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

    Science.gov (United States)

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

    2009-01-01

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

  3. Minimum cost connection networks

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Tvede, Mich

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

  4. Network connectivity value.

    Science.gov (United States)

    Dragicevic, Arnaud; Boulanger, Vincent; Bruciamacchie, Max; Chauchard, Sandrine; Dupouey, Jean-Luc; Stenger, Anne

    2017-04-21

    In order to unveil the value of network connectivity, we formalize the construction of ecological networks in forest environments as an optimal control dynamic graph-theoretic problem. The network is based on a set of bioreserves and patches linked by ecological corridors. The node dynamics, built upon the consensus protocol, form a time evolutive Mahalanobis distance weighted by the opportunity costs of timber production. We consider a case of complete graph, where the ecological network is fully connected, and a case of incomplete graph, where the ecological network is partially connected. The results show that the network equilibrium depends on the size of the reception zone, while the network connectivity depends on the environmental compatibility between the ecological areas. Through shadow prices, we find that securing connectivity in partially connected networks is more expensive than in fully connected networks, but should be undertaken when the opportunity costs are significant. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. 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...

  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. 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

  10. Partial anomalous pulmonary venous connection to the superior vena cava.

    Science.gov (United States)

    Aramendi, José I; Rey, Estibaliz; Hamzeh, Gadah; Crespo, Alejandro; Luis, Maite; Voces, Roberto

    2011-04-01

    We describe the surgical technique of reimplantation of the right superior pulmonary vein into the left atrium in 2 patients with partial anomalous pulmonary venous connection to the superior vena cava without atrial septal defect. A right axillary minithoracotomy is done through the fourth intercostal space. The pulmonary vein is detached from its origin in the superior vena cava. This is sutured with 6-0 reabsorbable polydioxanone suture (Ethicon, Somerville, NJ). A lateral clamp is applied to the left atrium, and the pulmonary vein is reimplanted. The patient is extubated in the operating room. Neither cardiopulmonary bypass nor blood transfusion was required. It is simple, safe, and reproducible. Copyright © 2011 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  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. Echocardiographic diagnosis of transposition of the great arteries associated with anomalous pulmonary venous connection

    Directory of Open Access Journals (Sweden)

    Lilian Maria Lopes

    2001-07-01

    Full Text Available We report 2 cases of transposition of the great arteries associated with anomalous pulmonary venous connection emphasizing the clinical findings, the diagnosis, and the evolution of the association. One of the patients had the anomalous pulmonary venous connection in its total infradiaphragmatic form, in the portal system, and the other patient had a partial form, in which an anomalous connection of the left superior lobar vein with the innominate vein existed. At the time of hospital admission, the patients had cyanosis and respiratory distress with clinical findings suggesting transposition of the great arteries. The diagnosis in 1 of the cases, in which the anomalous connection was partial, was established only with echocardiography, without invasive procedures that would represent risk for the patient; in the other case, in which the anomalous connection was total, the malformation was only evidenced with catheterization. The patients underwent surgery for anatomical correction of the heart disease. Only 1 patient had a good outcome.

  13. Connection between recurrence time statistics and anomalous transport

    International Nuclear Information System (INIS)

    Zaslavsky, G.M.; Tippett, M.K.

    1991-01-01

    For a model stationary flow with hexagonal symmetry, the recurrence time statistics are studied. The model has been shown to have a sharp transition from normal to anomalous transport. Here it is shown that this transition is accompanied by a correspondent change of the recurrence time statistics from normal to anomalous. The latter one displays the existence of a power tail. Recurrence time statistics provide a local measurement of anomalous transport that is of practical interest

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Clinical application of MSCT in the diagnosis of anomalous pulmonary venous connection in infants and children

    International Nuclear Information System (INIS)

    Huang Meiping; Liang Changhong; Zeng Hui; Liu Qishun; Zhang Zhonglin; Zhang Jin'e; Huang Biao

    2005-01-01

    Objective: To investigate the clinical usefulness of multislice computed tomography (MSCT) in the diagnosis of anomalous pulmonary venous connection in infants and children. Methods: Retrospective analysis on 20 cases with anomalous pulmonary venous connection was performed using contrast-enhanced MSCT volume scan. The age ranged from 11 days to 12 years. The slice thickness and slice interval were 1.250 mm and 0.625 mm, respectively. Three-dimensional reconstructions were performed with multiplanar reformation (MPR), sliding thin-slabmaximum intensity projection (STS-MIP), volume rendering (VR), and shade-surface displayment (SSD). Ultrasound echocardiography (US) was performed in all patients. Conventional cardiovascular angiography (CAG) was performed in 12 patients, and 14 cased received operation. Results: Of the 20 patients received MSCT, total anomalous pulmonary venous connection was diagnosed in 9, and partial anomalous pulmonary venous connection in 11, including supracardiac type (n=5), cardiac type (n=10), infracardiac type (n=4), and mixed type (n=1). MSCT clearly displayed the number, distribution, and location of anomalous pulmonary venous connection in all patients. Among them, the misdiagnosis by CAG and US were encountered in 3 cases and 10 cases, respectively. The diagnosis by MSCT was compatible with the operative findings in all 14 patients receiving surgery. Conclusion: MSCT has significant value in the diagnosis of pediatric anomalous pulmonary venous connection which may not be detectable with echocardiography or even cardiovascular angiography. (authors)

  19. Utilizing Weak Indicators to Detect Anomalous Behaviors in Networks

    Energy Technology Data Exchange (ETDEWEB)

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

    2018-02-06

    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. Additionally, we study indicators related to the speed of movement of a user based on the physical location of their current and previous logins. This data can be ascertained from the IP addresses of the users, and is likely very similar to the fraud detection schemes regularly utilized by credit card networks to detect anomalous activity. In future work we would look to nd a way to combine these indicators for use as an internal fraud detection system.

  20. 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 ...

  1. 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.

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

    Science.gov (United States)

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

    2015-03-01

    Research in Down syndrome has substantially progressed in the understanding of the effect of gene overexpression at the molecular level, but there is a paucity of information on the ultimate consequences on overall brain functional organization. We have assessed the brain functional status in Down syndrome using functional connectivity MRI. Resting-state whole-brain connectivity degree maps were generated in 20 Down syndrome individuals and 20 control subjects to identify sites showing anomalous synchrony with other areas. A subsequent region-of-interest mapping served to detail the anomalies and to assess their potential contribution to poor adaptive behavior. Down syndrome individuals showed higher regional connectivity in a ventral brain system involving the amygdala/anterior temporal region and the ventral aspect of both the anterior cingulate and frontal cortices. By contrast, lower functional connectivity was identified in dorsal executive networks involving dorsal prefrontal and anterior cingulate cortices and posterior insula. Both functional connectivity increases and decreases contributed to account for patient scoring on adaptive behavior related to communication skills. The data overall suggest a distinctive functional organization with system-specific anomalies associated with reduced adaptive efficiency. Opposite effects were identified on distinct frontal and anterior temporal structures and relative sparing of posterior brain areas, which is generally consistent with Down syndrome cognitive profile. Relevantly, measurable connectivity changes, as a marker of the brain functional anomaly, could have a role in the development of therapeutic strategies addressed to improve the quality of life in Down syndrome individuals. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. Pulmonary vein and atrial wall pathology in human total anomalous pulmonary venous connection

    NARCIS (Netherlands)

    Douglas, Yvonne L.; Jongbloed, Monique R. M.; den Hartog, Wietske C. E.; Bartelings, Margot M.; Bogers, Ad J. J. C.; Ebels, Tjark; DeRuiter, Marco C.; Gittenberger-de Groot, Adriana C.

    2009-01-01

    Background: Normally, the inside of the left atrial (LA) body and pulmonary veins (PVs) is lined by vessel wall tissue covered by myocardium. In total anomalous pulmonary venous connection (TAPVC), no connection of the PVs with the LA body exists. These veins have an increased incidence of PV

  4. Network Connection Management

    CERN Document Server

    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....

  5. 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 ...

  6. 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.

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. Nonrandom network connectivity comes in pairs

    Directory of Open Access Journals (Sweden)

    Felix Z. Hoffmann

    2017-02-01

    Full Text Available Overrepresentation of bidirectional connections in local cortical networks has been repeatedly reported and is a focus of the ongoing discussion of nonrandom connectivity. Here we show in a brief mathematical analysis that in a network in which connection probabilities are symmetric in pairs, Pij = Pji, the occurrences of bidirectional connections and nonrandom structures are inherently linked; an overabundance of reciprocally connected pairs emerges necessarily when some pairs of neurons are more likely to be connected than others. Our numerical results imply that such overrepresentation can also be sustained when connection probabilities are only approximately symmetric.

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

    Science.gov (United States)

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

    2017-11-21

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

  16. Switch-connected HyperX network

    Science.gov (United States)

    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.

  17. 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.

  18. 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.

  19. Synchronization from second order network connectivity statistics

    Directory of Open Access Journals (Sweden)

    Liqiong eZhao

    2011-07-01

    Full Text Available We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks (SONETs, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by a pool and redistribute mechanism. The pooling of many inputs averages out independent fluctuations, amplifying weak correlations in the inputs. With increased chain connections, neurons with many inputs tend to have many outputs. Hence, chains ensure that the amplified correlations in the neurons with many inputs are redistributed throughout the network, enhancing the development of synchrony across the network.

  20. 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.

  1. Synchronization from Second Order Network Connectivity Statistics

    Science.gov (United States)

    Zhao, Liqiong; Beverlin, Bryce; Netoff, Theoden; Nykamp, Duane Q.

    2011-01-01

    We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections, and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by their increasing the effective coupling strength. The decrease of synchrony with convergent connections is primarily due to the resulting heterogeneity in firing rates. PMID:21779239

  2. 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 ...

  3. 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

  4. Ecological connectivity networks in rapidly expanding cities

    Directory of Open Access Journals (Sweden)

    Amal Najihah M. Nor

    2017-06-01

    Full Text Available 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

  5. 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.

  6. Connecting Network Properties of Rapidly Disseminating Epizoonotics

    Science.gov (United States)

    Rivas, Ariel L.; Fasina, Folorunso O.; Hoogesteyn, Almira L.; Konah, Steven N.; Febles, José L.; Perkins, Douglas J.; Hyman, James M.; Fair, Jeanne M.; Hittner, James B.; Smith, Steven D.

    2012-01-01

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

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

    International Nuclear Information System (INIS)

    Oh, Ki Ho; Choo, Ki Seok; Lim, Soo Jin; Lee, Hyoung Doo; Park, Ji Ae; Jo, Min Jung; Sung, Si Chan; Chang, Yun Hee; Jeong, Dong Wook; Kim, Siho

    2009-01-01

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

  8. A case report of partial anomalous pulmonary venous connection and its surgical repair

    Directory of Open Access Journals (Sweden)

    Mandegar MH

    1994-05-01

    Full Text Available This article aim is to introduce a case of PAPVC (partial anomalous pulmonary venous connection. The patient was a 25-year-old women who had dyspnea and palpitation. She expressed no special disease, no past medical history, and no drug usage, but her brother and her aunt had the above-mentioned history. In the physical examination, lungs were clear and the heart had S2 splitting, and there was a systolic murmur in the pulmonary area. Her liver could be palpitated two centimeters below the costal edge, but she didn't have any hepatomegaly. In cardiac catheterism, she had PAPVC, atrial septal defect (ASD, and mitral valve prolapse (MVP. The patient underwent operation had left pulmonary vein was separated from the superior vena cava and anastomosed to the left atrial auricle. By means of the pericardial patch, the left atrium became enlarged and ASD was closed. She was in a good condition after surgery and left the hospital without any complication with a good condition and recovery and had no problem any longer.

  9. Using Hierarchical Temporal Memory for Detecting Anomalous Network Activity

    Science.gov (United States)

    2008-03-01

    warfare, computer network operations, psychological operations, military deception, and operations security, in concert with specified supporting and...you up short—you were subconsciously predicting something else and were surprised by the mismatch” [3]. Notable neurobiologist Horace Barlow of the...malicious network activity is flagged as abnormal . That is, test data should present the N-HTM network with spatial-temporal patterns that do not match 46

  10. Connecting Mobile Users Through Mobile Social Networks

    Directory of Open Access Journals (Sweden)

    Faisal Alkhateeb

    2012-10-01

    Full Text Available Nowadays, social networks become popular with the emerging of web-based social networking services. Recently, several mobile services are developed to connect users to their favourite social networks such as Facebook, Twitter, Flickr, etc. However, these services depends upon the existing web-based social networks. In this paper, we present a mobile service for joining groups across communities. The originality of the work is that the framework of the service allows creating and joining social networks that are self-contained for mobile company servers. The service consists of several sub-services such as users invitation, group finding and others. Users, regardless of their disability, can use the service and its sub-services without the need to create their own accounts on social web sites and thus their own groups. We also propose a privacy control policy for mobile social networks.

  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. Women’s connectivity in extreme networks

    Science.gov (United States)

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

    2016-01-01

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

  13. 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

  14. Network structure shapes spontaneous functional connectivity dynamics.

    Science.gov (United States)

    Shen, Kelly; Hutchison, R Matthew; Bezgin, Gleb; Everling, Stefan; McIntosh, Anthony R

    2015-04-08

    The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture. Copyright © 2015 the authors 0270-6474/15/355579-10$15.00/0.

  15. 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.

  16. 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.

  17. 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.

  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

    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.)

  19. 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.)

  20. Prioritizing connection requests in GMPLS-controlled optical networks

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Koster, A.; Andriolli, N.

    2009-01-01

    We prioritize bidirectional connection requests by combining dynamic connection provisioning with off-line optimization. Results show that the proposed approach decreases wavelength-converter usage, thereby allowing operators to reduce blocking-probably under bulk connection assignment or network...

  1. 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

  2. Anomalous Signal Detection in ELF Band Electromagnetic Wave using Multi-layer Neural Network with Wavelet Decomposition

    Science.gov (United States)

    Itai, Akitoshi; Yasukawa, Hiroshi; Takumi, Ichi; Hata, Masayasu

    It is well known that electromagnetic waves radiated from the earth's crust are useful for predicting earthquakes. We analyze the electromagnetic waves received at the extremely low frequency band of 223Hz. These observed signals contain the seismic radiation from the earth's crust, but also include several undesired signals. Our research focuses on the signal detection technique to identify an anomalous signal corresponding to the seismic radiation in the observed signal. Conventional anomalous signal detections lack a wide applicability due to their assumptions, e.g. the digital data have to be observed at the same time or the same sensor. In order to overcome the limitation related to the observed signal, we proposed the anomalous signals detection based on a multi-layer neural network which is trained by digital data observed during a span of a day. In the neural network approach, training data do not need to be recorded at the same place or the same time. However, some noises, which have a large amplitude, are detected as the anomalous signal. This paper develops a multi-layer neural network to decrease the false detection of the anomalous signal from the electromagnetic wave. The training data for the proposed network is the decomposed signal of the observed signal during several days, since the seismic radiations are often recorded from several days to a couple of weeks. Results show that the proposed neural network is useful to achieve the accurate detection of the anomalous signal that indicates seismic activity.

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

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

    Knowledge Access in Rural Inter-connected Areas Network (KariaNet) - Phase II ... the existing network to include two thematic networks on food security and rural ... Woman conquering male business in Yemen : Waleya's micro-enterprise.

  4. 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.

  5. 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.

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

    DEFF Research Database (Denmark)

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

    hop-count; (3) the connectivity distance, expressing the geographic distance that a message can be propagated in the network on multi-hop paths; (4) the connectivity hops, which corresponds to the number of hops that are necessary to reach all nodes in the connected network. The paper develops...

  7. 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.

  8. 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.

  9. Towards Designing PLC Networks for Ubiquitous Connectivity in Enterprises

    OpenAIRE

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

    2016-01-01

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

  10. 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.

  11. Light Manipulation in Metallic Nanowire Networks with Functional Connectivity

    KAUST Repository

    Galinski, Henning; Fratalocchi, Andrea; Dö beli, Max; Capasso, Federico

    2016-01-01

    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

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

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

    Knowledge Access in Rural Inter-connected Areas Network (KariaNet) - Phase II ... poor by sharing innovations, best practices and indigenous knowledge using ... A third thematic network - on knowledge management strategies - will play an ...

  13. 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.

  14. 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.

  15. Correlation connection between the anomalous magnetic and gravitational fields for regions with different types of the Earth's crust

    International Nuclear Information System (INIS)

    Lugovenko, V.N.; Pronin, V.P.; Kosheleva, L.V.

    1989-01-01

    A method for the correlation analysis of anomalous geophysical fields at different survey altitudes is proposed. The joint correlation analysis is performed for anomalous magnetic and gravitational fields for regions with different types of the Earth's crust. (author)

  16. Altered network hub connectivity after acute LSD administration

    Directory of Open Access Journals (Sweden)

    Felix Müller

    Full Text Available LSD is an ambiguous substance, said to mimic psychosis and to improve mental health in people suffering from anxiety and depression. Little is known about the neuronal correlates of altered states of consciousness induced by this substance. Limited previous studies indicated profound changes in functional connectivity of resting state networks after the administration of LSD. The current investigation attempts to replicate and extend those findings in an independent sample. In a double-blind, randomized, cross-over study, 100 μg LSD and placebo were orally administered to 20 healthy participants. Resting state brain activity was assessed by functional magnetic resonance imaging. Within-network and between-network connectivity measures of ten established resting state networks were compared between drug conditions. Complementary analysis were conducted using resting state networks as sources in seed-to-voxel analyses. Acute LSD administration significantly decreased functional connectivity within visual, sensorimotor and auditory networks and the default mode network. While between-network connectivity was widely increased and all investigated networks were affected to some extent, seed-to-voxel analyses consistently indicated increased connectivity between networks and subcortical (thalamus, striatum and cortical (precuneus, anterior cingulate cortex hub structures. These latter observations are consistent with findings on the importance of hubs in psychopathological states, especially in psychosis, and could underlay therapeutic effects of hallucinogens as proposed by a recent model. Keywords: LSD, fMRI, Functional connectivity, Networks, Hubs

  17. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1995-01-01

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

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

    DEFF Research Database (Denmark)

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

    2011-01-01

    distance, expressing the geographic distance that a message can be propagated in the network on multi-hop paths; (4) the connectivity hops, which corresponds to the number of hops that are necessary to reach all nodes in the connected network. The paper develops analytic expressions for the distributions...

  20. 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.…

  1. Attractor neural networks with resource-efficient synaptic connectivity

    Science.gov (United States)

    Pehlevan, Cengiz; Sengupta, Anirvan

    Memories are thought to be stored in the attractor states of recurrent neural networks. Here we explore how resource constraints interplay with memory storage function to shape synaptic connectivity of attractor networks. We propose that given a set of memories, in the form of population activity patterns, the neural circuit choses a synaptic connectivity configuration that minimizes a resource usage cost. We argue that the total synaptic weight (l1-norm) in the network measures the resource cost because synaptic weight is correlated with synaptic volume, which is a limited resource, and is proportional to neurotransmitter release and post-synaptic current, both of which cost energy. Using numerical simulations and replica theory, we characterize optimal connectivity profiles in resource-efficient attractor networks. Our theory explains several experimental observations on cortical connectivity profiles, 1) connectivity is sparse, because synapses are costly, 2) bidirectional connections are overrepresented and 3) are stronger, because attractor states need strong recurrence.

  2. 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.

  3. Dual pathology causing severe pulmonary hypertension following surgical repair of total anomalous pulmonary venous connection: Successful outcome following serial transcatheter interventions.

    Science.gov (United States)

    Jain, Shreepal; Bachani, Neeta S; Pinto, Robin J; Dalvi, Bharat V

    2018-01-01

    Surgical repair of total anomalous pulmonary venous connection (TAPVC) can be complicated by the development of pulmonary venous stenosis later on. In addition, the vertical vein, if left unligated, can remain patent and lead to hemodynamically significant left to right shunting. We report an infant who required transcatheter correction of both these problems after surgical repair of TAPVC.

