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Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-15

...-Location Fee Schedule Regarding Low Latency Network Connections; Correction AGENCY: Securities And Exchange Commission. ACTION: Notice; correction. SUMMARY: The Securities and Exchange Commission published a document... SECURITIES AND EXCHANGE COMMISSION [Release No. 34-65689A; File No. SR-Phlx-2011-142] Self...

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Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-21

... in the Exchange's Data Center November 15, 2013. Pursuant to Section 19(b)(1) \\1\\ of the Securities... have been prepared by the self-regulatory organization. The Commission is publishing this notice to... lower-latency 10 gigabit (``Gb'') Liquidity Center Network (``LCN'') connection in the Exchange's data...

Design of a network for concurrent message passing systems

NASA Astrophysics Data System (ADS)

Song, Paul Y.

1988-08-01

We describe the design of the network design frame (NDF), a self-timed routing chip for a message-passing concurrent computer. The NDF uses a partitioned data path, low-voltage output drivers, and a distributed token-passing arbiter to provide a bandwidth of 450 Mbits/sec into the network. Wormhole routing and bidirectional virtual channels are used to provide low latency communications, less than 2us latency to deliver a 216 bit message across the diameter of a 1K node mess-connected machine. To support concurrent software systems, the NDF provides two logical networks, one for user messages and one for system messages. The two networks share the same set of physical wires. To facilitate the development of network nodes, the NDF is a design frame. The NDF circuitry is integrated into the pad frame of a chip leaving the center of the chip uncommitted. We define an analytic framework in which to study the effects of network size, network buffering capacity, bidirectional channels, and traffic on this class of networks. The response of the network to various combinations of these parameters are obtained through extensive simulation of the network model. Through simulation, we are able to observe the macro behavior of the network as opposed to the micro behavior of the NDF routing controller.

Network characteristics for server selection in online games

NASA Astrophysics Data System (ADS)

Claypool, Mark

2008-01-01

Online gameplay is impacted by the network characteristics of players connected to the same server. Unfortunately, the network characteristics of online game servers are not well-understood, particularly for groups that wish to play together on the same server. As a step towards a remedy, this paper presents analysis of an extensive set of measurements of game servers on the Internet. Over the course of many months, actual Internet game servers were queried simultaneously by twenty-five emulated game clients, with both servers and clients spread out on the Internet. The data provides statistics on the uptime and populations of game servers over a month long period an an in-depth look at the suitability for game servers for multi-player server selection, concentrating on characteristics critical to playability--latency and fairness. Analysis finds most game servers have latencies suitable for third-person and omnipresent games, such as real-time strategy, sports and role-playing games, providing numerous server choices for game players. However, far fewer game servers have the low latencies required for first-person games, such as shooters or race games. In all cases, groups that wish to play together have a greatly reduced set of servers from which to choose because of inherent unfairness in server latencies and server selection is particularly limited as the group size increases. These results hold across different game types and even across different generations of games. The data should be useful for game developers and network researchers that seek to improve game server selection, whether for single or multiple players.

Latency causes and reduction in optical metro networks

NASA Astrophysics Data System (ADS)

Bobrovs, Vjaceslavs; Spolitis, Sandis; Ivanovs, Girts

2013-12-01

The dramatic growth of transmitted information in fiber optical networks is leading to a concern about the network latency for high-speed reliable services like financial transactions, telemedicine, virtual and augmented reality, surveillance, and other applications. In order to ensure effective latency engineering, the delay variability needs to be accurately monitored and measured, in order to control it. This paper in brief describes causes of latency in fiber optical metro networks. Several available latency reduction techniques and solutions are also discussed, namely concerning usage of different chromatic dispersion compensation methods, low-latency amplifiers, optical fibers as well as other network elements.

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

NASA Astrophysics Data System (ADS)

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.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Dong; Heidelberger, Philip; Sugawara, Yutaka

An apparatus and method for extending the scalability and improving the partitionability of networks that contain all-to-all links for transporting packet traffic from a source endpoint to a destination endpoint with low per-endpoint (per-server) cost and a small number of hops. An all-to-all wiring in the baseline topology is decomposed into smaller all-to-all components in which each smaller all-to-all connection is replaced with star topology by using global switches. Stacking multiple copies of the star topology baseline network creates a multi-planed switching topology for transporting packet traffic. Point-to-point unified stacking method using global switch wiring methods connects multiple planes ofmore » a baseline topology by using the global switches to create a large network size with a low number of hops, i.e., low network latency. Grouped unified stacking method increases the scalability (network size) of a stacked topology.« less

Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression

PubMed Central

Onesto, Valentina; Cosentino, Carlo; Di Fabrizio, Enzo; Cesarelli, Mario; Amato, Francesco; Gentile, Francesco

2016-01-01

Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect. PMID:27403421

Latency Hiding in Dynamic Partitioning and Load Balancing of Grid Computing Applications

NASA Technical Reports Server (NTRS)

Das, Sajal K.; Harvey, Daniel J.; Biswas, Rupak

2001-01-01

The Information Power Grid (IPG) concept developed by NASA is aimed to provide a metacomputing platform for large-scale distributed computations, by hiding the intricacies of highly heterogeneous environment and yet maintaining adequate security. In this paper, we propose a latency-tolerant partitioning scheme that dynamically balances processor workloads on the.IPG, and minimizes data movement and runtime communication. By simulating an unsteady adaptive mesh application on a wide area network, we study the performance of our load balancer under the Globus environment. The number of IPG nodes, the number of processors per node, and the interconnected speeds are parameterized to derive conditions under which the IPG would be suitable for parallel distributed processing of such applications. Experimental results demonstrate that effective solution are achieved when the IPG nodes are connected by a high-speed asynchronous interconnection network.

Six-port optical switch for cluster-mesh photonic network-on-chip

NASA Astrophysics Data System (ADS)

Jia, Hao; Zhou, Ting; Zhao, Yunchou; Xia, Yuhao; Dai, Jincheng; Zhang, Lei; Ding, Jianfeng; Fu, Xin; Yang, Lin

2018-05-01

Photonic network-on-chip for high-performance multi-core processors has attracted substantial interest in recent years as it offers a systematic method to meet the demand of large bandwidth, low latency and low power dissipation. In this paper we demonstrate a non-blocking six-port optical switch for cluster-mesh photonic network-on-chip. The architecture is constructed by substituting three optical switching units of typical Spanke-Benes network to optical waveguide crossings. Compared with Spanke-Benes network, the number of optical switching units is reduced by 20%, while the connectivity of routing path is maintained. By this way the footprint and power consumption can be reduced at the expense of sacrificing the network latency performance in some cases. The device is realized by 12 thermally tuned silicon Mach-Zehnder optical switching units. Its theoretical spectral responses are evaluated by establishing a numerical model. The experimental spectral responses are also characterized, which indicates that the optical signal-to-noise ratios of the optical switch are larger than 13.5 dB in the wavelength range from 1525 nm to 1565 nm. Data transmission experiment with the data rate of 32 Gbps is implemented for each optical link.

A secure 3-way routing protocols for intermittently connected mobile ad hoc networks.

PubMed

Sekaran, Ramesh; Parasuraman, Ganesh Kumar

2014-01-01

The mobile ad hoc network may be partially connected or it may be disconnected in nature and these forms of networks are termed intermittently connected mobile ad hoc network (ICMANET). The routing in such disconnected network is commonly an arduous task. Many routing protocols have been proposed for routing in ICMANET since decades. The routing techniques in existence for ICMANET are, namely, flooding, epidemic, probabilistic, copy case, spray and wait, and so forth. These techniques achieve an effective routing with minimum latency, higher delivery ratio, lesser overhead, and so forth. Though these techniques generate effective results, in this paper, we propose novel routing algorithms grounded on agent and cryptographic techniques, namely, location dissemination service (LoDiS) routing with agent AES, A-LoDiS with agent AES routing, and B-LoDiS with agent AES routing, ensuring optimal results with respect to various network routing parameters. The algorithm along with efficient routing ensures higher degree of security. The security level is cited testing with respect to possibility of malicious nodes into the network. This paper also aids, with the comparative results of proposed algorithms, for secure routing in ICMANET.

A Secure 3-Way Routing Protocols for Intermittently Connected Mobile Ad Hoc Networks

PubMed Central

Parasuraman, Ganesh Kumar

2014-01-01

The mobile ad hoc network may be partially connected or it may be disconnected in nature and these forms of networks are termed intermittently connected mobile ad hoc network (ICMANET). The routing in such disconnected network is commonly an arduous task. Many routing protocols have been proposed for routing in ICMANET since decades. The routing techniques in existence for ICMANET are, namely, flooding, epidemic, probabilistic, copy case, spray and wait, and so forth. These techniques achieve an effective routing with minimum latency, higher delivery ratio, lesser overhead, and so forth. Though these techniques generate effective results, in this paper, we propose novel routing algorithms grounded on agent and cryptographic techniques, namely, location dissemination service (LoDiS) routing with agent AES, A-LoDiS with agent AES routing, and B-LoDiS with agent AES routing, ensuring optimal results with respect to various network routing parameters. The algorithm along with efficient routing ensures higher degree of security. The security level is cited testing with respect to possibility of malicious nodes into the network. This paper also aids, with the comparative results of proposed algorithms, for secure routing in ICMANET. PMID:25136697

Going End to End to Deliver High-Speed Data

NASA Technical Reports Server (NTRS)

2005-01-01

By the end of the 1990s, the optical fiber "backbone" of the telecommunication and data-communication networks had evolved from megabits-per-second transmission rates to gigabits-per-second transmission rates. Despite this boom in bandwidth, however, users at the end nodes were still not being reached on a consistent basis. (An end node is any device that does not behave like a router or a managed hub or switch. Examples of end node objects are computers, printers, serial interface processor phones, and unmanaged hubs and switches.) The primary reason that prevents bandwidth from reaching the end nodes is the complex local network topology that exists between the optical backbone and the end nodes. This complex network topology consists of several layers of routing and switch equipment which introduce potential congestion points and network latency. By breaking down the complex network topology, a true optical connection can be achieved. Access Optical Networks, Inc., is making this connection a reality with guidance from NASA s nondestructive evaluation experts.

Delayed and Temporally Imprecise Neurotransmission in Reorganizing Cortical Microcircuits

PubMed Central

Barnes, Samuel J.; Cheetham, Claire E.; Liu, Yan; Bennett, Sophie H.; Albieri, Giorgia; Jorstad, Anne A.; Knott, Graham W.

2015-01-01

Synaptic neurotransmission is modified at cortical connections throughout life. Varying the amplitude of the postsynaptic response is one mechanism that generates flexible signaling in neural circuits. The timing of the synaptic response may also play a role. Here, we investigated whether weakening and loss of an entire connection between excitatory cortical neurons was foreshadowed in the timing of the postsynaptic response. We made electrophysiological recordings in rat primary somatosensory cortex that was undergoing experience-dependent loss of complete local excitatory connections. The synaptic latency of pyramid–pyramid connections, which typically comprise multiple synapses, was longer and more variable. Connection strength and latency were not correlated. Instead, prolonged latency was more closely related to progression of connection loss. The action potential waveform and axonal conduction velocity were unaffected, suggesting that the altered timing of neurotransmission was attributable to a synaptic mechanism. Modeling studies indicated that increasing the latency and jitter at a subset of synapses reduced the number of action potentials fired by a postsynaptic neuron. We propose that prolonged synaptic latency and diminished temporal precision of neurotransmission are hallmarks of impending loss of a cortical connection. PMID:26085628

SDN-controlled topology-reconfigurable optical mobile fronthaul architecture for bidirectional CoMP and low latency inter-cell D2D in the 5G mobile era.

PubMed

Cvijetic, Neda; Tanaka, Akihiro; Kanonakis, Konstantinos; Wang, Ting

2014-08-25

We demonstrate the first SDN-controlled optical topology-reconfigurable mobile fronthaul (MFH) architecture for bidirectional coordinated multipoint (CoMP) and low latency inter-cell device-to-device (D2D) connectivity in the 5G mobile networking era. SDN-based OpenFlow control is used to dynamically instantiate the CoMP and inter-cell D2D features as match/action combinations in control plane flow tables of software-defined optical and electrical switching elements. Dynamic re-configurability is thereby introduced into the optical MFH topology, while maintaining back-compatibility with legacy fiber deployments. 10 Gb/s peak rates with <7 μs back-to-back transmission latency and 29.6 dB total power budget are experimentally demonstrated, confirming the attractiveness of the new approach for optical MFH of future 5G mobile systems.

Evaluation of Real-Time Ground-Based GPS Meteorology

NASA Astrophysics Data System (ADS)

Fang, P.; Bock, Y.; Gutman, S.

2003-04-01

We demonstrate and evaluate a system to estimate zenith tropospheric delays in real time (5-10 minute latency) based on the technique of instantaneous GPS positioning as described by Bock et al. [2000] using data from the Orange County Real Time GPS Network. OCRTN is an upgrade of a sub-network of SCIGN sites in southern California to low latency (1-2 sec), high-rate (1 Hz) data streaming. Currently, ten sites are streaming data (Ashtech binary MBEN format) by means of dedicated, point-to-point radio modems to a network hub that translates the asynchronous serial data to TCP/IP and onto a PC workstation residing on a local area network. Software residing on the PC allows multiple clients to access the raw data simultaneously though TCP/IP. One of the clients is a Geodetics RTD server that receives and archives (1) the raw 1 Hz network data, (2) estimates of instantaneous positions and zenith tropospheric delays, and (3) RINEX data to decimated to 30 seconds. The network is composed of ten sites. The distribution of nine of the sites approximates a right triangle with two 60 km legs, and a tenth site on Catalina Island a distance of about 50 km (over water) from the hypotenuse of the triangle. Relative zenith delays are estimated every second with a latency less than a second. Median values are computed at a user-specified interval (e.g., 10 minutes) with outliers greater than 4 times the interquartile range rejected. We describe the results with those generated by our operational system using the GAMIT software, with a latency of 30-60 minutes. Earlier results (from a similar network) comparing 30-minute median RTD values to GAMIT 30-minute estimates indicate that the two solutions differ by about 1 cm. We also describe our approach to determining absolute zenith delays. If an Internet connection is available we will present a real-time demonstration. [Bock, Y., R. Nikolaidis, P. J. de Jonge, and M. Bevis, Instantaneous resolution of crustal motion at medium distances with the Global Positioning System, J. Geophys. Res., 105, 28,223-28,254, 2000.

Performance Evaluation of FAST TCP Traffic-Flows in Multihomed MANETs

NASA Astrophysics Data System (ADS)

Mudassir, Mumajjed Ul; Akram, Adeel

In Mobile Ad hoc Networks (MANETs) an efficient communication protocol is required at the transport layer. Mobile nodes moving around will have temporary and rather short-lived connectivity with each other and the Internet, thus requiring efficient utilization of network resources. Moreover the problems arising due to high mobility, collision and congestion must also be considered. Multihoming allows higher reliability and enhancement of network throughput. FAST TCP is a new promising transport layer protocol developed for high-speed high-latency networks. In this paper, we have analyzed the performance of FAST TCP traffic flows in multihomed MANETs and compared it with standard TCP (TCP Reno) traffic flows in non-multihomed MANETs.

Relationships between the resting-state network and the P3: Evidence from a scalp EEG study

NASA Astrophysics Data System (ADS)

Li, Fali; Liu, Tiejun; Wang, Fei; Li, He; Gong, Diankun; Zhang, Rui; Jiang, Yi; Tian, Yin; Guo, Daqing; Yao, Dezhong; Xu, Peng

2015-10-01

The P3 is an important event-related potential that can be used to identify neural activity related to the cognitive processes of the human brain. However, the relationships, especially the functional correlations, between resting-state brain activity and the P3 have not been well established. In this study, we investigated the relationships between P3 properties (i.e., amplitude and latency) and resting-state brain networks. The results indicated that P3 amplitude was significantly correlated with resting-state network topology, and in general, larger P3 amplitudes could be evoked when the resting-state brain network was more efficient. However, no significant relationships were found for the corresponding P3 latency. Additionally, the long-range connections between the prefrontal/frontal and parietal/occipital brain regions, which represent the synchronous activity of these areas, were functionally related to the P3 parameters, especially P3 amplitude. The findings of the current study may help us better understand inter-subject variation in the P3, which may be instructive for clinical diagnosis, cognitive neuroscience studies, and potential subject selection for brain-computer interface applications.

Performance Analysis of Inter-Domain Handoff Scheme Based on Virtual Layer in PMIPv6 Networks for IP-Based Internet of Things.

