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

    2009-11-01

    Full Text Available 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.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.This study extends the results of numerous previous schizophrenia studies that identified isolated dysfunctional brain regions by providing evidence of disrupted schizophrenia functional connectivity using ICA within

  2. Anomalous Metapopulation Dynamics on Scale-Free Networks

    Science.gov (United States)

    Fedotov, Sergei; Stage, Helena

    2017-03-01

    We model transport of individuals across a heterogeneous scale-free network where a few weakly connected nodes exhibit heavy-tailed residence times. Using the empirical law of the axiom of cumulative inertia and fractional analysis, we show that "anomalous cumulative inertia" overpowers highly connected nodes in attracting network individuals. This fundamentally challenges the classical result that individuals tend to accumulate in high-order nodes. The derived residence time distribution has a nontrivial U shape which we encounter empirically across human residence and employment times.

  3. Minimum cost connection networks

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Tvede, Mich

    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....... 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....

  4. Minimum cost connection networks

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Tvede, Mich

    2015-01-01

    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...... 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...

  5. Total Anomalous Pulmonary Venous Connection to the Portal Vein

    International Nuclear Information System (INIS)

    Wyttenbach, Marina; Carrel, Thierry; Schuepbach, Peter; Tschaeppeler, Heinz; Triller, Juergen

    1996-01-01

    Anomalous pulmonary venous return represents a rare congenital anomaly with wide anatomic and physiologic variability. We report a case of a newborn with a rare form of total infracardiac anomalous pulmonary venous connection (TAPVC). The pulmonary veins draining both lungs formed two vertical veins, which joined to a common pulmonary trunk below the diaphragm. This venous channel connected to the portal vein through the esophageal hiatus. The diagnosis was suggested by color Doppler sonography and confirmed by intravenous digital subtraction angiography, which allowed definition of the anatomy

  6. 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

  7. 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.

  8. Magnetic resonance imaging of anomalous pulmonary venous connections

    International Nuclear Information System (INIS)

    Choe, Yeon Hyeon; Lee, Heung Jae; Kim, Hak Soo; Ko, Jae Kon; Kim, Ji Eun; Han, Jae Jin

    1994-01-01

    We evaluated the capability of MR in the diagnosis of anomalous pulmonary venous connection (APVC). The patient group consisted of 11 total APVC and 8 partial APVC diagnosed with MR. Echocardiography was performed in all cases, cardiac angiography in 12 cases and operation in 12 cases. We compared MR findings with those of operation, echocardiography and cardiac angiography. In surgically proven 12 cases, diagnostic accuracy of preoperative MR, echocardiography and cardiac angiography was 100%, 67%, and 63%, respectively. In the remaining cases, MR findings well correlated with those of echocardiography or cardiac angiography. Stenosis of common pulmonary vein or superior vena cava was identified in 4 cases. In one patient, MR duplicated associated cortriatriatum clearly. MR is an effective modally in depicting anomalous pulmonary venous connections

  9. Connected Cubic Network Graph

    Directory of Open Access Journals (Sweden)

    Burhan Selçuk

    2017-06-01

    Full Text Available Hypercube is a popular interconnection network. Due to the popularity of hypercube, more researchers pay a great effort to develop the different variants of hypercube. In this paper, we have proposed a variant of hypercube which is called as “Connected Cubic Network Graphs”, and have investigated the Hamilton-like properties of Connected Cubic Network Graphs (CCNG. Firstly, we defined CCNG and showed the characteristic analyses of CCNG. Then, we showed that the CCNG has the properties of Hamilton graph, and can be labeled using a Gray coding based recursive algorithm. Finally, we gave the comparison results, a routing algorithm and a bitonic sort algorithm for CCNG. In case of sparsity and cost, CCNG is better than Hypercube.

  10. Anomalous Anticipatory Responses in Networked Random Data

    International Nuclear Information System (INIS)

    Nelson, Roger D.; Bancel, Peter A.

    2006-01-01

    We examine an 8-year archive of synchronized, parallel time series of random data from a world spanning network of physical random event generators (REGs). The archive is a publicly accessible matrix of normally distributed 200-bit sums recorded at 1 Hz which extends from August 1998 to the present. The primary question is whether these data show non-random structure associated with major events such as natural or man-made disasters, terrible accidents, or grand celebrations. Secondarily, we examine the time course of apparently correlated responses. Statistical analyses of the data reveal consistent evidence that events which strongly affect people engender small but significant effects. These include suggestions of anticipatory responses in some cases, leading to a series of specialized analyses to assess possible non-random structure preceding precisely timed events. A focused examination of data collected around the time of earthquakes with Richter magnitude 6 and greater reveals non-random structure with a number of intriguing, potentially important features. Anomalous effects in the REG data are seen only when the corresponding earthquakes occur in populated areas. No structure is found if they occur in the oceans. We infer that an important contributor to the effect is the relevance of the earthquake to humans. Epoch averaging reveals evidence for changes in the data some hours prior to the main temblor, suggestive of reverse causation

  11. Rare associations of tetralogy of Fallot with anomalous left coronary artery from pulmonary artery and totally anomalous pulmonary venous connection.

    Science.gov (United States)

    Sen, Supratim; Rao, Suresh G; Kulkarni, Snehal

    2016-06-01

    We describe the cases of two patients with tetralogy of Fallot, aged 4 years and 8 months, who were incidentally detected to have concomitant anomalous left coronary artery from pulmonary artery and total anomalous pulmonary venous connection, respectively, on preoperative imaging. They underwent surgical correction with good mid-term outcomes. In this study, we discuss the embryological basis, physiological effects, and review the literature of these two unusual associations. Awareness of these rare associations will avoid missed diagnoses and consequent surgical surprises.

  12. Navigation by anomalous random walks on complex networks.

    Science.gov (United States)

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

    2016-11-23

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

  13. Navigation by anomalous random walks on complex networks

    Science.gov (United States)

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

    2016-11-01

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

  14. Utilizing Weak Indicators to Detect Anomalous Behaviors in Networks

    Energy Technology Data Exchange (ETDEWEB)

    Egid, Adin [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-11-01

    We consider the use of a novel weak in- dicator alongside more commonly used weak indicators to help detect anomalous behavior in a large computer network. The data of the network which we are studying in this research paper concerns remote log-in information (Virtual Private Network, or VPN sessions) from the internal network of Los Alamos National Laboratory (LANL). The novel indicator we are utilizing is some- thing which, while novel in its application to data science/cyber security research, is a concept borrowed from the business world. The Her ndahl-Hirschman Index (HHI) is a computationally trivial index which provides a useful heuristic for regulatory agencies to ascertain the relative competitiveness of a particular industry. Using this index as a lagging indicator in the monthly format we have studied could help to detect anomalous behavior by a particular or small set of users on the network.

  15. Suppression of anomalous synchronization and nonstationary behavior of neural network under small-world topology

    Science.gov (United States)

    Boaretto, B. R. R.; Budzinski, R. C.; Prado, T. L.; Kurths, J.; Lopes, S. R.

    2018-05-01

    It is known that neural networks under small-world topology can present anomalous synchronization and nonstationary behavior for weak coupling regimes. Here, we propose methods to suppress the anomalous synchronization and also to diminish the nonstationary behavior occurring in weakly coupled neural network under small-world topology. We consider a network of 2000 thermally sensitive identical neurons, based on the model of Hodgkin-Huxley in a small-world topology, with the probability of adding non local connection equal to p = 0 . 001. Based on experimental protocols to suppress anomalous synchronization, as well as nonstationary behavior of the neural network dynamics, we make use of (i) external stimulus (pulsed current); (ii) biologic parameters changing (neuron membrane conductance changes); and (iii) body temperature changes. Quantification analysis to evaluate phase synchronization makes use of the Kuramoto's order parameter, while recurrence quantification analysis, particularly the determinism, computed over the easily accessible mean field of network, the local field potential (LFP), is used to evaluate nonstationary states. We show that the methods proposed can control the anomalous synchronization and nonstationarity occurring for weak coupling parameter without any effect on the individual neuron dynamics, neither in the expected asymptotic synchronized states occurring for large values of the coupling parameter.

  16. Clarifying the anatomy and physiology of totally anomalous systemic venous connection.

    Science.gov (United States)

    Gupta, Saurabh Kumar; Juneja, Rajnish; Anderson, Robert H; Gulati, Gurpreet S; Devagorou, Velayoudam

    2017-01-01

    The description of totally anomalous systemic venous connection is limited to case reports. In this review, we seek to clarify anatomic, physiologic, and hemodynamic aspects of this extremely rare anomaly. We also present findings of two patients in whom connection of all the systemic veins was anomalous. In the first patient, with usual atrial arrangement, all systemic veins, including the coronary sinus, were connected anomalously to the morphologically left atrium. Limited left-to-right shunt across an atrial septal defect provided the only source of blood flow to the lungs. The diagnosis was established by saline contrast echocardiography and cardiac catheterization. Extreme hypoplasia of the right ventricle precluded corrective surgery, so we performed a bidirectional Glenn operation, along with atrial septectomy. The second patient had isomerism of the left atrial appendages, which creates problems in the definition in anatomic terms since the connection of the systemic veins can never be normal anatomically when both atriums possess a morphologically left appendage. Our patient, nonetheless, had all the systemic and pulmonary veins, connected to the left-sided atrial chamber which then connected to the left ventricle, thus producing hemodynamics of totally anomalous systemic venous connection. We propose an algorithm for evaluation of this hemodynamic combination and discuss management options. We also intend to clarify the potential differences between connection and drainage, with particular attention to the arrangement of atrial appendages. Even though the hemodynamics may be comparable, in anatomic terms, both systemic and pulmonary venoatrial connection will always be anomalous with isomeric atrial appendages.

  17. Magnetic resonance imaging in the assessment of anomalous pulmonary venous connections.

    Science.gov (United States)

    Bernal Garnes, N; Méndez Díaz, C; Soler Fernández, R; Rodríguez García, E

    2016-01-01

    To illustrate the morphological and functional magnetic resonance findings for total and partial anomalous pulmonary venous connections as well as of the most common complications after surgery. The magnetic resonance findings are fundamental in defining the type of anomalous connection, deciding on the treatment, planning the surgery, and detecting postsurgical complications. Copyright © 2015 SERAM. Published by Elsevier España, S.L.U. All rights reserved.

  18. Identifying Anomalous Port-Specific Network Behavior

    Science.gov (United States)

    2010-05-01

    Backscatter 4.3 6.2 1.3 Connection Attempt 4.3 7.6 3.3 User Non-Web activity 3.9 22.0 11.9 SYN flood 3.6 9.0 4.4 Beaconing (Non-443) 3.6 20.5 5.0 Large...flagged events are composed of suspicious events such as beaconing (keep- alives on non-standard ports), SYN floods , scanning, and large data...systems. A port is an integer value between 0 and 65535 that represents a logical connection place for Transmission Control Protocol ( TCP ) and User

  19. Patterns of anomalous pulmonary venous connection as seen at ...

    African Journals Online (AJOL)

    Supra-cardiac and intra-cardiac anomalous were the commonest type of TAPVC representing 43.6% and 35.9% respectively. Among all patients with TAPVC 51.35% were associated with ostium secundum atrial septal defect, 74.4% had moderate to severe pulmonary hypertension. Overall mortality was 9.25%. Mortality ...

  20. Connecting and Networking for Schools

    Science.gov (United States)

    Resources for connecting and networking for schools through e-newsletters, finding school IAQ Champions and other EPA school programs such as Asthma, Energy Star, Clean School Bus USA, School Flag, etc.

  1. Clarifying the anatomy and physiology of totally anomalous systemic venous connection

    Directory of Open Access Journals (Sweden)

    Saurabh Kumar Gupta

    2017-01-01

    Full Text Available The description of totally anomalous systemic venous connection is limited to case reports. In this review, we seek to clarify anatomic, physiologic, and hemodynamic aspects of this extremely rare anomaly. We also present findings of two patients in whom connection of all the systemic veins was anomalous. In the first patient, with usual atrial arrangement, all systemic veins, including the coronary sinus, were connected anomalously to the morphologically left atrium. Limited left-to-right shunt across an atrial septal defect provided the only source of blood flow to the lungs. The diagnosis was established by saline contrast echocardiography and cardiac catheterization. Extreme hypoplasia of the right ventricle precluded corrective surgery, so we performed a bidirectional Glenn operation, along with atrial septectomy. The second patient had isomerism of the left atrial appendages, which creates problems in the definition in anatomic terms since the connection of the systemic veins can never be normal anatomically when both atriums possess a morphologically left appendage. Our patient, nonetheless, had all the systemic and pulmonary veins, connected to the left-sided atrial chamber which then connected to the left ventricle, thus producing hemodynamics of totally anomalous systemic venous connection. We propose an algorithm for evaluation of this hemodynamic combination and discuss management options. We also intend to clarify the potential differences between connection and drainage, with particular attention to the arrangement of atrial appendages. Even though the hemodynamics may be comparable, in anatomic terms, both systemic and pulmonary venoatrial connection will always be anomalous with isomeric atrial appendages.

  2. 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 ...

  3. 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....

  4. Isolated left-sided partial anomalous pulmonary venous connection in a child.

    Science.gov (United States)

    Onan, İsmihan Selen; Sen, Onur; Gökalp, Selman; Onan, Burak

    2017-09-01

    Isolated left-sided partial anomalous pulmonary venous connection with intact interatrial septum is a rare diagnosis in childhood. In these cases, a vertical vein drains the left upper pulmonary lobe into the brachiocephalic vein and finally to the right atrium. Surgical treatment is performed to prevent right ventricular failure and pulmonary artery disease in advanced age. In this report, the rare entity of isolated left-sided anomalous pulmonary venous connection in a 14-year-old girl and successful minimally invasive surgery without cardiopulmonary bypass are described.

  5. Anomalous Connection of the Right Pulmonary Vein to the Coronary Sinus in a Young Infant

    Directory of Open Access Journals (Sweden)

    Chi-Lin Ho

    2014-10-01

    Full Text Available Partial anomalous pulmonary venous connection (PAPVC is a rare congenital heart disease. Among previous cases, anomalous connection of the right pulmonary vein (RPV to the coronary sinus (CS was seldom reported. Here, we report an 8-month-old girl, initially presenting with congestive heart failure, who had this rare anomaly with moderate-sized secundum atrial septal defect (ASD. After confirmation by multi-detector row computed tomography (MDCT and cardiac catheterization, the infant underwent a successful surgical repair. To our knowledge, this is the first reported infant with this kind of rare anomaly.

  6. Comprehensive evaluation of anomalous pulmonary venous connection by electron beam computed tomography as compared with ultrasound

    International Nuclear Information System (INIS)

    Zhang Shaoxiong; Dai Ruping; Bai Hua; He Sha; Jing Baolian

    1999-01-01

    Objective: To investigate the clinical value of electron beam computed tomography (EBCT) in diagnosis of anomalous pulmonary venous connection. Methods: Retrospective analysis on 14 cases with anomalous pulmonary venous connection was performed using EBCT volume scan. The slice thickness and scan time were 3 mm and 100 ms respectively. Non-ionic contrast medium was applied. Three dimensional reconstruction of EBCT images were carried out on all cases. Meanwhile, ultrasound echocardiography was performed on all patients. Conventional cardiovascular angiography was performed on 8 patients and 2 cases received operation. Results: Ten patients with total anomalous pulmonary venous connection, including 6 cases of supra-cardiac type and 4 cases of cardiac type, were proved by EBCT examination. Among them, 3 cases of abnormal pulmonary venous drainage were not revealed by conventional cardiovascular angiography. Among four patients with partial pulmonary venous connection, including cardiac type in 2 cases, supra-cardiac type and infra-cardiac type in 1 case respectively, only one of them was demonstrated by echocardiography. Conclusion: EBCT has significant value in diagnosis of anomalous pulmonary venous connection which may not be detectable with echocardiography or even cardiovascular angiography

  7. Anomalous Transport in Natural Fracture Networks Induced by Tectonic Stress

    Science.gov (United States)

    Kang, P. K.; Lei, Q.; Lee, S.; Dentz, M.; Juanes, R.

    2017-12-01

    Fluid flow and transport in fractured rock controls many natural and engineered processes in the subsurface. However, characterizing flow and transport through fractured media is challenging due to the high uncertainty and large heterogeneity associated with fractured rock properties. In addition to these "static" challenges, geologic fractures are always under significant overburden stress, and changes in the stress state can lead to changes in the fracture's ability to conduct fluids. While confining stress has been shown to impact fluid flow through fractures in a fundamental way, the impact of confining stress on transportthrough fractured rock remains poorly understood. The link between anomalous (non-Fickian) transport and confining stress has been shown, only recently, at the level of a single rough fracture [1]. Here, we investigate the impact of geologic (tectonic) stress on flow and tracer transport through natural fracture networks. We model geomechanical effects in 2D fractured rock by means of a finite-discrete element method (FEMDEM) [2], which can capture the deformation of matrix blocks, reactivation of pre-existing fractures, and propagation of new cracks, upon changes in the stress field. We apply the model to a fracture network extracted from the geological map of an actual rock outcrop to obtain the aperture field at different stress conditions. We then simulate fluid flow and particle transport through the stressed fracture networks. We observe that anomalous transport emerges in response to confining stress on the fracture network, and show that the stress state is a powerful determinant of transport behavior: (1) An anisotropic stress state induces preferential flow paths through shear dilation; (2) An increase in geologic stress increases aperture heterogeneity that induces late-time tailing of particle breakthrough curves. Finally, we develop an effective transport model that captures the anomalous transport through the stressed fracture

  8. Detecting anomalous traders using multi-slice network analysis

    Science.gov (United States)

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi; Zhang, Yuqing

    2017-05-01

    Manipulation is an important issue for both developed and emerging stock markets. Many efforts have been made to detect manipulation in stock market. However, it is still an open problem to identify the fraudulent traders, especially when they collude with each other. In this paper, we focus on the problem of identifying anomalous traders using the transaction data of 8 manipulated stocks and 42 non-manipulated stocks during a one-year period. For each stock, we construct a multi-slice trading network to characterize the daily trading behavior and the cross-day participation of each trader. Comparing the multi-slice trading network of manipulated stocks and non-manipulated stocks with their randomized version, we find that manipulated stocks exhibit high number of trader pairs that trade with each other in multiple days and high deviation from randomized network at correlation between trading frequency and trading activity. These findings are effective at distinguishing manipulated stocks from non-manipulated ones and at identifying anomalous traders.

  9. 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.

  10. Fluctuation-Stabilized Marginal Networks and Anomalous Entropic Elasticity

    NARCIS (Netherlands)

    Dennison, M.; Sheinman, M.; Storm, C.; Mac Kintosh, F.C.

    2013-01-01

    We study the elastic properties of thermal networks of Hookean springs. In the purely mechanical limit, such systems are known to have a vanishing rigidity when their connectivity falls below a critical, isostatic value. In this work, we show that thermal networks exhibit a nonzero shear modulus G

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

    Science.gov (United States)

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

    2015-07-01

    Here we report a neonatal case of total anomalous pulmonary venous connection with left lung agenesis. Diagnostic imaging demonstrated that the left pulmonary veins were totally absent and the right pulmonary veins connected with the common pulmonary chamber. Drainage from the common pulmonary venous chamber entered the persistent left suerior vena cava. In addition, it revealed complete absence of the left main bronchus and left lung vessels. The neonate successfully underwent surgical repair 18 days after birth. © The Author(s) 2014.

  12. Finite connectivity attractor neural networks

    International Nuclear Information System (INIS)

    Wemmenhove, B; Coolen, A C C

    2003-01-01

    We study a family of diluted attractor neural networks with a finite average number of (symmetric) connections per neuron. As in finite connectivity spin glasses, their equilibrium properties are described by order parameter functions, for which we derive an integral equation in replica symmetric approximation. A bifurcation analysis of this equation reveals the locations of the paramagnetic to recall and paramagnetic to spin-glass transition lines in the phase diagram. The line separating the retrieval phase from the spin-glass phase is calculated at zero temperature. All phase transitions are found to be continuous

  13. Finite connectivity attractor neural networks

    Science.gov (United States)

    Wemmenhove, B.; Coolen, A. C. C.

    2003-09-01

    We study a family of diluted attractor neural networks with a finite average number of (symmetric) connections per neuron. As in finite connectivity spin glasses, their equilibrium properties are described by order parameter functions, for which we derive an integral equation in replica symmetric approximation. A bifurcation analysis of this equation reveals the locations of the paramagnetic to recall and paramagnetic to spin-glass transition lines in the phase diagram. The line separating the retrieval phase from the spin-glass phase is calculated at zero temperature. All phase transitions are found to be continuous.

  14. Anomalous diffusion on 2d randomly oriented diode networks

    International Nuclear Information System (INIS)

    Aydiner, E.; Kiymach, K.

    2002-01-01

    In this work, we have studied the diffusion properties of a randomly oriented two- dimensional diode network, using Monte Carlo Simulation method. The characteristic exponent α of the diffusion is obtained against the reverse transition probability W γ . We have found two critical values of W γ ; 0.003 and 0.4. α has been found to be 0.376 for W γ ≤ 0.003, and ≅ 1 for W γ ≥ 0.4 . For W γ >0.4 normal diffusion, and for 0.003≤W γ ≤0.4 anomalous sub-diffusion are observed. But for W γ ≤0.003 there seems to be no diffusion at all

  15. Supracardiac total anomalous pulmonary venous connection with a descending vertical vein.

    Science.gov (United States)

    Shah, Sejal; Singh, Mukesh; John, Colin; Maheshwari, Sunita

    2009-10-01

    The commonly used Darling classification for total anomalous pulmonary venous connection (TAPVC) consists of supracardiac, cardiac, infracardiac, and mixed types (Craig et al., Lab Invest 6:44-64, 1967). In supracardiac TAPVC, the common pulmonary vein drains superiorly into the left innominate vein, the superior vena cava, or the azygos vein by way of an ascending vertical vein. We describe a case of supracardiac TAPVC draining into the azygos vein atypically by way of a descending vertical vein.

  16. 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.)

  17. 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.

  18. k-connectivity for confined random networks

    Science.gov (United States)

    Georgiou, Orestis; Dettmann, Carl P.; Coon, Justin P.

    2013-07-01

    k-connectivity is an important measure of network robustness and resilience to random faults and disruptions. We undertake both local and global approaches to k-connectivity and calculate closed-form analytic formulas for the probability that a confined random network remains fully connected after the removal of k - 1 nodes. Our analysis reveals that k-connectivity is governed by microscopic details of the network domain such as sharp corners rather than the macroscopic total volume. Hence, our results can aid in the design of reliable networks, an important problem in, e.g., wireless ad hoc and sensor networks.

  19. Are we connected? : Ports in Global Networks

    NARCIS (Netherlands)

    R.A. Zuidwijk (Rob)

    2015-01-01

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

  20. Tc-99m MAA findings in dilated cardiomyopathy with partial anomalous venous connections.

    Science.gov (United States)

    Ishii, Shirou; Shishido, Fumio; Miyajima, Masayuki; Sakuma, Koutarou; Shigihara, Takeshi; Kikuchi, Ken

    2011-07-01

    Tc-99m MAA showed asymmetric uptake in the lung field in a 21-year-old man with dilated cardiomyopathy. CT revealed partial anomalous venous connections in the left upper lobe. Angiogram of the left pulmonary upper lobe showed all the contrast material drained into the left vertical vein. The possible cause of relative increase in the left upper lobe blood flow is that right pulmonary blood flow is slowed by the high pressure in the left atrium due to dilated cardiomyopathy, whereas the flow from the left upper lobe drains into the superior vena cava which has less pressure than left atrium.

  1. Switch-connected HyperX network

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Dong; Heidelberger, Philip

    2018-02-13

    A network system includes a plurality of sub-network planes and global switches. The sub-network planes have a same network topology as each other. Each of the sub-network planes includes edge switches. Each of the edge switches has N ports. Each of the global switches is configured to connect a group of edge switches at a same location in the sub-network planes. In each of the sub-network planes, some of the N ports of each of the edge switches are connected to end nodes, and others of the N ports are connected to other edge switches in the same sub-network plane, other of the N ports are connected to at least one of the global switches.

  2. Leadership Networking Connect, Collaborate, Create

    CERN Document Server

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

    2011-01-01

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

  3. Cross-Connects in Transmission Networks

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Cross-Connects in Transmission Networks. Cross-connects groom/switch traffic at various granularities. Narrow-band (64 kbps granularity); Wide-band (2/1.5 Mbps granularity); Broad-band (34/45/155 Mbps granularity). Large cross-connects are typically used in a ...

  4. 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.

  5. Node self-connections in network metrics.

    Science.gov (United States)

    Saura, Santiago

    2018-02-01

    Zamborain-Mason et al. (Ecol. Lett., 20, 2017, 815-831) state that they have newly proposed network metrics that account for node self-connections. Network metrics incorporating node self-connections, also referred to as intranode (intrapatch) connectivity, were however already proposed before and have been widely used in a variety of conservation planning applications. © 2017 The Author. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

  6. Low-stress bicycling and network connectivity.

    Science.gov (United States)

    2012-05-01

    For a bicycling network to attract the widest possible segment of the population, its most fundamental attribute should be low-stress connectivity, that is, providing routes between peoples origins and destinations that do not require cyclists to ...

  7. Ecological connectivity networks in rapidly expanding cities.

    Science.gov (United States)

    Nor, Amal Najihah M; Corstanje, Ron; Harris, Jim A; Grafius, Darren R; Siriwardena, Gavin M

    2017-06-01

    Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow ( Passer montanus ) and Yellow-vented bulbul ( Pycnonotus goiavier ) in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines). The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance) were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such models for

  8. Total Anomalous Pulmonary Venous Connection: Preoperative Anatomy, Physiology, Imaging, and Interventional Management of Postoperative Pulmonary Venous Obstruction.

    Science.gov (United States)

    Files, Matthew D; Morray, Brian

    2017-06-01

    Total anomalous pulmonary venous connection refers to a spectrum of cardiac anomalies where the pulmonary veins fail to return to the left atrium and the pulmonary venous blood returns through a systemic vein or directly to the right atrium. There is a wide anatomical variety of venous connections and degrees of pulmonary venous obstruction that affect the presentation, surgical repair, and outcomes. In this review, we explore the preoperative physiology, echocardiographic diagnosis, and approach to postoperative complications.

  9. Default Mode Network Connectivity in Stroke Patients.

    Science.gov (United States)

    Tuladhar, Anil Man; Snaphaan, Liselore; Shumskaya, Elena; Rijpkema, Mark; Fernandez, Guillén; Norris, David G; de Leeuw, Frank-Erik

    2013-01-01

    The pathophysiology of episodic memory dysfunction after infarction is not completely understood. It has been suggested that infarctions located anywhere in the brain can induce widespread effects causing disruption of functional networks of the cortical regions. The default mode network, which includes the medial temporal lobe, is a functional network that is associated with episodic memory processing. We investigated whether the default mode network activity is reduced in stroke patients compared to healthy control subjects in the resting state condition. We assessed the whole brain network properties during resting state functional MRI in 21 control subjects and 20 'first-ever' stroke patients. Patients were scanned 9-12 weeks after stroke onset. Stroke lesions were located in various parts of the brain. Independent component analyses were conducted to identify the default mode network and to compare the group differences of the default mode network. Furthermore, region-of-interest based analysis was performed to explore the functional connectivity between the regions of the default mode network. Stroke patients performed significantly worse than control subjects on the delayed recall score on California verbal learning test. We found decreased functional connectivity in the left medial temporal lobe, posterior cingulate and medial prefrontal cortical areas within the default mode network and reduced functional connectivity between these regions in stroke patients compared with controls. There were no significant volumetric differences between the groups. These results demonstrate that connectivity within the default mode network is reduced in 'first-ever' stroke patients compared to control subjects. This phenomenon might explain the occurrence of post-stroke cognitive dysfunction in stroke patients.

  10. Superior repair: A useful approach for some anatomic variants of total anomalous pulmonary venous connection

    Directory of Open Access Journals (Sweden)

    Kelechi E Okonta

    2013-01-01

    Full Text Available Background: Total anomalous pulmonary venous connection (TAPVC occurs when all the four pulmonary veins drain to the right atrium or to tributaries of the systemic veins. There have been various published techniques for the repair but none has been agreed on for the different anatomical variants that may be encountered during surgery. Patients and Methods: Between January 2005 and June 2010 the data of 6 of 18 patients who had surgical repair using the superior approach were retrospectively reviewed.Three patients had long narrow venous stalk connecting the coronary sinus to venous confluence; two had the right pulmonary veins draining to superior vena cava (SVC and left pulmonary veins to left lateral wall of SVC and one had an obstruction at entrance of Pulmonary Vein into venous confluence. Results: Five patients initially had the superior approach while one had transatrial with unroofing of the coronary sinus. Two had a concomitant Wardens procedure. The mean aortic cross clamping was 87.5 (60-125 min, the mean cardiopulmonary bypass time should have min as unit of 127.8 (100-180, the mean Intensive Care Unit (ICU stay of 2.5 (2-4 days and the mean hospital stay 8.2 (7-9 days. One patient died at early post-operation from low cardiac outputand five had an uneventful post-operative course and had remained stable until date. Conclusion: In our experience, the superior approach was an effective alternative approach for some anatomic variants of TAPVC that may be unexpectedly encountered during operation and also useful surgical approach for older children.

  11. Connectivity, topology and dynamics in climate networks

    Czech Academy of Sciences Publication Activity Database

    Paluš, Milan; Hartman, David; Hlinka, Jaroslav; Vejmelka, Martin

    2012-01-01

    Roč. 14, - (2012), s. 8397 ISSN 1607-7962. [European Geosciences Union General Assembly 2012. 22.04.2012-27.04.2012, Vienna] R&D Projects: GA ČR GCP103/11/J068 Institutional support: RVO:67985807 Keywords : complex networks * climate network * connectivity * entropy rate * El Nino Southern Oscillation * North Atlantic Oscillation Subject RIV: BB - Applied Statistics, Operational Research

  12. Discerning connectivity from dynamics in climate networks

    Czech Academy of Sciences Publication Activity Database

    Paluš, Milan; Hartman, David; Hlinka, Jaroslav; Vejmelka, Martin

    2011-01-01

    Roč. 18, č. 5 (2011), s. 751-763 ISSN 1023-5809 R&D Projects: GA ČR GCP103/11/J068 Institutional research plan: CEZ:AV0Z10300504 Keywords : complex networks * climate dynamics * connectivity * North Atlantic Oscillation * solar activity Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.597, year: 2011

  13. 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.

  14. Anomalous contagion and renormalization in networks with nodal mobility

    Science.gov (United States)

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

    2016-07-01

    A common occurrence in everyday human activity is where people join, leave and possibly rejoin clusters of other individuals —whether this be online (e.g. social media communities) or in real space (e.g. popular meeting places such as cafes). In the steady state, the resulting interaction network would appear static over time if the identities of the nodes are ignored. Here we show that even in this static steady-state limit, a non-zero nodal mobility leads to a diverse set of outbreak profiles that is dramatically different from known forms, and yet matches well with recent real-world social outbreaks. We show how this complication of nodal mobility can be renormalized away for a particular class of networks.

  15. Default mode network connectivity during task execution.

    Science.gov (United States)

    Vatansever, D; Menon, D K; Manktelow, A E; Sahakian, B J; Stamatakis, E A

    2015-11-15

    Initially described as task-induced deactivations during goal-directed paradigms of high attentional load, the unresolved functionality of default mode regions has long been assumed to interfere with task performance. However, recent evidence suggests a potential default mode network involvement in fulfilling cognitive demands. We tested this hypothesis in a finger opposition paradigm with task and fixation periods which we compared with an independent resting state scan using functional magnetic resonance imaging and a comprehensive analysis pipeline including activation, functional connectivity, behavioural and graph theoretical assessments. The results indicate task specific changes in the default mode network topography. Behaviourally, we show that increased connectivity of the posterior cingulate cortex with the left superior frontal gyrus predicts faster reaction times. Moreover, interactive and dynamic reconfiguration of the default mode network regions' functional connections illustrates their involvement with the task at hand with higher-level global parallel processing power, yet preserved small-world architecture in comparison with rest. These findings demonstrate that the default mode network does not disengage during this paradigm, but instead may be involved in task relevant processing. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. Predictability of anomalous transport on lattice networks with quenched disorder.

    Science.gov (United States)

    Kang, Peter K; Dentz, Marco; Juanes, Ruben

    2011-03-01

    We study stochastic transport through a lattice network with quenched disorder and evaluate the limits of predictability of the transport behavior across realizations of spatial heterogeneity. Within a Lagrangian framework, we perform coarse graining, noise averaging, and ensemble averaging, to obtain an effective transport model for the average particle density and its fluctuations between realizations. We show that the average particle density is described exactly by a continuous time random walk (CTRW), and the particle density variance is quantified by a novel two-particle CTRW.

  17. 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)

    Chan, Sherwin S.; Whitehead, Kevin K.; Kim, Timothy S.; Fu, Gregory L.; Fogel, Mark A.; Harris, Matthew A.; Keller, Marc S.

    2015-01-01

    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 2 vs. 118 ± 30 mL/m 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.)

  18. 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.)

  19. Micro-generation network connection (renewables)

    Energy Technology Data Exchange (ETDEWEB)

    Thornycroft, J.; Russell, T.; Curran, J.

    2003-07-01

    The drive to reduce emissions of carbon dioxide will result in an increase in the number of small generation units seeking connection to the electric power distribution network. The objectives of this study were to consider connection issues relating to micro-generation from renewables and their integration into the UK distribution network. The document is divided into two sections. The first section describes the present system which includes input from micro-generation, the technical impacts and the financial considerations. The second part discusses technical, financial and governance options for the future. A summary of preferred options and recommendations is given. The study was carried out by the Halcrow Group Ltd under contract to the DTI.

  20. Structural Connectivity Networks of Transgender People

    Science.gov (United States)

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

    2015-01-01

    Although previous investigations of transsexual people have focused on regional brain alterations, evaluations on a network level, especially those structural in nature, are largely missing. Therefore, we investigated the structural connectome of 23 female-to-male (FtM) and 21 male-to-female (MtF) transgender patients before hormone therapy as compared with 25 female and 25 male healthy controls. Graph theoretical analysis of whole-brain probabilistic tractography networks (adjusted for differences in intracranial volume) showed decreased hemispheric connectivity ratios of subcortical/limbic areas for both transgender groups. Subsequent analysis revealed that this finding was driven by increased interhemispheric lobar connectivity weights (LCWs) in MtF transsexuals and decreased intrahemispheric LCWs in FtM patients. This was further reflected on a regional level, where the MtF group showed mostly increased local efficiencies and FtM patients decreased values. Importantly, these parameters separated each patient group from the remaining subjects for the majority of significant findings. This work complements previously established regional alterations with important findings of structural connectivity. Specifically, our data suggest that network parameters may reflect unique characteristics of transgender patients, whereas local physiological aspects have been shown to represent the transition from the biological sex to the actual gender identity. PMID:25217469

  1. Structural Connectivity Networks of Transgender People.

    Science.gov (United States)

    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

    2015-10-01

    Although previous investigations of transsexual people have focused on regional brain alterations, evaluations on a network level, especially those structural in nature, are largely missing. Therefore, we investigated the structural connectome of 23 female-to-male (FtM) and 21 male-to-female (MtF) transgender patients before hormone therapy as compared with 25 female and 25 male healthy controls. Graph theoretical analysis of whole-brain probabilistic tractography networks (adjusted for differences in intracranial volume) showed decreased hemispheric connectivity ratios of subcortical/limbic areas for both transgender groups. Subsequent analysis revealed that this finding was driven by increased interhemispheric lobar connectivity weights (LCWs) in MtF transsexuals and decreased intrahemispheric LCWs in FtM patients. This was further reflected on a regional level, where the MtF group showed mostly increased local efficiencies and FtM patients decreased values. Importantly, these parameters separated each patient group from the remaining subjects for the majority of significant findings. This work complements previously established regional alterations with important findings of structural connectivity. Specifically, our data suggest that network parameters may reflect unique characteristics of transgender patients, whereas local physiological aspects have been shown to represent the transition from the biological sex to the actual gender identity. © The Author 2014. Published by Oxford University Press.

  2. Specializing network analysis to detect anomalous insider actions

    Science.gov (United States)

    Chen, You; Nyemba, Steve; Zhang, Wen; Malin, Bradley

    2012-01-01

    Collaborative information systems (CIS) enable users to coordinate efficiently over shared tasks in complex distributed environments. For flexibility, they provide users with broad access privileges, which, as a side-effect, leave such systems vulnerable to various attacks. Some of the more damaging malicious activities stem from internal misuse, where users are authorized to access system resources. A promising class of insider threat detection models for CIS focuses on mining access patterns from audit logs, however, current models are limited in that they assume organizations have significant resources to generate label cases for training classifiers or assume the user has committed a large number of actions that deviate from “normal” behavior. In lieu of the previous assumptions, we introduce an approach that detects when specific actions of an insider deviate from expectation in the context of collaborative behavior. Specifically, in this paper, we introduce a specialized network anomaly detection model, or SNAD, to detect such events. This approach assesses the extent to which a user influences the similarity of the group of users that access a particular record in the CIS. From a theoretical perspective, we show that the proposed model is appropriate for detecting insider actions in dynamic collaborative systems. From an empirical perspective, we perform an extensive evaluation of SNAD with the access logs of two distinct environments: the patient record access logs a large electronic health record system (6,015 users, 130,457 patients and 1,327,500 accesses) and the editing logs of Wikipedia (2,394,385 revisors, 55,200 articles and 6,482,780 revisions). We compare our model with several competing methods and demonstrate SNAD is significantly more effective: on average it achieves 20–30% greater area under an ROC curve. PMID:23399988

  3. Four-dimensional sonography with spatiotemporal image correlation and tomographic ultrasound imaging in the prenatal diagnosis of anomalous pulmonary venous connections.

    Science.gov (United States)

    Peng, Ruan; Xie, Hong-Ning; Du, Liu; Shi, Hui-Juan; Zheng, Ju; Zhu, Yun-Xiao

    2012-10-01

    To determine whether the use of 4-dimensional (4D) sonography with spatiotemporal image correlation (STIC) and tomographic ultrasound imaging (TUI) can provide additional information with respect to 2-dimensional (2D) echocardiography in the prenatal diagnosis of anomalous pulmonary venous connections. The study population consisted of 10 cases that were initially suspected to have total or partial anomalous pulmonary venous connections by prenatal 2D echocardiography between January 2008 and April 2011. All 10 cases were further examined and analyzed by 4D sonography with STIC-TUI. Detailed postnatal surgery or autopsy was performed on all 10 fetuses. Total anomalous pulmonary venous connections were found in 5 cases, and a partial connection was diagnosed in 1 fetus postnatally. The remaining 4 cases were confirmed to have normal pulmonary venous connections. Four of the 5 fetuses with anomalous pulmonary venous connections had an additional major cardiac defect; 1 fetus had an isolated connection. Anomalous drainage was supracardiac to the superior vena cava in 2 cases, cardiac to the coronary sinus in 3, and partially infracardiac to the portal vein in remaining case. The pulmonary venous connections were completely and correctly visualized with 2D echocardiography in 2 of the 10 cases, partially identified in 4, and not distinguished completely in 4. Four-dimensional sonography imaging with STIC-TUI clearly visualized the connections in 9 of the 10 cases, and the remaining case was partially identified. Four-dimensional sonography with STIC-TUI facilitates visualization of pulmonary venous connections, thus supplying additional information with respect to 2D echocardiography in the prenatal diagnosis of anomalous pulmonary venous connections.

  4. Manipulating connectivity and electrical conductivity in metallic nanowire networks.

    Science.gov (United States)

    Nirmalraj, Peter N; Bellew, Allen T; Bell, Alan P; Fairfield, Jessamyn A; McCarthy, Eoin K; O'Kelly, Curtis; Pereira, Luiz F C; Sorel, Sophie; Morosan, Diana; Coleman, Jonathan N; Ferreira, Mauro S; Boland, John J

    2012-11-14

    Connectivity in metallic nanowire networks with resistive junctions is manipulated by applying an electric field to create materials with tunable electrical conductivity. In situ electron microscope and electrical measurements visualize the activation and evolution of connectivity within these networks. Modeling nanowire networks, having a distribution of junction breakdown voltages, reveals universal scaling behavior applicable to all network materials. We demonstrate how local connectivity within these networks can be programmed and discuss material and device applications.

  5. Connectivity Restoration in Wireless Sensor Networks via Space Network Coding.

    Science.gov (United States)

    Uwitonze, Alfred; Huang, Jiaqing; Ye, Yuanqing; Cheng, Wenqing

    2017-04-20

    The problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments.

  6. 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.

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

    Science.gov (United States)

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

    2011-11-29

    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.