  4. Dual pathology causing severe pulmonary hypertension following surgical repair of total anomalous pulmonary venous connection: Successful outcome following serial transcatheter interventions

    Directory of Open Access Journals (Sweden)

    Shreepal Jain

    2018-01-01

    Full Text Available Surgical repair of total anomalous pulmonary venous connection (TAPVC can be complicated by the development of pulmonary venous stenosis later on. In addition, the vertical vein, if left unligated, can remain patent and lead to hemodynamically significant left to right shunting. We report an infant who required transcatheter correction of both these problems after surgical repair of TAPVC.

  5. 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.

  6. 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.

  7. Enabling Research Network Connectivity to Clouds with Virtual Router Technology

    Science.gov (United States)

    Seuster, R.; Casteels, K.; Leavett-Brown, CR; Paterson, M.; Sobie, RJ

    2017-10-01

    The use of opportunistic cloud resources by HEP experiments has significantly increased over the past few years. Clouds that are owned or managed by the HEP community are connected to the LHCONE network or the research network with global access to HEP computing resources. Private clouds, such as those supported by non-HEP research funds are generally connected to the international research network; however, commercial clouds are either not connected to the research network or only connect to research sites within their national boundaries. Since research network connectivity is a requirement for HEP applications, we need to find a solution that provides a high-speed connection. We are studying a solution with a virtual router that will address the use case when a commercial cloud has research network connectivity in a limited region. In this situation, we host a virtual router in our HEP site and require that all traffic from the commercial site transit through the virtual router. Although this may increase the network path and also the load on the HEP site, it is a workable solution that would enable the use of the remote cloud for low I/O applications. We are exploring some simple open-source solutions. In this paper, we present the results of our studies and how it will benefit our use of private and public clouds for HEP computing.

  8. 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

  9. 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.

  10. 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.

  11. Connectivity patterns in cognitive control networks predict naturalistic multitasking ability.

    Science.gov (United States)

    Wen, Tanya; Liu, De-Cyuan; Hsieh, Shulan

    2018-06-01

    Multitasking is a fundamental aspect of everyday life activities. To achieve a complex, multi-component goal, the tasks must be subdivided into sub-tasks and component steps, a critical function of prefrontal networks. The prefrontal cortex is considered to be organized in a cascade of executive processes from the sensorimotor to anterior prefrontal cortex, which includes execution of specific goal-directed action, to encoding and maintaining task rules, and finally monitoring distal goals. In the current study, we used a virtual multitasking paradigm to tap into real-world performance and relate it to each individual's resting-state functional connectivity in fMRI. While did not find any correlation between global connectivity of any of the major networks with multitasking ability, global connectivity of the lateral prefrontal cortex (LPFC) was predictive of multitasking ability. Further analysis showed that multivariate connectivity patterns within the sensorimotor network (SMN), and between-network connectivity of the frontoparietal network (FPN) and dorsal attention network (DAN), predicted individual multitasking ability and could be generalized to novel individuals. Together, these results support previous research that prefrontal networks underlie multitasking abilities and show that connectivity patterns in the cascade of prefrontal networks may explain individual differences in performance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  12. Chimera states in networks of logistic maps with hierarchical connectivities

    Science.gov (United States)

    zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

    2018-04-01

    Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.

  13. 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.

  14. Connecting Land-Based Networks to Ships

    Science.gov (United States)

    2013-06-01

    multipoint wireless broadband systems, and WiMAX networks were initially deployed for fixed and nomadic (portable) applications. These standards...CAPABILITIES OF SHIP-TO-SHORE COMMUNICATIONS A. US Navy Automated Digital Network System (ADNS) The U.S. Navy’s Automated Digital Network System (ADNS...submit digitally any necessary documents to the terminal operators, contact their logistics providers, access tidal information and receive

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. Connectivities and synchronous firing in cortical neuronal networks

    International Nuclear Information System (INIS)

    Jia, L.C.; Sano, M.; Lai, P.-Y.; Chan, C.K.

    2004-01-01

    Network connectivities (k-bar) of cortical neural cultures are studied by synchronized firing and determined from measured correlations between fluorescence intensities of firing neurons. The bursting frequency (f) during synchronized firing of the networks is found to be an increasing function of k-bar. With f taken to be proportional to k-bar, a simple random model with a k-bar dependent connection probability p(k-bar) has been constructed to explain our experimental findings successfully

  2. Social network of an internationally connected nurse leader.

    Science.gov (United States)

    Benton, David

    2016-03-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

  4. Population coding in sparsely connected networks of noisy neurons.

    Science.gov (United States)

    Tripp, Bryan P; Orchard, Jeff

    2012-01-01

    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 behavior. 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 modeled a sheet of cortical neurons with sparse, primarily local connections, and found that a network with this structure could encode multiple internal state variables with high signal-to-noise ratio. However, we were unable to create high-fidelity networks by instantiating connections at random according to spatial connection probabilities. In our models, high-fidelity networks required additional structure, with higher cluster factors and correlations between the inputs to nearby neurons.

  5. Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

    OpenAIRE

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

    2016-01-01

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

  6. Networks with fourfold connectivity in two dimensions.

    Science.gov (United States)

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

    2003-01-01

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

  7. 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

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

    Science.gov (United States)

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

    2015-12-01

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

  9. 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...

  10. Preliminary findings of altered functional connectivity of the default mode network linked to functional outcomes one year after pediatric traumatic brain injury.

    Science.gov (United States)

    Stephens, Jaclyn A; Salorio, Cynthia F; Barber, Anita D; Risen, Sarah R; Mostofsky, Stewart H; Suskauer, Stacy J

    2017-07-10

    This study examined functional connectivity of the default mode network (DMN) and examined brain-behavior relationships in a pilot cohort of children with chronic mild to moderate traumatic brain injury (TBI). Compared to uninjured peers, children with TBI demonstrated less anti-correlated functional connectivity between DMN and right Brodmann Area 40 (BA 40). In children with TBI, more anomalous less anti-correlated) connectivity between DMN and right BA 40 was linked to poorer performance on response inhibition tasks. Collectively, these preliminary findings suggest that functional connectivity between DMN and BA 40 may relate to longterm functional outcomes in chronic pediatric TBI.

  11. 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.

  12. Structural Connectivity Networks of Transgender People

    NARCIS (Netherlands)

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

    2015-01-01

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

  13. 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.

  14. Hydraulic Stability of Heat Networks for Connection of New Consumers

    Science.gov (United States)

    Seminenko, A. S.; Sheremet, E. O.; Gushchin, S. V.; Elistratova, J. V.; Kireev, V. M.

    2018-03-01

    Nowadays due to intensive urban construction, there is a need to connect new consumers to existing heating networks. Often the connection of new consumers leads to a hydraulic misalignment of the network, which in turn affects supplying existing consumers with heat. In order to minimize the possibility of misalignment, appropriate recommendations are needed that can be obtained during the research. In the article, the authors carried out a required experiment aimed at revealing the influence of the new consumers’ connection on the hydraulic stability of the entire network. The result of the research is relevant recommendations that will be useful for engineering specialists both for the design of new networks and the reconstruction of the old ones.

  15. 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.

  16. Connections between classical and parametric network entropies.

    Directory of Open Access Journals (Sweden)

    Matthias Dehmer

    Full Text Available This paper explores relationships between classical and parametric measures of graph (or network complexity. Classical measures are based on vertex decompositions induced by equivalence relations. Parametric measures, on the other hand, are constructed by using information functions to assign probabilities to the vertices. The inequalities established in this paper relating classical and parametric measures lay a foundation for systematic classification of entropy-based measures of graph complexity.

  17. 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.

  18. 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.

  19. Brain intrinsic network connectivity in individuals with frequent tanning behavior.

    Science.gov (United States)

    Ketcherside, Ariel; Filbey, Francesca M; Aubert, Pamela M; Seibyl, John P; Price, Julianne L; Adinoff, Bryon

    2018-05-01

    Emergent studies suggest a bidirectional relationship between brain functioning and the skin. This neurocutaneous connection may be responsible for the reward response to tanning and, thus, may contribute to excessive tanning behavior. To date, however, this association has not yet been examined. To explore whether intrinsic brain functional connectivity within the default mode network (DMN) is related to indoor tanning behavior. Resting state functional connectivity (rsFC) was obtained in twenty adults (16 females) with a history of indoor tanning. Using a seed-based [(posterior cingulate cortex (PCC)] approach, the relationship between tanning severity and FC strength was assessed. Tanning severity was measured with symptom count from the Structured Clinical Interview for Tanning Abuse and Dependence (SITAD) and tanning intensity (lifetime indoor tanning episodes/years tanning). rsFC strength between the PCC and other DMN regions (left globus pallidus, left medial frontal gyrus, left superior frontal gyrus) is positively correlated with tanning symptom count. rsFC strength between the PCC and salience network regions (right anterior cingulate cortex, left inferior parietal lobe, left inferior temporal gyrus) is correlated with tanning intensity. Greater connectivity between tanning severity and DMN and salience network connectivity suggests that heightened self-awareness of salient stimuli may be a mechanism that underlies frequent tanning behavior. These findings add to the growing evidence of brain-skin connection and reflect dysregulation in the reward processing networks in those with frequent tanning.

  20. 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.

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

    International Nuclear Information System (INIS)

    Pleym, Anngjerd; Mogstad, Olve

    2002-01-01

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

  2. Path connectivity based spectral defragmentation in flexible bandwidth networks.

    Science.gov (United States)

    Wang, Ying; Zhang, Jie; Zhao, Yongli; Zhang, Jiawei; Zhao, Jie; Wang, Xinbo; Gu, Wanyi

    2013-01-28

    Optical networks with flexible bandwidth provisioning have become a very promising networking architecture. It enables efficient resource utilization and supports heterogeneous bandwidth demands. In this paper, two novel spectrum defragmentation approaches, i.e. Maximum Path Connectivity (MPC) algorithm and Path Connectivity Triggering (PCT) algorithm, are proposed based on the notion of Path Connectivity, which is defined to represent the maximum variation of node switching ability along the path in flexible bandwidth networks. A cost-performance-ratio based profitability model is given to denote the prons and cons of spectrum defragmentation. We compare these two proposed algorithms with non-defragmentation algorithm in terms of blocking probability. Then we analyze the differences of defragmentation profitability between MPC and PCT algorithms.

  3. Spreading Sequence System for Full Connectivity Relay Network

    Science.gov (United States)

    Kwon, Hyuck M. (Inventor); Yang, Jie (Inventor); Pham, Khanh D. (Inventor)

    2018-01-01

    Fully connected uplink and downlink fully connected relay network systems using pseudo-noise spreading and despreading sequences subjected to maximizing the signal-to-interference-plus-noise ratio. The relay network systems comprise one or more transmitting units, relays, and receiving units connected via a communication network. The transmitting units, relays, and receiving units each may include a computer for performing the methods and steps described herein and transceivers for transmitting and/or receiving signals. The computer encodes and/or decodes communication signals via optimum adaptive PN sequences found by employing Cholesky decompositions and singular value decompositions (SVD). The PN sequences employ channel state information (CSI) to more effectively and more securely computing the optimal sequences.

  4. Connectivity effects in the dynamic model of neural networks

    International Nuclear Information System (INIS)

    Choi, J; Choi, M Y; Yoon, B-G

    2009-01-01

    We study, via extensive Monte Carlo calculations, the effects of connectivity in the dynamic model of neural networks, to observe that the Mattis-state order parameter increases with the number of coupled neurons. Such effects appear more pronounced when the average number of connections is increased by introducing shortcuts in the network. In particular, the power spectra of the order parameter at stationarity are found to exhibit power-law behavior, depending on how the average number of connections is increased. The cluster size distribution of the 'memory-unmatched' sites also follows a power law and possesses strong correlations with the power spectra. It is further observed that the distribution of waiting times for neuron firing fits roughly to a power law, again depending on how neuronal connections are increased

  5. 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.

  6. Periodic Hydraulic Testing for Discerning Fracture Network Connections

    Science.gov (United States)

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

    2015-12-01

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

  7. 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

  8. 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

  9. Population coding in sparsely connected networks of noisy neurons

    OpenAIRE

    Tripp, Bryan P.; Orchard, Jeff

    2012-01-01

    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 be...

  10. 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.

  11. Optimal topology to minimizing congestion in connected communication complex network

    Science.gov (United States)

    Benyoussef, M.; Ez-Zahraouy, H.; Benyoussef, A.

    In this paper, a new model of the interdependent complex network is proposed, based on two assumptions that (i) the capacity of a node depends on its degree, and (ii) the traffic load depends on the distribution of the links in the network. Based on these assumptions, the presented model proposes a method of connection not based on the node having a higher degree but on the region containing hubs. It is found that the final network exhibits two kinds of degree distribution behavior, depending on the kind and the way of the connection. This study reveals a direct relation between network structure and traffic flow. It is found that pc the point of transition between the free flow and the congested phase depends on the network structure and the degree distribution. Moreover, this new model provides an improvement in the traffic compared to the results found in a single network. The same behavior of degree distribution found in a BA network and observed in the real world is obtained; except for this model, the transition point between the free phase and congested phase is much higher than the one observed in a network of BA, for both static and dynamic protocols.

  12. Connectivity, excitability and activity patterns in neuronal networks

    International Nuclear Information System (INIS)

    Le Feber, Joost; Stoyanova, Irina I; Chiappalone, Michela

    2014-01-01

    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 (CFP i,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 CFP i,j with the autocorrelation of i (i.e. CFP i,i ), to obtain the single pulse response (SPR i,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. (papers)

  13. Brain network connectivity in individuals with schizophrenia and their siblings.

    Science.gov (United States)

    Repovs, Grega; Csernansky, John G; Barch, Deanna M

    2011-05-15

    Research on brain activity in schizophrenia has shown that changes in the function of any single region cannot explain the range of cognitive and affective impairments in this illness. Rather, neural circuits that support sensory, cognitive, and emotional processes are now being investigated as substrates for cognitive and affective impairments in schizophrenia, a shift in focus consistent with long-standing hypotheses about schizophrenia as a disconnection syndrome. Our goal was to further examine alterations in functional connectivity within and between the default mode network and three cognitive control networks (frontal-parietal, cingulo-opercular, and cerebellar) as a basis for such impairments. Resting state functional magnetic resonance imaging was collected from 40 individuals with DSM-IV-TR schizophrenia, 31 siblings of individuals with schizophrenia, 15 healthy control subjects, and 18 siblings of healthy control subjects while they rested quietly with their eyes closed. Connectivity metrics were compared between patients and control subjects for both within- and between-network connections and were used to predict clinical symptoms and cognitive function. Individuals with schizophrenia showed reduced distal and somewhat enhanced local connectivity between the cognitive control networks compared with control subjects. Additionally, greater connectivity between the frontal-parietal and cerebellar regions was robustly predictive of better cognitive performance across groups and predictive of fewer disorganization symptoms among patients. These results are consistent with the hypothesis that impairments of executive function and cognitive control result from disruption in the coordination of activity across brain networks and additionally suggest that these might reflect impairments in normal pattern of brain connectivity development. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  14. Node-based measures of connectivity in genetic networks.

    Science.gov (United States)

    Koen, Erin L; Bowman, Jeff; Wilson, Paul J

    2016-01-01

    At-site environmental conditions can have strong influences on genetic connectivity, and in particular on the immigration and settlement phases of dispersal. However, at-site processes are rarely explored in landscape genetic analyses. Networks can facilitate the study of at-site processes, where network nodes are used to model site-level effects. We used simulated genetic networks to compare and contrast the performance of 7 node-based (as opposed to edge-based) genetic connectivity metrics. We simulated increasing node connectivity by varying migration in two ways: we increased the number of migrants moving between a focal node and a set number of recipient nodes, and we increased the number of recipient nodes receiving a set number of migrants. We found that two metrics in particular, the average edge weight and the average inverse edge weight, varied linearly with simulated connectivity. Conversely, node degree was not a good measure of connectivity. We demonstrated the use of average inverse edge weight to describe the influence of at-site habitat characteristics on genetic connectivity of 653 American martens (Martes americana) in Ontario, Canada. We found that highly connected nodes had high habitat quality for marten (deep snow and high proportions of coniferous and mature forest) and were farther from the range edge. We recommend the use of node-based genetic connectivity metrics, in particular, average edge weight or average inverse edge weight, to model the influences of at-site habitat conditions on the immigration and settlement phases of dispersal. © 2015 John Wiley & Sons Ltd.

  15. 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

  16. 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

  17. 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.

  18. 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.

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

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

    Knowledge Access in Rural Inter-connected Areas Network (KariaNet) - Phase II ... and indigenous knowledge using information and communication technologies (ICTs) ... for research proposals on the aforementioned topics, action-research projects, ... Evaluating knowledge-sharing methods to improve land utilization and ...

  20. Quantifying Discrete Fracture Network Connectivity in Hydraulic Fracturing Stimulation

    Science.gov (United States)

    Urbancic, T.; Ardakani, E. P.; Baig, A.

    2017-12-01

    Hydraulic fracture stimulations generally result in microseismicity that is associated with the activation or extension of pre-existing microfractures and discontinuities. Microseismic events acquired under 3D downhole sensor coverage provide accurate event locations outlining hydraulic fracture growth. Combined with source characteristics, these events provide a high quality input for seismic moment tensor inversion and eventually constructing the representative discrete fracture network (DFN). In this study, we investigate the strain and stress state, identified fracture orientation, and DFN connectivity and performance for example stages in a multistage perf and plug completion in a North American shale play. We use topology, the familiar concept in many areas of structural geology, to further describe the relationships between the activated fractures and their effectiveness in enhancing permeability. We explore how local perturbations of stress state lead to the activation of different fractures sets and how that effects the DFN interaction and complexity. In particular, we observe that a more heterogeneous stress state shows a higher percentage of sub-horizontal fractures or bedding plane slips. Based on topology, the fractures are evenly distributed from the injection point, with decreasing numbers of connections by distance. The dimensionless measure of connection per branch and connection per line are used for quantifying the DFN connectivity. In order to connect the concept of connectivity back to productive volume and stimulation efficiency, the connectivity is compared with the character of deformation in the reservoir as deduced from the collective behavior of microseismicity using robustly determined source parameters.

  1. 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.

  2. Quantifying the connectivity of scale-free and biological networks

    Energy Technology Data Exchange (ETDEWEB)

    Shiner, J.S. E-mail: shiner@alumni.duke.edu; Davison, Matt E-mail: mdavison@uwo.ca

    2004-07-01

    Scale-free and biological networks follow a power law distribution p{sub k}{proportional_to}k{sup -{alpha}} for the probability that a node is connected to k other nodes; the corresponding ranges for {alpha} (biological: 1<{alpha}<2; scale-free: 2<{alpha}{<=}3) yield a diverging variance for the connectivity k and lack of predictability for the average connectivity. Predictability can be achieved with the Renyi, Tsallis and Landsberg-Vedral extended entropies and corresponding 'disorders' for correctly chosen values of the entropy index q. Escort distributions p{sub k}{proportional_to}k{sup -{alpha}}{sup q} with q>3/{alpha} also yield a nondiverging variance and predictability. It is argued that the Tsallis entropies may be the appropriate quantities for the study of scale-free and biological networks.

  3. 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.

  4. 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.