PubMed

Cho, Chulhee; Choi, Jae-Young; Jeong, Jongpil; Chung, Tai-Myoung

2017-01-01

Lately, we see that Internet of things (IoT) is introduced in medical services for global connection among patients, sensors, and all nearby things. The principal purpose of this global connection is to provide context awareness for the purpose of bringing convenience to a patient's life and more effectively implementing clinical processes. In health care, monitoring of biosignals of a patient has to be continuously performed while the patient moves inside and outside the hospital. Also, to monitor the accurate location and biosignals of the patient, appropriate mobility management is necessary to maintain connection between the patient and the hospital network. In this paper, a binding update scheme on PMIPv6, which reduces signal traffic during location updates by Virtual LMA (VLMA) on the top original Local Mobility Anchor (LMA) Domain, is proposed to reduce the total cost. If a Mobile Node (MN) moves to a Mobile Access Gateway (MAG)-located boundary of an adjacent LMA domain, the MN changes itself into a virtual mode, and this movement will be assumed to be a part of the VLMA domain. In the proposed scheme, MAGs eliminate global binding updates for MNs between LMA domains and significantly reduce the packet loss and latency by eliminating the handoff between LMAs. In conclusion, the performance analysis results show that the proposed scheme improves performance significantly versus PMIPv6 and HMIPv6 in terms of the binding update rate per user and average handoff latency.

Infectious disease control using contact tracing in random and scale-free networks

PubMed Central

Kiss, Istvan Z; Green, Darren M; Kao, Rowland R

2005-01-01

Contact tracing aims to identify and isolate individuals that have been in contact with infectious individuals. The efficacy of contact tracing and the hierarchy of traced nodes—nodes with higher degree traced first—is investigated and compared on random and scale-free (SF) networks with the same number of nodes N and average connection K. For values of the transmission rate larger than a threshold, the final epidemic size on SF networks is smaller than that on corresponding random networks. While in random networks new infectious and traced nodes from all classes have similar average degrees, in SF networks the average degree of nodes that are in more advanced stages of the disease is higher at any given time. On SF networks tracing removes possible sources of infection with high average degree. However a higher tracing effort is required to control the epidemic than on corresponding random networks due to the high initial velocity of spread towards the highly connected nodes. An increased latency period fails to significantly improve contact tracing efficacy. Contact tracing has a limited effect if the removal rate of susceptible nodes is relatively high, due to the fast local depletion of susceptible nodes. PMID:16849217

A Network of Hydrophobic Residues Impeding Helix αC Rotation Maintains Latency of Kinase Gcn2, Which Phosphorylates the α Subunit of Translation Initiation Factor 2▿

PubMed Central

Gárriz, Andrés; Qiu, Hongfang; Dey, Madhusudan; Seo, Eun-Joo; Dever, Thomas E.; Hinnebusch, Alan G.

2009-01-01

Kinase Gcn2 is activated by amino acid starvation and downregulates translation initiation by phosphorylating the α subunit of translation initiation factor 2 (eIF2α). The Gcn2 kinase domain (KD) is inert and must be activated by tRNA binding to the adjacent regulatory domain. Previous work indicated that Saccharomyces cerevisiae Gcn2 latency results from inflexibility of the hinge connecting the N and C lobes and a partially obstructed ATP-binding site in the KD. Here, we provide strong evidence that a network of hydrophobic interactions centered on Leu-856 also promotes latency by constraining helix αC rotation in the KD in a manner relieved during amino acid starvation by tRNA binding and autophosphorylation of Thr-882 in the activation loop. Thus, we show that mutationally disrupting the hydrophobic network in various ways constitutively activates eIF2α phosphorylation in vivo and bypasses the requirement for a key tRNA binding motif (m2) and Thr-882 in Gcn2. In particular, replacing Leu-856 with any nonhydrophobic residue activates Gcn2, while substitutions with various hydrophobic residues maintain kinase latency. We further provide strong evidence that parallel, back-to-back dimerization of the KD is a step on the Gcn2 activation pathway promoted by tRNA binding and autophosphorylation. Remarkably, mutations that disrupt the L856 hydrophobic network or enhance hinge flexibility eliminate the need for the conserved salt bridge at the parallel dimer interface, implying that KD dimerization facilitates the reorientation of αC and remodeling of the active site for enhanced ATP binding and catalysis. We propose that hinge remodeling, parallel dimerization, and reorientation of αC are mutually reinforcing conformational transitions stimulated by tRNA binding and secured by the ensuing autophosphorylation of T882 for stable kinase activation. PMID:19114556

A network of hydrophobic residues impeding helix alphaC rotation maintains latency of kinase Gcn2, which phosphorylates the alpha subunit of translation initiation factor 2.

PubMed

Gárriz, Andrés; Qiu, Hongfang; Dey, Madhusudan; Seo, Eun-Joo; Dever, Thomas E; Hinnebusch, Alan G

2009-03-01

Kinase Gcn2 is activated by amino acid starvation and downregulates translation initiation by phosphorylating the alpha subunit of translation initiation factor 2 (eIF2alpha). The Gcn2 kinase domain (KD) is inert and must be activated by tRNA binding to the adjacent regulatory domain. Previous work indicated that Saccharomyces cerevisiae Gcn2 latency results from inflexibility of the hinge connecting the N and C lobes and a partially obstructed ATP-binding site in the KD. Here, we provide strong evidence that a network of hydrophobic interactions centered on Leu-856 also promotes latency by constraining helix alphaC rotation in the KD in a manner relieved during amino acid starvation by tRNA binding and autophosphorylation of Thr-882 in the activation loop. Thus, we show that mutationally disrupting the hydrophobic network in various ways constitutively activates eIF2alpha phosphorylation in vivo and bypasses the requirement for a key tRNA binding motif (m2) and Thr-882 in Gcn2. In particular, replacing Leu-856 with any nonhydrophobic residue activates Gcn2, while substitutions with various hydrophobic residues maintain kinase latency. We further provide strong evidence that parallel, back-to-back dimerization of the KD is a step on the Gcn2 activation pathway promoted by tRNA binding and autophosphorylation. Remarkably, mutations that disrupt the L856 hydrophobic network or enhance hinge flexibility eliminate the need for the conserved salt bridge at the parallel dimer interface, implying that KD dimerization facilitates the reorientation of alphaC and remodeling of the active site for enhanced ATP binding and catalysis. We propose that hinge remodeling, parallel dimerization, and reorientation of alphaC are mutually reinforcing conformational transitions stimulated by tRNA binding and secured by the ensuing autophosphorylation of T882 for stable kinase activation.

Graphical processors for HEP trigger systems

NASA Astrophysics Data System (ADS)

Ammendola, R.; Biagioni, A.; Chiozzi, S.; Cotta Ramusino, A.; Di Lorenzo, S.; Fantechi, R.; Fiorini, M.; Frezza, O.; Lamanna, G.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Neri, I.; Paolucci, P. S.; Pastorelli, E.; Piandani, R.; Pontisso, L.; Rossetti, D.; Simula, F.; Sozzi, M.; Vicini, P.

2017-02-01

General-purpose computing on GPUs is emerging as a new paradigm in several fields of science, although so far applications have been tailored to employ GPUs as accelerators in offline computations. With the steady decrease of GPU latencies and the increase in link and memory throughputs, time is ripe for real-time applications using GPUs in high-energy physics data acquisition and trigger systems. We will discuss the use of online parallel computing on GPUs for synchronous low level trigger systems, focusing on tests performed on the trigger of the CERN NA62 experiment. Latencies of all components need analysing, networking being the most critical. To keep it under control, we envisioned NaNet, an FPGA-based PCIe Network Interface Card (NIC) enabling GPUDirect connection. Moreover, we discuss how specific trigger algorithms can be parallelised and thus benefit from a GPU implementation, in terms of increased execution speed. Such improvements are particularly relevant for the foreseen LHC luminosity upgrade where highly selective algorithms will be crucial to maintain sustainable trigger rates with very high pileup.

Integrated Service Provisioning in an Ipv6 over ATM Research Network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eli Dart; Helen Chen; Jerry Friesen

1999-02-01

During the past few years, the worldwide Internet has grown at a phenomenal rate, which has spurred the proposal of innovative network technologies to support the fast, efficient and low-latency transport of a wide spectrum of multimedia traffic types. Existing network infrastructures have been plagued by their inability to provide for real-time application traffic as well as their general lack of resources and resilience to congestion. This work proposes to address these issues by implementing a prototype high-speed network infrastructure consisting of Internet Protocol Version 6 (IPv6) on top of an Asynchronous Transfer Mode (ATM) transport medium. Since ATM ismore » connection-oriented whereas IP uses a connection-less paradigm, the efficient integration of IPv6 over ATM is especially challenging and has generated much interest in the research community. We propose, in collaboration with an industry partner, to implement IPv6 over ATM using a unique approach that integrates IP over fast A TM hardware while still preserving IP's connection-less paradigm. This is achieved by replacing ATM's control software with IP's routing code and by caching IP's forwarding decisions in ATM's VPI/VCI translation tables. Prototype ''VR'' and distributed-parallel-computing applications will also be developed to exercise the realtime capability of our IPv6 over ATM network.« less

Latency of TCP applications over the ATM-WAN using the GFR service category

NASA Astrophysics Data System (ADS)

Chen, Kuo-Hsien; Siliquini, John F.; Budrikis, Zigmantas

1998-10-01

The GFR service category has been proposed for data services in ATM networks. Since users are ultimately interested in data service that provide high efficiency and low latency, it is important to study the latency performance for data traffic of the GFR service category in an ATM network. Today much of the data traffic utilizes the TCP/IP protocol suite and in this paper we study through simulation the latency of TCP applications running over a wide-area ATM network utilizing the GFR service category using a realistic TCP traffic model. From this study, we find that during congestion periods the reserved bandwidth in GFR can improve the latency performance for TCP applications. However, due to TCP 'Slow Start' data segment generation dynamics, we show that a large proportion of TCP segments are discarded under network congestion even when the reserved bandwidth is equal to the average generated rate of user data. Therefore, a user experiences worse than expected latency performance when the network is congested. In this study we also examine the effects of segment size on the latency performance of TCP applications using the GFR service category.

Research on low-latency MAC protocols for wireless sensor networks

NASA Astrophysics Data System (ADS)

He, Chenguang; Sha, Xuejun; Lee, Chankil

2007-11-01

Energy-efficient should not be the only design goal in MAC protocols for wireless sensor networks, which involve the use of battery-operated computing and sensing devices. Low-latency operation becomes the same important as energy-efficient in the case that the traffic load is very heavy or the real-time constrain is used in applications like tracking or locating. This paper introduces some causes of traditional time delays which are inherent in a multi-hops network using existing WSN MAC protocols, illuminates the importance of low-latency MAC design for wireless sensor networks, and presents three MACs as examples of low-latency protocols designed specially for sleep delay, wait delay and wakeup delay in wireless sensor networks, respectively. The paper also discusses design trade-offs with emphasis on low-latency and points out their advantages and disadvantages, together with some design considerations and suggestions for MAC protocols for future applications and researches.

Generalized hypercube structures and hyperswitch communication network

NASA Technical Reports Server (NTRS)

Young, Steven D.

1992-01-01

This paper discusses an ongoing study that uses a recent development in communication control technology to implement hybrid hypercube structures. These architectures are similar to binary hypercubes, but they also provide added connectivity between the processors. This added connectivity increases communication reliability while decreasing the latency of interprocessor message passing. Because these factors directly determine the speed that can be obtained by multiprocessor systems, these architectures are attractive for applications such as remote exploration and experimentation, where high performance and ultrareliability are required. This paper describes and enumerates these architectures and discusses how they can be implemented with a modified version of the hyperswitch communication network (HCN). The HCN is analyzed because it has three attractive features that enable these architectures to be effective: speed, fault tolerance, and the ability to pass multiple messages simultaneously through the same hyperswitch controller.

Performance Analysis of Inter-Domain Handoff Scheme Based on Virtual Layer in PMIPv6 Networks for IP-Based Internet of Things

PubMed Central

Choi, Jae-Young; Jeong, Jongpil; Chung, Tai-Myoung

2017-01-01

Lately, we see that Internet of things (IoT) is introduced in medical services for global connection among patients, sensors, and all nearby things. The principal purpose of this global connection is to provide context awareness for the purpose of bringing convenience to a patient’s life and more effectively implementing clinical processes. In health care, monitoring of biosignals of a patient has to be continuously performed while the patient moves inside and outside the hospital. Also, to monitor the accurate location and biosignals of the patient, appropriate mobility management is necessary to maintain connection between the patient and the hospital network. In this paper, a binding update scheme on PMIPv6, which reduces signal traffic during location updates by Virtual LMA (VLMA) on the top original Local Mobility Anchor (LMA) Domain, is proposed to reduce the total cost. If a Mobile Node (MN) moves to a Mobile Access Gateway (MAG)-located boundary of an adjacent LMA domain, the MN changes itself into a virtual mode, and this movement will be assumed to be a part of the VLMA domain. In the proposed scheme, MAGs eliminate global binding updates for MNs between LMA domains and significantly reduce the packet loss and latency by eliminating the handoff between LMAs. In conclusion, the performance analysis results show that the proposed scheme improves performance significantly versus PMIPv6 and HMIPv6 in terms of the binding update rate per user and average handoff latency. PMID:28129355

Autonomous Congestion Control in Delay-Tolerant Networks

NASA Technical Reports Server (NTRS)

Burleigh, Scott C.; Jennings, Esther H.

2005-01-01

Congestion control is an important feature that directly affects network performance. Network congestion may cause loss of data or long delays. Although this problem has been studied extensively in the Internet, the solutions for Internet congestion control do not apply readily to challenged network environments such as Delay Tolerant Networks (DTN) where end-to-end connectivity may not exist continuously and latency can be high. In DTN, end-to-end rate control is not feasible. This calls for congestion control mechanisms where the decisions can be made autonomously with local information only. We use an economic pricing model and propose a rule-based congestion control mechanism where each router can autonomously decide on whether to accept a bundle (data) based on local information such as available storage and the value and risk of accepting the bundle (derived from historical statistics).

Remote Data Retrieval for Bioinformatics Applications: An Agent Migration Approach

PubMed Central

Gao, Lei; Dai, Hua; Zhang, Tong-Liang; Chou, Kuo-Chen

2011-01-01

Some of the approaches have been developed to retrieve data automatically from one or multiple remote biological data sources. However, most of them require researchers to remain online and wait for returned results. The latter not only requires highly available network connection, but also may cause the network overload. Moreover, so far none of the existing approaches has been designed to address the following problems when retrieving the remote data in a mobile network environment: (1) the resources of mobile devices are limited; (2) network connection is relatively of low quality; and (3) mobile users are not always online. To address the aforementioned problems, we integrate an agent migration approach with a multi-agent system to overcome the high latency or limited bandwidth problem by moving their computations to the required resources or services. More importantly, the approach is fit for the mobile computing environments. Presented in this paper are also the system architecture, the migration strategy, as well as the security authentication of agent migration. As a demonstration, the remote data retrieval from GenBank was used to illustrate the feasibility of the proposed approach. PMID:21701677

Communication latencies of wireless devices suitable for time-critical messaging to anesthesia providers.

PubMed

Epstein, Richard H; Dexter, Franklin; Rothman, Brian

2013-04-01

Rapid and reliable methods of text communication to mobile anesthesia care providers are important to patient care and to efficient operating room management. Anesthesia departments are implementing automated methods to send text messages to mobile devices for abnormal vital signs, clinical recommendations, quality of care, and compliance or billing issues. The most time-critical communications determine maximum acceptable latencies. We studied the reliability of several alphanumeric messaging systems to identify an appropriate technology for such use. Latencies between message initiation and delivery to 3 alphanumeric paging devices were measured over weeks. Two devices used Internet pathways outside the hospital's local network with an external paging vendor (SkyTel). The third device used only the internal hospital network (Zetron). Sequential cell phone text page latencies were examined for lag-1 autocorrelation using the runs test, with results binned by hour and by day. Message latencies subsequently were batched in successive 1-week bins for calculation of the mean and 99th percentiles of latencies. We defined acceptance criteria as a mean latency <30 seconds and no more than 1 in 200 pages (0.5%) having a latency longer than 100 seconds. Cell phone texting was used as a positive control to assure that the analysis was appropriate, because such devices have (known) poor reliability during high network activity. There was substantial correlation among latencies for sequential cell phone text messages when binned by hours (P < 0.0001), but not by days (P = 0.61). The 2 devices using Internet pathways outside the hospital's network demonstrated unacceptable performance, with 1.3% and 33% of latencies exceeding 100 seconds, respectively. The device dependent only on the internal network had a mean latency of 8 seconds, with 100% of 40,200 pages having latencies <100 seconds. The findings suggest that the network used was the deciding factor. Developers of anesthesia communication systems need to measure latencies of proposed communication pathways and devices used to deliver urgent messages to mobile users. Similar evaluation is relevant for text pagers used on an ad hoc basis for delivery of time-critical notifications. Testing over a period of hours to days is adequate only for disqualification of a candidate paging system, because acceptable results are not necessarily indicative of long-term performance. Rather, weeks of testing are required, with appropriate batching of pages for analysis.

First Applications of DoD Iridium RUDICS in the NSF Polar Programs

NASA Astrophysics Data System (ADS)

Valentic, T.; Stehle, R.

