for the same pc. The results imply that we can

  2. Connectivity, flow and transport in network models of fractured media

    International Nuclear Information System (INIS)

    In order to evaluate the safety of radioactive waste disposal underground it is important to understand the way in which radioactive material is transported through the rock to the surface. If the rock is fractured the usual models may not be applicable. In this work we look at three aspects of fracture networks: connectivity, flow and transport. These are studied numerically by generating fracture networks in a computer and modelling the processes which occur. Connectivity relates to percolation theory, and critical densities for fracture systems are found in two and three dimensions. The permeability of two-dimensional networks is studied. The way that permeability depends on fracture density, network size and spread of fracture length can be predicted using a cut lattice model. Transport through the fracture network by convection through the fractures and mixing at the intersections is studied. The Fickian dispersion equation does not describe the resulting hydrodynamic dispersion. Extensions to the techniques to three dimensions and to include other processes are discussed. (author)

  3. Diphosphine dioxides as extractants for actinides (in connection with the problem of anomalous aryl strengthening of complexes)

    International Nuclear Information System (INIS)

    Extraction study of uranylnitrate, plutonium in trivalent, tetravalent and gexavalent states and trivalent americium, curium, praseodymium and promethium by alkyl, aromatic and mixed diphosphine dioxides is briefly outlined. The influence of diphosphine dioxide structures on their extraction capacity and, in particular, the problem of anomalous aryl strengthening of compounds, both of entropy and binding character, are considered. Perchlorate media, as opposed to nitrate ones, are characteristic for their high distribution coefficients and extraction equilibrium constants. Anomalous aryl strengthening of trivalent lanthanides and actinides can be applied, at the minimum, for solution purifications from the traces of actinides and lanthanides

  4. 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.

  5. 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.

  6. Bayesian network models in brain functional connectivity analysis

    OpenAIRE

    Ide, Jaime S.; Zhang, Sheng; Chiang-shan R. Li

    2013-01-01

    Much effort has been made to better understand the complex integration of distinct parts of the human brain using functional magnetic resonance imaging (fMRI). Altered functional connectivity between brain regions is associated with many neurological and mental illnesses, such as Alzheimer and Parkinson diseases, addiction, and depression. In computational science, Bayesian networks (BN) have been used in a broad range of studies to model complex data set in the presence of uncertainty and wh...

  7. Exploring functional connectivity networks with multichannel brain array coils.

    Science.gov (United States)

    Anteraper, Sheeba Arnold; Whitfield-Gabrieli, Susan; Keil, Boris; Shannon, Steven; Gabrieli, John D; Triantafyllou, Christina

    2013-01-01

    The use of multichannel array head coils in functional and structural magnetic resonance imaging (MRI) provides increased signal-to-noise ratio (SNR), higher sensitivity, and parallel imaging capabilities. However, their benefits remain to be systematically explored in the context of resting-state functional connectivity MRI (fcMRI). In this study, we compare signal detectability within and between commercially available multichannel brain coils, a 32-Channel (32Ch), and a 12-Channel (12Ch) at 3T, in a high-resolution regime to accurately map resting-state networks. We investigate whether the 32Ch coil can extract and map fcMRI more efficiently and robustly than the 12Ch coil using seed-based and graph-theory-based analyses. Our findings demonstrate that although the 12Ch coil can be used to reveal resting-state connectivity maps, the 32Ch coil provides increased detailed functional connectivity maps (using seed-based analysis) as well as increased global and local efficiency, and cost (using graph-theory-based analysis), in a number of widely reported resting-state networks. The exploration of subcortical networks, which are scarcely reported due to limitations in spatial-resolution and coil sensitivity, also proved beneficial with the 32Ch coil. Further, comparisons regarding the data acquisition time required to successfully map these networks indicated that scan time can be significantly reduced by 50% when a coil with increased number of channels (i.e., 32Ch) is used. Switching to multichannel arrays in resting-state fcMRI could, therefore, provide both detailed functional connectivity maps and acquisition time reductions, which could further benefit imaging special subject populations, such as patients or pediatrics who have less tolerance in lengthy imaging sessions. PMID:23510203

  8. The value of less connected agents in Boolean networks

    Science.gov (United States)

    Epstein, Daniel; Bazzan, Ana L. C.

    2013-11-01

    In multiagent systems, agents often face binary decisions where one seeks to take either the minority or the majority side. Examples are minority and congestion games in general, i.e., situations that require coordination among the agents in order to depict efficient decisions. In minority games such as the El Farol Bar Problem, previous works have shown that agents may reach appropriate levels of coordination, mostly by looking at the history of past decisions. Not many works consider any kind of structure of the social network, i.e., how agents are connected. Moreover, when structure is indeed considered, it assumes some kind of random network with a given, fixed connectivity degree. The present paper departs from the conventional approach in some ways. First, it considers more realistic network topologies, based on preferential attachments. This is especially useful in social networks. Second, the formalism of random Boolean networks is used to help agents to make decisions given their attachments (for example acquaintances). This is coupled with a reinforcement learning mechanism that allows agents to select strategies that are locally and globally efficient. Third, we use agent-based modeling and simulation, a microscopic approach, which allows us to draw conclusions about individuals and/or classes of individuals. Finally, for the sake of illustration we use two different scenarios, namely the El Farol Bar Problem and a binary route choice scenario. With this approach we target systems that adapt dynamically to changes in the environment, including other adaptive decision-makers. Our results using preferential attachments and random Boolean networks are threefold. First we show that an efficient equilibrium can be achieved, provided agents do experimentation. Second, microscopic analysis show that influential agents tend to consider few inputs in their Boolean functions. Third, we have also conducted measurements related to network clustering and centrality

  9. 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.

  10. 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...

  11. 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.

  12. 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.

  13. 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

  14. Adjacency Matrix based method to compute the node connectivity of a Computer Communication Network

    CERN Document Server

    Kamalesh, V N

    2010-01-01

    Survivability of a computer communication network is the ability of a network to provide continuous service in the presence of link or node failures. It is an essential and considerable concern in the design of high speed communication network topologies. The connectivity number of a network is the graph theoretical metric to measure survivability of the communication network. Given a network and a positive integer k, few heuristics exist in literature to verify whether the given network is k connected or not. This paper presents a method to compute the connectivity number k of a given computer communication network.

  15. 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.

  16. 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...

  17. 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.

  18. Age-related differences in electroencephalogram connectivity and network topology.

    Science.gov (United States)

    Knyazev, Gennady G; Volf, Nina V; Belousova, Ludmila V

    2015-05-01

    To better understand age-related differences in brain function and behavior, connectivity between brain regions was estimated from electroencephalogram source time series in eyes closed versus eyes open resting condition. In beta band, decrease of connectivity upon eyes opening was more pronounced in younger than in older participants. The extent of this decrease was associated with reaction time in attention tasks, and this relationship was fully mediated by participants' age, implying that physiological processes, which lead to age-related slowing, include changes in beta reactivity. Graph-theoretical analysis showed a decrease of modularity and clustering in beta and gamma band networks in older adults, implying that age makes brain networks more random. The overall number of nodes identified as hubs in posterior cortical regions decreased in older participants. At the same time, increase of connectedness of anterior nodes, probably reflecting compensatory activation of the anterior attentional system, was observed in beta-band network of older adults. These findings show that normal aging mostly affects interactions in beta band, which are probably involved in attentional processes. PMID:25766772

  19. Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Neeraj Kumar

    2010-03-01

    Full Text Available There are many challenges when designing and deploying wireless sensor networks (WSNs. One of thekey challenges is how to make full use of the limited energy to prolong the lifetime of the network,because energy is a valuable resource in WSNs. The status of energy consumption should be continuouslymonitored after network deployment. In this paper, we propose coverage and connectivity aware neuralnetwork based energy efficient routing in WSN with the objective of maximizing the network lifetime. Inthe proposed scheme, the problem is formulated as linear programming (LP with coverage andconnectivity aware constraints. Cluster head selection is proposed using adaptive learning in neuralnetworks followed by coverage and connectivity aware routing with data transmission. The proposedscheme is compared with existing schemes with respect to the parameters such as number of alive nodes,packet delivery fraction, and node residual energy. The simulation results show that the proposed schemecan be used in wide area of applications in WSNs.

  20. Voter dynamics on an adaptive network with finite average connectivity

    Science.gov (United States)

    Mukhopadhyay, Abhishek; Schmittmann, Beate

    2009-03-01

    We study a simple model for voter dynamics in a two-party system. The opinion formation process is implemented in a random network of agents in which interactions are not restricted by geographical distance. In addition, we incorporate the rapidly changing nature of the interpersonal relations in the model. At each time step, agents can update their relationships, so that there is no history dependence in the model. This update is determined by their own opinion, and by their preference to make connections with individuals sharing the same opinion and with opponents. Using simulations and analytic arguments, we determine the final steady states and the relaxation into these states for different system sizes. In contrast to earlier studies, the average connectivity (``degree'') of each agent is constant here, independent of the system size. This has significant consequences for the long-time behavior of the model.

  1. 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.

  2. 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.

  3. Intrinsic Functional-Connectivity Networks for Diagnosis: Just Beautiful Pictures?

    Science.gov (United States)

    Moeller, James R.

    2011-01-01

    Abstract Resting-state functional connectivity has become a topic of enormous interest in the Neuroscience community in the last decade. Because resting-state data (1) harbor important information that often is diagnostically relevant and (2) are easy to acquire, there has been a rapid increase in the development of a variety of network analytic techniques for diagnostic applications, stimulating methodological research in general. While we are among those who welcome the increased interest in the resting state and multivariate analytic tools, we would like to draw attention to some entrenched practices that undermine the scientific quality of diagnostic functional-connectivity research, but whose correction is relatively easy to accomplish. With the current commentary we also hope to benefit the field at large and contribute to a healthy debate about research goals and best practices. PMID:22433005

  4. 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.

  5. Covert neurofeedback without awareness shapes cortical network spontaneous connectivity.

    Science.gov (United States)

    Ramot, Michal; Grossman, Shany; Friedman, Doron; Malach, Rafael

    2016-04-26

    Recent advances in blood oxygen level-dependent-functional MRI (BOLD-fMRI)-based neurofeedback reveal that participants can modulate neuronal properties. However, it is unknown whether such training effects can be introduced in the absence of participants' awareness that they are being trained. Here, we show unconscious neurofeedback training, which consequently produced changes in functional connectivity, introduced in participants who received positive and negative rewards that were covertly coupled to activity in two category-selective visual cortex regions. The results indicate that brain networks can be modified even in the complete absence of intention and awareness of the learning situation, raising intriguing possibilities for clinical interventions. PMID:27071084

  6. 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.

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

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano

    generation of pikes. When a stimulus is applied to the network, the spontaneous rings may prevail and hamper detection of the effects of the stimulus. Therefore, the spontaneous rings cannot be ignored and the response latency has to be detected on top of a background signal. Everything becomes more dicult...... if the latencies are expressed as a sum of deterministic (absolute response latency) and stochastic (relative response latency) parts. The third question is:what is the response latency to the stimulus? Non-parametric and parametric estimators of the two components are proposed in a single neuron framework....... 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...

  8. Small Universal Accepting Networks of Evolutionary Processors with Filtered Connections

    Directory of Open Access Journals (Sweden)

    Remco Loos

    2009-07-01

    Full Text Available In this paper, we present some results regarding the size complexity of Accepting Networks of Evolutionary Processors with Filtered Connections (ANEPFCs. We show that there are universal ANEPFCs of size 10, by devising a method for simulating 2-Tag Systems. This result significantly improves the known upper bound for the size of universal ANEPFCs which is 18. We also propose a new, computationally and descriptionally efficient simulation of nondeterministic Turing machines by ANEPFCs. More precisely, we describe (informally, due to space limitations how ANEPFCs with 16 nodes can simulate in O(f(n time any nondeterministic Turing machine of time complexity f(n. Thus the known upper bound for the number of nodes in a network simulating an arbitrary Turing machine is decreased from 26 to 16.

  9. 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. PMID:23501053

  10. 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.

  11. Node similarity is the basic principle behind connectivity in complex networks

    CERN Document Server

    Scholz, Matthias

    2010-01-01

    Who is connecting to whom in social communities? A popular belief is that preferential attachment to a highly connected network-node is an adequate model for real networks. By contrast, this work reveals that node similarity is the fundamental mechanism that gives complex networks its typical scale-free power-law characteristics. Additionally, it turns out that power-law node-degree distributions are restricted to only sparsely connected communities. More densely connected communities show an increasing divergence from power-law. A similarity model as proposed in this work, covers the full observed diversity of real networks and hence explains the topological transition from weakly to strongly connected societies.

  12. Surface water-groundwater connectivity in deltaic distributary channel networks

    Science.gov (United States)

    Sawyer, Audrey H.; Edmonds, Douglas A.; Knights, Deon

    2015-12-01

    Delta distributary channel networks increase river water contact with sediments and provide the final opportunity to process nutrients and other solutes before river water discharges to the ocean. In order to understand surface water-groundwater interactions at the scale of the distributary channel network, we created three numerical deltas that ranged in composition from silt to sand using Delft3D, a morphodynamic flow and sediment transport model. We then linked models of mean annual river discharge to steady groundwater flow in MODFLOW. Under mean annual discharge, exchange rates through the numerical deltas are enhanced relative to a single-threaded river. We calculate that exchange rates across a threaded river channel. Exchange rates are greatest in the coarse-grained delta due to its permeability and morphology. Groundwater residence times range from hours to centuries and have fractal tails. Deltas are vanishing due to relative sea level rise. River diversion projects aimed at creating new deltaic land should also aim to restore surface water-groundwater connectivity, which is critical for biogeochemical processing in wetlands. We recommend designing diversions to capture more sand and thus maximize surface water-groundwater connectivity.

  13. Connectivity of Large Scale Networks: Emergence of Unique Unbounded Component

    CERN Document Server

    Mao, Guoqiang

    2011-01-01

    This paper studies networks where all nodes are distributed on a unit square $A\\triangleq[(-1/2,1/2)^{2}$ following a Poisson distribution with known density $\\rho$ and a pair of nodes separated by an Euclidean distance $x$ are directly connected with probability $g(\\frac{x}{r_{\\rho}})$, independent of the event that any other pair of nodes are directly connected. Here $g:[0,\\infty)\\rightarrow[0,1]$ satisfies the conditions of rotational invariance, non-increasing monotonicity, integral boundedness and $g(x)=o(\\frac{1}{x^{2}\\log^{2}x})$; further, $r_{\\rho}=\\sqrt{\\frac{\\log\\rho+b}{C\\rho}}$ where $C=\\int_{\\Re^{2}}g(\\Vert \\boldsymbol{x}\\Vert)d\\boldsymbol{x}$ and $b$ is a constant. Denote the above network by\\textmd{}$\\mathcal{G}(\\mathcal{X}_{\\rho},g_{r_{\\rho}},A)$. We show that as $\\rho\\rightarrow\\infty$, asymptotically almost surely a) there is no component in $\\mathcal{G}(\\mathcal{X}_{\\rho},g_{r_{\\rho}},A)$ of fixed and finite order $k>1$; b) the number of components with an unbounded order is one. Therefore a...

  14. Learn the effective connectivity pattern of attention networks: a resting functional MRI and Bayesian network study

    Science.gov (United States)

    Li, Juan; Li, Rui; Yao, Li; Wu, Xia

    2011-03-01

    Task-based neuroimaging studies revealed that different attention operations were carried out by the functional interaction and cooperation between two attention systems: the dorsal attention network (DAN) and the ventral attention network (VAN), which were respectively involved in the "top-down" endogenous attention orienting and the "bottomup" exogenous attention reorienting process. Recent focused resting functional MRI (fMRI) studies found the two attention systems were inherently organized in the human brain regardless of whether or not the attention process were required, but how the two attention systems interact with each other in the absence of task is yet to be investigated. In this study, we first separated the DAN and VAN by applying the group independent component analysis (ICA) to the resting fMRI data acquired from 12 healthy young subjects, then used Gaussian Bayesian network (BN) learning approach to explore the plausible effective connectivity pattern of the two attention systems. It was found regions from the same attention network were strongly intra-dependent, and all the connections were located in the information flow from VAN to DAN, which suggested that an orderly functional interactions and information exchanges between the two attention networks existed in the intrinsic spontaneous brain activity, and the inherent connections might benefit the efficient cognitive process between DAN and VAN, such as the "top-down" and "bottom-up" reciprocal interaction when attention-related tasks were involved.

  15. 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.

  16. 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.

  17. Aberrant structural and functional connectivity in the salience network and central executive network circuit in schizophrenia.

    Science.gov (United States)

    Chen, Quan; Chen, Xingui; He, Xiaoxuan; Wang, Lu; Wang, Kai; Qiu, Bensheng

    2016-08-01

    Consistent structural and functional abnormities have been detected in the salience network (SN) and the central-executive network (CEN) in schizophrenia. SN, known for its critical role in switching CEN and default-mode network (DMN) during cognitively demanding tasks, is proved to show aberrant regulation on the interaction between DMN and CEN in schizophrenia. However, it has not been elucidated whether there is a direct alteration of structural and functional connectivity between SN and CEN. 22 schizophrenia patients and 21 healthy controls were recruited for functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) in present study. The results show that schizophrenia patients had lower fractional anisotropy (FA) in right inferior long fasciculus (ILF), left inferior fronto-occipital fasciculus (IFOF) and callosal body than healthy controls. Significantly reduced functional connectivity was also found between right fronto-insular cortex (rFIC) and right posterior parietal cortex (rPPC). FA in right ILF was positively correlated with the functional connectivity of rFIC-rPPC. Therefore, we proposed a disruption of structural and functional connectivity and a positive anatomo-functional relationship in SN-CEN circuit, which might account for a core feature of schizophrenia. PMID:27233217

  18. Secure Reprogramming of a Network Connected Device : Securing programmable logic controllers

    OpenAIRE

    Tesfaye, Mussie

    2012-01-01

    This is a master’s thesis project entitled “Secure reprogramming of network connected devices”. The thesis begins by providing some background information to enable the reader to understand the current vulnerabilities of network-connected devices, specifically with regard to cyber security and data integrity. Today supervisory control and data acquisition systems utilizing network connected programmable logic controllers are widely used in many industries and critical infrastructures. These n...