  5. Brain Connectivity Networks and the Aesthetic Experience of Music.

    Science.gov (United States)

    Reybrouck, Mark; Vuust, Peter; Brattico, Elvira

    2018-06-12

    Listening to music is above all a human experience, which becomes an aesthetic experience when an individual immerses himself/herself in the music, dedicating attention to perceptual-cognitive-affective interpretation and evaluation. The study of these processes where the individual perceives, understands, enjoys and evaluates a set of auditory stimuli has mainly been focused on the effect of music on specific brain structures, as measured with neurophysiology and neuroimaging techniques. The very recent application of network science algorithms to brain research allows an insight into the functional connectivity between brain regions. These studies in network neuroscience have identified distinct circuits that function during goal-directed tasks and resting states. We review recent neuroimaging findings which indicate that music listening is traceable in terms of network connectivity and activations of target regions in the brain, in particular between the auditory cortex, the reward brain system and brain regions active during mind wandering.

  6. 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.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    Li Liu

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

  9. 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

  10. 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

  11. 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)

  12. Intrinsic connectivity of neural networks in the awake rabbit.

    Science.gov (United States)

    Schroeder, Matthew P; Weiss, Craig; Procissi, Daniel; Disterhoft, John F; Wang, Lei

    2016-04-01

    The way in which the brain is functionally connected into different networks has emerged as an important research topic in order to understand normal neural processing and signaling. Since some experimental manipulations are difficult or unethical to perform in humans, animal models are better suited to investigate this topic. Rabbits are a species that can undergo MRI scanning in an awake and conscious state with minimal preparation and habituation. In this study, we characterized the intrinsic functional networks of the resting New Zealand White rabbit brain using BOLD fMRI data. Group independent component analysis revealed seven networks similar to those previously found in humans, non-human primates and/or rodents including the hippocampus, default mode, cerebellum, thalamus, and visual, somatosensory, and parietal cortices. For the first time, the intrinsic functional networks of the resting rabbit brain have been elucidated demonstrating the rabbit's applicability as a translational animal model. Without the confounding effects of anesthetics or sedatives, future experiments may employ rabbits to understand changes in neural connectivity and brain functioning as a result of experimental manipulation (e.g., temporary or permanent network disruption, learning-related changes, and drug administration). Copyright © 2016 Elsevier Inc. All rights reserved.

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

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano

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

  14. The value of less connected agents in Boolean networks

    Science.gov (United States)

    Epstein, Daniel; Bazzan, Ana L. C.

    2013-11-01

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

  15. 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.

  16. 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

  17. Measuring symmetry, asymmetry and randomness in neural network connectivity.

    Directory of Open Access Journals (Sweden)

    Umberto Esposito

    Full Text Available Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity.

  18. Measuring symmetry, asymmetry and randomness in neural network connectivity.

    Science.gov (United States)

    Esposito, Umberto; Giugliano, Michele; van Rossum, Mark; Vasilaki, Eleni

    2014-01-01

    Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity.

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

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2004-07-01

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

  20. 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...

  1. Stability of a neural network model with small-world connections

    International Nuclear Information System (INIS)

    Li Chunguang; Chen Guanrong

    2003-01-01

    Small-world networks are highly clustered networks with small distances among the nodes. There are many biological neural networks that present this kind of connection. There are no special weightings in the connections of most existing small-world network models. However, this kind of simply connected model cannot characterize biological neural networks, in which there are different weights in synaptic connections. In this paper, we present a neural network model with weighted small-world connections and further investigate the stability of this model

  2. 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.

  3. 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.

  4. Understanding magnetotransport signatures in networks of connected permalloy nanowires

    Science.gov (United States)

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

    2017-02-01

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

  5. 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.

  6. 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.

  7. 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.

  8. Atomoxetine Enhances Connectivity of Prefrontal Networks in Parkinson's Disease.

    Science.gov (United States)

    Borchert, Robin J; Rittman, Timothy; Passamonti, Luca; Ye, Zheng; Sami, Saber; Jones, Simon P; Nombela, Cristina; Vázquez Rodríguez, Patricia; Vatansever, Deniz; Rae, Charlotte L; Hughes, Laura E; Robbins, Trevor W; Rowe, James B

    2016-07-01

    Cognitive impairment is common in Parkinson's disease (PD), but often not improved by dopaminergic treatment. New treatment strategies targeting other neurotransmitter deficits are therefore of growing interest. Imaging the brain at rest ('task-free') provides the opportunity to examine the impact of a candidate drug on many of the brain networks that underpin cognition, while minimizing task-related performance confounds. We test this approach using atomoxetine, a selective noradrenaline reuptake inhibitor that modulates the prefrontal cortical activity and can facilitate some executive functions and response inhibition. Thirty-three patients with idiopathic PD underwent task-free fMRI. Patients were scanned twice in a double-blind, placebo-controlled crossover design, following either placebo or 40-mg oral atomoxetine. Seventy-six controls were scanned once without medication to provide normative data. Seed-based correlation analyses were used to measure changes in functional connectivity, with the right inferior frontal gyrus (IFG) a critical region for executive function. Patients on placebo had reduced connectivity relative to controls from right IFG to dorsal anterior cingulate cortex and to left IFG and dorsolateral prefrontal cortex. Atomoxetine increased connectivity from the right IFG to the dorsal anterior cingulate. In addition, the atomoxetine-induced change in connectivity from right IFG to dorsolateral prefrontal cortex was proportional to the change in verbal fluency, a simple index of executive function. The results support the hypothesis that atomoxetine may restore prefrontal networks related to executive functions. We suggest that task-free imaging can support translational pharmacological studies of new drug therapies and provide evidence for engagement of the relevant neurocognitive systems.

  9. 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.

  10. 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.

  11. Connection adaption for control of networked mobile chaotic agents.

    Science.gov (United States)

    Zhou, Jie; Zou, Yong; Guan, Shuguang; Liu, Zonghua; Xiao, Gaoxi; Boccaletti, S

    2017-11-22

    In this paper, we propose a strategy for the control of mobile chaotic oscillators by adaptively rewiring connections between nearby agents with local information. In contrast to the dominant adaptive control schemes where coupling strength is adjusted continuously according to the states of the oscillators, our method does not request adaption of coupling strength. As the resulting interaction structure generated by this proposed strategy is strongly related to unidirectional chains, by investigating synchronization property of unidirectional chains, we reveal that there exists a certain coupling range in which the agents could be controlled regardless of the length of the chain. This feature enables the adaptive strategy to control the mobile oscillators regardless of their moving speed. Compared with existing adaptive control strategies for networked mobile agents, our proposed strategy is simpler for implementation where the resulting interaction networks are kept unweighted at all time.

  12. 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......This paper assess field measurements, as part of the investigation of the suitability of cellular networks for providing connectivity to UAVs (unmanned aerial vehicles). Evaluation is done by means of field measurements obtained in a rural environment in Denmark with an airbone UAV......, downlink (DL) SINR levels obtained during flight measurements are also presented. An important result obtained from the measurents reveal that there is a height-related DL SINR degradation. Three main sources of uncertainty on the pathloss model that could be responsible for the SINR degradation are also...

  13. 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.

  14. Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

    Science.gov (United States)

    Fukushima, Makoto; Betzel, Richard F; He, Ye; van den Heuvel, Martijn P; Zuo, Xi-Nian; Sporns, Olaf

    2018-04-01

    Structural white matter connections are thought to facilitate integration of neural information across functionally segregated systems. Recent studies have demonstrated that changes in the balance between segregation and integration in brain networks can be tracked by time-resolved functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data and that fluctuations between segregated and integrated network states are related to human behavior. However, how these network states relate to structural connectivity is largely unknown. To obtain a better understanding of structural substrates for these network states, we investigated how the relationship between structural connectivity, derived from diffusion tractography, and functional connectivity, as measured by rs-fMRI, changes with fluctuations between segregated and integrated states in the human brain. We found that the similarity of edge weights between structural and functional connectivity was greater in the integrated state, especially at edges connecting the default mode and the dorsal attention networks. We also demonstrated that the similarity of network partitions, evaluated between structural and functional connectivity, increased and the density of direct structural connections within modules in functional networks was elevated during the integrated state. These results suggest that, when functional connectivity exhibited an integrated network topology, structural connectivity and functional connectivity were more closely linked to each other and direct structural connections mediated a larger proportion of neural communication within functional modules. Our findings point out the possibility of significant contributions of structural connections to integrative neural processes underlying human behavior.

  15. Oscillations, networks, and their development: MEG connectivity changes with age.

    Science.gov (United States)

    Schäfer, Carmen B; Morgan, Benjamin R; Ye, Annette X; Taylor, Margot J; Doesburg, Sam M

    2014-10-01

    Magnetoencephalographic (MEG) investigations of inter-regional amplitude correlations have yielded new insights into the organization and neurophysiology of resting-state networks (RSNs) first identified using fMRI. Inter-regional MEG amplitude correlations in adult RSNs have been shown to be most prominent in alpha and beta frequency ranges and to express strong congruence with RSN topologies found using fMRI. Despite such advances, little is known about how oscillatory connectivity in RSNs develops throughout childhood and adolescence. This study used a novel fMRI-guided MEG approach to investigate the maturation of resting-state amplitude correlations in physiologically relevant frequency ranges within and among six RSNs in 59 participants, aged 6-34 years. We report age-related increases in inter-regional amplitude correlations that were largest in alpha and beta frequency bands. In contrast to fMRI reports, these changes were observed both within and between the various RSNs analyzed. Our results provide the first evidence of developmental changes in spontaneous neurophysiological connectivity in source-resolved RSNs, which indicate increasing integration within and among intrinsic functional brain networks throughout childhood, adolescence, and early adulthood. Copyright © 2014 Wiley Periodicals, Inc.

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

    Science.gov (United States)

    Djurfeldt, Mikael

    2012-07-01

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

  17. 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.

  18. Intercluster Connection in Cognitive Wireless Mesh Networks Based on Intelligent Network Coding

    Science.gov (United States)

    Chen, Xianfu; Zhao, Zhifeng; Jiang, Tao; Grace, David; Zhang, Honggang

    2009-12-01

    Cognitive wireless mesh networks have great flexibility to improve spectrum resource utilization, within which secondary users (SUs) can opportunistically access the authorized frequency bands while being complying with the interference constraint as well as the QoS (Quality-of-Service) requirement of primary users (PUs). In this paper, we consider intercluster connection between the neighboring clusters under the framework of cognitive wireless mesh networks. Corresponding to the collocated clusters, data flow which includes the exchanging of control channel messages usually needs four time slots in traditional relaying schemes since all involved nodes operate in half-duplex mode, resulting in significant bandwidth efficiency loss. The situation is even worse at the gateway node connecting the two colocated clusters. A novel scheme based on network coding is proposed in this paper, which needs only two time slots to exchange the same amount of information mentioned above. Our simulation shows that the network coding-based intercluster connection has the advantage of higher bandwidth efficiency compared with the traditional strategy. Furthermore, how to choose an optimal relaying transmission power level at the gateway node in an environment of coexisting primary and secondary users is discussed. We present intelligent approaches based on reinforcement learning to solve the problem. Theoretical analysis and simulation results both show that the intelligent approaches can achieve optimal throughput for the intercluster relaying in the long run.

  19. Dynamic network expansion, contraction, and connectivity in the river corridor of mountain stream network

    Science.gov (United States)

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

    2017-12-01

    River networks are broadly recognized to expand and contract in response to hydrologic forcing. Additionally, the individual controls on river corridor dynamics of hydrologic forcing and geologic setting are well recognized. However, we currently lack tools to integrate our understanding of process dynamics in the river corridor and make predictions at the scale of river networks. In this study, we develop a perceptual model of the river corridor in mountain river networks, translate this into a reduced-complexity mechanistic model, and implement the model in a well-studied headwater catchment. We found that the river network was most sensitive to hydrologic dynamics under the lowest discharges (Qgauge managers of water resources who need to estimate connectivity and flow initiation location along the river corridor over broad, unstudied catchments.

  20. Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks

    OpenAIRE

    Petersen, Alexander; Zhao, Jianyang; Carmichael, Owen; Müller, Hans-Georg

    2016-01-01

    In typical functional connectivity studies, connections between voxels or regions in the brain are represented as edges in a network. Networks for different subjects are constructed at a given graph density and are summarized by some network measure such as path length. Examining these summary measures for many density values yields samples of connectivity curves, one for each individual. This has led to the adoption of basic tools of functional data analysis, most commonly to compare control...

  1. 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.

  2. 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)

  3. 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...... 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...... 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....

  4. Comb-like optical transmission spectra generated from one-dimensional two-segment-connected two-material waveguide networks optimized by genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yu [MOE Key Laboratory of Laser Life Science and Institute of Laser Life Science, College of Biophotonics, South China Normal University, Guangzhou 510631 (China); Yang, Xiangbo, E-mail: xbyang@scnu.edu.cn [MOE Key Laboratory of Laser Life Science and Institute of Laser Life Science, College of Biophotonics, South China Normal University, Guangzhou 510631 (China); School of Physical Education and Sports Science, South China Normal University, Guangzhou 510006 (China); Lu, Jian; Zhang, Guogang [MOE Key Laboratory of Laser Life Science and Institute of Laser Life Science, College of Biophotonics, South China Normal University, Guangzhou 510631 (China); Liu, Chengyi Timon [School of Physical Education and Sports Science, South China Normal University, Guangzhou 510006 (China)

    2014-03-01

    In this Letter, a one-dimensional (1D) two-segment-connected two-material waveguide network (TSCTMWN) is designed to produce comb-like frequency passbands, where each waveguide segment is composed of normal and anomalous dispersion materials and the length ratio of sub-waveguide segments is optimized by genetic algorithm (GA). It is found that 66 comb-like frequency passbands are created in the second frequency unit, maximal relative width difference of which is less than 2×10{sup −5}. It may be useful for the designing of dense wavelength division multiplexings (DWDMs) and multi-channel filters, etc., and provide new applications for GA.

  5. 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.

  6. 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

  7. 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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    OBJECTIVE: To investigate resting-state functional connectivity in the salience network (SN), the sensorimotor network (SMN), and the default mode network (DMN) during migraine attacks induced by pituitary adenylate cyclase-activating polypeptide-38 (PACAP38). METHODS: In a double-blind, randomized...... connectivity with the bilateral opercular part of the inferior frontal gyrus in the SN. In SMN, there was increased connectivity with the right premotor cortex and decreased connectivity with the left visual cortex. Several areas showed increased (left primary auditory, secondary somatosensory, premotor......, and visual cortices) and decreased (right cerebellum and left frontal lobe) connectivity with DMN. We found no resting-state network changes after VIP (n = 15). CONCLUSIONS: PACAP38-induced migraine attack is associated with altered connectivity of several large-scale functional networks of the brain....

  9. 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.

  10. 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)

    DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

    2016-03-29

    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.

  11. 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.

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

    Science.gov (United States)

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

    2017-09-16

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

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

    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

  14. 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.

  15. The Influence of Water Conservancy Projects on River Network Connectivity, A Case of Luanhe River Basin

    Science.gov (United States)

    Li, Z.; Li, C.

    2017-12-01

    Connectivity is one of the most important characteristics of a river, which is derived from the natural water cycle and determine the renewability of river water. The water conservancy project can change the connectivity of natural river networks, and directly threaten the health and stability of the river ecosystem. Based on the method of Dendritic Connectivity Index (DCI), the impacts from sluices and dams on the connectivity of river network are deeply discussed herein. DCI quantitatively evaluate the connectivity of river networks based on the number of water conservancy facilities, the connectivity of fish and geographical location. The results show that the number of water conservancy facilities and their location in the river basin have a great influence on the connectivity of the river network. With the increase of the number of sluices and dams, DCI is decreasing gradually, but its decreasing range is becoming smaller and smaller. The dam located in the middle of the river network cuts the upper and lower parts of the whole river network, and destroys the connectivity of the river network more seriously. Therefore, this method can be widely applied to the comparison of different alternatives during planning of river basins and then provide a reference for the site selection and design of the water conservancy project and facility concerned.

  16. 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.).

  17. Abnormal Functional Connectivity Between Default and Salience Networks in Pediatric Bipolar Disorder.

    Science.gov (United States)

    Lopez-Larson, Melissa P; Shah, Lubdha M; Weeks, Howard R; King, Jace B; Mallik, Atul K; Yurgelun-Todd, Deborah A; Anderson, Jeffrey S

    2017-01-01

    Pediatric bipolar disorder (PBD) (occurring prior to 18 years of age) is a developmental brain disorder that is among the most severe and disabling psychiatric conditions affecting youth. Despite increasing evidence that brain connectivity is atypical in adults with bipolar disorder, it is not clear how brain connectivity may be altered in youths with PBD. This cross-sectional resting-state functional magnetic resonance imaging study included 80 participants recruited over 4 years: 32 youths with PBD, currently euthymic (13 males; 15.1 years old), and 48 healthy control (HC) subjects (27 males; 14.5 years old). Functional connectivity between eight major intrinsic connectivity networks, along with connectivity measurements between 333 brain regions, was compared between PBD and HC subjects. Additionally, connectivity differences were evaluated between PBD and HC samples in negatively correlated connections, as defined by 839 subjects of the Human Connectome Project dataset. We found increased inter- but not intranetwork functional connectivity in PBD between the default mode and salience networks (p = .0017). Throughout the brain, atypical connections showed failure to develop anticorrelation with age during adolescence in PBD but not HC samples among connections that exhibit negative correlation in adulthood. Youths with PBD demonstrate reduced anticorrelation between default mode and salience networks. Further evaluation of the interaction between these networks is needed in development and with other mood states such as depression and mania to clarify if this atypical connectivity is a PBD trait biomarker. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  18. 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.

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

    Science.gov (United States)

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

    2015-06-17

    The human brain undergoes substantial development throughout adolescence and into early adulthood. This maturational process is thought to include the refinement of connectivity between putative connectivity hub regions of the brain, which collectively form a dense core that enhances the functional integration of anatomically distributed, and functionally specialized, neural systems. Here, we used longitudinal diffusion magnetic resonance imaging to characterize changes in connectivity between 80 cortical and subcortical anatomical regions over a 2 year period in 31 adolescents between the ages of 15 and 19 years. Connectome-wide analysis indicated that only a small subset of connections showed evidence of statistically significant developmental change over the study period, with 8% and 6% of connections demonstrating decreased and increased structural connectivity, respectively. Nonetheless, these connections linked 93% and 90% of the 80 regions, respectively, pointing to a selective, yet anatomically distributed pattern of developmental changes that involves most of the brain. Hub regions showed a distinct tendency to be highly connected to each other, indicating robust "rich-club" organization. Moreover, connectivity between hubs was disproportionately influenced by development, such that connectivity between subcortical hubs decreased over time, whereas frontal-subcortical and frontal-parietal hub-hub connectivity increased over time. These findings suggest that late adolescence is characterized by selective, yet significant remodeling of hub-hub connectivity, with the topological organization of hubs shifting emphasis from subcortical hubs in favor of an increasingly prominent role for frontal hub regions. Copyright © 2015 the authors 0270-6474/15/359078-10$15.00/0.

  20. 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…

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

    OpenAIRE

    Opdam, P.F.M.

    2014-01-01

    Humans adapt their landscapes, their living environment. Sustainable use of the various landscape benefits requires that land owners and users collaborate in managing ecological networks. Because the government is stepping back as the organizer of coordinated landscape adaptation, we need new landscape planning approaches that enhance collaboration by building social networks and link them to ecological networks. In this farewell address I will explain why the social-ecological network is a p...

  2. Transmission Range Assignment with Balancing Connectivity in Clustered Wireless Networks

    OpenAIRE

    Hussein, Abd Ali

    2014-01-01

    Currently, the main challenge for researchers in the field of wireless sensor networks is associated with reducing the energy consumption as much as possible to increase the lifetime of the nodes and improve the performance of the network. Furthermore, delivery of data to its destination is also an important key issue that represents throughput of the network. On the other hand, transmission range assignment in clustered wireless networks is the bottleneck of the balance between energy con...

  3. 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

  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.

  5. Algebraic connectivity of brain networks shows patterns of segregation leading to reduced network robustness in Alzheimer's disease

    Science.gov (United States)

    Daianu, Madelaine; Jahanshad, Neda; Nir, Talia M.; Leonardo, Cassandra D.; Jack, Clifford R.; Weiner, Michael W.; Bernstein, Matthew A.; Thompson, Paul M.