  8. Functional network connectivity alterations in schizophrenia and depression.

    Science.gov (United States)

    Wu, Xing-Jie; Zeng, Ling-Li; Shen, Hui; Yuan, Lin; Qin, Jian; Zhang, Peng; Hu, Dewen

    2017-05-30

    There is a high degree of overlap between the symptoms of major depressive disorder (MDD) and schizophrenia, but it remains unclear whether the similar symptoms are derived from convergent alterations in functional network connectivity. In this study, we performed a group independent component analysis on resting-state functional MRI data from 20 MDD patients, 24 schizophrenia patients, and 43 matched healthy controls. The functional network connectivity analysis revealed that, compared to healthy controls, the MDD and schizophrenia patients exhibited convergent decreased positive connectivity between the left and right fronto-parietal control network and decreased negative connectivity between the left control and medial visual networks. Furthermore, the MDD patients showed decreased negative connectivity between the left control and auditory networks, and the schizophrenia patients showed decreased positive connectivity between the bilateral control and language networks and decreased negative connectivity between the right control and dorsal attention networks. The convergent network connectivity alterations may underlie the common primary control and regulation disorders, and the divergent connectivity alterations may enable the distinction between the two disorders. All of the convergent and divergent network connectivity alterations were relevant to the control network, suggesting an important role of the network in the pathophysiology of MDD and schizophrenia. Copyright © 2017. Published by Elsevier B.V.

  9. Light Manipulation in Metallic Nanowire Networks with Functional Connectivity

    KAUST Repository

    Galinski, Henning

    2016-12-27

    Guided by ideas from complex systems, a new class of network metamaterials is introduced for light manipulation, which are based on the functional connectivity among heterogeneous subwavelength components arranged in complex networks. The model system is a nanonetwork formed by dealloying a metallic thin film. The connectivity of the network is deterministically controlled, enabling the formation of tunable absorbing states.

  10. Anomalous transport in disordered fracture networks: Spatial Markov model for dispersion with variable injection modes

    Science.gov (United States)

    Kang, Peter K.; Dentz, Marco; Le Borgne, Tanguy; Lee, Seunghak; Juanes, Ruben

    2017-08-01

    We investigate tracer transport on random discrete fracture networks that are characterized by the statistics of the fracture geometry and hydraulic conductivity. While it is well known that tracer transport through fractured media can be anomalous and particle injection modes can have major impact on dispersion, the incorporation of injection modes into effective transport modeling has remained an open issue. The fundamental reason behind this challenge is that-even if the Eulerian fluid velocity is steady-the Lagrangian velocity distribution experienced by tracer particles evolves with time from its initial distribution, which is dictated by the injection mode, to a stationary velocity distribution. We quantify this evolution by a Markov model for particle velocities that are equidistantly sampled along trajectories. This stochastic approach allows for the systematic incorporation of the initial velocity distribution and quantifies the interplay between velocity distribution and spatial and temporal correlation. The proposed spatial Markov model is characterized by the initial velocity distribution, which is determined by the particle injection mode, the stationary Lagrangian velocity distribution, which is derived from the Eulerian velocity distribution, and the spatial velocity correlation length, which is related to the characteristic fracture length. This effective model leads to a time-domain random walk for the evolution of particle positions and velocities, whose joint distribution follows a Boltzmann equation. Finally, we demonstrate that the proposed model can successfully predict anomalous transport through discrete fracture networks with different levels of heterogeneity and arbitrary tracer injection modes.

  11. Chaotic wandering motion in connected neural networks

    Science.gov (United States)

    Ohno, Takashi; Shimizu, Toshihiro

    2000-06-01

    A new type of neural network is proposed. In a system, which consists of one host network and three terminal networks, the associative memory problem is investigated. In each network different patterns are stored. It is shown that each network can retrieve the patterns stored in other networks, and the terminal networks exhibit synchronized behavior. The time evolution and the mechanism of retrieval investigated. .

  12. Total anomalous pulmonary venous connection in a 9-year-old girl at Usmanu Danfodiyo University Teaching Hospital, Sokoto, Nigeria

    Directory of Open Access Journals (Sweden)

    Usman Muhammad Sani

    2016-01-01

    Full Text Available Total anomalous pulmonary venous connection (TAPVC is a rare cyanotic congenital heart disease in which all the four pulmonary veins drain into the right atrium instead of the left. Without surgical intervention, 80% of the patients die before the age of 1 year. We report a 9-year-old girl with unrepaired supracardiac TAPVC complicated by severe pulmonary artery hypertension. The patient was managed conservatively including the use of pulmonary antihypertensive (sildenafil, with significant improvement. She is currently on follow-up at our pediatric cardiology clinic. TAPVC requires surgical intervention in early infancy to prevent the onset of pulmonary hypertension, which may contraindicate surgery. High index of suspicion and improved diagnostic skill will enhance early diagnosis and enable timely intervention.

  13. Multimodal Hyper-connectivity Networks for MCI Classification.

    Science.gov (United States)

    Li, Yang; Gao, Xinqiang; Jie, Biao; Yap, Pew-Thian; Kim, Min-Jeong; Wee, Chong-Yaw; Shen, Dinggang

    2017-09-01

    Hyper-connectivity network is a network where every edge is connected to more than two nodes, and can be naturally denoted using a hyper-graph. Hyper-connectivity brain network, either based on structural or functional interactions among the brain regions, has been used for brain disease diagnosis. However, the conventional hyper-connectivity network is constructed solely based on single modality data, ignoring potential complementary information conveyed by other modalities. The integration of complementary information from multiple modalities has been shown to provide a more comprehensive representation about the brain disruptions. In this paper, a novel multimodal hyper-network modelling method was proposed for improving the diagnostic accuracy of mild cognitive impairment (MCI). Specifically, we first constructed a multimodal hyper-connectivity network by simultaneously considering information from diffusion tensor imaging and resting-state functional magnetic resonance imaging data. We then extracted different types of network features from the hyper-connectivity network, and further exploited a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Our proposed multimodal hyper-connectivity network demonstrated a better MCI classification performance than the conventional single modality based hyper-connectivity networks.

  14. Default network connectivity in medial temporal lobe amnesia.

    Science.gov (United States)

    Hayes, Scott M; Salat, David H; Verfaellie, Mieke

    2012-10-17

    There is substantial overlap between the brain regions supporting episodic memory and the default network. However, in humans, the impact of bilateral medial temporal lobe (MTL) damage on a large-scale neural network such as the default mode network is unknown. To examine this issue, resting fMRI was performed with amnesic patients and control participants. Seed-based functional connectivity analyses revealed robust default network connectivity in amnesia in cortical default network regions such as medial prefrontal cortex, posterior medial cortex, and lateral parietal cortex, as well as evidence of connectivity to residual MTL tissue. Relative to control participants, decreased posterior cingulate cortex connectivity to MTL and increased connectivity to cortical default network regions including lateral parietal and medial prefrontal cortex were observed in amnesic patients. In contrast, somatomotor network connectivity was intact in amnesic patients, indicating that bilateral MTL lesions may selectively impact the default network. Changes in default network connectivity in amnesia were largely restricted to the MTL subsystem, providing preliminary support from MTL amnesic patients that the default network can be fractionated into functionally and structurally distinct components. To our knowledge, this is the first examination of the default network in amnesia.

  15. Abnormal functional network connectivity among resting-state networks in children with frontal lobe epilepsy.

    Science.gov (United States)

    Widjaja, E; Zamyadi, M; Raybaud, C; Snead, O C; Smith, M L

    2013-12-01

    Epilepsy is considered a disorder of neural networks. The aims of this study were to assess functional connectivity within resting-state networks and functional network connectivity across resting-state networks by use of resting-state fMRI in children with frontal lobe epilepsy and to relate changes in resting-state networks with neuropsychological function. Fifteen patients with frontal lobe epilepsy and normal MR imaging and 14 healthy control subjects were recruited. Spatial independent component analysis was used to identify the resting-state networks, including frontal, attention, default mode network, sensorimotor, visual, and auditory networks. The Z-maps of resting-state networks were compared between patients and control subjects. The relation between abnormal connectivity and neuropsychological function was assessed. Correlations from all pair-wise combinations of independent components were performed for each group and compared between groups. The frontal network was the only network that showed reduced connectivity in patients relative to control subjects. The remaining 5 networks demonstrated both reduced and increased functional connectivity within resting-state networks in patients. There was a weak association between connectivity in frontal network and executive function (P = .029) and a significant association between sensorimotor network and fine motor function (P = .004). Control subjects had 79 pair-wise independent components that showed significant temporal coherence across all resting-state networks except for default mode network-auditory network. Patients had 66 pairs of independent components that showed significant temporal coherence across all resting-state networks. Group comparison showed reduced functional network connectivity between default mode network-attention, frontal-sensorimotor, and frontal-visual networks and increased functional network connectivity between frontal-attention, default mode network-sensorimotor, and frontal

  16. Accelerated Distributed Dual Averaging Over Evolving Networks of Growing Connectivity

    Science.gov (United States)

    Liu, Sijia; Chen, Pin-Yu; Hero, Alfred O.

    2018-04-01

    We consider the problem of accelerating distributed optimization in multi-agent networks by sequentially adding edges. Specifically, we extend the distributed dual averaging (DDA) subgradient algorithm to evolving networks of growing connectivity and analyze the corresponding improvement in convergence rate. It is known that the convergence rate of DDA is influenced by the algebraic connectivity of the underlying network, where better connectivity leads to faster convergence. However, the impact of network topology design on the convergence rate of DDA has not been fully understood. In this paper, we begin by designing network topologies via edge selection and scheduling. For edge selection, we determine the best set of candidate edges that achieves the optimal tradeoff between the growth of network connectivity and the usage of network resources. The dynamics of network evolution is then incurred by edge scheduling. Further, we provide a tractable approach to analyze the improvement in the convergence rate of DDA induced by the growth of network connectivity. Our analysis reveals the connection between network topology design and the convergence rate of DDA, and provides quantitative evaluation of DDA acceleration for distributed optimization that is absent in the existing analysis. Lastly, numerical experiments show that DDA can be significantly accelerated using a sequence of well-designed networks, and our theoretical predictions are well matched to its empirical convergence behavior.

  17. 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.…

  18. Controllability of giant connected components in a directed network.

    Science.gov (United States)

    Liu, Xueming; Pan, Linqiang; Stanley, H Eugene; Gao, Jianxi

    2017-04-01

    When controlling a complex networked system it is not feasible to control the full network because many networks, including biological, technological, and social systems, are massive in size and complexity. But neither is it necessary to control the full network. In complex networks, the giant connected components provide the essential information about the entire system. How to control these giant connected components of a network remains an open question. We derive the mathematical expression of the degree distributions for four types of giant connected components and develop an analytic tool for studying the controllability of these giant connected components. We find that for both Erdős-Rényi (ER) networks and scale-free (SF) networks with p fraction of remaining nodes, the minimum driver node density to control the giant component first increases and then decreases as p increases from zero to one, showing a peak at a critical point p=p_{m}. We find that, for ER networks, the peak value of the driver node density remains the same regardless of its average degree 〈k〉 and that it is determined by p_{m}〈k〉. In addition, we find that for SF networks the minimum driver node densities needed to control the giant components of networks decrease as the degree distribution exponents increase. Comparing the controllability of the giant components of ER networks and SF networks, we find that when the fraction of remaining nodes p is low, the giant in-connected, out-connected, and strong-connected components in ER networks have lower controllability than those in SF networks.

  19. Scholastic performance and functional connectivity of brain networks in children.

    Directory of Open Access Journals (Sweden)

    Laura Chaddock-Heyman

    Full Text Available One of the keys to understanding scholastic success is to determine the neural processes involved in school performance. The present study is the first to use a whole-brain connectivity approach to explore whether functional connectivity of resting state brain networks is associated with scholastic performance in seventy-four 7- to 9-year-old children. We demonstrate that children with higher scholastic performance across reading, math and language have more integrated and interconnected resting state networks, specifically the default mode network, salience network, and frontoparietal network. To add specificity, core regions of the dorsal attention and visual networks did not relate to scholastic performance. The results extend the cognitive role of brain networks in children as well as suggest the importance of network connectivity in scholastic success.

  20. Effect of planning for connectivity on linear reserve networks.

    Science.gov (United States)

    Lentini, Pia E; Gibbons, Philip; Carwardine, Josie; Fischer, Joern; Drielsma, Michael; Martin, Tara G

    2013-08-01

    Although the concept of connectivity is decades old, it remains poorly understood and defined, and some argue that habitat quality and area should take precedence in conservation planning instead. However, fragmented landscapes are often characterized by linear features that are inherently connected, such as streams and hedgerows. For these, both representation and connectivity targets may be met with little effect on the cost, area, or quality of the reserve network. We assessed how connectivity approaches affect planning outcomes for linear habitat networks by using the stock-route network of Australia as a case study. With the objective of representing vegetation communities across the network at a minimal cost, we ran scenarios with a range of representation targets (10%, 30%, 50%, and 70%) and used 3 approaches to account for connectivity (boundary length modifier, Euclidean distance, and landscape-value [LV]). We found that decisions regarding the target and connectivity approach used affected the spatial allocation of reserve systems. At targets ≥50%, networks designed with the Euclidean distance and LV approaches consisted of a greater number of small reserves. Hence, by maximizing both representation and connectivity, these networks compromised on larger contiguous areas. However, targets this high are rarely used in real-world conservation planning. Approaches for incorporating connectivity into the planning of linear reserve networks that account for both the spatial arrangement of reserves and the characteristics of the intervening matrix highlight important sections that link the landscape and that may otherwise be overlooked. © 2013 Society for Conservation Biology.

  1. Association between functional connectivity hubs and brain networks.

    Science.gov (United States)

    Tomasi, Dardo; Volkow, Nora D

    2011-09-01

    Functional networks are usually accessed with "resting-state" functional magnetic resonance imaging using preselected "seeds" regions. Frequently, however, the selection of the seed locations is arbitrary. Recently, we proposed local functional connectivity density mapping (FCDM), an ultrafast data-driven to locate highly connected brain regions (functional hubs). Here, we used the functional hubs obtained from local FCDM to determine the functional networks of the resting state in 979 healthy subjects without a priori hypotheses on seed locations. In addition, we computed the global functional connectivity hubs. Seven networks covering 80% of the gray matter volume were identified. Four major cortical hubs (ventral precuneus/posterior cingulate, inferior parietal cortex, cuneus, and postcentral gyrus) were linked to 4 cortical networks (default mode, dorsal attention, visual, and somatosensory). Three subcortical networks were associated to the major subcortical hubs (cerebellum, thalamus, and amygdala). The networks differed in their resting activity and topology. The higher coupling and overlap of subcortical networks was associated to higher contribution of short-range functional connectivity in thalamus and cerebellum. Whereas cortical local FCD hubs were also hubs of long-range connectivity, which corroborates the key role of cortical hubs in network architecture, subcortical hubs had minimal long-range connectivity. The significant variability among functional networks may underlie their sensitivity/resilience to neuropathology.

  2. Activating and inhibiting connections in biological network dynamics

    Directory of Open Access Journals (Sweden)

    Knight Rob

    2008-12-01

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

  3. Sensitivity of marine protected area network connectivity to atmospheric variability.

    Science.gov (United States)

    Fox, Alan D; Henry, Lea-Anne; Corne, David W; Roberts, J Murray

    2016-11-01

    International efforts are underway to establish well-connected systems of marine protected areas (MPAs) covering at least 10% of the ocean by 2020. But the nature and dynamics of ocean ecosystem connectivity are poorly understood, with unresolved effects of climate variability. We used 40-year runs of a particle tracking model to examine the sensitivity of an MPA network for habitat-forming cold-water corals in the northeast Atlantic to changes in larval dispersal driven by atmospheric cycles and larval behaviour. Trajectories of Lophelia pertusa larvae were strongly correlated to the North Atlantic Oscillation (NAO), the dominant pattern of interannual atmospheric circulation variability over the northeast Atlantic. Variability in trajectories significantly altered network connectivity and source-sink dynamics, with positive phase NAO conditions producing a well-connected but asymmetrical network connected from west to east. Negative phase NAO produced reduced connectivity, but notably some larvae tracked westward-flowing currents towards coral populations on the mid-Atlantic ridge. Graph theoretical metrics demonstrate critical roles played by seamounts and offshore banks in larval supply and maintaining connectivity across the network. Larval longevity and behaviour mediated dispersal and connectivity, with shorter lived and passive larvae associated with reduced connectivity. We conclude that the existing MPA network is vulnerable to atmospheric-driven changes in ocean circulation.

  4. Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

    Science.gov (United States)

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

    2016-01-01

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

  5. Pramipexole Modulates Interregional Connectivity Within the Sensorimotor Network.

    Science.gov (United States)

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

    2017-05-01

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

  6. Selectivity and sparseness in randomly connected balanced networks.

    Directory of Open Access Journals (Sweden)

    Cengiz Pehlevan

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

  7. Structural and functional brain networks: from connections to cognition.

    Science.gov (United States)

    Park, Hae-Jeong; Friston, Karl

    2013-11-01

    How rich functionality emerges from the invariant structural architecture of the brain remains a major mystery in neuroscience. Recent applications of network theory and theoretical neuroscience to large-scale brain networks have started to dissolve this mystery. Network analyses suggest that hierarchical modular brain networks are particularly suited to facilitate local (segregated) neuronal operations and the global integration of segregated functions. Although functional networks are constrained by structural connections, context-sensitive integration during cognition tasks necessarily entails a divergence between structural and functional networks. This degenerate (many-to-one) function-structure mapping is crucial for understanding the nature of brain networks. The emergence of dynamic functional networks from static structural connections calls for a formal (computational) approach to neuronal information processing that may resolve this dialectic between structure and function.

  8. Stability of a giant connected component in a complex network

    Science.gov (United States)

    Kitsak, Maksim; Ganin, Alexander A.; Eisenberg, Daniel A.; Krapivsky, Pavel L.; Krioukov, Dmitri; Alderson, David L.; Linkov, Igor

    2018-01-01

    We analyze the stability of the network's giant connected component under impact of adverse events, which we model through the link percolation. Specifically, we quantify the extent to which the largest connected component of a network consists of the same nodes, regardless of the specific set of deactivated links. Our results are intuitive in the case of single-layered systems: the presence of large degree nodes in a single-layered network ensures both its robustness and stability. In contrast, we find that interdependent networks that are robust to adverse events have unstable connected components. Our results bring novel insights to the design of resilient network topologies and the reinforcement of existing networked systems.

  9. Electrophysiological signatures of atypical intrinsic brain connectivity networks in autism

    Science.gov (United States)

    Shou, Guofa; Mosconi, Matthew W.; Wang, Jun; Ethridge, Lauren E.; Sweeney, John A.; Ding, Lei

    2017-08-01

    Objective. Abnormal local and long-range brain connectivity have been widely reported in autism spectrum disorder (ASD), yet the nature of these abnormalities and their functional relevance at distinct cortical rhythms remains unknown. Investigations of intrinsic connectivity networks (ICNs) and their coherence across whole brain networks hold promise for determining whether patterns of functional connectivity abnormalities vary across frequencies and networks in ASD. In the present study, we aimed to probe atypical intrinsic brain connectivity networks in ASD from resting-state electroencephalography (EEG) data via characterizing the whole brain network. Approach. Connectivity within individual ICNs (measured by spectral power) and between ICNs (measured by coherence) were examined at four canonical frequency bands via a time-frequency independent component analysis on high-density EEG, which were recorded from 20 ASD and 20 typical developing (TD) subjects during an eyes-closed resting state. Main results. Among twelve identified electrophysiological ICNs, individuals with ASD showed hyper-connectivity in individual ICNs and hypo-connectivity between ICNs. Functional connectivity alterations in ASD were more severe in the frontal lobe and the default mode network (DMN) and at low frequency bands. These functional connectivity measures also showed abnormal age-related associations in ICNs related to frontal, temporal and motor regions in ASD. Significance. Our findings suggest that ASD is characterized by the opposite directions of abnormalities (i.e. hypo- and hyper-connectivity) in the hierarchical structure of the whole brain network, with more impairments in the frontal lobe and the DMN at low frequency bands, which are critical for top-down control of sensory systems, as well as for both cognition and social skills.

  10. Abnormal network connectivity in frontotemporal dementia: evidence for prefrontal isolation.

    Science.gov (United States)

    Farb, Norman A S; Grady, Cheryl L; Strother, Stephen; Tang-Wai, David F; Masellis, Mario; Black, Sandra; Freedman, Morris; Pollock, Bruce G; Campbell, Karen L; Hasher, Lynn; Chow, Tiffany W

    2013-01-01

    Degraded social function, disinhibition, and stereotypy are defining characteristics of frontotemporal dementia (FTD), manifesting in both the behavioral variant of frontotemporal dementia (bvFTD) and semantic dementia (SD) subtypes. Recent neuroimaging research also associates FTD with alterations in the brain's intrinsic connectivity networks. The present study explored the relationship between neural network connectivity and specific behavioral symptoms in FTD. Resting-state functional magnetic resonance imaging was employed to investigate neural network changes in bvFTD and SD. We used independent components analysis (ICA) to examine changes in frontolimbic network connectivity, as well as several metrics of local network strength, such as the fractional amplitude of low-frequency fluctuations, regional homogeneity, and seed-based functional connectivity. For each analysis, we compared each FTD subgroup to healthy controls, characterizing general and subtype-unique network changes. The relationship between abnormal connectivity in FTD and behavior disturbances was explored. Across multiple analytic approaches, both bvFTD and SD were associated with disrupted frontolimbic connectivity and elevated local connectivity within the prefrontal cortex. Even after controlling for structural atrophy, prefrontal hyperconnectivity was robustly associated with apathy scores. Frontolimbic disconnection was associated with lower disinhibition scores, suggesting that abnormal frontolimbic connectivity contributes to positive symptoms in dementia. Unique to bvFTD, stereotypy was associated with elevated default network connectivity in the right angular gyrus. The behavioral variant was also associated with marginally higher apathy scores and a more diffuse pattern of prefrontal hyperconnectivity than SD. The present findings support a theory of FTD as a disorder of frontolimbic disconnection leading to unconstrained prefrontal connectivity. Prefrontal hyperconnectivity may

  11. Hyper-connectivity of functional networks for brain disease diagnosis.

    Science.gov (United States)

    Jie, Biao; Wee, Chong-Yaw; Shen, Dinggang; Zhang, Daoqiang

    2016-08-01

    Exploring structural and functional interactions among various brain regions enables better understanding of pathological underpinnings of neurological disorders. Brain connectivity network, as a simplified representation of those structural and functional interactions, has been widely used for diagnosis and classification of neurodegenerative diseases, especially for Alzheimer's disease (AD) and its early stage - mild cognitive impairment (MCI). However, the conventional functional connectivity network is usually constructed based on the pairwise correlation among different brain regions and thus ignores their higher-order relationships. Such loss of high-order information could be important for disease diagnosis, since neurologically a brain region predominantly interacts with more than one other brain regions. Accordingly, in this paper, we propose a novel framework for estimating the hyper-connectivity network of brain functions and then use this hyper-network for brain disease diagnosis. Here, the functional connectivity hyper-network denotes a network where each of its edges representing the interactions among multiple brain regions (i.e., an edge can connect with more than two brain regions), which can be naturally represented by a hyper-graph. Specifically, we first construct connectivity hyper-networks from the resting-state fMRI (R-fMRI) time series by using sparse representation. Then, we extract three sets of brain-region specific features from the connectivity hyper-networks, and further exploit a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Finally, we use multi-kernel support vector machine (SVM) for classification. The experimental results on both MCI dataset and attention deficit hyperactivity disorder (ADHD) dataset demonstrate that, compared with the conventional connectivity network-based methods, the proposed method can not only improve the classification performance, but also help

  12. Intrinsic network connectivity and own body perception in gender dysphoria.

    Science.gov (United States)

    Feusner, Jamie D; Lidström, Andreas; Moody, Teena D; Dhejne, Cecilia; Bookheimer, Susan Y; Savic, Ivanka

    2017-08-01

    Gender dysphoria (GD) is characterized by incongruence between one's identity and gender assigned at birth. The biological mechanisms of GD are unclear. We investigated brain network connectivity patterns involved in own body perception in the context of self in GD. Twenty-seven female-to-male (FtM) individuals with GD, 27 male controls, and 27 female controls underwent resting state fMRI. We compared functional connections within intrinsic connectivity networks involved in self-referential processes and own body perception -default mode network (DMN) and salience network - and visual networks, using independent components analyses. Behavioral correlates of network connectivity were also tested using self-perception ratings while viewing own body images morphed to their sex assigned at birth, and to the sex of their gender identity. FtM exhibited decreased connectivity of anterior and posterior cingulate and precuneus within the DMN compared with controls. In FtM, higher "self" ratings for bodies morphed towards the sex of their gender identity were associated with greater connectivity of the anterior cingulate within the DMN, during long viewing times. In controls, higher ratings for bodies morphed towards their gender assigned at birth were associated with right insula connectivity within the salience network, during short viewing times. Within visual networks FtM showed weaker connectivity in occipital and temporal regions. Results suggest disconnectivity within networks involved in own body perception in the context of self in GD. Moreover, perception of bodies in relation to self may be reflective rather than reflexive, as a function of mesial prefrontal processes. These may represent neurobiological correlates to the subjective disconnection between perception of body and self-identification.

  13. Default network connectivity during a working memory task.

    Science.gov (United States)

    Bluhm, Robyn L; Clark, C Richard; McFarlane, Alexander C; Moores, Kathryn A; Shaw, Marnie E; Lanius, Ruth A

    2011-07-01

    The default network exhibits correlated activity at rest and has shown decreased activation during performance of cognitive tasks. There has been little investigation of changes in connectivity of this network during task performance. In this study, we examined task-related modulation of connectivity between two seed regions from the default network posterior cingulated cortex (PCC) and medial prefrontal cortex (mPFC) and the rest of the brain in 12 healthy adults. The purpose was to determine (1) whether connectivity within the default network differs between a resting state and performance of a cognitive (working memory) task and (2) whether connectivity differs between these nodes of the default network and other brain regions, particularly those implicated in cognitive tasks. There was little change in connectivity with the other main areas of the default network for either seed region, but moderate task-related changes in connectivity occurred between seed regions and regions outside the default network. For example, connectivity of the mPFC with the right insula and the right superior frontal gyrus decreased during task performance. Increased connectivity during the working memory task occurred between the PCC and bilateral inferior frontal gyri, and between the mPFC and the left inferior frontal gyrus, cuneus, superior parietal lobule, middle temporal gyrus and cerebellum. Overall, the areas showing greater correlation with the default network seed regions during task than at rest have been previously implicated in working memory tasks. These changes may reflect a decrease in the negative correlations occurring between the default and task-positive networks at rest. Copyright © 2010 Wiley-Liss, Inc.

  14. Connecting Land-Based Networks to Ships

    Science.gov (United States)

    2013-06-01

    VSAT ) system. The stations, equipped with VSAT antennas, share the satellite’s transmission capacity to transmit to the station having the central hub...and base stations, which are connected to the ship’s VSAT system by which the voice and data connections from the phones are routed from the ship to...Maritime VSAT Communications Solutions, June 2010. [17] MCP Maritime Communications Partner, “Technology overview,” August 2012, http

  15. 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

  16. Default Mode Network Connectivity in Stroke Patients

    NARCIS (Netherlands)

    Tuladhar, A.M.; Snaphaan, L.J.A.E.; Shumskaya, A.N.; Rijpkema, M.J.P.; Fernandez, G.S.E.; Norris, D.G.; Leeuw, F.E. de

    2013-01-01

    The pathophysiology of episodic memory dysfunction after infarction is not completely understood. It has been suggested that infarctions located anywhere in the brain can induce widespread effects causing disruption of functional networks of the cortical regions. The default mode network, which

  17. 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.

  18. Development of Connectivity in a Motoneuronal Network in Drosophila Larvae

    Science.gov (United States)

    Couton, Louise; Mauss, Alex S.; Yunusov, Temur; Diegelmann, Soeren; Evers, Jan Felix; Landgraf, Matthias

    2015-01-01

    Summary Background Much of our understanding of how neural networks develop is based on studies of sensory systems, revealing often highly stereotyped patterns of connections, particularly as these diverge from the presynaptic terminals of sensory neurons. We know considerably less about the wiring strategies of motor networks, where connections converge onto the dendrites of motoneurons. Here, we investigated patterns of synaptic connections between identified motoneurons with sensory neurons and interneurons in the motor network of the Drosophila larva and how these change as it develops. Results We find that as animals grow, motoneurons increase the number of synapses with existing presynaptic partners. Different motoneurons form characteristic cell-type-specific patterns of connections. At the same time, there is considerable variability in the number of synapses formed on motoneuron dendrites, which contrasts with the stereotypy reported for presynaptic terminals of sensory neurons. Where two motoneurons of the same cell type contact a common interneuron partner, each postsynaptic cell can arrive at a different connectivity outcome. Experimentally changing the positioning of motoneuron dendrites shows that the geography of dendritic arbors in relation to presynaptic partner terminals is an important determinant in shaping patterns of connectivity. Conclusions In the Drosophila larval motor network, the sets of connections that form between identified neurons manifest an unexpected level of variability. Synapse number and the likelihood of forming connections appear to be regulated on a cell-by-cell basis, determined primarily by the postsynaptic dendrites of motoneuron terminals. PMID:25702582

  19. Structural Connectivity Networks of Transgender People

    OpenAIRE

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

    2014-01-01

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

  20. 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…

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

    Science.gov (United States)

    Shinn, Ann K.; Baker, Justin T.; Lewandowski, Kathryn E.; Öngür, Dost; Cohen, Bruce M.

    2015-01-01

    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

  2. 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

  3. Dual connectivity for LTE-advanced heterogeneous networks

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  4. Learning Control Over Emotion Networks Through Connectivity-Based Neurofeedback.

    Science.gov (United States)

    Koush, Yury; Meskaldji, Djalel-E; Pichon, Swann; Rey, Gwladys; Rieger, Sebastian W; Linden, David E J; Van De Ville, Dimitri; Vuilleumier, Patrik; Scharnowski, Frank

    2017-02-01

    Most mental functions are associated with dynamic interactions within functional brain networks. Thus, training individuals to alter functional brain networks might provide novel and powerful means to improve cognitive performance and emotions. Using a novel connectivity-neurofeedback approach based on functional magnetic resonance imaging (fMRI), we show for the first time that participants can learn to change functional brain networks. Specifically, we taught participants control over a key component of the emotion regulation network, in that they learned to increase top-down connectivity from the dorsomedial prefrontal cortex, which is involved in cognitive control, onto the amygdala, which is involved in emotion processing. After training, participants successfully self-regulated the top-down connectivity between these brain areas even without neurofeedback, and this was associated with concomitant increases in subjective valence ratings of emotional stimuli of the participants. Connectivity-based neurofeedback goes beyond previous neurofeedback approaches, which were limited to training localized activity within a brain region. It allows to noninvasively and nonpharmacologically change interconnected functional brain networks directly, thereby resulting in specific behavioral changes. Our results demonstrate that connectivity-based neurofeedback training of emotion regulation networks enhances emotion regulation capabilities. This approach can potentially lead to powerful therapeutic emotion regulation protocols for neuropsychiatric disorders. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  5. Intrinsic connectivity networks within cerebellum and beyond in eating disorders.

    Science.gov (United States)

    Amianto, F; D'Agata, F; Lavagnino, L; Caroppo, P; Abbate-Daga, G; Righi, D; Scarone, S; Bergui, M; Mortara, P; Fassino, S

    2013-10-01

    Cerebellum seems to have a role both in feeding behavior and emotion regulation; therefore, it is a region that warrants further neuroimaging studies in eating disorders, severe conditions that determine a significant impairment in the physical and psychological domain. The aim of this study was to examine the cerebellum intrinsic connectivity during functional magnetic resonance imaging resting state in anorexia nervosa (AN), bulimia nervosa (BN), and healthy controls (CN). Resting state brain activity was decomposed into intrinsic connectivity networks (ICNs) using group spatial independent component analysis on the resting blood oxygenation level dependent time courses of 12 AN, 12 BN, and 10 CN. We extracted the cerebellar ICN and compared it between groups. Intrinsic connectivity within the cerebellar network showed some common alterations in eating disordered compared to healthy subjects (e.g., a greater connectivity with insulae, vermis, and paravermis and a lesser connectivity with parietal lobe); AN and BN patients were characterized by some peculiar alterations in connectivity patterns (e.g., greater connectivity with the insulae in AN compared to BN, greater connectivity with anterior cingulate cortex in BN compared to AN). Our data are consistent with the presence of different alterations in the cerebellar network in AN and BN patients that could be related to psychopathologic dimensions of eating disorders.

  6. On Connectivity of Wireless Sensor Networks with Directional Antennas

    Directory of Open Access Journals (Sweden)

    Qiu Wang

    2017-01-01

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

  7. Dynamic Network Connectivity: A New Form of Neuroplasticity

    Science.gov (United States)

    Arnsten, Amy F.T.; Paspalas, Constantinos D.; Gamo, Nao J.; Yang, Yang; Wang, Min

    2010-01-01

    Prefrontal cortical (PFC) working memory functions depend on pyramidal cell networks that interconnect on dendritic spines. Recent research has revealed that the strength of PFC network connections can be rapidly and reversibly increased or decreased by molecular signaling events within slender, elongated spines, a process we term Dynamic Network Connectivity (DNC). This newly discovered form of neuroplasticity provides great flexibility in mental state, but also confers vulnerability and limits mental capacity. A remarkable number of genetic and/or environmental insults to DNC signaling cascades are associated with cognitive disorders such as schizophrenia and age-related cognitive decline. These insults may dysregulate network connections and erode higher cognitive abilities, leading to symptoms such as forgetfulness, susceptibility to interference, and disorganized thought and behavior. PMID:20554470

  8. 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)

  9. Connectivity Gradients Between the Default Mode and Attention Control Networks

    Science.gov (United States)

    Ferguson, Michael A.; Lopez-Larson, Melissa; Yurgelun-Todd, Deborah

    2011-01-01

    Abstract Functional imaging studies have shown reduced activity within the default mode network during attention-demanding tasks. The network circuitry underlying this suppression remains unclear. Proposed hypotheses include an attentional switch in the right anterior insula and reciprocal inhibition between the default mode and attention control networks. We analyzed resting state blood oxygen level dependent (BOLD) data from 1278 subjects from 26 sites and constructed whole-brain maps of functional connectivity between 7266 regions of interest (ROIs) covering the gray matter at ∼5 mm resolution. ROIs belonging to the default mode network and attention control network were identified based on correlation to six published seed locations. Spatial heterogeneity of correlation between the default mode and attention control networks was observed, with smoothly varying gradients in every hub of both networks that ranged smoothly from weakly but significantly anticorrelated to positively correlated. Such gradients were reproduced in 3 separate groups of subjects. Anticorrelated subregions were identified in major hubs of both networks. Between-network connectivity gradients strengthen with age during late adolescence and early adulthood, with associated sharpening of the boundaries of the default mode network, integration of the insula and cingulate with frontoparietal attentional regions, and decreasing correlation between the default mode and attention control networks with age. PMID:22076305

  10. 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.

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

    Science.gov (United States)

    Rich, Scott; Zochowski, Michal; Booth, Victoria

    2018-01-01

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

  12. Population Coding in Sparsely Connected Networks of Noisy Neurons

    Directory of Open Access Journals (Sweden)

    Bryan Patrick Tripp

    2012-05-01

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

  13. Fast long-range connections in transportation networks

    International Nuclear Information System (INIS)

    Palhares Viana, Matheus; Fontoura Costa, Luciano da

    2011-01-01

    Multidimensional scaling is applied in order to visualize an analogue of the small-world effect implied by edges having different displacement velocities in transportation networks. Our findings are illustrated for two real-world systems, namely the London urban network (streets and underground) and the US highway network enhanced by some of the main US airlines routes. We also show that the travel time in these two networks is drastically changed by attacks targeting the edges with large displacement velocities. - Highlights: → Multidimensional scaling used to visualize the effects of fast long-range connections. → Fast long-range connections are important to decrease the average travel time. → The average travel time diverges quickly when the network is under target attacks.

  14. Connection Dynamics in Learning Networks: Games, Agents and Social Network Visualization

    NARCIS (Netherlands)

    Angehrn, Albert; Maxwell, Katrina; Sereno, Bertrand

    2007-01-01

    This paper addresses the challenge of enhancing social interaction through value-adding connections among the online members of Learning Networks. We report on our exploration of three types of connection dynamics: (1) features enabling network member to visualize and browse through relationship

  15. International networking: connecting midwives through social media.

    Science.gov (United States)

    Stewart, S; Sidebotham, M; Davis, D

    2012-09-01

    This article reports on the 'Virtual International Day of the Midwife E-vent', an innovative initiative that uses social media to provide opportunities for learning and networking internationally. This e-vent was conceived of and initiated in 2009 by a small group of midwives with an interest in social media. The e-vent uses web conferencing software and schedules a presentation every hour for a 24-h period so as to reach midwives or other interested parties in all time zones of the globe. The authors draw on their experiences to describe the e-vent including the e-vent aims and organizing processes, and to report on participation trends over the 3-year period. The e-vent has seen significant growth over a 3-year period with participation increasing from an average of five participants per session to 50. The organizing committee has expanded to include an international team and they have extended the reach of the project by establishing a Facebook page. While the use of social media has its limitations, projects such as the International Day of the Midwife E-vent have real potential to increase access to educational materials and provide opportunities for international networking. © 2012 The Authors. International Nursing Review © 2012 International Council of Nurses.

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

    Directory of Open Access Journals (Sweden)

    Nikita Vladimirov

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

  17. Role of plain radiography and CT angiography in the evaluation of obstructed total anomalous pulmonary venous connection

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Quanli; Pa, Mier; Hu, Xihong; Wang, Junbo [Children' s Hospital, Fudan University, Department of Radiology, Shanghai (China)

    2013-07-15

    Obstructed total anomalous pulmonary venous connection (TAPVC) is frequently misdiagnosed as pulmonary disease and without operative correction early death is common. It is important to make a correct diagnosis before surgery. The purpose of this study was to describe the chest radiographic features of obstructed TAPVC and compare CT angiography with transthoracic echocardiography in the evaluation of obstructed TAPVC. Eighteen children with obstructed TAPVC were assessed. Their clinical and imaging data were retrospectively reviewed. The characteristic radiographic findings were analyzed and compared with surgical results, and the diagnostic accuracy of CT angiography and transthoracic echocardiography was evaluated in terms of pulmonary venous drainage and obstruction detection. The common radiographic features included pulmonary venous congestion or edema or both (16 of 18 cases, 89%), and absence of cardiomegaly (12 of 18 cases, 67%). CT angiography correctly diagnosed TAPVC and clearly revealed the draining sites in all children (five with supracardiac TAPVC, three with cardiac TAPVC, eight with infracardiac TAPVC and two with mixed TAPVC). The diagnostic agreement between CT angiography and surgery was 100%. Transthoracic echocardiography only correctly revealed the draining sites in 11 children (5 with supracardiac TAPVC, 2 with cardiac TAPVC and 4 with infracardiac TAPVC). The diagnostic agreement between transthoracic echocardiography and surgery was 61%. The diagnostic accuracy of CT angiography was higher than that of transthoracic echocardiography (P = 0.0156). Thirty-four sites of obstruction were correctly detected by CT angiography (11 in the mediastinum, 1 at the diaphragmatic level, 9 below the diaphragm and 13 stenotic individual pulmonary veins in the lung). The diagnostic agreement between CT angiography and surgery was 92%. Transthoracic echocardiography only correctly detected 15 sites of obstruction (11 in the mediastinum, 1 at the

  18. Role of plain radiography and CT angiography in the evaluation of obstructed total anomalous pulmonary venous connection

    International Nuclear Information System (INIS)

    Shen, Quanli; Pa, Mier; Hu, Xihong; Wang, Junbo

    2013-01-01

    Obstructed total anomalous pulmonary venous connection (TAPVC) is frequently misdiagnosed as pulmonary disease and without operative correction early death is common. It is important to make a correct diagnosis before surgery. The purpose of this study was to describe the chest radiographic features of obstructed TAPVC and compare CT angiography with transthoracic echocardiography in the evaluation of obstructed TAPVC. Eighteen children with obstructed TAPVC were assessed. Their clinical and imaging data were retrospectively reviewed. The characteristic radiographic findings were analyzed and compared with surgical results, and the diagnostic accuracy of CT angiography and transthoracic echocardiography was evaluated in terms of pulmonary venous drainage and obstruction detection. The common radiographic features included pulmonary venous congestion or edema or both (16 of 18 cases, 89%), and absence of cardiomegaly (12 of 18 cases, 67%). CT angiography correctly diagnosed TAPVC and clearly revealed the draining sites in all children (five with supracardiac TAPVC, three with cardiac TAPVC, eight with infracardiac TAPVC and two with mixed TAPVC). The diagnostic agreement between CT angiography and surgery was 100%. Transthoracic echocardiography only correctly revealed the draining sites in 11 children (5 with supracardiac TAPVC, 2 with cardiac TAPVC and 4 with infracardiac TAPVC). The diagnostic agreement between transthoracic echocardiography and surgery was 61%. The diagnostic accuracy of CT angiography was higher than that of transthoracic echocardiography (P = 0.0156). Thirty-four sites of obstruction were correctly detected by CT angiography (11 in the mediastinum, 1 at the diaphragmatic level, 9 below the diaphragm and 13 stenotic individual pulmonary veins in the lung). The diagnostic agreement between CT angiography and surgery was 92%. Transthoracic echocardiography only correctly detected 15 sites of obstruction (11 in the mediastinum, 1 at the

  19. 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....