2008-12-01

We will present the first deployment and application of the new Iridium RUDICS service to remote instrumentation projects within the National Science Foundation's polar programs. The rise of automated observing networks has increased the demand for real-time connectivity to remote instruments, not only for immediate access to data, but to also interrogate health and status. Communicating with field sites in the polar regions is complicated by the remoteness from existing infrastructure, low temperatures and limited connection options. Sites located above 78° latitude are not able to see geostationary satellites, leaving the Iridium constellation as the only one that provide a direct connection. Some others, such as Orbcomm, only provide a store-and-forward service. Iridium is often used as a dial up modem to establish a PPP connection to the Internet with data files transferred via FTP. On low-bandwidth, high-latency networks like Iridium (2400bps with ping times of seconds), this approach is time consuming and inefficient. The dial up time alone takes upwards of a minute, and standard TCP/IP and FTP protocols are hampered by the long latencies. Minimizing transmission time is important for reducing battery usage and connection costs. The new Iridium RUDICS service can be used for more efficient transfers. RUDICS is an acronym for "Router-based Unstructured Digital Inter-working Connectivity Solution" and provides a direct connection between an instrument in the field and a server on the Internet. After dialing into the Iridium gateway, a socket connection is opened to a registered port on a user's server. Bytes sent to or from the modem appear at the server's socket. The connection time is reduced to about 10 seconds because the modem training and PPP negotiation stages are eliminated. The remote device does not need to have a full TCP/IP stack, allowing smaller instruments such as data loggers to directly handle the data transmission. Alternative protocols can be deployed that better exploit the characteristics of the Iridium channel. In addition, the setup naturally scales to handle hundreds of remote devices, an important aspect for larger sensor networks. As part of the NSF's Arctic Research Support and Logistics Services, we have deployed RUDICS systems with three different research projects. These are the first NSF RUDICS deployments for projects using the Department of Defense Iridium gateway, which allows for unlimited connection time at a flat monthly rate for US government users. The first project is O-Buoy, an IPY-OASIS project for self-contained, autonomous observations of atmospheric chemical species in the polar marine boundary layer. The second project is collection of low-power instrument towers on Alaska's North Slope at Imnavait Creek, part of the Arctic Observation Network (AON). Lastly, the autonomous instrument platform at Ivotuk, Alaska, uses RUDICS to provide telemetry about the renewable energy systems. A set of real-time web displays allow researchers for each project to monitor their remote sites and access real-time data.

Objective sleep disturbances are associated with greater waking resting-state connectivity between the retrosplenial cortex/ hippocampus and various nodes of the default mode network.

PubMed

Regen, Wolfram; Kyle, Simon D; Nissen, Christoph; Feige, Bernd; Baglioni, Chiara; Hennig, Jürgen; Riemann, Dieter; Spiegelhalder, Kai

2016-08-01

Psychological models highlight the bidirectional role of self-referential processing, introspection, worry and rumination in the development and maintenance of insomnia; however, little is known about the underlying neural substrates. Default mode network (DMN) functional connectivity has been previously linked to these cognitive processes. We used fMRI to investigate waking DMN functional connectivity in a well-characterized sample of patients with primary insomnia (PI) and good sleeper controls. We included 20 patients with PI (8 men and 12 women, mean age 42.7 ± 13.4 yr) and 20 controls (8 men and 12 women, mean age 44.1 ± 10.6 yr) in our study. While no between-group differences in waking DMN connectivity were observed, exploratory analyses across all participants suggested that greater waking connectivity between the retrosplenial cortex/hippocampus and various nodes of the DMN was associated with lower sleep efficiency, lower amounts of rapid eye movement sleep and greater sleep-onset latency. Owing to the cross-sectional nature of the study, conclusions about causality cannot be drawn. As sleep disturbances represent a transdiagnostic symptom that is characteristic of nearly all psychiatric disorders, our results may hold particular relevance to previous findings of increased DMN connectivity levels in patients with psychiatric disorders.

Instantaneous network RTK in Orange County, California

NASA Astrophysics Data System (ADS)

Bock, Y.

2003-04-01

The Orange County Real Time GPS Network (OCRTN) is an upgrade of a sub-network of SCIGN sites in southern California to low latency (1-2 sec), high-rate (1 Hz) data streaming, analysis, and dissemination. The project is a collaborative effort of the California Spatial Reference Center (CSRC) and the Orange County Public Resource and Facilities Division, with partners from the geophysical community, local and state government, and the private sector. Currently, ten sites are streaming 1 Hz raw data (Ashtech binary MBEN format) by means of dedicated, point-to-point radio modems to a network hub that translates the asynchronous serial data to TCP/IP and onto a PC workstation residing on a local area network. Software residing on the PC allows multiple clients to access the raw data simultaneously though TCP/IP. One of the clients is a Geodetics RTD server that receives and archives (1) the raw 1 Hz network data, (2) estimates of instantaneous positions and zenith tropospheric delays for quality control and detection of ground motion, and (3) RINEX data to decimated to 30 seconds. Data recovery is typically 99-100%. The server also produces 1 Hz RTCM data (messages 18, 19, 3 and 22) that are available by means of TCP/IP to RTK clients with wireless Internet modems. Coverage is excellent throughout the county. The server supports standard RTK users and is compatible with existing GPS instrumentation. Typical latency is 1-2 s, with initialization times of several seconds to minutes OCRTN site spacing is 10-15 km. In addition, the server supports “smart clients” who can retrieve data from the closest n sites (typically 3) and obtain an instantaneous network RTK position with 1-2 s latency. This mode currently requires a PDA running the RTD client software, and a wireless card. Since there is no initialization and re-initialization required this approach is well suited to support high-precision (centimeter-level) dynamic applications such as intelligent transportation and aircraft landing. We will discuss the results of field tests of this system, indicating that instantaneous network RTK can be performed accurately and reliably. If an Internet connection is available we will present a real-time demonstration.

Assessment of the suitability of public mobile data networks for aircraft telemetry and control purposes

NASA Astrophysics Data System (ADS)

Gonzalez, F.; Walker, R.; Rutherford, N.; Turner, C.

2011-04-01

This paper provides a review of the state of the art of relevant work on the use of public mobile data networks for aircraft telemetry and control proposes. Moreover, it describes the characterisation for airborne uses of the public mobile data communication systems known broadly as 3G. The motivation for this study was to explore how this mature public communication systems could be used for aviation purposes. An experimental system was fitted to a light aircraft to record communication latency, line speed, RF level, packet loss and cell tower identifier. Communications was established using internet protocols and connection was made to a local server. The aircraft was flown in both remote and populous areas at altitudes up to 8500 ft in a region located in South East Queensland, Australia. Results show that the average airborne RF levels are better than those on the ground by 21% and in the order of -77 dbm. Latencies were in the order of 500 ms (1/2 the latency of Iridium), an average download speed of 0.48 Mb/s, average uplink speed of 0.85 Mb/s, a packet of information loss of 6.5%. The maximum communication range was also observed to be 70 km from a single cell station. The paper also describes possible limitations and utility of using such communications architecture for both manned and unmanned aircraft systems.

Long-Term Effects of Attentional Performance on Functional Brain Network Topology

PubMed Central

Breckel, Thomas P. K.; Thiel, Christiane M.; Bullmore, Edward T.; Zalesky, Andrew; Patel, Ameera X.; Giessing, Carsten

2013-01-01

Individuals differ in their cognitive resilience. Less resilient people demonstrate a greater tendency to vigilance decrements within sustained attention tasks. We hypothesized that a period of sustained attention is followed by prolonged changes in the organization of “resting state” brain networks and that individual differences in cognitive resilience are related to differences in post-task network reorganization. We compared the topological and spatial properties of brain networks as derived from functional MRI data (N = 20) recorded for 6 mins before and 12 mins after the performance of an attentional task. Furthermore we analysed changes in brain topology during task performance and during the switches between rest and task conditions. The cognitive resilience of each individual was quantified as the rate of increase in response latencies over the 32-minute time course of the attentional paradigm. On average, functional networks measured immediately post-task demonstrated significant and prolonged changes in network organization compared to pre-task networks with higher connectivity strength, more clustering, less efficiency, and shorter distance connections. Individual differences in cognitive resilience were significantly correlated with differences in the degree of recovery of some network parameters. Changes in network measures were still present in less resilient individuals in the second half of the post-task period (i.e. 6–12 mins after task completion), while resilient individuals already demonstrated significant reductions of functional connectivity and clustering towards pre-task levels. During task performance brain topology became more integrated with less clustering and higher global efficiency, but linearly decreased with ongoing time-on-task. We conclude that sustained attentional task performance has prolonged, “hang-over” effects on the organization of post-task resting-state brain networks; and that more cognitively resilient individuals demonstrate faster rates of network recovery following a period of attentional effort. PMID:24040185

High-speed quantum networking by ship

NASA Astrophysics Data System (ADS)

Devitt, Simon J.; Greentree, Andrew D.; Stephens, Ashley M.; van Meter, Rodney

2016-11-01

Networked entanglement is an essential component for a plethora of quantum computation and communication protocols. Direct transmission of quantum signals over long distances is prevented by fibre attenuation and the no-cloning theorem, motivating the development of quantum repeaters, designed to purify entanglement, extending its range. Quantum repeaters have been demonstrated over short distances, but error-corrected, global repeater networks with high bandwidth require new technology. Here we show that error corrected quantum memories installed in cargo containers and carried by ship can provide a exible connection between local networks, enabling low-latency, high-fidelity quantum communication across global distances at higher bandwidths than previously proposed. With demonstrations of technology with sufficient fidelity to enable topological error-correction, implementation of the quantum memories is within reach, and bandwidth increases with improvements in fabrication. Our approach to quantum networking avoids technological restrictions of repeater deployment, providing an alternate path to a worldwide Quantum Internet.

High-speed quantum networking by ship

PubMed Central

Devitt, Simon J.; Greentree, Andrew D.; Stephens, Ashley M.; Van Meter, Rodney

2016-01-01

Networked entanglement is an essential component for a plethora of quantum computation and communication protocols. Direct transmission of quantum signals over long distances is prevented by fibre attenuation and the no-cloning theorem, motivating the development of quantum repeaters, designed to purify entanglement, extending its range. Quantum repeaters have been demonstrated over short distances, but error-corrected, global repeater networks with high bandwidth require new technology. Here we show that error corrected quantum memories installed in cargo containers and carried by ship can provide a exible connection between local networks, enabling low-latency, high-fidelity quantum communication across global distances at higher bandwidths than previously proposed. With demonstrations of technology with sufficient fidelity to enable topological error-correction, implementation of the quantum memories is within reach, and bandwidth increases with improvements in fabrication. Our approach to quantum networking avoids technological restrictions of repeater deployment, providing an alternate path to a worldwide Quantum Internet. PMID:27805001

Autonomous Congestion Control in Delay-Tolerant Networks

NASA Technical Reports Server (NTRS)

Burleigh, Scott; Jennings, Esther; Schoolcraft, Joshua

2006-01-01

Congestion control is an important feature that directly affects network performance. Network congestion may cause loss of data or long delays. Although this problem has been studied extensively in the Internet, the solutions for Internet congestion control do not apply readily to challenged network environments such as Delay Tolerant Networks (DTN) where end-to-end connectivity may not exist continuously and latency can be high. In DTN, end-to-end rate control is not feasible. This calls for congestion control mechanisms where the decisions can be made autonomously with local information only. We use an economic pricing model and propose a rule-based congestion control mechanism where each router can autonomously decide on whether to accept a bundle (data) based on local information such as available storage and the value and risk of accepting the bundle (derived from historical statistics). Preliminary experimental results show that this congestion control mechanism can protect routers from resource depletion without loss of data.

High-speed quantum networking by ship.

PubMed

Devitt, Simon J; Greentree, Andrew D; Stephens, Ashley M; Van Meter, Rodney

2016-11-02

Networked entanglement is an essential component for a plethora of quantum computation and communication protocols. Direct transmission of quantum signals over long distances is prevented by fibre attenuation and the no-cloning theorem, motivating the development of quantum repeaters, designed to purify entanglement, extending its range. Quantum repeaters have been demonstrated over short distances, but error-corrected, global repeater networks with high bandwidth require new technology. Here we show that error corrected quantum memories installed in cargo containers and carried by ship can provide a exible connection between local networks, enabling low-latency, high-fidelity quantum communication across global distances at higher bandwidths than previously proposed. With demonstrations of technology with sufficient fidelity to enable topological error-correction, implementation of the quantum memories is within reach, and bandwidth increases with improvements in fabrication. Our approach to quantum networking avoids technological restrictions of repeater deployment, providing an alternate path to a worldwide Quantum Internet.

Communication latencies of Apple push notification messages relevant for delivery of time-critical information to anesthesia providers.

PubMed

Rothman, Brian S; Dexter, Franklin; Epstein, Richard H

2013-08-01

Tablet computers and smart phones have gained popularity in anesthesia departments for educational and patient care purposes. VigiVU(™) is an iOS application developed at Vanderbilt University for remote viewing of perioperative information, including text message notifications delivered via the Apple Push Notification (APN) service. In this study, we assessed the reliability of the APN service. Custom software was written to send a message every minute to iOS devices (iPad(®), iPod Touch(®), and iPhone(®)) via wireless local area network (WLAN) and cellular pathways 24 hours a day over a 4-month period. Transmission and receipt times were recorded and batched by days, with latencies calculated as their differences. The mean, SEM, and the exact 95% upper confidence limits for the percent of days with ≥1 prolonged (>100 seconds) latency were calculated. Acceptable performance was defined as mean latency <30 seconds and ≤0.5% of latencies >100 seconds. Testing conditions included fixed locations of devices in high signal strength locations. Mean latencies were <1 second for iPad and iPod devices (WLAN), and <4 seconds for iPhone (cellular). Among >173,000 iPad and iPod latencies, none were >100 seconds. For iPhone latencies, 0.03% ± 0.01% were >100 seconds. The 95% upper confidence limits of days with ≥1 prolonged latency were 42% (iPhone) and 5% to 8% (iPad, iPod). The APN service was reliable for all studied devices over WLAN and cellular pathways, and performance was better than third party paging systems using Internet connections previously investigated using the same criteria. However, since our study was a best-case assessment, testing is required at individual sites considering use of this technology for critical messaging. Furthermore, since the APN service may fail due to Internet or service provider disruptions, a backup paging system is recommended if the APN service were to be used for critical messaging.

ConnectX2 In niBand Management Queues: New support for Network Of oaded

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graham, Richard L; Poole, Stephen W; Shamis, Pavel

2010-01-01

This paper introduces the newly developed InfiniBand (IB) Management Queue capability, used by the Host Channel Adapter (HCA) to manage network task data flow dependancies, and progress the communications associated with such flows. These tasks include sends, receives, and the newly supported wait task, and are scheduled by the HCA based on a data dependency description provided by the user. This functionality is supported by the ConnectX-2 HCA, and provides the means for delegating collective communication management and progress to the HCA, also known as collective communication offload. This provides a means for overlapping collective communications managed by the HCAmore » and computation on the Central Processing Unit (CPU), thus making it possible to reduce the impact of system noise on parallel applications using collective operations. This paper further describes how this new capability can be used to implement scalable Message Passing Interface (MPI) collective operations, describing the high level details of how this new capability is used to implement the MPI Barrier collective operation, focusing on the latency sensitive performance aspects of this new capability. This paper concludes with small scale benchmark experiments comparing implementations of the barrier collective operation, using the new network offload capabilities, with established point-to-point based implementations of these same algorithms, which manage the data flow using the central processing unit. These early results demonstrate the promise this new capability provides to improve the scalability of high-performance applications using collective communications. The latency of the HCA based implementation of the barrier is similar to that of the best performing point-to-point based implementation managed by the central processing unit, starting to outperform these as the number of processes involved in the collective operation increases.« less

ConnectX-2 InfiniBand Management Queues: First Investigation of the New Support for Network Offloaded Collective Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graham, Richard L; Poole, Stephen W; Shamis, Pavel

2010-01-01

This paper introduces the newly developed Infini-Band (IB) Management Queue capability, used by the Host Channel Adapter (HCA) to manage network task data flow dependancies, and progress the communications associated with such flows. These tasks include sends, receives, and the newly supported wait task, and are scheduled by the HCA based on a data dependency description provided by the user. This functionality is supported by the ConnectX-2 HCA, and provides the means for delegating collective communication management and progress to the HCA, also known as collective communication offload. This provides a means for overlapping collective communications managed by the HCAmore » and computation on the Central Processing Unit (CPU), thus making it possible to reduce the impact of system noise on parallel applications using collective operations. This paper further describes how this new capability can be used to implement scalable Message Passing Interface (MPI) collective operations, describing the high level details of how this new capability is used to implement the MPI Barrier collective operation, focusing on the latency sensitive performance aspects of this new capability. This paper concludes with small scale benchmark experiments comparing implementations of the barrier collective operation, using the new network offload capabilities, with established point-to-point based implementations of these same algorithms, which manage the data flow using the central processing unit. These early results demonstrate the promise this new capability provides to improve the scalability of high performance applications using collective communications. The latency of the HCA based implementation of the barrier is similar to that of the best performing point-to-point based implementation managed by the central processing unit, starting to outperform these as the number of processes involved in the collective operation increases.« less

Analysis and Tools for Improved Management of Connectionless and Connection-Oriented BLE Devices Coexistence

PubMed Central

Del Campo, Antonio; Cintioni, Lorenzo; Spinsante, Susanna; Gambi, Ennio

2017-01-01

With the introduction of low-power wireless technologies, like Bluetooth Low Energy (BLE), new applications are approaching the home automation, healthcare, fitness, automotive and consumer electronics markets. BLE devices are designed to maximize the battery life, i.e., to run for long time on a single coin-cell battery. In typical application scenarios of home automation and Ambient Assisted Living (AAL), the sensors that monitor relatively unpredictable and rare events should coexist with other sensors that continuously communicate health or environmental parameter measurements. The former usually work in connectionless mode, acting as advertisers, while the latter need a persistent connection, acting as slave nodes. The coexistence of connectionless and connection-oriented networks, that share the same central node, can be required to reduce the number of handling devices, thus keeping the network complexity low and limiting the packet’s traffic congestion. In this paper, the medium access management, operated by the central node, has been modeled, focusing on the scheduling procedure in both connectionless and connection-oriented communication. The models have been merged to provide a tool supporting the configuration design of BLE devices, during the network design phase that precedes the real implementation. The results highlight the suitability of the proposed tool: the ability to set the device parameters to allow us to keep a practical discovery latency for event-driven sensors and avoid undesired overlaps between scheduled scanning and connection phases due to bad management performed by the central node. PMID:28387724

Analysis and Tools for Improved Management of Connectionless and Connection-Oriented BLE Devices Coexistence.