    2015-01-01

    Measures of network topology and connectivity aid the understanding of network breakdown as the brain degenerates in Alzheimer's disease (AD). We analyzed 3-Tesla diffusion-weighted images from 202 patients scanned by the Alzheimer's Disease Neuroimaging Initiative – 50 healthy controls, 72 with early- and 38 with late-stage mild cognitive impairment (eMCI/lMCI) and 42 with AD. Using whole-brain tractography, we reconstructed structural connectivity networks representing connections between pairs of cortical regions. We examined, for the first time in this context, the network's Laplacian matrix and its Fiedler value, describing the network's algebraic connectivity, and the Fiedler vector, used to partition a graph. We assessed algebraic connectivity and four additional supporting metrics, revealing a decrease in network robustness and increasing disarray among nodes as dementia progressed. Network components became more disconnected and segregated, and their modularity increased. These measures are sensitive to diagnostic group differences, and may help understand the complex changes in AD. PMID:26640830

  6. Changes of functional connectivity in the left frontoparietal network following aphasic stroke

    Directory of Open Access Journals (Sweden)

    Dan eZhu

    2014-05-01

    Full Text Available Language is an essential higher cognitive function supported by large-scale brain networks. In this study, we investigated functional connectivity changes in the left frontoparietal network (LFPN, a language-cognition related brain network in aphasic patients. We enrolled thirteen aphasic patients who had undergone a stroke in the left hemisphere and age-, gender-, educational level-matched controls and analyzed the data by integrating independent component analysis (ICA with a network connectivity analysis method. Resting state functional magnetic resonance imaging (fMRI and clinical evaluation of language function were assessed at two stages: one and two months after stroke onset. We found reduced functional connectivity between the LFPN and the right middle frontal cortex, medial frontal cortex and right inferior frontal cortex in aphasic patients as compared to controls. Correlation analysis showed that stronger functional connectivity between the LFPN and the right middle frontal cortex and medial frontal cortex coincided with more preserved language comprehension ability after stroke. Network connectivity analysis showed reduced LFPN connectivity as indicated by the mean network connectivity index of key regions in the LFPN of aphasic patients. The decreased LFPN connectivity in stroke patients was significantly associated with the impairment of language function in their comprehension ability. We also found significant association between recovery of comprehension ability and the mean changes in intrinsic LFPN connectivity. Our findings suggest that brain lesions may influence language comprehension by altering functional connectivity between regions and that the patterns of abnormal functional connectivity may contribute to the recovery of language deficits.

  7. 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.

  8. Technical guide to the connection of generation to the distribution network

    Energy Technology Data Exchange (ETDEWEB)

    Jarrett, K.; Hedgecock, J.; Gregory, R.; Warham, T.

    2003-07-01

    This guide provides a 'route map' of the processes of getting a generation scheme connected to the network and is intended to help developers of any form of distributed generation connected to the UK's local electricity networks, eg: renewable energy schemes; waste-to-energy schemes; on-site generation and combined heat and power (CHP) schemes; and peak lopping schemes using back-up generators. Where necessary, the guide distinguishes between arrangements that apply in Scotland and those that apply in England and Wales. The guide aims to: provide background information about the electricity industry; highlight common technical issues that arise during connection negotiation and their implications for distribution network operators (DNOs) and developers; examine the main factors affecting connection costs and timescales for achieving connections; and identify the different types of contracts relating to connection. The report considers the connection process, the connection application process and timescales, costs and charges, competition in connection, the structure of the UK electricity industry, the statutory framework, the effects of distributed generation of the distribution system, earthing and protection design, safety issues and DNO network information. It includes a glossary, checklists, useful contact details and information about standards and other useful documents.

  9. Viewing socio-affective stimuli increases connectivity within an extended default mode network.

    Science.gov (United States)

    Göttlich, Martin; Ye, Zheng; Rodriguez-Fornells, Antoni; Münte, Thomas F; Krämer, Ulrike M

    2017-03-01

    Empathy is an essential ability for prosocial behavior. Previous imaging studies identified a number of brain regions implicated in affective and cognitive aspects of empathy. In this study, we investigated the neural correlates of empathy from a network perspective using graph theory and beta-series correlations. Two independent data sets were acquired using the same paradigm that elicited empathic responses to socio-affective stimuli. One data set was used to define the network nodes and modular structure, the other data set was used to investigate the effects of emotional versus neutral stimuli on network connectivity. Emotional relative to neutral stimuli increased connectivity between 74 nodes belonging to different networks. Most of these nodes belonged to an extended default mode network (eDMN). The other nodes belonged to a cognitive control network or visual networks. Within the eDMN, posterior STG/TPJ regions were identified as provincial hubs. The eDMN also showed stronger connectivity to the cognitive control network encompassing lateral PFC regions. Connector hubs between the two networks were posterior cingulate cortex and ventrolateral PFC. This stresses the advantage of a network approach as regions similarly modulated by task conditions can be dissociated into distinct networks and regions crucial for network integration can be identified. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

    Science.gov (United States)

    Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

    2018-06-01

    Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral

  11. 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.

  12. Wireless sensor communications and internet connectivity for sensor networks

    Energy Technology Data Exchange (ETDEWEB)

    Dunbar, M. [Crossbow Technology, Inc., San Jose, CA (United States)

    2001-07-01

    A wireless sensor network architecture is an integrated hardware/software solution that has the potential to change the way sensors are used in a virtually unlimited range of industries and applications. By leveraging Bluetooth wireless technology for low-cost, short-range radio links, wireless sensor networks such as CrossNet{sup TM} enable users to create wireless sensor networks. These wireless networks can link dozens or hundreds of sensors of disparate types and brands with data acquisition/analysis systems, such as handheld devices, internet-enabled laptop or desktop PCs. The overwhelming majority of sensor applications are hard-wired at present, and since wiring is often the most time-consuming, tedious, trouble-prone and expensive aspect of sensor applications, users in many fields will find compelling reasons to adopt the wireless sensor network solution. (orig.)

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

    Science.gov (United States)

    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

    2015-01-01

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

  14. Multi-species genetic connectivity in a terrestrial habitat network.

    Science.gov (United States)

    Marrotte, Robby R; Bowman, Jeff; Brown, Michael G C; Cordes, Chad; Morris, Kimberley Y; Prentice, Melanie B; Wilson, Paul J

    2017-01-01

    Habitat fragmentation reduces genetic connectivity for multiple species, yet conservation efforts tend to rely heavily on single-species connectivity estimates to inform land-use planning. Such conservation activities may benefit from multi-species connectivity estimates, which provide a simple and practical means to mitigate the effects of habitat fragmentation for a larger number of species. To test the validity of a multi-species connectivity model, we used neutral microsatellite genetic datasets of Canada lynx ( Lynx canadensis ), American marten ( Martes americana ), fisher ( Pekania pennanti ), and southern flying squirrel ( Glaucomys volans ) to evaluate multi-species genetic connectivity across Ontario, Canada. We used linear models to compare node-based estimates of genetic connectivity for each species to point-based estimates of landscape connectivity (current density) derived from circuit theory. To our knowledge, we are the first to evaluate current density as a measure of genetic connectivity. Our results depended on landscape context: habitat amount was more important than current density in explaining multi-species genetic connectivity in the northern part of our study area, where habitat was abundant and fragmentation was low. In the south however, where fragmentation was prevalent, genetic connectivity was correlated with current density. Contrary to our expectations however, locations with a high probability of movement as reflected by high current density were negatively associated with gene flow. Subsequent analyses of circuit theory outputs showed that high current density was also associated with high effective resistance, underscoring that the presence of pinch points is not necessarily indicative of gene flow. Overall, our study appears to provide support for the hypothesis that landscape pattern is important when habitat amount is low. We also conclude that while current density is proportional to the probability of movement per unit area

  15. 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.

  16. 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.

  17. 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

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

    Directory of Open Access Journals (Sweden)

    V. I. Lukovnikov

    2005-01-01

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

  19. Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity.

    Science.gov (United States)

    Keown, Christopher L; Datko, Michael C; Chen, Colleen P; Maximo, José Omar; Jahedi, Afrooz; Müller, Ralph-Axel

    2017-01-01

    Despite abundant evidence of brain network anomalies in autism spectrum disorder (ASD), findings have varied from broad functional underconnectivity to broad overconnectivity. Rather than pursuing overly simplifying general hypotheses ('under' vs. 'over'), we tested the hypothesis of atypical network distribution in ASD (i.e., participation of unusual loci in distributed functional networks). We used a selective high-quality data subset from the ABIDE datashare (including 111 ASD and 174 typically developing [TD] participants) and several graph theory metrics. Resting state functional MRI data were preprocessed and analyzed for detection of low-frequency intrinsic signal correlations. Groups were tightly matched for available demographics and head motion. As hypothesized, the Rand Index (reflecting how similar network organization was to a normative set of networks) was significantly lower in ASD than TD participants. This was accounted for by globally reduced cohesion and density, but increased dispersion of networks. While differences in hub architecture did not survive correction, rich club connectivity (among the hubs) was increased in the ASD group. Our findings support the model of reduced network integration (connectivity with networks) and differentiation (or segregation; based on connectivity outside network boundaries) in ASD. While the findings applied at the global level, they were not equally robust across all networks and in one case (greater cohesion within ventral attention network in ASD) even reversed.

  20. 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)

  1. 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...

  2. 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 ...

  3. 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.

  4. Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia

    Science.gov (United States)

    Van Snellenberg, Jared X.; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa

    2016-01-01

    Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during an n-back working-memory task) and positron emission tomography using the radiotracer [11C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networksconnectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. SIGNIFICANCE

  5. Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia.

    Science.gov (United States)

    Cassidy, Clifford M; Van Snellenberg, Jared X; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa; Horga, Guillermo

    2016-04-13

    Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during ann-back working-memory task) and positron emission tomography using the radiotracer [(11)C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networksconnectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. It is unclear

  6. 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.

  7. 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

  8. Developmental Reorganization of the Core and Extended Face Networks Revealed by Global Functional Connectivity.

    Science.gov (United States)

    Wang, Xu; Zhu, Qi; Song, Yiying; Liu, Jia

    2017-08-28

    Prior studies on development of functional specialization in human brain mainly focus on age-related increases in regional activation and connectivity among regions. However, a few recent studies on the face network demonstrate age-related decrease in face-specialized activation in the extended face network (EFN), in addition to increase in activation in the core face network (CFN). Here we used a voxel-based global brain connectivity approach to investigate whether development of the face network exhibited both increase and decrease in network connectivity. We found the voxel-wise resting-state functional connectivity (FC) within the CFN increased with age in bilateral posterior superior temporal sulcus, suggesting the integration of the CFN during development. Interestingly, the FC of the voxels in the EFN to the right fusiform face area and occipital face area decreased with age, suggesting that the CFN segregated from the EFN during development. Moreover, the age-related connectivity in the CFN was related to behavioral performance in face processing. Overall, our study demonstrated developmental reorganization of the face network achieved by both integration within the CFN and segregation of the CFN from the EFN, which may account for the simultaneous increases and decreases in neural activation during the development of the face network. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. Progressively Disrupted Brain Functional Connectivity Network in Subcortical Ischemic Vascular Cognitive Impairment Patients.

    Science.gov (United States)

    Sang, Linqiong; Chen, Lin; Wang, Li; Zhang, Jingna; Zhang, Ye; Li, Pengyue; Li, Chuanming; Qiu, Mingguo

    2018-01-01

    Cognitive impairment caused by subcortical ischemic vascular disease (SIVD) has been elucidated by many neuroimaging studies. However, little is known regarding the changes in brain functional connectivity networks in relation to the severity of cognitive impairment in SIVD. In the present study, 20 subcortical ischemic vascular cognitive impairment no dementia patients (SIVCIND) and 20 dementia patients (SIVaD) were enrolled; additionally, 19 normal controls were recruited. Each participant underwent a resting-state functional MRI scan. Whole-brain functional networks were analyzed with graph theory and network-based statistics (NBS) to study the functional organization of networks and find alterations in functional connectivity among brain regions. After adjustments for age, gender, and duration of formal education, there were significant group differences for two network functional organization indices, global efficiency and local efficiency, which decreased (NC > SIVCIND > SIVaD) as cognitive impairment worsened. Between-group differences in functional connectivity (NBS corrected, p  impairment worsened, with an increased number of decreased connections between brain regions. We also observed more reductions in nodal efficiency in the prefrontal and temporal cortices for SIVaD than for SIVCIND. These findings indicated a progressively disrupted pattern of the brain functional connectivity network with increased cognitive impairment and showed promise for the development of reliable biomarkers of network metric changes related to cognitive impairment caused by SIVD.

  10. 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

  11. 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

  12. 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...

  13. Spatial asymmetric retrieval states in symmetric Hebb network with uniform connectivity

    International Nuclear Information System (INIS)

    Koroutchev, K.; Korutcheva, E.

    2004-09-01

    In this paper we show tat during the retrieval process in a binary Hebb recursive neural network, spatial localized states can be observed when the connectivity of the network is distance-dependent. We point out that the minimal condition that leads to this type of behaviour is the asymmetry between the retrieval and the learning states. (author)

  14. 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

  15. 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.

  16. Analysis of connectivity map: Control to glutamate injured and phenobarbital treated neuronal network

    Science.gov (United States)

    Kamal, Hassan; Kanhirodan, Rajan; Srinivas, Kalyan V.; Sikdar, Sujit K.

    2010-04-01

    We study the responses of a cultured neural network when it is exposed to epileptogenesis glutamate injury causing epilepsy and subsequent treatment with phenobarbital by constructing connectivity map of neurons using correlation matrix. This study is particularly useful in understanding the pharmaceutical drug induced changes in the neuronal network properties with insights into changes at the systems biology level.

  17. Connectivity strategies to enhance the capacity of weight-bearing networks

    International Nuclear Information System (INIS)

    Janaki, T.M.; Gupte, Neelima

    2003-01-01

    The connectivity properties of a weight-bearing network are exploited to enhance its capacity. We study a 2D network of sites where the weight-bearing capacity of a given site depends on the capacities of the sites connected to it in the layers above. The network consists of clusters, viz., a set of sites connected with each other with the largest such collection of sites being denoted as the maximal cluster. New connections are made between sites in successive layers using two distinct strategies. The key element of our strategies consists of adding as many disjoint clusters as possible to the sites on the trunk T of the maximal cluster. In the first strategy the reconnections start from the last layer upwards and stop when no new sites are added. In the second case, the reconnections start from the top layer and go all the way down to the last layer. The new networks can bear much higher weights than the original networks and have much lower failure rates. The first strategy leads to a greater enhancement of stability, whereas the second leads to a greater enhancement of capacity compared to the original networks. The original network used here is a typical example of the branching hierarchical class. However, the application of strategies similar to ours can yield useful results in other types of networks as well

  18. 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...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

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

    CERN Document Server

    McManus, Sean

    2010-01-01

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

  4. 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.

  5. 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...

  6. Symposium Connects Government Problems with State of the Art Network Science Research

    Science.gov (United States)

    2015-10-16

    Symposium Connects Government Problems with State-of-the- Art Network Science Research By Rajmonda S. Caceres and Benjamin A. Miller Network...the US Gov- ernment, and match these with the state-of-the- art models and techniques developed in the network science research community. Since its... science has grown significantly in the last several years as a field at the intersec- tion of mathematics, computer science , social science , and engineering

  7. 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.

  8. 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.

  9. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2005-07-01

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

  11. 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...

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

    NARCIS (Netherlands)

    Opdam, P.F.M.

    2014-01-01

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

  13. 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.

  14. The brain matures with stronger functional connectivity and decreased randomness of its network.

    Directory of Open Access Journals (Sweden)

    Dirk J A Smit

    Full Text Available We investigated the development of the brain's functional connectivity throughout the life span (ages 5 through 71 years by measuring EEG activity in a large population-based sample. Connectivity was established with Synchronization Likelihood. Relative randomness of the connectivity patterns was established with Watts and Strogatz' (1998 graph parameters C (local clustering and L (global path length for alpha (~10 Hz, beta (~20 Hz, and theta (~4 Hz oscillation networks. From childhood to adolescence large increases in connectivity in alpha, theta and beta frequency bands were found that continued at a slower pace into adulthood (peaking at ~50 yrs. Connectivity changes were accompanied by increases in L and C reflecting decreases in network randomness or increased order (peak levels reached at ~18 yrs. Older age (55+ was associated with weakened connectivity. Semi-automatically segmented T1 weighted MRI images of 104 young adults revealed that connectivity was significantly correlated to cerebral white matter volume (alpha oscillations: r = 33, p<01; theta: r = 22, p<05, while path length was related to both white matter (alpha: max. r = 38, p<001 and gray matter (alpha: max. r = 36, p<001; theta: max. r = 36, p<001 volumes. In conclusion, EEG connectivity and graph theoretical network analysis may be used to trace structural and functional development of the brain.

  15. 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 (pmind performance were both associated with altered connectivity of default regions within the patient group (pmind 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.

  16. 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.

  17. 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...... 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...... of different size and composition showed that (1) Conduction is enhanced in models harboring long and thin endothelial cells that couple preferentially along the longitudinal axis. (2) Conduction across a branch point depends on endothelial connectivity between branches. (3) Low connectivity sub...

  18. Functional network connectivity underlying food processing: disturbed salience and visual processing in overweight and obese adults.

    Science.gov (United States)

    Kullmann, Stephanie; Pape, Anna-Antonia; Heni, Martin; Ketterer, Caroline; Schick, Fritz; Häring, Hans-Ulrich; Fritsche, Andreas; Preissl, Hubert; Veit, Ralf

    2013-05-01

    In order to adequately explore the neurobiological basis of eating behavior of humans and their changes with body weight, interactions between brain areas or networks need to be investigated. In the current functional magnetic resonance imaging study, we examined the modulating effects of stimulus category (food vs. nonfood), caloric content of food, and body weight on the time course and functional connectivity of 5 brain networks by means of independent component analysis in healthy lean and overweight/obese adults. These functional networks included motor sensory, default-mode, extrastriate visual, temporal visual association, and salience networks. We found an extensive modulation elicited by food stimuli in the 2 visual and salience networks, with a dissociable pattern in the time course and functional connectivity between lean and overweight/obese subjects. Specifically, only in lean subjects, the temporal visual association network was modulated by the stimulus category and the salience network by caloric content, whereas overweight and obese subjects showed a generalized augmented response in the salience network. Furthermore, overweight/obese subjects showed changes in functional connectivity in networks important for object recognition, motivational salience, and executive control. These alterations could potentially lead to top-down deficiencies driving the overconsumption of food in the obese population.

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

    Directory of Open Access Journals (Sweden)

    Adham Elshahabi

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

  20. 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

  1. 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

  2. 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.

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

    KAUST Repository

    Elwhishi, Ahmed; Ho, Pin-Han; Shihada, Basem

    2013-01-01

    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.

  4. 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.

  5. Religious and spiritual importance moderate relation between default mode network connectivity and familial risk for depression.

    Science.gov (United States)

    Svob, Connie; Wang, Zhishun; Weissman, Myrna M; Wickramaratne, Priya; Posner, Jonathan

    2016-11-10

    Individuals at high risk for depression have increased default mode network (DMN) connectivity, as well as reduced inverse connectivity between the DMN and the central executive network (CEN) [8]. Other studies have indicated that the belief in the importance of religion/spirituality (R/S) is protective against depression in high risk individuals [5]. Given these findings, we hypothesized that R/S importance would moderate DMN connectivity, potentially reducing DMN connectivity or increasing DMN-CEN inverse connectivity in individuals at high risk for depression. Using resting-state functional connectivity MRI (rs-fcMRI) in a sample of 104 individuals (aged 11-60) at high and low risk for familial depression, we previously reported increased DMN connectivity and reduced DMN-CEN inverse connectivity in high risk individuals. Here, we found that this effect was moderated by self-report measures of R/S importance. Greater R/S importance in the high risk group was associated with decreased DMN connectivity. These results may represent a protective neural adaptation in the DMN of individuals at high risk for depression, and may have implications for other meditation-based therapies for depression. Published by Elsevier Ireland Ltd.