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

    Science.gov (United States)

    Belcher, Annabelle M; Yen, Cecil Chern-Chyi; Notardonato, Lucia; Ross, Thomas J; Volkow, Nora D; Yang, Yihong; Stein, Elliot A; Silva, Afonso C; Tomasi, Dardo

    2016-01-01

    In combination with advances in analytical methods, resting-state fMRI is allowing unprecedented access to 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 FC 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.

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

    Directory of Open Access Journals (Sweden)

    Vito Paolo Pastore

    2016-03-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  3. 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.

  4. Functional Connectivity Networks in Asymptomatic and Symptomatic DYT1 Carriers.

    Science.gov (United States)

    Premi, Enrico; Diano, Matteo; Gazzina, Stefano; Cauda, Franco; Gualeni, Vera; Tinazzi, Michele; Fiorio, Mirta; Liberini, Paolo; Lazzarini, Clara; Archetti, Silvana; Biasiotto, Giorgio; Turla, Marinella; Bertasi, Valeria; Cotelli, Maria; Gasparotti, Roberto; Padovani, Alessandro; Borroni, Barbara

    2016-11-01

    DYT1 mutation is characterized by focal to generalized dystonia and incomplete penetrance. To explore the complex perturbations in the different neural networks and the mutual interactions among them, we studied symptomatic and asymptomatic DTY1 mutation carriers by resting-state functional MRI. A total of 7 symptomatic DYT1, 10 asymptomatic DYT1, and 26 healthy controls were considered. Resting-state functional MRI (Oxford Centre for Functional MRI of the Brain) [FMRIB] Software Library) (FSL) MELODIC, dual regression, (as a toolbox of FSL, with Nets is referred to "networks") (FSLNets) (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLNets) was performed on 9 resting-state neural networks. DYT1 mutation signature (symptomatic DYT1 and asymptomatic DYT1) was characterized by increased connectivity in the dorsal attention network and in the left fronto-parietal network. Functional correlates of symptomatic DYT1 patients (symptomatic DYT1 vs healthy controls) showed increased connectivity in the sensorimotor network. This study argues that DYT1 dystonia is a network disorder, with crucial nodes in sensory-motor integration of posterior parietal structures. A better characterization of cortical networks involved in dystonia is crucial for possible neurophysiological therapeutic interventions. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

  5. 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.

  6. 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

    2014-04-04

    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. Copyright © 2014 Elsevier B.V. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Yael Artzy-Randrup

    2010-08-01

    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

  8. Exponential stability of neural networks with asymmetric connection weights

    International Nuclear Information System (INIS)

    Yang Jinxiang; Zhong Shouming

    2007-01-01

    This paper investigates the exponential stability of a class of neural networks with asymmetric connection weights. By dividing the network state variables into various parts according to the characters of the neural networks, some new sufficient conditions of exponential stability are derived via constructing a Lyapunov function and using the method of the variation of constant. The new conditions are associated with the initial values and are described by some blocks of the interconnection matrix, and do not depend on other blocks. Examples are given to further illustrate the theory

  9. 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."

  10. Two Distinct Scene-Processing Networks Connecting Vision and Memory.

    Science.gov (United States)

    Baldassano, Christopher; Esteva, Andre; Fei-Fei, Li; Beck, Diane M

    2016-01-01

    A number of regions in the human brain are known to be involved in processing natural scenes, but the field has lacked a unifying framework for understanding how these different regions are organized and interact. We provide evidence from functional connectivity and meta-analyses for a new organizational principle, in which scene processing relies upon two distinct networks that split the classically defined parahippocampal place area (PPA). The first network of strongly connected regions consists of the occipital place area/transverse occipital sulcus and posterior PPA, which contain retinotopic maps and are not strongly coupled to the hippocampus at rest. The second network consists of the caudal inferior parietal lobule, retrosplenial complex, and anterior PPA, which connect to the hippocampus (especially anterior hippocampus), and are implicated in both visual and nonvisual tasks, including episodic memory and navigation. We propose that these two distinct networks capture the primary functional division among scene-processing regions, between those that process visual features from the current view of a scene and those that connect information from a current scene view with a much broader temporal and spatial context. This new framework for understanding the neural substrates of scene-processing bridges results from many lines of research, and makes specific functional predictions.

  11. Hidden Connectivity in Networks with Vulnerable Classes of Nodes

    Directory of Open Access Journals (Sweden)

    Sebastian M. Krause

    2016-10-01

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

  12. 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.

  13. 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.

  14. Connectivity and Nestedness in Bipartite Networks from Community Ecology

    International Nuclear Information System (INIS)

    Corso, Gilberto; De Araujo, A I Levartoski; De Almeida, Adriana M

    2011-01-01

    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 ν. The index ν is found using the relation ν = 1 - τ where τ is the temperature of the adjacency matrix of the bipartite network. By its turn τ 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 ν is a function of the connectivities of the bipartite network. In addition we find a concise way to find ν which avoid cumbersome algorithm manupulation of the adjacency matrix.

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

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano

    is connected to thousands of other neurons. The rst question is: how to model neural networks through stochastic processes? A multivariate Ornstein-Uhlenbeck process, obtained as a diffusion approximation of a jump process, is the proposed answer. Obviously, dependencies between neurons imply dependencies...... between their spike times. Therefore, the second question is: how to detect neural network connectivity from simultaneously recorded spike trains? Answering this question corresponds to investigate the joint distribution of sequences of rst passage times. A non-parametric method based on copulas...... 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...

  16. 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.

  17. Just-in-time connectivity for large spiking networks.

    Science.gov (United States)

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

    2008-11-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  19. Mapping effective connectivity within cortical networks with diffuse optical tomography.

    Science.gov (United States)

    Hassanpour, Mahlega S; Eggebrecht, Adam T; Peelle, Jonathan E; Culver, Joseph P

    2017-10-01

    Understanding how cortical networks interact in response to task demands is important both for providing insight into the brain's processing architecture and for managing neurological diseases and mental disorders. High-density diffuse optical tomography (HD-DOT) is a neuroimaging technique that offers the significant advantages of having a naturalistic, acoustically controllable environment and being compatible with metal implants, neither of which is possible with functional magnetic resonance imaging. We used HD-DOT to study the effective connectivity and assess the modulatory effects of speech intelligibility and syntactic complexity on functional connections within the cortical speech network. To accomplish this, we extend the use of a generalized psychophysiological interaction (PPI) analysis framework. In particular, we apply PPI methods to event-related HD-DOT recordings of cortical oxyhemoglobin activity during auditory sentence processing. We evaluate multiple approaches for selecting cortical regions of interest and for modeling interactions among these regions. Our results show that using subject-based regions has minimal effect on group-level connectivity maps. We also demonstrate that incorporating an interaction model based on estimated neural activity results in significantly stronger effective connectivity. Taken together our findings support the use of HD-DOT with PPI methods for noninvasively studying task-related modulations of functional connectivity.

  20. Genes2FANs: connecting genes through functional association networks

    Science.gov (United States)

    2012-01-01

    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 finding that disease genes in

  1. An improved algorithm for connectivity analysis of distribution networks

    International Nuclear Information System (INIS)

    Kansal, M.L.; Devi, Sunita

    2007-01-01

    In the present paper, an efficient algorithm for connectivity analysis of moderately sized distribution networks has been suggested. Algorithm is based on generation of all possible minimal system cutsets. The algorithm is efficient as it identifies only the necessary and sufficient conditions of system failure conditions in n-out-of-n type of distribution networks. The proposed algorithm is demonstrated with the help of saturated and unsaturated distribution networks. The computational efficiency of the algorithm is justified by comparing the computational efforts with the previously suggested appended spanning tree (AST) algorithm. The proposed technique has the added advantage as it can be utilized for generation of system inequalities which is useful in reliability estimation of capacitated networks

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

    International Nuclear Information System (INIS)

    Robinson, P.C.

    1984-10-01

    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. Thermodynamics of fully connected Blume-Emery-Griffiths neural networks

    Science.gov (United States)

    Bollé, D.; Verbeiren, T.

    2003-01-01

    The thermodynamic and retrieval properties of fully connected Blume-Emery-Griffiths networks are studied using replica mean-field theory. These networks can be considered as generalizations of the Hopfield model to the storage of ternary patterns. Capacity-temperature phase diagrams are derived for several values of the pattern activity. It is found that the retrieval phase is the largest in comparison with other three-state neuron models. Furthermore, the meaning and stability of the so-called quadrupolar phase is discussed as a function of both the temperature and the pattern activity. Where appropriate, the results are compared with the diluted version of the model.

  4. Thermodynamics of fully connected Blume-Emery-Griffiths neural networks

    International Nuclear Information System (INIS)

    Bolle, D; Verbeiren, T

    2003-01-01

    The thermodynamic and retrieval properties of fully connected Blume-Emery-Griffiths networks are studied using replica mean-field theory. These networks can be considered as generalizations of the Hopfield model to the storage of ternary patterns. Capacity-temperature phase diagrams are derived for several values of the pattern activity. It is found that the retrieval phase is the largest in comparison with other three-state neuron models. Furthermore, the meaning and stability of the so-called quadrupolar phase is discussed as a function of both the temperature and the pattern activity. Where appropriate, the results are compared with the diluted version of the model

  5. Restoration of lost connectivity of partitioned wireless sensor networks

    Directory of Open Access Journals (Sweden)

    Virender Ranga

    2016-05-01

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

  6. How has climate change altered network connectivity in a mountain stream network?

    Science.gov (United States)

    Ward, A. S.; Schmadel, N.; Wondzell, S. M.; Johnson, S.

    2017-12-01

    Connectivity along river networks is broadly recognized as dynamic, with seasonal and event-based expansion and contraction of the network extent. Intermittently flowing streams are particularly important as they define a crucial threshold for continuously connected waters that enable migration by aquatic species. In the Pacific northwestern U.S., changes in atmospheric circulation have been found to alter rainfall patterns and result in decreased summer low-flows in the region. However, the impact of this climate dynamic on network connectivity is heretofore unstudied. Thus, we ask: How has connectivity in the riparian corridor changed in response to observed changes in climate? In this study we take the well-studied H.J. Andrews Experimental Forest as representative of mountain river networks in the Pacific northwestern U.S. First, we analyze 63 years of stream gauge information from a network of 11 gauges to document observed changes in timing and magnitude of stream discharge. We found declining magnitudes of seasonal low-flows and shifting seasonality of water export from the catchment, both of which we attribute to changes in precipitation timing and storage as snow vs. rainfall. Next, we use these discharge data to drive a reduced-complexity model of the river network to simulate network connectivity over 63 years. Model results show that network contraction (i.e., minimum network extent) has decreased over the past 63 years. Unexpectedly, the increasing winter peak flows did not correspond with increasing network expansion, suggesting a geologic control on maximum flowing network extent. We find dynamic expansion and contraction of the network primarily occurs during period of catchment discharge less than about 1 m3/s at the outlet, whereas the network extent is generally constant for discharges from 1 to 300 m3/s. Results of our study are of interest to scientists focused on connectivity as a control on ecological processes both directly (e.g., fish

  7. Functional connectivity changes in the language network during stroke recovery.

    Science.gov (United States)

    Nair, Veena A; Young, Brittany M; La, Christian; Reiter, Peter; Nadkarni, Tanvi N; Song, Jie; Vergun, Svyatoslav; Addepally, Naga Saranya; Mylavarapu, Krishna; Swartz, Jennifer L; Jensen, Matthew B; Chacon, Marcus R; Sattin, Justin A; Prabhakaran, Vivek

    2015-02-01

    Several neuroimaging studies have examined language reorganization in stroke patients with aphasia. However, few studies have examined language reorganization in stroke patients without aphasia. Here, we investigated functional connectivity (FC) changes after stroke in the language network using resting-state fMRI and performance on a verbal fluency (VF) task in patients without clinically documented language deficits. Early-stage ischemic stroke patients (N = 26) (average 5 days from onset), 14 of whom were tested at a later stage (average 4.5 months from onset), 26 age-matched healthy control subjects (HCs), and 12 patients with cerebrovascular risk factors (patients at risk, PR) participated in this study. We examined FC of the language network with 23 seed regions based on a previous study. We evaluated patients' behavioral performance on a VF task and correlation between brain resting-state FC (rsFC) and behavior. Compared to HCs, early stroke patients showed significantly decreased rsFC in the language network but no difference with respect to PR. Early stroke patients showed significant differences in performance on the VF task compared to HCs but not PR. Late-stage patients compared to HCs and PR showed no differences in brain rsFC in the language network and significantly stronger connections compared to early-stage patients. Behavioral differences persisted in the late stage compared to HCs. Change in specific connection strengths correlated with changes in behavior from early to late stage. These results show decreased rsFC in the language network and verbal fluency deficits in early stroke patients without clinically documented language deficits.

  8. Discrete Symmetries on the Light Front and a General Relation connecting Nucleon Electric Dipole and Anomalous Magnetic Moments

    Energy Technology Data Exchange (ETDEWEB)

    Brodsky, Stanley J.; /SLAC; Gardner, Susan; /Kentucky U.; Hwang, Dae Sung; /Sejong U.

    2006-01-11

    We consider the electric dipole form factor, F{sub 3}(q{sup 2}), as well as the Dirac and Pauli form factors, F{sub 1}(q{sup 2}) and F{sub 2}(q{sup 2}), of the nucleon in the light-front formalism. We derive an exact formula for F{sub 3}(q{sup 2}) to complement those known for F{sub 1}(q{sup 2}) and F{sub 2}(q{sup 2}). We derive the light-front representation of the discrete symmetry transformations and show that time-reversal- and parity-odd effects are captured by phases in the light-front wave functions. We thus determine that the contributions to F{sub 2}(q{sup 2}) and F{sub 3}(q{sup 2}), Fock-state by Fock-state, are related, independent of the fundamental mechanism through which CP violation is generated. Our relation is not specific to the nucleon, but, rather, is true of spin-1/2 systems in general, be they lepton or baryon. The empirical values of the anomalous magnetic moments, in concert with empirical bounds on the associated electric dipole moments, can better constrain theories of CP violation. In particular, we find that the neutron and proton electric dipole moments echo the isospin structure of the anomalous magnetic moments, {kappa}{sup n} {approx} -{kappa}{sup p}.

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

    Science.gov (United States)

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

    2016-01-01

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

  10. Default Mode Network Connectivity as a Function of Familial and Environmental Risk for Psychotic Disorder

    NARCIS (Netherlands)

    Peeters, Sanne C. T.; van de Ven, Vincent; Gronenschild, Ed H. B. M.; Patel, Ameera X.; Habets, Petra; Goebel, Rainer; van Os, Jim; Marcelis, Machteld; Kahn, Rene; Linszen, Don; Wiersma, Durk; Bruggeman, Richard; Cahn, Wiepke; de Haan, Lieuwe; Krabbendam, Lydia; Myin-Germeys, Inez

    2015-01-01

    Background 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

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

    DEFF Research Database (Denmark)

    Kwon, Soyoung; Watanabe, Masataka; Fischer, Elvira

    2017-01-01

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

  12. Dynamical graph theory networks techniques for the analysis of sparse connectivity networks in dementia

    Science.gov (United States)

    Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke

    2017-05-01

    Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.

  13. Stability and anomalous entropic elasticity of subisostatic random-bond networks

    NARCIS (Netherlands)

    Wigbers, M.C.; Mac Kintosh, F.C.; Dennison, M.

    2015-01-01

    We study the elasticity of thermalized spring networks under an applied bulk strain. The networks considered are subisostatic random-bond networks that, in the athermal limit, are known to have vanishing bulk and linear shear moduli at zero bulk strain. Above a bulk strain threshold, however, these

  14. 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.

  15. Neural network connectivity differences in children who stutter

    Science.gov (United States)

    Zhu, David C.

    2013-01-01

    Affecting 1% of the general population, stuttering impairs the normally effortless process of speech production, which requires precise coordination of sequential movement occurring among the articulatory, respiratory, and resonance systems, all within millisecond time scales. Those afflicted experience frequent disfluencies during ongoing speech, often leading to negative psychosocial consequences. The aetiology of stuttering remains unclear; compared to other neurodevelopmental disorders, few studies to date have examined the neural bases of childhood stuttering. Here we report, for the first time, results from functional (resting state functional magnetic resonance imaging) and structural connectivity analyses (probabilistic tractography) of multimodal neuroimaging data examining neural networks in children who stutter. We examined how synchronized brain activity occurring among brain areas associated with speech production, and white matter tracts that interconnect them, differ in young children who stutter (aged 3–9 years) compared with age-matched peers. Results showed that children who stutter have attenuated connectivity in neural networks that support timing of self-paced movement control. The results suggest that auditory-motor and basal ganglia-thalamocortical networks develop differently in stuttering children, which may in turn affect speech planning and execution processes needed to achieve fluent speech motor control. These results provide important initial evidence of neurological differences in the early phases of symptom onset in children who stutter. PMID:24131593

  16. Connecting Patterns Inspire Link Prediction in Complex Networks

    Directory of Open Access Journals (Sweden)

    Ming-Yang Zhou

    2017-01-01

    Full Text Available Link prediction uses observed data to predict future or potential relations in complex networks. An underlying hypothesis is that two nodes have a high likelihood of connecting together if they share many common characteristics. The key issue is to develop different similarity-evaluating approaches. However, in this paper, by characterizing the differences of the similarity scores of existing and nonexisting links, we find an interesting phenomenon that two nodes with some particular low similarity scores also have a high probability to connect together. Thus, we put forward a new framework that utilizes an optimal one-variable function to adjust the similarity scores of two nodes. Theoretical analysis suggests that more links of low similarity scores (long-range links could be predicted correctly by our method without losing accuracy. Experiments in real networks reveal that our framework not only enhances the precision significantly but also predicts more long-range links than state-of-the-art methods, which deepens our understanding of the structure of complex networks.

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

    Science.gov (United States)

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

    2017-01-13

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

  18. 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.

  19. 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.

  20. Controlling Voltage Levels of Distribution Network-Radial Feeder after Connecting Wind Turbines to the Network

    Directory of Open Access Journals (Sweden)

    Muhammad Al Badri

    2017-11-01

    Full Text Available Several factors in power generation and supply need to be taken into account such as shortages of energy supply, system stability, and energy quality and system disruption due to network losses, industrial development and population expansion. The addition of wind turbines to the distribution network is of great benefit in providing additional power and solving these problems, but this addition is accompanied by the problem of low voltage network. This research found optimal solutions to the problem of low voltage distribution network after connecting wind turbines. The main idea of this paper is to optimize the low-voltage problem as a result of connecting the wind turbines to the "far end" of the radial feeder for a distribution network and to obtain a voltage level within an acceptable and stable range. The problem of low voltage solved by using the load-drop compensation, capacitor-bank and “doubly-fed” induction generators. The results of this study were based on the operation of the entire design of the simulation system which would be compatible with the reality of the energy flow of all network components by using the PSCAD program. The present analysis program revealed an optimum solution for the low voltage profile of the distribution network after connecting the wind turbine.

  1. Network robustness assessed within a dual connectivity framework: joint dynamics of the Active and Idle Networks.

    Science.gov (United States)

    Tejedor, Alejandro; Longjas, Anthony; Zaliapin, Ilya; Ambroj, Samuel; Foufoula-Georgiou, Efi

    2017-08-17

    Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. But current definition of robustness is only accounting for half of the story: the connectivity of the nodes unaffected by the attack. Here we propose a new framework to assess network robustness, wherein the connectivity of the affected nodes is also taken into consideration, acknowledging that it plays a crucial role in properly evaluating the overall network robustness in terms of its future recovery from the attack. Specifically, 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 that of building-up the IN. We show, via analysis of well-known prototype networks and real world data, that trade-offs between the efficiency of Active and Idle Network dynamics give rise to surprising robustness crossovers and re-rankings, which can have significant implications for decision making.

  2. The Fuzzy Logic of Network Connectivity in Mouse Visual Thalamus.

    Science.gov (United States)

    Morgan, Josh Lyskowski; Berger, Daniel Raimund; Wetzel, Arthur Willis; Lichtman, Jeff William

    2016-03-24

    In an attempt to chart parallel sensory streams passing through the visual thalamus, we acquired a 100-trillion-voxel electron microscopy (EM) dataset and identified cohorts of retinal ganglion cell axons (RGCs) that innervated each of a diverse group of postsynaptic thalamocortical neurons (TCs). Tracing branches of these axons revealed the set of TCs innervated by each RGC cohort. Instead of finding separate sensory pathways, we found a single large network that could not be easily subdivided because individual RGCs innervated different kinds of TCs and different kinds of RGCs co-innervated individual TCs. We did find conspicuous network subdivisions organized on the basis of dendritic rather than neuronal properties. This work argues that, in the thalamus, neural circuits are not based on a canonical set of connections between intrinsically different neuronal types but, rather, may arise by experience-based mixing of different kinds of inputs onto individual postsynaptic cells. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Fully connected network of superconducting qubits in a cavity

    International Nuclear Information System (INIS)

    Tsomokos, Dimitris I; Ashhab, Sahel; Nori, Franco

    2008-01-01

    A fully connected qubit network is considered, where every qubit interacts with every other one. When the interactions between the qubits are homogeneous, the system is a special case of the finite Lipkin-Meshkov-Glick (LMG) model. We propose a natural implementation of this model using superconducting qubits in state-of-the-art circuit QED. The ground state, the low-lying energy spectrum and the dynamical evolution are investigated. We find that, under realistic conditions, highly entangled states of Greenberger-Horne-Zeilinger (GHZ) and W types can be generated. We also comment on the influence of disorder on the system and discuss the possibility of simulating complex quantum systems, such as Sherrington-Kirkpatrick (SK) spin glasses, with superconducting qubit networks.

  4. Quetiapine modulates functional connectivity in brain aggression networks.

    Science.gov (United States)

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

    2013-07-15

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

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    Vijayvignesh Selvaraj

    2014-06-01

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

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

    Science.gov (United States)

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

    2017-02-01

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

  8. Alterations of Intrinsic Connectivity Networks in Antipsychotic-Naïve First-Episode Schizophrenia

    DEFF Research Database (Denmark)

    Anhøj, Simon; Ødegaard Nielsen, Mette; Jensen, Maria Høj

    2018-01-01

    controls were scanned with functional magnetic resonance imaging under resting conditions. Main outcome measures were differences in functional connectivity between groups and the relationship between network alterations, psychopathology and cognition. Results: Altered connectivity was found between right...

  9. Evaluating the effect of street network connectivity on first/last mile transit performance.

    Science.gov (United States)

    2011-11-01

    "This study defines a novel connectivity indicator (CI) to predict transit performance by : identifying the role that street network connectivity plays in influencing the service quality of : demand responsive feeder transit services. This new CI def...

  10. Shyness and Trajectories of Functional Network Connectivity Over Early Adolescence.

    Science.gov (United States)

    Sylvester, Chad M; Whalen, Diana J; Belden, Andy C; Sanchez, Shana L; Luby, Joan L; Barch, Deanna M

    2017-12-08

    High shyness during early adolescence is associated with impaired peer relationships and risk for psychiatric disorders. Little is known, however, about the relation between shyness and trajectories of brain development over early adolescence. The current study longitudinally examined trajectories of resting-state functional connectivity (rs-fc) within four brain networks in 147 adolescents. Subjects underwent functional magnetic resonance imaging at three different time points, at average ages 10.5 (range = 7.8-13.0), 11.7 (range = 9.3-14.1), and 12.9 years (range = 10.1-15.2). Multilevel linear modeling indicated that high shyness was associated with a less steep negative slope of default mode network (DMN) rs-fc over early adolescence relative to low shyness. Less steep decreases in DMN rs-fc may relate to increased self-focus in adolescents with high shyness. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

  11. Parameterized algorithmics for finding connected motifs in biological networks.

    Science.gov (United States)

    Betzler, Nadja; van Bevern, René; Fellows, Michael R; Komusiewicz, Christian; Niedermeier, Rolf

    2011-01-01

    We study the NP-hard LIST-COLORED GRAPH MOTIF problem which, given an undirected list-colored graph G = (V, E) and a multiset M of colors, asks for maximum-cardinality sets S ⊆ V and M' ⊆ M such that G[S] is connected and contains exactly (with respect to multiplicity) the colors in M'. LIST-COLORED GRAPH MOTIF has applications in the analysis of biological networks. We study LIST-COLORED GRAPH MOTIF with respect to three different parameterizations. For the parameters motif size |M| and solution size |S|, we present fixed-parameter algorithms, whereas for the parameter |V| - |M|, we show W[1]-hardness for general instances and achieve fixed-parameter tractability for a special case of LIST-COLORED GRAPH MOTIF. We implemented the fixed-parameter algorithms for parameters |M| and |S|, developed further speed-up heuristics for these algorithms, and applied them in the context of querying protein-interaction networks, demonstrating their usefulness for realistic instances. Furthermore, we show that extending the request for motif connectedness to stronger demands, such as biconnectedness or bridge-connectedness leads to W[1]-hard problems when the parameter is the motif size |M|.

  12. Nuclear medicine image segmentation using a connective network

    Energy Technology Data Exchange (ETDEWEB)

    Peter, J.; Smith, M.F.; Coleman, R.E. [Dresden Univ. of Technology (Germany)] [and others

    1996-12-31

    A method for post-reconstruction nuclear medicine image segmentation based on an analogy to the Ising model of a two-dimensional square lattice of N particles (pixel values) is presented. A reconstructed 2-D slice image is analyzed as a multi-pixel system where pixel values correspond to a 2-D lattice of points with non-zero interaction energy with their nearest neighbors. The model assumes that pixel intensities belonging to the same homogeneous image region are relatively constant, where region intensity means (or labels) are determined by both statistical parameter estimation and deterministic image analysis. The change in value of each pixel during the segmentation process depends on (1) the statistical properties in the reconstructed image and (2) the values (or states) of its nearest neighbors. These changes are either in the direction of statistically estimated intensity means or other previously analyzed regions of significance. The segmentation technique uses a new innovative relaxation labeling connective network. The global relaxation dynamics of the network are controlled by the interaction of local synergetic and logistic functions assigned to each pixel. This result may improve the localization of hot and cold regions of interest as compared to the original image.

  13. Power in the heterogeneous connections model: The emergence of core-periphery networks

    OpenAIRE

    Persitz, Dotan

    2009-01-01

    The heterogeneous connections model is a generalization of the homogeneous connections model of Jackson and Wolinsky (1996) in which the intrinsic value of each connection is set by a discrete, positive and symmetric function that depends solely on the types of the two end agents. Core periphery networks are defined as networks in which the agents' set can be partitioned into two subsets, one in which the members are completely connected among themselves and the other where there are no inter...

  14. Default network connectivity as a vulnerability marker for obsessive compulsive disorder.

    Science.gov (United States)

    Peng, Z W; Xu, T; He, Q H; Shi, C Z; Wei, Z; Miao, G D; Jing, J; Lim, K O; Zuo, X N; Chan, R C K

    2014-05-01

    Aberrant functional connectivity within the default network is generally assumed to be involved in the pathophysiology of obsessive compulsive disorder (OCD); however, the genetic risk of default network connectivity in OCD remains largely unknown. Here, we systematically investigated default network connectivity in 15 OCD patients, 15 paired unaffected siblings and 28 healthy controls. We sought to examine the profiles of default network connectivity in OCD patients and their siblings, exploring the correlation between abnormal default network connectivity and genetic risk for this population. Compared with healthy controls, OCD patients exhibited reduced strength of default network functional connectivity with the posterior cingulate cortex (PCC), and increased functional connectivity in the right inferior frontal lobe, insula, superior parietal cortex and superior temporal cortex, while their unaffected first-degree siblings only showed reduced local connectivity in the PCC. These findings suggest that the disruptions of default network functional connectivity might be associated with family history of OCD. The decreased default network connectivity in both OCD patients and their unaffected siblings may serve as a potential marker of OCD.

  15. Chaos in complex motor networks induced by Newman—Watts small-world connections

    International Nuclear Information System (INIS)

    Wei Du-Qu; Luo Xiao-Shu; Zhang Bo

    2011-01-01

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

  16. Aberrant within- and between-network connectivity of the mirror neuron system network and the mentalizing network in first episode psychosis.

    Science.gov (United States)

    Choe, Eugenie; Lee, Tae Young; Kim, Minah; Hur, Ji-Won; Yoon, Youngwoo Bryan; Cho, Kang-Ik K; Kwon, Jun Soo

    2018-03-26

    It has been suggested that the mentalizing network and the mirror neuron system network support important social cognitive processes that are impaired in schizophrenia. However, the integrity and interaction of these two networks have not been sufficiently studied, and their effects on social cognition in schizophrenia remain unclear. Our study included 26 first-episode psychosis (FEP) patients and 26 healthy controls. We utilized resting-state functional connectivity to examine the a priori-defined mirror neuron system network and the mentalizing network and to assess the within- and between-network connectivities of the networks in FEP patients. We also assessed the correlation between resting-state functional connectivity measures and theory of mind performance. FEP patients showed altered within-network connectivity of the mirror neuron system network, and aberrant between-network connectivity between the mirror neuron system network and the mentalizing network. The within-network connectivity of the mirror neuron system network was noticeably correlated with theory of mind task performance in FEP patients. The integrity and interaction of the mirror neuron system network and the mentalizing network may be altered during the early stages of psychosis. Additionally, this study suggests that alterations in the integrity of the mirror neuron system network are highly related to deficient theory of mind in schizophrenia, and this problem would be present from the early stage of psychosis. Copyright © 2018 Elsevier B.V. All rights reserved.

  17. 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.

  18. Inferring structural connectivity using Ising couplings in models of neuronal networks.

    Science.gov (United States)

    Kadirvelu, Balasundaram; Hayashi, Yoshikatsu; Nasuto, Slawomir J

    2017-08-15

    Functional connectivity metrics have been widely used to infer the underlying structural connectivity in neuronal networks. Maximum entropy based Ising models have been suggested to discount the effect of indirect interactions and give good results in inferring the true anatomical connections. However, no benchmarking is currently available to assess the performance of Ising couplings against other functional connectivity metrics in the microscopic scale of neuronal networks through a wide set of network conditions and network structures. In this paper, we study the performance of the Ising model couplings to infer the synaptic connectivity in in silico networks of neurons and compare its performance against partial and cross-correlations for different correlation levels, firing rates, network sizes, network densities, and topologies. Our results show that the relative performance amongst the three functional connectivity metrics depends primarily on the network correlation levels. Ising couplings detected the most structural links at very weak network correlation levels, and partial correlations outperformed Ising couplings and cross-correlations at strong correlation levels. The result was consistent across varying firing rates, network sizes, and topologies. The findings of this paper serve as a guide in choosing the right functional connectivity tool to reconstruct the structural connectivity.

  19. Introspection-based Periodicity Awareness Model for Intermittently Connected Mobile Networks

    NARCIS (Netherlands)

    Türkes, Okan; Scholten, Johan; Havinga, Paul J.M.

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

  20. 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

  1. Predicting learning plateau of working memory from whole-brain intrinsic network connectivity patterns.

    Science.gov (United States)

    Yamashita, Masahiro; Kawato, Mitsuo; Imamizu, Hiroshi

    2015-01-05

    Individual learning performance of cognitive function is related to functional connections within 'task-activated' regions where activities increase during the corresponding cognitive tasks. On the other hand, since any brain region is connected with other regions and brain-wide networks, learning is characterized by modulations in connectivity between networks with different functions. Therefore, we hypothesized that learning performance is determined by functional connections among intrinsic networks that include both task-activated and less-activated networks. Subjects underwent resting-state functional MRI and a short period of training (80-90 min) in a working memory task on separate days. We calculated functional connectivity patterns of whole-brain intrinsic networks and examined whether a sparse linear regression model predicts a performance plateau from the individual patterns. The model resulted in highly accurate predictions (R(2) = 0.73, p = 0.003). Positive connections within task-activated networks, including the left fronto-parietal network, accounted for nearly half (48%) of the contribution ratio to the prediction. Moreover, consistent with our hypothesis, connections of the task-activated networks with less-activated networks showed a comparable contribution (44%). Our findings suggest that learning performance is potentially constrained by system-level interactions within task-activated networks as well as those between task-activated and less-activated networks.

  2. Task-dependent reorganization of functional connectivity networks during visual semantic decision making.

    Science.gov (United States)

    DeSalvo, Matthew N; Douw, Linda; Takaya, Shigetoshi; Liu, Hesheng; Stufflebeam, Steven M

    2014-01-01

    Functional MRI is widely used to study task-related changes in neuronal activity as well as resting-state functional connectivity. In this study, we explore task-related changes in functional connectivity networks using fMRI. Dynamic connectivity may represent a new measure of neural network robustness that would impact both clinical and research efforts. However, prior studies of task-related changes in functional connectivity have shown apparently conflicting results, leading to several competing hypotheses regarding the relationship between task-related and resting-state brain networks. We used a graph theory-based network approach to compare functional connectivity in healthy subjects between the resting state and when performing a clinically used semantic decision task. We analyzed fMRI data from 21 healthy, right-handed subjects. While three nonoverlapping, highly intraconnected functional modules were observed in the resting state, an additional language-related module emerged during the semantic decision task. Both overall and within-module connectivity were greater in default mode network (DMN) and classical language areas during semantic decision making compared to rest, while between-module connectivity was diffusely greater at rest, revealing a more widely distributed pattern of functional connectivity at rest. The results of this study suggest that there are differences in network topology between resting and task states. Specifically, semantic decision making is associated with a reduction in distributed connectivity through hub areas of the DMN as well as an increase in connectivity within both default and language networks.

  3. Reduced left executive control network functional connectivity is associated with alcohol use disorders.

    Science.gov (United States)

    Weiland, Barbara J; Sabbineni, Amithrupa; Calhoun, Vince D; Welsh, Robert C; Bryan, Angela D; Jung, Rex E; Mayer, Andrew R; Hutchison, Kent E

    2014-09-01

    Altered functional connectivity in critical networks has been associated with chronic alcohol abuse. In turn, changes in connectivity in executive control networks (ECNs) may undermine the ability to control alcohol consumption. It was hypothesized that network connectivity would be reduced in individuals with problematic alcohol use (ALC) compared with controls and that diminished network connectivity would be associated with greater failure to control drinking. Resting-state functional magnetic resonance imaging was analyzed to identify 14 previously identified intrinsic connectivity networks (ICNs) using a priori regions of interest in cases ranging from binge drinkers to those with severe alcohol use disorder, as well as control subjects. Analyses tested for differences in network connectivity strength between 255 ALC cases and 87 age- and gender-matched controls. Further, structural equation analysis, using 383 ALC cases, tested whether functional connectivity strength mediated the relationship between years of regular drinking and alcohol problems. The age- and gender-matched analysis showed that ALC had significantly lower network connectivity strength than controls in the left executive control (LECN), basal ganglia, and primary visual networks. For all ALC, LECN connectivity strength is negatively correlated with failed control and alcohol disorder severity. Edges connecting parietal regions with dorsolateral prefrontal, middle frontal, and temporal regions within the LECN drove these relationships. A positive association between years of drinking and severity of alcohol problems was mediated by reduced ECN connectivity. This study reports relationships between network strength and problematic alcohol use, suggesting that chronic drinking negatively impacts brain connectivity, specifically in the LECN. Altered functional connectivity, related to chronic alcohol abuse, may contribute to the etiology of alcohol dependence and relapse. Copyright © 2014 by

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

    DEFF Research Database (Denmark)

    Fagertun, Anna Manolova; Ruepp, Sarah Renée

    2014-01-01

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

  5. Effective connectivity analysis of default mode network based on the Bayesian network learning approach

    Science.gov (United States)

    Li, Rui; Chen, Kewei; Zhang, Nan; Fleisher, Adam S.; Li, Yao; Wu, Xia

    2009-02-01

    This work proposed to use the linear Gaussian Bayesian network (BN) to construct the effective connectivity model of the brain's default mode network (DMN), a set of regions characterized by more increased neural activity during rest-state than most goal-oriented tasks. In a complete unsupervised data-driven manner, Bayesian information criterion (BIC) based learning approach was utilized to identify a highest scored network whose nodes (brain regions) were selected based on the result from the group independent component analysis (Group ICA) examining the DMN. We put forward to adopt the statistical significance testing method for regression coefficients used in stepwise regression analysis to further refine the network identified by BIC. The final established BN, learned from the functional magnetic resonance imaging (fMRI) data acquired from 12 healthy young subjects during rest-state, revealed that the hippocampus (HC) was the most influential brain region that affected activities in all other regions included in the BN. In contrast, the posterior cingulate cortex (PCC) was influenced by other regions, but had no reciprocal effects on any other region. Overall, the configuration of our BN illustrated that a prominent connection from HC to PCC existed in the DMN.

  6. The frequency dimension of fMRI dynamic connectivity: Network connectivity, functional hubs and integration in the resting brain.

    Science.gov (United States)

    Thompson, William Hedley; Fransson, Peter

    2015-11-01

    The large-scale functional MRI connectome of the human brain is composed of multiple resting-state networks (RSNs). However, the network dynamics, such as integration and segregation between and within RSNs is largely unknown. To address this question we created high-resolution "frequency graphlets", connectivity matrices derived across the low-frequency spectrum of the BOLD fMRI resting-state signal (0.01-0.1 Hz) in a cohort of 100 subjects. We then apply and compare graph theoretical measures across the frequency graphlets. Our results show that the within- and between-network connectivity and presence of functional hubs shift as a function of frequency. Furthermore, we show that the small world network property peaks at different frequencies with corresponding spatial connectivity profiles. We conclude that the frequency dependence of the network connectivity and the spatial configuration of functional hubs suggest that the dynamics of large-scale network integration and segregation operate at different time scales. Copyright © 2015. Published by Elsevier Inc.

  7. MDD diagnosis based on partial-brain functional connection network

    Science.gov (United States)

    Yan, Gaoliang; Hu, Hailong; Zhao, Xiang; Zhang, Lin; Qu, Zehui; Li, Yantao

    2018-04-01

    Artificial intelligence (AI) is a hotspot in computer science research nowadays. To apply AI technology in all industries has been the developing direction for researchers. Major depressive disorder (MDD) is a common disease of serious mental disorders. The World Health Organization (WHO) reports that MDD is projected to become the second most common cause of death and disability by 2020. At present, the way of MDD diagnosis is single. Applying AI technology to MDD diagnosis and pathophysiological research will speed up the MDD research and improve the efficiency of MDD diagnosis. In this study, we select the higher degree of brain network functional connectivity by statistical methods. And our experiments show that the average accuracy of Logistic Regression (LR) classifier using feature filtering reaches 88.48%. Compared with other classification methods, both the efficiency and accuracy of this method are improved, which will greatly improve the process of MDD diagnose. In these experiments, we also define the brain regions associated with MDD, which plays a vital role in MDD pathophysiological research.

  8. 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.

  9. Intrinsic connectivity networks from childhood to late adolescence: Effects of age and sex

    Directory of Open Access Journals (Sweden)

    Cristina Solé-Padullés

    2016-02-01

    Full Text Available There is limited evidence on the effects of age and sex on intrinsic connectivity of networks underlying cognition during childhood and adolescence. Independent component analysis was conducted in 113 subjects aged 7–18; the default mode, executive control, anterior salience, basal ganglia, language and visuospatial networks were identified. The effect of age was examined with multiple regression, while sex and ‘age × sex’ interactions were assessed by dividing the sample according to age (7–12 and 13–18 years. As age increased, connectivity in the dorsal and ventral default mode network became more anterior and posterior, respectively, while in the executive control network, connectivity increased within frontoparietal regions. The basal ganglia network showed increased engagement of striatum, thalami and precuneus. The anterior salience network showed greater connectivity in frontal areas and anterior cingulate, and less connectivity of orbitofrontal, middle cingulate and temporoparietal regions. The language network presented increased connectivity of inferior frontal and decreased connectivity within the right middle frontal and left inferior parietal cortices. The visuospatial network showed greater engagement of inferior parietal and frontal cortices. No effect of sex, nor age by sex interactions was observed. These findings provide evidence of strengthening of cortico-cortical and cortico-subcortical networks across childhood and adolescence.