PubMed

Del Campo, Antonio; Cintioni, Lorenzo; Spinsante, Susanna; Gambi, Ennio

2017-04-07

With the introduction of low-power wireless technologies, like Bluetooth Low Energy (BLE), new applications are approaching the home automation, healthcare, fitness, automotive and consumer electronics markets. BLE devices are designed to maximize the battery life, i.e., to run for long time on a single coin-cell battery. In typical application scenarios of home automation and Ambient Assisted Living (AAL), the sensors that monitor relatively unpredictable and rare events should coexist with other sensors that continuously communicate health or environmental parameter measurements. The former usually work in connectionless mode, acting as advertisers, while the latter need a persistent connection, acting as slave nodes. The coexistence of connectionless and connection-oriented networks, that share the same central node, can be required to reduce the number of handling devices, thus keeping the network complexity low and limiting the packet's traffic congestion. In this paper, the medium access management, operated by the central node, has been modeled, focusing on the scheduling procedure in both connectionless and connection-oriented communication. The models have been merged to provide a tool supporting the configuration design of BLE devices, during the network design phase that precedes the real implementation. The results highlight the suitability of the proposed tool: the ability to set the device parameters to allow us to keep a practical discovery latency for event-driven sensors and avoid undesired overlaps between scheduled scanning and connection phases due to bad management performed by the central node.

A study on predicting network corrections in PPP-RTK processing

NASA Astrophysics Data System (ADS)

Wang, Kan; Khodabandeh, Amir; Teunissen, Peter

2017-10-01

In PPP-RTK processing, the network corrections including the satellite clocks, the satellite phase biases and the ionospheric delays are provided to the users to enable fast single-receiver integer ambiguity resolution. To solve the rank deficiencies in the undifferenced observation equations, the estimable parameters are formed to generate full-rank design matrix. In this contribution, we firstly discuss the interpretation of the estimable parameters without and with a dynamic satellite clock model incorporated in a Kalman filter during the network processing. The functionality of the dynamic satellite clock model is tested in the PPP-RTK processing. Due to the latency generated by the network processing and data transfer, the network corrections are delayed for the real-time user processing. To bridge the latencies, we discuss and compare two prediction approaches making use of the network corrections without and with the dynamic satellite clock model, respectively. The first prediction approach is based on the polynomial fitting of the estimated network parameters, while the second approach directly follows the dynamic model in the Kalman filter of the network processing and utilises the satellite clock drifts estimated in the network processing. Using 1 Hz data from two networks in Australia, the influences of the two prediction approaches on the user positioning results are analysed and compared for latencies ranging from 3 to 10 s. The accuracy of the positioning results decreases with the increasing latency of the network products. For a latency of 3 s, the RMS of the horizontal and the vertical coordinates (with respect to the ground truth) do not show large differences applying both prediction approaches. For a latency of 10 s, the prediction approach making use of the satellite clock model has generated slightly better positioning results with the differences of the RMS at mm-level. Further advantages and disadvantages of both prediction approaches are also discussed in this contribution.

λ-augmented tree for robust data collection in Advanced Metering Infrastructure

DOE PAGES

Kamto, Joseph; Qian, Lijun; Li, Wei; ...

2016-01-01

In this study, tree multicast configuration of smart meters (SMs) can maintain the connectivity and meet the latency requirements for the Advanced Metering Infrastructure (AMI). However, such topology is extremely weak as any single failure suffices to break its connectivity. On the other hand, the impact of a SM node failure can be more or less significant: a noncut SM node will have a limited local impact compared to a cut SM node that will break the network connectivity. In this work, we design a highly connected tree with a set of backup links to minimize the weakness of treemore » topology of SMs. A topology repair scheme is proposed to address the impact of a SM node failure on the connectivity of the augmented tree network. It relies on a loop detection scheme to define the criticality of a SM node and specifically targets cut SM node by selecting backup parent SM to cover its children. Detailed algorithms to create such AMI tree and related theoretical and complexity analysis are provided with insightful simulation results: sufficient redundancy is provided to alleviate data loss at the cost of signaling overhead. It is however observed that biconnected tree provides the best compromise between the two entities.« less

λ-augmented tree for robust data collection in Advanced Metering Infrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kamto, Joseph; Qian, Lijun; Li, Wei

In this study, tree multicast configuration of smart meters (SMs) can maintain the connectivity and meet the latency requirements for the Advanced Metering Infrastructure (AMI). However, such topology is extremely weak as any single failure suffices to break its connectivity. On the other hand, the impact of a SM node failure can be more or less significant: a noncut SM node will have a limited local impact compared to a cut SM node that will break the network connectivity. In this work, we design a highly connected tree with a set of backup links to minimize the weakness of treemore » topology of SMs. A topology repair scheme is proposed to address the impact of a SM node failure on the connectivity of the augmented tree network. It relies on a loop detection scheme to define the criticality of a SM node and specifically targets cut SM node by selecting backup parent SM to cover its children. Detailed algorithms to create such AMI tree and related theoretical and complexity analysis are provided with insightful simulation results: sufficient redundancy is provided to alleviate data loss at the cost of signaling overhead. It is however observed that biconnected tree provides the best compromise between the two entities.« less

Drawing Inspiration from Human Brain Networks: Construction of Interconnected Virtual Networks

PubMed Central

Kominami, Daichi; Leibnitz, Kenji; Murata, Masayuki

2018-01-01

Virtualization of wireless sensor networks (WSN) is widely considered as a foundational block of edge/fog computing, which is a key technology that can help realize next-generation Internet of things (IoT) networks. In such scenarios, multiple IoT devices and service modules will be virtually deployed and interconnected over the Internet. Moreover, application services are expected to be more sophisticated and complex, thereby increasing the number of modifications required for the construction of network topologies. Therefore, it is imperative to establish a method for constructing a virtualized WSN (VWSN) topology that achieves low latency on information transmission and high resilience against network failures, while keeping the topological construction cost low. In this study, we draw inspiration from inter-modular connectivity in human brain networks, which achieves high performance when dealing with large-scale networks composed of a large number of modules (i.e., regions) and nodes (i.e., neurons). We propose a method for assigning inter-modular links based on a connectivity model observed in the cerebral cortex of the brain, known as the exponential distance rule (EDR) model. We then choose endpoint nodes of these links by controlling inter-modular assortativity, which characterizes the topological connectivity of brain networks. We test our proposed methods using simulation experiments. The results show that the proposed method based on the EDR model can construct a VWSN topology with an optimal combination of communication efficiency, robustness, and construction cost. Regarding the selection of endpoint nodes for the inter-modular links, the results also show that high assortativity enhances the robustness and communication efficiency because of the existence of inter-modular links of two high-degree nodes. PMID:29642483

Drawing Inspiration from Human Brain Networks: Construction of Interconnected Virtual Networks.

PubMed

Murakami, Masaya; Kominami, Daichi; Leibnitz, Kenji; Murata, Masayuki

2018-04-08

Virtualization of wireless sensor networks (WSN) is widely considered as a foundational block of edge/fog computing, which is a key technology that can help realize next-generation Internet of things (IoT) networks. In such scenarios, multiple IoT devices and service modules will be virtually deployed and interconnected over the Internet. Moreover, application services are expected to be more sophisticated and complex, thereby increasing the number of modifications required for the construction of network topologies. Therefore, it is imperative to establish a method for constructing a virtualized WSN (VWSN) topology that achieves low latency on information transmission and high resilience against network failures, while keeping the topological construction cost low. In this study, we draw inspiration from inter-modular connectivity in human brain networks, which achieves high performance when dealing with large-scale networks composed of a large number of modules (i.e., regions) and nodes (i.e., neurons). We propose a method for assigning inter-modular links based on a connectivity model observed in the cerebral cortex of the brain, known as the exponential distance rule (EDR) model. We then choose endpoint nodes of these links by controlling inter-modular assortativity, which characterizes the topological connectivity of brain networks. We test our proposed methods using simulation experiments. The results show that the proposed method based on the EDR model can construct a VWSN topology with an optimal combination of communication efficiency, robustness, and construction cost. Regarding the selection of endpoint nodes for the inter-modular links, the results also show that high assortativity enhances the robustness and communication efficiency because of the existence of inter-modular links of two high-degree nodes.

Low Latency MAC Protocol in Wireless Sensor Networks Using Timing Offset

NASA Astrophysics Data System (ADS)

Choi, Seung Sik

This paper proposes a low latency MAC protocol that can be used in sensor networks. To extend the lifetime of sensor nodes, the conventional solution is to synchronize active/sleep periods of all sensor nodes. However, due to these synchronized sensor nodes, packets in the intermediate nodes must wait until the next node wakes up before it can forward a packet. This induces a large delay in sensor nodes. To solve this latency problem, a clustered sensor network which uses two types of sensor nodes and layered architecture is considered. Clustered heads in each cluster are synchronized with different timing offsets to reduce the sleep delay. Using this concept, the latency problem can be solved and more efficient power usage can be obtained.

77 FR 12100 - Self-Regulatory Organizations; NASDAQ OMX PHLX LLC; Notice of Filing and Immediate Effectiveness...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-28

... proposes a pass-through reduction in the fees for connectivity to Toronto and Chicago venues as follows: (1... low latency telecommunication carriers. The Exchange is passing along the entire savings of the... passing on the reduction in low latency connectivity fees to the Toronto and Chicago venues to the members...

Investigation of Asynchronous Events in Non-Time-Managed Federations

DTIC Science & Technology

2005-09-01

filtering allowed the use of 80% of received messages. The effects of network latency can be minimized by designing for uniformity in latency across the...quantified tradeoffs between time and non-time-managed federations in the presence of network latency, which is a major federation design issue. The...presence sur Ie reseau de trafic peu intense comparativement aux ressources disponibles. On a suppose que la baisse du rendement resultait

Intraoperative dorsal language network mapping by using single-pulse electrical stimulation.

PubMed

Yamao, Yukihiro; Matsumoto, Riki; Kunieda, Takeharu; Arakawa, Yoshiki; Kobayashi, Katsuya; Usami, Kiyohide; Shibata, Sumiya; Kikuchi, Takayuki; Sawamoto, Nobukatsu; Mikuni, Nobuhiro; Ikeda, Akio; Fukuyama, Hidenao; Miyamoto, Susumu

2014-09-01

The preservation of language function during brain surgery still poses a challenge. No intraoperative methods have been established to monitor the language network reliably. We aimed to establish intraoperative language network monitoring by means of cortico-cortical evoked potentials (CCEPs). Subjects were six patients with tumors located close to the arcuate fasciculus (AF) in the language-dominant left hemisphere. Under general anesthesia, the anterior perisylvian language area (AL) was first defined by the CCEP connectivity patterns between the ventrolateral frontal and temporoparietal area, and also by presurgical neuroimaging findings. We then monitored the integrity of the language network by stimulating AL and by recording CCEPs from the posterior perisylvian language area (PL) consecutively during both general anesthesia and awake condition. High-frequency electrical stimulation (ES) performed during awake craniotomy confirmed language function at AL in all six patients. Despite an amplitude decline (≤32%) in two patients, CCEP monitoring successfully prevented persistent language impairment. After tumor removal, single-pulse ES was applied to the white matter tract beneath the floor of the removal cavity in five patients, in order to trace its connections into the language cortices. In three patients in whom high-frequency ES of the white matter produced naming impairment, this "eloquent" subcortical site directly connected AL and PL, judging from the latencies and distributions of cortico- and subcortico-cortical evoked potentials. In conclusion, this study provided the direct evidence that AL, PL, and AF constitute the dorsal language network. Intraoperative CCEP monitoring is clinically useful for evaluating the integrity of the language network. Copyright © 2014 Wiley Periodicals, Inc.

WindTalker: A P2P-Based Low-Latency Anonymous Communication Network

NASA Astrophysics Data System (ADS)

Zhang, Jia; Duan, Haixin; Liu, Wu; Wu, Jianping

Compared with traditional static anonymous communication networks, the P2P architecture can provide higher anonymity in communication. However, the P2P architecture also leads to more challenges, such as route, stability, trust and so on. In this paper, we present WindTalker, a P2P-based low-latency anonymous communication network. It is a pure decentralized mix network and can provide low-latency services which help users hide their real identity in communication. In order to ensure stability and reliability, WindTalker imports “seed nodes” to help a peer join in the P2P network and the peer nodes can use gossip-based protocol to exchange active information. Moreover, WindTalker uses layer encryption to ensure the information of relayed messages cannot be leaked. In addition, malicious nodes in the network are the major threat to anonymity of P2P anonymous communication, so WindTalker imports a trust mechanism which can help the P2P network exclude malicious nodes and optimize the strategy of peer discovery, tunnel construction, and relaying etc. in anonymous communications. We deploy peer nodes of WindTalker in our campus network to test reliability and analyze anonymity in theory. The network measurement and simulation analysis shows that WindTalker can provide low-latency and reliable anonymous communication services.

A low-latency high-port count optical switch with optical delay line buffering for disaggregated data centers

NASA Astrophysics Data System (ADS)

Moralis-Pegios, M.; Terzenidis, N.; Mourgias-Alexandris, G.; Vyrsokinos, K.; Pleros, N.

2018-02-01

Disaggregated Data Centers (DCs) have emerged as a powerful architectural framework towards increasing resource utilization and system power efficiency, requiring, however, a networking infrastructure that can ensure low-latency and high-bandwidth connectivity between a high-number of interconnected nodes. This reality has been the driving force towards high-port count and low-latency optical switching platforms, with recent efforts concluding that the use of distributed control architectures as offered by Broadcast-and-Select (BS) layouts can lead to sub-μsec latencies. However, almost all high-port count optical switch designs proposed so far rely either on electronic buffering and associated SerDes circuitry for resolving contention or on buffer-less designs with packet drop and re-transmit procedures, unavoidably increasing latency or limiting throughput. In this article, we demonstrate a 256x256 optical switch architecture for disaggregated DCs that employs small-size optical delay line buffering in a distributed control scheme, exploiting FPGA-based header processing over a hybrid BS/Wavelength routing topology that is implemented by a 16x16 BS design and a 16x16 AWGR. Simulation-based performance analysis reveals that even the use of a 2- packet optical buffer can yield <620nsec latency with >85% throughput for up to 100% loads. The switch has been experimentally validated with 10Gb/s optical data packets using 1:16 optical splitting and a SOA-MZI wavelength converter (WC) along with fiber delay lines for the 2-packet buffer implementation at every BS outgoing port, followed by an additional SOA-MZI tunable WC and the 16x16 AWGR. Error-free performance in all different switch input/output combinations has been obtained with a power penalty of <2.5dB.

An All-Optical Access Metro Interface for Hybrid WDM/TDM PON Based on OBS

NASA Astrophysics Data System (ADS)

Segarra, Josep; Sales, Vicent; Prat, Josep

2007-04-01

A new all-optical access metro network interface based on optical burst switching (OBS) is proposed. A hybrid wavelength-division multiplexing/time-division multiplexing (WDM/TDM) access architecture with reflective optical network units (ONUs), an arrayed-waveguide-grating outside plant, and a tunable laser stack at the optical line terminal (OLT) is presented as a solution for the passive optical network. By means of OBS and a dynamic bandwidth allocation (DBA) protocol, which polls the ONUs, the available access bandwidth is managed. All the network intelligence and costly equipment is located at the OLT, where the DBA module is centrally implemented, providing quality of service (QoS). To scale this access network, an optical cross connect (OXC) is then used to attain a large number of ONUs by the same OLT. The hybrid WDM/TDM structure is also extended toward the metropolitan area network (MAN) by introducing the concept of OBS multiplexer (OBS-M). The network element OBS-M bridges the MAN and access networks by offering all-optical cross connection, wavelength conversion, and data signaling. The proposed innovative OBS-M node yields a full optical data network, interfacing access and metro with a geographically distributed access control. The resulting novel access metro architectures are nonblocking and, with an improved signaling, provide QoS, scalability, and very low latency. Finally, numerical analysis and simulations demonstrate the traffic performance of the proposed access scheme and all-optical access metro interface and architectures.