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

    Science.gov (United States)

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

    2016-01-15

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

  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.; Atria, Alireza

    2014-01-01

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

  9. 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

  10. Chimera states in brain networks: Empirical neural vs. modular fractal connectivity

    Science.gov (United States)

    Chouzouris, Teresa; Omelchenko, Iryna; Zakharova, Anna; Hlinka, Jaroslav; Jiruska, Premysl; Schöll, Eckehard

    2018-04-01

    Complex spatiotemporal patterns, called chimera states, consist of coexisting coherent and incoherent domains and can be observed in networks of coupled oscillators. The interplay of synchrony and asynchrony in complex brain networks is an important aspect in studies of both the brain function and disease. We analyse the collective dynamics of FitzHugh-Nagumo neurons in complex networks motivated by its potential application to epileptology and epilepsy surgery. We compare two topologies: an empirical structural neural connectivity derived from diffusion-weighted magnetic resonance imaging and a mathematically constructed network with modular fractal connectivity. We analyse the properties of chimeras and partially synchronized states and obtain regions of their stability in the parameter planes. Furthermore, we qualitatively simulate the dynamics of epileptic seizures and study the influence of the removal of nodes on the network synchronizability, which can be useful for applications to epileptic surgery.

  11. 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.

  12. 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.)

  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. Implementation of neural networks on 'Connection Machine'

    International Nuclear Information System (INIS)

    Belmonte, Ghislain

    1990-12-01

    This report is a first approach to the notion of neural networks and their possible applications within the framework of artificial intelligence activities of the Department of Applied Mathematics of the Limeil-Valenton Research Center. The first part is an introduction to the field of neural networks; the main neural network models are described in this section. The applications of neural networks in the field of classification have mainly been studied because they could more particularly help to solve some of the decision support problems dealt with by the C.E.A. As the neural networks perform a large number of parallel operations, it was therefore logical to use a parallel architecture computer: the Connection Machine (which uses 16384 processors and is located at E.T.C.A. Arcueil). The second part presents some generalities on the parallelism and the Connection Machine, and two implementations of neural networks on Connection Machine. The first of these implementations concerns one of the most used algorithms to realize the learning of neural networks: the Gradient Retro-propagation algorithm. The second one, less common, concerns a network of neurons destined mainly to the recognition of forms: the Fukushima Neocognitron. The latter is studied by the C.E.A. of Bruyeres-le-Chatel in order to realize an embedded system (including hardened circuits) for the fast recognition of forms [fr

  16. 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.

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

    International Nuclear Information System (INIS)

    Ahnert, Sebastian E; A N Travencolo, Bruno; Costa, Luciano da Fontoura

    2009-01-01

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

  18. 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.

  19. 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.

  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. 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.

  2. 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.

  3. 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.

  4. Toward Rigorous Parameterization of Underconstrained Neural Network Models Through Interactive Visualization and Steering of Connectivity Generation

    Directory of Open Access Journals (Sweden)

    Christian Nowke

    2018-06-01

    Full Text Available Simulation models in many scientific fields can have non-unique solutions or unique solutions which can be difficult to find. Moreover, in evolving systems, unique final state solutions can be reached by multiple different trajectories. Neuroscience is no exception. Often, neural network models are subject to parameter fitting to obtain desirable output comparable to experimental data. Parameter fitting without sufficient constraints and a systematic exploration of the possible solution space can lead to conclusions valid only around local minima or around non-minima. To address this issue, we have developed an interactive tool for visualizing and steering parameters in neural network simulation models. In this work, we focus particularly on connectivity generation, since finding suitable connectivity configurations for neural network models constitutes a complex parameter search scenario. The development of the tool has been guided by several use cases—the tool allows researchers to steer the parameters of the connectivity generation during the simulation, thus quickly growing networks composed of multiple populations with a targeted mean activity. The flexibility of the software allows scientists to explore other connectivity and neuron variables apart from the ones presented as use cases. With this tool, we enable an interactive exploration of parameter spaces and a better understanding of neural network models and grapple with the crucial problem of non-unique network solutions and trajectories. In addition, we observe a reduction in turn around times for the assessment of these models, due to interactive visualization while the simulation is computed.

  5. Investigating the effects of streamline-based fiber tractography on matrix scaling in brain connective network.

    Science.gov (United States)

    Jan, Hengtai; Chao, Yi-Ping; Cho, Kuan-Hung; Kuo, Li-Wei

    2013-01-01

    Investigating the brain connective network using the modern graph theory has been widely applied in cognitive and clinical neuroscience research. In this study, we aimed to investigate the effects of streamline-based fiber tractography on the change of network properties and established a systematic framework to understand how an adequate network matrix scaling can be determined. The network properties, including degree, efficiency and betweenness centrality, show similar tendency in both left and right hemispheres. By employing the curve-fitting process with exponential law and measuring the residuals, the association between changes of network properties and threshold of track numbers is found and an adequate range of investigating the lateralization of brain network is suggested. The proposed approach can be further applied in clinical applications to improve the diagnostic sensitivity using network analysis with graph theory.

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

    Science.gov (United States)

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

    2016-01-01

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

  7. Reconstruction of sparse connectivity in neural networks from spike train covariances

    International Nuclear Information System (INIS)

    Pernice, Volker; Rotter, Stefan

    2013-01-01

    The inference of causation from correlation is in general highly problematic. Correspondingly, it is difficult to infer the existence of physical synaptic connections between neurons from correlations in their activity. Covariances in neural spike trains and their relation to network structure have been the subject of intense research, both experimentally and theoretically. The influence of recurrent connections on covariances can be characterized directly in linear models, where connectivity in the network is described by a matrix of linear coupling kernels. However, as indirect connections also give rise to covariances, the inverse problem of inferring network structure from covariances can generally not be solved unambiguously. Here we study to what degree this ambiguity can be resolved if the sparseness of neural networks is taken into account. To reconstruct a sparse network, we determine the minimal set of linear couplings consistent with the measured covariances by minimizing the L 1 norm of the coupling matrix under appropriate constraints. Contrary to intuition, after stochastic optimization of the coupling matrix, the resulting estimate of the underlying network is directed, despite the fact that a symmetric matrix of count covariances is used for inference. The performance of the new method is best if connections are neither exceedingly sparse, nor too dense, and it is easily applicable for networks of a few hundred nodes. Full coupling kernels can be obtained from the matrix of full covariance functions. We apply our method to networks of leaky integrate-and-fire neurons in an asynchronous–irregular state, where spike train covariances are well described by a linear model. (paper)

  8. 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....

  9. Impaired clock output by altered connectivity in the circadian network.

    Science.gov (United States)

    Fernández, María de la Paz; Chu, Jessie; Villella, Adriana; Atkinson, Nigel; Kay, Steve A; Ceriani, María Fernanda

    2007-03-27

    Substantial progress has been made in elucidating the molecular processes that impart a temporal control to physiology and behavior in most eukaryotes. In Drosophila, dorsal and ventral neuronal networks act in concert to convey rhythmicity. Recently, the hierarchical organization among the different circadian clusters has been addressed, but how molecular oscillations translate into rhythmic behavior remains unclear. The small ventral lateral neurons can synchronize certain dorsal oscillators likely through the release of pigment dispersing factor (PDF), a neuropeptide central to the control of rhythmic rest-activity cycles. In the present study, we have taken advantage of flies exhibiting a distinctive arrhythmic phenotype due to mutation of the potassium channel slowpoke (slo) to examine the relevance of specific neuronal populations involved in the circadian control of behavior. We show that altered neuronal function associated with the null mutation specifically impaired PDF accumulation in the dorsal protocerebrum and, in turn, desynchronized molecular oscillations in the dorsal clusters. However, molecular oscillations in the small ventral lateral neurons are properly running in the null mutant, indicating that slo is acting downstream of these core pacemaker cells, most likely in the output pathway. Surprisingly, disrupted PDF signaling by slo dysfunction directly affects the structure of the underlying circuit. Our observations demonstrate that subtle structural changes within the circadian network are responsible for behavioral arrhythmicity.

  10. Contention Aware Routing for Intermittently Connected Mobile Networks

    KAUST Repository

    Elwhishi, Ahmed; Ho, Pin Han; Naik, Sagar; Shihada, Basem

    2011-01-01

    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.

  11. 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.

  12. 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.

  13. Enhanced fuzzy-connective-based hierarchical aggregation network using particle swarm optimization

    Science.gov (United States)

    Wang, Fang-Fang; Su, Chao-Ton

    2014-11-01

    The fuzzy-connective-based aggregation network is similar to the human decision-making process. It is capable of aggregating and propagating degrees of satisfaction of a set of criteria in a hierarchical manner. Its interpreting ability and transparency make it especially desirable. To enhance its effectiveness and further applicability, a learning approach is successfully developed based on particle swarm optimization to determine the weights and parameters of the connectives in the network. By experimenting on eight datasets with different characteristics and conducting further statistical tests, it has been found to outperform the gradient- and genetic algorithm-based learning approaches proposed in the literature; furthermore, it is capable of generating more accurate estimates. The present approach retains the original benefits of fuzzy-connective-based aggregation networks and is widely applicable. The characteristics of the learning approaches are also discussed and summarized, providing better understanding of the similarities and differences among these three approaches.

  14. 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.

  15. [Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.

    Science.gov (United States)

    Yu, Ya Ping; Yin, Hai Wei; Kong, Fan Hua; Wang, Jing Jing; Xu, Wen Bin

    2016-07-01

    Based on ArcGIS, Erdas, GuidosToolbox, Conefor and other software platforms, using morphological spatial pattern analysis (MSPA) and landscape connectivity analysis methods, this paper quantitatively analysed the scale effect, edge effect and distance effect of the Nanjing urban green infrastructure network pattern in 2013 by setting different pixel sizes (P) and edge widths in MSPA analysis, and setting different dispersal distance thresholds in landscape connectivity analysis. The results showed that the type of landscape acquired based on the MSPA had a clear scale effect and edge effect, and scale effects only slightly affected landscape types, whereas edge effects were more obvious. Different dispersal distances had a great impact on the landscape connectivity, 2 km or 2.5 km dispersal distance was a critical threshold for Nanjing. When selecting the pixel size 30 m of the input data and the edge wide 30 m used in the morphological model, we could get more detailed landscape information of Nanjing UGI network. Based on MSPA and landscape connectivity, analysis of the scale effect, edge effect, and distance effect on the landscape types of the urban green infrastructure (UGI) network was helpful for selecting the appropriate size, edge width, and dispersal distance when developing these networks, and for better understanding the spatial pattern of UGI networks and the effects of scale and distance on the ecology of a UGI network. This would facilitate a more scientifically valid set of design parameters for UGI network spatiotemporal pattern analysis. The results of this study provided an important reference for Nanjing UGI networks and a basis for the analysis of the spatial and temporal patterns of medium-scale UGI landscape networks in other regions.

  16. 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.

  17. 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.

  18. A case for motor network contributions to schizophrenia symptoms: Evidence from resting-state connectivity.

    Science.gov (United States)

    Bernard, Jessica A; Goen, James R M; Maldonado, Ted

    2017-09-01

    Though schizophrenia (SCZ) is classically defined based on positive symptoms and the negative symptoms of the disease prove to be debilitating for many patients, motor deficits are often present as well. A growing literature highlights the importance of motor systems and networks in the disease, and it may be the case that dysfunction in motor networks relates to the pathophysiology and etiology of SCZ. To test this and build upon recent work in SCZ and in at-risk populations, we investigated cortical and cerebellar motor functional networks at rest in SCZ and controls using publically available data. We analyzed data from 82 patients and 88 controls. We found key group differences in resting-state connectivity patterns that highlight dysfunction in motor circuits and also implicate the thalamus. Furthermore, we demonstrated that in SCZ, these resting-state networks are related to both positive and negative symptom severity. Though the ventral prefrontal cortex and corticostriatal pathways more broadly have been implicated in negative symptom severity, here we extend these findings to include motor-striatal connections, as increased connectivity between the primary motor cortex and basal ganglia was associated with more severe negative symptoms. Together, these findings implicate motor networks in the symptomatology of psychosis, and we speculate that these networks may be contributing to the etiology of the disease. Overt motor deficits in SCZ may signal underlying network dysfunction that contributes to the overall disease state. Hum Brain Mapp 38:4535-4545, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  19. 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

  20. 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

  1. Fractional charge and anomalous commutators

    International Nuclear Information System (INIS)

    Frishman, Y.; Gepner, D.

    1983-06-01

    Non-integer charges on topological objects in the presence of fermions are further investigated. The connection with anomalous commutators is discussed. The reason for the identical results in two-dimensional solutions and four-dimensional monopoles is pointed out. (author)

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

    Science.gov (United States)

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

    2016-08-01

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

  3. 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

  4. 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.

  5. 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.

  6. Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks.

    Science.gov (United States)

    Petersen, Alexander; Zhao, Jianyang; Carmichael, Owen; Müller, Hans-Georg

    2016-09-01

    In typical functional connectivity studies, connections between voxels or regions in the brain are represented as edges in a network. Networks for different subjects are constructed at a given graph density and are summarized by some network measure such as path length. Examining these summary measures for many density values yields samples of connectivity curves, one for each individual. This has led to the adoption of basic tools of functional data analysis, most commonly to compare control and disease groups through the average curves in each group. Such group differences, however, neglect the variability in the sample of connectivity curves. In this article, the use of functional principal component analysis (FPCA) is demonstrated to enrich functional connectivity studies by providing increased power and flexibility for statistical inference. Specifically, individual connectivity curves are related to individual characteristics such as age and measures of cognitive function, thus providing a tool to relate brain connectivity with these variables at the individual level. This individual level analysis opens a new perspective that goes beyond previous group level comparisons. Using a large data set of resting-state functional magnetic resonance imaging scans, relationships between connectivity and two measures of cognitive function-episodic memory and executive function-were investigated. The group-based approach was implemented by dichotomizing the continuous cognitive variable and testing for group differences, resulting in no statistically significant findings. To demonstrate the new approach, FPCA was implemented, followed by linear regression models with cognitive scores as responses, identifying significant associations of connectivity in the right middle temporal region with both cognitive scores.

  7. 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.

  8. 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.

  9. 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.

  10. An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks

    Directory of Open Access Journals (Sweden)

    Ying Zhang

    2018-01-01

    Full Text Available With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms.

  11. An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks.

    Science.gov (United States)

    Zhang, Ying; Wang, Jun; Hao, Guan

    2018-01-08

    With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms.

  12. 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.

  13. An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks

    Science.gov (United States)

    Zhang, Ying; Wang, Jun; Hao, Guan

    2018-01-01

    With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms. PMID:29316702

  14. 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.

  15. 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

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

    OpenAIRE

    Nikolovski, Srete; Papuga, Vanja; Knežević, Goran

    2014-01-01

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

  17. Earlier adolescent substance use onset predicts stronger connectivity between reward and cognitive control brain networks

    Directory of Open Access Journals (Sweden)

    David G. Weissman

    2015-12-01

    Discussion: The regions that demonstrated significant positive linear relationships between the number of adolescent years using substances and connectivity with NAcc are nodes in the right frontoparietal network, which is central to cognitive control. The coupling of reward and cognitive control networks may be a mechanism through which earlier onset of substance use is related to brain function over time, a trajectory that may be implicated in subsequent substance use disorders.

  18. 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

    Background: The investigation of large-scale intrinsic connectivity networks in antipsychotic-naïve first-episode schizophrenia increases our understanding of system-level cerebral dysfunction in schizophrenia while enabling control of confounding effects of medication and disease progression. Re......-parietal networks suggested to be involved in the control of cognitive and sensory functions. Moreover, the present study suggests that the problem of not disengaging the VAN leads to difficulties with attention and possibly subjective awareness....

  19. 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.

  20. Increased Default Mode Network Connectivity in Individuals at High Familial Risk for Depression.

    Science.gov (United States)

    Posner, Jonathan; Cha, Jiook; Wang, Zhishun; Talati, Ardesheer; Warner, Virginia; Gerber, Andrew; Peterson, Bradley S; Weissman, Myrna

    2016-06-01

    Research into the pathophysiology of major depressive disorder (MDD) has focused largely on individuals already affected by MDD. Studies have thus been limited in their ability to disentangle effects that arise as a result of MDD from precursors of the disorder. By studying individuals at high familial risk for MDD, we aimed to identify potential biomarkers indexing risk for developing MDD, a critical step toward advancing prevention and early intervention. Using resting-state functional connectivity MRI (rs-fcMRI) and diffusion MRI (tractography), we examined connectivity within the default mode network (DMN) and between the DMN and the central executive network (CEN) in 111 individuals, aged 11-60 years, at high and low familial risk for depression. Study participants were part of a three-generation longitudinal, cohort study of familial depression. Based on rs-fcMRI, individuals at high vs low familial risk for depression showed increased DMN connectivity, as well as decreased DMN-CEN-negative connectivity. These findings remained significant after excluding individuals with a current or lifetime history of depression. Diffusion MRI measures based on tractography supported the findings of decreased DMN-CEN-negative connectivity. Path analyses indicated that decreased DMN-CEN-negative connectivity mediated a relationship between familial risk and a neuropsychological measure of impulsivity. Our findings suggest that DMN and DMN-CEN connectivity differ in those at high vs low risk for depression and thus suggest potential biomarkers for identifying individuals at risk for developing MDD.

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

    Science.gov (United States)

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

    2014-03-01

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

  2. 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

  3. Large-scale functional networks connect differently for processing words and symbol strings.

    Science.gov (United States)

    Liljeström, Mia; Vartiainen, Johanna; Kujala, Jan; Salmelin, Riitta

    2018-01-01

    Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalography (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8-13 Hz) and high gamma (60-90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21-29 Hz) and low gamma (30-45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.

  4. 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.

  5. Anti-correlated cortical networks of intrinsic connectivity in the rat brain.

    Science.gov (United States)

    Schwarz, Adam J; Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

    2013-01-01

    In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline "DMN-like" network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans.

  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. Reduced Functional Connectivity of Default Mode and Set-Maintenance Networks in Ornithine Transcarbamylase Deficiency.

    Directory of Open Access Journals (Sweden)

    Ileana Pacheco-Colón

    Full Text Available Ornithine transcarbamylase deficiency (OTCD is an X-chromosome linked urea cycle disorder (UCD that causes hyperammonemic episodes leading to white matter injury and impairments in executive functioning, working memory, and motor planning. This study aims to investigate differences in functional connectivity of two resting-state networks--default mode and set-maintenance--between OTCD patients and healthy controls.Sixteen patients with partial OTCD and twenty-two control participants underwent a resting-state scan using 3T fMRI. Combining independent component analysis (ICA and region-of-interest (ROI analyses, we identified the nodes that comprised each network in each group, and assessed internodal connectivity.Group comparisons revealed reduced functional connectivity in the default mode network (DMN of OTCD patients, particularly between the anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC node and bilateral inferior parietal lobule (IPL, as well as between the ACC/mPFC node and the posterior cingulate cortex (PCC node. Patients also showed reduced connectivity in the set-maintenance network, especially between right anterior insula/frontal operculum (aI/fO node and bilateral superior frontal gyrus (SFG, as well as between the right aI/fO and ACC and between the ACC and right SFG.Internodal functional connectivity in the DMN and set-maintenance network is reduced in patients with partial OTCD compared to controls, most likely due to hyperammonemia-related white matter damage. Because several of the affected areas are involved in executive functioning, it is postulated that this reduced connectivity is an underlying cause of the deficits OTCD patients display in this cognitive domain.