  19. 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.

  20. 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. PMID:27004840

  1. 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.

  2. 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...

  3. A Connected Enterprise - Transformation Through Mobility and Social Networks

    Directory of Open Access Journals (Sweden)

    Jitendra Maan

    2012-09-01

    Full Text Available Due to rapid changes in business dynamics, there is a growing demand to encourage social conversations/exchanges and the ability to connect and communicate with peers, partners, customers andother stakeholders anytime, anywhere which drives the need of mobile-enable, the existing enterprise applications. This paper highlights a distinct set of needs and key customer challenges that must be considered and addressed for deployment of Social Collaboration applications and Mobility services in enterprises. It not only addresses the Critical Success Factors for enterprise mobility enablement but also outlines the unique business requirements to rapidly create social collaboration culture and the discipline of turning social data into meaningful insights to drive business decisions in real-time. Moreover, the paper emphasizes on developing composite offerings on social enterprise and Mobile networks that not only offer the value proposition in terms of financially oriented results, but also help customer to maximize return on investment (ROI.

  4. 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.

  5. Default network connectivity decodes brain states with simulated microgravity.

    Science.gov (United States)

    Zeng, Ling-Li; Liao, Yang; Zhou, Zongtan; Shen, Hui; Liu, Yadong; Liu, Xufeng; Hu, Dewen

    2016-04-01

    With great progress of space navigation technology, it becomes possible to travel beyond Earth's gravity. So far, it remains unclear whether the human brain can function normally within an environment of microgravity and confinement. Particularly, it is a challenge to figure out some neuroimaging-based markers for rapid screening diagnosis of disrupted brain function in microgravity environment. In this study, a 7-day -6° head down tilt bed rest experiment was used to simulate the microgravity, and twenty healthy male participants underwent resting-state functional magnetic resonance imaging scans at baseline and after the simulated microgravity experiment. We used a multivariate pattern analysis approach to distinguish the brain states with simulated microgravity from normal gravity based on the functional connectivity within the default network, resulting in an accuracy of no less than 85 % via cross-validation. Moreover, most discriminative functional connections were mainly located between the limbic system and cortical areas and were enhanced after simulated microgravity, implying a self-adaption or compensatory enhancement to fulfill the need of complex demand in spatial navigation and motor control functions in microgravity environment. Overall, the findings suggest that the brain states in microgravity are likely different from those in normal gravity and that brain connectome could act as a biomarker to indicate the brain state in microgravity. PMID:27066149

  6. 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.

  7. 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.

  8. 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

    manner under attacks. This work proposes four policies for failure handling in a connection-oriented optical transport network, under Generalized MultiProtocol Label Switching control plane, and evaluates their performance under multiple correlated large-scale failures. We employ the Susceptible-Infected-Disabled......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....

  9. 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.

  10. Properties of networks with partially structured and partially random connectivity

    Science.gov (United States)

    Ahmadian, Yashar; Fumarola, Francesco; Miller, Kenneth D.

    2015-01-01

    Networks studied in many disciplines, including neuroscience and mathematical biology, have connectivity that may be stochastic about some underlying mean connectivity represented by a non-normal matrix. Furthermore, the stochasticity may not be independent and identically distributed (iid) across elements of the connectivity matrix. More generally, the problem of understanding the behavior of stochastic matrices with nontrivial mean structure and correlations arises in many settings. We address this by characterizing large random N ×N matrices of the form A =M +L J R , where M ,L , and R are arbitrary deterministic matrices and J is a random matrix of zero-mean iid elements. M can be non-normal, and L and R allow correlations that have separable dependence on row and column indices. We first provide a general formula for the eigenvalue density of A . For A non-normal, the eigenvalues do not suffice to specify the dynamics induced by A , so we also provide general formulas for the transient evolution of the magnitude of activity and frequency power spectrum in an N -dimensional linear dynamical system with a coupling matrix given by A . These quantities can also be thought of as characterizing the stability and the magnitude of the linear response of a nonlinear network to small perturbations about a fixed point. We derive these formulas and work them out analytically for some examples of M ,L , and R motivated by neurobiological models. We also argue that the persistence as N →∞ of a finite number of randomly distributed outlying eigenvalues outside the support of the eigenvalue density of A , as previously observed, arises in regions of the complex plane Ω where there are nonzero singular values of L-1(z 1 -M ) R-1 (for z ∈Ω ) that vanish as N →∞ . When such singular values do not exist and L and R are equal to the identity, there is a correspondence in the normalized Frobenius norm (but not in the operator norm) between the support of the spectrum

  11. 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

  12. The strength of weak connections in the macaque cortico-cortical network.

    Science.gov (United States)

    Goulas, Alexandros; Schaefer, Alexander; Margulies, Daniel S

    2015-09-01

    Examination of the cortico-cortical network of mammals has unraveled key topological features and their role in the function of the healthy and diseased brain. Recent findings from social and biological networks pinpoint the significant role of weak connections in network coherence and mediation of information from segregated parts of the network. In the current study, inspired by such findings and proposed architectures pertaining to social networks, we examine the structure of weak connections in the macaque cortico-cortical network by employing a tract-tracing dataset. We demonstrate that the cortico-cortical connections as a whole, as well as connections between segregated communities of brain areas, comply with the architecture suggested by the so-called strength-of-weak-ties hypothesis. However, we find that the wiring of these connections is not optimal with respect to the aforementioned architecture. This configuration is not attributable to a trade-off with factors known to constrain brain wiring, i.e., wiring cost and efficiency. Lastly, weak connections, but not strong ones, appear important for network cohesion. Our findings relate a topological property to the strength of cortico-cortical connections, highlight the prominent role of weak connections in the cortico-cortical structural network and pinpoint their potential functional significance. These findings suggest that certain neuroimaging studies, despite methodological challenges, should explicitly take them into account and not treat them as negligible. PMID:25035063

  13. Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

    Science.gov (United States)

    D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

    2016-03-01

    We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

  14. 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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    connectivity with the bilateral opercular part of the inferior frontal gyrus in the SN. In SMN, there was increased connectivity with the right premotor cortex and decreased connectivity with the left visual cortex. Several areas showed increased (left primary auditory, secondary somatosensory, premotor......, 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....

  16. 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.

  17. 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.

  18. A Virtual Network Embedding Algorithm for Providing Stronger Connectivity in the Residual Networks

    Directory of Open Access Journals (Sweden)

    Yan Luo

    2013-04-01

    Full Text Available How to efficiently map the nodes and links in a given virtual network (VN to those in the substrate network (SN so that the residual substrate network (RSN can host as many VN requests as possible is a major challenge in virtual network embedding. Most research has developed heuristic algorithms with interactive or two-stage methods. These methods, however, could cause the RSN fragmented into several disconnected components that are insufficient to host a large number of given VN requests.Without loss of generality, we assume that SNs, as the Internet, are small world and scale free, meaning that the average number of hops between any two nodes is a small constant and that most nodes have small degrees while only a small number of nodes have large degrees. Taking advantage of these two properties, we devise in this paper a new twostage VN embedding approach to improve the connectivity of the residual substrate network so that it has the capacity to host more VN requests. Our algorithm uses a greedy strategy that maps neighboring VN nodes to substrate nodes whose distances are bounded by a small constant. We also map the edge nodes of given VN, i.e., nodes with small degrees, to nodes with large degrees in the SN. We then map the links by solving shortest path problems. Our experimental evaluations show that our algorithms offer better mappings and results in significantly fewer rejections for VN requests.

  19. 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

  20. A network theory approach for a better understanding of overland flow connectivity

    Science.gov (United States)

    Masselink, Rens; Heckmann, Tobias; Temme, Arnaud; Anders, Niels; Keesstra, Saskia

    2016-04-01

    Hydrological connectivity describes the physical coupling, or linkages of different elements within a landscape regarding (sub)surface flows. A firm understanding of hydrological connectivity is important for catchment management applications, for e.g. habitat and species protection, and for flood resistance and resilience improvement. Thinking about (geomorphological) systems as networks can lead to new insights, which has been recognised within the scientific community as well, seeing the recent increase in the use of network (graph) theory within the geosciences. Network theory supports the analysis and understanding of complex systems by providing data structures for modelling objects and their linkages, and a versatile toolbox to quantitatively appraise network structure and properties. The objective of this study was to characterise overland flow connectivity dynamics on hillslopes in a humid sub-Mediterranean environment by using a combination of high-resolution digital-terrain models, overland flow sensors and a network approach. Results showed that there are significant differences between overland flow on agricultural areas and semi-natural shrubs areas. Positive correlations between connectivity and precipitation characteristics were found, while negative correlations between connectivity and soil moisture were found, probably due to soil water repellency. The combination of a structural network to determine potential connectivity with dynamic networks to determine the actual connectivity proved a powerful tool in analysing overland flow connectivity.

  1. Meditation-State Functional Connectivity (msFC): Strengthening of the Dorsal Attention Network and Beyond

    OpenAIRE

    Brett Froeliger; Garland, Eric L.; Kozink, Rachel V.; Modlin, Leslie A.; Nan-Kuei Chen; F. Joseph McClernon; Greeson, Jeffrey M.; Paul Sobin

    2012-01-01

    Meditation practice alters intrinsic resting-state functional connectivity (rsFC) in the default mode network (DMN). However, little is known regarding the effects of meditation on other resting-state networks. The aim of current study was to investigate the effects of meditation experience and meditation-state functional connectivity (msFC) on multiple resting-state networks (RSNs). Meditation practitioners (MPs) performed two 5-minute scans, one during rest, one while meditating. A meditati...

  2. Optimal design of experiments on connected units with application to social networks

    OpenAIRE

    Parker, Ben M.; GILMOUR, Steven G.; Schormans, John Alexander

    2016-01-01

    When experiments are performed on social networks, it is difficult to justify the usual assumption of treatment-unit additivity, due to the connections between actors in the network. We investigate how connections between experimental units affect the design of experiments on those experimental units. Specifically, where we have unstructured treatments, whose effects propagate according to a linear network effects model which we introduce, we show that optimal designs are no longer necessaril...

  3. 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.

  4. Connecting the Dots: Understanding the Flow of Research Knowledge within a Research Brokering Network

    Science.gov (United States)

    Rodway, Joelle

    2015-01-01

    Networks are frequently cited as an important knowledge mobilization strategy; however, there is little empirical research that considers how they connect research and practice. Taking a social network perspective, I explore how central office personnel find, understand and share research knowledge within a research brokering network. This mixed…

  5. 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…

  6. 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.

  7. Optimizing the natural connectivity of scale-free networks using simulated annealing

    Science.gov (United States)

    Duan, Boping; Liu, Jing; Tang, Xianglong

    2016-09-01

    In real-world networks, the path between two nodes always plays a significant role in the fields of communication or transportation. In some cases, when one path fails, the two nodes cannot communicate any more. Thus, it is necessary to increase alternative paths between nodes. In the recent work (Wu et al., 2011), Wu et al. proposed the natural connectivity as a novel robustness measure of complex networks. The natural connectivity considers the redundancy of alternative paths in a network by computing the number of closed paths of all lengths. To enhance the robustness of networks in terms of the natural connectivity, in this paper, we propose a simulated annealing method to optimize the natural connectivity of scale-free networks without changing the degree distribution. The experimental results show that the simulated annealing method clearly outperforms other local search methods.

  8. 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.

  9. 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. PMID:26416398

  10. Anomalous Magnetohydrodynamics

    OpenAIRE

    Giovannini, Massimo

    2013-01-01

    Anomalous symmetries induce currents which can be parallel rather than orthogonal to the hypermagnetic field. Building on the analogy with charged liquids at high magnetic Reynolds numbers, the persistence of anomalous currents is scrutinized for parametrically large conductivities when the plasma approximation is accurate. Different examples in globally neutral systems suggest that the magnetic configurations minimizing the energy density with the constraint that the helicity be conserved co...

  11. 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. PMID:26869313

  12. Functional connectivity dynamics during film viewing reveal common networks for different emotional experiences.

    Science.gov (United States)

    Raz, Gal; Touroutoglou, Alexandra; Wilson-Mendenhall, Christine; Gilam, Gadi; Lin, Tamar; Gonen, Tal; Jacob, Yael; Atzil, Shir; Admon, Roee; Bleich-Cohen, Maya; Maron-Katz, Adi; Hendler, Talma; Barrett, Lisa Feldman

    2016-08-01

    Recent theoretical and empirical work has highlighted the role of domain-general, large-scale brain networks in generating emotional experiences. These networks are hypothesized to process aspects of emotional experiences that are not unique to a specific emotional category (e.g., "sadness," "happiness"), but rather that generalize across categories. In this article, we examined the dynamic interactions (i.e., changing cohesiveness) between specific domain-general networks across time while participants experienced various instances of sadness, fear, and anger. We used a novel method for probing the network connectivity dynamics between two salience networks and three amygdala-based networks. We hypothesized, and found, that the functional connectivity between these networks covaried with the intensity of different emotional experiences. Stronger connectivity between the dorsal salience network and the medial amygdala network was associated with more intense ratings of emotional experience across six different instances of the three emotion categories examined. Also, stronger connectivity between the dorsal salience network and the ventrolateral amygdala network was associated with more intense ratings of emotional experience across five out of the six different instances. Our findings demonstrate that a variety of emotional experiences are associated with dynamic interactions of domain-general neural systems. PMID:27142636

  13. 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

    2016-01-01

    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. PMID:26869313

  14. 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.

  15. Second-Order Consensus of Multiple Agents with Bounded Control Inputs and Preserved Network Connectivity

    Institute of Scientific and Technical Information of China (English)

    孙光甦

    2012-01-01

    This paper investigates second-order consensus of multi-agent systems with a virtual leader of varying velocity while preserving network connectivity.We propose a novel second-order consensus algorithm with bounded control inputs.Under the condition that the initial network is connected,the network will be connected all the time and all agents and the virtual leader can attain the same position and move with the same velocity.A simulation example is proposed to illustrate the effective of the proposed algorithm.

  16. 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...

  17. 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....

  18. 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...

  19. From Facilitated to Independent Tourism Learning Networks Connecting the Dots

    OpenAIRE

    Kelliher , Felicity; Reinl, Leana

    2010-01-01

    Facilitated networks are regularly cited in tourism literature as a means to promote sustainable competitive advantage in small tourism firms. These networks function for a variety of reasons including marketing, innovation and research and development; however learning networks specifically seek to encourage learning among tourism entrepreneurs. Once established, the question remains whether such networks can transition from facilitated cooperative learning strategies to become independent l...

  20. 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)

  1. Decreased Resting-State Connectivity between Neurocognitive Networks in Treatment Resistant Depression

    OpenAIRE

    Bart P de Kwaasteniet; Rive, Maria M; Ruhé, Henricus G; Aart H Schene; Veltman, Dick J.; Fellinger, Lisanne; van Wingen, Guido A.; Denys, Damiaan

    2015-01-01

    Approximately one-third of patients with major depressive disorder (MDD) do not achieve remission after various treatment options and develop treatment resistant depression (TRD). So far, little is known about the pathophysiology of TRD. Studies in MDD patients showed aberrant functional connectivity (FC) of three “core” neurocognitive networks: the salience network (SN), cognitive control network (CCN), and default mode network (DMN). We used a cross-sectional design and performed resting-st...

  2. 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.

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    Xin-Wei Gong

    Full Text Available 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.