Cutter Connectivity Bandwidth Study

NASA Astrophysics Data System (ADS)

2002-10-01

The goal of this study was to determine how much bandwidth is required for cutters to meet emerging data transfer requirements. The Cutter Connectivity Business Solutions Team with guidance front the Commandant's 5 Innovation Council sponsored this study. Today, many Coast Guard administrative and business functions are being conducted via electronic means. Although our larger cutters can establish part-time connectivity using commercial satellite communications (SATCOM) while underway, there are numerous complaints regarding poor application performance. Additionally, smaller cutters do not have any standard means of underway connectivity. The R&D study shows the most important factor affecting web performance and enterprise applications onboard cutters was latency. Latency describes the time it takes the signal to reach the satellite and come back down through space. The latency due to use of higher orbit satellites is causing poor application performance and inefficient use of expensive SATCOM links. To improve performance, the CC must, (1) reduce latency by using alternate communications links such as low-earth orbit satellites, (2) tailor applications to the SATCOM link and/or (3) optimize protocols used for data communication to minimize time required by present applications to establish communications between the user and the host systems.

Reconfigurable-logic-based fiber channel network card

NASA Astrophysics Data System (ADS)

Casselman, Steve

1996-10-01

Currently all networking hardware must have predefined tradeoffs between latency and bandwidth. In some applications one feature is more important than the other. We present a system where the tradeoff can be made on a case by case basis. To show this we implement an extremely low latency semaphore passing network within a point to point system.

Fault-Tolerant Self-Stabilizing Distributed Clock Synchronization Protocol for Arbitrary Digraphs

NASA Technical Reports Server (NTRS)

Malekpour, Mahyar R. (Inventor)

2014-01-01

A self-stabilizing network in the form of an arbitrary, non-partitioned digraph includes K nodes having a synchronizer executing a protocol. K-1 monitors of each node may receive a Sync message transmitted from a directly connected node. When the Sync message is received, the logical clock value for the receiving node is set to between 0 and a communication latency value (gamma) if the clock value is less than a minimum event-response delay (D). A new Sync message is also transmitted to any directly connected nodes if the clock value is greater than or equal to both D and a graph threshold (T(sub S)). When the Sync message is not received the synchronizer increments the clock value if the clock value is less than a resynchronization period (P), and resets the clock value and transmits a new Sync message to all directly connected nodes when the clock value equals or exceeds P.

Industrial WSN Based on IR-UWB and a Low-Latency MAC Protocol

NASA Astrophysics Data System (ADS)

Reinhold, Rafael; Underberg, Lisa; Wulf, Armin; Kays, Ruediger

2016-07-01

Wireless sensor networks for industrial communication require high reliability and low latency. As current wireless sensor networks do not entirely meet these requirements, novel system approaches need to be developed. Since ultra wideband communication systems seem to be a promising approach, this paper evaluates the performance of the IEEE 802.15.4 impulse-radio ultra-wideband physical layer and the IEEE 802.15.4 Low Latency Deterministic Network (LLDN) MAC for industrial applications. Novel approaches and system adaptions are proposed to meet the application requirements. In this regard, a synchronization approach based on circular average magnitude difference functions (CAMDF) and on a clean template (CT) is presented for the correlation receiver. An adapted MAC protocol titled aggregated low latency (ALL) MAC is proposed to significantly reduce the resulting latency. Based on the system proposals, a hardware prototype has been developed, which proves the feasibility of the system and visualizes the real-time performance of the MAC protocol.

De-optical-line-terminal hybrid access-aggregation optical network for time-sensitive services based on software-defined networking orchestration

NASA Astrophysics Data System (ADS)

Bai, Wei; Yang, Hui; Xiao, Hongyun; Yu, Ao; He, Linkuan; Zhang, Jie; Li, Zhen; Du, Yi

2017-11-01

With the increase in varieties of services in network, time-sensitive services (TSSs) appear and bring forward an impending need for delay performance. Ultralow-latency communication has become one of the important development goals for many scenarios in the coming 5G era (e.g., robotics and driverless cars). However, the conventional methods, which decrease delay by promoting the available resources and the network transmission speed, have limited effect; a new breakthrough for ultralow-latency communication is necessary. We propose a de-optical-line-terminal (De-OLT) hybrid access-aggregation optical network (DAON) for TSS based on software-defined networking (SDN) orchestration. In this network, low-latency all-optical communication based on optical burst switching can be achieved by removing OLT. For supporting this network and guaranteeing the quality of service for TSSs, we design SDN-driven control method and service provision method. Numerical results demonstrate the proposed DAON promotes network service efficiency and avoids traffic congestion.

Performance Evaluation of Bluetooth Low Energy: A Systematic Review.

PubMed

Tosi, Jacopo; Taffoni, Fabrizio; Santacatterina, Marco; Sannino, Roberto; Formica, Domenico

2017-12-13

Small, compact and embedded sensors are a pervasive technology in everyday life for a wide number of applications (e.g., wearable devices, domotics, e-health systems, etc.). In this context, wireless transmission plays a key role, and among available solutions, Bluetooth Low Energy (BLE) is gaining more and more popularity. BLE merges together good performance, low-energy consumption and widespread diffusion. The aim of this work is to review the main methodologies adopted to investigate BLE performance. The first part of this review is an in-depth description of the protocol, highlighting the main characteristics and implementation details. The second part reviews the state of the art on BLE characteristics and performance. In particular, we analyze throughput, maximum number of connectable sensors, power consumption, latency and maximum reachable range, with the aim to identify what are the current limits of BLE technology. The main results can be resumed as follows: throughput may theoretically reach the limit of ~230 kbps, but actual applications analyzed in this review show throughputs limited to ~100 kbps; the maximum reachable range is strictly dependent on the radio power, and it goes up to a few tens of meters; the maximum number of nodes in the network depends on connection parameters, on the network architecture and specific device characteristics, but it is usually lower than 10; power consumption and latency are largely modeled and analyzed and are strictly dependent on a huge number of parameters. Most of these characteristics are based on analytical models, but there is a need for rigorous experimental evaluations to understand the actual limits.

Performance Evaluation of Bluetooth Low Energy: A Systematic Review

PubMed Central

Taffoni, Fabrizio; Santacatterina, Marco; Sannino, Roberto

2017-01-01

Small, compact and embedded sensors are a pervasive technology in everyday life for a wide number of applications (e.g., wearable devices, domotics, e-health systems, etc.). In this context, wireless transmission plays a key role, and among available solutions, Bluetooth Low Energy (BLE) is gaining more and more popularity. BLE merges together good performance, low-energy consumption and widespread diffusion. The aim of this work is to review the main methodologies adopted to investigate BLE performance. The first part of this review is an in-depth description of the protocol, highlighting the main characteristics and implementation details. The second part reviews the state of the art on BLE characteristics and performance. In particular, we analyze throughput, maximum number of connectable sensors, power consumption, latency and maximum reachable range, with the aim to identify what are the current limits of BLE technology. The main results can be resumed as follows: throughput may theoretically reach the limit of ~230 kbps, but actual applications analyzed in this review show throughputs limited to ~100 kbps; the maximum reachable range is strictly dependent on the radio power, and it goes up to a few tens of meters; the maximum number of nodes in the network depends on connection parameters, on the network architecture and specific device characteristics, but it is usually lower than 10; power consumption and latency are largely modeled and analyzed and are strictly dependent on a huge number of parameters. Most of these characteristics are based on analytical models, but there is a need for rigorous experimental evaluations to understand the actual limits. PMID:29236085

Low Power Multi-Hop Networking Analysis in Intelligent Environments.

PubMed

Etxaniz, Josu; Aranguren, Gerardo

2017-05-19

Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide.

Low Power Multi-Hop Networking Analysis in Intelligent Environments

PubMed Central

Etxaniz, Josu; Aranguren, Gerardo

2017-01-01

Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide. PMID:28534847

Sentient networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chapline, G.

1998-03-01

The engineering problems of constructing autonomous networks of sensors and data processors that can provide alerts for dangerous situations provide a new context for debating the question whether man-made systems can emulate the cognitive capabilities of the mammalian brain. In this paper we consider the question whether a distributed network of sensors and data processors can form ``perceptions`` based on sensory data. Because sensory data can have exponentially many explanations, the use of a central data processor to analyze the outputs from a large ensemble of sensors will in general introduce unacceptable latencies for responding to dangerous situations. A bettermore » idea is to use a distributed ``Helmholtz machine`` architecture in which the sensors are connected to a network of simple processors, and the collective state of the network as a whole provides an explanation for the sensory data. In general communication within such a network will require time division multiplexing, which opens the door to the possibility that with certain refinements to the Helmholtz machine architecture it may be possible to build sensor networks that exhibit a form of artificial consciousness.« less

Hybrid Mobile Communication Networks for Planetary Exploration

NASA Technical Reports Server (NTRS)

Alena, Richard; Lee, Charles; Walker, Edward; Osenfort, John; Stone, Thom

2007-01-01

A paper discusses the continuing work of the Mobile Exploration System Project, which has been performing studies toward the design of hybrid communication networks for future exploratory missions to remote planets. A typical network could include stationary radio transceivers on a remote planet, mobile radio transceivers carried by humans and robots on the planet, terrestrial units connected via the Internet to an interplanetary communication system, and radio relay transceivers aboard spacecraft in orbit about the planet. Prior studies have included tests on prototypes of these networks deployed in Arctic and desert regions chosen to approximate environmental conditions on Mars. Starting from the findings of the prior studies, the paper discusses methods of analysis, design, and testing of the hybrid communication networks. It identifies key radio-frequency (RF) and network engineering issues. Notable among these issues is the study of wireless LAN throughput loss due to repeater use, RF signal strength, and network latency variations. Another major issue is that of using RF-link analysis to ensure adequate link margin in the face of statistical variations in signal strengths.

Using Arduino microcontroller boards to measure response latencies.

PubMed

Schubert, Thomas W; D'Ausilio, Alessandro; Canto, Rosario

2013-12-01

Latencies of buttonpresses are a staple of cognitive science paradigms. Often keyboards are employed to collect buttonpresses, but their imprecision and variability decreases test power and increases the risk of false positives. Response boxes and data acquisition cards are precise, but expensive and inflexible, alternatives. We propose using open-source Arduino microcontroller boards as an inexpensive and flexible alternative. These boards connect to standard experimental software using a USB connection and a virtual serial port, or by emulating a keyboard. In our solution, an Arduino measures response latencies after being signaled the start of a trial, and communicates the latency and response back to the PC over a USB connection. We demonstrated the reliability, robustness, and precision of this communication in six studies. Test measures confirmed that the error added to the measurement had an SD of less than 1 ms. Alternatively, emulation of a keyboard results in similarly precise measurement. The Arduino performs as well as a serial response box, and better than a keyboard. In addition, our setup allows for the flexible integration of other sensors, and even actuators, to extend the cognitive science toolbox.

Optical multicast system for data center networks.

PubMed

Samadi, Payman; Gupta, Varun; Xu, Junjie; Wang, Howard; Zussman, Gil; Bergman, Keren

2015-08-24

We present the design and experimental evaluation of an Optical Multicast System for Data Center Networks, a hardware-software system architecture that uniquely integrates passive optical splitters in a hybrid network architecture for faster and simpler delivery of multicast traffic flows. An application-driven control plane manages the integrated optical and electronic switched traffic routing in the data plane layer. The control plane includes a resource allocation algorithm to optimally assign optical splitters to the flows. The hardware architecture is built on a hybrid network with both Electronic Packet Switching (EPS) and Optical Circuit Switching (OCS) networks to aggregate Top-of-Rack switches. The OCS is also the connectivity substrate of splitters to the optical network. The optical multicast system implementation requires only commodity optical components. We built a prototype and developed a simulation environment to evaluate the performance of the system for bulk multicasting. Experimental and numerical results show simultaneous delivery of multicast flows to all receivers with steady throughput. Compared to IP multicast that is the electronic counterpart, optical multicast performs with less protocol complexity and reduced energy consumption. Compared to peer-to-peer multicast methods, it achieves at minimum an order of magnitude higher throughput for flows under 250 MB with significantly less connection overheads. Furthermore, for delivering 20 TB of data containing only 15% multicast flows, it reduces the total delivery energy consumption by 50% and improves latency by 55% compared to a data center with a sole non-blocking EPS network.

Source space analysis of event-related dynamic reorganization of brain networks.

PubMed

Ioannides, Andreas A; Dimitriadis, Stavros I; Saridis, George A; Voultsidou, Marotesa; Poghosyan, Vahe; Liu, Lichan; Laskaris, Nikolaos A

2012-01-01

How the brain works is nowadays synonymous with how different parts of the brain work together and the derivation of mathematical descriptions for the functional connectivity patterns that can be objectively derived from data of different neuroimaging techniques. In most cases static networks are studied, often relying on resting state recordings. Here, we present a quantitative study of dynamic reconfiguration of connectivity for event-related experiments. Our motivation is the development of a methodology that can be used for personalized monitoring of brain activity. In line with this motivation, we use data with visual stimuli from a typical subject that participated in different experiments that were previously analyzed with traditional methods. The earlier studies identified well-defined changes in specific brain areas at specific latencies related to attention, properties of stimuli, and tasks demands. Using a recently introduced methodology, we track the event-related changes in network organization, at source space level, thus providing a more global and complete view of the stages of processing associated with the regional changes in activity. The results suggest the time evolving modularity as an additional brain code that is accessible with noninvasive means and hence available for personalized monitoring and clinical applications.

Energy latency tradeoffs for medium access and sleep scheduling in wireless sensor networks

NASA Astrophysics Data System (ADS)

Gang, Lu

Wireless sensor networks are expected to be used in a wide range of applications from environment monitoring to event detection. The key challenge is to provide energy efficient communication; however, latency remains an important concern for many applications that require fast response. The central thesis of this work is that energy efficient medium access and sleep scheduling mechanisms can be designed without necessarily sacrificing application-specific latency performance. We validate this thesis through results from four case studies that cover various aspects of medium access and sleep scheduling design in wireless sensor networks. Our first effort, DMAC, is to design an adaptive low latency and energy efficient MAC for data gathering to reduce the sleep latency. We propose staggered schedule, duty cycle adaptation, data prediction and the use of more-to-send packets to enable seamless packet forwarding under varying traffic load and channel contentions. Simulation and experimental results show significant energy savings and latency reduction while ensuring high data reliability. The second research effort, DESS, investigates the problem of designing sleep schedules in arbitrary network communication topologies to minimize the worst case end-to-end latency (referred to as delay diameter). We develop a novel graph-theoretical formulation, derive and analyze optimal solutions for the tree and ring topologies and heuristics for arbitrary topologies. The third study addresses the problem of minimum latency joint scheduling and routing (MLSR). By constructing a novel delay graph, the optimal joint scheduling and routing can be solved by M node-disjoint paths algorithm under multiple channel model. We further extended the algorithm to handle dynamic traffic changes and topology changes. A heuristic solution is proposed for MLSR under single channel interference. In the fourth study, EEJSPC, we first formulate a fundamental optimization problem that provides tunable energy-latency-throughput tradeoffs with joint scheduling and power control and present both exponential and polynomial complexity solutions. Then we investigate the problem of minimizing total transmission energy while satisfying transmission requests within a latency bound, and present an iterative approach which converges rapidly to the optimal parameter settings.

Latency in Distributed Acquisition and Rendering for Telepresence Systems.

PubMed

Ohl, Stephan; Willert, Malte; Staadt, Oliver

2015-12-01

Telepresence systems use 3D techniques to create a more natural human-centered communication over long distances. This work concentrates on the analysis of latency in telepresence systems where acquisition and rendering are distributed. Keeping latency low is important to immerse users in the virtual environment. To better understand latency problems and to identify the source of such latency, we focus on the decomposition of system latency into sub-latencies. We contribute a model of latency and show how it can be used to estimate latencies in a complex telepresence dataflow network. To compare the estimates with real latencies in our prototype, we modify two common latency measurement methods. This presented methodology enables the developer to optimize the design, find implementation issues and gain deeper knowledge about specific sources of latency.

Development of face recognition: Dynamic causal modelling of MEG data.