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

    Science.gov (United States)

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

    2015-10-01

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

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

    Science.gov (United States)

    Siedner, Mark J; Lankowski, Alexander; Musinga, Derrick; Jackson, Jonathon; Muzoora, Conrad; Hunt, Peter W; Martin, Jeffrey N; Bangsberg, David R; Haberer, Jessica E

    2012-01-01

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

  10. 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.

  11. Resting-state brain networks revealed by granger causal connectivity in frogs.

    Science.gov (United States)

    Xue, Fei; Fang, Guangzhan; Yue, Xizi; Zhao, Ermi; Brauth, Steven E; Tang, Yezhong

    2016-10-15

    Resting-state networks (RSNs) refer to the spontaneous brain activity generated under resting conditions, which maintain the dynamic connectivity of functional brain networks for automatic perception or higher order cognitive functions. Here, Granger causal connectivity analysis (GCCA) was used to explore brain RSNs in the music frog (Babina daunchina) during different behavioral activity phases. The results reveal that a causal network in the frog brain can be identified during the resting state which reflects both brain lateralization and sexual dimorphism. Specifically (1) ascending causal connections from the left mesencephalon to both sides of the telencephalon are significantly higher than those from the right mesencephalon, while the right telencephalon gives rise to the strongest efferent projections among all brain regions; (2) causal connections from the left mesencephalon in females are significantly higher than those in males and (3) these connections are similar during both the high and low behavioral activity phases in this species although almost all electroencephalograph (EEG) spectral bands showed higher power in the high activity phase for all nodes. The functional features of this network match important characteristics of auditory perception in this species. Thus we propose that this causal network maintains auditory perception during the resting state for unexpected auditory inputs as resting-state networks do in other species. These results are also consistent with the idea that females are more sensitive to auditory stimuli than males during the reproductive season. In addition, these results imply that even when not behaviorally active, the frogs remain vigilant for detecting external stimuli. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

  12. 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.

  13. 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.

  14. Efficient Gatherings in Wireless Sensor Networks Using Distributed Computation of Connected Dominating Sets

    Directory of Open Access Journals (Sweden)

    Vincent BOUDET

    2012-03-01

    Full Text Available In this paper, we are interested in enhancing lifetime of wireless sensor networks trying to collect data from all the nodes to a “sink”-node for non-safety critical applications. Connected Dominating Sets are used as a basis for routing messages to the sink. We present a simple distributed algorithm, which computes several CDS trying to distribute the consumption of energy over all the nodes of the network. The simulations show a significant improvement of the network lifetime.

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    Edith J Liemburg

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

  17. 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......, the current study investigated whether WM-dependent modulation of effective connectivity in this network is affected in a group of first-episode schizophrenia (FES) patients compared with similarly performing healthy participants during a verbal n-back task. Dynamic causal modeling (DCM) of the coupling...... between regions (left inferior frontal gyrus (IFG), left inferior parietal lobe (IPL), and primary visual area) identified in a psychophysiological interaction (PPI) analysis was performed to characterize effective connectivity during the n-back task. The PPI analysis revealed that the connectivity...

  18. Impaired development of intrinsic connectivity networks in children with medically intractable localization-related epilepsy.

    Science.gov (United States)

    Ibrahim, George M; Morgan, Benjamin R; Lee, Wayne; Smith, Mary Lou; Donner, Elizabeth J; Wang, Frank; Beers, Craig A; Federico, Paolo; Taylor, Margot J; Doesburg, Sam M; Rutka, James T; Snead, O Carter

    2014-11-01

    Typical childhood development is characterized by the emergence of intrinsic connectivity networks (ICNs) by way of internetwork segregation and intranetwork integration. The impact of childhood epilepsy on the maturation of ICNs is, however, poorly understood. The developmental trajectory of ICNs in 26 children (8-17 years) with localization-related epilepsy and 28 propensity-score matched controls was evaluated using graph theoretical analysis of whole brain connectomes from resting-state functional magnetic resonance imaging (fMRI) data. Children with epilepsy demonstrated impaired development of regional hubs in nodes of the salience and default mode networks (DMN). Seed-based connectivity and hierarchical clustering analysis revealed significantly decreased intranetwork connections, and greater internetwork connectivity in children with epilepsy compared to controls. Significant interactions were identified between epilepsy duration and the expected developmental trajectory of ICNs, indicating that prolonged epilepsy may cause progressive alternations in large-scale networks throughout childhood. DMN integration was also associated with better working memory, whereas internetwork segregation was associated with higher full-scale intelligence quotient scores. Furthermore, subgroup analyses revealed the thalamus, hippocampus, and caudate were weaker hubs in children with secondarily generalized seizures, relative to other patient subgroups. Our findings underscore that epilepsy interferes with the developmental trajectory of brain networks underlying cognition, providing evidence supporting the early treatment of affected children. Copyright © 2014 Wiley Periodicals, Inc.

  19. 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 ... services is a prerequisite to sustainable socio-economic development. ... It will provide case studies and formulate recommendations with respect to ... An IDRC delegation will join international delegates and city representatives at the ICLEI World ...

  20. 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…

  1. Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity

    Science.gov (United States)

    2010-12-10

    Armen Babikyan, Nathaniel M. Jones, Thomas H. Shake, and Andrew P. Worthen MIT Lincoln Laboratory 244 Wood Street Lexington, MA 02420 DDRE, 1777...delay U U U U SAR 11 Zach Sweet 781-981-5997 1 Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity Brooke Shrader, Armen

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

    Directory of Open Access Journals (Sweden)

    Nicholas eFurl

    2015-05-01

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

  3. 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

  4. Altered Network Oscillations and Functional Connectivity Dynamics in Children Born Very Preterm.

    Science.gov (United States)

    Moiseev, Alexander; Doesburg, Sam M; Herdman, Anthony T; Ribary, Urs; Grunau, Ruth E

    2015-09-01

    Structural brain connections develop atypically in very preterm children, and altered functional connectivity is also evident in fMRI studies. Such alterations in brain network connectivity are associated with cognitive difficulties in this population. Little is known, however, about electrophysiological interactions among specific brain networks in children born very preterm. In the present study, we recorded magnetoencephalography while very preterm children and full-term controls performed a visual short-term memory task. Regions expressing task-dependent activity changes were identified using beamformer analysis, and inter-regional phase synchrony was calculated. Very preterm children expressed altered regional recruitment in distributed networks of brain areas, across standard physiological frequency ranges including the theta, alpha, beta and gamma bands. Reduced oscillatory synchrony was observed among task-activated brain regions in very preterm children, particularly for connections involving areas critical for executive abilities, including middle frontal gyrus. These findings suggest that inability to recruit neurophysiological activity and interactions in distributed networks including frontal regions may contribute to difficulties in cognitive development in children born very preterm.

  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. 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

    reliable operation of aerial vehicles in various deployment scenarios. In this paper, we investigate the performance of aerial radio connectivity in a typical rural area network deployment using extensive channel measurements and system simulations. First, we highlight that downlink and uplink radio...

  7. 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.

  8. From static to temporal network theory: Applications to functional brain connectivity

    Directory of Open Access Journals (Sweden)

    William Hedley Thompson

    2017-06-01

    Full Text Available Network neuroscience has become an established paradigm to tackle questions related to the functional and structural connectome of the brain. Recently, interest has been growing in examining the temporal dynamics of the brain’s network activity. Although different approaches to capturing fluctuations in brain connectivity have been proposed, there have been few attempts to quantify these fluctuations using temporal network theory. This theory is an extension of network theory that has been successfully applied to the modeling of dynamic processes in economics, social sciences, and engineering article but it has not been adopted to a great extent within network neuroscience. The objective of this article is twofold: (i to present a detailed description of the central tenets of temporal network theory and describe its measures, and; (ii to apply these measures to a resting-state fMRI dataset to illustrate their utility. Furthermore, we discuss the interpretation of temporal network theory in the context of the dynamic functional brain connectome. All the temporal network measures and plotting functions described in this article are freely available as the Python package Teneto. Temporal network theory is a subfield of network theory that has had limited application to date within network neuroscience. The aims of this work are to introduce temporal network theory, define the metrics relevant to the context of network neuroscience, and illustrate their potential by analyzing a resting-state fMRI dataset. We found both between-subjects and between-task differences that illustrate the potential for these tools to be applied in a wider context. Our tools for analyzing temporal networks have been released in a Python package called Teneto.

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    Zhao Baixiao

    2008-11-01

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

  11. Large photonic band gaps and strong attenuations of two-segment-connected Peano derivative networks

    International Nuclear Information System (INIS)

    Lu, Jian; Yang, Xiangbo; Zhang, Guogang; Cai, Lianzhang

    2011-01-01

    In this Letter, based on ancient Peano curves we construct four kinds of interesting Peano derivative networks composed of one-dimensional (1D) waveguides and investigate the optical transmission spectra and photonic attenuation behavior of electromagnetic (EM) waves in one- and two-segment-connected networks. It is found that for some two-segment-connected networks large photonic band gaps (PBGs) can be created and the widths of large PBGs can be controlled by adjusting the matching ratio of waveguide length and are insensitive to generation number. Diamond- and hexagon-Peano networks are good selectable structures for the designing of optical devices with large PBG(s) and strong attenuation(s). -- Highlights: → Peano and Peano derivative networks composed of 1D waveguides are designed. → Large PBGs with strong attenuations have been created by these fractal networks. → New approach for designing optical devices with large PBGs is proposed. → Diamond- and hexagon-Peano networks with d2:d1=2:1 are good selectable structures.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Social climber attachment in forming networks produces a phase transition in a measure of connectivity

    Science.gov (United States)

    Taylor, Dane; Larremore, Daniel B.

    2012-09-01

    The formation and fragmentation of networks are typically studied using percolation theory, but most previous research has been restricted to studying a phase transition in cluster size, examining the emergence of a giant component. This approach does not study the effects of evolving network structure on dynamics that occur at the nodes, such as the synchronization of oscillators and the spread of information, epidemics, and neuronal excitations. We introduce and analyze an alternative link-formation rule, called social climber (SC) attachment, that may be combined with arbitrary percolation models to produce a phase transition using the largest eigenvalue of the network adjacency matrix as the order parameter. This eigenvalue is significant in the analyses of many network-coupled dynamical systems in which it measures the quality of global coupling and is hence a natural measure of connectivity. We highlight the important self-organized properties of SC attachment and discuss implications for controlling dynamics on networks.

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

    Science.gov (United States)

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

    2013-07-30

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

  19. 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.

  20. 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.

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

    Science.gov (United States)

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

    2016-04-01

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

  2. Mapping a Careflow Network to assess the connectedness of Connected Health.

    Science.gov (United States)

    Carroll, Noel; Richardson, Ita

    2017-04-01

    Connected Health is an emerging and rapidly developing field which has the potential to transform healthcare service systems by increasing its safety, quality and overall efficiency. From a healthcare perspective, process improvement models have mainly focused on the static workflow viewpoint. The objective of this article is to study and model the dynamic nature of healthcare delivery, allowing us to identify where potential issues exist within the service system and to examine how Connected Health technological solutions may support service efficiencies. We explore the application of social network analysis (SNA) as a modelling technique which captures the dynamic nature of a healthcare service. We demonstrate how it can be used to map the 'Careflow Network' and guide Connected Health innovators to examine specific opportunities within the healthcare service. Our results indicate that healthcare technology must be correctly identified and implemented within the Careflow Network to enjoy improvements in service delivery. Oftentimes, prior to making the transformation to Connected Health, researchers use various modelling techniques that fail to identify where Connected Health innovation is best placed in a healthcare service network. Using SNA allows us to develop an understanding of the current operation of healthcare system within which they can effect change. It is important to identify and model the resource exchanges to ensure that the quality and safety of care are enhanced, efficiencies are increased and the overall healthcare service system is improved. We have shown that dynamic models allow us to study the exchange of resources. These are often intertwined within a socio-technical context in an informal manner and not accounted for in static models, yet capture a truer insight on the operations of a Careflow Network.

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

    International Nuclear Information System (INIS)

    Hobbs, L.W.; Jesurum, C.E.; Pulim, V.

    1997-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Ceronmani Sharmila

    2016-06-01

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

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

    Science.gov (United States)

    Lee, JongHyup; Pak, Dohyun

    2016-01-01

    For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

  10. 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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-03-15

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

  12. 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

  13. 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...

  14. 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.

  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. 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

  17. 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

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

    Science.gov (United States)

    Verly, Marjolein; Verhoeven, Judith; Zink, Inge; Mantini, Dante; Peeters, Ronald; Deprez, Sabine; Emsell, Louise; Boets, Bart; Noens, Ilse; Steyaert, Jean; Lagae, Lieven; De Cock, Paul; Rommel, Nathalie; Sunaert, Stefan

    2014-01-01

    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. PMID:24567909

  19. 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.

  20. Global terrestrial water storage connectivity revealed using complex climate network analyses

    Science.gov (United States)

    Sun, A. Y.; Chen, J.; Donges, J.

    2015-07-01

    Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.

  1. Altering neuronal excitability to preserve network connectivity in a computational model of Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Willem de Haan

    2017-09-01

    Full Text Available Neuronal hyperactivity and hyperexcitability of the cerebral cortex and hippocampal region is an increasingly observed phenomenon in preclinical Alzheimer's disease (AD. In later stages, oscillatory slowing and loss of functional connectivity are ubiquitous. Recent evidence suggests that neuronal dynamics have a prominent role in AD pathophysiology, making it a potentially interesting therapeutic target. However, although neuronal activity can be manipulated by various (non-pharmacological means, intervening in a highly integrated system that depends on complex dynamics can produce counterintuitive and adverse effects. Computational dynamic network modeling may serve as a virtual test ground for developing effective interventions. To explore this approach, a previously introduced large-scale neural mass network with human brain topology was used to simulate the temporal evolution of AD-like, activity-dependent network degeneration. In addition, six defense strategies that either enhanced or diminished neuronal excitability were tested against the degeneration process, targeting excitatory and inhibitory neurons combined or separately. Outcome measures described oscillatory, connectivity and topological features of the damaged networks. Over time, the various interventions produced diverse large-scale network effects. Contrary to our hypothesis, the most successful strategy was a selective stimulation of all excitatory neurons in the network; it substantially prolonged the preservation of network integrity. The results of this study imply that functional network damage due to pathological neuronal activity can be opposed by targeted adjustment of neuronal excitability levels. The present approach may help to explore therapeutic effects aimed at preserving or restoring neuronal network integrity and contribute to better-informed intervention choices in future clinical trials in AD.

  2. 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.

  3. Broca's area network in language function.Broca's area network in language function: A pooling-data connectivity study

    Directory of Open Access Journals (Sweden)

    Byron eBernal

    2015-05-01

    Full Text Available Background and Objective. Modern neuroimaging developments have demonstrated that cognitive functions correlate with brain networks rather than specific areas. The purpose of this paper was to analyze the connectivity of Broca's area based on language tasks. Methods. A connectivity modeling study was performed by pooling data of Broca's activation in language tasks. Fifty-seven papers that included 883 subjects in 84 experiments were analyzed. Analysis of Likelihood Estimates of pooled data was utilized to generate the map; thresholds at p < 0.01 were corrected for multiple comparisons and false discovery rate. Resulting images were co-registered into MNI standard space. Results. A network consisting of 16 clusters of activation was obtained. Main clusters were located in the frontal operculum, left posterior temporal region, supplementary motor area, and the parietal lobe. Less common clusters were seen in the sub-cortical structures including the left thalamus, left putamen, secondary visual areas and the right cerebellum. Conclusions. BA44-related networks involved in language processing were demonstrated utilizing a pooling-data connectivity study. Significance, interpretation and limitations of the results are discussed.

  4. Bayesian network analysis reveals alterations to default mode network connectivity in individuals at risk for Alzheimer's disease.

    Science.gov (United States)

    Li, Rui; Yu, Jing; Zhang, Shouzi; Bao, Feng; Wang, Pengyun; Huang, Xin; Li, Juan

    2013-01-01

    Alzheimer's disease (AD) is associated with abnormal functioning of the default mode network (DMN). Functional connectivity (FC) changes to the DMN have been found in patients with amnestic mild cognitive impairment (aMCI), which is the prodromal stage of AD. However, whether or not aMCI also alters the effective connectivity (EC) of the DMN remains unknown. We employed a combined group independent component analysis (ICA) and Bayesian network (BN) learning approach to resting-state functional MRI (fMRI) data from 17 aMCI patients and 17 controls, in order to establish the EC pattern of DMN, and to evaluate changes occurring in aMCI. BN analysis demonstrated heterogeneous regional convergence degree across DMN regions, which were organized into two closely interacting subsystems. Compared to controls, the aMCI group showed altered directed connectivity weights between DMN regions in the fronto-parietal, temporo-frontal, and temporo-parietal pathways. The aMCI group also exhibited altered regional convergence degree in the right inferior parietal lobule. Moreover, we found EC changes in DMN regions in aMCI were correlated with regional FC levels, and the connectivity metrics were associated with patients' cognitive performance. This study provides novel sights into our understanding of the functional architecture of the DMN and adds to a growing body of work demonstrating the importance of the DMN as a mechanism of aMCI.

  5. 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 < .05) after mindfulness training relative to the relaxation control. Right dlPFC showed increased connectivity to right MFG (T = 4.97, p < .05). We report that mindfulness training increases rsFC between dlPFC and dorsal network (superior parietal lobule, supplementary eye field, MFG) and ventral network (right IFG, middle temporal/angular gyrus) regions. These findings extend previous 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.

  6. Income change alters default mode network connectivity for adolescents in poverty

    Directory of Open Access Journals (Sweden)

    David G. Weissman

    2018-04-01

    Full Text Available Experiencing poverty during childhood and adolescence may affect brain function. However, income is dynamic, and studies have not addressed whether income change relates to brain function. In the present study, we investigated whether intrinsic functional connectivity of default mode network (DMN regions was influenced by mean family income and family income change. Parents of 68 Mexican-origin adolescents (35 females reported family income annually when adolescents were 10–16 years old. Intercept and slope of income at each of these ages were calculated for each participant. At age 16 years, adolescents completed a resting state functional neuroimaging scan. Adolescents from high and low income families did not differ in their functional connectivity, but for adolescents in families with lower incomes, their connectivity patterns depended on their income slope. Low-income adolescents whose income increased demonstrated greater connectivity between the posterior cingulate cortex (PCC and the medial prefrontal cortex (mPFC, both DMN regions, and between the PCC and the right inferior frontal gyrus. Increases in income were associated with greater connectivity of the mPFC with the right inferior frontal gyrus and the left superior parietal lobule regardless of mean income. Increases in income, especially among adolescents in poverty, may alleviate stressors, influencing the development of brain networks. Keywords: Adversity, Brain, fMRI, Resting state, Socio-economic status, Youth

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

    Science.gov (United States)

    Brent, Lauren J N

    2015-05-01

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

  8. 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

  9. Income change alters default mode network connectivity for adolescents in poverty.

    Science.gov (United States)

    Weissman, David G; Conger, Rand D; Robins, Richard W; Hastings, Paul D; Guyer, Amanda E

    2018-04-01

    Experiencing poverty during childhood and adolescence may affect brain function. However, income is dynamic, and studies have not addressed whether income change relates to brain function. In the present study, we investigated whether intrinsic functional connectivity of default mode network (DMN) regions was influenced by mean family income and family income change. Parents of 68 Mexican-origin adolescents (35 females) reported family income annually when adolescents were 10-16 years old. Intercept and slope of income at each of these ages were calculated for each participant. At age 16 years, adolescents completed a resting state functional neuroimaging scan. Adolescents from high and low income families did not differ in their functional connectivity, but for adolescents in families with lower incomes, their connectivity patterns depended on their income slope. Low-income adolescents whose income increased demonstrated greater connectivity between the posterior cingulate cortex (PCC) and the medial prefrontal cortex (mPFC), both DMN regions, and between the PCC and the right inferior frontal gyrus. Increases in income were associated with greater connectivity of the mPFC with the right inferior frontal gyrus and the left superior parietal lobule regardless of mean income. Increases in income, especially among adolescents in poverty, may alleviate stressors, influencing the development of brain networks. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  10. The brain network reflecting bodily self-consciousness: a functional connectivity study

    Science.gov (United States)

    Ionta, Silvio; Martuzzi, Roberto; Salomon, Roy

    2014-01-01

    Several brain regions are important for processing self-location and first-person perspective, two important aspects of bodily self-consciousness. However, the interplay between these regions has not been clarified. In addition, while self-location and first-person perspective in healthy subjects are associated with bilateral activity in temporoparietal junction (TPJ), disturbed self-location and first-person perspective result from damage of only the right TPJ. Identifying the involved brain network and understanding the role of hemispheric specializations in encoding self-location and first-person perspective, will provide important information on system-level interactions neurally mediating bodily self-consciousness. Here, we used functional connectivity and showed that right and left TPJ are bilaterally connected to supplementary motor area, ventral premotor cortex, insula, intraparietal sulcus and occipitotemporal cortex. Furthermore, the functional connectivity between right TPJ and right insula had the highest selectivity for changes in self-location and first-person perspective. Finally, functional connectivity revealed hemispheric differences showing that self-location and first-person perspective modulated the connectivity between right TPJ, right posterior insula, and right supplementary motor area, and between left TPJ and right anterior insula. The present data extend previous evidence on healthy populations and clinical observations in neurological deficits, supporting a bilateral, but right-hemispheric dominant, network for bodily self-consciousness. PMID:24396007

  11. 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.