  5. Altered network connectivity in frontotemporal dementia with C9orf72 hexanucleotide repeat expansion.

    Science.gov (United States)

    Lee, Suzee E; Khazenzon, Anna M; Trujillo, Andrew J; Guo, Christine C; Yokoyama, Jennifer S; Sha, Sharon J; Takada, Leonel T; Karydas, Anna M; Block, Nikolas R; Coppola, Giovanni; Pribadi, Mochtar; Geschwind, Daniel H; Rademakers, Rosa; Fong, Jamie C; Weiner, Michael W; Boxer, Adam L; Kramer, Joel H; Rosen, Howard J; Miller, Bruce L; Seeley, William W

    2014-11-01

    Hexanucleotide repeat expansion in C9orf72 represents the most common genetic cause of familial and sporadic behavioural variant frontotemporal dementia. Previous studies show that some C9orf72 carriers with behavioural variant frontotemporal dementia exhibit distinctive atrophy patterns whereas others show mild or undetectable atrophy despite severe behavioural impairment. To explore this observation, we examined intrinsic connectivity network integrity in patients with or without the C9orf72 expansion. We studied 28 patients with behavioural variant frontotemporal dementia, including 14 C9orf72 mutation carriers (age 58.3 ± 7.7 years, four females) and 14 non-carriers (age 60.8 ± 6.9 years, four females), and 14 age- and sex-matched healthy controls. Both patient groups included five patients with comorbid motor neuron disease. Neuropsychological data, structural brain magnetic resonance imaging, and task-free functional magnetic resonance imaging were obtained. Voxel-based morphometry delineated atrophy patterns, and seed-based intrinsic connectivity analyses enabled group comparisons of the salience, sensorimotor, and default mode networks. Single-patient analyses were used to explore network imaging as a potential biomarker. Despite contrasting atrophy patterns in C9orf72 carriers versus non-carriers, patient groups showed topographically similar connectivity reductions in the salience and sensorimotor networks. Patients without C9orf72 expansions exhibited increases in default mode network connectivity compared to controls and mutation carriers. Across all patients, behavioural symptom severity correlated with diminished salience network connectivity and heightened default mode network connectivity. In C9orf72 carriers, salience network connectivity reduction correlated with atrophy in the left medial pulvinar thalamic nucleus, and this region further showed diminished connectivity with key salience network hubs. Single-patient analyses revealed salience

  6. 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

  7. Default mode network connectivity as a function of familial and environmental risk for psychotic disorder.

    Directory of Open Access Journals (Sweden)

    Sanne C T Peeters

    Full Text Available Research suggests that altered interregional connectivity in specific networks, such as the default mode network (DMN, is associated with cognitive and psychotic symptoms in schizophrenia. In addition, frontal and limbic connectivity alterations have been associated with trauma, drug use and urban upbringing, though these environmental exposures have never been examined in relation to DMN functional connectivity in psychotic disorder.Resting-state functional MRI scans were obtained from 73 patients with psychotic disorder, 83 non-psychotic siblings of patients with psychotic disorder and 72 healthy controls. Posterior cingulate cortex (PCC seed-based correlation analysis was used to estimate functional connectivity within the DMN. DMN functional connectivity was examined in relation to group (familial risk, group × environmental exposure (to cannabis, developmental trauma and urbanicity and symptomatology.There was a significant association between group and PCC connectivity with the inferior parietal lobule (IPL, the precuneus (PCu and the medial prefrontal cortex (MPFC. Compared to controls, patients and siblings had increased PCC connectivity with the IPL, PCu and MPFC. In the IPL and PCu, the functional connectivity of siblings was intermediate to that of controls and patients. No significant associations were found between DMN connectivity and (subclinical psychotic/cognitive symptoms. In addition, there were no significant interactions between group and environmental exposures in the model of PCC functional connectivity.Increased functional connectivity in individuals with (increased risk for psychotic disorder may reflect trait-related network alterations. The within-network "connectivity at rest" intermediate phenotype was not associated with (subclinical psychotic or cognitive symptoms. The association between familial risk and DMN connectivity was not conditional on environmental exposure.

  8. 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.

  9. 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.

  10. Innovative applications of cars connectivity network – way to intelligent vehicle

    OpenAIRE

    Milan Kovac; Andrea Leskova

    2012-01-01

    The presented article focuses on characteristic of possibilities to use of ICT tools in automotive traffic. There are specified selected potentialities for a network connected to automotive integration in near future. There is also considerable innovation in the field of Internet-enabled in-car systems. In this contribution we want illustrating affects of Internet networking in automobiles by examples of applications. The goal is to present conceptual model of vehicle connected to external in...

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

    OpenAIRE

    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 ...

  12. 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...

  13. The Air Connectivity Index : Measuring Integration in the Global Air Transport Network

    OpenAIRE

    Arvis, Jean-François; Shepherd, Ben

    2011-01-01

    The authors construct a new measure of connectivity in the global air transport network, covering 211 countries and territories for the year 2007. It is grounded in network analysis methods, and is based on a gravity-like model that is familiar from the international trade and regional science literatures. It is a global measure of connectivity, in the sense that it captures the full range...

  14. 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. PMID:27445870

  15. 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. PMID:27445870

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Alterations of Resting State Functional Connectivity in the Default Network in Adolescents with Autism Spectrum Disorders

    OpenAIRE

    Weng, Shih-Jen; Wiggins, Jillian Lee; Peltier, Scott J.; Carrasco, Melisa; Risi, Susan; Lord, Catherine; Monk, Christopher S.

    2009-01-01

    Autism spectrum disorders (ASD) are associated with disturbances of neural connectivity. Functional connectivity between neural structures is typically examined within the context of a cognitive task, but also exists in the absence of a task (i.e., “rest”). Connectivity during rest is particularly active in a set of structures called the default network, which includes the posterior cingulate cortex (PCC), retrosplenial cortex, lateral parietal cortex/angular gyrus, medial prefrontal cortex, ...

  1. Neuroanatomy: connectome connects fly and mammalian brain networks.

    Science.gov (United States)

    Kaiser, Marcus

    2015-05-18

    A recent study shows that brain connectivity in Drosophila melanogaster follows a small-world, modular and rich-club organisation that facilitates information processing. This organisation shows a striking similarity with the mammalian brain. PMID:25989081

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

    Science.gov (United States)

    Fallon, Nicholas; 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

  3. 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

  4. Network performance, hub connectivity potential, and competitive position of primary airports in Asia/Pacific region

    NARCIS (Netherlands)

    H. Matsumoto; J. Veldhuis; J. de Wit; G. Burghouwt

    2008-01-01

    Recently, hub-and-spoke network configurations are more and more developed in the Asia/Pacific region. In this paper, it is argued that the measurement of network performance in hub-and-spoke systems should take into account the quantity and quality of both direct and indirect connections. The NetSc

  5. Demographic Diversity as Network Connections: Homophily and the Diversity-Performance Debate

    OpenAIRE

    Reagans, Ray Eugene

    2012-01-01

    Research documenting the influence of demopraphic diversity on informal social networks is reviewed and critiqued. I focus in particular on research describing the importance of demographic diversity in the development of strong interpersonal relationships. I also consider the importance of network connections between team members and with colleagues outside the team in mediating the association between demographic diversity and team performance.

  6. Aberrant Resting-State Functional Connectivity in the Salience Network of Adolescent Chronic Fatigue Syndrome

    Science.gov (United States)

    Endestad, Tor; Melinder, Annika Maria D.; Øie, Merete Glenne; Sevenius, Andre; Bruun Wyller, Vegard

    2016-01-01

    Neural network investigations are currently absent in adolescent chronic fatigue syndrome (CFS). In this study, we examine whether the core intrinsic connectivity networks (ICNs) are altered in adolescent CFS patients. Eighteen adolescent patients with CFS and 18 aged matched healthy adolescent control subjects underwent resting-state functional magnetic resonance imaging (rfMRI). Data was analyzed using dual-regression independent components analysis, which is a data-driven approach for the identification of independent brain networks. Intrinsic connectivity was evaluated in the default mode network (DMN), salience network (SN), and central executive network (CEN). Associations between network characteristics and symptoms of CFS were also explored. Adolescent CFS patients displayed a significant decrease in SN functional connectivity to the right posterior insula compared to healthy comparison participants, which was related to fatigue symptoms. Additionally, there was an association between pain intensity and SN functional connectivity to the left middle insula and caudate that differed between adolescent patients and healthy comparison participants. Our findings of insula dysfunction and its association with fatigue severity and pain intensity in adolescent CFS demonstrate an aberration of the salience network which might play a role in CFS pathophysiology. PMID:27414048

  7. 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.

  8. 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.].

  9. 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.].

  10. Niche partitioning due to adaptive foraging reverses effects of nestedness and connectance on pollination network stability.

    Science.gov (United States)

    Valdovinos, Fernanda S; Brosi, Berry J; Briggs, Heather M; Moisset de Espanés, Pablo; Ramos-Jiliberto, Rodrigo; Martinez, Neo D

    2016-10-01

    Much research debates whether properties of ecological networks such as nestedness and connectance stabilise biological communities while ignoring key behavioural aspects of organisms within these networks. Here, we computationally assess how adaptive foraging (AF) behaviour interacts with network architecture to determine the stability of plant-pollinator networks. We find that AF reverses negative effects of nestedness and positive effects of connectance on the stability of the networks by partitioning the niches among species within guilds. This behaviour enables generalist pollinators to preferentially forage on the most specialised of their plant partners which increases the pollination services to specialist plants and cedes the resources of generalist plants to specialist pollinators. We corroborate these behavioural preferences with intensive field observations of bee foraging. Our results show that incorporating key organismal behaviours with well-known biological mechanisms such as consumer-resource interactions into the analysis of ecological networks may greatly improve our understanding of complex ecosystems. PMID:27600659

  11. 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.

  12. 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

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

    Science.gov (United States)

    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.

  14. 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. PMID:26869896

  15. 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.

  16. 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...

  17. Focusing on connected personal leisure networks: selected results from a snowball sample

    OpenAIRE

    Matthias Kowald; Axhausen, Kay W.

    2012-01-01

    Abstract. Explanations of leisure travel must take the influence of participants’ social contacts into account. To analyze this influence, transport planning uses social network analysis methods. While most past projects have focused on isolated network components, this paper presents a study collecting data on connected personal networks by taking a snowball sample. The paper explains difficulties for transport planning in approaching and explaining leisure travel and then introduces both th...

  18. Connected Spatial Networks over Random Points and a Route-Length Statistic

    OpenAIRE

    Aldous, David J.; Shun, Julian

    2010-01-01

    We review mathematically tractable models for connected networks on random points in the plane, emphasizing the class of proximity graphs which deserves to be better known to applied probabilists and statisticians. We introduce and motivate a particular statistic $R$ measuring shortness of routes in a network. We illustrate, via Monte Carlo in part, the trade-off between normalized network length and $R$ in a one-parameter family of proximity graphs. How close this family comes to the optimal...

  19. Mapping Thalamocortical Networks in Rat Brain using Resting-State Functional Connectivity

    OpenAIRE

    Liang, Zhifeng; Li, Tao; King, Jean; Zhang, Nanyin

    2013-01-01

    Thalamocortical connectivity plays a vital role in brain function. The anatomy and function of thalamocortical networks have been extensively studied in animals by numerous invasive techniques. Non-invasively mapping thalamocortical networks in humans has also been demonstrated by utilizing resting-state functional magnetic resonance imaging (rsfMRI). However, success in simultaneously imaging multiple thalamocortical networks in animals is rather limited. This is largely due to the profound ...

  20. Bridges over troubled water: suppliers as connective nodes in global supply networks

    DEFF Research Database (Denmark)

    Christensen, Poul Rind; Andersen, Poul Houman

    2005-01-01

    Increasingly, industrial selling and purchasing is embedded in supplier networks extending national borders. The internationalisation of supply activities adds considerable complexity to the coordination tasks performed by suppliers. Traditionally, supply chain management was upstream......-oriented, focusing on the leading contractor's supply chain management. However, the increased demand for flexibility echoes down in supply network, decentralising the coordination task. We focus on subcontractors as connective nodes in supply networks and outline how coordinative roles are linked to the diversity...

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Innovative applications of cars connectivity network – way to intelligent vehicle

    Directory of Open Access Journals (Sweden)

    Milan Kovac

    2012-10-01

    Full Text Available The presented article focuses on characteristic of possibilities to use of ICT tools in automotive traffic. There are specified selected potentialities for a network connected to automotive integration in near future. There is also considerable innovation in the field of Internet-enabled in-car systems. In this contribution we want illustrating affects of Internet networking in automobiles by examples of applications. The goal is to present conceptual model of vehicle connected to external interfaces. Subject of article covered the tendencies in the development of the specific application in automotive sector. Objectives is an increased public perception and customer acceptance of cars network systems which is suitable for multiple application domains – external connectivity, networking, security, diagnosis, integrated safety management etc.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

    2015-01-01

    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

  10. 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.

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

    OpenAIRE

    Hala ElAarag; David Bauschlicher; Steven Bauschlicher

    2013-01-01

    Over the last decade, the demand for efficient healthcare monitoring has increased and forced the health and wellness industry to embrace modern technological advances. Body Sensor Networks, or BSNs, can remotely collect users data and upload vital statistics to servers over the Internet. Advances in wireless technologies such as cellular devices and Bluetooth increase the mobility users experience while wearing a body sensor network. When connected by the proper framework, BSNs can efficient...

  12. Spreading dynamics on small-world networks with connectivity fluctuations and correlations

    Science.gov (United States)

    Vazquez, Alexei

    2006-11-01

    Infectious diseases and computer malwares spread among humans and computers through the network of contacts among them. These networks are characterized by wide connectivity fluctuations, connectivity correlations, and the small-world property. In a previous work [Phys. Rev. Lett. 96, 038702 (2006)] I have shown that the connectivity fluctuations together with the small-world property lead to a spreading law characterized by an initial power law growth with an exponent determined by the average node distance on the network. Here I extend these results to consider the influence of connectivity correlations which are generally observed in real networks. I show that assortative and disassortative connectivity correlations enhance and diminish, respectively, the range of validity of this spreading law. As a corollary I obtain the region of connectivity fluctuations and degree correlations characterized by the absence of an epidemic threshold. These results are relevant for the spreading of infectious diseases, rumors, and information among humans and the spreading of computer viruses, email worms, and hoaxes among computer users.

  13. 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.

  14. 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.

  15. Tracking Topology Dynamicity for Link Prediction in Intermittently Connected Wireless Networks

    CERN Document Server

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

    2012-01-01

    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. We attest that the tensor-based technique is effective for temporal link prediction applied to the intermittently connected networks. The validity of this method is proved when the prediction is made in a distributed way (i.e. with local information) and its performance is compared to well-known link prediction metrics proposed in the literature.

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

    International Nuclear Information System (INIS)

    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.)

  18. 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.)

  19. 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. PMID:27442678

  20. 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.

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

    Science.gov (United States)

    Berkovich-Ohana, Aviva; Harel, Michal; Hahamy, Avital; Arieli, Amos; Malach, Rafael

    2016-09-01

    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. PMID:27508242

  2. 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.

  3. 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

  4. 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.

  5. Exploring Functional Connectivity Networks with Multichannel Brain Array Coils

    OpenAIRE

    Anteraper, Sheeba Arnold; Keil, Boris; Triantafyllou, Christina; Gabrieli, Susan; Shannon, Steven P.; Gabrieli, John D.E.

    2013-01-01

    The use of multichannel array head coils in functional and structural magnetic resonance imaging (MRI) provides increased signal-to-noise ratio (SNR), higher sensitivity, and parallel imaging capabilities. However, their benefits remain to be systematically explored in the context of resting-state functional connectivity MRI (fcMRI). In this study, we compare signal detectability within and between commercially available multichannel brain coils, a 32-Channel (32Ch), and a 12-Channel (12Ch) a...

  6. A Connected Enterprise - Transformation through Mobility and Social Networks

    OpenAIRE

    Jitendra Maan

    2012-01-01

    Due to rapid changes in business dynamics, there is a growing demand to encourage social conversations/exchanges and the ability to connect and communicate with peers, partners, customers andother stakeholders anytime, anywhere which drives the need of mobile-enable, the existing enterprise applications. This paper highlights a distinct set of needs and key customer challenges that must be considered and addressed for deployment of Social Collaboration applications and Mobility services in en...

  7. Distributed generation connected to the local network - a guide

    International Nuclear Information System (INIS)

    This guide provides advice to the developers and operators of small distributed generation plant (including microgenerators) in the UK about the practical issues associated with connecting their plant and trading their output. Particular attention is given to sales revenues and how to access these revenue streams, including the mechanisms for purchasing Renewable Obligation Certificates (ROCs). The guide clarifies key terms, explains the wholesale trading system and provides an overview of sales opportunities (including ROCs and Levy Exemption Certificates (LECs)). Requirements on small distributed generation (including licensing, claiming class exemptions and metering) are described and the commercial aspects of connection (including the recent reduction in the barriers to connection) examined. Microgeneration (ie generators below 10 kW) issues are covered in their own chapter. The six appendices contain: background information about the industry; a list of purchasers of electricity from small distributed generators; descriptions of the generation, transmission and supply industries; information about industry standards and their governance; the role of government departments and institutions; and a glossary and other links

  8. 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.

  9. Identifying effective guaranteed connections in a multimodal public transport network

    NARCIS (Netherlands)

    Sparing, D.; Goverde, R.M.P.

    2012-01-01

    Minimizing transfer waiting time is important in making public transport networks more attractive. A guaranteed transfer, with the departing vehicle waiting on moderately delayed arriving vehicles at a transfer node, is an effective way to reduce waiting times at transfers between low frequency publ

  10. Identifying effective guaranteed connections in a multimodal network

    NARCIS (Netherlands)

    Sparing, D.; Goverde, R.M.P.

    2012-01-01

    Minimizing transfer waiting time is important in making public transport networks more attractive. A guaranteed transfer, with the departing vehicle waiting on moderately delayed arriving vehicles at a transfer node, is an effective way to reduce waiting times at transfers between low frequency publ

  11. Connecting the dots in Huntington's disease with protein interaction networks

    OpenAIRE

    Giorgini, Flaviano; Muchowski, Paul J.

    2005-01-01

    Analysis of protein-protein interaction networks is becoming important for inferring the function of uncharacterized proteins. A recent study using this approach has identified new proteins and interactions that might be involved in the pathogenesis of the neurodegenerative disorder Huntington's disease, including a GTPase-activating protein that co-localizes with protein aggregates in Huntington's disease patients.

  12. 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 plarge-scale networks may contribute to individual responsivity to exercise. PMID:26921099

  13. 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.

  14. 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.