PubMed

He, Wei; Johnson, Blake W

2018-04-01

Electrophysiological studies of adults indicate that brain activity is enhanced during viewing of repeated faces, at a latency of about 250 ms after the onset of the face (M250/N250). The present study aimed to determine if this effect was also present in preschool-aged children, whose brain activity was measured in a custom-sized pediatric MEG system. The results showed that, unlike adults, face repetition did not show any significant modulation of M250 amplitude in children; however children's M250 latencies were significantly faster for repeated than non-repeated faces. Dynamic causal modelling (DCM) of the M250 in both age groups tested the effects of face repetition within the core face network including the occipital face area (OFA), the fusiform face area (FFA), and the superior temporal sulcus (STS). DCM revealed that repetition of identical faces altered both forward and backward connections in children and adults; however the modulations involved inputs to both FFA and OFA in adults but only to OFA in children. These findings suggest that the amplitude-insensitivity of the immature M250 may be due to a weaker connection between the FFA and lower visual areas. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Fast MAC-Layer Handover for an IEEE 802.16e-Based WMAN

NASA Astrophysics Data System (ADS)

Ray, Sayan K.; Pawlikowski, Krzysztof; Sirisena, Harsha

We propose a modification of the IEEE 802.16e hard handover (HHO) procedure, which significantly reduces the handover latency constraint of the original HHO procedure in IEEE 802.16e networks. It allows a better handling of the delay-sensitive traffic by avoiding unnecessary time-consuming scanning and synchronization activity as well as simplifies the network re-entry procedure. With the help of the backhaul network, it reduces the number of control messages in the original handover policy, making the handover latency acceptable also for real-time streaming traffic. Preliminary performance evaluation studies show that the modified handover procedure is able to reduce the total handover latency by about 50%.

Data Delivery Latency Improvements And First Steps Towards The Distributed Computing Of The Caltech/USGS Southern California Seismic Network Earthquake Early Warning System

NASA Astrophysics Data System (ADS)

Stubailo, I.; Watkins, M.; Devora, A.; Bhadha, R. J.; Hauksson, E.; Thomas, V. I.

2016-12-01

The USGS/Caltech Southern California Seismic Network (SCSN) is a modern digital ground motion seismic network. It develops and maintains Earthquake Early Warning (EEW) data collection and delivery systems in southern California as well as real-time EEW algorithms. Recently, Behr et al., SRL, 2016 analyzed data from several regional seismic networks deployed around the globe. They showed that the SCSN was the network with the smallest data communication delays or latency. Since then, we have reduced further the telemetry delays for many of the 330 current sites. The latency has been reduced on average from 2-6 sec to 0.4 seconds by tuning the datalogger parameters and/or deploying software upgrades. Recognizing the latency data as one of the crucial parameters in EEW, we have started archiving the per-packet latencies in mseed format for all the participating sites in a similar way it is traditionally done for the seismic waveform data. The archived latency values enable us to understand and document long-term changes in performance of the telemetry links. We can also retroactively investigate how latent the waveform data were during a specific event or during a specific time period. In addition the near-real time latency values are useful for monitoring and displaying the real-time station latency, in particular to compare different telemetry technologies. A future step to reduce the latency is to deploy the algorithms on the dataloggers at the seismic stations and transmit either the final solutions or intermediate parameters to a central processing center. To implement this approach, we are developing a stand-alone version of the OnSite algorithm to run on the dataloggers in the field. This will increase the resiliency of the SCSN to potential telemetry restrictions in the immediate aftermath of a large earthquake, either by allowing local alarming by the single station, or permitting transmission of lightweight parametric information rather than continuous waveform data to the central processing facility. State-of-the-art development of Internet of Things (IoT) tools and platforms, which can be used to distribute and maintain software on a large number of remote devices are making this approach to earthquake early warning more feasible.

5G: rethink mobile communications for 2020+.

PubMed

Chih-Lin, I; Han, Shuangfeng; Xu, Zhikun; Sun, Qi; Pan, Zhengang

2016-03-06

The 5G network is anticipated to meet the challenging requirements of mobile traffic in the 2020s, which are characterized by super high data rate, low latency, high mobility, high energy efficiency and high traffic density. This paper provides an overview of China Mobile's 5G vision and potential solutions. Three key characteristics of 5G are analysed, i.e. super fast, soft and green. The main 5G R&D themes are further elaborated, which include five fundamental rethinkings of the traditional design methodologies. The 5G network design considerations are also discussed, with cloud radio access network, ultra-dense network, software defined network and network function virtualization examined as key potential solutions towards a green and soft 5G network. The paradigm shift to user-centric network operation from the traditional cell-centric operation is also investigated, where the decoupled downlink and uplink, control and data, and adaptive multiple connections provide sufficient means to achieve a user-centric 5G network with 'no more cells'. The software defined air interface is investigated under a uniform framework and can adaptively adapt the parameters to well satisfy various requirements in different 5G scenarios. © 2016 The Author(s).

CSMA Versus Prioritized CSMA for Air-Traffic-Control Improvement

NASA Technical Reports Server (NTRS)

Robinson, Daryl C.

2001-01-01

OPNET version 7.0 simulations are presented involving an important application of the Aeronautical Telecommunications Network (ATN), Controller Pilot Data Link Communications (CPDLC) over the Very High Frequency Data Link, Mode 2 (VDL-2). Communication is modeled for essentially all incoming and outgoing nonstop air-traffic for just three United States cities: Cleveland, Cincinnati, and Detroit. There are 32 airports in the simulation, 29 of which are either sources or destinations for the air-traffic of the aforementioned three airports. The simulation involves 111 Air Traffic Control (ATC) ground stations, and 1,235 equally equipped aircraft-taking off, flying realistic free-flight trajectories, and landing in a 24-hr period. Collisionless, Prioritized Carrier Sense Multiple Access (CSMA) is successfully tested and compared with the traditional CSMA typically associated with VDL-2. The performance measures include latency, throughput, and packet loss. As expected, Prioritized CSMA is much quicker and more efficient than traditional CSMA. These simulation results show the potency of Prioritized CSMA for implementing low latency, high throughput, and efficient connectivity.

A prototype Infrastructure for Cloud-based distributed services in High Availability over WAN

NASA Astrophysics Data System (ADS)

Bulfon, C.; Carlino, G.; De Salvo, A.; Doria, A.; Graziosi, C.; Pardi, S.; Sanchez, A.; Carboni, M.; Bolletta, P.; Puccio, L.; Capone, V.; Merola, L.

2015-12-01

In this work we present the architectural and performance studies concerning a prototype of a distributed Tier2 infrastructure for HEP, instantiated between the two Italian sites of INFN-Romal and INFN-Napoli. The network infrastructure is based on a Layer-2 geographical link, provided by the Italian NREN (GARR), directly connecting the two remote LANs of the named sites. By exploiting the possibilities offered by the new distributed file systems, a shared storage area with synchronous copy has been set up. The computing infrastructure, based on an OpenStack facility, is using a set of distributed Hypervisors installed in both sites. The main parameter to be taken into account when managing two remote sites with a single framework is the effect of the latency, due to the distance and the end-to-end service overhead. In order to understand the capabilities and limits of our setup, the impact of latency has been investigated by means of a set of stress tests, including data I/O throughput, metadata access performance evaluation and network occupancy, during the life cycle of a Virtual Machine. A set of resilience tests has also been performed, in order to verify the stability of the system on the event of hardware or software faults. The results of this work show that the reliability and robustness of the chosen architecture are effective enough to build a production system and to provide common services. This prototype can also be extended to multiple sites with small changes of the network topology, thus creating a National Network of Cloud-based distributed services, in HA over WAN.

CISN ShakeAlert Earthquake Early Warning System Monitoring Tools

NASA Astrophysics Data System (ADS)

Henson, I. H.; Allen, R. M.; Neuhauser, D. S.

2015-12-01

CISN ShakeAlert is a prototype earthquake early warning system being developed and tested by the California Integrated Seismic Network. The system has recently been expanded to support redundant data processing and communications. It now runs on six machines at three locations with ten Apache ActiveMQ message brokers linking together 18 waveform processors, 12 event association processes and 4 Decision Module alert processes. The system ingests waveform data from about 500 stations and generates many thousands of triggers per day, from which a small portion produce earthquake alerts. We have developed interactive web browser system-monitoring tools that display near real time state-of-health and performance information. This includes station availability, trigger statistics, communication and alert latencies. Connections to regional earthquake catalogs provide a rapid assessment of the Decision Module hypocenter accuracy. Historical performance can be evaluated, including statistics for hypocenter and origin time accuracy and alert time latencies for different time periods, magnitude ranges and geographic regions. For the ElarmS event associator, individual earthquake processing histories can be examined, including details of the transmission and processing latencies associated with individual P-wave triggers. Individual station trigger and latency statistics are available. Detailed information about the ElarmS trigger association process for both alerted events and rejected events is also available. The Google Web Toolkit and Map API have been used to develop interactive web pages that link tabular and geographic information. Statistical analysis is provided by the R-Statistics System linked to a PostgreSQL database.

A macrochip interconnection network enabled by silicon nanophotonic devices.

PubMed

Zheng, Xuezhe; Cunningham, John E; Koka, Pranay; Schwetman, Herb; Lexau, Jon; Ho, Ron; Shubin, Ivan; Krishnamoorthy, Ashok V; Yao, Jin; Mekis, Attila; Pinguet, Thierry

2010-03-01

We present an advanced wavelength-division multiplexing point-to-point network enabled by silicon nanophotonic devices. This network offers strictly non-blocking all-to-all connectivity while maximizing bisection bandwidth, making it ideal for multi-core and multi-processor interconnections. We introduce one of the key components, the nanophotonic grating coupler, and discuss, for the first time, how this device can be useful for practical implementations of the wavelength-division multiplexing network using optical proximity communications. Finite difference time-domain simulation of the nanophotonic grating coupler device indicates that it can be made compact (20 microm x 50 microm), low loss (3.8 dB), and broadband (100 nm). These couplers require subwavelength material modulation at the nanoscale to achieve the desired functionality. We show that optical proximity communication provides unmatched optical I/O bandwidth density to electrical chips, which enables the application of wavelength-division multiplexing point-to-point network in macrochip with unprecedented bandwidth-density. The envisioned physical implementation is discussed. The benefits of such an interconnect network include a 5-6x improvement in latency when compared to a purely electronic implementation. Performance analysis shows that the wavelength-division multiplexing point-to-point network offers better overall performance over other optical network architectures.

A Reinforcement Sensor Embedded Vertical Handoff Controller for Vehicular Heterogeneous Wireless Networks

PubMed Central

Li, Limin; Xu, Yubin; Soong, Boon-Hee; Ma, Lin

2013-01-01

Vehicular communication platforms that provide real-time access to wireless networks have drawn more and more attention in recent years. IEEE 802.11p is the main radio access technology that supports communication for high mobility terminals, however, due to its limited coverage, IEEE 802.11p is usually deployed by coupling with cellular networks to achieve seamless mobility. In a heterogeneous cellular/802.11p network, vehicular communication is characterized by its short time span in association with a wireless local area network (WLAN). Moreover, for the media access control (MAC) scheme used for WLAN, the network throughput dramatically decreases with increasing user quantity. In response to these compelling problems, we propose a reinforcement sensor (RFS) embedded vertical handoff control strategy to support mobility management. The RFS has online learning capability and can provide optimal handoff decisions in an adaptive fashion without prior knowledge. The algorithm integrates considerations including vehicular mobility, traffic load, handoff latency, and network status. Simulation results verify that the proposed algorithm can adaptively adjust the handoff strategy, allowing users to stay connected to the best network. Furthermore, the algorithm can ensure that RSUs are adequate, thereby guaranteeing a high quality user experience. PMID:24193101

D-MSR: a distributed network management scheme for real-time monitoring and process control applications in wireless industrial automation.

PubMed

Zand, Pouria; Dilo, Arta; Havinga, Paul

2013-06-27

Current wireless technologies for industrial applications, such as WirelessHART and ISA100.11a, use a centralized management approach where a central network manager handles the requirements of the static network. However, such a centralized approach has several drawbacks. For example, it cannot cope with dynamicity/disturbance in large-scale networks in a real-time manner and it incurs a high communication overhead and latency for exchanging management traffic. In this paper, we therefore propose a distributed network management scheme, D-MSR. It enables the network devices to join the network, schedule their communications, establish end-to-end connections by reserving the communication resources for addressing real-time requirements, and cope with network dynamicity (e.g., node/edge failures) in a distributed manner. According to our knowledge, this is the first distributed management scheme based on IEEE 802.15.4e standard, which guides the nodes in different phases from joining until publishing their sensor data in the network. We demonstrate via simulation that D-MSR can address real-time and reliable communication as well as the high throughput requirements of industrial automation wireless networks, while also achieving higher efficiency in network management than WirelessHART, in terms of delay and overhead.

D-MSR: A Distributed Network Management Scheme for Real-Time Monitoring and Process Control Applications in Wireless Industrial Automation

PubMed Central

Zand, Pouria; Dilo, Arta; Havinga, Paul

2013-01-01

Current wireless technologies for industrial applications, such as WirelessHART and ISA100.11a, use a centralized management approach where a central network manager handles the requirements of the static network. However, such a centralized approach has several drawbacks. For example, it cannot cope with dynamicity/disturbance in large-scale networks in a real-time manner and it incurs a high communication overhead and latency for exchanging management traffic. In this paper, we therefore propose a distributed network management scheme, D-MSR. It enables the network devices to join the network, schedule their communications, establish end-to-end connections by reserving the communication resources for addressing real-time requirements, and cope with network dynamicity (e.g., node/edge failures) in a distributed manner. According to our knowledge, this is the first distributed management scheme based on IEEE 802.15.4e standard, which guides the nodes in different phases from joining until publishing their sensor data in the network. We demonstrate via simulation that D-MSR can address real-time and reliable communication as well as the high throughput requirements of industrial automation wireless networks, while also achieving higher efficiency in network management than WirelessHART, in terms of delay and overhead. PMID:23807687

Latency-Efficient Communication in Wireless Mesh Networks under Consideration of Large Interference Range

NASA Astrophysics Data System (ADS)

Xin, Qin; Yao, Xiaolan; Engelstad, Paal E.

2010-09-01

Wireless Mesh Networking is an emerging communication paradigm to enable resilient, cost-efficient and reliable services for the future-generation wireless networks. We study here the minimum-latency communication primitive of gossiping (all-to-all communication) in multi-hop ad-hoc Wireless Mesh Networks (WMNs). Each mesh node in the WMN is initially given a message and the objective is to design a minimum-latency schedule such that each mesh node distributes its message to all other mesh nodes. Minimum-latency gossiping problem is well known to be NP-hard even for the scenario in which the topology of the WMN is known to all mesh nodes in advance. In this paper, we propose a new latency-efficient approximation scheme that can accomplish gossiping task in polynomial time units in any ad-hoc WMN under consideration of Large Interference Range (LIR), e.g., the interference range is much larger than the transmission range. To the best of our knowledge, it is first time to investigate such a scenario in ad-hoc WMNs under LIR, our algorithm allows the labels (e.g., identifiers) of the mesh nodes to be polynomially large in terms of the size of the WMN, which is the first time that the scenario of large labels has been considered in ad-hoc WMNs under LIR. Furthermore, our gossiping scheme can be considered as a framework which can be easily implied to the scenario under consideration of mobility-related issues since we assume that the mesh nodes have no knowledge on the network topology even for its neighboring mesh nodes.

Stochastic Characterization of Communication Network Latency for Wide Area Grid Control Applications.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ameme, Dan Selorm Kwami; Guttromson, Ross

This report characterizes communications network latency under various network topologies and qualities of service (QoS). The characterizations are probabilistic in nature, allowing deeper analysis of stability for Internet Protocol (IP) based feedback control systems used in grid applications. The work involves the use of Raspberry Pi computers as a proxy for a controlled resource, and an ns-3 network simulator on a Linux server to create an experimental platform (testbed) that can be used to model wide-area grid control network communications in smart grid. Modbus protocol is used for information transport, and Routing Information Protocol is used for dynamic route selectionmore » within the simulated network.« less

Collective network for computer structures

DOEpatents

Blumrich, Matthias A; Coteus, Paul W; Chen, Dong; Gara, Alan; Giampapa, Mark E; Heidelberger, Philip; Hoenicke, Dirk; Takken, Todd E; Steinmacher-Burow, Burkhard D; Vranas, Pavlos M

2014-01-07

A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to the needs of a processing algorithm.

Collective network for computer structures

DOEpatents

Blumrich, Matthias A [Ridgefield, CT; Coteus, Paul W [Yorktown Heights, NY; Chen, Dong [Croton On Hudson, NY; Gara, Alan [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Hoenicke, Dirk [Ossining, NY; Takken, Todd E [Brewster, NY; Steinmacher-Burow, Burkhard D [Wernau, DE; Vranas, Pavlos M [Bedford Hills, NY

2011-08-16

A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices ate included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network and class structures. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to needs of a processing algorithm.