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-11-15

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1992-01-01

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

  13. Characterizing structure connectivity correlation with the default mode network in Alzheimer's patients and normal controls

    Science.gov (United States)

    Guo, Jia; Xu, Peng; Song, Chao; Yao, Li; Zhao, Xiaojie

    2012-03-01

    Magnetic resonance diffusion tensor imaging (DTI) is a kind of effective measure to do non-invasive investigation on brain fiber structure at present. Studies of fiber tracking based on DTI showed that there was structural connection of white matter fiber among the nodes of resting-state functional network, denoting that the connection of white matter was the basis of gray matter regions in functional network. Nevertheless, relationship between these structure connectivity regions and functional network has not been clearly indicated. Moreover, research of fMRI found that activation of default mode network (DMN) in Alzheimer's disease (AD) was significantly descended, especially in hippocampus and posterior cingulated cortex (PCC). The relationship between this change of DMN activity and structural connection among functional networks needs further research. In this study, fast marching tractography (FMT) algorithm was adopted to quantitative calculate fiber connectivity value between regions, and hippocampus and PCC which were two important regions in DMN related with AD were selected to compute white matter connection region between them in elderly normal control (NC) and AD patient. The fiber connectivity value was extracted to do the correlation analysis with activity intensity of DMN. Results showed that, between PCC and hippocampus of NC, there exited region with significant high connectivity value of white matter fiber whose performance has relatively strong correlation with the activity of DMN, while there was no significant white matter connection region between them for AD patient which might be related with reduced network activation in these two regions of AD.

  14. Connectivity of vehicular ad hoc networks with continuous node distribution patterns

    OpenAIRE

    Jin, W L; Wang, Bruce

    2010-01-01

    The connectivity of vehicular ad hoc networks (VANets) can be affected by the special distribution patterns, usually dependent and non-uniform, of vehicles in a transportation network. In this study, we introduce a new framework for computing the connectivity in a VANet for continuous distribution patterns of communication nodes on a line in a transportation network. Such distribution patterns can be estimated from traffic densities obtained through loop detectors or other detectors. When com...

  15. A preferential attachment strategy for connectivity link addition strategy in improving the robustness of interdependent networks

    Science.gov (United States)

    Wang, Xingyuan; Cao, Jianye; Li, Rui; Zhao, Tianfang

    2017-10-01

    Given the same two networks and only one-to-one interlinks are allowed, apparently interdependent networks coupled by these two networks has the optimal robustness when we connect every pair of the same nodes in these two networks. According to the structure of this interdependent network with the optimal robustness, we propose a preferential attachment strategy. And by applying this preferential attachment strategy to three existing connectivity link addition strategies RA (random addition strategy), LD (low degree addition strategy) and LIDD (low inter degree-degree difference addition strategy), we find that each improved strategy is obviously better than before in improving the robustness of interdependent networks. Our findings can provide guidance on connectivity link addition strategy to improve robustness of interdependent networks against cascading failures.

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

    Directory of Open Access Journals (Sweden)

    Jiangfeng Wang

    2016-12-01

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

  17. 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…

  18. Intermittent Theta-Burst Stimulation of the Lateral Cerebellum Increases Functional Connectivity of the Default Network

    Science.gov (United States)

    Farzan, Faranak; Eldaief, Mark C.; Schmahmann, Jeremy D.; Pascual-Leone, Alvaro

    2014-01-01

    Cerebral cortical intrinsic connectivity networks share topographically arranged functional connectivity with the cerebellum. However, the contribution of cerebellar nodes to distributed network organization and function remains poorly understood. In humans, we applied theta-burst transcranial magnetic stimulation, guided by subject-specific connectivity, to regions of the cerebellum to evaluate the functional relevance of connections between cerebellar and cerebral cortical nodes in different networks. We demonstrate that changing activity in the human lateral cerebellar Crus I/II modulates the cerebral default mode network, whereas vermal lobule VII stimulation influences the cerebral dorsal attention system. These results provide novel insights into the distributed, but anatomically specific, modulatory impact of cerebellar effects on large-scale neural network function. PMID:25186750

  19. Spontaneous structure formation in a network of chaotic units with variable connection strengths.

    Science.gov (United States)

    Ito, Junji; Kaneko, Kunihiko

    2002-01-14

    As a model of temporally evolving networks, we consider a globally coupled logistic map with variable connection weights. The model exhibits self-organization of network structure, reflected by the collective behavior of units. Structural order emerges even without any interunit synchronization of dynamics. Within this structure, units spontaneously separate into two groups whose distinguishing feature is that the first group possesses many outwardly directed connections to the second group, while the second group possesses only a few outwardly directed connections to the first. The relevance of the results to structure formation in neural networks is briefly discussed.

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

    Science.gov (United States)

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

    2014-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Moriah E. Thomason

    2015-02-01

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

  2. Functional organization of intrinsic connectivity networks in Chinese-chess experts.

    Science.gov (United States)

    Duan, Xujun; Long, Zhiliang; Chen, Huafu; Liang, Dongmei; Qiu, Lihua; Huang, Xiaoqi; Liu, Timon Cheng-Yi; Gong, Qiyong

    2014-04-16

    The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low-frequency coherent neuronal fluctuations during a resting state condition. Accumulating evidence suggests that the overall organization of functional connectivity networks is associated with individual differences in cognitive performance and prior experience. Such an association raises the question of how cognitive expertise exerts an influence on the topological properties of large-scale functional networks. To address this question, we examined the overall organization of brain functional networks in 20 grandmaster and master level Chinese-chess players (GM/M) and twenty novice players, by means of resting-state functional connectivity and graph theoretical analyses. We found that, relative to novices, functional connectivity was increased in GM/Ms between basal ganglia, thalamus, hippocampus, and several parietal and temporal areas, suggesting the influence of cognitive expertise on intrinsic connectivity networks associated with learning and memory. Furthermore, we observed economical small-world topology in the whole-brain functional connectivity networks in both groups, but GM/Ms exhibited significantly increased values of normalized clustering coefficient which resulted in increased small-world topology. These findings suggest an association between the functional organization of brain networks and individual differences in cognitive expertise, which might provide further evidence of the mechanisms underlying expert behavior. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Dichotomous Dynamics in E-I Networks with Strongly and Weakly Intra-connected Inhibitory Neurons

    Directory of Open Access Journals (Sweden)

    Scott Rich

    2017-12-01

    Full Text Available The interconnectivity between excitatory and inhibitory neural networks informs mechanisms by which rhythmic bursts of excitatory activity can be produced in the brain. One such mechanism, Pyramidal Interneuron Network Gamma (PING, relies primarily upon reciprocal connectivity between the excitatory and inhibitory networks, while also including intra-connectivity of inhibitory cells. The causal relationship between excitatory activity and the subsequent burst of inhibitory activity is of paramount importance to the mechanism and has been well studied. However, the role of the intra-connectivity of the inhibitory network, while important for PING, has not been studied in detail, as most analyses of PING simply assume that inhibitory intra-connectivity is strong enough to suppress subsequent firing following the initial inhibitory burst. In this paper we investigate the role that the strength of inhibitory intra-connectivity plays in determining the dynamics of PING-style networks. We show that networks with weak inhibitory intra-connectivity exhibit variations in burst dynamics of both the excitatory and inhibitory cells that are not obtained with strong inhibitory intra-connectivity. Networks with weak inhibitory intra-connectivity exhibit excitatory rhythmic bursts with weak excitatory-to-inhibitory synapses for which classical PING networks would show no rhythmic activity. Additionally, variations in dynamics of these networks as the excitatory-to-inhibitory synaptic weight increases illustrates the important role that consistent pattern formation in the inhibitory cells serves in maintaining organized and periodic excitatory bursts. Finally, motivated by these results and the known diversity of interneurons, we show that a PING-style network with two inhibitory subnetworks, one strongly intra-connected and one weakly intra-connected, exhibits organized and periodic excitatory activity over a larger parameter regime than networks with a

  4. Directed connectivity of brain default networks in resting state using GCA and motif.

    Science.gov (United States)

    Jiao, Zhuqing; Wang, Huan; Ma, Kai; Zou, Ling; Xiang, Jianbo

    2017-06-01

    Nowadays, there is a lot of interest in assessing functional interactions between key brain regions. In this paper, Granger causality analysis (GCA) and motif structure are adopted to study directed connectivity of brain default mode networks (DMNs) in resting state. Firstly, the time series of functional magnetic resonance imaging (fMRI) data in resting state were extracted, and the causal relationship values of the nodes representing related brain regions are analyzed in time domain to construct a default network. Then, the network structures were searched from the default networks of controls and patients to determine the fixed connection mode in the networks. The important degree of motif structures in directed connectivity of default networks was judged according to p-value and Z-score. Both node degree and average distance were used to analyze the effect degree an information transfer rate of brain regions in motifs and default networks, and efficiency of the network. Finally, activity and functional connectivity strength of the default brain regions are researched according to the change of energy distributions between the normals and the patients' brain regions. Experimental results demonstrate that, both normal subjects and stroke patients have some corresponding fixed connection mode of three nodes, and the efficiency and power spectrum of the patient's default network is somewhat lower than that of the normal person. In particular, the Right Posterior Cingulate Gyrus (PCG.R) has a larger change in functional connectivity and its activity. The research results verify the feasibility of the application of GCA and motif structure to study the functional connectivity of default networks in resting state.

  5. Knowledge Access in Rural Inter-connected Areas Network ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    A third thematic network - on knowledge management strategies - will play an advisory and support role to the larger network. Project activities will include a call for ... Rapports. Learning from experience : a manual for organising, analysing and documenting field based information [Arabic language]. Téléchargez le PDF.

  6. Twitter Chats: Connect, Foster, and Engage Internal Extension Networks

    Science.gov (United States)

    Seger, Jamie; Hill, Paul; Stafne, Eric; Swadley, Emy

    2017-01-01

    The eXtension Educational Technology Learning Network (EdTechLN) has found Twitter to be an effective form of informal communication for routinely engaging network members. Twitter chats provide Extension professionals an opportunity to reach and engage one other. As the EdTechLN's experimentation with Twitter chats has demonstrated, the use of…

  7. Networked Connections and Experience of Liquid Love: A Qualitative Study on Female Students of Guilan University

    Directory of Open Access Journals (Sweden)

    Mohammad Amin Kanani

    2016-06-01

    Full Text Available Following the expansion of internet penetration, social interactions between the sexes have taken new dimensions. The objective of the present study is to investigate network connections of students and their attitudes towards these relationships using Zygmunt Bauman's theory of liquid love. The main research question is that in the online relations and friendships of students, which characteristics and consequences are identifiable? This research was conducted using qualitative method of Focus Group Discussions(FGDs among female students of Guilan University.The results revealed that two characteristics of network connections, namely, simplicity and anonymity, and also the only positive outcome of these connections, freedom, are the main causes of student’s tendency towards these connections. However, they are aware of negative consequences of network connections, mostly have positive attitudes regarding internet relations and friendships.

  8. Further evidence of alerted default network connectivity and association with theory of mind ability in schizophrenia.

    Science.gov (United States)

    Mothersill, Omar; Tangney, Noreen; Morris, Derek W; McCarthy, Hazel; Frodl, Thomas; Gill, Michael; Corvin, Aiden; Donohoe, Gary

    2017-06-01

    Resting-state functional magnetic resonance imaging (rs-fMRI) has repeatedly shown evidence of altered functional connectivity of large-scale networks in schizophrenia. The relationship between these connectivity changes and behaviour (e.g. symptoms, neuropsychological performance) remains unclear. Functional connectivity in 27 patients with schizophrenia or schizoaffective disorder, and 25 age and gender matched healthy controls was examined using rs-fMRI. Based on seed regions from previous studies, we examined functional connectivity of the default, cognitive control, affective and attention networks. Effects of symptom severity and theory of mind performance on functional connectivity were also examined. Patients showed increased connectivity between key nodes of the default network including the precuneus and medial prefrontal cortex compared to controls (pdefault regions within the patient group (pdefault hyper-connectivity in schizophrenia spectrum patients and reveals an association between altered default connectivity and positive symptom severity. As a novel find, this study also shows that default connectivity is correlated to and predictive of theory of mind performance. Extending these findings by examining the effects of emerging social cognition treatments on both default connectivity and theory of mind performance is now an important goal for research. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Traffic grooming in WDM optical network with grooming resources at Max Connectivity nodes

    Science.gov (United States)

    Paul, Partha; Rawat, Balbeer Singh; Ghorai, S. K.

    2012-12-01

    In this paper, we propose Max Connectivity grooming in WDM mesh networks under static lightpath connection requests. The grooming and wavelength conversion resources are placed at the nodes having maximum connections. We propose a heuristic genetic algorithm (GA) model to solve grooming, routing and wavelength assignment. The GA algorithm has been used to optimize the cost of grooming and wavelength conversion resources. The blocking probability has been investigated under different lightpath connections. The performance of Max Connectivity grooming has been compared with other grooming policies. Our results indicate the improvement of resource utilization with minimum blocking probability.

  10. 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.

  11. Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

    Science.gov (United States)

    Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

    2018-01-01

    Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are

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

    OpenAIRE

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

    2017-01-01

    As the world ages, it becomes urgent to unravel the mechanisms underlying brain aging and find ways of intervening with them. While for decades cognitive aging has been related to localized brain changes, growing attention is now being paid to alterations in distributed brain networks. Functional connectivity magnetic resonance imaging (fcMRI) has become a particularly useful tool to explore large-scale brain networks; yet, the temporal course of connectivity lifetime changes has not been est...

  13. Altered default mode and affective network connectivity in stroke patients with and without dysphagia.

    Science.gov (United States)

    Li, Shasha; Zhou, Muke; Yu, Bo; Ma, Zhenxing; Chen, Sihan; Gong, Qiyong; He, Li; Huang, Xiaoqi; Lui, Su; Wang, Xiaotong; Zhou, Dong; He, Chengqi

    2014-02-01

    Neuroimaging studies in stroke patients provide substantial evidence for the involvement of widespread cortical and subcortical regions in the control of swallowing. Although the affective network and the default mode network are functionally related to "autonomic" and "volitional" swallowing, little is known about their functional changes in dysphagic stroke patients. Unbiased seeds functional connectivity analysis was used to study the connectivity patterns of these resting-state networks. Resting-state functional magnetic resonance imaging was performed in stroke patients with (n = 12) and without dysphagia (n = 12). Compared with healthy controls, stroke patients with and without dysphagia had decreased functional connectivity in the default mode network and the affective network. Moreover, stroke patients with dysphagia also had decreased functional connectivity in both the default mode network and the affective network relative to patients without dysphagia. The difference in the extent of impairment in the default mode network and affective network of stroke patients with and without dysphagia may lead to improved understanding of the neuropathophysiological mechanism and rehabilitation of dysphagia.

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

    Science.gov (United States)

    Xing, Qi-Bin; Zhang, Yuan-Biao; Liang, Zhi-Ning; Zhang, Fan

    2011-12-01

    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.

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

    Science.gov (United States)

    Cui, Ying; Jiao, Yun; Chen, Hua-Jun; Ding, Jie; Luo, Bing; Peng, Cheng-Yu; Ju, Sheng-Hong; Teng, Gao-Jun

    2015-11-01

    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. • Type 2 diabetes mellitus is associated with impaired cognition • Default- mode network plays a central role in maintaining normal cognition • Network connectivity within the default mode was disrupted in type 2 diabetes patients • Decreased network connectivity was correlated with cognitive performance and insulin resistance level • Disrupted default-mode network might explain the impaired cognition in diabetic population.

  16. Topological probability and connection strength induced activity in complex neural networks

    International Nuclear Information System (INIS)

    Du-Qu, Wei; Bo, Zhang; Dong-Yuan, Qiu; Xiao-Shu, Luo

    2010-01-01

    Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world (SW) connections. Network elements are described by two-dimensional map neurons (2DMNs) with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied. (general)

  17. Cognitive behavioral therapy increases amygdala connectivity with the cognitive control network in both MDD and PTSD

    Directory of Open Access Journals (Sweden)

    Haochang Shou

    2017-01-01

    Conclusion: We found evidence for the hypothesis that CBT treatment is associated with changes in connectivity between the amygdala and the fronto-parietal network. CBT may work by strengthening connections between the amygdala and brain regions that are involved in cognitive control, potentially providing enhanced top-down control of affective processes that are dysregulated in both MDD and PTSD.

  18. Dysregulation of Microtubule Stability Impairs Morphofunctional Connectivity in Primary Neuronal Networks.

    Science.gov (United States)

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

    2017-01-01

    Functionally related neurons assemble into connected networks that process and transmit electrochemical information. To do this in a coordinated manner, the number and strength of synaptic connections is tightly regulated. Synapse function relies on the microtubule (MT) cytoskeleton, the dynamics of which are in turn controlled by a plethora of MT-associated proteins, including the MT-stabilizing protein Tau. Although mutations in the Tau-encoding MAPT gene underlie a set of neurodegenerative disorders, termed tauopathies, the exact contribution of MT dynamics and the perturbation thereof to neuronal network connectivity has not yet been scrutinized. Therefore, we investigated the impact of targeted perturbations of MT stability on morphological (e.g., neurite- and synapse density) and functional (e.g., synchronous calcium bursting) correlates of connectivity in networks of primary hippocampal neurons. We found that treatment with MT-stabilizing or -destabilizing compounds impaired morphofunctional connectivity in a reversible manner. We also discovered that overexpression of MAPT induced significant connectivity defects, which were accompanied by alterations in MT dynamics and increased resistance to pharmacological MT depolymerization. Overexpression of a MAPT variant harboring the P301L point mutation in the MT-binding domain did far less, directly linking neuronal connectivity with Tau's MT binding affinity. Our results show that MT stability is a vulnerable node in tauopathies and that its precise pharmacological tuning may positively affect neuronal network connectivity. However, a critical balance in MT turnover causes it to be a difficult therapeutic target with a narrow operating window.

  19. Dysregulation of Microtubule Stability Impairs Morphofunctional Connectivity in Primary Neuronal Networks

    Directory of Open Access Journals (Sweden)

    Peter Verstraelen

    2017-06-01

    Full Text Available Functionally related neurons assemble into connected networks that process and transmit electrochemical information. To do this in a coordinated manner, the number and strength of synaptic connections is tightly regulated. Synapse function relies on the microtubule (MT cytoskeleton, the dynamics of which are in turn controlled by a plethora of MT-associated proteins, including the MT-stabilizing protein Tau. Although mutations in the Tau-encoding MAPT gene underlie a set of neurodegenerative disorders, termed tauopathies, the exact contribution of MT dynamics and the perturbation thereof to neuronal network connectivity has not yet been scrutinized. Therefore, we investigated the impact of targeted perturbations of MT stability on morphological (e.g., neurite- and synapse density and functional (e.g., synchronous calcium bursting correlates of connectivity in networks of primary hippocampal neurons. We found that treatment with MT-stabilizing or -destabilizing compounds impaired morphofunctional connectivity in a reversible manner. We also discovered that overexpression of MAPT induced significant connectivity defects, which were accompanied by alterations in MT dynamics and increased resistance to pharmacological MT depolymerization. Overexpression of a MAPT variant harboring the P301L point mutation in the MT-binding domain did far less, directly linking neuronal connectivity with Tau's MT binding affinity. Our results show that MT stability is a vulnerable node in tauopathies and that its precise pharmacological tuning may positively affect neuronal network connectivity. However, a critical balance in MT turnover causes it to be a difficult therapeutic target with a narrow operating window.

  20. Community access networks: how to connect the next billion to the ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Community access networks: how to connect the next billion to the Internet. Despite recent progress with mobile technology diffusion, more than four billion people worldwide are unconnected and have limited access to global communication infrastructure. The cost of implementing connectivity infrastructure in underserved ...

  1. Resting-state connectivity and modulated somatomotor and default-mode networks in Huntington disease.

    Science.gov (United States)

    Sánchez-Castañeda, Cristina; de Pasquale, Francesco; Caravasso, Chiara Falletta; Marano, Massimo; Maffi, Sabrina; Migliore, Simone; Sabatini, Umberto; Squitieri, Ferdinando

    2017-06-01

    To analyze brain functional connectivity in the somatomotor and default-mode networks (DMNs) of patients with Huntington disease (HD), its relationship with gray matter (GM) volume loss, and functional changes after pridopidine treatment. Ten patients and ten untreated controls underwent T1-weighted imaging and resting-state functional magnetic resonance imaging (fMRI); four patients were also assessed after 3 months of pridopidine treatment (90 mg/d). The seed-based functional connectivity patterns from the posterior cingulate cortex and the supplementary motor area (SMA), considered cortical hubs of the DMN and somatomotor networks, respectively, were computed. FMRIB Software Library voxel-based morphometry measured GM volume. Patients had GM volume decrease in all cortical and subcortical areas of the somatomotor network with preservation of the SMA, and increased somatomotor and DMN connectivity. In DMN structures, functional connectivity impairment preceded volume loss. Pridopidine reduced the intensity of these aberrant connections. The abnormal connectivity of the somatomotor and DMN observed in HD patients may represent an early dysfunction marker, as it preceded volume loss in DMN. Pridopidine reduced connectivity of these networks in all four treated patients, suggesting that connectivity is sensitive to treatment response. © 2017 John Wiley & Sons Ltd.

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

    DEFF Research Database (Denmark)

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

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

  3. 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.

  4. 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 interpersonalrelationships. 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 as korisknik different social networks.

  5. Graph Analysis and Modularity of Brain Functional Connectivity Networks: Searching for the Optimal Threshold

    Directory of Open Access Journals (Sweden)

    Cécile Bordier

    2017-08-01

    Full Text Available Neuroimaging data can be represented as networks of nodes and edges that capture the topological organization of the brain connectivity. Graph theory provides a general and powerful framework to study these networks and their structure at various scales. By way of example, community detection methods have been widely applied to investigate the modular structure of many natural networks, including brain functional connectivity networks. Sparsification procedures are often applied to remove the weakest edges, which are the most affected by experimental noise, and to reduce the density of the graph, thus making it theoretically and computationally more tractable. However, weak links may also contain significant structural information, and procedures to identify the optimal tradeoff are the subject of active research. Here, we explore the use of percolation analysis, a method grounded in statistical physics, to identify the optimal sparsification threshold for community detection in brain connectivity networks. By using synthetic networks endowed with a ground-truth modular structure and realistic topological features typical of human brain functional connectivity networks, we show that percolation analysis can be applied to identify the optimal sparsification threshold that maximizes information on the networks' community structure. We validate this approach using three different community detection methods widely applied to the analysis of brain connectivity networks: Newman's modularity, InfoMap and Asymptotical Surprise. Importantly, we test the effects of noise and data variability, which are critical factors to determine the optimal threshold. This data-driven method should prove particularly useful in the analysis of the community structure of brain networks in populations characterized by different connectivity strengths, such as patients and controls.

  6. CONNECTIONS USING SOCIAL NETWORKS AND SOCIAL INTELLIGENCE OF STUDENTS

    OpenAIRE

    Belma Duvnjak; Jasna Bajraktarević

    2013-01-01

    Social intelligence is the ability and skills to cope with everyday life situations and how to cope with interpersonalrelationships. 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 Most...

  7. Changes in dynamic resting state network connectivity following aphasia therapy.

    Science.gov (United States)

    Duncan, E Susan; Small, Steven L

    2017-10-24

    Resting state magnetic resonance imaging (rsfMRI) permits observation of intrinsic neural networks produced by task-independent correlations in low frequency brain activity. Various resting state networks have been described, with each thought to reflect common engagement in some shared function. There has been limited investigation of the plasticity in these network relationships after stroke or induced by therapy. Twelve individuals with language disorders after stroke (aphasia) were imaged at multiple time points before (baseline) and after an imitation-based aphasia therapy. Language assessment using a narrative production task was performed at the same time points. Group independent component analysis (ICA) was performed on the rsfMRI data to identify resting state networks. A sliding window approach was then applied to assess the dynamic nature of the correlations among these networks. Network correlations during each 30-second window were used to cluster the data into ten states for each window at each time point for each subject. Correlation was performed between changes in time spent in each state and therapeutic gains on the narrative task. The amount of time spent in a single one of the (ten overall) dynamic states was positively associated with behavioral improvement on the narrative task at the 6-week post-therapy maintenance interval, when compared with either baseline or assessment immediately following therapy. This particular state was characterized by minimal correlation among the task-independent resting state networks. Increased functional independence and segregation of resting state networks underlies improvement on a narrative production task following imitation-based aphasia treatment. This has important clinical implications for the targeting of noninvasive brain stimulation in post-stroke remediation.

  8. Geometry of river networks. III. Characterization of component connectivity

    International Nuclear Information System (INIS)

    Dodds, Peter Sheridan; Rothman, Daniel H.

    2001-01-01

    Essential to understanding the overall structure of river networks is a knowledge of their detailed architecture. Here we explore the presence of randomness in river network structure and the details of its consequences. We first show that an averaged view of network architecture is provided by a proposed self-similarity statement about the scaling of drainage density, a local measure of stream concentration. This scaling of drainage density is shown to imply Tokunaga's law, a description of the scaling of side branch abundance along a given stream, as well as a scaling law for stream lengths. We then consider fluctuations in drainage density and consequently the numbers of side branches. Data are analyzed for the Mississippi River basin and a model of random directed networks. Numbers of side streams are found to follow exponential distributions, as are intertributary distances along streams. Finally, we derive a joint variation of side stream abundance with stream length, affording a full description of fluctuations in network structure. Fluctuations in side stream numbers are shown to be a direct result of fluctuations in stream lengths. This is the last paper in a series of three on the geometry of river networks

  9. Default-mode network connectivity and white matter burden in late-life depression.

    Science.gov (United States)

    Wu, Minjie; Andreescu, Carmen; Butters, Meryl A; Tamburo, Robert; Reynolds, Charles F; Aizenstein, Howard

    2011-10-31

    The brain's default-mode network has been the focus of intense research. This study characterizes the default-mode network activity in late-life depression and the correlation of the default-mode network activity changes with the white-matter hyperintensities burden. We hypothesized that elderly depressed subjects would have altered default-mode network activity, which would correlate with the increased white-matter hyperintensities burden. Twelve depressed subjects (mean Hamilton Depression Rating Scale 19.8±4.1, mean age 70.5±4.9) and 12 non-depressed, comparison subjects (mean age 69±6.5) were included. Functional magnetic resonance imaging (fMRI) data were collected while subjects performed a low cognitive load, event-related task. We compared the default-mode network activity in these groups (including depressed subjects pre- and post-antidepressant treatment). We analyzed the resting connectivity patterns of the posterior cingulate cortex. Deconvolution was used to evaluate the correlation of resting-state connectivity scores with the white-matter hyperintensities burden. Compared with non-depressed elderly, depressed subjects pretreatment had decreased connectivity in the subgenual anterior cingulate cortex and increased connectivity in the dorsomedial prefrontal cortex and the orbito-frontal cortex. The abnormal connectivity was significantly correlated with the white-matter hyperintensities burden. Remitted elderly depressed subjects had improved functional connectivity compared to pretreatment, although alterations persisted in the anterior cingulate and the prefrontal cortex when remitted elderly depressed subjects were compared with non-depressed elderly. Our study provides evidence for altered default-mode network connectivity in late-life depression. The correlation between white-matter hyperintensities burden and default-mode network connectivity emphasizes the role of vascular changes in late-life depression etiopathogenesis. Copyright © 2011

  10. Renewal-anomalous-heterogeneous files

    International Nuclear Information System (INIS)

    Flomenbom, Ophir

    2010-01-01

    Renewal-anomalous-heterogeneous files are solved. A simple file is made of Brownian hard spheres that diffuse stochastically in an effective 1D channel. Generally, Brownian files are heterogeneous: the spheres' diffusion coefficients are distributed and the initial spheres' density is non-uniform. In renewal-anomalous files, the distribution of waiting times for individual jumps is not exponential as in Brownian files, yet obeys: ψ α (t)∼t -1-α , 0 2 >, obeys, 2 >∼ 2 > nrml α , where 2 > nrml is the MSD in the corresponding Brownian file. This scaling is an outcome of an exact relation (derived here) connecting probability density functions of Brownian files and renewal-anomalous files. It is also shown that non-renewal-anomalous files are slower than the corresponding renewal ones.

  11. Social Connection Dynamics in a Health Promotion Network

    NARCIS (Netherlands)

    Fernandes de Mello Araujo, Eric; Klein, Michel; van Halteren, Aart

    2016-01-01

    The influence of social connections on human behaviour has been demonstrated in many occasions. This paper presents the analysis of the dynamic properties of longitudinal (335 days) community data (n=3,375 participants) from an online health promotion program. The community data is unique as it

  12. Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity

    Science.gov (United States)

    Yeh, Hsiang J.; Guindani, Michele; Vannucci, Marina; Haneef, Zulfi; Stern, John M.

    2018-01-01

    Estimation of functional connectivity (FC) has become an increasingly powerful tool for investigating healthy and abnormal brain function. Static connectivity, in particular, has played a large part in guiding conclusions from the majority of resting-state functional MRI studies. However, accumulating evidence points to the presence of temporal fluctuations in FC, leading to increasing interest in estimating FC as a dynamic quantity. One central issue that has arisen in this new view of connectivity is the dramatic increase in complexity caused by dynamic functional connectivity (dFC) estimation. To computationally handle this increased complexity, a limited set of dFC properties, primarily the mean and variance, have generally been considered. Additionally, it remains unclear how to integrate the increased information from dFC into pattern recognition techniques for subject-level prediction. In this study, we propose an approach to address these two issues based on a large number of previously unexplored temporal and spectral features of dynamic functional connectivity. A Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to estimate time-varying patterns of functional connectivity between resting-state networks. Time-frequency analysis is then performed on dFC estimates, and a large number of previously unexplored temporal and spectral features drawn from signal processing literature are extracted for dFC estimates. We apply the investigated features to two neurologic populations of interest, healthy controls and patients with temporal lobe epilepsy, and show that the proposed approach leads to substantial increases in predictive performance compared to both traditional estimates of static connectivity as well as current approaches to dFC. Variable importance is assessed and shows that there are several quantities that can be extracted from dFC signal which are more informative than the traditional mean or variance of dFC. This work

  13. Abnormal connectivity in the sensorimotor network predicts attention deficits in traumatic brain injury.

    Science.gov (United States)

    Shumskaya, Elena; van Gerven, Marcel A J; Norris, David G; Vos, Pieter E; Kessels, Roy P C

    2017-03-01

    The aim of this study was to explore modifications of functional connectivity in multiple resting-state networks (RSNs) after moderate to severe traumatic brain injury (TBI) and evaluate the relationship between functional connectivity patterns and cognitive abnormalities. Forty-three moderate/severe TBI patients and 34 healthy controls (HC) underwent resting-state fMRI. Group ICA was applied to identify RSNs. Between-subject analysis was performed using dual regression. Multiple linear regressions were used to investigate the relationship between abnormal connectivity strength and neuropsychological outcome. Forty (93%) TBI patients showed moderate disability, while 2 (5%) and 1 (2%) upper severe disability and low good recovery, respectively. TBI patients performed worse than HC on the domains attention and language. We found increased connectivity in sensorimotor, visual, default mode (DMN), executive, and cerebellar RSNs after TBI. We demonstrated an effect of connectivity in the sensorimotor RSN on attention (p < 10 -3 ) and a trend towards a significant effect of the DMN connectivity on attention (p = 0.058). A group-by-network interaction on attention was found in the sensorimotor network (p = 0.002). In TBI, attention was positively related to abnormal connectivity within the sensorimotor RSN, while in HC this relation was negative. Our results show altered patterns of functional connectivity after TBI. Attention impairments in TBI were associated with increased connectivity in the sensorimotor network. Further research is needed to test whether attention in TBI patients is directly affected by changes in functional connectivity in the sensorimotor network or whether the effect is actually driven by changes in the DMN.

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

    Directory of Open Access Journals (Sweden)

    Rong Li

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

  15. How to ensure reliable connectivity for aerial vehicles over cellular networks

    DEFF Research Database (Denmark)

    Nguyen, Huan Cong; Amorim, Rafhael Medeiros de; Wigard, Jeroen

    2018-01-01

    Widely deployed cellular networks are an attractive solution to provide large scale radio connectivity to unmanned aerial vehicles. One main prerequisite is that co-existence and optimal performance for both aerial and terrestrial users can be provided. Today’s cellular networks are, however, not...

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  17. An investigation into the functional and structural connectivity of the Default Mode Network

    NARCIS (Netherlands)

    van Oort, E.S.B.; van Cappellen van Walsum, Anne-Marie; Norris, David Gordon

    2014-01-01

    Connectivity analyses based on both resting-state (rs-)fMRI and diffusion weighted imaging studies suggest that the human brain contains regions that act as hubs for the entire brain, and that elements of the Default Mode Network (DMN) play a pivotal role in this network. In the present study, the

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

    Directory of Open Access Journals (Sweden)

    Laura Anne Wortinger

    Full Text Available 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.

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

    NARCIS (Netherlands)

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

    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

  20. Decreased triple network connectivity in patients with post-traumatic stress disorder

    Science.gov (United States)

    Liu, Yang; Li, Liang; Li, Baojuan; Zhang, Xi; Lu, Hongbing

    2017-03-01

    The triple network model provides a common framework for understanding affective and neurocognitive dysfunctions across multiple disorders, including central executive network (CEN), default mode network (DMN), and salience network (SN). Considering the effect of traumatic experience on post-traumatic stress disorder (PTSD), this study aims to explore the alteration of triple network connectivity in a specific PTSD induced by a single prolonged trauma exposure. With arterial spin labeling sequence, three networks were identified using independent component analysis in 10 PTSD patients and 10 healthy survivors, who experienced the same coal mining flood disaster. In PTSD patients, decreased connectivity was identified in left middle frontal gyrus of CEN, left precuneus and bilateral superior frontal gyrus of DMN, and right anterior insula of SN. The decreased connectivity in left middle frontal gyrus was identified to associate with clinical severity. These results indicated the decreased triple network connectivity, which not only supported the proposal of the triple network model, but also prompted possible neurobiology mechanism of cognitive dysfunction for this kind of PTSD.

  1. Changes in Effective Connectivity Network Patterns in Drug Abusers, Treated With Different Methods

    Directory of Open Access Journals (Sweden)

    Arash Zare Sadeghi

    2017-07-01

    Conclusion: This study revealed an activation network similar to the emotional and inhibitory control networks observed in drug abusers in previous works. The results of DCM analysis also support the regulatory role of frontal regions on bottom regions. Furthermore, this study demonstrates the different effective connectivity patterns after drug abuse treatment and in this way helps the experts in the field.

  2. A fully connected network of Bernoulli units with correlation learning

    Science.gov (United States)

    Dente, J. A.; Vilela Mendes, R.

    1996-02-01

    Biological evidence suggests that pattern recognition and associative memory in the mammalian nervous system operates through the establishment of spatio-temporal patterns of activity and not by the evolution towards an equilibrium point as in attractor neural networks. Information is carried by the space-time correlation of the activity intensities rather than by the details of individual neuron signals. Furthermore the fast recognition times that are achieved with relatively slow biological neurons seem to be associated to the chaotic nature of the basal nervous activity. To copy the biology hardware may not be technologically sound, but to look for inspiration in the efficient biological information processing methods is an idea that deserves consideration. Inspired by the mechanisms at work in the mammalian olfactory system we study a network where, in the absence of external inputs, the units have a dynamics of the Bernoulli shift type. When an external signal is presented, the pattern of excitation bursts depends on the learning history of the network. Association and pattern identification in the network operates by the selection, by the external stimulus, of distinct invariant measures in the chaotic system. The simplicity of the node dynamics, that is chosen, allows a reasonable analytical control of the network behavior.

  3. An efficient optical architecture for sparsely connected neural networks

    Science.gov (United States)

    Hine, Butler P., III; Downie, John D.; Reid, Max B.

    1990-01-01

    An architecture for general-purpose optical neural network processor is presented in which the interconnections and weights are formed by directing coherent beams holographically, thereby making use of the space-bandwidth products of the recording medium for sparsely interconnected networks more efficiently that the commonly used vector-matrix multiplier, since all of the hologram area is in use. An investigation is made of the use of computer-generated holograms recorded on such updatable media as thermoplastic materials, in order to define the interconnections and weights of a neural network processor; attention is given to limits on interconnection densities, diffraction efficiencies, and weighing accuracies possible with such an updatable thin film holographic device.

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Tanya eWen

    2016-02-01

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

  6. Remote effects of hippocampal damage on default network connectivity in the human brain.

    Science.gov (United States)

    Frings, Lars; Schulze-Bonhage, Andreas; Spreer, Joachim; Wagner, Kathrin

    2009-12-01

    In the healthy human brain the hippocampus is known to work in concert with a variety of cortical brain regions. It has recently been linked to the default network of the brain, with the precuneus being its core hub. Here we studied the remote effects of damage to the hippocampus on functional connectivity patterns of the precuneus. From 14 epilepsy patients with selective, unilateral hippocampal sclerosis and 8 healthy control subjects, we acquired functional MRI data during performance of an object-location memory task. We assessed functional connectivity of a functionally defined region in the precuneus, which showed the typical properties of the default network: significant task-related deactivation, which was reduced in patients compared to control subjects. In control subjects, a largely symmetrical pattern of functional coherence to the precuneus emerged, including canonical default network areas such as ventral medial prefrontal cortex, inferior parietal cortex, and the hippocampi. Assessment of group differences within the default network areas revealed reduced connectivity to the precuneus in ipsilesional middle temporal gyrus and hippocampus in left hippocampal sclerosis patients compared to controls. Furthermore, left hippocampal sclerosis patients showed lower connectivity than right hippocampal sclerosis patients in left middle temporal gyrus, ventral medial prefrontal cortex, and left amygdala. We report remote effects of unilateral hippocampal damage on functional connectivity between distant brain regions associated with the default network of the human brain. These preliminary results underline the impact of circumscribed pathology on functionally connected brain regions.

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

    Science.gov (United States)

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

    2014-01-15

    Functional magnetic resonance imaging studies have shown that the insular cortex has a significant role in pain identification 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 subjects 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 importance of the interaction between these regions in pain processing.

  8. Disrupted functional connectivity of the default mode network due to acute vestibular deficit

    Directory of Open Access Journals (Sweden)

    Carsten M. Klingner

    2014-01-01

    Here, we employ functional magnetic resonance imaging (fMRI in the resting state to investigate changes in the functional connectivity between the DMN and task-positive networks, in a longitudinal design combined with measurements of caloric function. We demonstrate an initially disturbed connectedness of the DMN after vestibular neuritis. We hypothesize that the disturbed connectivity between the default mode network and particular parts of the task-positive network might be related to a sustained utilization of processing capacity by diverging sensory information. The current results provide some insights into mechanisms of central compensation following an acute vestibular deficit and the importance of the DMN in this disease.

  9. Leadership Insularity: A New Measure of Connectivity Between Central Nodes in Networks

    Science.gov (United States)

    Arbesman, Samuel; Christakis, Nicholas A.

    2010-01-01

    We combine two foci of interest with respect to community identification and node centrality and create a novel metric termed “leadership insularity.” By determining the most highly connected nodes within each community of a network, we designate the ‘community leaders’ within the graph. In doing this, we have the basis for a novel metric that examines how connected, or disconnected, the leaders are to each other. This measure has a number of appealing measurement properties and provides a new way of understanding how network structure can affect its dynamics, especially information flow. We explore leadership insularity in a variety of networks. PMID:24648604

  10. Implementation of a digital cross-connect switch to a GSM network testing environment

    OpenAIRE

    Haverinen, Perttu

    2010-01-01

    Purpose of this thesis was to implement a Nokia Digital Cross-Connect Switch for Time-Division Multiplexing (SXC T) device to a telecommunication testing laboratory. Thesis work was done in local Nokia Siemens Networks corporation site in Tampere, Finland. SXC T acts as a device that interconnects network elements and enables dynamic, software based switching and creation of circuits. Tasks of device are similar to a typical IP network packet switch, but with enhanced features. It provides th...

  11. 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

    -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......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...

  12. Accelerated Monte Carlo system reliability analysis through machine-learning-based surrogate models of network connectivity

    International Nuclear Information System (INIS)

    Stern, R.E.; Song, J.; Work, D.B.

    2017-01-01

    The two-terminal reliability problem in system reliability analysis is known to be computationally intractable for large infrastructure graphs. Monte Carlo techniques can estimate the probability of a disconnection between two points in a network by selecting a representative sample of network component failure realizations and determining the source-terminal connectivity of each realization. To reduce the runtime required for the Monte Carlo approximation, this article proposes an approximate framework in which the connectivity check of each sample is estimated using a machine-learning-based classifier. The framework is implemented using both a support vector machine (SVM) and a logistic regression based surrogate model. Numerical experiments are performed on the California gas distribution network using the epicenter and magnitude of the 1989 Loma Prieta earthquake as well as randomly-generated earthquakes. It is shown that the SVM and logistic regression surrogate models are able to predict network connectivity with accuracies of 99% for both methods, and are 1–2 orders of magnitude faster than using a Monte Carlo method with an exact connectivity check. - Highlights: • Surrogate models of network connectivity are developed by machine-learning algorithms. • Developed surrogate models can reduce the runtime required for Monte Carlo simulations. • Support vector machine and logistic regressions are employed to develop surrogate models. • Numerical example of California gas distribution network demonstrate the proposed approach. • The developed models have accuracies 99%, and are 1–2 orders of magnitude faster than MCS.