  15. Automatic Generation of Connectivity for Large-Scale Neuronal Network Models through Structural Plasticity.

    Science.gov (United States)

    Diaz-Pier, Sandra; Naveau, Mikaël; Butz-Ostendorf, Markus; Morrison, Abigail

    2016-01-01

    With the emergence of new high performance computation technology in the last decade, the simulation of large scale neural networks which are able to reproduce the behavior and structure of the brain has finally become an achievable target of neuroscience. Due to the number of synaptic connections between neurons and the complexity of biological networks, most contemporary models have manually defined or static connectivity. However, it is expected that modeling the dynamic generation and deletion of the links among neurons, locally and between different regions of the brain, is crucial to unravel important mechanisms associated with learning, memory and healing. Moreover, for many neural circuits that could potentially be modeled, activity data is more readily and reliably available than connectivity data. Thus, a framework that enables networks to wire themselves on the basis of specified activity targets can be of great value in specifying network models where connectivity data is incomplete or has large error margins. To address these issues, in the present work we present an implementation of a model of structural plasticity in the neural network simulator NEST. In this model, synapses consist of two parts, a pre- and a post-synaptic element. Synapses are created and deleted during the execution of the simulation following local homeostatic rules until a mean level of electrical activity is reached in the network. We assess the scalability of the implementation in order to evaluate its potential usage in the self generation of connectivity of large scale networks. We show and discuss the results of simulations on simple two population networks and more complex models of the cortical microcircuit involving 8 populations and 4 layers using the new framework. PMID:27303272

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. Connectivity correlations in three topological spaces of urban bus-transport networks in China

    Institute of Scientific and Technical Information of China (English)

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

    2008-01-01

    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,(Kw nn(k))Knn(k),and k,and the other is the correlations between the aesortativity 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.

  1. 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 ...

  2. 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.

  3. 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.

  4. Partitioning Biological Networks into Highly Connected Clusters with Maximum Edge Coverage.

    Science.gov (United States)

    Hüffner, Falk; Komusiewicz, Christian; Liebtrau, Adrian; Niedermeier, Rolf

    2014-01-01

    A popular clustering algorithm for biological networks which was proposed by Hartuv and Shamir identifies nonoverlapping highly connected components. We extend the approach taken by this algorithm by introducing the combinatorial optimization problem Highly Connected Deletion, which asks for removing as few edges as possible from a graph such that the resulting graph consists of highly connected components. We show that Highly Connected Deletion is NP-hard and provide a fixed-parameter algorithm and a kernelization. We propose exact and heuristic solution strategies, based on polynomial-time data reduction rules and integer linear programming with column generation. The data reduction typically identifies 75 percent of the edges that are deleted for an optimal solution; the column generation method can then optimally solve protein interaction networks with up to 6,000 vertices and 13,500 edges within five hours. Additionally, we present a new heuristic that finds more clusters than the method by Hartuv and Shamir. PMID:26356014

  5. 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.

  6. Graph theoretical analysis of structural and functional connectivity MRI in normal and pathological brain networks.

    Science.gov (United States)

    Guye, Maxime; Bettus, Gaelle; Bartolomei, Fabrice; Cozzone, Patrick J

    2010-12-01

    Graph theoretical analysis of structural and functional connectivity MRI data (ie. diffusion tractography or cortical volume correlation and resting-state or task-related (effective) fMRI, respectively) has provided new measures of human brain organization in vivo. The most striking discovery is that the whole-brain network exhibits "small-world" properties shared with many other complex systems (social, technological, information, biological). This topology allows a high efficiency at different spatial and temporal scale with a very low wiring and energy cost. Its modular organization also allows for a high level of adaptation. In addition, degree distribution of brain networks demonstrates highly connected hubs that are crucial for the whole-network functioning. Many of these hubs have been identified in regions previously defined as belonging to the default-mode network (potentially explaining the high basal metabolism of this network) and the attentional networks. This could explain the crucial role of these hub regions in physiology (task-related fMRI data) as well as in pathophysiology. Indeed, such topological definition provides a reliable framework for predicting behavioral consequences of focal or multifocal lesions such as stroke, tumors or multiple sclerosis. It also brings new insights into a better understanding of pathophysiology of many neurological or psychiatric diseases affecting specific local or global brain networks such as epilepsy, Alzheimer's disease or schizophrenia. Graph theoretical analysis of connectivity MRI data provides an outstanding framework to merge anatomical and functional data in order to better understand brain pathologies. PMID:20349109

  7. 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.

  8. 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

  9. Fault-Tolerant Algorithms for Connectivity Restoration in Wireless Sensor Networks.

    Science.gov (United States)

    Zeng, Yali; Xu, Li; Chen, Zhide

    2015-01-01

    As wireless sensor network (WSN) is often deployed in a hostile environment, nodes in the networks are prone to large-scale failures, resulting in the network not working normally. In this case, an effective restoration scheme is needed to restore the faulty network timely. Most of existing restoration schemes consider more about the number of deployed nodes or fault tolerance alone, but fail to take into account the fact that network coverage and topology quality are also important to a network. To address this issue, we present two algorithms named Full 2-Connectivity Restoration Algorithm (F2CRA) and Partial 3-Connectivity Restoration Algorithm (P3CRA), which restore a faulty WSN in different aspects. F2CRA constructs the fan-shaped topology structure to reduce the number of deployed nodes, while P3CRA constructs the dual-ring topology structure to improve the fault tolerance of the network. F2CRA is suitable when the restoration cost is given the priority, and P3CRA is suitable when the network quality is considered first. Compared with other algorithms, these two algorithms ensure that the network has stronger fault-tolerant function, larger coverage area and better balanced load after the restoration. PMID:26703616

  10. 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.

  11. Axon and dendrite geography predict the specificity of synaptic connections in a functioning spinal cord network

    OpenAIRE

    Borisyuk Roman; Soffe Stephen R; Sautois Bart; Cooke Tom; Li Wen-Chang; Roberts Alan

    2007-01-01

    Abstract Background How specific are the synaptic connections formed as neuronal networks develop and can simple rules account for the formation of functioning circuits? These questions are assessed in the spinal circuits controlling swimming in hatchling frog tadpoles. This is possible because detailed information is now available on the identity and synaptic connections of the main types of neuron. Results The probabilities of synapses between 7 types of identified spinal neuron were measur...

  12. Spanning connectivity in a multilayer network and its relationship to site-bond percolation

    Science.gov (United States)

    Guha, Saikat; Towsley, Donald; Nain, Philippe; ćapar, ćaǧatay; Swami, Ananthram; Basu, Prithwish

    2016-06-01

    We analyze the connectivity of an M -layer network over a common set of nodes that are active only in a fraction of the layers. Each layer is assumed to be a subgraph (of an underlying connectivity graph G ) induced by each node being active in any given layer with probability q . The M -layer network is formed by aggregating the edges over all M layers. We show that when q exceeds a threshold qc(M ) , a giant connected component appears in the M -layer network—thereby enabling far-away users to connect using "bridge" nodes that are active in multiple network layers—even though the individual layers may only have small disconnected islands of connectivity. We show that qc(M ) ≲√{-ln(1 -pc) }/√{M } , where pc is the bond percolation threshold of G , and qc(1 ) ≡qc is its site-percolation threshold. We find qc(M ) exactly for when G is a large random network with an arbitrary node-degree distribution. We find qc(M ) numerically for various regular lattices and find an exact lower bound for the kagome lattice. Finally, we find an intriguingly close connection between this multilayer percolation model and the well-studied problem of site-bond percolation in the sense that both models provide a smooth transition between the traditional site- and bond-percolation models. Using this connection, we translate known analytical approximations of the site-bond critical region, which are functions only of pc and qc of the respective lattice, to excellent general approximations of the multilayer connectivity threshold qc(M ) .

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states.

    Science.gov (United States)

    Dao Duc, Khanh; Parutto, Pierre; Chen, Xiaowei; Epsztein, Jérôme; Konnerth, Arthur; Holcman, David

    2015-01-01

    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 time 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. PMID:26283956

  1. 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.

  2. 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.

  3. Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients

    OpenAIRE

    Assaf, Michal; Jagannathan, Kanchana; Calhoun, Vince D.; Miller, Laura; Stevens, Michael C.; Sahl, Robert; O'Boyle, Jacqueline G.; Schultz, Robert T.; Godfrey D. Pearlson

    2010-01-01

    Autism spectrum disorders (ASDs) are characterized by deficits in social and communication processes. Recent data suggest that altered functional connectivity (FC), i.e. synchronous brain activity, might contribute to these deficits. Of specific interest is the FC integrity of the default mode network (DMN), a network active during passive resting states and cognitive processes related to social deficits seen in ASD, e.g. Theory of Mind. We investigated the role of altered FC of default mode ...

  4. The connection between culture, business networks and SME internationalization; an example from Japan

    OpenAIRE

    Häkälä, I.-L. (Inka-Liisa)

    2015-01-01

    This study takes an example from Japan into the connection between culture, business networks and SME internationalization. This is divided into two parts, a literature review and six (N=6) face-to-face semi-structured expert interviews with Japanese SME internationalization experts. The literature review finds that there is a consensus in the field that business networks generally increase the propensity and success of SME internationalization. Culture is also found to have a clear impact in...

  5. Relay Protection Coordination for Photovoltaic Power Plant Connected on Distribution Network

    OpenAIRE

    Nikolovski, Srete; Papuga, Vanja; Knežević, Goran

    2014-01-01

    This paper presents a procedure and computation of relay protection coordination for a PV power plant connected to the distribution network. In recent years, the growing concern for environment preservation has caused expansion of photovoltaic PV power plants in distribution networks. Numerical computer simulation is an indispensable tool for studying photovoltaic (PV) systems protection coordination. In this paper, EasyPower computer program is used with the module Power Protector. Time-curr...

  6. Connecting Spiking Neurons to a Spiking Memristor Network Changes the Memristor Dynamics

    OpenAIRE

    Gater, Deborah; Iqbal, Attya; Davey, Jeffrey; Gale, Ella

    2014-01-01

    Memristors have been suggested as neuromorphic computing elements. Spike-time dependent plasticity and the Hodgkin-Huxley model of the neuron have both been modelled effectively by memristor theory. The d.c. response of the memristor is a current spike. Based on these three facts we suggest that memristors are well-placed to interface directly with neurons. In this paper we show that connecting a spiking memristor network to spiking neuronal cells causes a change in the memristor network dyna...

  7. Model for simulating mechanisms responsible of similarities between people connected in networks of social relations

    OpenAIRE

    Zak, Blazej; Zbieg, Anita

    2014-01-01

    It the literature have been identified three social mechanisms explaining the similarity between people connected in the network of social relations homophily, confounding and social contagion. The article proposes a simple model for simulating mechanisms responsible for similarity of attitudes in networks of social relations; along with a measure that is able to indicate which of the three mechanisms has taken major role in the process.

  8. Functional connectivity analysis of resting-state fMRI networks in nicotine dependent patients

    Science.gov (United States)

    Smith, Aria; Ehtemami, Anahid; Fratte, Daniel; Meyer-Baese, Anke; Zavala-Romero, Olmo; Goudriaan, Anna E.; Schmaal, Lianne; Schulte, Mieke H. J.

    2016-03-01

    Brain imaging studies identified brain networks that play a key role in nicotine dependence-related behavior. Functional connectivity of the brain is dynamic; it changes over time due to different causes such as learning, or quitting a habit. Functional connectivity analysis is useful in discovering and comparing patterns between functional magnetic resonance imaging (fMRI) scans of patients' brains. In the resting state, the patient is asked to remain calm and not do any task to minimize the contribution of external stimuli. The study of resting-state fMRI networks have shown functionally connected brain regions that have a high level of activity during this state. In this project, we are interested in the relationship between these functionally connected brain regions to identify nicotine dependent patients, who underwent a smoking cessation treatment. Our approach is on the comparison of the set of connections between the fMRI scans before and after treatment. We applied support vector machines, a machine learning technique, to classify patients based on receiving the treatment or the placebo. Using the functional connectivity (CONN) toolbox, we were able to form a correlation matrix based on the functional connectivity between different regions of the brain. The experimental results show that there is inadequate predictive information to classify nicotine dependent patients using the SVM classifier. We propose other classification methods be explored to better classify the nicotine dependent patients.

  9. 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.

  10. Transferring learning from external to internal weights in echo-state networks with sparse connectivity.

    Science.gov (United States)

    Sussillo, David; Abbott, L F

    2012-01-01

    Modifying weights within a recurrent network to improve performance on a task has proven to be difficult. Echo-state networks in which modification is restricted to the weights of connections onto network outputs provide an easier alternative, but at the expense of modifying the typically sparse architecture of the network by including feedback from the output back into the network. We derive methods for using the values of the output weights from a trained echo-state network to set recurrent weights within the network. The result of this "transfer of learning" is a recurrent network that performs the task without requiring the output feedback present in the original network. We also discuss a hybrid version in which online learning is applied to both output and recurrent weights. Both approaches provide efficient ways of training recurrent networks to perform complex tasks. Through an analysis of the conditions required to make transfer of learning work, we define the concept of a "self-sensing" network state, and we compare and contrast this with compressed sensing. PMID:22655041

  11. Transferring learning from external to internal weights in echo-state networks with sparse connectivity.

    Directory of Open Access Journals (Sweden)

    David Sussillo

    Full Text Available Modifying weights within a recurrent network to improve performance on a task has proven to be difficult. Echo-state networks in which modification is restricted to the weights of connections onto network outputs provide an easier alternative, but at the expense of modifying the typically sparse architecture of the network by including feedback from the output back into the network. We derive methods for using the values of the output weights from a trained echo-state network to set recurrent weights within the network. The result of this "transfer of learning" is a recurrent network that performs the task without requiring the output feedback present in the original network. We also discuss a hybrid version in which online learning is applied to both output and recurrent weights. Both approaches provide efficient ways of training recurrent networks to perform complex tasks. Through an analysis of the conditions required to make transfer of learning work, we define the concept of a "self-sensing" network state, and we compare and contrast this with compressed sensing.

  12. 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.

  13. 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

  14. Clinical Application of EBCT in the Diagnosis of Anomalous Pulmonary Venous Connection%电子束CT在肺静脉异常连接诊断中的临床价值

    Institute of Scientific and Technical Information of China (English)

    杨有优; 孟悛非; 戴汝平; 荆宝莲; 何沙; 白桦

    2001-01-01

    Objective To investigate the clinical usefulness of electron beam computed tomography (EBCT) in the diagnosis of anomalous pulmonary venous connection. Materials and Methods Anomalous pulmonary venous connection was diagnosed with EBCT in 21 patients, including 13 males and 8 females and aged 3~63 years (mean 15.6 years). Contrast-enhanced single-slice scanning was performed in 17 patients, and contrast-enhanced continuos volume scanning in 4 patients. Shaded surface display was done for 3D reconstruction in all patients. Both angiocardiographic and operative outcomes were obtained in 4 patients, while only angiocardiographic results in 9, only operative results in 4. Results Of the 20 patients received EBCT before operation, partial anomalous pulmonary venous connection was diagnosed in 8, and total anomalous pulmonary venous connection in 12, including supracardiac type (n=3), cardiac type (n=8) and mixed type (n=1). EBCT clearly displayed the number, distribution and location of anomalous pulmonary venous connection in all patients. The diagnosis by EBCT was compatible with the operative results in all the 8 patients receiving surgery. EBCT revealed a stenosis of anastomotic stoma in 1 patient after surgery, as well as the syndrome of visceroatrial heterotaxia in 7 patients with total anomalous pulmonary venous connection.  Conclusion EBCT with 3D reconstruction can detect not only the number, distribution, connective location and postoperative stenosis of anomalous pulmonary venous connection, but also the thoracic and abdominal complicated lesions such as the syndrome of visceroatrial heterotaxia. It is a noninvasive method with high accuracy for the diagnosis of anomalous pulmonary venous connection.%目的探讨电子束CT(EBCT)在肺静脉异常连接诊断中的临床价值。材料与方法 EBCT诊断肺静脉异常连接患者21例,其中男13例,女8例。年龄3~63岁,平均15.6岁。17例行增强单层容积扫描,4例行

  15. The Semantic Network at Work and Rest: Differential Connectivity of Anterior Temporal Lobe Subregions

    Science.gov (United States)

    Jackson, Rebecca L.; Hoffman, Paul; Pobric, Gorana

    2016-01-01

    The anterior temporal lobe (ATL) makes a critical contribution to semantic cognition. However, the functional connectivity of the ATL and the functional network underlying semantic cognition has not been elucidated. In addition, subregions of the ATL have distinct functional properties and thus the potential differential connectivity between these subregions requires investigation. We explored these aims using both resting-state and active semantic task data in humans in combination with a dual-echo gradient echo planar imaging (EPI) paradigm designed to ensure signal throughout the ATL. In the resting-state analysis, the ventral ATL (vATL) and anterior middle temporal gyrus (MTG) were shown to connect to areas responsible for multimodal semantic cognition, including bilateral ATL, inferior frontal gyrus, medial prefrontal cortex, angular gyrus, posterior MTG, and medial temporal lobes. In contrast, the anterior superior temporal gyrus (STG)/superior temporal sulcus was connected to a distinct set of auditory and language-related areas, including bilateral STG, precentral and postcentral gyri, supplementary motor area, supramarginal gyrus, posterior temporal cortex, and inferior and middle frontal gyri. Complementary analyses of functional connectivity during an active semantic task were performed using a psychophysiological interaction (PPI) analysis. The PPI analysis highlighted the same semantic regions suggesting a core semantic network active during rest and task states. This supports the necessity for semantic cognition in internal processes occurring during rest. The PPI analysis showed additional connectivity of the vATL to regions of occipital and frontal cortex. These areas strongly overlap with regions found to be sensitive to executively demanding, controlled semantic processing. SIGNIFICANCE STATEMENT Previous studies have shown that semantic cognition depends on subregions of the anterior temporal lobe (ATL). However, the network of regions