  12. A Virtual Private Local PCN Ring Network Based on ATM VP Cross—Connection

    Institute of Scientific and Technical Information of China (English)

    LinBin; MaYingjun; 等

    1995-01-01

    Avirtual private local PCNring network (VPLPR)is proposed .VPLPR is a virtual logic ring seuved for digital cordless telephone system and it works on ATM VP cross-connection mechanism.Full-distributed data bases are organized for visitor location registers(VLR)and home location register(HLR).The signaling protocols are compatible upward to B-ISDN. The architecture and some of the main characteristics of VPLPR are given.How to configure the ATM VP cross-connection ring is described.And then a protocol conversion between STM frames and ATMcells in base station controller(BSC)is presented.

  13. 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.

  14. Theory of liquid crystal elastomers and polymer networks : Connection between neoclassical theory and differential geometry.

    Science.gov (United States)

    Nguyen, Thanh-Son; Selinger, Jonathan V

    2017-09-01

    In liquid crystal elastomers and polymer networks, the orientational order of liquid crystals is coupled with elastic distortions of crosslinked polymers. Previous theoretical research has described these materials through two different approaches: a neoclassical theory based on the liquid crystal director and the deformation gradient tensor, and a geometric elasticity theory based on the difference between the actual metric tensor and a reference metric. Here, we connect those two approaches using a formalism based on differential geometry. Through this connection, we determine how both the director and the geometry respond to a change of temperature.

  15. 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...

  16. 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.

  17. 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...

  18. Performance of highly connected photonic switching lossless metro-access optical networks

    Science.gov (United States)

    Martins, Indayara Bertoldi; Martins, Yara; Barbosa, Felipe Rudge

    2018-03-01

    The present work analyzes the performance of photonic switching networks, optical packet switching (OPS) and optical burst switching (OBS), in mesh topology of different sizes and configurations. The "lossless" photonic switching node is based on a semiconductor optical amplifier, demonstrated and validated with experimental results on optical power gain, noise figure, and spectral range. The network performance was evaluated through computer simulations based on parameters such as average number of hops, optical packet loss fraction, and optical transport delay (Am). The combination of these elements leads to a consistent account of performance, in terms of network traffic and packet delivery for OPS and OBS metropolitan networks. Results show that a combination of highly connected mesh topologies having an ingress e-buffer present high efficiency and throughput, with very low packet loss and low latency, ensuring fast data delivery to the final receiver.

  19. Impact of connection density on regional cost differences for network operators in the Netherlands

    International Nuclear Information System (INIS)

    2009-04-01

    The Dutch Office of Energy Regulation ('Energiekamer') has an obligation to investigate the extent to which the electricity and gas distribution businesses (DNOs) in the Netherlands face different structural environments that result in regional cost differences which, in turn, could justify tariff differences. On the basis of previous studies, Energiekamer has identified 'water crossings' and 'local taxes' as allowable regional differences. To account for them, Energiekamer has introduced an adjustment to the regulated revenues formula in order to guarantee a level-playing field to the Dutch DNOs. In addition to these factors, it has been claimed that connection density may have an impact on distribution costs and that, therefore, regulated revenues should be adjusted to compensate for regional differences in connection density between DNOs. However, so far, the research in this field has been unable to identify a sufficiently robust relationship between cost and connection density to support this claim. In order to address this issue, Energiekamer has asked Frontier Economics and Consentec to further investigate the relationship between connection density and distribution costs in the Netherlands. Therefore, our analysis has aimed at determining whether, and to what extent, connection density in the Netherlands is a significant driver of the costs of electricity and gas distribution networks. The following three questions are answered: (1) Is connection density a significant cost driver in electricity and gas networks in the Netherlands?; (2) If so, which functional form (e.g. U-shaped) does this relationship have in the Netherlands?; (3) Finally, based on the evidence collected, is the influence of connection density sufficiently well-determined to be considered a regional difference in the Dutch regulatory framework?

  20. 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.

  1. Connecting primary care clinics and community pharmacies through a nationwide electronic prescribing network: A qualitative study

    Directory of Open Access Journals (Sweden)

    Marie-Pierre Gagnon

    2015-10-01

    Full Text Available Background The use of medication is at the heart of primary care, but is also the cause for major health concerns. It is therefore important to examine the prescription of medication process.Objective This study identifies the barriers and facilitators perceived by community pharmacists and primary care physicians concerning the adoption of a nationwide electronic prescribing (e-prescribing network in the province of Quebec, Canada.Methods We used purposive sampling to identify the most intensive users of the e-prescribing network. We conducted phone and in-person interviews. Interviews were transcribed, and we analysed their content with NVivo, using the clinical adoption framework (CAF for the codification of the data.Results We interviewed 33 pharmacists, 2 pharmacy technicians, 11 physicians and 3 clinic managers. Adoption of the e-prescribing network was fairly low. The respondents underlined adaptation of their work environment, openness to change and perception of benefits as facilitators to the adoption of the network. However, important barriers were perceived, including system quality issues and paper prescriptions being the only legal document in the prescribing process. Even if respondents recognised that the e-prescribing network can offer substantial benefits to the prescribing process, issues still persisted and raised barriers to the full use of such a network, especially in a context where different local information systems are connected within a nationwide e-prescribing network.Conclusion This study, based on the CAF, provides a better understanding of the factors related to the adoption of a nationwide e-prescribing network connecting primary care clinics and community pharmacies. 

  2. Rest but busy: Aberrant resting-state functional connectivity of triple network model in insomnia.

    Science.gov (United States)

    Dong, Xiaojuan; Qin, Haixia; Wu, Taoyu; Hu, Hua; Liao, Keren; Cheng, Fei; Gao, Dong; Lei, Xu

    2018-02-01

    One classical hypothesis among many models to explain the etiology and maintenance of insomnia disorder (ID) is hyperarousal. Aberrant functional connectivity among resting-state large-scale brain networks may be the underlying neurological mechanisms of this hypothesis. The aim of current study was to investigate the functional network connectivity (FNC) among large-scale brain networks in patients with insomnia disorder (ID) during resting state. In the present study, the resting-state fMRI was used to evaluate whether patients with ID showed aberrant FNC among dorsal attention network (DAN), frontoparietal control network (FPC), anterior default mode network (aDMN), and posterior default mode network (pDMN) compared with healthy good sleepers (HGSs). The Pearson's correlation analysis was employed to explore whether the abnormal FNC observed in patients with ID was associated with sleep parameters, cognitive and emotional scores, and behavioral performance assessed by questionnaires and tasks. Patients with ID had worse subjective thought control ability measured by Thought Control Ability Questionnaire (TCAQ) and more negative affect than HGSs. Intriguingly, relative to HGSs, patients with ID showed a significant increase in FNC between DAN and FPC, but a significant decrease in FNC between aDMN and pDMN. Exploratory analysis in patients with ID revealed a significantly positive correlation between the DAN-FPC FNC and reaction time (RT) of psychomotor vigilance task (PVT). The current study demonstrated that even during the resting state, the task-activated and task-deactivated large-scale brain networks in insomniacs may still maintain a hyperarousal state, looking quite similar to the pattern in a task condition with external stimuli. Those results support the hyperarousal model of insomnia.

  3. Effective connectivity within the frontoparietal control network differentiates cognitive control and working memory.

    Science.gov (United States)

    Harding, Ian H; Yücel, Murat; Harrison, Ben J; Pantelis, Christos; Breakspear, Michael

    2015-02-01

    Cognitive control and working memory rely upon a common fronto-parietal network that includes the inferior frontal junction (IFJ), dorsolateral prefrontal cortex (dlPFC), pre-supplementary motor area/dorsal anterior cingulate cortex (pSMA/dACC), and intraparietal sulcus (IPS). This network is able to flexibly adapt its function in response to changing behavioral goals, mediating a wide range of cognitive demands. Here we apply dynamic causal modeling to functional magnetic resonance imaging data to characterize task-related alterations in the strength of network interactions across distinct cognitive processes. Evidence in favor of task-related connectivity dynamics was accrued across a very large space of possible network structures. Cognitive control and working memory demands were manipulated using a factorial combination of the multi-source interference task and a verbal 2-back working memory task, respectively. Both were found to alter the sensitivity of the IFJ to perceptual information, and to increase IFJ-to-pSMA/dACC connectivity. In contrast, increased connectivity from the pSMA/dACC to the IPS, as well as from the dlPFC to the IFJ, was uniquely driven by cognitive control demands; a task-induced negative influence of the dlPFC on the pSMA/dACC was specific to working memory demands. These results reflect a system of both shared and unique context-dependent dynamics within the fronto-parietal network. Mechanisms supporting cognitive engagement, response selection, and action evaluation may be shared across cognitive domains, while dynamic updating of task and context representations within this network are potentially specific to changing demands on cognitive control. Copyright © 2014 Elsevier Inc. All rights reserved.

  4. 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

  5. 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.

  6. 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...

  7. 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

  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. Childhood poverty and stress reactivity are associated with aberrant functional connectivity in default mode network.

    Science.gov (United States)

    Sripada, Rebecca K; Swain, James E; Evans, Gary W; Welsh, Robert C; Liberzon, Israel

    2014-08-01

    Convergent research suggests that childhood poverty is associated with perturbation in the stress response system. This might extend to aberrations in the connectivity of large-scale brain networks, which subserve key cognitive and emotional functions. Resting-state brain activity was measured in adults with a documented history of childhood poverty (n=26) and matched controls from middle-income families (n=26). Participants also underwent a standard laboratory social stress test and provided saliva samples for cortisol assay. Childhood poverty was associated with reduced default mode network (DMN) connectivity. This, in turn, was associated with higher cortisol levels in anticipation of social stress. These results suggest a possible brain basis for exaggerated stress sensitivity in low-income individuals. Alterations in DMN may be associated with less efficient cognitive processing or greater risk for development of stress-related psychopathology among individuals who experienced the adversity of chronic childhood poverty.

  10. Functional brain connectivity is predictable from anatomic network's Laplacian eigen-structure.

    Science.gov (United States)

    Abdelnour, Farras; Dayan, Michael; Devinsky, Orrin; Thesen, Thomas; Raj, Ashish

    2018-05-15

    How structural connectivity (SC) gives rise to functional connectivity (FC) is not fully understood. Here we mathematically derive a simple relationship between SC measured from diffusion tensor imaging, and FC from resting state fMRI. We establish that SC and FC are related via (structural) Laplacian spectra, whereby FC and SC share eigenvectors and their eigenvalues are exponentially related. This gives, for the first time, a simple and analytical relationship between the graph spectra of structural and functional networks. Laplacian eigenvectors are shown to be good predictors of functional eigenvectors and networks based on independent component analysis of functional time series. A small number of Laplacian eigenmodes are shown to be sufficient to reconstruct FC matrices, serving as basis functions. This approach is fast, and requires no time-consuming simulations. It was tested on two empirical SC/FC datasets, and was found to significantly outperform generative model simulations of coupled neural masses. Copyright © 2018. Published by Elsevier Inc.

  11. 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

  12. Scaling of Airborne Ad-hoc Network Metrics with Link Range and Satellite Connectivity

    Directory of Open Access Journals (Sweden)

    Kai-Daniel BÜCHTER

    2018-06-01

    Full Text Available In this contribution, large-scale commercial aeronautical ad-hoc networks are evaluated. The investigation is based on a simulation environment with input from 2016 flight schedule and aircraft performance databases for flight movement modelling, along with a defined infrastructure of ground gateways and communication satellites. A cluster-based algorithm is used to build the communication network topology between aircraft. Cloud top pressure data can be considered to estimate cloud height and evaluate the impact of link obscuration on network availability, assuming a free-space optics-based communication network. The effects of communication range, satellite availability, fleet equipage ratio and clouds are discussed. It is shown how network reach and performance can be enhanced by adding taps to the network in the form of high-speed satellite links. The effect of adding these is two-fold: firstly, network reach can be increased by connecting remote aircraft clusters. Secondly, larger clusters can effectively be split into smaller ones in order to increase performance especially with regard to hop count and available overall capacity. In a realistic scenario concerning communication range and with moderate numbers of high-speed satellite terminals, on average, 78% of all widebody aircraft can be reached. With clouds considered (assuming laser links, this number reduces by 10%.

  13. 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.

  14. 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.

  15. 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.

  16. Interindividual differences in motor network connectivity and behavioral response to iTBS in stroke patients

    Directory of Open Access Journals (Sweden)

    Svenja Diekhoff-Krebs

    2017-01-01

    Full Text Available Cerebral plasticity-inducing approaches like repetitive transcranial magnetic stimulation (rTMS are of high interest in situations where reorganization of neural networks can be observed, e.g., after stroke. However, an increasing number of studies suggest that improvements in motor performance of the stroke-affected hand following modulation of primary motor cortex (M1 excitability by rTMS shows a high interindividual variability. We here tested the hypothesis that in stroke patients the interindividual variability of behavioral response to excitatory rTMS is related to interindividual differences in network connectivity of the stimulated region. Chronic stroke patients (n = 14 and healthy controls (n = 12 were scanned with functional magnetic resonance imaging (fMRI while performing a simple hand motor task. Dynamic causal modeling (DCM was used to investigate effective connectivity of key motor regions. On two different days after the fMRI experiment, patients received either intermittent theta-burst stimulation (iTBS over ipsilesional M1 or control stimulation over the parieto-occipital cortex. Motor performance and TMS parameters of cortical excitability were measured before and after iTBS. Our results revealed that patients with better motor performance of the affected hand showed stronger endogenous coupling between supplemental motor area (SMA and M1 before starting the iTBS intervention. Applying iTBS to ipsilesional M1 significantly increased ipsilesional M1 excitability and decreased contralesional M1 excitability as compared to control stimulation. Individual behavioral improvements following iTBS specifically correlated with neural coupling strengths in the stimulated hemisphere prior to stimulation, especially for connections targeting the stimulated M1. Combining endogenous connectivity and behavioral parameters explained 82% of the variance in hand motor performance observed after iTBS. In conclusion, the data suggest that

  17. Interindividual differences in motor network connectivity and behavioral response to iTBS in stroke patients.

    Science.gov (United States)

    Diekhoff-Krebs, Svenja; Pool, Eva-Maria; Sarfeld, Anna-Sophia; Rehme, Anne K; Eickhoff, Simon B; Fink, Gereon R; Grefkes, Christian

    2017-01-01

    Cerebral plasticity-inducing approaches like repetitive transcranial magnetic stimulation (rTMS) are of high interest in situations where reorganization of neural networks can be observed, e.g., after stroke. However, an increasing number of studies suggest that improvements in motor performance of the stroke-affected hand following modulation of primary motor cortex (M1) excitability by rTMS shows a high interindividual variability. We here tested the hypothesis that in stroke patients the interindividual variability of behavioral response to excitatory rTMS is related to interindividual differences in network connectivity of the stimulated region. Chronic stroke patients ( n  = 14) and healthy controls ( n  = 12) were scanned with functional magnetic resonance imaging (fMRI) while performing a simple hand motor task. Dynamic causal modeling (DCM) was used to investigate effective connectivity of key motor regions. On two different days after the fMRI experiment, patients received either intermittent theta-burst stimulation (iTBS) over ipsilesional M1 or control stimulation over the parieto-occipital cortex. Motor performance and TMS parameters of cortical excitability were measured before and after iTBS. Our results revealed that patients with better motor performance of the affected hand showed stronger endogenous coupling between supplemental motor area (SMA) and M1 before starting the iTBS intervention. Applying iTBS to ipsilesional M1 significantly increased ipsilesional M1 excitability and decreased contralesional M1 excitability as compared to control stimulation. Individual behavioral improvements following iTBS specifically correlated with neural coupling strengths in the stimulated hemisphere prior to stimulation, especially for connections targeting the stimulated M1. Combining endogenous connectivity and behavioral parameters explained 82% of the variance in hand motor performance observed after iTBS. In conclusion, the data suggest that the

  18. 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.

  19. Control of Three-Phase Grid-Connected Microgrids Using Artificial Neural Networks

    OpenAIRE

    Shuhui, L.; Fu, X.; Jaithwa, I.; Alonso, E.; Fairbank, M.; Wunsch, D. C.

    2015-01-01

    A microgrid consists of a variety of inverter-interfaced distributed energy resources (DERs). A key issue is how to control DERs within the microgrid and how to connect them to or disconnect them from the microgrid quickly. This paper presents a strategy for controlling inverter-interfaced DERs within a microgrid using an artificial neural network, which implements a dynamic programming algorithm and is trained with a new Levenberg-Marquardt backpropagation algorithm. Compared to conventional...

  20. 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

    2018-06-01

    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.

  1. 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 ...

  2. Close encounters: Analyzing how social similarity and propinquity contribute to strong network connections.

    OpenAIRE

    Reagans, Ray Eugene

    2010-01-01

    Models of network formation emphasize the importance of social similarity and propinquity in producing strong interpersonal connections. The positive effect each factor can have on tie strength has been documented across a number of studies, and yet we know surprisingly very little about how the two factors combine to produce strong ties. Being in close proximity could either amplify or dampen the positive effect that social similarity can have on tie strength. Data on tie strength among teac...

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

    OpenAIRE

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

    2016-01-01

    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 source for humor and information, others sharing a common background, as well as relationship maintenance) and inspirational motives (i.e., others providing a target for upward social comparison) c...