  13. 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.

  14. Insecure Network, Unknown Connection: Understanding Wi-Fi Privacy Assumptions of Mobile Device Users

    Directory of Open Access Journals (Sweden)

    Bram Bonné

    2017-07-01

    Full Text Available Smartphones and other mobile devices have proliferated in the past five years. The expectation of mobile device users to always be online has led to Wi-Fi networks being offered by a variety of providers. Using these networks introduces multiple security risks. In this work, we assess to what extent the privacy stance of mobile device users corresponds with their actual behavior by conducting a study with 108 participants. Our methodology consists of monitoring Wi-Fi networks that the participants’ devices connect to and the connections made by apps on these devices, for a period of 30 days. Afterwards, participants are surveyed about their awareness and privacy sensitiveness. We show that while a higher expertise in computer networks corresponds to more awareness about the connections made by apps, neither this expertise nor the actual privacy stance of the participant translates to better security habits. Moreover, participants in general were unaware about a significant part of connections made by apps on their devices, a matter that is worsened by the fact that one third of Wi-Fi networks that participants connect to do not have any security enabled. Based on our results, we provide recommendations to network providers, developers and users on how to improve Wi-Fi security for mobile devices.

  15. Functional Network Connectivity Patterns between Idiopathic Generalized Epilepsy with Myoclonic and Absence Seizures

    Directory of Open Access Journals (Sweden)

    Qifu Li

    2017-05-01

    Full Text Available The extensive cerebral cortex and subcortical structures are considered as the major regions related to the generalized epileptiform discharges in idiopathic generalized epilepsy. However, various clinical syndromes and electroencephalogram (EEG signs exist across generalized seizures, such as the loss of consciousness during absence seizures (AS and the jerk of limbs during myoclonic seizures (MS. It is presumed that various functional systems affected by discharges lead to the difference in syndromes of these seizures. Twenty epileptic patients with MS, 21 patients with AS, and 21 healthy controls were recruited in this study. The functional network connectivity was analyzed based on the resting-state functional magnetic resonance imaging scans. The statistical analysis was performed in three groups to assess the difference in the functional brain networks in two types of generalized seizures. Twelve resting-state networks were identified in three groups. Both patient groups showed common abnormalities, including decreased functional connectivity in salience network (SN, cerebellum network, and primary perceptional networks and decreased connection between SN and visual network, compared with healthy controls. Interestingly, the frontal part of high-level cognitive resting-state networks showed increased functional connectivity (FC in patients with MS, but decreased FC in patients with AS. Moreover, patients with MS showed decreased negative connections between high-level cognitive networks and primary system. The common alteration in both patient groups, including SN, might reflect a similar mechanism associated with the loss of consciousness during generalized seizures. This study provided the evidence of brain network in generalized epilepsy to understand the difference between MS and AS.

  16. Early development of structural networks and the impact of prematurity on brain connectivity.

    Science.gov (United States)

    Batalle, Dafnis; Hughes, Emer J; Zhang, Hui; Tournier, J-Donald; Tusor, Nora; Aljabar, Paul; Wali, Luqman; Alexander, Daniel C; Hajnal, Joseph V; Nosarti, Chiara; Edwards, A David; Counsell, Serena J

    2017-04-01

    Preterm infants are at high risk of neurodevelopmental impairment, which may be due to altered development of brain connectivity. We aimed to (i) assess structural brain development from 25 to 45 weeks gestational age (GA) using graph theoretical approaches and (ii) test the hypothesis that preterm birth results in altered white matter network topology. Sixty-five infants underwent MRI between 25 +3 and 45 +6 weeks GA. Structural networks were constructed using constrained spherical deconvolution tractography and were weighted by measures of white matter microstructure (fractional anisotropy, neurite density and orientation dispersion index). We observed regional differences in brain maturation, with connections to and from deep grey matter showing most rapid developmental changes during this period. Intra-frontal, frontal to cingulate, frontal to caudate and inter-hemispheric connections matured more slowly. We demonstrated a core of key connections that was not affected by GA at birth. However, local connectivity involving thalamus, cerebellum, superior frontal lobe, cingulate gyrus and short range cortico-cortical connections was related to the degree of prematurity and contributed to altered global topology of the structural brain network. The relative preservation of core connections at the expense of local connections may support more effective use of impaired white matter reserve following preterm birth. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  17. A multiscale network analysis of protected-area connectivity for mammals in the United States.

    Science.gov (United States)

    Minor, Emily S; Lookingbill, Todd R

    2010-12-01

    Protected areas must be close, or connected, enough to allow for the preservation of large-scale ecological and evolutionary processes, such as gene flow, migration, and range shifts in response to climate change. Nevertheless, it is unknown whether the network of protected areas in the United States is connected in a way that will preserve biodiversity over large temporal and spatial scales. It is also unclear whether protected-area networks that function for larger species will function for smaller species. We assessed the connectivity of protected areas in the three largest biomes in the United States. With methods from graph theory--a branch of mathematics that deals with connectivity and flow--we identified and measured networks of protected areas for three different groups of mammals. We also examined the value of using umbrella species (typically large-bodied, far-ranging mammals) in designing large-scale networks of protected areas. Although the total amount of protected land varied greatly among biomes in the United States, overall connectivity did not. In general, protected-area networks were well connected for large mammals but not for smaller mammals. Additionally, it was not possible to predict connectivity for small mammals on the basis of connectivity for large mammals, which suggests the umbrella species approach may not be an appropriate design strategy for conservation networks intended to protect many species. Our findings indicate different strategies should be used to increase the likelihood of persistence for different groups of species. Strategic linkages of existing lands should be a conservation priority for smaller mammals, whereas conservation of larger mammals would benefit most from the protection of more land. © 2010 Society for Conservation Biology.

  18. Rod-Shaped Neural Units for Aligned 3D Neural Network Connection.

    Science.gov (United States)

    Kato-Negishi, Midori; Onoe, Hiroaki; Ito, Akane; Takeuchi, Shoji

    2017-08-01

    This paper proposes neural tissue units with aligned nerve fibers (called rod-shaped neural units) that connect neural networks with aligned neurons. To make the proposed units, 3D fiber-shaped neural tissues covered with a calcium alginate hydrogel layer are prepared with a microfluidic system and are cut in an accurate and reproducible manner. These units have aligned nerve fibers inside the hydrogel layer and connectable points on both ends. By connecting the units with a poly(dimethylsiloxane) guide, 3D neural tissues can be constructed and maintained for more than two weeks of culture. In addition, neural networks can be formed between the different neural units via synaptic connections. Experimental results indicate that the proposed rod-shaped neural units are effective tools for the construction of spatially complex connections with aligned nerve fibers in vitro. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Pathloss Measurements and Modeling for UAVs Connected to Cellular Networks

    DEFF Research Database (Denmark)

    Amorim, Rafhael Medeiros de; Mogensen, Preben Elgaard; Sørensen, Troels Bundgaard

    2017-01-01

    . The measurements were conducted in an operating LTE network (850 MHz), using a commercial cell phone, placed inside the frame of the UAV. Trials were conducted for UAV flying at 5 different heights measured above ground level (20, 40, 60, 80 and 100m) and a pathloss regression line was obtained from results. Then...

  20. Low-stress bicycling and network connectivity : [research brief].

    Science.gov (United States)

    2012-05-01

    In one sense, a citys or regions bicycling network includes all of its roads and paths on which bicycling is permitted. However, some streets provide such a poor level of safety and comfort for bicycling that the majority of the population cons...

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

    NARCIS (Netherlands)

    Boonstra, T.W.; Danna-Dos-Santos, A.; Xie, H-B; Roerdink, M.; Stins, J.F.; Breakspear, M.

    2015-01-01

    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

  2. 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.

  3. 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

  4. A Space Operations Network Alternative: Using 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. Shifted intrinsic connectivity of central executive and salience network in borderline personality disorder

    Directory of Open Access Journals (Sweden)

    Anselm eDoll

    2013-10-01

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

  6. 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.

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

    Directory of Open Access Journals (Sweden)

    Karen eCampbell

    2013-11-01

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

  8. Flexible modulation of network connectivity related to cognition in Alzheimer's disease.

    Science.gov (United States)

    McLaren, Donald G; Sperling, Reisa A; Atri, Alireza

    2014-10-15

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

  9. Decreased middle temporal gyrus connectivity in the language network in schizophrenia patients with auditory verbal hallucinations.

    Science.gov (United States)

    Zhang, Linchuan; Li, Baojuan; Wang, Huaning; Li, Liang; Liao, Qimei; Liu, Yang; Bao, Xianghong; Liu, Wenlei; Yin, Hong; Lu, Hongbing; Tan, Qingrong

    2017-07-13

    As the most common symptoms of schizophrenia, the long-term persistence of obstinate auditory verbal hallucinations (AVHs) brings about great mental pain to patients. Neuroimaging studies of schizophrenia have indicated that AVHs were associated with altered functional and structural connectivity within the language network. However, effective connectivity that could reflect directed information flow within this network and is of great importance to understand the neural mechanisms of the disorder remains largely unknown. In this study, we utilized stochastic dynamic causal modeling (DCM) to investigate directed connections within the language network in schizophrenia patients with and without AVHs. Thirty-six patients with schizophrenia (18 with AVHs and 18 without AVHs), and 37 healthy controls participated in the current resting-state functional magnetic resonance imaging (fMRI) study. The results showed that the connection from the left inferior frontal gyrus (LIFG) to left middle temporal gyrus (LMTG) was significantly decreased in patients with AVHs compared to those without AVHs. Meanwhile, the effective connection from the left inferior parietal lobule (LIPL) to LMTG was significantly decreased compared to the healthy controls. Our findings suggest aberrant pattern of causal interactions within the language network in patients with AVHs, indicating that the hypoconnectivity or disrupted connection from frontal to temporal speech areas might be critical for the pathological basis of AVHs. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. A generative modeling approach to connectivity-Electrical conduction in vascular networks

    DEFF Research Database (Denmark)

    Hald, Bjørn Olav

    2016-01-01

    The physiology of biological structures is inherently dynamic and emerges from the interaction and assembly of large collections of small entities. The extent of coupled entities complicates modeling and increases computational load. Here, microvascular networks are used to present a novel...... generative approach to connectivity based on the observation that biological organization is hierarchical and composed of a limited set of building blocks, i.e. a vascular network consists of blood vessels which in turn are composed by one or more cell types. Fast electrical communication is crucial...... to synchronize vessel tone across the vast distances within a network. We hypothesize that electrical conduction capacity is delimited by the size of vascular structures and connectivity of the network. Generation and simulation of series of dynamical models of electrical spread within vascular networks...

  11. Structural and functional properties of a probabilistic model of neuronal connectivity in a simple locomotor network

    Science.gov (United States)

    Merrison-Hort, Robert; Soffe, Stephen R; Borisyuk, Roman

    2018-01-01

    Although, in most animals, brain connectivity varies between individuals, behaviour is often similar across a species. What fundamental structural properties are shared across individual networks that define this behaviour? We describe a probabilistic model of connectivity in the hatchling Xenopus tadpole spinal cord which, when combined with a spiking model, reliably produces rhythmic activity corresponding to swimming. The probabilistic model allows calculation of structural characteristics that reflect common network properties, independent of individual network realisations. We use the structural characteristics to study examples of neuronal dynamics, in the complete network and various sub-networks, and this allows us to explain the basis for key experimental findings, and make predictions for experiments. We also study how structural and functional features differ between detailed anatomical connectomes and those generated by our new, simpler, model (meta-model). PMID:29589828

  12. Reduced functional connectivity of somatosensory network in writer's cramp patients.

    Science.gov (United States)

    Cheng, Chia-Hsiung; Tseng, Yi-Jhan; Chen, Rou-Shayn; Lin, Yung-Yang

    2016-03-01

    The involvement of motor cortex and sensorimotor integration in patients with writer's cramp (WC) has been well documented. However, the exact neurophysiological profile within the somatosensory system, including primary somatosensory cortex (SI), contralateral (SIIc), and ipsilateral (SIIi) secondary somatosensory areas remains less understood. This study investigated the neuromagnetic cortical activities of median nerve stimulation in 10 patients with WC and 10 healthy controls (HC). To comprehensively explore all the aspects of somatosensory functioning, we analyzed our data with the minimum norm estimate (MNE), the time-frequency approach with evoked and induced activities, and functional connectivity between SI and SIIc (SI-SIIc), SI and SIIi (SI-SIIi), and SIIc and SIIi (SIIc-SIIi) from theta to gamma oscillations. No significant between-group differences were found in the MNE cortical amplitudes of SI, SIIc, and SIIi. Power strengths of evoked gamma oscillation and induced beta synchronization were also equivalent between WC and HC groups. However, we found significantly reduced theta coherence of SI-SIIi, alpha coherence of SI-SIIi and SIIc-SIIi, as well as beta coherence of SIIc-SIIi in patients with WC. Our results suggest the involvement of somatosensory abnormalities, primarily with the form of functional connectivity, in patients with WC.

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

    International Nuclear Information System (INIS)

    Cui, Ying; Jiao, Yun; Chen, Hua-Jun; Ding, Jie; Luo, Bing; Peng, Cheng-Yu; Ju, Sheng-Hong; Teng, Gao-Jun

    2015-01-01

    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.)

  14. Stomach-brain synchrony reveals a novel, delayed-connectivity resting-state network in humans.

    Science.gov (United States)

    Rebollo, Ignacio; Devauchelle, Anne-Dominique; Béranger, Benoît; Tallon-Baudry, Catherine

    2018-03-21

    Resting-state networks offer a unique window into the brain's functional architecture, but their characterization remains limited to instantaneous connectivity thus far. Here, we describe a novel resting-state network based on the delayed connectivity between the brain and the slow electrical rhythm (0.05 Hz) generated in the stomach. The gastric network cuts across classical resting-state networks with partial overlap with autonomic regulation areas. This network is composed of regions with convergent functional properties involved in mapping bodily space through touch, action or vision, as well as mapping external space in bodily coordinates. The network is characterized by a precise temporal sequence of activations within a gastric cycle, beginning with somato-motor cortices and ending with the extrastriate body area and dorsal precuneus. Our results demonstrate that canonical resting-state networks based on instantaneous connectivity represent only one of the possible partitions of the brain into coherent networks based on temporal dynamics. © 2018, Rebollo et al.

  15. Dynamic network participation of functional connectivity hubs assessed by resting-state fMRI.

    Science.gov (United States)

    Schaefer, Alexander; Margulies, Daniel S; Lohmann, Gabriele; Gorgolewski, Krzysztof J; Smallwood, Jonathan; Kiebel, Stefan J; Villringer, Arno

    2014-01-01

    Network studies of large-scale brain connectivity have demonstrated that highly connected areas, or "hubs," are a key feature of human functional and structural brain organization. We use resting-state functional MRI data and connectivity clustering to identify multi-network hubs and show that while hubs can belong to multiple networks their degree of integration into these different networks varies dynamically over time. The extent of the network variation was related to the connectedness of the hub. In addition, we found that these network dynamics were inversely related to positive self-generated thoughts reported by individuals and were further decreased with older age. Moreover, the left caudate varied its degree of participation between a default mode subnetwork and a limbic network. This variation was predictive of individual differences in the reports of past-related thoughts. These results support an association between ongoing thought processes and network dynamics and offer a new approach to investigate the brain dynamics underlying mental experience.

  16. 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.)

  17. 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.

  18. Altered Functional Connectivity of the Default Mode Network in Low-Empathy Subjects.

    Science.gov (United States)

    Kim, Seung Jun; Kim, Sung Eun; Kim, Hyo Eun; Han, Kiwan; Jeong, Bumseok; Kim, Jae Jin; Namkoong, Kee; Kim, Ji Woong

    2017-09-01

    Empathy is the ability to identify with or make a vicariously experience of another person's feelings or thoughts based on memory and/or self-referential mental simulation. The default mode network in particular is related to self-referential empathy. In order to elucidate the possible neural mechanisms underlying empathy, we investigated the functional connectivity of the default mode network in subjects from a general population. Resting state functional magnetic resonance imaging data were acquired from 19 low-empathy subjects and 18 medium-empathy subjects. An independent component analysis was used to identify the default mode network, and differences in functional connectivity strength were compared between the two groups. The low-empathy group showed lower functional connectivity of the medial prefrontal cortex and anterior cingulate cortex (Brodmann areas 9 and 32) within the default mode network, compared to the medium-empathy group. The results of the present study suggest that empathy is related to functional connectivity of the medial prefrontal cortex/anterior cingulate cortex within the default mode network. Functional decreases in connectivity among low-empathy subjects may reflect an impairment of self-referential mental simulation. © Copyright: Yonsei University College of Medicine 2017.

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

    Directory of Open Access Journals (Sweden)

    Peng Fang

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

  20. Simulating urban growth by emphasis on connective routes network (case study: Bojnourd city

    Directory of Open Access Journals (Sweden)

    Mehdi Saadat Novin

    2017-06-01

    Full Text Available Development of urban construction and ever-increasing growth of population lead to landuse changes especially in agricultural lands, which play an important role in providing human food. According to this issue, a proper landuse planning is required to protecting and preserving the valuable agricultural lands and environment, in today’s world. The prediction of urban growth can help in understanding the potential impacts on a region’s water resource, economy and people. One of the effective parameters in development of cities is connective routes network and their different types and qualities that play an important role in decreasing or increasing the growth of the city. On the other hand, the type of the connective routes network is an important factor for the speed and quality of development. In this paper, two different scenarios were used to simulate landuse changes and analyzing their results. In first scenario, modeling is based on the effective parameters in urban growth without classification of connective routes network. In the second scenario, effective parameters in urban growth were considered and connective routes were classified in 6 different classes with different weights in order to examine their effect on urban development. Simulation of landuse has been carried out for 2020–2050. The results clearly showed the effect of the connective routes network classification in output maps so that the effect of the first and second main routes network in development, is conspicuous.

  1. Identifying disease foci from static and dynamic effective connectivity networks: Illustration in soldiers with trauma.

    Science.gov (United States)

    Rangaprakash, D; Dretsch, Michael N; Venkataraman, Archana; Katz, Jeffrey S; Denney, Thomas S; Deshpande, Gopikrishna

    2018-01-01

    Brain connectivity studies report group differences in pairwise connection strengths. While informative, such results are difficult to interpret since our understanding of the brain relies on region-based properties, rather than on connection information. Given that large disruptions in the brain are often caused by a few pivotal sources, we propose a novel framework to identify the sources of functional disruption from effective connectivity networks. Our approach integrates static and time-varying effective connectivity modeling in a probabilistic framework, to identify aberrant foci and the corresponding aberrant connectomics network. Using resting-state fMRI, we illustrate the utility of this novel approach in U.S. Army soldiers (N = 87) with posttraumatic stress disorder (PTSD), mild traumatic brain injury (mTBI) and combat controls. Additionally, we employed machine-learning classification to identify those significant connectivity features that possessed high predictive ability. We identified three disrupted foci (middle frontal gyrus [MFG], insula, hippocampus), and an aberrant prefrontal-subcortical-parietal network of information flow. We found the MFG to be the pivotal focus of network disruption, with aberrant strength and temporal-variability of effective connectivity to the insula, amygdala and hippocampus. These connectivities also possessed high predictive ability (giving a classification accuracy of 81%); and they exhibited significant associations with symptom severity and neurocognitive functioning. In summary, dysregulation originating in the MFG caused elevated and temporally less-variable connectivity in subcortical regions, followed by a similar effect on parietal memory-related regions. This mechanism likely contributes to the reduced control over traumatic memories leading to re-experiencing, hyperarousal and flashbacks observed in soldiers with PTSD and mTBI. Hum Brain Mapp 39:264-287, 2018. © 2017 Wiley Periodicals, Inc. © 2017

  2. Anticipating changes to future connectivity within a network of marine protected areas.

    Science.gov (United States)

    Coleman, Melinda A; Cetina-Heredia, Paulina; Roughan, Moninya; Feng, Ming; van Sebille, Erik; Kelaher, Brendan P

    2017-09-01

    Continental boundary currents are projected to be altered under future scenarios of climate change. As these currents often influence dispersal and connectivity among populations of many marine organisms, changes to boundary currents may have dramatic implications for population persistence. Networks of marine protected areas (MPAs) often aim to maintain connectivity, but anticipation of the scale and extent of climatic impacts on connectivity are required to achieve this critical conservation goal in a future of climate change. For two key marine species (kelp and sea urchins), we use oceanographic modelling to predict how continental boundary currents are likely to change connectivity among a network of MPAs spanning over 1000 km of coastline off the coast of eastern Australia. Overall change in predicted connectivity among pairs of MPAs within the network did not change significantly over and above temporal variation within climatic scenarios, highlighting the need for future studies to incorporate temporal variation in dispersal to robustly anticipate likely change. However, the intricacies of connectivity between different pairs of MPAs were noteworthy. For kelp, poleward connectivity among pairs of MPAs tended to increase in the future, whereas equatorward connectivity tended to decrease. In contrast, for sea urchins, connectivity among pairs of MPAs generally decreased in both directions. Self-seeding within higher-latitude MPAs tended to increase, and the role of low-latitude MPAs as a sink for urchins changed significantly in contrasting ways. These projected changes have the potential to alter important genetic parameters with implications for adaptation and ecosystem vulnerability to climate change. Considering such changes, in the context of managing and designing MPA networks, may ensure that conservation goals are achieved into the future. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

  3. Improved Road-Network-Flow Control Strategy Based on Macroscopic Fundamental Diagrams and Queuing Length in Connected-Vehicle Network

    Directory of Open Access Journals (Sweden)

    Xiaohui Lin

    2017-01-01

    Full Text Available Connected-vehicles network provides opportunities and conditions for improving traffic signal control, and macroscopic fundamental diagrams (MFD can control the road network at the macrolevel effectively. This paper integrated proposed real-time access to the number of mobile vehicles and the maximum road queuing length in the Connected-vehicles network. Moreover, when implementing a simple control strategy to limit the boundary flow of a road network based on MFD, we determined whether the maximum queuing length of each boundary section exceeds the road-safety queuing length in real-time calculations and timely adjusted the road-network influx rate to avoid the overflow phenomenon in the boundary section. We established a road-network microtraffic simulation model in VISSIM software taking a district as the experimental area, determined MFD of the region based on the number of mobile vehicles, and weighted traffic volume of the road network. When the road network was tending to saturate, we implemented a simple control strategy and our algorithm limits the boundary flow. Finally, we compared the traffic signal control indicators with three strategies: (1 no control strategy, (2 boundary control, and (3 boundary control with limiting queue strategy. The results show that our proposed algorithm is better than the other two.

  4. 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.

  5. 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 ...... 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....

  6. 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.

  7. A New Delay Connection for Long Short-Term Memory Networks.

    Science.gov (United States)

    Wang, Jianyong; Zhang, Lei; Chen, Yuanyuan; Yi, Zhang

    2017-12-17

    Connections play a crucial role in neural network (NN) learning because they determine how information flows in NNs. Suitable connection mechanisms may extensively enlarge the learning capability and reduce the negative effect of gradient problems. In this paper, a new delay connection is proposed for Long Short-Term Memory (LSTM) unit to develop a more sophisticated recurrent unit, called Delay Connected LSTM (DCLSTM). The proposed delay connection brings two main merits to DCLSTM with introducing no extra parameters. First, it allows the output of the DCLSTM unit to maintain LSTM, which is absent in the LSTM unit. Second, the proposed delay connection helps to bridge the error signals to previous time steps and allows it to be back-propagated across several layers without vanishing too quickly. To evaluate the performance of the proposed delay connections, the DCLSTM model with and without peephole connections was compared with four state-of-the-art recurrent model on two sequence classification tasks. DCLSTM model outperformed the other models with higher accuracy and F1[Formula: see text]score. Furthermore, the networks with multiple stacked DCLSTM layers and the standard LSTM layer were evaluated on Penn Treebank (PTB) language modeling. The DCLSTM model achieved lower perplexity (PPL)/bit-per-character (BPC) than the standard LSTM model. The experiments demonstrate that the learning of the DCLSTM models is more stable and efficient.

  8. A neural network model to minimize the connected dominating set for self-configuration of wireless sensor networks.

    Science.gov (United States)

    He, Hongmei; Zhu, Zhenhuan; Mäkinen, Erkki

    2009-06-01

    A wireless ad hoc sensor network consists of a number of sensors spreading across a geographical area. The performance of the network suffers as the number of nodes grows, and a large sensor network quickly becomes difficult to manage. Thus, it is essential that the network be able to self-organize. Clustering is an efficient approach to simplify the network structure and to alleviate the scalability problem. One method to create clusters is to use weakly connected dominating sets (WCDSs). Finding the minimum WCDS in an arbitrary graph is an NP-complete problem. We propose a neural network model to find the minimum WCDS in a wireless sensor network. We present a directed convergence algorithm. The new algorithm outperforms the normal convergence algorithm both in efficiency and in the quality of solutions. Moreover, it is shown that the neural network is robust. We investigate the scalability of the neural network model by testing it on a range of sized graphs and on a range of transmission radii. Compared with Guha and Khuller's centralized algorithm, the proposed neural network with directed convergency achieves better results when the transmission radius is short, and equal performance when the transmission radius becomes larger. The parallel version of the neural network model takes time O(d), where d is the maximal degree in the graph corresponding to the sensor network, while the centralized algorithm takes O(n2). We also investigate the effect of the transmission radius on the size of WCDS. The results show that it is important to select a suitable transmission radius to make the network stable and to extend the lifespan of the network. The proposed model can be used on sink nodes in sensor networks, so that a sink node can inform the nodes to be a coordinator (clusterhead) in the WCDS obtained by the algorithm. Thus, the message overhead is O(M), where M is the size of the WCDS.

  9. 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.

  10. On the deployment of a connected sensor network for confident information coverage.

    Science.gov (United States)

    Xu, Huping; Zhu, Jiajun; Wang, Bang

    2015-05-14

    Coverage and connectivity are two important performance metrics in wireless sensor networks. In this paper, we study the sensor placement problem to achieve both coverage and connectivity. Instead of using the simplistic disk coverage model, we use our recently proposed confident information coverage model as the sensor coverage model. The grid approach is applied to discretize the sensing field, and our objective is to place the minimum number of sensors to form a connected network and to provide confident information coverage for all of the grid points. We first formulate the sensor placement problem as a constrained optimization problem. Then, two heuristic algorithms, namely the connected cover formation (CCF) algorithm and the cover formation and relay placement with redundancy removal (CFRP-RR) algorithm, are proposed to find the approximate solutions for the sensor placement problem. The simulation results validate their effectiveness, and the CCF algorithm performs slightly better than the CFRP-RR algorithm.

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

    DEFF Research Database (Denmark)

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

    2017-01-01

    Working memory (WM) impairment is regarded as a core aspect of schizophrenia. However, the neural mechanisms behind this cognitive deficit remain unclear. The connectivity of a frontoparietal network is known to be important for subserving WM. Using functional magnetic resonance imaging, the curr......Working memory (WM) impairment is regarded as a core aspect of schizophrenia. However, the neural mechanisms behind this cognitive deficit remain unclear. The connectivity of a frontoparietal network is known to be important for subserving WM. Using functional magnetic resonance imaging...... between regions (left inferior frontal gyrus (IFG), left inferior parietal lobe (IPL), and primary visual area) identified in a psychophysiological interaction (PPI) analysis was performed to characterize effective connectivity during the n-back task. The PPI analysis revealed that the connectivity...

  12. Synchronization landscapes in small-world-connected computer networks

    Science.gov (United States)

    Guclu, Hasan

    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 also study the role of various complex communication topologies as synchronization networks. 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, oil 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 synchronization. This leads to a fully scalable parallel simulation for underlying systems with asynchronous dynamics and short-range interactions. We study both short-range and small-world synchronization topologies in one- and two-dimensional systems. We also provide a coarse-grained description for the small-world-synchronized virtual-time horizon and compare the findings to those obtained by "simulating the simulations" based on the exact algorithmic rules. We also present numerical results for the evolution of the virtual-tithe horizon oil scale-free Barabasi-Albert networks serving as communication topology among the processing elements. Finally, we investigate to what extent small-world couplings (extending the original local relaxational dynamics through the random links) lead to the suppression of extreme fluctuations in the synchronization landscape. In the

  13. Connectivity in gene coexpression networks negatively correlates with rates of molecular evolution in flowering plants.

    Science.gov (United States)

    Masalia, Rishi R; Bewick, Adam J; Burke, John M

    2017-01-01

    Gene coexpression networks are a useful tool for summarizing transcriptomic data and providing insight into patterns of gene regulation in a variety of species. Though there has been considerable interest in studying the evolution of network topology across species, less attention has been paid to the relationship between network position and patterns of molecular evolution. Here, we generated coexpression networks from publicly available expression data for seven flowering plant taxa (Arabidopsis thaliana, Glycine max, Oryza sativa, Populus spp., Solanum lycopersicum, Vitis spp., and Zea mays) to investigate the relationship between network position and rates of molecular evolution. We found a significant negative correlation between network connectivity and rates of molecular evolution, with more highly connected (i.e., "hub") genes having significantly lower nonsynonymous substitution rates and dN/dS ratios compared to less highly connected (i.e., "peripheral") genes across the taxa surveyed. These findings suggest that more centrally located hub genes are, on average, subject to higher levels of evolutionary constraint than are genes located on the periphery of gene coexpression networks. The consistency of this result across disparate taxa suggests that it holds for flowering plants in general, as opposed to being a species-specific phenomenon.

  14. 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. © 2016 by the Ecological Society of America.

  15. 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.

  16. Method of Geometric Connected Disk Cover Problem for UAV realy network deployment

    Directory of Open Access Journals (Sweden)

    Chuang Liu

    2017-01-01

    Full Text Available Aiming at the problem of the effective connectivity of a large number of mobile combat units in the future aeronautic swarm operation, this paper proposes an idea of using UAV(Unmanned Aerial Vehicle to build, and studies the deployment of the network. User coverage and network connectivity are important for a relay network planning which are studied separately in traditional ways. In order to effectively combine these two factors while the network’s survivability is taken into account. Firstly, the concept of node aggregation degree is proposed. Secondly, a performance evaluation parameter for UAV relay network is proposed based on node aggregation degree, then analyzes the lack of deterministic deployment and presents one a PSO (VFA-PSO deployment algorithm based on virtual force. Finally, compared with the existing algorithms, the validity and stability of the algorithm are verified. The experimental results show that the VFA-PSO algorithm can effectively improve the network coverage and the survivability of the network under the premise of ensuring the network connectivity, and has better deployment effect.

  17. A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

    Science.gov (United States)

    Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

    2017-04-01

    The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of

  18. 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

  19. 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. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  20. Functional Connectivity with Distinct Neural Networks Tracks Fluctuations in Gain/Loss Framing Susceptibility

    Science.gov (United States)

    Smith, David V.; Sip, Kamila E.; Delgado, Mauricio R.

    2016-01-01

    Multiple large-scale neural networks orchestrate a wide range of cognitive processes. For example, interoceptive processes related to self-referential thinking have been linked to the default-mode network (DMN); whereas exteroceptive processes related to cognitive control have been linked to the executive-control network (ECN). Although the DMN and ECN have been postulated to exert opposing effects on cognition, it remains unclear how connectivity with these spatially overlapping networks contribute to fluctuations in behavior. While previous work has suggested the medial prefrontal cortex (MPFC) is involved in behavioral change following feedback, these observations could be linked to interoceptive processes tied to DMN or exteroceptive processes tied to ECN because MPFC is positioned in both networks. To address this problem, we employed independent component analysis combined with dual-regression functional connectivity analysis. Participants made a series of financial decisions framed as monetary gains or losses. In some sessions, participants received feedback from a peer observing their choices; in other sessions, feedback was not provided. Following feedback, framing susceptibility—indexed as the increase in gambling behavior in loss frames compared to gain frames—was heightened in some participants and diminished in others. We examined whether these individual differences were linked to differences in connectivity by contrasting sessions containing feedback against those that did not contain feedback. We found two key results. As framing susceptibility increased, the MPFC increased connectivity with DMN; in contrast, temporal-parietal junction decreased connectivity with the ECN. Our results highlight how functional connectivity patterns with distinct neural networks contribute to idiosyncratic behavioral changes. PMID:25858445

  1. Cognitive behavioral therapy increases amygdala connectivity with the cognitive control network in both MDD and PTSD.

    Science.gov (United States)

    Shou, Haochang; Yang, Zhen; Satterthwaite, Theodore D; Cook, Philip A; Bruce, Steven E; Shinohara, Russell T; Rosenberg, Benjamin; Sheline, Yvette I

    2017-01-01

    Both major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) are characterized by alterations in intrinsic functional connectivity. Here we investigated changes in intrinsic functional connectivity across these disorders as a function of cognitive behavioral therapy (CBT), an effective treatment in both disorders. 53 unmedicated right-handed participants were included in a longitudinal study. Patients were diagnosed with PTSD ( n  = 18) and MDD ( n  = 17) with a structured diagnostic interview and treated with 12 sessions of manualized CBT over a 12-week period. Patients received an MRI scan (Siemens 3 T Trio) before and after treatment. Longitudinal functional principal components analysis (LFPCA) was performed on functional connectivity of the bilateral amygdala with the fronto-parietal network. A matched healthy control group ( n  = 18) was also scanned twice for comparison. LFPCA identified four eigenimages or principal components (PCs) that contributed significantly to the longitudinal change in connectivity. The second PC differentiated CBT-treated patients from controls in having significantly increased connectivity of the amygdala with the fronto-parietal network following CBT. Analysis of CBT-induced amygdala connectivity changes was restricted to the a priori determined fronto-parietal network. Future studies are needed to determine the generalizability of these findings, given the small and predominantly female sample. We found evidence for the hypothesis that CBT treatment is associated with changes in connectivity between the amygdala and the fronto-parietal network. CBT may work by strengthening connections between the amygdala and brain regions that are involved in cognitive control, potentially providing enhanced top-down control of affective processes that are dysregulated in both MDD and PTSD.

  2. Resting-State EEG Oscillatory Dynamics in Fragile X Syndrome: Abnormal Functional Connectivity and Brain Network Organization

    NARCIS (Netherlands)

    van der Molen, M.J.W.; Stam, C.J.; van der Molen, M.W.

    2014-01-01

    Disruptions in functional connectivity and dysfunctional brain networks are considered to be a neurological hallmark of neurodevelopmental disorders. Despite the vast literature on functional brain connectivity in typical brain development, surprisingly few attempts have been made to characterize

  3. 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

    2014-11-01

    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. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  4. Disrupted modularity and local connectivity of brain functional networks in childhood-onset schizophrenia

    Directory of Open Access Journals (Sweden)

    Aaron F Alexander-Bloch

    2010-10-01

    Full Text Available Modularity is a fundamental concept in systems neuroscience, referring to the formation of local cliques or modules of densely intra-connected nodes that are sparsely inter-connected with nodes in other modules. Topological modularity of brain functional networks can quantify theoretically anticipated abnormality of brain network community structure--so called dysmodularity--in developmental disorders such as childhood-onset schizophrenia (COS. We used graph theory to investigate topology of networks derived from resting-state fMRI data on 13 COS patients and 19 healthy volunteers. We measured functional connectivity between each pair of 100 regional nodes, focusing on wavelet correlation in the frequency interval 0.05-0.1 Hz, then applied global and local thresholding rules to construct graphs from each individual association matrix over the full range of possible connection densities. We show how local thresholding based on the minimum spanning tree facilitates group comparisons of networks by forcing the connectedness of sparse graphs. Threshold-dependent graph theoretical results are compatible with the results of a k-means unsupervised learning algorithm and a multi-resolution (spin glass approach to modularity, both of which also find community structure but do not require thresholding of the association matrix. In general modularity of brain functional networks was significantly reduced in COS, due to a relatively reduced density of intra-modular connections between neighboring regions. Other network measures of local organization such as clustering were also decreased, while complementary measures of global efficiency and robustness were increased, in the COS group. The group differences in complex network properties were mirrored by differences in simpler statistical properties of the data, such as the variability of the global time series and the internal homogeneity of the time series within anatomical regions of interest.

  5. How Much Control is Enough for Network Connectivity Preservation and Collision Avoidance?

    Science.gov (United States)

    Chen, Zhiyong; Fan, Ming-Can; Zhang, Hai-Tao

    2015-08-01

    For a multiagent system in free space, the agents are required to generate sufficiently large cohesive force for network connectivity preservation and sufficiently large repulsive force for collision avoidance. This paper gives an energy function based approach for estimating the control force in a general setting. In particular, the force estimated for network connectivity preservation and collision avoidance is separated from the force for other collective behavior of the agents. Moreover, the estimation approach is applied in three typical collective control scenarios including swarming, flocking, and flocking without velocity measurement.

  6. 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.

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

    Science.gov (United States)

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

    2017-02-01

    Overvaluation of palatable food is a primary driver of obesity, and is associated with brain regions of the reward system. However, it remains unclear if this network is specialized in food reward, or generally involved in reward processing. We used functional magnetic resonance imaging (fMRI) to characterize functional connectivity during processing of food and monetary rewards. Thirty-nine adults with excess weight and 37 adults with normal weight performed the Willingness to Pay for Food task and the Monetary Incentive Delay task in the fMRI scanner. A data-driven graph approach was applied to compare whole-brain, task-related functional connectivity between groups. Excess weight was associated with decreased functional connectivity during the processing of food rewards in a network involving primarily frontal and striatal areas, and increased functional connectivity during the processing of monetary rewards in a network involving principally frontal and parietal areas. These two networks were topologically and anatomically distinct, and were independently associated with BMI. The processing of food and monetary rewards involve segregated neural networks, and both are altered in individuals with excess weight. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications.

    Directory of Open Access Journals (Sweden)

    Bosiljka Tadić

    Full Text Available Human behaviour in various circumstances mirrors the corresponding brain connectivity patterns, which are suitably represented by functional brain networks. While the objective analysis of these networks by graph theory tools deepened our understanding of brain functions, the multi-brain structures and connections underlying human social behaviour remain largely unexplored. In this study, we analyse the aggregate graph that maps coordination of EEG signals previously recorded during spoken communications in two groups of six listeners and two speakers. Applying an innovative approach based on the algebraic topology of graphs, we analyse higher-order topological complexes consisting of mutually interwoven cliques of a high order to which the identified functional connections organise. Our results reveal that the topological quantifiers provide new suitable measures for differences in the brain activity patterns and inter-brain synchronisation between speakers and listeners. Moreover, the higher topological complexity correlates with the listener's concentration to the story, confirmed by self-rating, and closeness to the speaker's brain activity pattern, which is measured by network-to-network distance. The connectivity structures of the frontal and parietal lobe consistently constitute distinct clusters, which extend across the listener's group. Formally, the topology quantifiers of the multi-brain communities exceed the sum of those of the participating individuals and also reflect the listener's rated attributes of the speaker and the narrated subject. In the broader context, the presented study exposes the relevance of higher topological structures (besides standard graph measures for characterising functional brain networks under different stimuli.

  9. 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.

  10. Increased functional connectivity within memory networks following memory rehabilitation in multiple sclerosis.

    Science.gov (United States)

    Leavitt, Victoria M; Wylie, Glenn R; Girgis, Peter A; DeLuca, John; Chiaravalloti, Nancy D

    2014-09-01

    Identifying effective behavioral treatments to improve memory in persons with learning and memory impairment is a primary goal for neurorehabilitation researchers. Memory deficits are the most common cognitive symptom in multiple sclerosis (MS), and hold negative professional and personal consequences for people who are often in the prime of their lives when diagnosed. A 10-session behavioral treatment, the modified Story Memory Technique (mSMT), was studied in a randomized, placebo-controlled clinical trial. Behavioral improvements and increased fMRI activation were shown after treatment. Here, connectivity within the neural networks underlying memory function was examined with resting-state functional connectivity (RSFC) in a subset of participants from the clinical trial. We hypothesized that the treatment would result in increased integrity of connections within two primary memory networks of the brain, the hippocampal memory network, and the default network (DN). Seeds were placed in left and right hippocampus, and the posterior cingulate cortex. Increased connectivity was found between left hippocampus and cortical regions specifically involved in memory for visual imagery, as well as among critical hubs of the DN. These results represent the first evidence for efficacy of a behavioral intervention to impact the integrity of neural networks subserving memory functions in persons with MS.