  16. Optimizing network connectivity for mobile health technologies in sub-Saharan Africa.

    Directory of Open Access Journals (Sweden)

    Mark J Siedner

    Full Text Available Mobile health (mHealth technologies hold incredible promise to improve healthcare delivery in resource-limited settings. Network reliability across large catchment areas can be a major challenge. We performed an analysis of network failure frequency as part of a study of real-time adherence monitoring in rural Uganda. We hypothesized that the addition of short messaging service (SMS+GPRS to the standard cellular network modality (GPRS would reduce network disruptions and improve transmission of data.Participants were enrolled in a study of real-time adherence monitoring in southwest Uganda. In June 2011, we began using Wisepill devices that transmit data each time the pill bottle is opened. We defined network failures as medication interruptions of >48 hours duration that were transmitted when network connectivity was re-established. During the course of the study, we upgraded devices from GPRS to GPRS+SMS compatibility. We compared network failure rates between GPRS and GPRS+SMS periods and created geospatial maps to graphically demonstrate patterns of connectivity.One hundred fifty-seven participants met inclusion criteria of seven days of SMS and seven days of SMS+GPRS observation time. Seventy-three percent were female, median age was 40 years (IQR 33-46, 39% reported >1-hour travel time to clinic and 17% had home electricity. One hundred one had GPS coordinates recorded and were included in the geospatial maps. The median number of network failures per person-month for the GPRS and GPRS+SMS modalities were 1.5 (IQR 1.0-2.2 and 0.3 (IQR 0-0.9 respectively, (mean difference 1.2, 95%CI 1.0-1.3, p-value<0.0001. Improvements in network connectivity were notable throughout the region. Study costs increased by approximately $1USD per person-month.Addition of SMS to standard GPRS cellular network connectivity can significantly reduce network connection failures for mobile health applications in remote areas. Projects depending on mobile health data

  17. Synchronization in Small-World-Connected Computer Networks

    CERN Document Server

    Guclu, H

    2006-01-01

    In this thesis we study synchronization phenomena in natural and artificial coupled multi-component systems, applicable to the scalability of parallel discrete-event simulation for systems with asynchronous dynamics. We analyze the properties of the virtual time horizon or synchronization landscape (corresponding to the progress of the processing elements) of these networks by using the framework of non-equilibrium surface growth. When the communication topology mimics that of the short-range interacting underlying system, the virtual time horizon exhibits Kardar-Parisi-Zhang-like kinetic roughening. Although the virtual times, on average, progress at a nonzero rate, their statistical spread diverges with the number of processing elements, hindering efficient data collection. We show that when the synchronization topology is extended to include quenched random communication links (small-world links) between the processing elements, they make a close-to-uniform progress with a nonzero rate, without global sync...

  18. 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.

  19. Silence is Golden with High Probability: Maintaining a Connected Backbone in Wireless Sensor Networks

    OpenAIRE

    Santi, Paolo; Simon, J?nos

    2003-01-01

    Reducing node energy consumption to extend network life- time is a vital requirement in wireless sensor networks. In this paper, we present and analyze the energy consumption of a class of cell-based energy conservation protocols. The goal of our protocols is to alternately turn off/on the transceivers of the nodes, while maintaining a connected backbone of active nodes. The protocols presented in this paper are shown to be optimal, in the sense that they extend the network lifetime by a fact...

  20. 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.

  1. Frontoparietal Connectivity and Hierarchical Structure of the Brain’s Functional Network during Sleep

    Directory of Open Access Journals (Sweden)

    Victor I Spoormaker

    2012-05-01

    Full Text Available Frontal and parietal regions are associated with some of the most complex cognitive functions, and several frontoparietal resting-state networks can be observed in wakefulness. We used functional magnetic resonance imaging (fMRI data acquired in polysomnographically validated wakefulness, light sleep and slow-wave sleep to examine the hierarchical structure of a low-frequency functional brain network, and to examine whether frontoparietal connectivity would disintegrate in sleep. Whole-brain analyses with hierarchical cluster analysis on predefined atlases were performed, as well as regression of inferior parietal lobules seeds against all voxels in the brain, and an evaluation of the integrity of voxel time-courses in subcortical regions-of-interest. We observed that frontoparietal functional connectivity disintegrated in sleep stage 1 and was absent in deeper sleep stages. Slow-wave sleep was characterized by strong hierarchical clustering of local submodules. Frontoparietal connectivity between inferior parietal lobules and superior medial and right frontal gyrus was lower in sleep stages than in wakefulness. Moreover, thalamus voxels showed maintained integrity in sleep stage 1, making intrathalamic desynchronization an unlikely source of reduced thalamocortical connectivity in this sleep stage. Our data suggest a transition from a globally integrated functional brain network in wakefulness to a disintegrated network consisting of local submodules in slow-wave sleep, in which frontoparietal inter-modular nodes may play a crucial role, possibly in combination with the thalamus.

  2. 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.

  3. 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

  4. Complexity of functional connectivity networks in mild cognitive impairment subjects during a working memory task

    NARCIS (Netherlands)

    Ahmadlou, M; Adeli, Anahita; Bajo, Ricardo; Adeli, Hojjat

    2014-01-01

    OBJECTIVES: The objective is to study the changes of brain activity in patients with mild cognitive impairment (MCI). Using magneto-encephalogram (MEG) signals, the authors investigate differences of complexity of functional connectivity network between MCI and normal elderly subjects during a worki

  5. The Linked Classroom as Studio: Connectivity and the Etymology of Networks.

    Science.gov (United States)

    Badaracco, Claire Hoertz

    2002-01-01

    Notes that a developing multimedia network to connect three campuses allowed students in a Media, Religion and Cultural Identity course, national spokespersons, editors, and journalists to discuss the role of mediated religion, its impact on public opinion and on popular culture. Considers how a learning community was created. Argues for…

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. FMRI connectivity analysis of acupuncture effects on an amygdala-associated brain network

    Directory of Open Access Journals (Sweden)

    Zhao Baixiao

    2008-11-01

    Full Text Available Abstract Background Recently, increasing evidence has indicated that the primary acupuncture effects are mediated by the central nervous system. However, specific brain networks underpinning these effects remain unclear. Results In the present study using fMRI, we employed a within-condition interregional covariance analysis method to investigate functional connectivity of brain networks involved in acupuncture. The fMRI experiment was performed before, during and after acupuncture manipulations on healthy volunteers at an acupuncture point, which was previously implicated in a neural pathway for pain modulation. We first identified significant fMRI signal changes during acupuncture stimulation in the left amygdala, which was subsequently selected as a functional reference for connectivity analyses. Our results have demonstrated that there is a brain network associated with the amygdala during a resting condition. This network encompasses the brain structures that are implicated in both pain sensation and pain modulation. We also found that such a pain-related network could be modulated by both verum acupuncture and sham acupuncture. Furthermore, compared with a sham acupuncture, the verum acupuncture induced a higher level of correlations among the amygdala-associated network. Conclusion Our findings indicate that acupuncture may change this amygdala-specific brain network into a functional state that underlies pain perception and pain modulation.

  11. 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.

  12. 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. PMID:26262217

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Meta-Analysis of Differential Connectivity in Gene Co-Expression Networks in Multiple Sclerosis.

    Science.gov (United States)

    Creanza, Teresa Maria; Liguori, Maria; Liuni, Sabino; Nuzziello, Nicoletta; Ancona, Nicola

    2016-01-01

    Differential gene expression analyses to investigate multiple sclerosis (MS) molecular pathogenesis cannot detect genes harboring genetic and/or epigenetic modifications that change the gene functions without affecting their expression. Differential co-expression network approaches may capture changes in functional interactions resulting from these alterations. We re-analyzed 595 mRNA arrays from publicly available datasets by studying changes in gene co-expression networks in MS and in response to interferon (IFN)-β treatment. Interestingly, MS networks show a reduced connectivity relative to the healthy condition, and the treatment activates the transcription of genes and increases their connectivity in MS patients. Importantly, the analysis of changes in gene connectivity in MS patients provides new evidence of association for genes already implicated in MS by single-nucleotide polymorphism studies and that do not show differential expression. This is the case of amiloride-sensitive cation channel 1 neuronal (ACCN1) that shows a reduced number of interacting partners in MS networks, and it is known for its role in synaptic transmission and central nervous system (CNS) development. Furthermore, our study confirms a deregulation of the vitamin D system: among the transcription factors that potentially regulate the deregulated genes, we find TCF3 and SP1 that are both involved in vitamin D3-induced p27Kip1 expression. Unveiling differential network properties allows us to gain systems-level insights into disease mechanisms and may suggest putative targets for the treatment. PMID:27314336

  18. 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.

  19. Functional network connectivity of pain-related resting state networks in somatoform pain disorder: an exploratory fMRI study

    Science.gov (United States)

    Otti, Alexander; Guendel, Harald; Henningsen, Peter; Zimmer, Claus; Wohlschlaeger, Afra M.; Noll-Hussong, Michael

    2013-01-01

    Background Without stimulation, the human brain spontaneously produces highly organized, low-frequency fluctuations of neural activity in intrinsic connectivity networks (ICNs). Furthermore, without adequate explanatory nociceptive input, patients with somatoform pain disorder experience pain symptoms, thus implicating a central dysregulation of pain homeostasis. The present study aimed to test whether interactions among pain-related ICNs, such as the default mode network (DMN), cingular–insular network (CIN) and sensorimotor network (SMN), are altered in somatoform pain during resting conditions. Methods Patients with somatoform pain disorder and healthy controls underwent resting functional magnetic resonance imaging that lasted 370 seconds. Using a data-driven approach, the ICNs were isolated, and the functional network connectivity (FNC) was computed. Results Twenty-one patients and 19 controls enrolled in the study. Significant FNC (p < 0.05, corrected for false discovery rate) was detected between the CIN and SMN/anterior DMN, the anterior DMN and posterior DMN/SMN, and the posterior DMN and SMN. Interestingly, no group differences in FNC were detected. Limitations The most important limitation of this study was the relatively short resting state paradigm. Conclusion To our knowledge, our results demonstrated for the first time the resting FNC among pain-related ICNs. However, our results suggest that FNC signatures alone are not able to characterize the putative central dysfunction underpinning somatoform pain disorder. PMID:22894821

  20. Scaling of nearest neighbors' connectivity distribution for scale-free networks

    Science.gov (United States)

    Wei, Zong-Wen; Zhang, Wen-Yao; li, Yu-Jian; Wang, Bing-Hong

    2015-09-01

    Most of real-world networks are called scale-free networks, since the degree distribution follows a power law. However, observing from a node, its nearest neighbors' degree distribution expressed by conditional probability P(k'|k) lacks definite studies and conclusions. Here, we provide a systematic study combined with theoretical and empirical demonstrations, which reveal the inherent connectivity profile of real-world networks. We show that P(k'|k) in the regime k' and k'>k can be approximated by different power laws. One is strongly determined by the degree correlation, and the other depends on both degree distribution and correlation. Based on this result, we propose a degree correlation spectra approach beyond the widely used Pearson correlation coefficient, finding that some networks exhibit sophisticated hybrid correlation patterns. Our results represent a step forward in understanding the structure of complex networks.

  1. 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...... networks. The results represent typically worst-case situations, as more and more people tend to switch off their short-range technology due to the battery consumption and the possible attacks. We explore typical public places like airports, convention centers, shopping malls and bars and extract from them...... some statistics of the size of the mesh network and type of constituent nodes. This information is essential for analyzing and devising cooperative strategies among the terminals of mesh networks in different scenarios....

  2. Microelectromechanical filter formed from parallel-connected lattice networks of contour-mode resonators

    Science.gov (United States)

    Wojciechowski, Kenneth E; Olsson, III, Roy H; Ziaei-Moayyed, Maryam

    2013-07-30

    A microelectromechanical (MEM) filter is disclosed which has a plurality of lattice networks formed on a substrate and electrically connected together in parallel. Each lattice network has a series resonant frequency and a shunt resonant frequency provided by one or more contour-mode resonators in the lattice network. Different types of contour-mode resonators including single input, single output resonators, differential resonators, balun resonators, and ring resonators can be used in MEM filter. The MEM filter can have a center frequency in the range of 10 MHz-10 GHz, with a filter bandwidth of up to about 1% when all of the lattice networks have the same series resonant frequency and the same shunt resonant frequency. The filter bandwidth can be increased up to about 5% by using unique series and shunt resonant frequencies for the lattice networks.

  3. Meta-connectomics: human brain network and connectivity meta-analyses.

    Science.gov (United States)

    Crossley, N A; Fox, P T; Bullmore, E T

    2016-04-01

    Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders. PMID:26809184

  4. 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.

  5. 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

  6. Investigating Default Mode and Sensorimotor Network Connectivity in Amyotrophic Lateral Sclerosis.

    Science.gov (United States)

    Chenji, Sneha; Jha, Shankar; Lee, Dawon; Brown, Matthew; Seres, Peter; Mah, Dennell; Kalra, Sanjay

    2016-01-01

    Amyotrophic lateral sclerosis (ALS) is a neurodegenerative condition characterized by degeneration of upper motor neurons (UMN) arising from the motor cortex in the brain and lower motor neurons (LMN) in the brainstem and spinal cord. Cerebral changes create differences in brain activity captured by functional magnetic resonance imaging (fMRI), including the spontaneous and simultaneous activity occurring between regions known as the resting state networks (RSNs). Progressive neurodegeneration as observed in ALS may lead to a disruption of RSNs which could provide insights into the disease process. Previous studies have reported conflicting findings of increased, decreased, or unaltered RSN functional connectivity in ALS and do not report the contribution of UMN changes to RSN connectivity. We aimed to bridge this gap by exploring two networks, the default mode network (DMN) and the sensorimotor network (SMN), in 21 ALS patients and 40 age-matched healthy volunteers. An UMN score dichotomized patients into UMN+ and UMN- groups. Subjects underwent resting state fMRI scan on a high field MRI operating at 4.7 tesla. The DMN and SMN changes between subject groups were compared. Correlations between connectivity and clinical measures such as the ALS Functional Rating Scale-Revised (ALSFRS-R), disease progression rate, symptom duration, UMN score and finger tapping were assessed. Significant group differences in resting state networks between patients and controls were absent, as was the dependence on degree of UMN burden. However, DMN connectivity was increased in patients with greater disability and faster progression rate, and SMN connectivity was reduced in those with greater motor impairment. These patterns of association are in line with literature supporting loss of inhibitory interneurons. PMID:27322194

  7. Investigating Default Mode and Sensorimotor Network Connectivity in Amyotrophic Lateral Sclerosis.

    Directory of Open Access Journals (Sweden)

    Sneha Chenji

    Full Text Available Amyotrophic lateral sclerosis (ALS is a neurodegenerative condition characterized by degeneration of upper motor neurons (UMN arising from the motor cortex in the brain and lower motor neurons (LMN in the brainstem and spinal cord. Cerebral changes create differences in brain activity captured by functional magnetic resonance imaging (fMRI, including the spontaneous and simultaneous activity occurring between regions known as the resting state networks (RSNs. Progressive neurodegeneration as observed in ALS may lead to a disruption of RSNs which could provide insights into the disease process. Previous studies have reported conflicting findings of increased, decreased, or unaltered RSN functional connectivity in ALS and do not report the contribution of UMN changes to RSN connectivity. We aimed to bridge this gap by exploring two networks, the default mode network (DMN and the sensorimotor network (SMN, in 21 ALS patients and 40 age-matched healthy volunteers. An UMN score dichotomized patients into UMN+ and UMN- groups. Subjects underwent resting state fMRI scan on a high field MRI operating at 4.7 tesla. The DMN and SMN changes between subject groups were compared. Correlations between connectivity and clinical measures such as the ALS Functional Rating Scale-Revised (ALSFRS-R, disease progression rate, symptom duration, UMN score and finger tapping were assessed. Significant group differences in resting state networks between patients and controls were absent, as was the dependence on degree of UMN burden. However, DMN connectivity was increased in patients with greater disability and faster progression rate, and SMN connectivity was reduced in those with greater motor impairment. These patterns of association are in line with literature supporting loss of inhibitory interneurons.

  8. 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.

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

    Science.gov (United States)

    Lee, JongHyup; Pak, Dohyun

    2016-01-01

    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. PMID:27589743

  10. 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.)