  4. The role of degree distribution in shaping the dynamics in networks of sparsely connected spiking neurons

    Directory of Open Access Journals (Sweden)

    Alex eRoxin

    2011-03-01

    Full Text Available Neuronal network models often assume a fixed probability of connectionbetween neurons. This assumption leads to random networks withbinomial in-degree and out-degree distributions which are relatively narrow. Here I study the effect of broaddegree distributions on network dynamics by interpolating between abinomial and a truncated powerlaw distribution for the in-degree andout-degree independently. This is done both for an inhibitory network(I network as well as for the recurrent excitatory connections in anetwork of excitatory and inhibitory neurons (EI network. In bothcases increasing the width of the in-degree distribution affects theglobal state of the network by driving transitions betweenasynchronous behavior and oscillations. This effect is reproduced ina simplified rate model which includes the heterogeneity in neuronalinput due to the in-degree of cells. On the other hand, broadeningthe out-degree distribution is shown to increase the fraction ofcommon inputs to pairs of neurons. This leads to increases in theamplitude of the cross-correlation (CC of synaptic currents. In thecase of the I network, despite strong oscillatory CCs in the currents, CCs of the membrane potential are low due to filtering and reset effects, leading to very weak CCs of the spikecount. In the asynchronous regime ofthe EI network, broadening the out-degree increases the amplitude ofCCs in the recurrent excitatory currents, while CC of the totalcurrent is essentially unaffected as are pairwise spikingcorrelations. This is due to a dynamic balance between excitatoryand inhibitory synaptic currents. In the oscillatory regime, changesin the out-degree can have a large effect on spiking correlations andeven on the qualitative dynamical state of the network.

  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. Network inter-connectivity and capacity reservation behaviour: an investigation of the Belgian gas transmission network

    International Nuclear Information System (INIS)

    Cuijpers, Ch.; Woitrin, D.

    2009-01-01

    Lack of cross-border integration explains largely why natural gas markets remain basically national in scope, with levels of concentration similarly high as when the liberalization process commenced. This paper presents the results of an assessment of the upstream/downstream capacity of the Belgian natural gas transmission network which is highly interconnected with adjacent networks and fosters important transit activities. It is shown that the tendency to a better market coupling still suffers from important mismatches of capacity provisions on both sides of cross-border interconnections. Moreover, shippers use gas transmission networks more and more from a commercial portfolio perspective which goes beyond the traditional security of supply purpose of network designs. Capacity booking rates appear to be significantly higher than the underlying physical gas flows. From these findings, the paper contributes to a better understanding of the market barrier created by contractual congestion at cross-border interconnection points. The paper argues that contractual congestion is a symptom of suboptimal cooperation of adjacent network operators and lack of effective mechanisms to bring booked but non-used capacity back to the market, rather than an indicator for an overall need to increase investment budgets. (authors)

  7. A triple network connectivity study of large-scale brain systems in cognitively normal APOE4 carriers

    Directory of Open Access Journals (Sweden)

    Xia Wu

    2016-09-01

    Full Text Available The triple network model, consisting of the central executive network, salience network and default mode network, has been recently employed to understand dysfunction in core networks across various disorders. Here we used the triple network model to investigate the large-scale brain networks in cognitively normal APOE4 carriers who are at risk of Alzheimer’s disease (AD. To explore the functional connectivity for each of the three networks and the effective connectivity among them, we evaluated 17 cognitively normal individuals with a family history of AD and at least one copy of the apolipoprotein e4 (APOE4 allele and compared the findings to those of 12 individuals who did not carry the APOE4 gene or have a family history of AD, using independent component analysis and Bayesian network approach. Our findings indicated altered within-network connectivity that suggests future cognitive decline risk, and preserved between-network connectivity that may support their current preserved cognition in the cognitively normal APOE4 allele carries. The study provides novel sights into our understanding of the risk factors for AD and their influence on the triple network model of major psychopathology.

  8. 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

  9. 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.

  10. 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.

  11. 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

  12. Frequency-Dependent Altered Functional Connections of Default Mode Network in Alzheimer’s Disease

    Directory of Open Access Journals (Sweden)

    Youjun Li

    2017-08-01

    Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder associated with the progressive dysfunction of cognitive ability. Previous research has indicated that the default mode network (DMN is closely related to cognition and is impaired in Alzheimer’s disease. Because recent studies have shown that different frequency bands represent specific physiological functions, DMN functional connectivity studies of the different frequency bands based on resting state fMRI (RS-fMRI data may provide new insight into AD pathophysiology. In this study, we explored the functional connectivity based on well-defined DMN regions of interest (ROIs from the five frequency bands: slow-5 (0.01–0.027 Hz, slow-4 (0.027–0.073 Hz, slow-3 (0.073–0.198 Hz, slow-2 (0.198–0.25 Hzs and standard low-frequency oscillations (LFO (0.01–0.08 Hz. We found that the altered functional connectivity patterns are mainly in the frequency band of slow-5 and slow-4 and that the decreased connections are long distance, but some relatively short connections are increased. In addition, the altered functional connections of the DMN in AD are frequency dependent and differ between the slow-5 and slow-4 bands. Mini-Mental State Examination scores were significantly correlated with the altered functional connectivity patterns in the slow-5 and slow-4 bands. These results indicate that frequency-dependent functional connectivity changes might provide potential biomarkers for AD pathophysiology.

  13. 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; Repovš, Grega; Barch, Deanna M

    2012-09-01

    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 preschool depression. DMN functional connectivity was assessed using resting state functional connectivity magnetic resonance imaging data and the posterior cingulate (PCC) as a seed region of interest. Thirty-nine medication naïve school age children (21 with a history of preschool depression and 18 healthy peers) and their families who were ascertained as preschoolers and prospectively assessed over at least 4 annual waves as part of a federally funded study of preschool depression were included.   Decreased connectivity between the PCC and regions within the middle temporal gyrus (MTG), inferior parietal lobule, and cerebellum was found in children with known depression during the preschool period. Increased connectivity between the PCC and regions within the subgenual and anterior cingulate cortices and anterior MTG bilaterally was also found in these children. Additionally, a clinically relevant 'brain-behavior' relationship between atypical functional connectivity of the PCC and disruptions in emotion regulation was identified. To our knowledge, this is the first study to examine the DMN in children known to have experienced the onset of a clinically significant depressive syndrome during preschool. Results suggest that a history of preschool depression is associated with atypical DMN connectivity. However, longitudinal studies are needed to clarify whether the current findings of atypical DMN connectivity are a precursor or a consequence of preschool depression. © 2012 The Authors. Journal of Child Psychology and Psychiatry © 2012 Association for Child and Adolescent Mental Health.

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

    Energy Technology Data Exchange (ETDEWEB)

    Li, Shumei; Tian, Junzhang; Li, Meng; Wang, Tianyue; Lin, Chulan; Yin, Yi; Jiang, Guihua [Guangdong Second Provincial General Hospital, Department of Medical Imaging, Guangzhou (China); Zeng, Luxian [Guangdong Second Provincial General Hospital, Department of Science and Education, Guangzhou (China); Li, Cheng [Guangdong Second Provincial General Hospital, Department of Renal Transplantation, Guangzhou (China)

    2018-02-15

    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.)

  15. Protein complex prediction based on k-connected subgraphs in protein interaction network

    Directory of Open Access Journals (Sweden)

    Habibi Mahnaz

    2010-09-01

    Full Text Available Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on connectivity number on subgraphs. We evaluate CFA using several protein interaction networks on reference protein complexes in two benchmark data sets (MIPS and Aloy, containing 1142 and 61 known complexes respectively. We compare CFA to some existing protein complex prediction methods (CMC, MCL, PCP and RNSC in terms of recall and precision. We show that CFA predicts more complexes correctly at a competitive level of precision. Conclusions Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number. Our CFA program and results are freely available from http://www.bioinf.cs.ipm.ir/softwares/cfa/CFA.rar.

  16. 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.

  17. Earlier adolescent substance use onset predicts stronger connectivity between reward and cognitive control brain networks.

    Science.gov (United States)

    Weissman, David G; Schriber, Roberta A; Fassbender, Catherine; Atherton, Olivia; Krafft, Cynthia; Robins, Richard W; Hastings, Paul D; Guyer, Amanda E

    2015-12-01

    Early adolescent onset of substance use is a robust predictor of future substance use disorders. We examined the relation between age of substance use initiation and resting state functional connectivity (RSFC) of the core reward processing (nucleus accumbens; NAcc) to cognitive control (prefrontal cortex; PFC) brain networks. Adolescents in a longitudinal study of Mexican-origin youth reported their substance use annually from ages 10 to 16 years. At age 16, 69 adolescents participated in a resting state functional magnetic resonance imaging scan. Seed-based correlational analyses were conducted using regions of interest in bilateral NAcc. The earlier that adolescents initiated substance use, the stronger the connectivity between bilateral NAcc and right dorsolateral PFC, right dorsomedial PFC, right pre-supplementary motor area, right inferior parietal lobule, and left medial temporal gyrus. The regions that demonstrated significant positive linear relationships between the number of adolescent years using substances and connectivity with NAcc are nodes in the right frontoparietal network, which is central to cognitive control. The coupling of reward and cognitive control networks may be a mechanism through which earlier onset of substance use is related to brain function over time, a trajectory that may be implicated in subsequent substance use disorders. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  18. 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.)

  19. Dynamic facial expressions evoke distinct activation in the face perception network: a connectivity analysis study.

    Science.gov (United States)

    Foley, Elaine; Rippon, Gina; Thai, Ngoc Jade; Longe, Olivia; Senior, Carl

    2012-02-01

    Very little is known about the neural structures involved in the perception of realistic dynamic facial expressions. In the present study, a unique set of naturalistic dynamic facial emotional expressions was created. Through fMRI and connectivity analysis, a dynamic face perception network was identified, which is demonstrated to extend Haxby et al.'s [Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. The distributed human neural system for face perception. Trends in Cognitive Science, 4, 223-233, 2000] distributed neural system for face perception. This network includes early visual regions, such as the inferior occipital gyrus, which is identified as insensitive to motion or affect but sensitive to the visual stimulus, the STS, identified as specifically sensitive to motion, and the amygdala, recruited to process affect. Measures of effective connectivity between these regions revealed that dynamic facial stimuli were associated with specific increases in connectivity between early visual regions, such as the inferior occipital gyrus and the STS, along with coupling between the STS and the amygdala, as well as the inferior frontal gyrus. These findings support the presence of a distributed network of cortical regions that mediate the perception of different dynamic facial expressions.

  20. Increased Default Mode Network Connectivity in Obsessive–Compulsive Disorder During Reward Processing

    Directory of Open Access Journals (Sweden)

    Kathrin Koch

    2018-06-01

    Full Text Available Objective: Obsessive-compulsive disorder (OCD is characterized by anxiety-provoking, obsessive thoughts (i.e., obsessions which patients react to with compulsive behaviors (i.e., compulsions. Due to the transient feeling of relief following the reduction of obsession-induced anxiety, compulsions are often described as relieving or even rewarding. Several studies investigated functional activation during reward processing in OCD, but findings are heterogeneous up to now and little is known about potential alterations in functional connectivity.Method: Against this background we studied OCD patients (n = 44 and healthy controls (n = 37 during the receipt of monetary reward by assessing both activation and functional connectivity.Results: Patients showed a decreased activation in several frontal regions and the posterior cingulate (PCC, BA31 together with a stronger connectivity between the PCC and the vmPFC (BA10.Conclusion: Present findings demonstrate an increased connectivity in patients within major nodes of the default mode network (DMN—a network known to be involved in the evaluation of internal mental states. These results may indicate an increased activity of internal, self-related processing at the expense of a normal responsiveness toward external rewards and incentives. This, in turn, may explain the constant urge for additional reinforcement and patients' inability to inhibit their compulsive behaviors.

  1. 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.

  2. Abnormal resting-state connectivity of motor and cognitive networks in early manifest Huntington's disease.

    Science.gov (United States)

    Wolf, R C; Sambataro, F; Vasic, N; Depping, M S; Thomann, P A; Landwehrmeyer, G B; Süssmuth, S D; Orth, M

    2014-11-01

    Functional magnetic resonance imaging (fMRI) of multiple neural networks during the brain's 'resting state' could facilitate biomarker development in patients with Huntington's disease (HD) and may provide new insights into the relationship between neural dysfunction and clinical symptoms. To date, however, very few studies have examined the functional integrity of multiple resting state networks (RSNs) in manifest HD, and even less is known about whether concomitant brain atrophy affects neural activity in patients. Using MRI, we investigated brain structure and RSN function in patients with early HD (n = 20) and healthy controls (n = 20). For resting-state fMRI data a group-independent component analysis identified spatiotemporally distinct patterns of motor and prefrontal RSNs of interest. We used voxel-based morphometry to assess regional brain atrophy, and 'biological parametric mapping' analyses to investigate the impact of atrophy on neural activity. Compared with controls, patients showed connectivity changes within distinct neural systems including lateral prefrontal, supplementary motor, thalamic, cingulate, temporal and parietal regions. In patients, supplementary motor area and cingulate cortex connectivity indices were associated with measures of motor function, whereas lateral prefrontal connectivity was associated with cognition. This study provides evidence for aberrant connectivity of RSNs associated with motor function and cognition in early manifest HD when controlling for brain atrophy. This suggests clinically relevant changes of RSN activity in the presence of HD-associated cortical and subcortical structural abnormalities.

  3. 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.

  4. 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.

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

    Science.gov (United States)

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

    2016-04-01

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

  6. Bipartite Network Analysis of the Archaeal Virosphere: Evolutionary Connections between Viruses and Capsidless Mobile Elements.

    Science.gov (United States)

    Iranzo, Jaime; Koonin, Eugene V; Prangishvili, David; Krupovic, Mart

    2016-12-15

    Archaea and particularly hyperthermophilic crenarchaea are hosts to many unusual viruses with diverse virion shapes and distinct gene compositions. As is typical of viruses in general, there are no universal genes in the archaeal virosphere. Therefore, to obtain a comprehensive picture of the evolutionary relationships between viruses, network analysis methods are more productive than traditional phylogenetic approaches. Here we present a comprehensive comparative analysis of genomes and proteomes from all currently known taxonomically classified and unclassified, cultivated and uncultivated archaeal viruses. We constructed a bipartite network of archaeal viruses that includes two classes of nodes, the genomes and gene families that connect them. Dissection of this network using formal community detection methods reveals strong modularity, with 10 distinct modules and 3 putative supermodules. However, compared to similar previously analyzed networks of eukaryotic and bacterial viruses, the archaeal virus network is sparsely connected. With the exception of the tailed viruses related to bacteriophages of the order Caudovirales and the families Turriviridae and Sphaerolipoviridae that are linked to a distinct supermodule of eukaryotic and bacterial viruses, there are few connector genes shared by different archaeal virus modules. In contrast, most of these modules include, in addition to viruses, capsidless mobile elements, emphasizing tight evolutionary connections between the two types of entities in archaea. The relative contributions of distinct evolutionary origins, in particular from nonviral elements, and insufficient sampling to the sparsity of the archaeal virus network remain to be determined by further exploration of the archaeal virosphere. Viruses infecting archaea are among the most mysterious denizens of the virosphere. Many of these viruses display no genetic or even morphological relationship to viruses of bacteria and eukaryotes, raising questions

  7. 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

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

    Science.gov (United States)

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

    2010-10-25

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

  9. Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks

    Science.gov (United States)

    Amin, Hayder; Maccione, Alessandro; Nieus, Thierry

    2017-01-01

    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. PMID:28749937

  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.

    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.

  12. [Functional connectivity and complex networks in focal epilepsy. Pathophysiology and therapeutic implications].

    Science.gov (United States)

    Pastor, Jesús; Sola, Rafael G; Vega-Zelaya, Lorena; Garnes, Óscar; Ortega, Guillermo J

    2014-05-01

    The traditional surgical approach to treat drug-resistant focal epileptic patients is in the resection or disconnection of the epileptic focus. However, a significant minority of patients continue to experience seizures after surgery, which shows the incomplete level of knowledge that currently we have of this pathology. This paper introduces some concepts of functional connectivity and complex networks methodology with its application to the study of neurophysiological recordings from patients suffering from drug-resistant focal epilepsy. In order to fully understand the new developments in the area of complex networks and its applications to the study of epilepsy, we will here review fundamental concepts in complex networks methodology, synchronization and functional connectivity. Some of the most recent published works dealing with focal epilepsy viewed under this new perspective will be revised and commented. We think that a wider perspective in the study of epilepsy, such as the one reviewed in this work, will allow epileptologists to consider surgical alternatives in the usual treatment of focal epilepsy at those currently performed in most medical centers around the world. Combining the traditional knowledge with new insights provided by network theory will certainly fill many of the gaps we have today in the fragmented understanding of epilepsy.

  13. 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.

  14. 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.

    2015-01-01

    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 the cerebro-cerebellar interactions in cognitive function. These data provide support for the potential targeting of CerDMN areas for therapeutic interventions in ADHD. PMID:26109476

  15. 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.

  16. 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.

  17. Coordinated system services from offshore wind power plants connected through HVDC networks

    DEFF Research Database (Denmark)

    Zeni, Lorenzo; Glasdam, Jakob; Hesselbæk, Bo

    2014-01-01

    This paper presents an overview of power system services in networks involving multiple onshore power systems, a voltage sourced converter (VSC) based high voltage direct current (HVDC) offshore network and an offshore wind power plant (OWPP). A comprehensive list of services regarding onshore...... as well as offshore network operation – both AC and DC – will be discussed from a state of the art perspective. Among them, the most interesting have been selected and will be treated in more detail and the main contribution of this paper will be to shed light on the most relevant aspects related...... to their implementation. For example, new findings on onshore AC voltage control are reported, that help the characterisation of potential AC voltage control that a VSC-HVDC station may offer to an onshore AC grid. The HVDC system behind the VSC-HVDC station may connect, through other converters, to another AC power...

  18. Detection of anomalous events

    Science.gov (United States)

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

    2016-06-07

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

  19. 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

  20. 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.

  1. Anterior-Posterior Connectivity within the Default Mode Network Increases During Maturation.

    Science.gov (United States)

    Washington, Stuart D; VanMeter, John W

    The default mode network (DMN) supports self-referential thought processes important for successful socialization including: theory-of-mind, episodic memory, and prospection. Connectivity between DMN's nodes, which are distributed between the frontal, temporal, and parietal lobes, change with age and may continue changing into adulthood. We have previously explored the maturation of functional connections in the DMN as they relate to autism spectrum disorder (ASD) in children 6 to 18 years of age. In this chapter, we refine our earlier study of DMN functional maturation by focusing on the development of inter-nodal connectivity in a larger pool of typically developing people 6 to 25 years of age (mean = 13.22 years ± 5.36 s.d.; N = 36; 42% female). Correlations in BOLD activity (Fisher's Z) between ROIs revealed varying strengths of functional connectivity between regions, the strongest of which was between the left and right inferior parietal lobules or IPLs (Z = 0.62 ± 0.25 s.d.) and the weakest of which was between the posterior cingulate cortex (PCC) and right middle temporal gyrus or MTG (Z = 0.06 ± 0.22 s.d.). Further, connectivity between two pairs of DMN nodes significantly increased as a quadratic function of age ( p maturational trajectory.

  2. Altered resting-state connectivity within default mode network associated with late chronotype.

    Science.gov (United States)

    Horne, Charlotte Mary; Norbury, Ray

    2018-04-20

    Current evidence suggests late chronotype individuals have an increased risk of developing depression. However, the underlying neural mechanisms of this association are not fully understood. Forty-six healthy, right-handed individuals free of current or previous diagnosis of depression, family history of depression or sleep disorder underwent resting-state functional Magnetic Resonance Imaging (rsFMRI). Using an Independent Component Analysis (ICA) approach, the Default Mode Network (DMN) was identified based on a well validated template. Linear effects of chronotype on DMN connectivity were tested for significance using non-parametric permutation tests (applying 5000 permutations). Sleep quality, age, gender, measures of mood and anxiety, time of scan and cortical grey matter volume were included as covariates in the regression model. A significant positive correlation between chronotype and functional connectivity within nodes of the DMN was observed, including; bilateral PCC and precuneus, such that later chronotype (participants with lower rMEQ scores) was associated with decreased connectivity within these regions. The current results appear consistent with altered DMN connectivity in depressed patients and weighted evidence towards reduced DMN connectivity in other at-risk populations which may, in part, explain the increased vulnerability for depression in late chronotype individuals. The effect may be driven by self-critical thoughts associated with late chronotype although future studies are needed to directly investigate this. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. 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.

  4. 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.