  11. Correlation Networks for Identifying Changes in Brain Connectivity during Epileptiform Discharges and Transcranial Magnetic Stimulation

    Directory of Open Access Journals (Sweden)

    Elsa Siggiridou

    2014-07-01

    Full Text Available The occurrence of epileptiform discharges (ED in electroencephalographic (EEG recordings of patients with epilepsy signifies a change in brain dynamics and particularly brain connectivity. Transcranial magnetic stimulation (TMS has been recently acknowledged as a non-invasive brain stimulation technique that can be used in focal epilepsy for therapeutic purposes. In this case study, it is investigated whether simple time-domain connectivity measures, namely cross-correlation and partial cross-correlation, can detect alterations in the connectivity structure estimated from selected EEG channels before and during ED, as well as how this changes with the application of TMS. The correlation for each channel pair is computed on non-overlapping windows of 1 s duration forming weighted networks. Further, binary networks are derived by thresholding or statistical significance tests (parametric and randomization tests. The information for the binary networks is summarized by statistical network measures, such as the average degree and the average path length. Alterations of brain connectivity before, during and after ED with or without TMS are identified by statistical analysis of the network measures at each state.

  12. 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.

  13. Network analysis of mesoscale optical recordings to assess regional, functional connectivity.

    Science.gov (United States)

    Lim, Diana H; LeDue, Jeffrey M; Murphy, Timothy H

    2015-10-01

    With modern optical imaging methods, it is possible to map structural and functional connectivity. Optical imaging studies that aim to describe large-scale neural connectivity often need to handle large and complex datasets. In order to interpret these datasets, new methods for analyzing structural and functional connectivity are being developed. Recently, network analysis, based on graph theory, has been used to describe and quantify brain connectivity in both experimental and clinical studies. We outline how to apply regional, functional network analysis to mesoscale optical imaging using voltage-sensitive-dye imaging and channelrhodopsin-2 stimulation in a mouse model. We include links to sample datasets and an analysis script. The analyses we employ can be applied to other types of fluorescence wide-field imaging, including genetically encoded calcium indicators, to assess network properties. We discuss the benefits and limitations of using network analysis for interpreting optical imaging data and define network properties that may be used to compare across preparations or other manipulations such as animal models of disease.

  14. Simulation of dynamic expansion, contraction, and connectivity in a mountain stream network

    Science.gov (United States)

    Ward, Adam S.; Schmadel, Noah M.; Wondzell, Steven M.

    2018-04-01

    Headwater stream networks expand and contract in response to changes in stream discharge. The changes in the extent of the stream network are also controlled by geologic or geomorphic setting - some reaches go dry even under relatively wet conditions, other reaches remain flowing under relatively dry conditions. While such patterns are well recognized, we currently lack tools to predict the extent of the stream network and the times and locations where the network is dry within large river networks. Here, we develop a perceptual model of the river corridor in a headwater mountainous catchment, translate this into a reduced-complexity mechanistic model, and implement the model to examine connectivity and network extent over an entire water year. Our model agreed reasonably well with our observations, showing that the extent and connectivity of the river network was most sensitive to hydrologic forcing under the lowest discharges (Qgauge 10 L s-1) the extent of the network was relatively insensitive to hydrologic forcing and was instead determined by the network topology. We do not expect that the specific thresholds observed in this study would be transferable to other catchments with different geology, topology, or hydrologic forcing. However, we expect that the general pattern should be robust: the dominant controls will shift from hydrologic forcing to geologic setting as discharge increases. Furthermore, our method is readily transferable as the model can be applied with minimal data requirements (a single stream gauge, a digital terrain model, and estimates of hydrogeologic properties) to estimate flow duration or connectivity along the river corridor in unstudied catchments. As the available information increases, the model could be better calibrated to match site-specific observations of network extent, locations of dry reaches, or solute break through curves as demonstrated in this study. Based on the low initial data requirements and ability to later tune

  15. A network of networks model to study phase synchronization using structural connection matrix of human brain

    Science.gov (United States)

    Ferrari, F. A. S.; Viana, R. L.; Reis, A. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.

    2018-04-01

    The cerebral cortex plays a key role in complex cortical functions. It can be divided into areas according to their function (motor, sensory and association areas). In this paper, the cerebral cortex is described as a network of networks (cortex network), we consider that each cortical area is composed of a network with small-world property (cortical network). The neurons are assumed to have bursting properties with the dynamics described by the Rulkov model. We study the phase synchronization of the cortex network and the cortical networks. In our simulations, we verify that synchronization in cortex network is not homogeneous. Besides, we focus on the suppression of neural phase synchronization. Synchronization can be related to undesired and pathological abnormal rhythms in the brain. For this reason, we consider the delayed feedback control to suppress the synchronization. We show that delayed feedback control is efficient to suppress synchronous behavior in our network model when an appropriate signal intensity and time delay are defined.

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

    Directory of Open Access Journals (Sweden)

    Le The Dung

    2017-03-01

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

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

    OpenAIRE

    Sauve, Alix Marianne Carine; Thébault, Elisa; Pocock, Michael J. O.; Fontaine, Colin

    2015-01-01

    International audience; 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 dat...

  18. Role of connectivity in immune and neural network models: memory development and aging.

    Science.gov (United States)

    Remondini, Daniel; Bazzani, Armando; Franceschi, Claudio; Bersani, Ferdinando; Verondini, Ettore; Castellani, Gastone

    2003-01-01

    In this paper we analyzed how connectivity (defined as number of connections between network elements) can affect the memory capacity of a network-based model of the Immune System (IS) and of a model of the Nervous System (NS) synaptic plasticity (BCM model). The key point is the concept of competition between the characteristic variables that represent the response of such systems to environmental stimuli: the clonal concentrations for the IS, and the neuron responses for the BCM model. The memory states of both systems are characterized by a high selectivity to specific input patterns, reflecting a similar behaviour of their development rules. This selectivity property of memory states can be controlled by changing the degree of the internal connectivity in each system. We can explain the changes occurring in IS memory states during lifespan as due to a reshaping of its internal connectivity. This assumption is in agreement with experimental observations, reporting an increase of IS memory cells during lifespan. The change of connectivity in the BCM model leads to the introduction of quasilocal variables governing the plasticity of groups of synaptic junctions. This could be interpreted as the result of a refinement of neuron internal mechanisms during development, or it could be seen as a different learning rule deriving from the original BCM theory. We argue that connectivity seems to play an important role in a large class of biological systems controlled by competition mechanisms. Moreover, changes in connectivity may lead to changes in memory properties during development and aging.

  19. 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.

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

    Science.gov (United States)

    2012-01-01

    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. PMID:22462685

  1. Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture

    Directory of Open Access Journals (Sweden)

    Regina J. Meszlényi

    2017-10-01

    Full Text Available Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN. Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.

  2. Functional connectivity within and between intrinsic brain networks correlates with trait mind wandering.

    Science.gov (United States)

    Godwin, Christine A; Hunter, Michael A; Bezdek, Matthew A; Lieberman, Gregory; Elkin-Frankston, Seth; Romero, Victoria L; Witkiewitz, Katie; Clark, Vincent P; Schumacher, Eric H

    2017-08-01

    Individual differences across a variety of cognitive processes are functionally associated with individual differences in intrinsic networks such as the default mode network (DMN). The extent to which these networks correlate or anticorrelate has been associated with performance in a variety of circumstances. Despite the established role of the DMN in mind wandering processes, little research has investigated how large-scale brain networks at rest relate to mind wandering tendencies outside the laboratory. Here we examine the extent to which the DMN, along with the dorsal attention network (DAN) and frontoparietal control network (FPCN) correlate with the tendency to mind wander in daily life. Participants completed the Mind Wandering Questionnaire and a 5-min resting state fMRI scan. In addition, participants completed measures of executive function, fluid intelligence, and creativity. We observed significant positive correlations between trait mind wandering and 1) increased DMN connectivity at rest and 2) increased connectivity between the DMN and FPCN at rest. Lastly, we found significant positive correlations between trait mind wandering and fluid intelligence (Ravens) and creativity (Remote Associates Task). We interpret these findings within the context of current theories of mind wandering and executive function and discuss the possibility that certain instances of mind wandering may not be inherently harmful. Due to the controversial nature of global signal regression (GSReg) in functional connectivity analyses, we performed our analyses with and without GSReg and contrast the results from each set of analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Spike-Triggered Regression for Synaptic Connectivity Reconstruction in Neuronal Networks.

    Science.gov (United States)

    Zhang, Yaoyu; Xiao, Yanyang; Zhou, Douglas; Cai, David

    2017-01-01

    How neurons are connected in the brain to perform computation is a key issue in neuroscience. Recently, the development of calcium imaging and multi-electrode array techniques have greatly enhanced our ability to measure the firing activities of neuronal populations at single cell level. Meanwhile, the intracellular recording technique is able to measure subthreshold voltage dynamics of a neuron. Our work addresses the issue of how to combine these measurements to reveal the underlying network structure. We propose the spike-triggered regression (STR) method, which employs both the voltage trace and firing activity of the neuronal population to reconstruct the underlying synaptic connectivity. Our numerical study of the conductance-based integrate-and-fire neuronal network shows that only short data of 20 ~ 100 s is required for an accurate recovery of network topology as well as the corresponding coupling strength. Our method can yield an accurate reconstruction of a large neuronal network even in the case of dense connectivity and nearly synchronous dynamics, which many other network reconstruction methods cannot successfully handle. In addition, we point out that, for sparse networks, the STR method can infer coupling strength between each pair of neurons with high accuracy in the absence of the global information of all other neurons.

  4. Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture

    Science.gov (United States)

    Meszlényi, Regina J.; Buza, Krisztian; Vidnyánszky, Zoltán

    2017-01-01

    Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network. PMID:29089883

  5. Aberrant salience network (bilateral insula and anterior cingulate cortex) connectivity during information processing in schizophrenia.

    Science.gov (United States)

    White, Thomas P; Joseph, Verghese; Francis, Susan T; Liddle, Peter F

    2010-11-01

    A salience network, comprising bilateral insula and anterior cingulate cortex (ACC), is thought to play a role in recruiting relevant brain regions for the processing of sensory information. Here, we present a functional network connectivity (FNC) analysis of spatial networks identified during somatosensation, performed to test the hypothesis that salience network connectivity is disturbed during information processing in schizophrenia. 19 medicated individuals with schizophrenia and 19 matched healthy controls participated in a functional magnetic resonance imaging study. 100 Hz vibrotactile stimuli were presented to the right index fingertip while whole-head blood oxygenation level-dependent contrast gradient-echo echo-planar images were acquired. Six spatial components of interest were identified using group independent component analysis: (1) bilateral insula, superior temporal and precentral gyrus (INS); (2) dorsal ACC; (3) left dorsolateral frontal and parietal cortex (left central executive network (LCEN)); (4) right dorsolateral frontal and parietal cortex (RCEN); (5) ventromedial frontal cortex (FDMN); and (6) precuneus, posterior cingulate and angular gyrus (PDMN). Maximal-lagged correlation was examined between all pairwise combinations of components. Significantly reduced FNC was observed in schizophrenia compared to controls between: INS and ACC; INS and FDMN; and LCEN and PDMN. There was no evidence of increased FNC in schizophrenia. Reduced salience network connectivity during information processing in schizophrenia suggests disturbance to the system which effects changes between contextually-relevant functional brain states. This aberrance may provide a mechanistic explanation of several clinical features of the disorder. Copyright © 2010 Elsevier B.V. All rights reserved.

  6. Connection Setup Signaling Scheme with Flooding-Based Path Searching for Diverse-Metric Network

    Science.gov (United States)

    Kikuta, Ko; Ishii, Daisuke; Okamoto, Satoru; Oki, Eiji; Yamanaka, Naoaki

    Connection setup on various computer networks is now achieved by GMPLS. This technology is based on the source-routing approach, which requires the source node to store metric information of the entire network prior to computing a route. Thus all metric information must be distributed to all network nodes and kept up-to-date. However, as metric information become more diverse and generalized, it is hard to update all information due to the huge update overhead. Emerging network services and applications require the network to support diverse metrics for achieving various communication qualities. Increasing the number of metrics supported by the network causes excessive processing of metric update messages. To reduce the number of metric update messages, another scheme is required. This paper proposes a connection setup scheme that uses flooding-based signaling rather than the distribution of metric information. The proposed scheme requires only flooding of signaling messages with requested metric information, no routing protocol is required. Evaluations confirm that the proposed scheme achieves connection establishment without excessive overhead. Our analysis shows that the proposed scheme greatly reduces the number of control messages compared to the conventional scheme, while their blocking probabilities are comparable.

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

    Directory of Open Access Journals (Sweden)

    Borisyuk Roman

    2007-09-01

    Full Text Available 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 measured directly by making electrical recordings from 500 pairs of neurons. For the same neuron types, the dorso-ventral distributions of axons and dendrites were measured and then used to calculate the probabilities that axons would encounter particular dendrites and so potentially form synaptic connections. Surprisingly, synapses were found between all types of neuron but contact probabilities could be predicted simply by the anatomical overlap of their axons and dendrites. These results suggested that synapse formation may not require axons to recognise specific, correct dendrites. To test the plausibility of simpler hypotheses, we first made computational models that were able to generate longitudinal axon growth paths and reproduce the axon distribution patterns and synaptic contact probabilities found in the spinal cord. To test if probabilistic rules could produce functioning spinal networks, we then made realistic computational models of spinal cord neurons, giving them established cell-specific properties and connecting them into networks using the contact probabilities we had determined. A majority of these networks produced robust swimming activity. Conclusion Simple factors such as morphogen gradients controlling dorso-ventral soma, dendrite and axon positions may sufficiently constrain the synaptic connections made between different types of neuron as the spinal cord first develops and allow functional networks to form. Our analysis implies that

  8. Complex networks of functional connectivity in a wetland reconnected to its floodplain

    Science.gov (United States)

    Larsen, Laurel G.; Newman, Susan; Saunders, Colin; Harvey, Judson

    2017-01-01

    Disturbances such as fire or flood, in addition to changing the local magnitude of ecological, hydrological, or biogeochemical processes, can also change their functional connectivity—how those processes interact in space. Complex networks offer promise for quantifying functional connectivity in watersheds. The approach resolves connections between nodes in space based on statistical similarities in perturbation signals (derived from solute time series) and is sensitive to a wider range of timescales than traditional mass-balance modeling. We use this approach to test hypotheses about how fire and flood impact ecological and biogeochemical dynamics in a wetland (Everglades, FL, USA) that was reconnected to its floodplain. Reintroduction of flow pulses after decades of separation by levees fundamentally reconfigured functional connectivity networks. The most pronounced expansion was that of the calcium network, which reflects periphyton dynamics and may represent an indirect influence of elevated nutrients, despite the comparatively smaller observed expansion of phosphorus networks. With respect to several solutes, periphyton acted as a “biotic filter,” shifting perturbations in water-quality signals to different timescales through slow but persistent transformations of the biotic community. The complex-networks approach also revealed portions of the landscape that operate in fundamentally different regimes with respect to dissolved oxygen, separated by a threshold in flow velocity of 1.2 cm/s, and suggested that complete removal of canals may be needed to restore connectivity with respect to biogeochemical processes. Fire reconfigured functional connectivity networks in a manner that reflected localized burn severity, but had a larger effect on the magnitude of solute concentrations.

  9. 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.

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

    Science.gov (United States)

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

    2015-01-01

    We hypothesized that brain circuits involved in reward and salience respond differently to fasting in obese versus lean individuals. We compared functional connectivity networks related to food reward and saliency after an overnight fast (baseline) and after a prolonged fast of 48 h in lean versus obese subjects. We included 13 obese (2 males, 11 females, BMI 35.4 ± 1.2 kg/m(2), age 31 ± 3 years) and 11 lean subjects (2 males, 9 females, BMI 23.2 ± 0.5 kg/m(2), age 28 ± 3 years). Resting-state functional magnetic resonance imaging scans were made after an overnight fast (baseline) and after a prolonged 48 h fast. Functional connectivity of the amygdala, hypothalamus and posterior cingulate cortex (default-mode) networks was assessed using seed-based correlations. At baseline, we found a stronger connectivity between hypothalamus and left insula in the obese subjects. This effect diminished upon the prolonged fast. After prolonged fasting, connectivity of the hypothalamus with the dorsal anterior cingulate cortex (dACC) increased in lean subjects and decreased in obese subjects. Amygdala connectivity with the ventromedial prefrontal cortex was stronger in lean subjects at baseline, which did not change upon the prolonged fast. No differences in posterior cingulate cortex connectivity were observed. In conclusion, obesity is marked by alterations in functional connectivity networks involved in food reward and salience. Prolonged fasting differentially affected hypothalamic connections with the dACC and the insula between obese and lean subjects. Our data support the idea that food reward and nutrient deprivation are differently perceived and/or processed in obesity. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. The Structural Connectivity Pattern of the Default Mode Network and Its Association with Memory and Anxiety.

    Science.gov (United States)

    Tao, Yan; Liu, Bing; Zhang, Xiaolong; Li, Jin; Qin, Wen; Yu, Chunshui; Jiang, Tianzi

    2015-01-01

    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 with age ranging from 18 to 29 years old. The Group ICA method was used to extract the DMN component from functional magnetic resonance imaging (fMRI) data and a probabilistic fiber tractography technique based on DTI data was applied to construct the global structural connectivity pattern of the DMN. Then we used the graph theory method to analyze the DMN structural network 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, the results we found that the network efficiency of the DMN were related to memory and anxiety measures, indicated that the DMN may play a role in the memory and anxiety.

  12. An Efficient Steady-State Analysis Method for Large Boolean Networks with High Maximum Node Connectivity.

    Science.gov (United States)

    Hong, Changki; Hwang, Jeewon; Cho, Kwang-Hyun; Shin, Insik

    2015-01-01

    Boolean networks have been widely used to model biological processes lacking detailed kinetic information. Despite their simplicity, Boolean network dynamics can still capture some important features of biological systems such as stable cell phenotypes represented by steady states. For small models, steady states can be determined through exhaustive enumeration of all state transitions. As the number of nodes increases, however, the state space grows exponentially thus making it difficult to find steady states. Over the last several decades, many studies have addressed how to handle such a state space explosion. Recently, increasing attention has been paid to a satisfiability solving algorithm due to its potential scalability to handle large networks. Meanwhile, there still lies a problem in the case of large models with high maximum node connectivity where the satisfiability solving algorithm is known to be computationally intractable. To address the problem, this paper presents a new partitioning-based method that breaks down a given network into smaller subnetworks. Steady states of each subnetworks are identified by independently applying the satisfiability solving algorithm. Then, they are combined to construct the steady states of the overall network. To efficiently apply the satisfiability solving algorithm to each subnetwork, it is crucial to find the best partition of the network. In this paper, we propose a method that divides each subnetwork to be smallest in size and lowest in maximum node connectivity. This minimizes the total cost of finding all steady states in entire subnetworks. The proposed algorithm is compared with others for steady states identification through a number of simulations on both published small models and randomly generated large models with differing maximum node connectivities. The simulation results show that our method can scale up to several hundreds of nodes even for Boolean networks with high maximum node connectivity. The

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

    CERN Document Server

    Cass, Tony; CERN. Geneva. IT Department

    2016-01-01

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

  14. International network connectivity and performance -- The challenge from high energy physics

    Energy Technology Data Exchange (ETDEWEB)

    Matthews, W.

    2000-03-20

    The requirements of the new generation of High Energy and Nuclear Physics (HENP) experiments such as the BaBar detector at the Stanford Linear Accelerator Center (SLAC), the Relativistic Heavy Ion Collider (RHIC) groups at the Brookhaven National Laboratory (BNL) and the LHC projects currently under development at the European Center for Particle Physics (CERN) are a huge challenge to networking. In order to increase understanding and to improve performance and connectivity by identifying bottlenecks and allocating resources, the HENP networking community has been actively monitoring the network for over five years.

  15. Connectivity model for Inter-working multi-hop wireless networks

    CSIR Research Space (South Africa)

    Salami, O

    2009-08-01

    Full Text Available , while a route refers to the last mile connection path between a source and destination pair. In section II, a description of the model of the inter- working wireless network and the node distribution model; and an explanation of the node degree... transmission range of each of the nodes is R and the distance between any two nodes, Xi and Xj in the network is represented by d(Xi,Xj). In a wireless multi-hop network, two nodes are able to communicate with each other if d(Xi, Xj)≤R [2]. B. Node Degree...

  16. Reduced functional connectivity between salience and visual networks in migraine with aura.

    Science.gov (United States)

    Niddam, David M; Lai, Kuan-Lin; Fuh, Jong-Ling; Chuang, Chih-Ying Naomi; Chen, Wei-Ta; Wang, Shuu-Jiun

    2016-01-01

    Migraine with visual aura (MA) is associated with distinct visual disturbances preceding migraine attacks, but shares other visual deficits in between attacks with migraine without aura (MO). Here, we seek to determine if abnormalities specific to interictal MA patients exist in functional brain connectivity of intrinsic cognitive networks. In particular, these networks are involved in top-down modulation of visual processing. Using resting-state functional magnetic resonance imaging, whole-brain functional connectivity maps were derived from seeds placed in the anterior insula and the middle frontal gyrus, key nodes of the salience and dorsal attention networks, respectively. Twenty-six interictal MA patients were compared with 26 matched MO patients and 26 healthy matched controls. The major findings were: connectivity between the anterior insula and occipital areas, including area V3A, was reduced in MA but not in MO. Connectivity changes between the anterior insula and occipital areas further correlated with the headache severity in MA only. The unique pattern of connectivity changes found in interictal MA patients involved area V3A, an area previously implicated in aura generation. Hypoconnectivity to this and other occipital regions may either represent a compensatory response to occipital dysfunctions or predispose MA patients to the development of aura. © International Headache Society 2015.

  17. Abnormal Connectivity Within Executive Resting-State Network in Migraine With Aura.

    Science.gov (United States)

    Tessitore, Alessandro; Russo, Antonio; Conte, Francesca; Giordano, Alfonso; De Stefano, Manuela; Lavorgna, Luigi; Corbo, Daniele; Caiazzo, Giuseppina; Esposito, Fabrizio; Tedeschi, Gioacchino

    2015-06-01

    To evaluate the executive control network connectivity integrity in patients with migraine with aura, in the interictal period, in comparison to patients with migraine without aura and healthy controls. Using resting-state functional magnetic resonance imaging, we compared executive control network functional connectivity in 20 patients with migraine with aura vs 20 sex and age-matched patients with migraine without aura and 20 healthy controls, and assessed the correlation between executive control network functional connectivity and clinical features of patients with migraine. We used voxel-based morphometry and diffusion tensor imaging to investigate potential structural or microstructural changes. Neuropsychological data revealed no significant executive dysfunction in patients with migraine. Resting-state functional magnetic resonance imaging showed significant group differences in right middle frontal gyrus (Talairach coordinates x, y, z: +26, +2, +48) and dorsal anterior cingulate cortex (Talairach coordinates x, y, z: +6, +13, +49), indicating that these areas had a decreased component activity in both patients with migraine with and without aura when compared with healthy controls. Conversely, there were no significant differences in the executive control network functional connectivity between patients with migraine with and without aura (P aura, in the interictal period. Although this functional phenomenon is present in the absence of clinically relevant executive deficits, it may reflect a vulnerability to executive high-demanding conditions of daily living activities in patients with migraine. © 2015 American Headache Society.

  18. Increased interictal visual network connectivity in patients with migraine with aura.

    Science.gov (United States)

    Tedeschi, Gioacchino; Russo, Antonio; Conte, Francesca; Corbo, Daniele; Caiazzo, Giuseppina; Giordano, Alfonso; Conforti, Renata; Esposito, Fabrizio; Tessitore, Alessandro

    2016-02-01

    To evaluate the resting-state visual network functional connectivity in patients with migraine with aura and migraine without aura during the interictal period. Using resting-state functional magnetic resonance imaging, the resting-state visual network integrity was investigated in 20 patients with migraine with aura, 20 age- and sex-matched patients with migraine without aura and 20 healthy controls. Voxel-based morphometry and diffusion tensor imaging were used to assess whether between-groups differences in functional connectivity were dependent on structural or microstructural changes. Resting-state functional magnetic resonance imaging data showed that patients with migraine with aura, compared to both patients with migraine without aura and healthy controls, had a significant increased functional connectivity in the right lingual gyrus within the resting-state visual network (p aura exhibit an altered resting-state visual network connectivity. These results support the hypothesis of an extrastriate cortex involvement, centred in the lingual gyrus, a brain region related to mechanisms underlying the initiation and propagation of the migraine aura. This resting-state functional magnetic resonance imaging finding may represent a functional biomarker that could differentiate patients experiencing the aura phenomenon from patients with migraine without aura, even between migraine attacks. © International Headache Society 2015.

  19. Negative mood-induction modulates default mode network resting-state functional connectivity in chronic depression

    NARCIS (Netherlands)

    Renner, F.; Siep, N.; Arntz, A.; van de Ven, V.; Peeters, F.P.M.L.; Quaedflieg, C.W.E.M.; Huibers, M.J.H.

    2017-01-01

    BACKGROUND: The aim of this study was to investigate the effects of sad mood on default mode network (DMN) resting-state connectivity in persons with chronic major depressive disorder (cMDD). METHODS: Participants with a diagnosis of cMDD (n=18) and age, gender and education level matched

  20. Increased default mode network connectivity and increased regional homogeneity in migraineurs without aura.

    Science.gov (United States)

    Zhang, Jilei; Su, Jingjing; Wang, Mengxing; Zhao, Ying; Yao, Qian; Zhang, Qiting; Lu, Haifeng; Zhang, Hui; Wang, Shuo; Li, Ge-Fei; Wu, Yi-Lan; Liu, Feng-Di; Shi, Yan-Hui; Li, Jianqi; Liu, Jian-Ren; Du, Xiaoxia

    2016-12-01

    The precuneus/posterior cingulate cortex, which has been associated with pain sensitivity, plays a pivotal role in the default mode network. However, information regarding migraine-related alterations in resting-state brain functional connectivity in the default mode network and in local regional spontaneous neuronal activity is not adequate. This study used functional magnetic resonance imaging to acquire resting-state scans in 22 migraineurs without aura and in 22 healthy matched controls. Independent component analysis, a data-driven method, was used to calculate the resting-state functional connectivity of the default mode network in the patient and healthy control groups. Regional homogeneity (ReHo) was used to analyse the local features of spontaneous resting-state brain activity in the migraineurs without aura. Compared with the healthy controls, migraineurs without aura showed increased functional connectivity in the left precuneus/posterior cingulate cortex within the default mode network and significant increase in ReHo values in the bilateral precuneus/posterior cingulate cortex, left pons and trigeminal nerve entry zone. In addition, functional connectivity was decreased between the areas with abnormal ReHo (using the peaks in the precuneus/posterior cingulate cortex) and other brain areas. The abnormalities in the precuneus/posterior cingulate cortex suggest that migraineurs without aura may exhibit information transfer and multimodal integration dysfunction and that pain sensitivity and pian processing may also be affected.

  1. Default Mode Network Connectivity in Children with a History of Preschool Onset Depression

    Science.gov (United States)

    Gaffrey, Michael S.; Luby, Joan L.; Botteron, Kelly; Repovs, Grega; Barch, Deanna M.

    2012-01-01

    Background: Atypical Default Mode Network (DMN) functional connectivity has been previously reported in depressed adults. However, there is relatively little data informing the developmental nature of this phenomenon. The current case-control study examined the DMN in a unique prospective sample of school-age children with a previous history of…

  2. Cognitive correlates of frontoparietal network connectivity 'at rest' in individuals with differential risk for psychotic disorder

    NARCIS (Netherlands)

    Peeters, S. C. T.; van Bronswijk, S.; van de Ven, V.; Gronenschild, E. H. B. M.; Goebel, R.; van Os, J.; Marcelis, M.; Bruggeman, Richard; Cahn, Wiepke; de Haan, Lieuwe; Kahn, René; Meijer, Carin; Myin-Germeys, Inez; van Os, Jim; Wiersma, Durk

    2015-01-01

    Altered frontoparietal network functional connectivity (FPN-fc) has been associated with neurocognitive dysfunction in individuals with (risk for) psychotic disorder. Cannabis use is associated with cognitive and FPN-fc alterations in healthy individuals, but it is not known whether cannabis

  3. Multi-netclust: an efficient tool for finding connected clusters in multi-parametric networks

    NARCIS (Netherlands)

    Kuzniar, A.; Dhir, S.; Nijveen, H.; Pongor, S.; Leunissen, J.A.M.

    2010-01-01

    Multi-netclust is a simple tool that allows users to extract connected clusters of data represented by different networks given in the form of matrices. The tool uses user-defined threshold values to combine the matrices, and uses a straightforward, memory-efficient graph algorithm to find clusters

  4. 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.

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

    Science.gov (United States)

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

    2013-01-01

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

  6. Analysis of Heterogeneous Networks with Dual Connectivity in a Realistic Urban Deployment

    DEFF Research Database (Denmark)

    Gerardino, Guillermo Andrés Pocovi; Barcos, Sonia; Wang, Hua

    2015-01-01

    Dual Connectivity (DC) has been studied and proved to be an effective solution to deal with the fragmented resources in deployment scenarios where the macro and small cells use different frequency carriers. The performance of DC has mainly been analyzed using generic network models such as those...

  7. 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).

  8. Motives for online friending and following: The dark side of social network site connections

    NARCIS (Netherlands)

    Ouwerkerk, J.W.; Johnson, B.K.

    Motives for “friending,” following, or connecting with others on social network sites are often positive, but darker motives may also play an important role. A survey with a novel Following Motives Scale (FMS) demonstrates accordingly that positive, sociable motives (i.e., others providing a valued

  9. 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…

  10. Brain networks of the imaginative mind: Dynamic functional connectivity of default and cognitive control networks relates to openness to experience.

    Science.gov (United States)

    Beaty, Roger E; Chen, Qunlin; Christensen, Alexander P; Qiu, Jiang; Silvia, Paul J; Schacter, Daniel L

    2018-02-01

    Imagination and creative cognition are often associated with the brain's default network (DN). Recent evidence has also linked cognitive control systems to performance on tasks involving imagination and creativity, with a growing number of studies reporting functional interactions between cognitive control and DN regions. We sought to extend the emerging literature on brain dynamics supporting imagination by examining individual differences in large-scale network connectivity in relation to Openness to Experience, a personality trait typified by imagination and creativity. To this end, we obtained personality and resting-state fMRI data from two large samples of participants recruited from the United States and China, and we examined contributions of Openness to temporal shifts in default and cognitive control network interactions using multivariate structural equation modeling and dynamic functional network connectivity analysis. In Study 1, we found that Openness was related to the proportion of scan time (i.e., "dwell time") that participants spent in a brain state characterized by positive correlations among the default, executive, salience, and dorsal attention networks. Study 2 replicated and extended the effect of Openness on dwell time in a correlated brain state comparable to the state found in Study 1, and further demonstrated the robustness of this effect in latent variable models including fluid intelligence and other major personality factors. The findings suggest that Openness to Experience is associated with increased functional connectivity between default and cognitive control systems, a connectivity profile that may account for the enhanced imaginative and creative abilities of people high in Openness to Experience. © 2017 Wiley Periodicals, Inc.

  11. Disrupted functional connectivity in dorsal and ventral attention networks during attention orienting in autism spectrum disorders.

    Science.gov (United States)

    Fitzgerald, Jacqueline; Johnson, Katherine; Kehoe, Elizabeth; Bokde, Arun L W; Garavan, Hugh; Gallagher, Louise; McGrath, Jane

    2015-04-01

    Attention orienting is a cognitive process that facilitates the movement of attention focus from one location to another: this may be impaired in autism spectrum disorder (ASD). Dorsal and ventral attention networks (DAN and VAN) sub-serve the process of attention orienting. This study investigated the functional connectivity of attention orienting in these networks in ASD using the Posner Cueing Task. Twenty-one adolescents with ASD and 21 age and IQ matched controls underwent functional magnetic resonance imaging. A psychophysical interaction (PPI) analysis was implemented to investigate task-dependent functional connectivity, measuring synchronicity of brain regions during the task. Regions of interest (ROI) were selected to explore functional connectivity in the DAN during cue-only conditions and in the VAN during invalid and valid trials. Behaviourally, the ASD and control groups performed the task in a similar manner. Functional MRI results indicated that the ASD and control groups activated similar brain regions. During invalid trials (VAN), the ASD group showed significant positive functional connectivity to multiple brain regions, whilst the control group demonstrated negative connectivity. During valid trials (VAN), the two groups also showed contrasting patterns of connectivity. In the cue-only conditions (DAN), the ASD group showed weaker functional connectivity. The DAN analysis suggests that the ASD group has weaker coherence between brain areas involved in goal-driven, endogenous attention control. The strong positive functional connectivity exhibited by the ASD group in the VAN during the invalid trials suggests that individuals with ASD may generate compensatory mechanisms to achieve neurotypical behaviour. These results support the theory of abnormal cortical connectivity in autism. © 2014 International Society for Autism Research, Wiley Periodicals, Inc.

  12. 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.

  13. 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.

  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. Heritability of the Effective Connectivity in the Resting-State Default Mode Network.

    Science.gov (United States)

    Xu, Junhai; Yin, Xuntao; Ge, Haitao; Han, Yan; Pang, Zengchang; Liu, Baolin; Liu, Shuwei; Friston, Karl

    2017-12-01

    The default mode network (DMN) is thought to reflect endogenous neural activity, which is considered as one of the most intriguing phenomena in cognitive neuroscience. Previous studies have found that key regions within the DMN are highly interconnected. Here, we characterized the genetic influences on causal or directed information flow within the DMN during the resting state. In this study, we recruited 46 pairs of twins and collected fMRI imaging data using a 3.0 T scanner. Dynamic causal modeling was conducted for each participant, and a structural equation model was used to calculate the heritability of DMN in terms of its effective connectivity. Model comparison favored a full-connected model. Structural equal modeling was used to estimate the additive genetics (A), common environment (C) and unique environment (E) contributions to variance for the DMN effective connectivity. The ACE model was preferred in the comparison of structural equation models. Heritability of DMN effective connectivity was 0.54, suggesting that the genetic made a greater contribution to the effective connectivity within DMN. Establishing the heritability of default-mode effective connectivity endorses the use of resting-state networks as endophenotypes or intermediate phenotypes in the search for the genetic basis of psychiatric or neurological illnesses. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  16. Reduced functional connectivity of fronto-parietal sustained attention networks in severe childhood abuse.

    Directory of Open Access Journals (Sweden)

    Heledd Hart

    Full Text Available Childhood maltreatment is associated with attention deficits. We examined the effect of childhood abuse and abuse-by-gene (5-HTTLPR, MAOA, FKBP5 interaction on functional brain connectivity during sustained attention in medication/drug-free adolescents. Functional connectivity was compared, using generalised psychophysiological interaction (gPPI analysis of functional magnetic resonance imaging (fMRI data, between 21 age-and gender-matched adolescents exposed to severe childhood abuse and 27 healthy controls, while they performed a parametrically modulated vigilance task requiring target detection with a progressively increasing load of sustained attention. Behaviourally, participants exposed to childhood abuse had increased omission errors compared to healthy controls. During the most challenging attention condition abused participants relative to controls exhibited reduced connectivity, with a left-hemispheric bias, in typical fronto-parietal attention networks, including dorsolateral, rostromedial and inferior prefrontal and inferior parietal regions. Abuse-related connectivity abnormalities were exacerbated in individuals homozygous for the risky C-allele of the single nucleotide polymorphism rs3800373 of the FK506 Binding Protein 5 (FKBP5 gene. Findings suggest that childhood abuse is associated with decreased functional connectivity in fronto-parietal attention networks and that the FKBP5 genotype moderates neurobiological vulnerability to abuse. These findings represent a first step towards the delineation of abuse-related neurofunctional connectivity abnormalities, which hopefully will facilitate the development of specific treatment strategies for victims of childhood maltreatment.

  17. Estimation of effective connectivity using multi-layer perceptron artificial neural network.

    Science.gov (United States)

    Talebi, Nasibeh; Nasrabadi, Ali Motie; Mohammad-Rezazadeh, Iman

    2018-02-01

    Studies on interactions between brain regions estimate effective connectivity, (usually) based on the causality inferences made on the basis of temporal precedence. In this study, the causal relationship is modeled by a multi-layer perceptron feed-forward artificial neural network, because of the ANN's ability to generate appropriate input-output mapping and to learn from training examples without the need of detailed knowledge of the underlying system. At any time instant, the past samples of data are placed in the network input, and the subsequent values are predicted at its output. To estimate the strength of interactions, the measure of " Causality coefficient " is defined based on the network structure, the connecting weights and the parameters of hidden layer activation function. Simulation analysis demonstrates that the method, called "CREANN" (Causal Relationship Estimation by Artificial Neural Network), can estimate time-invariant and time-varying effective connectivity in terms of MVAR coefficients. The method shows robustness with respect to noise level of data. Furthermore, the estimations are not significantly influenced by the model order (considered time-lag), and the different initial conditions (initial random weights and parameters of the network). CREANN is also applied to EEG data collected during a memory recognition task. The results implicate that it can show changes in the information flow between brain regions, involving in the episodic memory retrieval process. These convincing results emphasize that CREANN can be used as an appropriate method to estimate the causal relationship among brain signals.

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

    Directory of Open Access Journals (Sweden)

    José R. C. Piqueira

    2008-01-01

    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.

  19. 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.

  20. Human brain networks in physiological aging: a graph theoretical analysis of cortical connectivity from EEG data.

    Science.gov (United States)

    Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria

    2014-01-01

    Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity 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...... 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....... 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...

  2. 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....

  3. 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.

  4. 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

  5. Streaming Multimedia via Overlay Networks using Wi-Fi Peer-to-Peer Connections

    DEFF Research Database (Denmark)

    Poderys, Justas; Soler, José

    2017-01-01

    Short range ad-hoc wireless networks can be used to deliver streaming multimedia for information, entertainment and advertisement purposes. To enable short-range communication between various devices, the Wi-Fi Alliance proposed an extension to the IEEE802.11 Wi-Fi standard called Wi-Fi Peer......-to-Peer (P2P). It allows compliant devices to form ad-hoc communication groups without interrupting conventional access point-based Wi-Fi communication. This paper proposes to use Wi-Fi P2P connectivity to distribute streaming multimedia in ah-hoc formed user groups. The exchange of multimedia data...... is performed by forming an overlay network using Peer-to-Peer Streaming Peer Protocol (PPSPP). In order to make PPSPP function over WiFi P2P connections, this paper proposes a number of changes to the protocol. The performance of the proposed system is evaluated using a computer networks emulator...

  6. 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.

  7. Multi-netclust: an efficient tool for finding connected clusters in multi-parametric networks.

    Science.gov (United States)

    Kuzniar, Arnold; Dhir, Somdutta; Nijveen, Harm; Pongor, Sándor; Leunissen, Jack A M

    2010-10-01

    Multi-netclust is a simple tool that allows users to extract connected clusters of data represented by different networks given in the form of matrices. The tool uses user-defined threshold values to combine the matrices, and uses a straightforward, memory-efficient graph algorithm to find clusters that are connected in all or in either of the networks. The tool is written in C/C++ and is available either as a form-based or as a command-line-based program running on Linux platforms. The algorithm is fast, processing a network of > 10(6) nodes and 10(8) edges takes only a few minutes on an ordinary computer. http://www.bioinformatics.nl/netclust/.

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

    Directory of Open Access Journals (Sweden)

    JongHyup Lee

    2016-08-01

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

  9. Connectivity diagnostics in the Mediterranean obtained from Lagrangian Flow Networks; global patterns, sensitivity and robustness

    Science.gov (United States)

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

    2017-04-01

    Lagrangian Flow Network (LFN) is a modeling framework in which geographical sub-areas of the ocean are represented as nodes in a network and are interconnected by links representing the transport of water, substances or propagules (eggs and larvae) by currents. Here we compute for the surface of the whole Mediterranean basin four connectivity metrics derived from LFN that measure retention and exchange processes, thus providing a systematic characterization of propagule dispersal driven by the ocean circulation. Then we assess the sensitivity and robustness of the results with respect to the most relevant parameters: the density of released particles, the node size (spatial-scales of discretization), the Pelagic Larval Duration (PLD) and the modality of spawning. We find a threshold for the number of particles per node that guarantees reliable values for most of the metrics examined, independently of node size. For our setup, this threshold is 100 particles per node. We also find that the size of network nodes has a non-trivial influence on the spatial variability of both exchange and retention metrics. Although the spatio-temporal fluctuations of the circulation affect larval transport in a complex and unpredictable manner, our analyses evidence how specific biological parametrization impact the robustness of connectivity diagnostics. Connectivity estimates for long PLDs are more robust against biological uncertainties (PLD and spawning date) than for short PLDs. Furthermore, our model suggests that for mass-spawners that release propagules over short periods (≃ 2 to 10 days), daily release must be simulated to properly consider connectivity fluctuations. In contrast, average connectivity estimates for species that spawn repeatedly over longer duration (a few weeks to a few months) remain robust even using longer periodicity (5 to 10 days). Our results give a global view of the surface connectivity of the Mediterranean Sea and have implications for the design of

  10. The Strategy of Micro-Network for Research on Network Connections

    OpenAIRE

    MladenKralj, -; LilijanaZupan, -

    2013-01-01

    This paper emphasizes mainly on the grid-connected control strategy of the micro-grid during the grid-connected process. The typical configuration of the micro-grid is presented. The power flow in the micro-grid is analyzed based on the characteristic curve of frequency-power, and the method of the best connection point selection is given. In consideration of the harmonics, disturbances and time delay, the gridconnected control strategy is proposed. The micro-grid is simulated by the simulati...