  11. Increased Functional Connectivity in an Insula-Based Network is Associated with Improved Smoking Cessation Outcomes.

    Science.gov (United States)

    Addicott, Merideth A; Sweitzer, Maggie M; Froeliger, Brett; Rose, Jed E; McClernon, Francis J

    2015-10-01

    Little is known regarding the underlying neurobiology of smoking cessation. Neuroimaging studies indicate a role for the insula in connecting the interoceptive awareness of tobacco craving with a larger brain network that motivates smoking. We investigated differences in insula-based functional connectivity between smokers who did not relapse during a quit attempt vs those who relapsed. Smokers (n=85) underwent a resting-state functional connectivity scan and were then randomized into two groups (either smoking usual brand cigarettes or smoking very low nicotine cigarettes plus nicotine replacement therapy) for 30 days before their target quit date. Following the quit date, all participants received nicotine replacement therapy and their smoking behavior was observed for 10 weeks. Participants were subsequently classified as nonrelapsed (n=44) or relapsed (i.e., seven consecutive days of smoking ⩾1 cigarette/day; n=41). The right and left insula, as well as insula subdivisions (posterior, ventroanterior, and dorsoanterior) were used as seed regions of interest in the connectivity analysis. Using the right and left whole-insula seed regions, the nonrelapsed group had greater functional connectivity than the relapsed group with the bilateral pre- and postcentral gyri. This effect was isolated to the right and left posterior insula seed regions. Our results suggest that relapse vulnerability is associated with weaker connectivity between the posterior insula and primary sensorimotor cortices. Perhaps greater connectivity in this network improves the ability to inhibit a motor response to cigarette cravings when those cravings conflict with a goal to remain abstinent. These results are consistent with recent studies demonstrating a positive relationship between insula-related functional connectivity and cessation likelihood among neurologically intact smokers. PMID:25895453

  12. Altered functional connectivity networks in acallosal and socially impaired BTBR mice.

    Science.gov (United States)

    Sforazzini, Francesco; Bertero, Alice; Dodero, Luca; David, Gergely; Galbusera, Alberto; Scattoni, Maria Luisa; Pasqualetti, Massimo; Gozzi, Alessandro

    2016-03-01

    Agenesis of the corpus callosum (AgCC) is a congenital condition associated with wide-ranging emotional and social impairments often overlapping with the diagnostic criteria for autism. Mapping functional connectivity in the acallosal brain can help identify neural correlates of the deficits associated with this condition, and elucidate how congenital white matter alterations shape the topology of large-scale functional networks. By using resting-state BOLD functional magnetic resonance imaging (rsfMRI), here we show that acallosal BTBR T+tpr3tf/J (BTBR) mice, an idiopathic model of autism, exhibit impaired intra-hemispheric connectivity in fronto-cortical, but not in posterior sensory cortical areas. We also document profoundly altered subcortical and intra-hemispheric connectivity networks, with evidence of marked fronto-thalamic and striatal disconnectivity, along with aberrant spatial extension and strength of ipsilateral and local connectivity. Importantly, inter-hemispheric tracing of monosynaptic connections in the primary visual cortex using recombinant rabies virus confirmed the absence of direct homotopic pathways between posterior cortical areas of BTBR mice, suggesting a polysynaptic origin for the synchronous rsfMRI signal observed in these regions. Collectively, the observed long-range connectivity impairments recapitulate hallmark neuroimaging findings in autism, and are consistent with the behavioral phenotype of BTBR mice. In contrast to recent rsfMRI studies in high functioning AgCC individuals, the profound fronto-cortical and subcortical disconnectivity mapped suggest that compensatory mechanism may not necessarily restore the full connectional topology of the brain, resulting in residual connectivity alterations that serve as plausible substrates for the cognitive and emotional deficits often associated with AgCC. PMID:25445840

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

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    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

  14. 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.

  15. A Peer-to-Peer Overlay System for Message Delivery in Wide Intermittently-Connected Hybrid Networks

    OpenAIRE

    Esnault, Armel; Le Sommer, Nicolas; Guidec, Frédéric

    2014-01-01

    With the emergence of the Internet of Things, billions of new devices will be wirelessly-connected to the Internet in the next decade, thus yielding a growth of the data traffic, especially in the network infrastructures maintained by mobile operators. Intermittently-connected hybrid networks (ICHNs), which combine an infrastructure part and loosely-connected mobile ad hoc parts, offer interesting perspectives to cope with the growing data traffic. Abstract. This paper presents a decentralize...

  16. Functional MRI neurofeedback training on connectivity between two regions induces long-lasting changes in intrinsic functional network

    OpenAIRE

    Megumi, Fukuda; Yamashita, Ayumu; Kawato, Mitsuo; Imamizu, Hiroshi

    2015-01-01

    Motor or perceptual learning is known to influence functional connectivity between brain regions and induce short-term changes in the intrinsic functional networks revealed as correlations in slow blood-oxygen-level dependent (BOLD) signal fluctuations. However, no cause-and-effect relationship has been elucidated between a specific change in connectivity and a long-term change in global networks. Here, we examine the hypothesis that functional connectivity (i.e., temporal correlation between...

  17. 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.

  18. 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?

  19. 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. PMID:25136697

  20. 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.

  1. 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.

  2. Discover the network mechanisms underlying the connections between aging and age-related diseases.

    Science.gov (United States)

    Yang, Jialiang; Huang, Tao; Song, Won-Min; Petralia, Francesca; Mobbs, Charles V; Zhang, Bin; Zhao, Yong; Schadt, Eric E; Zhu, Jun; Tu, Zhidong

    2016-01-01

    Although our knowledge of aging has greatly expanded in the past decades, it remains elusive why and how aging contributes to the development of age-related diseases (ARDs). In particular, a global mechanistic understanding of the connections between aging and ARDs is yet to be established. We rely on a network modelling named "GeroNet" to study the connections between aging and more than a hundred diseases. By evaluating topological connections between aging genes and disease genes in over three thousand subnetworks corresponding to various biological processes, we show that aging has stronger connections with ARD genes compared to non-ARD genes in subnetworks corresponding to "response to decreased oxygen levels", "insulin signalling pathway", "cell cycle", etc. Based on subnetwork connectivity, we can correctly "predict" if a disease is age-related and prioritize the biological processes that are involved in connecting to multiple ARDs. Using Alzheimer's disease (AD) as an example, GeroNet identifies meaningful genes that may play key roles in connecting aging and ARDs. The top modules identified by GeroNet in AD significantly overlap with modules identified from a large scale AD brain gene expression experiment, supporting that GeroNet indeed reveals the underlying biological processes involved in the disease. PMID:27582315

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Learning Effective Connectivity Network Structure from fMRI Data Based on Artificial Immune Algorithm.

    Science.gov (United States)

    Ji, Junzhong; Liu, Jinduo; Liang, Peipeng; Zhang, Aidong

    2016-01-01

    Many approaches have been designed to extract brain effective connectivity from functional magnetic resonance imaging (fMRI) data. However, few of them can effectively identify the connectivity network structure due to different defects. In this paper, a new algorithm is developed to infer the effective connectivity between different brain regions by combining artificial immune algorithm (AIA) with the Bayes net method, named as AIAEC. In the proposed algorithm, a brain effective connectivity network is mapped onto an antibody, and four immune operators are employed to perform the optimization process of antibodies, including clonal selection operator, crossover operator, mutation operator and suppression operator, and finally gets an antibody with the highest K2 score as the solution. AIAEC is then tested on Smith's simulated datasets, and the effect of the different factors on AIAEC is evaluated, including the node number, session length, as well as the other potential confounding factors of the blood oxygen level dependent (BOLD) signal. It was revealed that, as contrast to other existing methods, AIAEC got the best performance on the majority of the datasets. It was also found that AIAEC could attain a relative better solution under the influence of many factors, although AIAEC was differently affected by the aforementioned factors. AIAEC is thus demonstrated to be an effective method for detecting the brain effective connectivity. PMID:27045295

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. Altered topological properties of functional network connectivity in schizophrenia during resting state: a small-world brain network study.

    Directory of Open Access Journals (Sweden)

    Qingbao Yu

    Full Text Available 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. Optimal Weights of Certain Branches of an Arbitrary Connected Network for Fastest Distributed Consensus Averaging Problem

    CERN Document Server

    Jafarizadeh, Saber

    2010-01-01

    Solving fastest distributed consensus averaging problem over networks with different topologies has been an active area of research for a number of years. The main purpose of distributed consensus averaging is to compute the average of the initial values, via a distributed algorithm, in which the nodes only communicate with their neighbors. In the previous works full knowledge about the network's topology was required for finding optimal weights and convergence rate of network, but here in this work for the first time the optimal weights are determined analytically for the edges of certain types of branches, namely path branch, lollipop branch, semi-complete Branch and Ladder branch independent of the rest of network. The solution procedure consists of stratification of associated connectivity graph of branch and Semidefinite Programming (SDP), particularly solving the slackness conditions, where the optimal weights are obtained by inductive comparing of the characteristic polynomials initiated by slackness c...

  20. 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.

  1. 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.

  2. 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

  3. 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. 

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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

  9. "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.

  10. 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.

  11. Contribution of Network Connectivity in Determining the Relationship between Gene Expression and Metabolite Concentration Changes

    DEFF Research Database (Denmark)

    Zelezniak, Aleksej; Sheridan, Steven; Patil, Kiran Raosaheb

    2014-01-01

    of reaction kinetics in metabolite concentration control is well studied at the level of individual reactions, the contribution of network connectivity has remained relatively unclear. Here we report a modeling framework that integrates both reaction kinetics and network connectivity constraints...... for describing the interplay between metabolite concentrations and mRNA levels. We used this framework to investigate correlations between the gene expression and the metabolite concentration changes in Saccharomyces cerevisiae during its metabolic cycle, as well as in response to three fundamentally different......One of the primary mechanisms through which a cell exerts control over its metabolic state is by modulating expression levels of its enzyme-coding genes. However, the changes at the level of enzyme expression allow only indirect control over metabolite levels, for two main reasons. First...

  12. 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.

  13. 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...

  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. 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.

  16. Abnormal Brain Default-Mode Network Functional Connectivity in Drug Addicts

    OpenAIRE

    Ma, Ning; Liu, Ying; Fu, Xian-ming; Li, Nan; Wang, Chang-Xin; Zhang, Hao; Qian, Ruo-Bing; Xu, Hu-Sheng; Hu, Xiaoping; Zhang, Da-Ren

    2011-01-01

    Background The default mode network (DMN) is a set of brain regions that exhibit synchronized low frequency oscillations at resting-state, and is believed to be relevant to attention and self-monitoring. As the anterior cingulate cortex and hippocampus are impaired in drug addiction and meanwhile are parts of the DMN, the present study examined addiction-related alteration of functional connectivity of the DMN. Methodology Resting-state functional magnetic resonance imaging data of chronic he...

  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. Learning Bayesian Network to Explore Connectivity of Risk Factors in Enterprise Risk Management

    OpenAIRE

    Paradee Namwongse; Yachai Limpiyakorn

    2012-01-01

    Enterprise Risk Management provides a holistic top-down view of key risks facing an organization. Developing techniques that can exhibit the inter-connectivity of risks are required to effectively manage risks on an enterprise-wide. This research thus proposed Bayesian Network learning technique to explore the correlated risks in portfolio risk management using the Expressway Authority of Thailand for empirical study. The comparisons of three Bayes Net algorithms for building the risk map wer...

  19. The default mode network and social understanding of others: what do brain connectivity studies tell us

    OpenAIRE

    Li, Wanqing; Mai, Xiaoqin; Liu, Chao

    2014-01-01

    The Default Mode Network (DMN) has been found to be involved in various domains of cognitive and social processing. The present article will review brain connectivity results related to the DMN in the fields of social understanding of others: emotion perception, empathy, theory of mind, and morality. Most of the reviewed studies focused on healthy subjects with no neurological and psychiatric disease, but some studies on patients with autism and psychopathy will also be discussed. Common resu...

  20. The Default Mode Network and Social Understanding of Others: What do Brain Connectivity Studies Tell Us

    OpenAIRE

    Wanqing eLi; Xiaoqin eMai; Chao eLiu

    2014-01-01

    The Default Mode Network (DMN) has been found to be involved in various domains of cognitive and social processing. The present article will review brain connectivity results related to the DMN in the fields of social understanding of others: emotion perception, empathy, theory of mind, and morality. Most of the reviewed studies focused on healthy subjects with no neurological and psychiatric disease, but some studies on patients with autism and psychopathy will also be discussed. Common res...

  1. 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.

  2. Energy-economic valuation of aerogenerators and possibilities of connecting them to the electricity network

    International Nuclear Information System (INIS)

    On 30 March 1995 the Institut for Landes- and Stadtentwicklungsforschung (Institute for Research on Regional and Urban Development) in North Rhine Westphalia held a workshop on the subject of 'Regional coordination of aeorogenerators'. The author deals with the energy-economic valuation of aerogenerators and reports on possibilities of connecting them to the network from the viewpoint of RWE Energie in the case of a windy highland service region. (orig.)

  3. Combining EEG source connectivity and network similarity: Application to object categorization in the human brain

    OpenAIRE

    Mheich, Ahmad; Hassan, Mahmoud; Dufor, Olivier; Khalil, Mohamad; Wendling, Fabrice

    2016-01-01

    A major challenge in cognitive neuroscience is to evaluate the ability of the human brain to categorize or group visual stimuli based on common features. This categorization process is very fast and occurs in few hundreds of millisecond time scale. However, an accurate tracking of the spatiotemporal dynamics of large-scale brain networks is still an unsolved issue. Here, we show the combination of recently developed method called dense-EEG source connectivity to identify functional brain netw...

  4. Does Broadband Connectivity and Social networking sites build and maintain social capital in rural communities?

    OpenAIRE

    Tiwari, Sanjib; Lane, Michael; Alam, Khorshed

    2016-01-01

    Broadband internet access is a major enabling technology for building social capital (SC) by better connecting rural and regional communities which are often geographically dispersed both locally nationally and internationally. The main objectives of this paper were determine to what extent Social Networking Sites (SNS) can build SC for households in a rural and regional context of rural household adoption and use of broadband internet. A large scale survey of households was used to collect e...

  5. Resting-state network disruption and APOE genotype in Alzheimer's disease: a lagged functional connectivity study.

    Directory of Open Access Journals (Sweden)

    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

  6. Nicotine restores functional connectivity of the ventral attention network in schizophrenia.

    Science.gov (United States)

    Smucny, Jason; Olincy, Ann; Tregellas, Jason R

    2016-09-01

    While previous work has suggested that nicotine may transiently improve attention deficits in schizophrenia, the neuronal mechanisms are poorly understood. This study is the first to examine the effects of nicotine on connectivity within the ventral attention network (VAN) during a selective attention task in schizophrenia. Using a crossover design, 17 nonsmoking patients with schizophrenia and 20 age/gender-matched nonsmoking healthy controls performed a go/no-go task with environmental noise distractors during application of a 7 mg nicotine or placebo patch. Psychophysiological interaction analysis was performed to analyze task-associated changes in connectivity between a ventral parietal cortex (VPC) seed and the inferior frontal gyrus (IFG), key components of the human VAN. Effects of nicotine on resting state VAN connectivity were also examined. A significant diagnosis × drug interaction was observed on task-associated connectivity between the VPC seed and the left IFG (F(1,35) = 8.03, p < 0.01). This effect was driven by decreased connectivity after placebo in patients and greater connectivity after nicotine. Resting state connectivity analysis showed a significant main effect of diagnosis between the seed and right IFG (F = 4.25, p = 0.023) due to increased connectivity in patients during placebo, but no drug × diagnosis interactions or main effects of drug. This study is the first to demonstrate that 1) the VAN is disconnected in schizophrenia during selective attention, and 2) nicotine may normalize this pathological state. PMID:27085606

  7. Functional connectivity in task-negative network of the Deaf: effects of sign language experience

    Directory of Open Access Journals (Sweden)

    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.

  8. Hybrid crosstalk aware Q-Factor analysis for selection of optical virtual private network connection

    Science.gov (United States)

    Das, S. K.; Samantray, A. K.; Patra, S. K.

    2016-01-01

    The presence of physical layer impairments (PLIs) in high-speed optical virtual private network (OVPN) over wavelength-division multiplexing/ dense-wavelength division multiplexing network degrades the connection quality (CQ). The quality can be numerically expressed as the quality factor (Q-Factor) of the connection. The CQ can be further affected by the increasing demand of connections and data speed. It is important to have an efficient OVPN control manager (OVPNCM) to maintain the CQ. OVPNCM can ensure better quality of transmission to the OVPN clients. Traditional routing and wavelength assignment (RWA) algorithms have less regards to the PLIs and cannot provide guaranteed OVPN connection (OVPNC) quality. In order to achieve a guaranteed CQ, we proposed a wavelength assignment (WA) scheme and a hybrid crosstalk model based on linear in-band and nonlinear four-wave mixing crosstalk. The performance of the proposed WA scheme with the hybrid crosstalk model is demonstrated. The results show that the proposed hybrid crosstalk model with WA scheme not only provides a guaranteed OVPNC, but also improves the OVPN performance in terms of blocking probability.

  9. 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.

  10. Age-related decline in functional connectivity of the vestibular cortical network.

    Science.gov (United States)

    Cyran, Carolin Anna Maria; Boegle, Rainer; Stephan, Thomas; Dieterich, Marianne; Glasauer, Stefan

    2016-04-01

    In the elderly, major complaints include dizziness and an increasing number of falls, possibly related to an altered processing of vestibular sensory input. In this study, we therefore investigate age-related changes induced by processing of vestibular sensory stimulation. While previous functional imaging studies of healthy aging have investigated brain function during task performance or at rest, we used galvanic vestibular stimulation during functional MRI in a task-free sensory stimulation paradigm to study the effect of healthy aging on central vestibular processing, which might only become apparent during stimulation processing. Since aging may affect signatures of brain function beyond the BOLD-signal amplitude-such as functional connectivity or temporal signal variability-we employed independent component analysis and partial least squares analysis of temporal signal variability. We tested for age-associated changes unrelated to vestibular processing, using a motor paradigm, voxel-based morphometry and diffusion tensor imaging. This allows us to control for general age-related modifications, possibly originating from vascular, atrophic or structural connectivity changes. Age-correlated decreases of functional connectivity and increases of BOLD-signal variability were associated with multisensory vestibular networks. In contrast, no age-related functional connectivity changes were detected in somatosensory networks or during the motor paradigm. The functional connectivity decrease was not due to structural changes but to a decrease in response amplitude. In synopsis, our data suggest that both the age-dependent functional connectivity decrease and the variability increase may be due to deteriorating reciprocal cortico-cortical inhibition with age and related to multimodal vestibular integration of sensory inputs. PMID:25567421

  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. PMID:25403143

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

    Directory of Open Access Journals (Sweden)

    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. 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.