A metro-access integrated network with all-optical virtual private network function using DPSK/ASK modulation format

NASA Astrophysics Data System (ADS)

Tian, Yue; Leng, Lufeng; Su, Yikai

2008-11-01

All-optical virtual private network (VPN), which offers dedicated optical channels to connect users within a VPN group, is considered a promising approach to efficient internetworking with low latency and enhanced security implemented in the physical layer. On the other hand, time-division multiplexed (TDM) / wavelength-division multiplexed (WDM) network architecture based on a feeder-ring with access-tree topology, is considered a pragmatic migration scenario from current TDM-PONs to future WDM-PONs and a potential convergence scheme for access and metropolitan networks, due to its efficiently shared hardware and bandwidth resources. All-optical VPN internetworking in such a metro-access integrated structure is expected to cover a wider service area and therefore is highly desirable. In this paper, we present a TDM/WDM metro-access integrated network supporting all-optical VPN internetworking among ONUs in different sub- PONs based on orthogonal differential-phase-shift keying (DPSK) / amplitude-shift keying (ASK) modulation format. In each ONU, no laser but a single Mach-Zehnder modulator (MZM) is needed for the upstream and VPN signal generation, which is cost-effective. Experiments and simulations are performed to verify its feasibility as a potential solution to the future access service.

Fuzzy Logic based Handoff Latency Reduction Mechanism in Layer 2 of Heterogeneous Mobile IPv6 Networks

NASA Astrophysics Data System (ADS)

Anwar, Farhat; Masud, Mosharrof H.; Latif, Suhaimi A.

2013-12-01

Mobile IPv6 (MIPv6) is one of the pioneer standards that support mobility in IPv6 environment. It has been designed to support different types of technologies for providing seamless communications in next generation network. However, MIPv6 and subsequent standards have some limitations due to its handoff latency. In this paper, a fuzzy logic based mechanism is proposed to reduce the handoff latency of MIPv6 for Layer 2 (L2) by scanning the Access Points (APs) while the Mobile Node (MN) is moving among different APs. Handoff latency occurs when the MN switches from one AP to another in L2. Heterogeneous network is considered in this research in order to reduce the delays in L2. Received Signal Strength Indicator (RSSI) and velocity of the MN are considered as the input of fuzzy logic technique. This technique helps the MN to measure optimum signal quality from APs for the speedy mobile node based on fuzzy logic input rules and makes a list of interfaces. A suitable interface from the list of available interfaces can be selected like WiFi, WiMAX or GSM. Simulation results show 55% handoff latency reduction and 50% packet loss improvement in L2 compared to standard to MIPv6.

High-throughput and low-latency 60GHz small-cell network architectures over radio-over-fiber technologies

NASA Astrophysics Data System (ADS)

Pleros, N.; Kalfas, G.; Mitsolidou, C.; Vagionas, C.; Tsiokos, D.; Miliou, A.

2017-01-01

Future broadband access networks in the 5G framework will need to be bilateral, exploiting both optical and wireless technologies. This paper deals with new approaches and synergies on radio-over-fiber (RoF) technologies and how those can be leveraged to seamlessly converge wireless technology for agility and mobility with passive optical networks (PON)-based backhauling. The proposed convergence paradigm is based upon a holistic network architecture mixing mm-wave wireless access with photonic integration, dynamic capacity allocation and network coding schemes to enable high bandwidth and low-latency fixed and 60GHz wireless personal area communications for gigabit rate per user, proposing and deploying on top a Medium-Transparent MAC (MT-MAC) protocol as a low-latency bandwidth allocation mechanism. We have evaluated alternative network topologies between the central office (CO) and the access point module (APM) for data rates up to 2.5 Gb/s and SC frequencies up to 60 GHz. Optical network coding is demonstrated for SCM-based signaling to enhance bandwidth utilization and facilitate optical-wireless convergence in 5G applications, reporting medium-transparent network coding directly at the physical layer between end-users communicating over a RoF infrastructure. Towards equipping the physical layer with the appropriate agility to support MT-MAC protocols, a monolithic InP-based Remote Antenna Unit optoelectronic PIC interface is shown that ensures control over the optical resource allocation assisting at the same time broadband wireless service. Finally, the MT-MAC protocol is analysed and simulation and analytical theoretical results are presented that are found to be in good agreement confirming latency values lower than 1msec for small- to mid-load conditions.

W-MAC: A Workload-Aware MAC Protocol for Heterogeneous Convergecast in Wireless Sensor Networks

PubMed Central

Xia, Ming; Dong, Yabo; Lu, Dongming

2011-01-01

The power consumption and latency of existing MAC protocols for wireless sensor networks (WSNs) are high in heterogeneous convergecast, where each sensor node generates different amounts of data in one convergecast operation. To solve this problem, we present W-MAC, a workload-aware MAC protocol for heterogeneous convergecast in WSNs. A subtree-based iterative cascading scheduling mechanism and a workload-aware time slice allocation mechanism are proposed to minimize the power consumption of nodes, while offering a low data latency. In addition, an efficient schedule adjustment mechanism is provided for adapting to data traffic variation and network topology change. Analytical and simulation results show that the proposed protocol provides a significant energy saving and latency reduction in heterogeneous convergecast, and can effectively support data aggregation to further improve the performance. PMID:22163753

Network rhythms influence the relationship between spike-triggered local field potential and functional connectivity

PubMed Central

Maunsell, John H.R.

2012-01-01

Characterizing the functional connectivity between neurons is key for understanding brain function. We recorded spikes and local field potentials (LFP) from multi-electrode arrays implanted in monkey visual cortex to test the hypotheses that spikes generated outward traveling LFP waves and the strength of functional connectivity depended on stimulus contrast, as described recently. These hypotheses were proposed based on the observation that the latency of the peak negativity of the spike-triggered LFP average (STA) increased with distance between the spike and LFP electrodes, and the magnitude of the STA negativity and the distance over which it was observed decreased with increasing stimulus contrast. Detailed analysis of the shape of the STA, however, revealed contributions from two distinct sources – a transient negativity in the LFP locked to the spike (∼0 ms) that attenuated rapidly with distance, and a low frequency rhythm with peak negativity ∼25 ms after the spike that attenuated slowly with distance. The overall negative peak of the LFP, which combined both these components, shifted from ∼0 to ∼25 ms going from electrodes near the spike to electrodes far from the spike, giving an impression of a traveling wave, although the shift was fully explained by changing contributions from the two fixed components. The low frequency rhythm was attenuated during stimulus presentations, decreasing the overall magnitude of the STA. These results highlight the importance of accounting for the network activity while using STAs to determine functional connectivity. PMID:21880928

Designing and application of SAN extension interface based on CWDM

NASA Astrophysics Data System (ADS)

Qin, Leihua; Yu, Shengsheng; Zhou, Jingli

2005-11-01

As Fibre Channel (FC) becomes the protocol of choice within corporate data centers, enterprises are increasingly deploying SANs in their data central. In order to mitigate the risk of losing data and improve the availability of data, more and more enterprises are increasingly adopting storage extension technologies to replicate their business critical data to a secondary site. Transmitting this information over distance requires a carrier grade environment with zero data loss, scalable throughput, low jitter, high security and ability to travel long distance. To address this business requirements, there are three basic architectures for storage extension, they are Storage over Internet Protocol, Storage over Synchronous Optical Network/Synchronous Digital Hierarchy (SONET/SDH) and Storage over Dense Wavelength Division Multiplexing (DWDM). Each approach varies in functionality, complexity, cost, scalability, security, availability , predictable behavior (bandwidth, jitter, latency) and multiple carrier limitations. Compared with these connectiviy technologies,Coarse Wavelength Division Multiplexing (CWDM) is a Simplified, Low Cost and High Performance connectivity solutions for enterprises to deploy their storage extension. In this paper, we design a storage extension connectivity over CWDM and test it's electrical characteristic and random read and write performance of disk array through the CWDM connectivity, testing result show us that the performance of the connectivity over CWDM is acceptable. Furthermore, we propose three kinds of network architecture of SAN extension based on CWDM interface. Finally the credit-Based flow control mechanism of FC, and the relationship between credits and extension distance is analyzed.

Remotely supported prehospital ultrasound: A feasibility study of real-time image transmission and expert guidance to aid diagnosis in remote and rural communities.

PubMed

Eadie, Leila; Mulhern, John; Regan, Luke; Mort, Alasdair; Shannon, Helen; Macaden, Ashish; Wilson, Philip

2017-01-01

Introduction Our aim is to expedite prehospital assessment of remote and rural patients using remotely-supported ultrasound and satellite/cellular communications. In this paradigm, paramedics are remotely-supported ultrasound operators, guided by hospital-based specialists, to record images before receiving diagnostic advice. Technology can support users in areas with little access to medical imaging and suboptimal communications coverage by connecting to multiple cellular networks and/or satellites to stream live ultrasound and audio-video. Methods An ambulance-based demonstrator system captured standard trauma and novel transcranial ultrasound scans from 10 healthy volunteers at 16 locations across the Scottish Highlands. Volunteers underwent brief scanning training before receiving expert guidance via the communications link. Ultrasound images were streamed with an audio/video feed to reviewers for interpretation. Two sessions were transmitted via satellite and 21 used cellular networks. Reviewers rated image and communication quality, and their utility for diagnosis. Transmission latency and bandwidth were recorded, and effects of scanner and reviewer experience were assessed. Results Appropriate views were provided in 94% of the simulated trauma scans. The mean upload rate was 835/150 kbps and mean latency was 114/2072 ms for cellular and satellite networks, respectively. Scanning experience had a significant impact on time to achieve a diagnostic image, and review of offline scans required significantly less time than live-streamed scans. Discussion This prehospital ultrasound system could facilitate early diagnosis and streamlining of treatment pathways for remote emergency patients, being particularly applicable in rural areas worldwide with poor communications infrastructure and extensive transport times.

78 FR 50477 - Self-Regulatory Organizations; NASDAQ OMX PHLX LLC; Notice of Filing and Immediate Effectiveness...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-19

... them in sequence for entry into the System for execution. Each of Phlx's current connection offerings... connectivity and installation fees for a 10Gb Ultra low latency fiber connection option, and provide a waiver... bandwidth options for connectivity to the Exchange, including a 40Gb fiber connection, a 10Gb fiber...

78 FR 50132 - Self-Regulatory Organizations; NASDAQ OMX BX, Inc.; Notice of Filing and Immediate Effectiveness...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-16

... into the System for execution. Each of BX's current connection offerings uses different switches... 10Gb Ultra low latency fiber connection option, and provide a waiver of installation fees for... to the Exchange, including a 40Gb fiber connection, a 10Gb fiber connection, a 1Gb fiber connection...

Three Degrees of Inclusion: the Gossip-Effect in Human Networks

NASA Astrophysics Data System (ADS)

Szekfu˝, Balázs; Szvetelszky, Zsuzsanna

2005-06-01

Using the scientific definition of gossip, an ancient and ubiquitous phenomenon of the social networks, we present our preliminary study and its results on how to measure the networks based on dissemination of connections and information. We try to accurately calculate the gossip-effects in networks with our hypothesis of "three degrees of inclusion". Our preliminary study on the subject of "three degrees of inclusion" gives latency to a very important property of social networks. Observing the human communication of closely knit social groups we came to the conclusion that the human networks are based on not more than three degrees of links. Taking the strong human ties into account our research indicates that whoever is on the fourth degree rarely counts as an in-group member. Our close friend's close friend's close friend — that is about the farthest — three steps — our network can reach out when it comes to telling a story or asking for a favor. Up to now no investigations have been performed to see whether the effects of gossip lead to the phase transition of the content of network's self-organizing communication. Our conclusion is that the gossip-effect must be considered as the prefactor of the news and opinions diffusion and dynamics at the social level.

A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks

PubMed Central

Sha, Chao; Qiu, Jian-mei; Li, Shu-yan; Qiang, Meng-ye; Wang, Ru-chuan

2016-01-01

To balance energy consumption and reduce latency on data transmission in Wireless Sensor Networks (WSNs), a type of low-latency data gathering method with multi-Sink (LDGM for short) is proposed in this paper. The network is divided into several virtual regions consisting of three or less data gathering units and the leader of each region is selected according to its residual energy as well as distance to all of the other nodes. Only the leaders in each region need to communicate with the mobile Sinks which have effectively reduced energy consumption and the end-to-end delay. Moreover, with the help of the sleep scheduling and the sensing radius adjustment strategies, redundancy in network coverage could also be effectively reduced. Simulation results show that LDGM is energy efficient in comparison with MST as well as MWST and its time efficiency on data collection is higher than one Sink based data gathering methods. PMID:27338401

A new, ultra-low latency data transmission protocol for Earthquake Early Warning Systems

NASA Astrophysics Data System (ADS)

Hill, P.; Hicks, S. P.; McGowan, M.

2016-12-01

One measure used to assess the performance of Earthquake Early Warning Systems (EEWS) is the delay time between earthquake origin and issued alert. EEWS latency is dependent on a number of sources (e.g. P-wave propagation, digitisation, transmission, receiver processing, triggering, event declaration). Many regional seismic networks use the SEEDlink protocol; however, packet size is fixed to 512-byte miniSEED records, resulting in transmission latencies of >0.5 s. Data packetisation is seen as one of the main sources of delays in EEWS (Brown et al., 2011). Optimising data-logger and telemetry configurations is a cost-effective strategy to improve EEWS alert times (Behr et al., 2015). Digitisers with smaller, selectable packets can result in faster alerts (Sokos et al., 2016). We propose a new seismic protocol for regional seismic networks benefiting low-latency applications such as EEWS. The protocol, based on Güralp's existing GDI-link format is an efficient and flexible method to exchange data between seismic stations and data centers for a range of network configurations. The main principle is to stream data sample-by-sample instead of fixed-length packets to minimise transmission latency. Self-adaptive packetisation with compression maximises available telemetry bandwidth. Highly flexible metadata fields within GDI-link are compatible with existing miniSEED definitions. Data is sent as integers or floats, supporting a wide range of data formats, including discrete parameters such as Pd & τC for on-site earthquake early warning. Other advantages include: streaming station state-of-health information, instrument control, support of backfilling and fail-over strategies during telemetry outages. Based on tests carried out on the Güralp Minimus data-logger, we show our new protocol can reduce transmission latency to as low as 1 ms. The low-latency protocol is currently being implemented with common processing packages. The results of these tests will help to highlight latency levels that can be achieved with next-generation EEWS.

Exploring Infiniband Hardware Virtualization in OpenNebula towards Efficient High-Performance Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pais Pitta de Lacerda Ruivo, Tiago; Bernabeu Altayo, Gerard; Garzoglio, Gabriele

2014-11-11

has been widely accepted that software virtualization has a big negative impact on high-performance computing (HPC) application performance. This work explores the potential use of Infiniband hardware virtualization in an OpenNebula cloud towards the efficient support of MPI-based workloads. We have implemented, deployed, and tested an Infiniband network on the FermiCloud private Infrastructure-as-a-Service (IaaS) cloud. To avoid software virtualization towards minimizing the virtualization overhead, we employed a technique called Single Root Input/Output Virtualization (SRIOV). Our solution spanned modifications to the Linux’s Hypervisor as well as the OpenNebula manager. We evaluated the performance of the hardware virtualization on up to 56more » virtual machines connected by up to 8 DDR Infiniband network links, with micro-benchmarks (latency and bandwidth) as well as w a MPI-intensive application (the HPL Linpack benchmark).« less

Open source IPSEC software in manned and unmanned space missions

NASA Astrophysics Data System (ADS)

Edwards, Jacob

Network security is a major topic of research because cyber attackers pose a threat to national security. Securing ground-space communications for NASA missions is important because attackers could endanger mission success and human lives. This thesis describes how an open source IPsec software package was used to create a secure and reliable channel for ground-space communications. A cost efficient, reproducible hardware testbed was also created to simulate ground-space communications. The testbed enables simulation of low-bandwidth and high latency communications links to experiment how the open source IPsec software reacts to these network constraints. Test cases were built that allowed for validation of the testbed and the open source IPsec software. The test cases also simulate using an IPsec connection from mission control ground routers to points of interest in outer space. Tested open source IPsec software did not meet all the requirements. Software changes were suggested to meet requirements.

A dynamically reconfigurable logic cell: from artificial neural networks to quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Naqvi, Syed Rameez; Akram, Tallha; Iqbal, Saba; Haider, Sajjad Ali; Kamran, Muhammad; Muhammad, Nazeer

2018-02-01

Considering the lack of optimization support for Quantum-dot Cellular Automata, we propose a dynamically reconfigurable logic cell capable of implementing various logic operations by means of artificial neural networks. The cell can be reconfigured to any 2-input combinational logic gate by altering the strength of connections, called weights and biases. We demonstrate how these cells may appositely be organized to perform multi-bit arithmetic and logic operations. The proposed work is important in that it gives a standard implementation of an 8-bit arithmetic and logic unit for quantum-dot cellular automata with minimal area and latency overhead. We also compare the proposed design with a few existing arithmetic and logic units, and show that it is more area efficient than any equivalent available in literature. Furthermore, the design is adaptable to 16, 32, and 64 bit architectures.

Integration of power over fiber on RoF systems in different scenarios

NASA Astrophysics Data System (ADS)

Vázquez, C.; Montero, D. S.; Pinzón, P. J.; López-Cardona, J. D.; Contreras, P.; Tapetado, A.