  11. Connectivity trajectory across lifespan differentiates the precuneus from the default network.

    Science.gov (United States)

    Yang, Zhi; Chang, Catie; Xu, Ting; Jiang, Lili; Handwerker, Daniel A; Castellanos, F Xavier; Milham, Michael P; Bandettini, Peter A; Zuo, Xi-Nian

    2014-04-01

    The default network of the human brain has drawn much attention due to its relevance to various brain disorders, cognition, and behavior. However, its functional components and boundaries have not been precisely defined. There is no consensus as to whether the precuneus, a hub in the functional connectome, acts as part of the default network. This discrepancy is more critical for brain development and aging studies: it is not clear whether age has a stronger impact on the default network or precuneus, or both. We used Generalized Ranking and Averaging Independent Component Analysis by Reproducibility (gRAICAR) to investigate the lifespan trajectories of intrinsic functional networks. By estimating individual-specific spatial components and aligning them across subjects, gRAICAR measures the spatial variation of component maps across a population without constraining the same components to appear in every subject. In a cross-lifespan fMRI dataset (N=126, 7-85years old), we observed stronger age dependence in the spatial pattern of a precuneus-dorsal posterior cingulate cortex network compared to the default network, despite the fact that the two networks exhibit considerable spatial overlap and temporal correlation. These results remained even when analyses were restricted to a subpopulation with very similar head motion across age. Our analyses further showed that the two networks tend to merge with increasing age. Post-hoc analyses of functional connectivity confirmed the distinguishable cross-lifespan trajectories between the two networks. Based on these observations, we proposed a dynamic model of cross-lifespan functional segregation and integration between the two networks, suggesting that the precuneus network may have a different functional role than the default network, which declines with age. These findings have implications for understanding the functional roles of the default network, gaining insight into its dynamics throughout life, and guiding

  12. A QCQP Approach for OPF in Multiphase Radial Networks with Wye and Delta Connections: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zamzam, Ahmed, S.; Zhaoy, Changhong; Dall' Anesey, Emiliano; Sidiropoulos, Nicholas D.

    2017-06-27

    This paper examines the AC Optimal Power Flow (OPF) problem for multiphase distribution networks featuring renewable energy resources (RESs). We start by outlining a power flow model for radial multiphase systems that accommodates wye-connected and delta-connected RESs and non-controllable energy assets. We then formalize an AC OPF problem that accounts for both types of connections. Similar to various AC OPF renditions, the resultant problem is a non convex quadratically-constrained quadratic program. However, the so-called Feasible Point Pursuit-Successive Convex Approximation algorithm is leveraged to obtain a feasible and yet locally-optimal solution. The merits of the proposed solution approach are demonstrated using two unbalanced multiphase distribution feeders with both wye and delta connections.

  13. Academics’ online connections: Characterising the structure of personal networks on academic social networking sites and Twitter

    OpenAIRE

    Jordan, Katy

    2016-01-01

    Academic social networking sites (SNS), such as Academia.edu and ResearchGate, seek to bring the benefits of online social networking to academics' professional lives. Online academic social networking offers the potential to revolutionise academic publishing, foster novel collaborations, and empower academics to develop their professional identities online. However, the role that such sites play in relation to academic practice and other social media is not well understood at present.\\ud \\ud...

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

    Science.gov (United States)

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

    2013-01-01

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

  15. Functional connectivity in the basal ganglia network differentiates PD patients from controls

    Science.gov (United States)

    Szewczyk-Krolikowski, Konrad; Menke, Ricarda A.L.; Rolinski, Michal; Duff, Eugene; Salimi-Khorshidi, Gholamreza; Filippini, Nicola; Zamboni, Giovanna; Hu, Michele T.M.

    2014-01-01

    Objective: To examine functional connectivity within the basal ganglia network (BGN) in a group of cognitively normal patients with early Parkinson disease (PD) on and off medication compared to age- and sex-matched healthy controls (HC), and to validate the findings in a separate cohort of participants with PD. Methods: Participants were scanned with resting-state fMRI (RS-fMRI) at 3T field strength. Resting-state networks were isolated using independent component analysis. A BGN template was derived from 80 elderly HC participants. BGN maps were compared between 19 patients with PD on and off medication in the discovery group and 19 age- and sex-matched controls to identify a threshold for optimal group separation. The threshold was applied to 13 patients with PD (including 5 drug-naive) in the validation group to establish reproducibility of findings. Results: Participants with PD showed reduced functional connectivity with the BGN in a wide range of areas. Administration of medication significantly improved connectivity. Average BGN connectivity differentiated participants with PD from controls with 100% sensitivity and 89.5% specificity. The connectivity threshold was tested on the validation cohort and achieved 85% accuracy. Conclusions: We demonstrate that resting functional connectivity, measured with MRI using an observer-independent method, is reproducibly reduced in the BGN in cognitively intact patients with PD, and increases upon administration of dopaminergic medication. Our results hold promise for RS-fMRI connectivity as a biomarker in early PD. Classification of evidence: This study provides Class III evidence that average connectivity in the BGN as measured by RS-fMRI distinguishes patients with PD from age- and sex-matched controls. PMID:24920856

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

    Directory of Open Access Journals (Sweden)

    Gang Sun

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

  17. Pseudo-Bootstrap Network Analysis-an Application in Functional Connectivity Fingerprinting.

    Science.gov (United States)

    Cheng, Hu; Li, Ao; Koenigsberger, Andrea A; Huang, Chunfeng; Wang, Yang; Sheng, Jinhua; Newman, Sharlene D

    2017-01-01

    Brain parcellation divides the brain's spatial domain into small regions, which are represented by nodes within the network analysis framework. While template-based parcellations are widely used, the parcels on the template do not necessarily match individual's functional nodes. A new method is developed to overcome the inconsistent network analysis results by by-passing the difficulties of parcellating the brain into functionally meaningful areas. First, roughly equal-sized parcellations are obtained. Second, these random parcellations are applied to individual subjects multiple times and a pseudo-bootstrap (PBS) of the network is obtained for statistical inferences. It was found that the variation of mean global network metrics from PBS sampling is smaller compared with inter-subject variation or within-subject variation between two diffusion MRI scans. Using the mean global network metrics from PBS sampling, the intra-class correlation is always higher than the average obtained from using a single random parcellation. As one application, the PBS method was tested on the Human Connectome Project resting state dataset to identify individuals across scan sessions based on the mean functional connectivity (FC)-a trivial network property that has little information about the connectivity between nodes. An accuracy rate of ∼90% was achieved by simply finding the maximum correlation of mean FC of PBS samples between two scan sessions.

  18. 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.

  19. 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.

  20. Reduced Default Mode Network Connectivity in Treatment-Resistant Idiopathic Generalized Epilepsy

    Science.gov (United States)

    Kay, Benjamin P; DiFrancesco, Mark W; Privitera, Michael D; Gotman, Jean; Holland, Scott K; Szaflarski, Jerzy P

    2012-01-01

    Summary Purpose Idiopathic generalized epilepsy (IGE) resistant to treatment is common, but its neuronal correlates are not entirely understood. Thus, the aim of this study was to examine resting-state default mode network (DMN) functional connectivity in patients with treatment-resistant IGE. Methods Treatment-resistance was defined as continuing seizures despite an adequate dose of valproic acid (valproate, VPA). Data from 60 epilepsy patients and 38 healthy controls who underwent simultaneous EEG and resting-state fMRI were included (EEG/fMRI). Independent component analysis (ICA) and dual regression were used to quantify DMN connectivity. Confirmatory analysis using seed-based voxel correlation was performed. Key Findings There was a significant reduction of DMN connectivity in patients with treatment-resistant epilepsy when compared to patients who were treatment-responsive and healthy controls. Connectivity was negatively correlated with duration of epilepsy. Significance Our findings in this large sample of patients with IGE indicate the presence of reduced DMN connectivity in IGE and show that connectivity is further reduced in treatment-resistant epilepsy. DMN connectivity may be useful as a biomarker for treatment-resistance. PMID:23293853

  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. Dopaminergic modulation of default mode network brain functional connectivity in attention deficit hyperactivity disorder.

    Science.gov (United States)

    Silberstein, Richard B; Pipingas, Andrew; Farrow, Maree; Levy, Florence; Stough, Con K

    2016-12-01

    Recent evidence suggests that attention deficit hyperactivity disorder (ADHD) is associated with a range of brain functional connectivity abnormalities, with one of the most prominent being reduced inhibition of the default mode network (DMN) while performing a cognitive task. In this study, we examine the effects of a methylphenidate dose on brain functional connectivity in boys diagnosed with ADHD while they performed a cognitive task. Brain functional connectivity was estimated using steady-state visual evoked potential partial coherence before and 90 min after the administration of a methylphenidate dose to 42 stimulant drug-naïve boys newly diagnosed with ADHD while they performed the A-X version of the continuous performance task (CPT A-X). Methylphenidate robustly reversed the transient functional connectivity increase in the A-X interval seen premedication to a postmedication decrease during this interval. In addition, methylphenidate-induced reductions in individual reaction time were correlated with corresponding reductions in functional connectivity. These findings suggest that methylphenidate suppresses the increased functional connectivity observed in ADHD and that such suppression is associated with improved performance. Our findings support the suggestion that the increased functional connectivity we have observed in ADHD is associated with abnormal DMN activity. In addition, we comment on the significance of specific frequency channels mediating top-down communication within the cortex and the extent to which our findings are selectively sensitive to top-down intracortical communication.

  3. Decreased intra- and inter- salience network functional connectivity is related to trait anxiety in adolescents

    Directory of Open Access Journals (Sweden)

    Haiyang eGeng

    2016-01-01

    Full Text Available Objective: Adolescence is a critical period for the vulnerability of anxiety. Imaging studies focusing on adolescents’ susceptibility to anxiety suggest that the different development trajectories between the limbic system and the executive control system may play important roles in this phenomenon. However, few studies have explored the brain basis of this susceptibility from the perspective of functional networks. The salience network(SN)consists of a series of key limbic and prefrontal regions that are engaged in the development of anxiety, such as the amygdala, anterior insula (AI and dorsal anterior cingulate cortex (dACC. Intra- and inter- network connections in this system play essential roles in bottom-up attention and top-down regulation of anxiety, nevertheless, little is known about whether the SN-centered connections are associated with trait anxiety (i.e., susceptibility to anxiety in adolescents. Method: Here, we applied resting-state functional magnetic resonance imaging (fMRI to explore the relationship between intra- and inter- network functional connectivity (FC of the SN and trait anxiety in adolescents using the amygdala, AI and dACC as the regions of interest (ROI. Results: We found that trait anxiety levels were inversely associated with both characteristic AI-dACC FC in the SN and distributed inter-network FC between the SN and multiple functional systems, which included the default mode network and the executive control network. Conclusions: Our results indicate that weaker intra- and inter- network FC of the SN was linked to higher trait anxiety among adolescents, and it may underlie altered salience processing and cognitive regulation.

  4. Prefrontal Cortical Network Connections: Key Site of Vulnerability in Stress and Schizophrenia

    Science.gov (United States)

    Arnsten, Amy F.T.

    2011-01-01

    The symptoms of schizophrenia involve profound dysfunction of the prefrontal cortex (PFC). PFC networks create our “mental sketch pad”, and PFC dysfunction contributes to symptoms such as cognitive deficits, thought disorder, delusions and hallucinations. Neuropathological studies of schizophrenia have shown marked loss of dendritic spines in deep layer III, the sublayer where PFC microcircuits reside. The microcircuits consist of recurrent excitatory pyramidal cell networks that interconnect on spines, and excite each other via NMDA receptor signaling. The pyramidal cell persistent firing is sculpted by lateral inhibition from GABAergic basket and chandelier cells, thus creating tuned, persistent firing needed for accurate representational knowledge (i.e. working memory). The strength of pyramidal cell network connections is markedly and flexibly altered by intracellular signaling pathways in dendritic spines, a process called Dynamic Network Connectivity (DNC). DNC proteins such as HCN channels are concentrated on dendritic spines in deep layer III. Under optimal conditions, network inputs to pyramidal cells are strengthened by noradrenergic alpha-2A inhibition of cAMP-HCN channel signaling, and sculpted by dopamine D1-cAMP-HCN channel weakening of inappropriate inputs. However, with stress exposure, high levels of cAMP-HCN channel signaling produces a collapse in network firing. With chronic stress exposure, spines reduce in size and are lost, and this process involves increased PKC signaling. Importantly, molecules that normally strengthen PFC networks connections and/or reverse the stress response, are often genetically altered in schizophrenia. As exposure to stress is a key factor in the precipitation of schizophrenic symptoms, these dysregulated signaling pathways in deep layer III may interact with already vulnerable circuitry to cause spine loss and the descent into illness. PMID:21345366

  5. Hubs of Anticorrelation in High-Resolution Resting-State Functional Connectivity Network Architecture.

    Science.gov (United States)

    Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Cabanban, Romeo; Crosson, Bruce A

    2015-06-01

    A major focus of brain research recently has been to map the resting-state functional connectivity (rsFC) network architecture of the normal brain and pathology through functional magnetic resonance imaging. However, the phenomenon of anticorrelations in resting-state signals between different brain regions has not been adequately examined. The preponderance of studies on resting-state fMRI (rsFMRI) have either ignored anticorrelations in rsFC networks or adopted methods in data analysis, which have rendered anticorrelations in rsFC networks uninterpretable. The few studies that have examined anticorrelations in rsFC networks using conventional methods have found anticorrelations to be weak in strength and not very reproducible across subjects. Anticorrelations in rsFC network architecture could reflect mechanisms that subserve a number of important brain processes. In this preliminary study, we examined the properties of anticorrelated rsFC networks by systematically focusing on negative cross-correlation coefficients (CCs) among rsFMRI voxel time series across the brain with graph theory-based network analysis. A number of methods were implemented to enhance the neuronal specificity of resting-state functional connections that yield negative CCs, although at the cost of decreased sensitivity. Hubs of anticorrelation were seen in a number of cortical and subcortical brain regions. Examination of the anticorrelation maps of these hubs indicated that negative CCs in rsFC network architecture highlight a number of regulatory interactions between brain networks and regions, including reciprocal modulations, suppression, inhibition, and neurofeedback.

  6. Developmental changes in within- and between-network connectivity between late childhood and adulthood.

    Science.gov (United States)

    Barber, Anita D; Caffo, Brian S; Pekar, James J; Mostofsky, Stewart H

    2013-01-01

    A number of behavioral changes occur between late childhood and adulthood, including maturation of social cognition, reward receptivity, impulsiveness, risk-taking and cognitive control. Although some of these abilities show linear improvements with age, some abilities may temporarily worsen, reflecting both the restructuring and/or strengthening of connections within some brain systems. The current study uses resting state functional connectivity to examine developmental differences between late childhood and adulthood in task positive (TP) regions, which play a role in cognitive control functions, and task negative (TN) regions, which play a role in social cognition, self-referential, and internally-directed thought. Within the TP network, developmental differences in connectivity were found with the left dorsolateral prefrontal cortex. Within the TN network, developmental differences in connectivity were found with a broad area of the medial prefrontal cortex and the right parahippocampal gyrus. Connections between the two networks also showed significant developmental differences. Stronger anticorrelations were found in the TN maps of the adult group for the right anterior insula/inferior frontal gyrus, bilateral anterior inferior parietal lobule, bilateral superior parietal lobule and an anterior portion of the right posterior cingulate cortex. There was a significant brain-behavior relationship between the strength of anticorrelation in these regions and inhibitory control performance on two Go/No-go tasks suggesting that the development of anticorrelations between late childhood and adulthood supports mature inhibitory control. Overall, maturation of these networks occurred in specific regions which are associated with cognitive control of goal-directed behavior, including those involved in working memory, social cognition, and inhibitory control. Copyright © 2012 Elsevier Ltd. All rights reserved.

  7. Friends of friends: are indirect connections in social networks important to animal behaviour?

    Science.gov (United States)

    Brent, Lauren J. N.

    2015-01-01

    Friend of a friend relationships, or the indirect connections between people, influence our health, well-being, financial success and reproductive output. As with humans, social behaviours in other animals often occur within a broad interconnected network of social ties. Yet studies of animal social behaviour tend to focus on associations between pairs of individuals. With the increase in popularity of social network analysis, researchers have started to look beyond the dyad to examine the role of indirect connections in animal societies. Here, I provide an overview of the new knowledge that has been uncovered by these studies. I focus on research that has addressed both the causes of social behaviours, i.e. the cognitive and genetic basis of indirect connections, as well as their consequences, i.e. the impact of indirect connections on social cohesion, information transfer, cultural practices and fitness. From these studies, it is apparent that indirect connections play an important role in animal behaviour, although future research is needed to clarify their contribution. PMID:25937639

  8. Altered Effective Connectivity of Hippocampus-Dependent Episodic Memory Network in mTBI Survivors

    Directory of Open Access Journals (Sweden)

    Hao Yan

    2016-01-01

    Full Text Available Traumatic brain injuries (TBIs are generally recognized to affect episodic memory. However, less is known regarding how external force altered the way functionally connected brain structures of the episodic memory system interact. To address this issue, we adopted an effective connectivity based analysis, namely, multivariate Granger causality approach, to explore causal interactions within the brain network of interest. Results presented that TBI induced increased bilateral and decreased ipsilateral effective connectivity in the episodic memory network in comparison with that of normal controls. Moreover, the left anterior superior temporal gyrus (aSTG, the concept forming hub, left hippocampus (the personal experience binding hub, and left parahippocampal gyrus (the contextual association hub were no longer network hubs in TBI survivors, who compensated for hippocampal deficits by relying more on the right hippocampus (underlying perceptual memory and the right medial frontal gyrus (MeFG in the anterior prefrontal cortex (PFC. We postulated that the overrecruitment of the right anterior PFC caused dysfunction of the strategic component of episodic memory, which caused deteriorating episodic memory in mTBI survivors. Our findings also suggested that the pattern of brain network changes in TBI survivors presented similar functional consequences to normal aging.

  9. The dynamics of socio-connective trust within support networks accessed by informal caregivers.

    Science.gov (United States)

    Ray, Robin A; Street, Annette F

    2011-03-01

    This article introduces the concept of socio-connective trust, the synapse between the social structures and processes that underpin relationships in supportive care networks. Data from an ethnographic case study of 18 informal caregivers providing in-home care for people with life-limiting illness were analysed drawing on theoretical concepts from the work of Giddens and writings on social capital, as well as the construction of trust in the caregiving literature. While conceptions of trust were found to contribute to understanding supportive care relationships, they did not account for the dynamic nature of the availability and use of support networks. Instead, informal caregivers undertook ongoing reflexive negotiation of relationship boundaries in response to their own conception of the current situation and their perception of trust in their relationships with the various members of the support network. The concept of socio-connective trust describes the movement and flow of the flexible bonds that influence relationships among care networks and determine the type and range of support accessed by informal caregivers. Understanding the complexities of socio-connective trust in caregiving relationships will assist health and social care workers to mobilize relevant resources to support informal caregivers.

  10. Structural connectivity in spatial attention network: reconstruction from left hemispatial neglect.

    Science.gov (United States)

    Hattori, Takaaki; Ito, Kenji; Nakazawa, Chika; Numasawa, Yoshiyuki; Watanabe, Mayumi; Aoki, Shigeki; Mizusawa, Hidehiro; Ishiai, Sumio; Yokota, Takanori

    2018-04-01

    Left hemispatial neglect (neglect) is an impaired state of spatial attention. We aimed to reconstruct structural connectivity in the spatial attention network and to identify disconnection patterns underlying neglect. We enrolled 59 right-handed patients who had their first-ever infarction in the right hemisphere and classified them into neglect group (34 patients with neglect) and control group (25 patients without neglect). The neglect group was further subcategorized into 6 subgroups based on infarcted vascular territories. Diffusion tensor imaging data were obtained from all patients. Fractional anisotropy maps were compared between neglect group/subgroups and the control group by using non-parametric voxel-based analysis, generating a lesion path mask. Probabilistic tractography analysis using the lesion path mask reconstructed the following structural connectivity in the spatial attention network, which is specifically damaged in neglect patients: (1) superior longitudinal fasciculus (SLF) I connecting the superior parietal lobule/intraparietal sulcus with the superior frontal gyrus/frontal eye field (SFG/FEF) (dorsal attention network); (2) SLF III/the arcuate fasciculus (AF) and the extreme capsule/inferior fronto-occipital fasciculus (IFOF) connecting the right inferior parietal lobule/temporoparietal junction/superior temporal gyrus (IPL/TPJ/STG) with the middle frontal gyrus/inferior frontal gyrus (ventral attention network); (3) the thalamic radiations to the spatial attention-related cortices; and (4) SLF II and IFOF interconnecting dorsal and ventral attention networks. Individual analysis indicated that isolated damage in SLF I, SLF II, SLF III/AF or the thalamic radiations to IPL/TPJ/STG due to posterior cerebral artery infarction, or simultaneous damage in four thalamic radiations due to anterior choroidal artery infarction, underlies different phenotypes of neglect.

  11. Overview of FACTS devices for wind power plants directly connected to the transmission network

    DEFF Research Database (Denmark)

    Adamczyk, Andrzej Grzegorz; Teodorescu, Remus; Rodriguez, Pedro

    2010-01-01

    of the electrical network with high wind energy penetration might be compromised. For this reason transmission system operators (TSO) impose more stringent connection requirements on the wind power plant (WPP) owners. On the other hand flexible AC transmission systems (FACTS) devices offer enhancement of grid...... stability and can facilitate grid code compliance for WPP. In this paper state-of-the-art in FACTS for WPPs with AC connection is given. FACTS devices with their properties are described. HVDC, which in literature is also often recognized as FACTS device, is out of this paper scope. Academic and industrial...

  12. 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.

  13. Integrated monitoring of multi-domain backbone connections Operational experience in the LHC optical private network

    CERN Document Server

    Marcu, Patricia; Fritz, Wolfgang; Yampolskiy, Mark; Hommel, Wolfgang

    2011-01-01

    Novel large scale research projects often require cooperation between various different project partners that are spread among the entire world. They do not only need huge computing resources, but also a reliable network to operate on. The Large Hadron Collider (LHC) at CERN is a representative example for such a project. Its experiments result in a vast amount of data, which is interesting for researchers around the world. For transporting the data from CERN to 11 data processing and storage sites, an optical private network (OPN) has been constructed. As the experiment data is highly valuable, LHC defines very high requirements to the underlying network infrastructure. In order to fulfil those requirements, the connections have to be managed and monitored permanently. In this paper, we present the integrated monitoring solution developed for the LHCOPN. We first outline the requirements and show how they are met on the single network layers. After that, we describe, how those single measurements can be comb...

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

    DEFF Research Database (Denmark)

    Abulanwar, Elsayed; Hu, Weihao; Chen, Zhe

    2016-01-01

    and smoothness at the point of connection (POC) in order to maximise the wind power penetration into such networks. Intensive simulation case studies under different network topology and wind speed ranges reveal the effectiveness of the AVC scheme to effectively suppress the POC voltage variations particularly......Significant voltage fluctuations and power quality issues pose considerable constraints on the efficient integration of remotely located wind turbines into weak networks. Besides, 3p oscillations arising from the wind shear and tower shadow effects induce further voltage perturbations during...... continuous operation. This study investigates and analyses the repercussions raised by integrating a doubly-fed induction generator wind turbine into an ac network of different parameters and very weak conditions. An adaptive voltage control (AVC) strategy is proposed to retain voltage constancy...

  15. 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.

  16. Resting-state Network-specific Breakdown of Functional Connectivity during Ketamine Alteration of Consciousness in Volunteers.

    Science.gov (United States)

    Bonhomme, Vincent; Vanhaudenhuyse, Audrey; Demertzi, Athena; Bruno, Marie-Aurélie; Jaquet, Oceane; Bahri, Mohamed Ali; Plenevaux, Alain; Boly, Melanie; Boveroux, Pierre; Soddu, Andrea; Brichant, Jean François; Maquet, Pierre; Laureys, Steven

    2016-11-01

    Consciousness-altering anesthetic agents disturb connectivity between brain regions composing the resting-state consciousness networks (RSNs). The default mode network (DMn), executive control network, salience network (SALn), auditory network, sensorimotor network (SMn), and visual network sustain mentation. Ketamine modifies consciousness differently from other agents, producing psychedelic dreaming and no apparent interaction with the environment. The authors used functional magnetic resonance imaging to explore ketamine-induced changes in RSNs connectivity. Fourteen healthy volunteers received stepwise intravenous infusions of ketamine up to loss of responsiveness. Because of agitation, data from six subjects were excluded from analysis. RSNs connectivity was compared between absence of ketamine (wake state [W1]), light ketamine sedation, and ketamine-induced unresponsiveness (deep sedation [S2]). Increasing the depth of ketamine sedation from W1 to S2 altered DMn and SALn connectivity and suppressed the anticorrelated activity between DMn and other brain regions. During S2, DMn connectivity, particularly between the medial prefrontal cortex and the remaining network (effect size β [95% CI]: W1 = 0.20 [0.18 to 0.22]; S2 = 0.07 [0.04 to 0.09]), and DMn anticorrelated activity (e.g., right sensory cortex: W1 = -0.07 [-0.09 to -0.04]; S2 = 0.04 [0.01 to 0.06]) were broken down. SALn connectivity was nonuniformly suppressed (e.g., left parietal operculum: W1 = 0.08 [0.06 to 0.09]; S2 = 0.05 [0.02 to 0.07]). Executive control networks, auditory network, SMn, and visual network were minimally affected. Ketamine induces specific changes in connectivity within and between RSNs. Breakdown of frontoparietal DMn connectivity and DMn anticorrelation and sensory and SMn connectivity preservation are common to ketamine and propofol-induced alterations of consciousness.

  17. 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.

  18. 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

  19. 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

  20. Thalamocortical functional connectivity in Lennox-Gastaut syndrome is abnormally enhanced in executive-control and default-mode networks.

    Science.gov (United States)

    Warren, Aaron E L; Abbott, David F; Jackson, Graeme D; Archer, John S

    2017-12-01

    To identify abnormal thalamocortical circuits in the severe epilepsy of Lennox-Gastaut syndrome (LGS) that may explain the shared electroclinical phenotype and provide potential treatment targets. Twenty patients with a diagnosis of LGS (mean age = 28.5 years) and 26 healthy controls (mean age = 27.6 years) were compared using task-free functional magnetic resonance imaging (MRI). The thalamus was parcellated according to functional connectivity with 10 cortical networks derived using group-level independent component analysis. For each cortical network, we assessed between-group differences in thalamic functional connectivity strength using nonparametric permutation-based tests. Anatomical locations were identified by quantifying spatial overlap with a histologically informed thalamic MRI atlas. In both groups, posterior thalamic regions showed functional connectivity with visual, auditory, and sensorimotor networks, whereas anterior, medial, and dorsal thalamic regions were connected with networks of distributed association cortex (including the default-mode, anterior-salience, and executive-control networks). Four cortical networks (left and right executive-control network; ventral and dorsal default-mode network) showed significantly enhanced thalamic functional connectivity strength in patients relative to controls. Abnormal connectivity was maximal in mediodorsal and ventrolateral thalamic nuclei. Specific thalamocortical circuits are affected in LGS. Functional connectivity is abnormally enhanced between the mediodorsal and ventrolateral thalamus and the default-mode and executive-control networks, thalamocortical circuits that normally support diverse cognitive processes. In contrast, thalamic regions connecting with primary and sensory cortical networks appear to be less affected. Our previous neuroimaging studies show that epileptic activity in LGS is expressed via the default-mode and executive-control networks. Results of the present study suggest that

  1. Mindfulness is associated with intrinsic functional connectivity between default mode and salience networks

    Science.gov (United States)

    Doll, Anselm; Hölzel, Britta K.; Boucard, Christine C.; Wohlschläger, Afra M.; Sorg, Christian

    2015-01-01

    Mindfulness is attention to present moment experience without judgment. Mindfulness practice is associated with brain activity in areas overlapping with the default mode, salience, and central executive networks (DMN, SN, CEN). We hypothesized that intrinsic functional connectivity (iFC; i.e., synchronized ongoing activity) across these networks is associated with mindfulness scores. After 2 weeks of daily 20 min attention to breath training, healthy participants were assessed by mindfulness questionnaires and resting-state functional MRI. Independent component analysis (ICA) of imaging data revealed networks of interest, whose activity time series defined inter-network intrinsic functional connectivity (inter-iFC) by temporal correlation. Inter-iFC between subnetworks of the DMN and SN—and inter-iFC between subnetworks of the SN and left CEN at trend—was correlated with mindfulness scores. Additional control analyses about visual networks’ inter-iFC support the specificity of our findings. Results provide evidence that mindfulness is associated with iFC between DMN and SN. Data suggest that ongoing interactions among central intrinsic brain networks link with the ability to attend to current experience without judgment. PMID:26379526

  2. Evaluating the impact of connectivity, continuity, and topography of sidewalk network on pedestrian safety.

    Science.gov (United States)

    Osama, Ahmed; Sayed, Tarek

    2017-10-01

    With the increasing demand for sustainability, walking is being encouraged as one of the main active modes of transportation. However, pedestrians are vulnerable to severe injuries when involved in crashes which can discourage road users from walking. Therefore, studying factors that affect the safety of pedestrians is important. This paper investigates the relationship between pedestrian-motorist crashes and various sidewalk network indicators in the city of Vancouver. The goal is to assess the impact of network connectivity, directness, and topography on pedestrian safety using macro-level collision prediction models. The models were developed using generalized linear regression and full Bayesian techniques. Both walking trips and vehicle kilometers travelled were used as the main traffic exposure variables in the models. The safety models supported the safety in numbers hypothesis showing a non-linear positive association between pedestrian-motorist crashes and the increase in walking trips and vehicle traffic. The model results also suggested that higher continuity, linearity, coverage, and slope of sidewalk networks were associated with lower crash occurrence. However, network connectivity was associated with higher crash occurrence. The spatial effects were accounted for in the full Bayes models and were found significant. The models provide insights about the factors that influence pedestrian safety and the spatial variability of pedestrian crashes within a city, which can be useful for the planning of pedestrian networks. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Analyzing Social Media Networks with NodeXL Insights from a Connected World

    CERN Document Server

    Hansen, Derek; Smith, Marc A

    2010-01-01

    Businesses, entrepreneurs, individuals, and government agencies alike are looking to social network analysis (SNA) tools for insight into trends, connections, and fluctuations in social media. Microsoft's NodeXL is a free, open-source SNA plug-in for use with Excel. It provides instant graphical representation of relationships of complex networked data. But it goes further than other SNA tools -- NodeXL was developed by a multidisciplinary team of experts that bring together information studies, computer science, sociology, human-computer interaction, and over 20 years of visual analytic theor

  4. Characterization and assessment of voltage and power constraints of DFIG WT connected to a weak network

    DEFF Research Database (Denmark)

    Abulanwar, Elsayed; Hu, Weihao; Iov, Florin

    2014-01-01

    This article thoroughly investigates the challenges and constraints raised by the integration of a Doubly-fed Induction generator wind turbine, DFIG WT, into an ac network of extensively varying parameters and very weak conditions. The objective is to mitigate the voltage variations at the point...... of common coupling, PCC, and maximize the wind power penetration into weak networks. As a basis of investigation, a simplified system model is utilized and the respective PCC voltage, active and reactive power stability issues are identified. Besides, a steady-state study for DFIG WT connected to a weak...

  5. 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.

  6. Replicated landscape genetic and network analyses reveal wide variation in functional connectivity for American pikas.

    Science.gov (United States)

    Castillo, Jessica A; Epps, Clinton W; Jeffress, Mackenzie R; Ray, Chris; Rodhouse, Thomas J; Schwalm, Donelle

    2016-09-01

    Landscape connectivity is essential for maintaining viable populations, particularly for species restricted to fragmented habitats or naturally arrayed in metapopulations and facing rapid climate change. The importance of assessing both structural connectivity (physical distribution of favorable habitat patches) and functional connectivity (how species move among habitat patches) for managing such species is well understood. However, the degree to which functional connectivity for a species varies among landscapes, and the resulting implications for conservation, have rarely been assessed. We used a landscape genetics approach to evaluate resistance to gene flow and, thus, to determine how landscape and climate-related variables influence gene flow for American pikas (Ochotona princeps) in eight federally managed sites in the western United States. We used empirically derived, individual-based landscape resistance models in conjunction with predictive occupancy models to generate patch-based network models describing functional landscape connectivity. Metareplication across landscapes enabled identification of limiting factors for dispersal that would not otherwise have been apparent. Despite the cool microclimates characteristic of pika habitat, south-facing aspects consistently represented higher resistance to movement, supporting the previous hypothesis that exposure to relatively high temperatures may limit dispersal in American pikas. We found that other barriers to dispersal included areas with a high degree of topographic relief, such as cliffs and ravines, as well as streams and distances greater than 1-4 km depending on the site. Using the empirically derived network models of habitat patch connectivity, we identified habitat patches that were likely disproportionately important for maintaining functional connectivity, areas in which habitat appeared fragmented, and locations that could be targeted for management actions to improve functional connectivity

  7. 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.

  8. Network modularity reveals critical scales for connectivity in ecology and evolution

    Science.gov (United States)

    Fletcher, Robert J.; Revell, Andre; Reichert, Brian E.; Kitchens, Wiley M.; Dixon, J.; Austin, James D.

    2013-01-01

    For nearly a century, biologists have emphasized the profound importance of spatial scale for ecology, evolution and conservation. Nonetheless, objectively identifying critical scales has proven incredibly challenging. Here we extend new techniques from physics and social sciences that estimate modularity on networks to identify critical scales for movement and gene flow in animals. Using four species that vary widely in dispersal ability and include both mark-recapture and population genetic data, we identify significant modularity in three species, two of which cannot be explained by geographic distance alone. Importantly, the inclusion of modularity in connectivity and population viability assessments alters conclusions regarding patch importance to connectivity and suggests higher metapopulation viability than when ignoring this hidden spatial scale. We argue that network modularity reveals critical meso-scales that are probably common in populations, providing a powerful means of identifying fundamental scales for biology and for conservation strategies aimed at recovering imperilled species.

  9. 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.

  10. 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.

  11. Barbed channels enhance unidirectional connectivity between neuronal networks cultured on multi electrode arrays.

    Directory of Open Access Journals (Sweden)

    Joost eLe Feber

    2015-11-01

    Full Text Available Cultured neurons on multi electrode arrays (MEAs have been widely used to study various as-pects of neuronal (network functioning. A possible drawback of this approach is the lack of structure in these networks. At the single cell level, several solutions have been proposed to ena-ble directed connectivity, and promising results were obtained. At the level of connected sub-populations, a few attempts have been made with promising results. First assessment of the de-signs’ functionality, however, suggested room for further improvement.We designed a two chamber MEA aiming to create a unidirectional connection between the net-works in both chambers (‘emitting’ and ‘receiving’. To achieve this unidirectionality, all inter-connecting channels contained barbs that hindered axon growth in the opposite direction (from receiving to emitting chamber. Visual inspection showed that axons predominantly grew through the channels in the promoted direction . This observation was confirmed by spontaneous activity recordings. Cross-correlation between the signals from two electrodes inside the channels suggested signal propagation at ≈2 m/s from emitting to receiving chamber. Cross-correlation between the firing patterns in both chambers indicated that most correlated activity was initiated in the emitting chamber, which was also reflected by a significantly lower fraction of partial bursts (e. a one-chamber-only burst in the emitting chamber. Finally, electrical stimulation in the emitting chamber induced a fast response in that chamber, and a slower response in the receiving chamber. Stimulation in the receiving chamber evoked a fast response in that chamber, but no response in the emitting chamber. These results confirm the predominantly unidirectional nature of the connecting channels from emitting to receiving chamber.

  12. Aberrant functional network connectivity in psychopathy from a large (N = 985) forensic sample.

    Science.gov (United States)

    Espinoza, Flor A; Vergara, Victor M; Reyes, Daisy; Anderson, Nathaniel E; Harenski, Carla L; Decety, Jean; Rachakonda, Srinivas; Damaraju, Eswar; Rashid, Barnaly; Miller, Robyn L; Koenigs, Michael; Kosson, David S; Harenski, Keith; Kiehl, Kent A; Calhoun, Vince D

    2018-03-02

    Psychopathy is a personality disorder characterized by antisocial behavior, lack of remorse and empathy, and impaired decision making. The disproportionate amount of crime committed by psychopaths has severe emotional and economic impacts on society. Here we examine the neural correlates associated with psychopathy to improve early assessment and perhaps inform treatments for this condition. Previous resting-state functional magnetic resonance imaging (fMRI) studies in psychopathy have primarily focused on regions of interest. This study examines whole-brain functional connectivity and its association to psychopathic traits. Psychopathy was hypothesized to be characterized by aberrant functional network connectivity (FNC) in several limbic/paralimbic networks. Group-independent component and regression analyses were applied to a data set of resting-state fMRI from 985 incarcerated adult males. We identified resting-state networks (RSNs), estimated FNC between RSNs, and tested their association to psychopathy factors and total summary scores (Factor 1, interpersonal/affective; Factor 2, lifestyle/antisocial). Factor 1 scores showed both increased and reduced functional connectivity between RSNs from seven brain domains (sensorimotor, cerebellar, visual, salience, default mode, executive control, and attentional). Consistent with hypotheses, RSNs from the paralimbic system-insula, anterior and posterior cingulate cortex, amygdala, orbital frontal cortex, and superior temporal gyrus-were related to Factor 1 scores. No significant FNC associations were found with Factor 2 and total PCL-R scores. In summary, results suggest that the affective and interpersonal symptoms of psychopathy (Factor 1) are associated with aberrant connectivity in multiple brain networks, including paralimbic regions. © 2018 Wiley Periodicals, Inc.

  13. Altered resting-state network connectivity in stroke patients with and without apraxia of speech

    OpenAIRE

    New, Anneliese B.; Robin, Donald A.; Parkinson, Amy L.; Duffy, Joseph R.; McNeil, Malcom R.; Piguet, Olivier; Hornberger, Michael; Price, Cathy J.; Eickhoff, Simon B.; Ballard, Kirrie J.

    2015-01-01

    Motor speech disorders, including apraxia of speech (AOS), account for over 50% of the communication disorders following stroke. Given its prevalence and impact, and the need to understand its neural mechanisms, we used resting state functional MRI to examine functional connectivity within a network of regions previously hypothesized as being associated with AOS (bilateral anterior insula (aINS), inferior frontal gyrus (IFG), and ventral premotor cortex (PM)) in a group of 32 left hemisphere ...

  14. 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.

  15. Slowly evolving connectivity in recurrent neural networks: I. The extreme dilution regime

    Science.gov (United States)

    Wemmenhove, B.; Skantzos, N. S.; Coolen, A. C. C.

    2004-08-01

    We study extremely diluted spin models of neural networks in which the connectivity evolves in time, although adiabatically slowly compared to the neurons, according to stochastic equations which on average aim to reduce frustration. The (fast) neurons and (slow) connectivity variables equilibrate separately, but at different temperatures. Our model is exactly solvable in equilibrium. We obtain phase diagrams upon making the condensed ansatz (i.e. recall of one pattern). These show that, as the connectivity temperature is lowered, the volume of the retrieval phase diverges and the fraction of mis-aligned spins is reduced. Still one always retains a region in the retrieval phase where recall states other than the one corresponding to the 'condensed' pattern are locally stable, so the associative memory character of our model is preserved.