  14. 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.

  15. Altered Effective Connectivity among Core Neurocognitive Networks in Idiopathic Generalized Epilepsy: An fMRI Evidence.

    Science.gov (United States)

    Wei, Huilin; An, Jie; Shen, Hui; Zeng, Ling-Li; Qiu, Shijun; Hu, Dewen

    2016-01-01

    Idiopathic generalized epilepsy (IGE) patients with generalized tonic-clonic seizures (GTCS) suffer long-term cognitive impairments, and present a higher incidence of psychosocial and psychiatric disturbances than healthy people. It is possible that the cognitive dysfunctions and higher psychopathological risk in IGE-GTCS derive from disturbed causal relationship among core neurocognitive brain networks. To test this hypothesis, we examined the effective connectivity across the salience network (SN), default mode network (DMN), and central executive network (CEN) using resting-state functional magnetic resonance imaging (fMRI) data collected from 27 IGE-GTCS patients and 29 healthy controls. In the study, a combination framework of time domain and frequency domain multivariate Granger causality analysis was firstly proposed, and proved to be valid and accurate by simulation experiments. Using this method, we then observed significant differences in the effective connectivity graphs between the patient and control groups. Specifically, between-group statistical analysis revealed that relative to the healthy controls, the patients established significantly enhanced Granger causal influence from the dorsolateral prefrontal cortex to the dorsal anterior cingulate cortex, which is coherent both in the time and frequency domains analyses. Meanwhile, time domain analysis also revealed decreased Granger causal influence from the right fronto-insular cortex to the posterior cingulate cortex in the patients. These findings may provide new evidence for functional brain organization disruption underlying cognitive dysfunctions and psychopathological risk in IGE-GTCS. PMID:27656137

  16. Resolving the Connectivity-Throughput Trade-Off in Random Networks

    CERN Document Server

    Tanbourgi, Ralph; Jondral, Friedrich K

    2010-01-01

    The discrepancy between the upper bound on throughput in wireless networks and the throughput scaling in random networks which is also known as the connectivity-throughput trade-off is analyzed. In a random network with $\\lambda$ nodes per unit area, throughput is found to scale by a factor of $\\sqrt{\\log{\\lambda}}$ worse compared to the upper bound which is due to the uncertainty in the nodes' location. In the present model, nodes are assumed to know their geographical location and to employ power control, which we understand as an additional degree of freedom to improve network performance. The expected throughput-progress and the expected packet delay normalized to the one-hop progress are chosen as performance metrics. These metrics are investigated for a nearest neighbor forwarding strategy, which benefits from power control by reducing transmission power and, hence spatial contention. It is shown that the connectivity-throughput trade-off can be resolved if nodes employ a nearest neighbor forwarding str...

  17. Disrupted functional connectivity of cerebellar default network areas in attention-deficit/hyperactivity disorder.

    Science.gov (United States)

    Kucyi, Aaron; Hove, Michael J; Biederman, Joseph; Van Dijk, Koene R A; Valera, Eve M

    2015-09-01

    Attention-deficit/hyperactivity disorder (ADHD) is increasingly understood as a disorder of spontaneous brain-network interactions. The default mode network (DMN), implicated in ADHD-linked behaviors including mind-wandering and attentional fluctuations, has been shown to exhibit abnormal spontaneous functional connectivity (FC) within-network and with other networks (salience, dorsal attention and frontoparietal) in ADHD. Although the cerebellum has been implicated in the pathophysiology of ADHD, it remains unknown whether cerebellar areas of the DMN (CerDMN) exhibit altered FC with cortical networks in ADHD. Here, 23 adults with ADHD and 23 age-, IQ-, and sex-matched controls underwent resting state fMRI. The mean time series of CerDMN areas was extracted, and FC with the whole brain was calculated. Whole-brain between-group differences in FC were assessed. Additionally, relationships between inattention and individual differences in FC were assessed for between-group interactions. In ADHD, CerDMN areas showed positive FC (in contrast to average FC in the negative direction in controls) with widespread regions of salience, dorsal attention and sensorimotor networks. ADHD individuals also exhibited higher FC (more positive correlation) of CerDMN areas with frontoparietal and visual network regions. Within the control group, but not in ADHD, participants with higher inattention had higher FC between CerDMN and regions in the visual and dorsal attention networks. This work provides novel evidence of impaired CerDMN coupling with cortical networks in ADHD and highlights a role of cerebro-cerebellar interactions in cognitive function. These data provide support for the potential targeting of CerDMN areas for therapeutic interventions in ADHD. PMID:26109476

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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. PMID:27168362

  11. Differential deactivation during mentalizing and classification of autism based on default mode network connectivity.

    Directory of Open Access Journals (Sweden)

    Donna L Murdaugh

    Full Text Available The default mode network (DMN is a collection of brain areas found to be consistently deactivated during task performance. Previous neuroimaging studies of resting state have revealed reduced task-related deactivation of this network in autism. We investigated the DMN in 13 high-functioning adults with autism spectrum disorders (ASD and 14 typically developing control participants during three fMRI studies (two language tasks and a Theory-of-Mind (ToM task. Each study had separate blocks of fixation/resting baseline. The data from the task blocks and fixation blocks were collated to examine deactivation and functional connectivity. Deficits in the deactivation of the DMN in individuals with ASD were specific only to the ToM task, with no group differences in deactivation during the language tasks or a combined language and self-other discrimination task. During rest blocks following the ToM task, the ASD group showed less deactivation than the control group in a number of DMN regions, including medial prefrontal cortex (MPFC, anterior cingulate cortex, and posterior cingulate gyrus/precuneus. In addition, we found weaker functional connectivity of the MPFC in individuals with ASD compared to controls. Furthermore, we were able to reliably classify participants into ASD or typically developing control groups based on both the whole-brain and seed-based connectivity patterns with accuracy up to 96.3%. These findings indicate that deactivation and connectivity of the DMN were altered in individuals with ASD. In addition, these findings suggest that the deficits in DMN connectivity could be a neural signature that can be used for classifying an individual as belonging to the ASD group.

  12. 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.

  13. 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.

  14. 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.

  15. Increased Functional Connectivity Between Subcortical and Cortical Resting-State Networks in Autism Spectrum Disorder

    Science.gov (United States)

    Cerliani, Leonardo; Mennes, Maarten; Thomas, Rajat M.; Di Martino, Adriana; Thioux, Marc; Keysers, Christian

    2016-01-01

    Importance Individuals with autism spectrum disorder (ASD) exhibit severe difficulties in social interaction, motor coordination, behavioral flexibility, and atypical sensory processing, with considerable interindividual variability. This heterogeneous set of symptoms recently led to investigating the presence of abnormalities in the interaction across large-scale brain networks. To date, studies have focused either on constrained sets of brain regions or whole-brain analysis, rather than focusing on the interaction between brain networks. Objectives To compare the intrinsic functional connectivity between brain networks in a large sample of individuals with ASD and typically developing control subjects and to estimate to what extent group differences would predict autistic traits and reflect different developmental trajectories. Design, Setting, and Participants We studied 166 male individuals (mean age, 17.6 years; age range, 7-50 years) diagnosed as having DSM-IV-TR autism or Asperger syndrome and 193 typical developing male individuals (mean age, 16.9 years; age range, 6.5-39.4 years) using resting-state functional magnetic resonance imaging (MRI). Participants were matched for age, IQ, head motion, and eye status (open or closed) in the MRI scanner. We analyzed data from the Autism Brain Imaging Data Exchange (ABIDE), an aggregated MRI data set from 17 centers, made public in August 2012. Main Outcomes and Measures We estimated correlations between time courses of brain networks extracted using a data-driven method (independent component analysis). Subsequently, we associated estimates of interaction strength between networks with age and autistic traits indexed by the Social Responsiveness Scale. Results Relative to typically developing control participants, individuals with ASD showed increased functional connectivity between primary sensory networks and subcortical networks (thalamus and basal ganglia) (all t ≥ 3.13, P < .001 corrected). The strength of

  16. 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

  17. Mixed Effects Models for Resampled Network Statistics Improves Statistical Power to Find Differences in Multi-Subject Functional Connectivity

    OpenAIRE

    Narayan, Manjari; Allen, Genevera I.

    2016-01-01

    Many complex brain disorders, such as autism spectrum disorders, exhibit a wide range of symptoms and disability. To understand how brain communication is impaired in such conditions, functional connectivity studies seek to understand individual differences in brain network structure in terms of covariates that measure symptom severity. In practice, however, functional connectivity is not observed but estimated from complex and noisy neural activity measurements. Imperfect subject network est...

  18. New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

    Science.gov (United States)

    Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

    2012-01-21

    Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction

  19. New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

    Science.gov (United States)

    Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

    2012-01-21

    Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction

  20. 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...

  1. 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

    2014-01-01

    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. PMID:25167363

  2. 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.

  3. 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.

  4. 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.

  5. Functional MRI neurofeedback training on connectivity between two regions induces long-lasting changes in intrinsic functional network

    Directory of Open Access Journals (Sweden)

    Fukuda eMegumi

    2015-03-01

    Full Text Available Motor or perceptual learning is known to influence functional connectivity between brain regions and induce short-term changes in the intrinsic functional networks revealed as correlations in slow blood-oxygen-level dependent (BOLD signal fluctuations. However, no cause-and-effect relationship has been elucidated between a specific change in connectivity and a long-term change in global networks. Here, we examine the hypothesis that functional connectivity (i.e. temporal correlation between two regions is increased and preserved for a long time when two regions are simultaneously activated or deactivated. Using the connectivity-neurofeedback training paradigm, subjects successfully learned to increase the correlation of activity between the lateral parietal and primary motor areas, regions that belong to different intrinsic networks and negatively correlated before training under the resting conditions. Furthermore, whole-brain hypothesis-free analysis as well as functional network analyses demonstrated that the correlation in the resting state between these areas as well as the correlation between the intrinsic networks that include the areas increased for at least two months. These findings indicate that the connectivity-neurofeedback training can cause long-term changes in intrinsic connectivity and that intrinsic networks can be shaped by experience-driven modulation of regional correlation.

  6. 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

  7. A local average connectivity-based method for identifying essential proteins from the network level.

    Science.gov (United States)

    Li, Min; Wang, Jianxin; Chen, Xiang; Wang, Huan; Pan, Yi

    2011-06-01

    Identifying essential proteins is very important for understanding the minimal requirements of cellular survival and development. Fast growth in the amount of available protein-protein interactions has produced unprecedented opportunities for detecting protein essentiality from the network level. Essential proteins have been found to be more abundant among those highly connected proteins. However, there exist a number of highly connected proteins which are not essential. By analyzing these proteins, we find that few of their neighbors interact with each other. Thus, we propose a new local method, named LAC, to determine a protein's essentiality by evaluating the relationship between a protein and its neighbors. The performance of LAC is validated based on the yeast protein interaction networks obtained from two different databases: DIP and BioGRID. The experimental results of the two networks show that the number of essential proteins predicted by LAC clearly exceeds that explored by Degree Centrality (DC). More over, LAC is also compared with other seven measures of protein centrality (Neighborhood Component (DMNC), Betweenness Centrality (BC), Closeness Centrality (CC), Bottle Neck (BN), Information Centrality (IC), Eigenvector Centrality (EC), and Subgraph Centrality (SC)) in identifying essential proteins. The comparison results based on the validations of sensitivity, specificity, F-measure, positive predictive value, negative predictive value, and accuracy consistently show that LAC outweighs these seven previous methods. PMID:21704260

  8. 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...

  9. An Exploratory Investigation of Functional Network Connectivity of Empathy and Default Mode Networks in a Free-Viewing Task.

    Science.gov (United States)

    Vemuri, Kavita; Surampudi, Bapi Raju

    2015-08-01

    This study reports dynamic functional network connectivity (dFNC) analysis on time courses of putative empathy networks-cognitive, emotional, and motor-and the default mode network (DMN) identified from independent components (ICs) derived by the group independent component analysis (ICA) method. The functional magnetic resonance imaging (fMRI) data were collected from 15 subjects watching movies of three genres, an animation (S1), Indian Hindi (S2), and a Hollywood English (S3) movie. The hypothesis of the study is that empathic engagement in a movie narrative would modulate the activation with the DMN. The clippings were individually rated for emotional expressions, context, and empathy self-response by the fMRI subjects post scanning and by 40 participants in an independent survey who rated at four time intervals in each clipping. The analysis illustrates the following: (a) the ICA method separated ICs with areas reported for empathy response and anterior/posterior DMNs. An IC indicating insula region activation reported to be crucial for the emotional empathy network was separated for S2 and S3 movies only, but not for S1, (b) the dFNC between DMN and ICs corresponding to cognitive empathy network showed higher positive periodical fluctuating correlations for all three movies, while ICs with areas crucial to motor or emotional empathy display lower positive or negative correlation values with no distinct periodicity. A possible explanation for the lower values and anticorrelation between the DMN and emotional empathy networks could possibly be inhibition due to internal self-reflections, attributed to DMN, while processing and preparing a response to external emotional content. The positive higher correlation values for cognitive empathy networks may reflect a functional overlap with DMN for enhanced internal self-reflections, inferring beliefs and intentions about the 'other', all triggered by the external stimuli. The findings are useful in the study of

  10. Detection of anomalous events

    Science.gov (United States)

    Ferragut, Erik M.; Laska, Jason A.; Bridges, Robert A.

    2016-06-07

    A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The system can include a plurality of anomaly detectors that together implement an algorithm to identify low-probability events and detect atypical traffic patterns. The anomaly detector provides for comparability of disparate sources of data (e.g., network flow data and firewall logs.) Additionally, the anomaly detector allows for regulatability, meaning that the algorithm can be user configurable to adjust a number of false alerts. The anomaly detector can be used for a variety of probability density functions, including normal Gaussian distributions, irregular distributions, as well as functions associated with continuous or discrete variables.

  11. Resting state functional MRI reveals abnormal network connectivity in neurofibromatosis 1.

    Science.gov (United States)

    Tomson, Steffie N; Schreiner, Matthew J; Narayan, Manjari; Rosser, Tena; Enrique, Nicole; Silva, Alcino J; Allen, Genevera I; Bookheimer, Susan Y; Bearden, Carrie E

    2015-11-01

    Neurofibromatosis type I (NF1) is a genetic disorder caused by mutations in the neurofibromin 1 gene at locus 17q11.2. Individuals with NF1 have an increased incidence of learning disabilities, attention deficits, and autism spectrum disorders. As a single-gene disorder, NF1 represents a valuable model for understanding gene-brain-behavior relationships. While mouse models have elucidated molecular and cellular mechanisms underlying learning deficits associated with this mutation, little is known about functional brain architecture in human subjects with NF1. To address this question, we used resting state functional connectivity magnetic resonance imaging (rs-fcMRI) to elucidate the intrinsic network structure of 30 NF1 participants compared with 30 healthy demographically matched controls during an eyes-open rs-fcMRI scan. Novel statistical methods were employed to quantify differences in local connectivity (edge strength) and modularity structure, in combination with traditional global graph theory applications. Our findings suggest that individuals with NF1 have reduced anterior-posterior connectivity, weaker bilateral edges, and altered modularity clustering relative to healthy controls. Further, edge strength and modular clustering indices were correlated with IQ and internalizing symptoms. These findings suggest that Ras signaling disruption may lead to abnormal functional brain connectivity; further investigation into the functional consequences of these alterations in both humans and in animal models is warranted. PMID:26304096

  12. 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.

  13. Abnormal brain default-mode network functional connectivity in drug addicts.

    Directory of Open Access Journals (Sweden)

    Ning Ma

    Full Text Available BACKGROUND: The default mode network (DMN is a set of brain regions that exhibit synchronized low frequency oscillations at resting-state, and is believed to be relevant to attention and self-monitoring. As the anterior cingulate cortex and hippocampus are impaired in drug addiction and meanwhile are parts of the DMN, the present study examined addiction-related alteration of functional connectivity of the DMN. METHODOLOGY: Resting-state functional magnetic resonance imaging data of chronic heroin users (14 males, age: 30.1±5.3 years, range from 22 to 39 years and non-addicted controls (13 males, age: 29.8±7.2 years, range from 20 to 39 years were investigated with independent component analysis to address their functional connectivity of the DMN. PRINCIPAL FINDINGS: Compared with controls, heroin users showed increased functional connectivity in right hippocampus and decreased functional connectivity in right dorsal anterior cingulate cortex and left caudate in the DMN. CONCLUSIONS: These findings suggest drug addicts' abnormal functional organization of the DMN, and are discussed as addiction-related abnormally increased memory processing but diminished cognitive control related to attention and self-monitoring, which may underlie the hypersensitivity toward drug related cues but weakened strength of cognitive control in the state of addiction.

  14. 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.

  15. 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.

  16. 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. PMID:27119360

  17. Two-layer tree-connected feed-forward neural network model for neural cryptography

    Science.gov (United States)

    Lei, Xinyu; Liao, Xiaofeng; Chen, Fei; Huang, Tingwen

    2013-03-01

    Neural synchronization by means of mutual learning provides an avenue to design public key exchange protocols, bringing about what is known as neural cryptography. Two identically structured neural networks learn from each other and reach full synchronization eventually. The full synchronization enables two networks to have the same weight, which can be used as a secret key for many subsequent cryptographic purposes. It is striking to observe that after the first decade of neural cryptography, the tree parity machine (TPM) network with hidden unit K=3 appears to be the sole network that is suitable for a neural protocol. No convincingly secure neural protocol is well designed by using other network structures despite considerable research efforts. With the goal of overcoming the limitations of a suitable network structure, in this paper we develop a two-layer tree-connected feed-forward neural network (TTFNN) model for a neural protocol. The TTFNN model captures the notion that two partners are capable of exchanging a vector with multiple bits in each time step. An in-depth study of the dynamic process of TTFNN-based protocols is then undertaken, based upon which a feasible condition is theoretically obtained to seek applicable protocols. Afterward, according to two analytically derived heuristic rules, a complete methodology for designing feasible TTFNN-based protocols is elaborated. A variety of feasible neural protocols are constructed, which exhibit the effectiveness and benefits of the proposed model. With another look from the perspective of application, TTFNN-based instances, which can outperform the conventional TPM-based protocol with respect to synchronization speed, are also experimentally confirmed.

  18. Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

    Directory of Open Access Journals (Sweden)

    Ma'ayan Avi

    2007-10-01

    Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

  19. An Enhanced Connectivity Aware Routing Protocol for Vehicular Ad hoc Networks

    Directory of Open Access Journals (Sweden)

    Ahmadu Maidorawa

    2014-04-01

    Full Text Available This study proposed an Enhanced Connectivity Aware Routing (ECAR protocol for Vehicular Ad hoc Network (VANET. The protocol uses a control broadcast to reduce the number of overhead packets needed in a route discovery process. It is also equipped with an alternative backup route that is used whenever a primary path to destination failed, which highly reduces the frequent launching and re-launching of the route discovery process that waste useful bandwidth and unnecessarily prolonging the average packet delay. NS2 simulation results show that the performance of ECAR protocol outperformed the original Connectivity Aware Routing (CAR protocol by reducing the average packet delay by 28%, control overheads by 27% and increased the packet delivery ratio by 22%.

  20. 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.

  1. 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 were then instructed to release the joystick handle after target disappearance, allowing the cursor to re-center for the next trial. Performance was assessed by measuring direction error (DE), defined as the angle between the line from the start to the target position, and the line from the start

  2. Tracking multiple sediment cascades at the river network scale identifies controls and emerging patterns of sediment connectivity

    Science.gov (United States)

    Schmitt, Rafael J. P.; Bizzi, Simone; Castelletti, Andrea

    2016-05-01

    Sediment connectivity in fluvial networks results from the transfer of sediment between multiple sources and sinks. Connectivity scales differently between all sources and sinks as a function of distance, source grain size and sediment supply, network topology and topography, and hydrologic forcing. In this paper, we address the challenge of quantifying sediment connectivity and its controls at the network scale. We expand the concept of a single, catchment-scale sediment cascade toward representing sediment transport from each source as a suite of individual cascading processes. We implement this approach in the herein presented CAtchment Sediment Connectivity And DElivery (CASCADE) modeling framework. In CASCADE, each sediment cascade establishes connectivity between a specific source and its multiple sinks. From a source perspective, the fate of sediment is controlled by its detachment and downstream transport capacity, resulting in a specific trajectory of transfer and deposition. From a sink perspective, the assemblage of incoming cascades defines provenance, sorting, and magnitude of sediment deliveries. At the network scale, this information reveals emerging patterns of connectivity and the location of bottlenecks, where disconnectivity occurs. In this paper, we apply CASCADE to quantitatively analyze the sediment connectivity of a major river system in SE Asia. The approach provides a screening model that can support analyses of large, poorly monitored river systems. We test the sensitivity of CASCADE to various parameters and identify the distribution of energy between the multiple, simultaneously active sediment cascades as key control behind network sediment connectivity. To conclude, CASCADE enables a quantitative, spatially explicit analysis of network sediment connectivity with potential applications in both river science and management.

  3. Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

    International Nuclear Information System (INIS)

    The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime

  4. Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

    Energy Technology Data Exchange (ETDEWEB)

    Cabral, Joana [Theoretical and Computational Neuroscience Group, Center of Brain and Cognition, Universitat Pompeu Fabra, Barcelona 08018 (Spain); Department of Psychiatry, University of Oxford, Oxford OX3 7JX (United Kingdom); Fernandes, Henrique M.; Van Hartevelt, Tim J.; Kringelbach, Morten L. [Department of Psychiatry, University of Oxford, Oxford OX3 7JX (United Kingdom); Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Aarhus (Denmark); James, Anthony C. [Department of Psychiatry, University of Oxford, Oxford OX3 7JX (United Kingdom); Highfield Unit, Warneford Hospital, Oxford OX3 7JX (United Kingdom); Deco, Gustavo [Theoretical and Computational Neuroscience Group, Center of Brain and Cognition, Universitat Pompeu Fabra, Barcelona 08018 (Spain); Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona 08010 (Spain)

    2013-12-15

    The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.

  5. Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

    Science.gov (United States)

    Cabral, Joana; Fernandes, Henrique M.; Van Hartevelt, Tim J.; James, Anthony C.; Kringelbach, Morten L.; Deco, Gustavo

    2013-12-01

    The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Dirk Wildgruber

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

  8. Social connections and the persuasiveness of viral campaigns in social network sites: persuasive intent as the underlying mechanism

    NARCIS (Netherlands)

    G. van Noort; M.L. Antheunis; E.A. van Reijmersdal

    2012-01-01

    Social media are increasingly popular. Consequently, marketers more and more recognize social network sites as a platform for commercial campaigns. Social network users forward these campaigns to their online connections. However, our understanding of the persuasiveness of these campaigns is scarce.

  9. Optical cross-connect and link dimensioning of a multi-wavelength network with and without wavelength converters

    DEFF Research Database (Denmark)

    Limal, Emmanuel; Mikkelsen, Benny; Stubkjær, Kristian Elmholdt

    1997-01-01

    Optimisation of a new modular WDM network architecture, with and without wavelength converters, is performed. Trade-offs between the number of WDM channels, the channel bit rate, the total amount of fibre in the network and the optical cross-connect components count are identified....

  10. Short-term antidepressant administration reduces default mode and task-positive network connectivity in healthy individuals during rest

    NARCIS (Netherlands)

    van Wingen, Guido A; Tendolkar, Indira; Urner, Maren; van Marle, Hein J; Denys, D.; Verkes, Robbert-Jan; Fernández, Guillén

    2014-01-01

    Resting-state studies in depressed patients have revealed increased connectivity within the default mode network (DMN) and task-positive network (TPN). This has been associated with heightened rumination, which is the tendency to repetitively think about symptoms of distress. Here, we performed a ph

  11. Short-term antidepressant administration reduces default mode and task-positive network connectivity in healthy individuals during rest

    NARCIS (Netherlands)

    Wingen, G.A. van; Tendolkar, I.; Urner, M.; Marle, H.J.F. van; Denys, D.; Verkes, R.J.; Fernandez, G.S.E.

    2013-01-01

    Resting-state studies in depressed patients have revealed increased connectivity within the default mode network (DMN) and task-positive network (TPN). This has been associated with heightened rumination, which is the tendency to repetitively think about symptoms of distress. Here, we performed a ph

  12. Space Link Extension Protocol Emulation for High-Throughput, High-Latency Network Connections

    Science.gov (United States)

    Tchorowski, Nicole; Murawski, Robert

    2014-01-01

    New space missions require higher data rates and new protocols to meet these requirements. These high data rate space communication links push the limitations of not only the space communication links, but of the ground communication networks and protocols which forward user data to remote ground stations (GS) for transmission. The Consultative Committee for Space Data Systems, (CCSDS) Space Link Extension (SLE) standard protocol is one protocol that has been proposed for use by the NASA Space Network (SN) Ground Segment Sustainment (SGSS) program. New protocol implementations must be carefully tested to ensure that they provide the required functionality, especially because of the remote nature of spacecraft. The SLE protocol standard has been tested in the NASA Glenn Research Center's SCENIC Emulation Lab in order to observe its operation under realistic network delay conditions. More specifically, the delay between then NASA Integrated Services Network (NISN) and spacecraft has been emulated. The round trip time (RTT) delay for the continental NISN network has been shown to be up to 120ms; as such the SLE protocol was tested with network delays ranging from 0ms to 200ms. Both a base network condition and an SLE connection were tested with these RTT delays, and the reaction of both network tests to the delay conditions were recorded. Throughput for both of these links was set at 1.2Gbps. The results will show that, in the presence of realistic network delay, the SLE link throughput is significantly reduced while the base network throughput however remained at the 1.2Gbps specification. The decrease in SLE throughput has been attributed to the implementation's use of blocking calls. The decrease in throughput is not acceptable for high data rate links, as the link requires constant data a flow in order for spacecraft and ground radios to stay synchronized, unless significant data is queued a the ground station. In cases where queuing the data is not an option

  13. Improving Link Prediction in Intermittently Connected Wireless Networks by Considering Link and Proximity Stabilities

    CERN Document Server

    Zayani, Mohamed-Haykel; Zeghlache, Djamal

    2012-01-01

    Several works have outlined the fact that the mobility in intermittently connected wireless networks is strongly governed by human behaviors as they are basically human-centered. It has been shown that the users' moves can be correlated and that the social ties shared by the users highly impact their mobility patterns and hence the network structure. Tracking these correlations and measuring the strength of social ties have led us to propose an efficient distributed tensor-based link prediction technique. In fact, we are convinced that the feedback provided by such a prediction mechanism can enhance communication protocols such as opportunistic routing protocols. In this paper, we aim to bring out that measuring the stabilities of the link and the proximity at two hops can improve the efficiency of the proposed link prediction technique. To quantify these two parameters, we propose an entropy estimator in order to measure the two stability aspects over successive time periods. Then, we join these entropy esti...

  14. Mutual information and self-control of a fully-connected low-activity neural network

    Science.gov (United States)

    Bollé, D.; Carreta, D. Dominguez

    2000-11-01

    A self-control mechanism for the dynamics of a three-state fully connected neural network is studied through the introduction of a time-dependent threshold. The self-adapting threshold is a function of both the neural and the pattern activity in the network. The time evolution of the order parameters is obtained on the basis of a recently developed dynamical recursive scheme. In the limit of low activity the mutual information is shown to be the relevant parameter in order to determine the retrieval quality. Due to self-control an improvement of this mutual information content as well as an increase of the storage capacity and an enlargement of the basins of attraction are found. These results are compared with numerical simulations.

  15. 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

    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......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...... grid is presented and qualitative conclusions about the system inherent interactions and typical restraints are presented and discussed. The impact of the wind power feed-in and the reactive power flow on the PCC voltage is assessed under widely varying system parameters. Results verification...

  16. An Algorithm to Determine Stable Connected Dominating Sets for Mobile Ad hoc Networks using Strong Neighborhoods

    Directory of Open Access Journals (Sweden)

    Natarajan Meghanathan

    2012-05-01

    Full Text Available We propose an algorithm to determine stable connected dominating sets (CDS for mobile ad hoc networks using the notion of strong neighborhood (SN. The SN-CDS algorithm takes an input parameter called the Threshold Neighborhood Distance Ratio (TNDR; for an edge to be part of a strong neighborhood-based topology, the ratio of the physical Euclidean distance between the end nodes of the edge to that of the transmission range per node has to be less than or equal to the TNDR. The algorithm prefers to include nodes (into the SN-CDS in the decreasing order of the number of uncovered strong neighbors until all nodes in the network are covered. We observe the SN-CDS (TNDR < 1 to have a significantly longer lifetime than a maximum density-based CDS (MaxD-CDS with TNDR = 1.0; the tradeoff being a slightly larger CDS Node Size and hop count per path.

  17. Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients.

    Science.gov (United States)

    Assaf, Michal; Jagannathan, Kanchana; Calhoun, Vince D; Miller, Laura; Stevens, Michael C; Sahl, Robert; O'Boyle, Jacqueline G; Schultz, Robert T; Pearlson, Godfrey D

    2010-10-15

    Autism spectrum disorders (ASDs) are characterized by deficits in social and communication processes. Recent data suggest that altered functional connectivity (FC), i.e. synchronous brain activity, might contribute to these deficits. Of specific interest is the FC integrity of the default mode network (DMN), a network active during passive resting states and cognitive processes related to social deficits seen in ASD, e.g. Theory of Mind. We investigated the role of altered FC of default mode sub-networks (DM-SNs) in 16 patients with high-functioning ASD compared to 16 matched healthy controls of short resting fMRI scans using independent component analysis (ICA). ICA is a multivariate data-driven approach that identifies temporally coherent networks, providing a natural measure of FC. Results show that compared to controls, patients showed decreased FC between the precuneus and medial prefrontal cortex/anterior cingulate cortex, DMN core areas, and other DM-SNs areas. FC magnitude in these regions inversely correlated with the severity of patients' social and communication deficits as measured by the Autism Diagnostic Observational Schedule and the Social Responsiveness Scale. Importantly, supplemental analyses suggest that these results were independent of treatment status. These results support the hypothesis that DM-SNs under-connectivity contributes to the core deficits seen in ASD. Moreover, these data provide further support for the use of data-driven analysis with resting-state data for illuminating neural systems that differ between groups. This approach seems especially well suited for populations where compliance with and performance of active tasks might be a challenge, as it requires minimal cooperation. PMID:20621638

  18. Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke.

    Science.gov (United States)

    Siegel, Joshua Sarfaty; Ramsey, Lenny E; Snyder, Abraham Z; Metcalf, Nicholas V; Chacko, Ravi V; Weinberger, Kilian; Baldassarre, Antonello; Hacker, Carl D; Shulman, Gordon L; Corbetta, Maurizio

    2016-07-26

    Deficits following stroke are classically attributed to focal damage, but recent evidence suggests a key role of distributed brain network disruption. We measured resting functional connectivity (FC), lesion topography, and behavior in multiple domains (attention, visual memory, verbal memory, language, motor, and visual) in a cohort of 132 stroke patients, and used machine-learning models to predict neurological impairment in individual subjects. We found that visual memory and verbal memory were better predicted by FC, whereas visual and motor impairments were better predicted by lesion topography. Attention and language deficits were well predicted by both. Next, we identified a general pattern of physiological network dysfunction consisting of decrease of interhemispheric integration and intrahemispheric segregation, which strongly related to behavioral impairment in multiple domains. Network-specific patterns of dysfunction predicted specific behavioral deficits, and loss of interhemispheric communication across a set of regions was associated with impairment across multiple behavioral domains. These results link key organizational features of brain networks to brain-behavior relationships in stroke. PMID:27402738

  19. A two-level on-line learning algorithm of Artificial Neural Network with forward connections

    Directory of Open Access Journals (Sweden)

    Stanislaw Placzek

    2014-12-01

    Full Text Available An Artificial Neural Network with cross-connection is one of the most popular network structures. The structure contains: an input layer, at least one hidden layer and an output layer. Analysing and describing an ANN structure, one usually finds that the first parameter is the number of ANN’s layers. A hierarchical structure is a default and accepted way of describing the network. Using this assumption, the network structure can be described from a different point of view. A set of concepts and models can be used to describe the complexity of ANN’s structure in addition to using a two-level learning algorithm. Implementing the hierarchical structure to the learning algorithm, an ANN structure is divided into sub-networks. Every sub-network is responsible for finding the optimal value of its weight coefficients using a local target function to minimise the learning error. The second coordination level of the learning algorithm is responsible for coordinating the local solutions and finding the minimum of the global target function. In the article a special emphasis is placed on the coordinator’s role in the learning algorithm and its target function. In each iteration the coordinator has to send coordination parameters into the first level of subnetworks. Using the input X and the teaching Z vectors, the local procedures are working and finding their weight coefficients. At the same step the feedback information is calculated and sent to the coordinator. The process is being repeated until the minimum of local target functions is achieved. As an example, a two-level learning algorithm is used to implement an ANN in the underwriting process for classifying the category of health in a life insurance company.

  20. The default mode network and social understanding of others: what do brain connectivity studies tell us.

    Science.gov (United States)

    Li, Wanqing; Mai, Xiaoqin; Liu, Chao

    2014-01-01

    The Default Mode Network (DMN) has been found to be involved in various domains of cognitive and social processing. The present article will review brain connectivity results related to the DMN in the fields of social understanding of others: emotion perception, empathy, theory of mind, and morality. Most of the reviewed studies focused on healthy subjects with no neurological and psychiatric disease, but some studies on patients with autism and psychopathy will also be discussed. Common results show that the medial prefrontal cortex (MPFC) plays a key role in the social understanding of others, and the subregions of the MPFC contribute differently to this function according to their roles in different subsystems of the DMN. At the bottom, the ventral MPFC in the medial temporal lobe (MTL) subsystem and its connections with emotion regions are mainly associated with emotion engagement during social interactions. Above, the anterior MPFC (aMPFC) in the cortical midline structures (CMS) and its connections with posterior and anterior cingulate cortex contribute mostly to making self-other distinctions. At the top, the dorsal MPFC (dMPFC) in the dMPFC subsystem and its connection with the temporo-parietal junction (TPJ) are primarily related to the understanding of other's mental states. As behaviors become more complex, the related regions in frontal cortex are located higher. This reflects the transfer of information processing from automatic to cognitive processes with the increase of the complexity of social interaction. Besides the MPFC and TPJ, the connectivities of posterior cingulate cortex (PCC) also show some changes during tasks from the four social fields. These results indicate that the DMN is indispensable in the social understanding of others. PMID:24605094