  16. Slowly evolving connectivity in recurrent neural networks: I. The extreme dilution regime

    International Nuclear Information System (INIS)

    Wemmenhove, B; Skantzos, N S; Coolen, A C C

    2004-01-01

    We study extremely diluted spin models of neural networks in which the connectivity evolves in time, although adiabatically slowly compared to the neurons, according to stochastic equations which on average aim to reduce frustration. The (fast) neurons and (slow) connectivity variables equilibrate separately, but at different temperatures. Our model is exactly solvable in equilibrium. We obtain phase diagrams upon making the condensed ansatz (i.e. recall of one pattern). These show that, as the connectivity temperature is lowered, the volume of the retrieval phase diverges and the fraction of mis-aligned spins is reduced. Still one always retains a region in the retrieval phase where recall states other than the one corresponding to the 'condensed' pattern are locally stable, so the associative memory character of our model is preserved

  17. 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

  18. Facilitating efficient augmentation of transmission networks to connect renewable energy generation: the Australian experience

    International Nuclear Information System (INIS)

    Wright, Glen

    2012-01-01

    Australia is heavily dependent on coal for electricity generation. The Renewable Energy Target has spurred growth in the utilization of renewable energy sources, with further growth expected into the future. Australia's strongest renewable energy sources are generally distant from the transmission network in resource ‘basins’. Investment is needed to augment the transmission network to enable delivery of electricity from these sources to consumers. Considerable economies of scale flow from anticipating the connection of numerous generators in an area over time and sizing augmentations accordingly. Following a lengthy rulemaking process, the National Electricity Rules were recently amended by a new rule, designed to facilitate the construction of such efficiently sized augmentations. However, the new rule is more conservative than initially envisaged, making little substantive change to the current frameworks for augmentation and connection. This paper outlines these frameworks and the rulemaking process and identifies the key debates surrounding the rule change are identified. This paper then provides a detailed analysis of the new rule, concluding that it is defective in a number of respects and is unlikely to result in the efficient and timely augmentation of the network needed to unlock the potential of Australia's strongest renewable energy resources. - Highlights: ► Remoteness of renewable energy sources is a barrier to greater renewable energy utilization. ► Significant economies of scale flow from efficiently-sized transmission network augmentation. ► Current frameworks in Australia do not incentivise efficiently-sized network augmentations. ► The lack of property rights in an augmentation is particularly problematic. ► The new Scale Efficient Network Extensions rule is not apt to facilitate efficiently-sized network augmentations.

  19. Comparing brain networks of different size and connectivity density using graph theory.

    Directory of Open Access Journals (Sweden)

    Bernadette C M van Wijk

    Full Text Available Graph theory is a valuable framework to study the organization of functional and anatomical connections in the brain. Its use for comparing network topologies, however, is not without difficulties. Graph measures may be influenced by the number of nodes (N and the average degree (k of the network. The explicit form of that influence depends on the type of network topology, which is usually unknown for experimental data. Direct comparisons of graph measures between empirical networks with different N and/or k can therefore yield spurious results. We list benefits and pitfalls of various approaches that intend to overcome these difficulties. We discuss the initial graph definition of unweighted graphs via fixed thresholds, average degrees or edge densities, and the use of weighted graphs. For instance, choosing a threshold to fix N and k does eliminate size and density effects but may lead to modifications of the network by enforcing (ignoring non-significant (significant connections. Opposed to fixing N and k, graph measures are often normalized via random surrogates but, in fact, this may even increase the sensitivity to differences in N and k for the commonly used clustering coefficient and small-world index. To avoid such a bias we tried to estimate the N,k-dependence for empirical networks, which can serve to correct for size effects, if successful. We also add a number of methods used in social sciences that build on statistics of local network structures including exponential random graph models and motif counting. We show that none of the here-investigated methods allows for a reliable and fully unbiased comparison, but some perform better than others.

  20. Emergence of modular structure in a large-scale brain network with interactions between dynamics and connectivity

    Directory of Open Access Journals (Sweden)

    Cornelis Jan Stam

    2010-09-01

    Full Text Available A network of 32 or 64 connected neural masses, each representing a large population of interacting excitatory and inhibitory neurons and generating an EEG / MEG like output signal, was used to demonstrate how an interaction between dynamics and connectivity might explain the emergence of complex network features, in particular modularity. Network evolution was modeled by two processes: (i synchronization dependent plasticity (SDP and (ii growth dependent plasticity (GDP. In the case of SDP, connections between neural masses were strengthened when they were strongly synchronized, and were weakened when they were not. GDP was modeled as a homeostatic process with random, distance dependent outgrowth of new connections between neural masses. GDP alone resulted in stable networks with distance dependent connection strengths, typical small-world features, but no degree correlations and only weak modularity. SDP applied to random networks induced clustering, but no clear modules. Stronger modularity evolved only through an interaction of SDP and GDP, with the number and size of the modules depending on the relative strength of both processes, as well as on the size of the network. Lesioning part of the network, after a stable state was achieved, resulted in a temporary disruption of the network structure. The model gives a possible scenario to explain how modularity can arise in developing brain networks, and makes predictions about the time course of network changes during development and following acute lesions.

  1. 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.

  2. Altered resting state connectivity in right side frontoparietal network in primary insomnia patients

    International Nuclear Information System (INIS)

    Li, Shumei; Tian, Junzhang; Li, Meng; Wang, Tianyue; Lin, Chulan; Yin, Yi; Jiang, Guihua; Zeng, Luxian; Li, Cheng

    2018-01-01

    This study investigated alterations of resting-state networks (RSNs) in primary insomnia patients as well as relationships between these changes and clinical features. Fifty-nine primary insomnia patients and 53 healthy control subjects underwent a resting-state fMRI scan (rs-fMRI). Ten RSNs were identified using independent component analysis of rs-fMRI data. To assess significant differences between the two groups, voxel-wise analysis of ten RSNs was conducted using dual regression with FSL randomised non-parametric permutation testing and a threshold-free cluster enhanced technique to control for multiple comparisons. Relationships between abnormal functional connectivity and clinical variables were then investigated with Pearson's correlation analysis. Primary insomnia patients showed decreased connectivity in regions of the right frontoparietal network (FPN), including the superior parietal lobule and superior frontal gyrus. Moreover, decreased connectivity in the right middle temporal gyrus and right lateral occipital cortex with the FPN showed significant positive correlations with disease duration and self-rated anxiety, respectively. Our study suggests that primary insomnia patients are characterised by abnormal organisation of the right FPN, and dysfunction of the FPN is correlated with disease duration and anxiety. The results enhance our understanding of neural substrates underlying symptoms of primary insomnia from the viewpoint of resting-state networks. (orig.)

  3. Circadian waves of cytosolic calcium concentration and long-range network connections in rat suprachiasmatic nucleus.

    Science.gov (United States)

    Hong, Jin Hee; Jeong, Byeongha; Min, Cheol Hong; Lee, Kyoung J

    2012-05-01

    The suprachiasmatic nucleus (SCN) is the master clock in mammals governing the daily physiological and behavioral rhythms. It is composed of thousands of clock cells with their own intrinsic periods varying over a wide range (20-28 h). Despite this heterogeneity, an intact SCN maintains a coherent 24 h periodic rhythm through some cell-to-cell coupling mechanisms. This study examined how the clock cells are connected to each other and how their phases are organized in space by monitoring the cytosolic free calcium ion concentration ([Ca(2+)](c)) of clock cells using the calcium-binding fluorescent protein, cameleon. Extensive analysis of 18 different organotypic slice cultures of the SCN showed that the SCN calcium dynamics is coordinated by phase-synchronizing networks of long-range neurites as well as by diffusively propagating phase waves. The networks appear quite extensive and far-reaching, and the clock cells connected by them exhibit heterogeneous responses in their amplitudes and periods of oscillation to tetrodotoxin treatments. Taken together, our study suggests that the network of long-range cellular connectivity has an important role for the SCN in achieving its phase and period coherence. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  4. Early math achievement and functional connectivity in the fronto-parietal network.

    Science.gov (United States)

    Emerson, Robert W; Cantlon, Jessica F

    2012-02-15

    In this study we test the hypothesis that the functional connectivity of the frontal and parietal regions that children recruit during a basic numerical task (matching Arabic numerals to arrays of dots) is predictive of their math test scores (TEMA-3; Ginsburg, 2003). Specifically, we tested 4-11-year-old children on a matching task during fMRI to localize a fronto-parietal network that responds more strongly during numerical matching than matching faces, words, or shapes. We then tested the functional connectivity between those regions during an independent task: natural viewing of an educational video that included math topics. Using this novel natural viewing method, we found that the connectivity between frontal and parietal regions during task-independent free-viewing of educational material is correlated with children's basic number matching ability, as well as their scores on the standardized test of mathematical ability (the TEMA). The correlation between children's mathematics scores and fronto-parietal connectivity is math-specific in the sense that it is independent of children's verbal IQ scores. Moreover, a control network, selective for faces, showed no correlation with mathematics performance. Finally, brain regions that correlate with subjects' overall response times in the matching task do not account for our number- and math-related effects. We suggest that the functional intersection of number-related frontal and parietal regions is math-specific. Copyright © 2011 Elsevier Ltd. All rights reserved.

  5. FLOW-BASED NETWORK MEASURES OF BRAIN CONNECTIVITY IN ALZHEIMER'S DISEASE.

    Science.gov (United States)

    Prasad, Gautam; Joshi, Shantanu H; Nir, Talia M; Toga, Arthur W; Thompson, Paul M

    2013-01-01

    We present a new flow-based method for modeling brain structural connectivity. The method uses a modified maximum-flow algorithm that is robust to noise in the diffusion data and guided by biologically viable pathways and structure of the brain. A flow network is first created using a lattice graph by connecting all lattice points (voxel centers) to all their neighbors by edges. Edge weights are based on the orientation distribution function (ODF) value in the direction of the edge. The maximum-flow is computed based on this flow graph using the flow or the capacity between each region of interest (ROI) pair by following the connected tractography fibers projected onto the flow graph edges. Network measures such as global efficiency, transitivity, path length, mean degree, density, modularity, small world, and assortativity are computed from the flow connectivity matrix. We applied our method to diffusion-weighted images (DWIs) from 110 subjects (28 normal elderly, 56 with early and 11 with late mild cognitive impairment, and 15 with AD) and segmented co-registered anatomical MRIs into cortical regions. Experimental results showed better performance compared to the standard fiber-counting methods when distinguishing Alzheimer's disease from normal aging.

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Fernanda Palhano-Fontes

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

  8. Mindfulness Meditation Training and Executive Control Network Resting State Functional Connectivity: A Randomized Controlled Trial.

    Science.gov (United States)

    Taren, Adrienne A; Gianaros, Peter J; Greco, Carol M; Lindsay, Emily K; Fairgrieve, April; Brown, Kirk Warren; Rosen, Rhonda K; Ferris, Jennifer L; Julson, Erica; Marsland, Anna L; Creswell, J David

    Mindfulness meditation training has been previously shown to enhance behavioral measures of executive control (e.g., attention, working memory, cognitive control), but the neural mechanisms underlying these improvements are largely unknown. Here, we test whether mindfulness training interventions foster executive control by strengthening functional connections between dorsolateral prefrontal cortex (dlPFC)-a hub of the executive control network-and frontoparietal regions that coordinate executive function. Thirty-five adults with elevated levels of psychological distress participated in a 3-day randomized controlled trial of intensive mindfulness meditation or relaxation training. Participants completed a resting state functional magnetic resonance imaging scan before and after the intervention. We tested whether mindfulness meditation training increased resting state functional connectivity (rsFC) between dlPFC and frontoparietal control network regions. Left dlPFC showed increased connectivity to the right inferior frontal gyrus (T = 3.74), right middle frontal gyrus (MFG) (T = 3.98), right supplementary eye field (T = 4.29), right parietal cortex (T = 4.44), and left middle temporal gyrus (T = 3.97, all p work showing increased functional connectivity among brain regions associated with executive function during active meditation by identifying specific neural circuits in which rsFC is enhanced by a mindfulness intervention in individuals with high levels of psychological distress. Clinicaltrials.gov,NCT01628809.

  9. Hypothesis for the pathophysiology of delirium: role of baseline brain network connectivity and changes in inhibitory tone.

    Science.gov (United States)

    Sanders, Robert D

    2011-07-01

    Normal brain function is facilitated by a highly organized and interconnected structure allowing complex integration of sensory information and motor responses. The acute confusional state of delirium is characterized by a fluctuating disturbance in consciousness, arousal level and cognition-memory; as such, delirium represents a failure in the integration and appropriate processing of information. The pathogenesis of this cognitive disintegration is unclear; herein a hypothesis is proposed that delirium results from an acute breakdown in network connectivity within the brain. The hypothesis predicts that the extent to which the network connectivity breaks down is dependent on two factors: (i) the baseline connectivity within the brain and (ii) the level of inhibitory tone. Baseline connectivity is the connectivity of neural networks within the brain before the precipitating insult provoking delirium. Many non-modifiable risk factors for delirium influence baseline connectivity such as age, cognitive impairment, dementia and depression. Precipitant events that provoke delirium (modifiable risk factors) are hypothesized to further, and acutely, breakdown network connectivity by increasing inhibitory tone within the brain. Modifiable risk factors include inflammation, metabolic abnormalities, sleep deprivation and medication such as benzodiazepines. An important role for GABAergic neurotransmission is implicated in increasing the inhibitory tone to produce delirium. This theory accounts for the various forms of delirium, hypoactive, hyperactive and mixed. The form of delirium that ensues will depend upon how and which networks breakdown (dependent on both the individual's baseline network connectivity and the degree change in inhibitory tone produced). Copyright © 2011 Elsevier Ltd. All rights reserved.

  10. 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.

  11. Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks.

    Science.gov (United States)

    Lonardoni, Davide; Amin, Hayder; Di Marco, Stefano; Maccione, Alessandro; Berdondini, Luca; Nieus, Thierry

    2017-07-01

    Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs), interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities) that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity.

  12. Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks.

    Directory of Open Access Journals (Sweden)

    Davide Lonardoni

    2017-07-01

    Full Text Available Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs, interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity.

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

    Directory of Open Access Journals (Sweden)

    Recep Colak

    2010-10-01

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

  14. Dendritic Connectivity, Heterogeneity, and Scaling in Urban Stormwater Networks: Implications for Socio-Hydrology

    Science.gov (United States)

    Mejia, A.; Jovanovic, T.; Hale, R. L.; Gironas, J. A.

    2017-12-01

    Urban stormwater networks (USNs) are unique dendritic (tree-like) structures that combine both artificial (e.g., swales and pipes) and natural (e.g., streams and wetlands) components. They are central to stream ecosystem structure and function in urban watersheds. The emphasis of conventional stormwater management, however, has been on localized, temporal impacts (e.g., changes to hydrographs at discrete locations), and the performance of individual stormwater control measures. This is the case even though control measures are implemented to prevent impacts on the USN. We develop a modeling approach to retrospectively study hydrological fluxes and states in USNs and apply the model to an urban watershed in Scottsdale, Arizona, USA. Using outputs from the model, we analyze over space and time the network properties of dendritic connectivity, heterogeneity, and scaling. Results show that as the network growth over time, due to increasing urbanization, it tends to become more homogenous in terms of topological features but increasingly heterogeneous in terms of dynamic features. We further use the modeling results to address socio-hydrological implications for USNs. We find that the adoption over time of evolving management strategies (e.g., widespread implementation of vegetated swales and retention ponds versus pipes) may be locally beneficial to the USN but benefits may not propagate systematically through the network. The latter can be reinforced by sudden, perhaps unintended, changes to the overall dendritic connectivity.

  15. Altered effective connectivity among core neurocognitive networks in idiopathic generalized epilepsy: An fMRI evidence

    Directory of Open Access Journals (Sweden)

    Huilin Wei

    2016-09-01

    Full Text Available 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.

  16. 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. © 2015 Wiley Periodicals, Inc.

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

    Directory of Open Access Journals (Sweden)

    Ettore Mosca

    2017-09-01

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

  18. Intrinsic default mode network connectivity predicts spontaneous verbal descriptions of autobiographical memories during social processing

    Directory of Open Access Journals (Sweden)

    Xiao-Fei eYang

    2013-01-01

    Full Text Available Neural systems activated in a coordinated way during rest, known as the default mode network (DMN, also support autobiographical memory (AM retrieval and social processing/mentalizing. However, little is known about how individual variability in reliance on personal memories during social processing relates to individual differences in DMN functioning during rest (intrinsic functional connectivity. Here we examined 18 participants’ spontaneous descriptions of autobiographical memories during a two-hour, private, open-ended interview in which they reacted to a series of true stories about real people’s social situations and responded to the prompt, how does this person’s story make you feel? We classified these descriptions as either containing factual information (semantic AMs or more elaborate descriptions of emotionally meaningful events (episodic AMs. We also collected resting state fMRI scans from the participants and related individual differences in frequency of described AMs to participants’ intrinsic functional connectivity within regions of the DMN. We found that producing more descriptions of either memory type correlated with stronger intrinsic connectivity in the parahippocampal and middle temporal gyri. Additionally, episodic AM descriptions correlated with connectivity in the bilateral hippocampi and medial prefrontal cortex, and semantic memory descriptions correlated with connectivity in right inferior lateral parietal cortex. These findings suggest that in individuals who naturally invoke more memories during social processing, brain regions involved in memory retrieval and self/social processing are more strongly coupled to the DMN during rest.

  19. 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.

  20. Intrinsic Default Mode Network Connectivity Predicts Spontaneous Verbal Descriptions of Autobiographical Memories during Social Processing.

    Science.gov (United States)

    Yang, Xiao-Fei; Bossmann, Julia; Schiffhauer, Birte; Jordan, Matthew; Immordino-Yang, Mary Helen

    2012-01-01

    Neural systems activated in a coordinated way during rest, known as the default mode network (DMN), also support autobiographical memory (AM) retrieval and social processing/mentalizing. However, little is known about how individual variability in reliance on personal memories during social processing relates to individual differences in DMN functioning during rest (intrinsic functional connectivity). Here we examined 18 participants' spontaneous descriptions of autobiographical memories during a 2 h, private, open-ended interview in which they reacted to a series of true stories about real people's social situations and responded to the prompt, "how does this person's story make you feel?" We classified these descriptions as either containing factual information ("semantic" AMs) or more elaborate descriptions of emotionally meaningful events ("episodic" AMs). We also collected resting state fMRI scans from the participants and related individual differences in frequency of described AMs to participants' intrinsic functional connectivity within regions of the DMN. We found that producing more descriptions of either memory type correlated with stronger intrinsic connectivity in the parahippocampal and middle temporal gyri. Additionally, episodic AM descriptions correlated with connectivity in the bilateral hippocampi and medial prefrontal cortex, and semantic memory descriptions correlated with connectivity in right inferior lateral parietal cortex. These findings suggest that in individuals who naturally invoke more memories during social processing, brain regions involved in memory retrieval and self/social processing are more strongly coupled to the DMN during rest.

  1. RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks

    Energy Technology Data Exchange (ETDEWEB)

    Balasundaram, Balabhaskar [Oklahoma State Univ., Stillwater, OK (United States); Butenko, Sergiy [Texas A & M Univ., College Station, TX (United States); Boginski, Vladimir [Univ. of Florida, Gainesville, FL (United States); Uryasev, Stan [Univ. of Florida, Gainesville, FL (United States)

    2013-12-25

    The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need

  2. Assessing the congruence between perceived connectivity and network centrality measures specific to pandemic influenza preparedness in Alberta.

    Science.gov (United States)

    Hall, Justin N; Moore, Spencer; Shiell, Alan

    2010-03-10

    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. 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. Significant mean differences among jurisdictions were observed for in-degree (F(3,116) = 26.60, p 0.05). The results suggest in terms of pandemic preparedness that perceived connectivity may serve as a partial proxy measure of formal out-degree network connectivity.

  3. Does landscape connectivity shape local and global social network structure in white-tailed deer?

    Directory of Open Access Journals (Sweden)

    Erin L Koen

    Full Text Available Intraspecific social behavior can be influenced by both intrinsic and extrinsic factors. While much research has focused on how characteristics of individuals influence their roles in social networks, we were interested in the role that landscape structure plays in animal sociality at both individual (local and population (global levels. We used female white-tailed deer (Odocoileus virginianus in Illinois, USA, to investigate the potential effect of landscape on social network structure by weighting the edges of seasonal social networks with association rate (based on proximity inferred from GPS collar data. At the local level, we found that sociality among female deer in neighboring social groups (n = 36 was mainly explained by their home range overlap, with two exceptions: 1 during fawning in an area of mixed forest and grassland, deer whose home ranges had low forest connectivity were more social than expected; and 2 during the rut in an area of intensive agriculture, deer inhabiting home ranges with high amount and connectedness of agriculture were more social than expected. At the global scale, we found that deer populations (n = 7 in areas with highly connected forest-agriculture edge, a high proportion of agriculture, and a low proportion of forest tended to have higher weighted network closeness, although low sample size precluded statistical significance. This result implies that infectious disease could spread faster in deer populations inhabiting such landscapes. Our work advances the general understanding of animal social networks, demonstrating how landscape features can underlie differences in social behavior both within and among wildlife social networks.

  4. Apathy and intrinsic functional connectivity networks in amnestic mild cognitive impairment

    Directory of Open Access Journals (Sweden)

    Joo SH

    2016-12-01

    Full Text Available Soo Hyun Joo,1 Chang Uk Lee,1 Hyun Kook Lim2 1Department of Psychiatry, Seoul St Mary’s Hospital, Seoul, 2Department of Psychiatry, Saint Vincent Hospital, College of Medicine, The Catholic University of Korea, Suwon, Republic of Korea Background: Although several prior works reported that apathy is associated with conversion to Alzheimer’s disease in individuals with amnestic mild cognitive impairment (aMCI, effects of apathy on the functional connectivity (FC of the brain remain unclear. In this study, we assessed the pattern of association between apathy and default mode network (DMN, salience network and central executive network (CEN in aMCI subjects.Methods: Fifty subjects with aMCI and 50 controls (CONs participated in this study. They underwent clinical assessments and magnetic resonance imaging for the structural and resting-state scan. We explored the patterns of association between apathy inventory (IA total score and the whole-brain voxel-wise FCs of the DMN, salience network and CEN in aMCI subjects.Results: We observed that the FCs of the DMN were less and those of CEN were more in the aMCI group than the CON group. Total IA score was negatively correlated with FCs of the anterior cingulate within the DMN, and positively correlated with FCs of the middle frontal, inferior frontal, and supramarginal gyrus within the CEN in the aMCI group.Conclusion: Our findings suggest that distinctive patterns of association between apathy and FCs in the DMN and CEN in the aMCI group might reflect the putative role of functional network change in the development of apathy in aMCI. Keywords: apathy, amnestic mild cognitive impairment, intrinsic connectivity networks

  5. Default Mode Network Aberrant Connectivity Associated with Neurological Soft Signs in Schizophrenia Patients and Unaffected Relatives.

    Science.gov (United States)

    Galindo, Liliana; Bergé, Daniel; Murray, Graham K; Mané, Anna; Bulbena, Antonio; Pérez, Victor; Vilarroya, Oscar

    2017-01-01

    Brain connectivity and neurological soft signs (NSS) are reportedly abnormal in schizophrenia and unaffected relatives, suggesting they might be useful neurobiological markers of the illness. NSS are discrete sensorimotor impairments thought to correspond to deviant brain development. Although NSS support the hypothesis that schizophrenia involves disruption in functional circuits involving several hetero modal association areas, little is known about the relationship between NSS and brain connectivity. We explored functional connectivity abnormalities of the default mode network (DMN) related to NSS in schizophrenia. A cross-sectional study was performed with 27 patients diagnosed with schizophrenia, 23 unaffected relatives who were unrelated to the schizophrenia subjects included in the study, and 35 healthy controls. Subjects underwent magnetic resonance imaging scans including a functional resting-state acquisition and NSS evaluation. Seed-to-voxel and independent component analyses were used to study brain connectivity. NSS scores were significantly different between groups, ranging from a higher to lower scores for patients, unaffected relatives, and healthy controls, respectively (analysis of variance effect of group F  = 56.51, p  hyperconnectivity in the fusiform gyrus, insular and dorsolateral prefrontal cortices, inferior and middle frontal gyri, middle and superior temporal gyri, and posterior cingulate cortex [minimum p-family wise error (FWE) hyperconnectivity in relation to controls in the supramarginal association and dorsal posterior cingulate cortices (p-FWE hyperconnectivity in relation to controls in the supramarginal association and dorsal posterior cingulate cortices (p-FWE = 0.001) and in the anterior prefrontal cortex (42 voxels, p-FWE = 0.047). A negative correlation was found between left caudate connectivity and NSS [p-FWE = 0.044, cluster size ( k ) = 110 voxels]. These findings support the theory of widespread

  6. Barbed channels enhance unidirectional connectivity between neuronal networks cultured on multi electrode arrays

    Science.gov (United States)

    le Feber, Joost; Postma, Wybren; de Weerd, Eddy; Weusthof, Marcel; Rutten, Wim L. C.

    2015-01-01

    Cultured neurons on multi electrode arrays (MEAs) have been widely used to study various aspects of neuronal (network) functioning. A possible drawback of this approach is the lack of structure in these networks. At the single cell level, several solutions have been proposed to enable directed connectivity, and promising results were obtained. At the level of connected sub-populations, a few attempts have been made with promising results. First assessment of the designs' functionality, however, suggested room for further improvement. We designed a two chamber MEA aiming to create a unidirectional connection between the networks in both chambers (“emitting” and “receiving”). To achieve this unidirectionality, all interconnecting channels contained barbs that hindered axon growth in the opposite direction (from receiving to emitting chamber). Visual inspection showed that axons predominantly grew through the channels in the promoted direction. This observation was confirmed by spontaneous activity recordings. Cross-correlation between the signals from two electrodes inside the channels suggested signal propagation at ≈2 m/s from emitting to receiving chamber. Cross-correlation between the firing patterns in both chambers indicated that most correlated activity was initiated in the emitting chamber, which was also reflected by a significantly lower fraction of partial bursts (i.e., a one-chamber-only burst) in the emitting chamber. Finally, electrical stimulation in the emitting chamber induced a fast response in that chamber, and a slower response in the receiving chamber. Stimulation in the receiving chamber evoked a fast response in that chamber, but no response in the emitting chamber. These results confirm the predominantly unidirectional nature of the connecting channels from emitting to receiving chamber. PMID:26578869

  7. 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.

  8. 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.

  9. Altered functional connectivity in default mode network in Internet gaming disorder: Influence of childhood ADHD.

    Science.gov (United States)

    Lee, Deokjong; Lee, Junghan; Lee, Jung Eun; Jung, Young-Chul

    2017-04-03

    Internet gaming disorder (IGD) is a type of behavioral addiction characterized by abnormal executive control, leading to loss of control over excessive gaming. Attention deficit and hyperactivity disorder (ADHD) is one of the most common comorbid disorders in IGD, involving delayed development of the executive control system, which could predispose individuals to gaming addiction. We investigated the influence of childhood ADHD on neural network features of IGD. Resting-state functional magnetic resonance imaging analysis was performed on 44 young, male IGD subjects with and without childhood ADHD and 19 age-matched, healthy male controls. Posterior cingulate cortex (PCC)-seeded connectivity was evaluated to assess abnormalities in default mode network (DMN) connectivity, which is associated with deficits in executive control. IGD subjects without childhood ADHD showed expanded functional connectivity (FC) between DMN-related regions (PCC, medial prefrontal cortex, thalamus) compared with controls. These subjects also exhibited expanded FC between the PCC and brain regions implicated in salience processing (anterior insula, orbitofrontal cortex) compared with IGD subjects with childhood ADHD. IGD subjects with childhood ADHD showed expanded FC between the PCC and cerebellum (crus II), a region involved in executive control. The strength of connectivity between the PCC and cerebellum (crus II) was positively correlated with self-reporting scales reflecting impulsiveness. Individuals with IGD showed altered PCC-based FC, the characteristics of which might be dependent upon history of childhood ADHD. Our findings suggest that altered neural networks for executive control in ADHD would be a predisposition for developing IGD. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. 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.

  11. 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.

  12. Altered effective connectivity of default model brain network underlying amnestic MCI

    Science.gov (United States)

    Yan, Hao; Wang, Yonghui; Tian, Jie

    2012-02-01

    Mild cognitive impairment (MCI) is the transitional, heterogeneous continuum from healthy elderly to Alzheimer's disease (AD). Previous studies have shown that brain functional activity in the default mode network (DMN) is impaired in MCI patients. However, the altered effective connectivity of the DMN in MCI patients remains largely unknown. The present study combined an independent component analysis (ICA) approach with Granger causality analysis (mGCA) to investigate the effective connectivity within the DMN in 12 amnestic MCI patients and 12 age-matched healthy elderly. Compared to the healthy control, the MCI exhibited decreased functional activity in the posterior DMN regions, as well as a trend towards activity increases in anterior DMN regions. Results from mGCA further supported this conclusion that the causal influence projecting to the precuneus/PCC became much weaker in MCI, while stronger interregional interactions emerged within the frontal-parietal cortices. These findings suggested that abnormal effective connectivity within the DMN may elucidate the dysfunctional and compensatory processes in MCI brain networks.

  13. Network science and the effects of music preference on functional brain connectivity: from Beethoven to Eminem.

    Science.gov (United States)

    Wilkins, R W; Hodges, D A; Laurienti, P J; Steen, M; Burdette, J H

    2014-08-28

    Most people choose to listen to music that they prefer or 'like' such as classical, country or rock. Previous research has focused on how different characteristics of music (i.e., classical versus country) affect the brain. Yet, when listening to preferred music--regardless of the type--people report they often experience personal thoughts and memories. To date, understanding how this occurs in the brain has remained elusive. Using network science methods, we evaluated differences in functional brain connectivity when individuals listened to complete songs. We show that a circuit important for internally-focused thoughts, known as the default mode network, was most connected when listening to preferred music. We also show that listening to a favorite song alters the connectivity between auditory brain areas and the hippocampus, a region responsible for memory and social emotion consolidation. Given that musical preferences are uniquely individualized phenomena and that music can vary in acoustic complexity and the presence or absence of lyrics, the consistency of our results was unexpected. These findings may explain why comparable emotional and mental states can be experienced by people listening to music that differs as widely as Beethoven and Eminem. The neurobiological and neurorehabilitation implications of these results are discussed.

  14. Finding multiscale connectivity in our geospace observational system: Network analysis of total electron content

    Science.gov (United States)

    McGranaghan, Ryan M.; Mannucci, Anthony J.; Verkhoglyadova, Olga; Malik, Nishant

    2017-07-01

    We present the first complex network theory-based analysis of high-latitude total electron content (TEC) data, including dependencies on interplanetary magnetic field (IMF) clock angle and hemisphere. We examine several network measures to quantify the spatiotemporal correlation patterns in the TEC data for winter and summer months in 2016. We find that significant structure exists in the correlation patterns, distinguishing the dayside and nightside ionosphere, and specific features in the high latitudes such as the polar cap and auroral oval, including the cusp and ionospheric foot points of magnetospheric boundary layers. These features vary with the IMF, exhibiting a strong dependence on the north-south direction and generally larger variations during the winter months in both hemispheres. Our exploratory results suggest that network analysis of TEC data can be used to study characteristic ionospheric spatial scales at high latitudes, thereby extending the utility of these data. We explore mesoscale and large scale (greater than tens of kilometers and greater than hundreds of kilometers, respectively) as a function of winter/summer season, hemisphere, and IMF direction and conclude that the relative importance of different ionospheric scales is not a constant relationship. Together with an identification of important areas of future work, our findings provide a foundation for the application of network analysis techniques to ionospheric TEC. Our results suggest that network analysis can reveal new physical connections in the ionospheric system.

  15. Emotional intelligence is associated with connectivity within and between resting state networks

    Science.gov (United States)

    Smith, Ryan; Olson, Elizabeth A; Weber, Mareen; Rauch, Scott L; Nickerson, Lisa D

    2017-01-01

    Abstract Emotional intelligence (EI) is defined as an individual’s capacity to accurately perceive, understand, reason about, and regulate emotions, and to apply that information to facilitate thought and achieve goals. Although EI plays an important role in mental health and success in academic, professional and social realms, the neurocircuitry underlying this capacity remains poorly characterized, and no study to date has yet examined the relationship between EI and intrinsic neural network function. Here, in a sample of 54 healthy individuals (28 women, 26 men), we apply independent components analysis (ICA) with dual regression to functional magnetic resonance imaging (fMRI) data acquired while subjects were resting in the scanner to investigate brain circuits (intrinsic resting state networks) whose activity is associated with greater self-reported (i.e. Trait) and objectively measured (i.e. Ability) EI. We show that higher Ability EI, but not Trait EI, is associated with stronger negatively correlated spontaneous fMRI signals between the basal ganglia/limbic network (BGN) and posterior default mode network (DMN), and regions involved in emotional processing and regulation. Importantly, these findings suggest that the functional connectivity within and between intrinsic networks associated with mentation, affective regulation, emotion processing, and reward are strongly related to ability EI. PMID:28981827

  16. Emotional intelligence is associated with connectivity within and between resting state networks.

    Science.gov (United States)

    Killgore, William D S; Smith, Ryan; Olson, Elizabeth A; Weber, Mareen; Rauch, Scott L; Nickerson, Lisa D

    2017-10-01

    Emotional intelligence (EI) is defined as an individual's capacity to accurately perceive, understand, reason about, and regulate emotions, and to apply that information to facilitate thought and achieve goals. Although EI plays an important role in mental health and success in academic, professional and social realms, the neurocircuitry underlying this capacity remains poorly characterized, and no study to date has yet examined the relationship between EI and intrinsic neural network function. Here, in a sample of 54 healthy individuals (28 women, 26 men), we apply independent components analysis (ICA) with dual regression to functional magnetic resonance imaging (fMRI) data acquired while subjects were resting in the scanner to investigate brain circuits (intrinsic resting state networks) whose activity is associated with greater self-reported (i.e. Trait) and objectively measured (i.e. Ability) EI. We show that higher Ability EI, but not Trait EI, is associated with stronger negatively correlated spontaneous fMRI signals between the basal ganglia/limbic network (BGN) and posterior default mode network (DMN), and regions involved in emotional processing and regulation. Importantly, these findings suggest that the functional connectivity within and between intrinsic networks associated with mentation, affective regulation, emotion processing, and reward are strongly related to ability EI. © The Author (2017). Published by Oxford University Press.

  17. Novel leak localization in pressurized pipeline networks using acoustic emission and geometric connectivity

    International Nuclear Information System (INIS)

    Ozevin, Didem; Harding, James

    2012-01-01

    Time dependent aging and instantaneous threats can cause the initiation of damage in the buried and on-ground pipelines. Damage may propagate all through the structural thickness and cause leaking. The leakage detection in oil, water, gas or steam pipeline networks before it becomes structurally instable is important to prevent any catastrophic failures. The leak in pressurized pipelines causes turbulent flow at its location, which generates solid particles or gas bubbles impacting on the pipeline material. The impact energy causes propagating elastic waves that can be detected by the sensors mounted on the pipeline. The method is called Acoustic Emission, which can be used for real time detection of damage caused by unintentional or intentional sources in the pipeline networks. In this paper, a new leak localization approach is proposed for pipeline networks spread in a two dimensional configuration. The approach is to determine arrival time differences using cross correlation function, and introduce the geometric connectivity in order to identify the path that the leak waves should propagate to reach the AE sensors. The leak location in multi-dimensional space is identified in an effective approach using an array of sensors spread on the pipeline network. The approach is successfully demonstrated on laboratory scale polypropylene pipeline networks. - Highlights: ► Leak is identified in 2D using the 1D algorithm and geometric connectivity. ► The methodology is applicable if the source to sensor path is not straight. ► The hit sequence based on average signal level improves the source location. ► The leak localization in viscoelastic materials is high due to attenuation.

  18. Connectivity reliability and topological controllability of infrastructure networks: A comparative assessment

    International Nuclear Information System (INIS)

    Li, Jian; Dueñas-Osorio, Leonardo; Chen, Changkun; Shi, Congling

    2016-01-01

    As infrastructure systems evolve, their design, maintenance, and optimal performance require mature tools from system reliability theory, as well as principles to handle emerging system features, such as controllability. This paper conducts a comparative study of the connectivity reliability (CR) and topological controllability (TC) of infrastructure systems in terms of three aspects: topology, robustness, and node importance. Taking eight city-level power transmission networks and thousands of artificial networks as examples, this paper reveals that a dense and homogeneous network topology is better to satisfy CR and TC requirements, than more common sparse and heterogeneous networks when node attributes are generic. It is observed that the average degree's impact on CR is more significant than on TC, while degree heterogeneity is more significant on TC. When node attributes are accounted for, for generators the reliability-based node importance measure may underestimate some important nodes in terms of TC, and vice versa—an issue not observed for substation nodes. The findings in this paper suggest a potential new direction to enhance reliability-based design by integrating it with emerging controllability-based measures relevant in the future as infrastructure networks increase reliance on information systems. - Highlights: • Compares connectivity reliability (CR) and topological controllability (TC) metrics. • Develops a controllability index and a controllability-based node importance metric. • CR is more sensitive to degree while TC is more sensitive to degree heterogeneity. • CR-based importance measures match TC-based measures for substation nodes. • CR- and TC-based measures are complementary to identify important generator nodes.

  19. Dynamic connectivity modulates local activity in the core regions of the default-mode network.

    Science.gov (United States)

    Tang, Wei; Liu, Hesheng; Douw, Linda; Kramer, Mark A; Eden, Uri T; Hämäläinen, Matti S; Stufflebeam, Steven M

    2017-09-05

    Segregation and integration are distinctive features of large-scale brain activity. Although neuroimaging studies have been unraveling their neural correlates, how integration takes place over segregated modules remains elusive. Central to this problem is the mechanism by which a brain region adjusts its activity according to the influence it receives from other regions. In this study, we explore how dynamic connectivity between two regions affects the neural activity within a participating region. Combining functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) in the same group of subjects, we analyzed resting-state data from the core of the default-mode network. We observed directed influence from the posterior cingulate cortex (PCC) to the anterior cingulate cortex (ACC) in the 10-Hz range. This time-varying influence was associated with the power alteration in the ACC: strong influence corresponded with a decrease of power around 13-16 Hz and an increase of power in the lower (1-7 Hz) and higher (30-55 Hz) ends of the spectrum. We also found that the amplitude of the 30- to 55-Hz activity was coupled to the phase of the 3- to 4-Hz activity in the ACC. These results characterized the local spectral changes associated with network interactions. The specific spectral information both highlights the functional roles of PCC-ACC connectivity in the resting state and provides insights into the dynamic relationship between local activity and coupling dynamics of a network.

  20. Functional Connectivity of Precipitation Networks in the Brazilian Rainforest-Savanna Transition Zone

    Science.gov (United States)

    Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

    2016-12-01

    In the Brazilian rainforest-savanna transition zone, vegetation change has the potential to significantly affect precipitation patterns. Deforestation, in particular, can affect precipitation patterns by increasing land surface albedo, increasing aerosol loading to the atmosphere, changing land surface roughness, and reducing transpiration. Understanding land surface-precipitation couplings in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching and agriculture, hydropower generation, and drinking water management. Simulations suggest complex, scale-dependent interactions between precipitation and land cover. For example, the size and distribution of deforested patches has been found to affect precipitation patterns. We take an empirical approach to ask: (1) what are the dominant spatial and temporal length scales of precipitation coupling in the Brazilian rainforest-savanna transition zone? (2) How do these length scales change over time? (3) How does the connectivity of precipitation change over time? The answers to these questions will help address fundamental questions about the impacts of deforestation on precipitation. We use rain gauge data from 1100 rain gauges intermittently covering the period 1980 - 2013, a period of intensive land cover change in the region. The dominant spatial and temporal length scales of precipitation coupling are resolved using transfer entropy, a metric from information theory. Connectivity of the emergent network of couplings is quantified using network statistics. Analyses using transfer entropy and network statistics reveal the spatial and temporal interdependencies of rainfall events occurring in different parts of the study domain.

  1. Chimeras in leaky integrate-and-fire neural networks: effects of reflecting connectivities

    Science.gov (United States)

    Tsigkri-DeSmedt, Nefeli Dimitra; Hizanidis, Johanne; Schöll, Eckehard; Hövel, Philipp; Provata, Astero

    2017-07-01

    The effects of attracting-nonlocal and reflecting connectivity are investigated in coupled Leaky Integrate-and-Fire (LIF) elements, which model the exchange of electrical signals between neurons. Earlier investigations have demonstrated that repulsive-nonlocal and hierarchical network connectivity can induce complex synchronization patterns and chimera states in systems of coupled oscillators. In the LIF system we show that if the elements are nonlocally linked with positive diffusive coupling on a ring network, the system splits into a number of alternating domains. Half of these domains contain elements whose potential stays near the threshold and they are interrupted by active domains where the elements perform regular LIF oscillations. The active domains travel along the ring with constant velocity, depending on the system parameters. When we introduce reflecting coupling in LIF networks unexpected complex spatio-temporal structures arise. For relatively extensive ranges of parameter values, the system splits into two coexisting domains: one where all elements stay near the threshold and one where incoherent states develop, characterized by multi-leveled mean phase velocity profiles.

  2. Joint multiple fully connected convolutional neural network with extreme learning machine for hepatocellular carcinoma nuc