2017-01-01

Future high capacity of the 5th Generation radio environment will boost transport networks to be adapted. The high bandwidth, together with stringent delay and jitter requirements, make dedicated optical connectivity a preferred solution for fronthaul. Those Radio Access Networks apart from higher capacity and lower latency should have higher energy efficiency. In order to cover this aspect, power over fiber has been pointed out as a key technology for that purpose having in mind that control plane will be centralized on future Cloud RAN and that sometimes Remote Radio Heads should be deployed in places lacking external power supply in order to fulfill the desired coverage. In this paper, different scenarios on potential demanding environments of power over fiber on Radio over Fiber systems such as automotive, in-house and remote mobile fronthaul will be discussed. Some tests on power over fiber systems based on different optical fibers are provided.

How to make your own response boxes: A step-by-step guide for the construction of reliable and inexpensive parallel-port response pads from computer mice.

PubMed

Voss, Andreas; Leonhart, Rainer; Stahl, Christoph

2007-11-01

Psychological research is based in large parts on response latencies, which are often registered by keypresses on a standard computer keyboard. Recording response latencies with a standard keyboard is problematic because keypresses are buffered within the keyboard hardware before they are signaled to the computer, adding error variance to the recorded latencies. This can be circumvented by using external response pads connected to the computer's parallel port. In this article, we describe how to build inexpensive, reliable, and easy-to-use response pads with six keys from two standard computer mice that can be connected to the PC's parallel port. We also address the problem of recording data from the parallel port with different software packages under Microsoft's Windows XP.

Moving Large Data Sets Over High-Performance Long Distance Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodson, Stephen W; Poole, Stephen W; Ruwart, Thomas

2011-04-01

In this project we look at the performance characteristics of three tools used to move large data sets over dedicated long distance networking infrastructure. Although performance studies of wide area networks have been a frequent topic of interest, performance analyses have tended to focus on network latency characteristics and peak throughput using network traffic generators. In this study we instead perform an end-to-end long distance networking analysis that includes reading large data sets from a source file system and committing large data sets to a destination file system. An evaluation of end-to-end data movement is also an evaluation of themore » system configurations employed and the tools used to move the data. For this paper, we have built several storage platforms and connected them with a high performance long distance network configuration. We use these systems to analyze the capabilities of three data movement tools: BBcp, GridFTP, and XDD. Our studies demonstrate that existing data movement tools do not provide efficient performance levels or exercise the storage devices in their highest performance modes. We describe the device information required to achieve high levels of I/O performance and discuss how this data is applicable in use cases beyond data movement performance.« less

Three degrees of inclusion: the emergence of self-organizing social beliefs

NASA Astrophysics Data System (ADS)

Szvetelszky, Zsuzsanna; Szekfu˝, Balázs

2005-07-01

Using the scientific definition of gossip, an ancient and ubiquitous phenomenon of the social networks, we present our preliminary study and its results on how to measure the networks based on dissemination of connections and information. We try to accurately calculate the gossip-effects in networks with our hypothesis of "three degrees of inclusion". Our preliminary study on the subject of "three degrees of inclusion" gives latency to a very important property of social networks. Observing the human communication of closely knit social groups we came to the conclusion that the human networks are based on not more than three degrees of links. Taking the strong human ties into account our research indicates that whoever is on the fourth degree rarely counts as an in-group member. Our close friend's close friend's close friend — that is about the farthest — three steps — our network can reach out when it comes to telling a story or asking for a favor. Up to now no investigations have been performed to see whether the effects of gossip lead to the phase transition of the content of network's self-organizing communication. Our conclusion is that the gossip-effect must be considered as the prefactor of the news and opinions diffusion and dynamics at the social level.

Bluetooth Low Power Modes Applied to the Data Transportation Network in Home Automation Systems.

PubMed

Etxaniz, Josu; Aranguren, Gerardo

2017-04-30

Even though home automation is a well-known research and development area, recent technological improvements in different areas such as context recognition, sensing, wireless communications or embedded systems have boosted wireless smart homes. This paper focuses on some of those areas related to home automation. The paper draws attention to wireless communications issues on embedded systems. Specifically, the paper discusses the multi-hop networking together with Bluetooth technology and latency, as a quality of service (QoS) metric. Bluetooth is a worldwide standard that provides low power multi-hop networking. It is a radio license free technology and establishes point-to-point and point-to-multipoint links, known as piconets, or multi-hop networks, known as scatternets. This way, many Bluetooth nodes can be interconnected to deploy ambient intelligent networks. This paper introduces the research on multi-hop latency done with park and sniff low power modes of Bluetooth over the test platform developed. Besides, an empirical model is obtained to calculate the latency of Bluetooth multi-hop communications over asynchronous links when links in scatternets are always in sniff or the park mode. Smart home devices and networks designers would take advantage of the models and the estimation of the delay they provide in communications along Bluetooth multi-hop networks.

Bluetooth Low Power Modes Applied to the Data Transportation Network in Home Automation Systems

PubMed Central

Etxaniz, Josu; Aranguren, Gerardo

2017-01-01

Even though home automation is a well-known research and development area, recent technological improvements in different areas such as context recognition, sensing, wireless communications or embedded systems have boosted wireless smart homes. This paper focuses on some of those areas related to home automation. The paper draws attention to wireless communications issues on embedded systems. Specifically, the paper discusses the multi-hop networking together with Bluetooth technology and latency, as a quality of service (QoS) metric. Bluetooth is a worldwide standard that provides low power multi-hop networking. It is a radio license free technology and establishes point-to-point and point-to-multipoint links, known as piconets, or multi-hop networks, known as scatternets. This way, many Bluetooth nodes can be interconnected to deploy ambient intelligent networks. This paper introduces the research on multi-hop latency done with park and sniff low power modes of Bluetooth over the test platform developed. Besides, an empirical model is obtained to calculate the latency of Bluetooth multi-hop communications over asynchronous links when links in scatternets are always in sniff or the park mode. Smart home devices and networks designers would take advantage of the models and the estimation of the delay they provide in communications along Bluetooth multi-hop networks. PMID:28468294

The Contribution of Network Organization and Integration to the Development of Cognitive Control

PubMed Central

Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N.; Luna, Beatriz

2015-01-01

Abstract Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10–26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control. PMID:26713863

The Contribution of Network Organization and Integration to the Development of Cognitive Control.

PubMed

Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N; Luna, Beatriz

2015-12-01

Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10-26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control.

Rate based failure detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Brett Emery Trabun; Gamage, Thoshitha Thanushka; Bakken, David Edward

This disclosure describes, in part, a system management component and failure detection component for use in a power grid data network to identify anomalies within the network and systematically adjust the quality of service of data published by publishers and subscribed to by subscribers within the network. In one implementation, subscribers may identify a desired data rate, a minimum acceptable data rate, desired latency, minimum acceptable latency and a priority for each subscription. The failure detection component may identify an anomaly within the network and a source of the anomaly. Based on the identified anomaly, data rates and or datamore » paths may be adjusted in real-time to ensure that the power grid data network does not become overloaded and/or fail.« less

A Modern Operating System for Near-real-time Environmental Observatories

NASA Astrophysics Data System (ADS)

Orcutt, John; Vernon, Frank

2014-05-01

The NSF Ocean Observatory Initiative (OOI) provided an opportunity for expanding the capabilities for managing open, near-real-time (latencies of seconds) data from ocean observatories. The sensors deployed in this system largely return data from seafloor, cabled fiber optic cables as well as satellite telemetry. Bandwidth demands range from high-definition movies to the transmission of data via Iridium satellite. The extended Internet also provides an opportunity to not only return data, but to also control the sensors and platforms that comprise the observatory. The data themselves are openly available to any users. In order to provide heightened network security and overall reliability, the connections to and from the sensors/platforms are managed without Layer 3 of the Internet, but instead rely upon message passing using an open protocol termed Advanced Queuing Messaging Protocol (AMQP). The highest bandwidths in the system are in the Regional Scale Network (RSN) off Oregon and Washington and on the continent with highly reliable network connections between observatory components at 10 Gbps. The maintenance of metadata and life cycle histories of sensors and platforms is critical for providing data provenance over the years. The integrated cyberinfrastructure is best thought of as an operating system for the observatory - like the data, the software is also open and can be readily applied to new observatories, for example, in the rapidly evolving Arctic.

Topographical Organization of Attentional, Social, and Memory Processes in the Human Temporoparietal Cortex123

PubMed Central

Webb, Taylor W.; Kelly, Yin T.; Graziano, Michael S. A.

2016-01-01

Abstract The temporoparietal junction (TPJ) is activated in association with a large range of functions, including social cognition, episodic memory retrieval, and attentional reorienting. An ongoing debate is whether the TPJ performs an overarching, domain-general computation, or whether functions reside in domain-specific subdivisions. We scanned subjects with fMRI during five tasks known to activate the TPJ, probing social, attentional, and memory functions, and used data-driven parcellation (independent component analysis) to isolate task-related functional processes in the bilateral TPJ. We found that one dorsal component in the right TPJ, which was connected with the frontoparietal control network, was activated in all of the tasks. Other TPJ subregions were specific for attentional reorienting, oddball target detection, or social attribution of belief. The TPJ components that participated in attentional reorienting and oddball target detection appeared spatially separated, but both were connected with the ventral attention network. The TPJ component that participated in the theory-of-mind task was part of the default-mode network. Further, we found that the BOLD response in the domain-general dorsal component had a longer latency than responses in the domain-specific components, suggesting an involvement in distinct, perhaps postperceptual, computations. These findings suggest that the TPJ performs both domain-general and domain-specific computations that reside within spatially distinct functional components. PMID:27280153

Intrinsic Connectivity Provides the Baseline Framework for Variability in Motor Performance: A Multivariate Fusion Analysis of Low- and High-Frequency Resting-State Oscillations and Antisaccade Performance.

PubMed

Jamadar, Sharna D; Egan, Gary F; Calhoun, Vince D; Johnson, Beth; Fielding, Joanne

2016-07-01

Intrinsic brain activity provides the functional framework for the brain's full repertoire of behavioral responses; that is, a common mechanism underlies intrinsic and extrinsic neural activity, with extrinsic activity building upon the underlying baseline intrinsic activity. The generation of a motor movement in response to sensory stimulation is one of the most fundamental functions of the central nervous system. Since saccadic eye movements are among our most stereotyped motor responses, we hypothesized that individual variability in the ability to inhibit a prepotent saccade and make a voluntary antisaccade would be related to individual variability in intrinsic connectivity. Twenty-three individuals completed the antisaccade task and resting-state functional magnetic resonance imaging (fMRI). A multivariate analysis of covariance identified relationships between fMRI oscillations (0.01-0.2 Hz) of resting-state networks determined using high-dimensional independent component analysis and antisaccade performance (latency, error rate). Significant multivariate relationships between antisaccade latency and directional error rate were obtained in independent components across the entire brain. Some of the relationships were obtained in components that overlapped substantially with the task; however, many were obtained in components that showed little overlap with the task. The current results demonstrate that even in the absence of a task, spectral power in regions showing little overlap with task activity predicts an individual's performance on a saccade task.

Complexity Optimization and High-Throughput Low-Latency Hardware Implementation of a Multi-Electrode Spike-Sorting Algorithm

PubMed Central

Dragas, Jelena; Jäckel, David; Hierlemann, Andreas; Franke, Felix

2017-01-01

Reliable real-time low-latency spike sorting with large data throughput is essential for studies of neural network dynamics and for brain-machine interfaces (BMIs), in which the stimulation of neural networks is based on the networks' most recent activity. However, the majority of existing multi-electrode spike-sorting algorithms are unsuited for processing high quantities of simultaneously recorded data. Recording from large neuronal networks using large high-density electrode sets (thousands of electrodes) imposes high demands on the data-processing hardware regarding computational complexity and data transmission bandwidth; this, in turn, entails demanding requirements in terms of chip area, memory resources and processing latency. This paper presents computational complexity optimization techniques, which facilitate the use of spike-sorting algorithms in large multi-electrode-based recording systems. The techniques are then applied to a previously published algorithm, on its own, unsuited for large electrode set recordings. Further, a real-time low-latency high-performance VLSI hardware architecture of the modified algorithm is presented, featuring a folded structure capable of processing the activity of hundreds of neurons simultaneously. The hardware is reconfigurable “on-the-fly” and adaptable to the nonstationarities of neuronal recordings. By transmitting exclusively spike time stamps and/or spike waveforms, its real-time processing offers the possibility of data bandwidth and data storage reduction. PMID:25415989

Complexity optimization and high-throughput low-latency hardware implementation of a multi-electrode spike-sorting algorithm.

PubMed

Dragas, Jelena; Jackel, David; Hierlemann, Andreas; Franke, Felix

2015-03-01

Reliable real-time low-latency spike sorting with large data throughput is essential for studies of neural network dynamics and for brain-machine interfaces (BMIs), in which the stimulation of neural networks is based on the networks' most recent activity. However, the majority of existing multi-electrode spike-sorting algorithms are unsuited for processing high quantities of simultaneously recorded data. Recording from large neuronal networks using large high-density electrode sets (thousands of electrodes) imposes high demands on the data-processing hardware regarding computational complexity and data transmission bandwidth; this, in turn, entails demanding requirements in terms of chip area, memory resources and processing latency. This paper presents computational complexity optimization techniques, which facilitate the use of spike-sorting algorithms in large multi-electrode-based recording systems. The techniques are then applied to a previously published algorithm, on its own, unsuited for large electrode set recordings. Further, a real-time low-latency high-performance VLSI hardware architecture of the modified algorithm is presented, featuring a folded structure capable of processing the activity of hundreds of neurons simultaneously. The hardware is reconfigurable “on-the-fly” and adaptable to the nonstationarities of neuronal recordings. By transmitting exclusively spike time stamps and/or spike waveforms, its real-time processing offers the possibility of data bandwidth and data storage reduction.

Integrating Sediment Connectivity into Water Resources Management Trough a Graph Theoretic, Stochastic Modeling Framework.

NASA Astrophysics Data System (ADS)

Schmitt, R. J. P.; Castelletti, A.; Bizzi, S.

2014-12-01

Understanding sediment transport processes at the river basin scale, their temporal spectra and spatial patterns is key to identify and minimize morphologic risks associated to channel adjustments processes. This work contributes a stochastic framework for modeling bed-load connectivity based on recent advances in the field (e.g., Bizzi & Lerner, 2013; Czubas & Foufoulas-Georgiu, 2014). It presents river managers with novel indicators from reach scale vulnerability to channel adjustment in large river networks with sparse hydrologic and sediment observations. The framework comprises three steps. First, based on a distributed hydrological model and remotely sensed information, the framework identifies a representative grain size class for each reach. Second, sediment residence time distributions are calculated for each reach in a Monte-Carlo approach applying standard sediment transport equations driven by local hydraulic conditions. Third, a network analysis defines the up- and downstream connectivity for various travel times resulting in characteristic up/downstream connectivity signatures for each reach. Channel vulnerability indicators quantify the imbalance between up/downstream connectivity for each travel time domain, representing process dependent latency of morphologic response. Last, based on the stochastic core of the model, a sensitivity analysis identifies drivers of change and major sources of uncertainty in order to target key detrimental processes and to guide effective gathering of additional data. The application, limitation and integration into a decision analytic framework is demonstrated for a major part of the Red River Basin in Northern Vietnam (179.000 km2). Here, a plethora of anthropic alterations ranging from large reservoir construction to land-use changes results in major downstream deterioration and calls for deriving concerted sediment management strategies to mitigate current and limit future morphologic alterations.

River networks as biodiversity hotlines.

PubMed

Décamps, Henri

2011-05-01

For several years, measures to insure healthy river functions and to protect biodiversity have focused on management at the scale of drainage basins. Indeed, rivers bear witness to the health of their drainage basins, which justifies integrated basin management. However, this vision should not mask two other aspects of the protection of aquatic and riparian biodiversity as well as services provided by rivers. First, although largely depending on the ecological properties of the surrounding terrestrial environment, rivers are ecological systems by themselves, characterized by their linearity: they are organized in connected networks, complex and ever changing, open to the sea. Second, the structure and functions of river networks respond to manipulations of their hydrology, and are particularly vulnerable to climatic variations. Whatever the scale considered, river networks represent "hotlines" for sharing water between ecological and societal systems, as well as for preserving both systems in the face of global change. River hotlines are characterized by spatial as well as temporal legacies: every human impact to a river network may be transmitted far downstream from its point of origin, and may produce effects only after a more or less prolonged latency period. Here, I review some of the current issues of river ecology in light of the linear character of river networks. Copyright © 2011 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Operational Data Quality Assessment of the Combined PBO, TLALOCNet and COCONet Real-Time GNSS Networks

NASA Astrophysics Data System (ADS)

Hodgkinson, K. M.; Mencin, D.; Fox, O.; Walls, C. P.; Mann, D.; Blume, F.; Berglund, H. T.; Phillips, D.; Meertens, C. M.; Mattioli, G. S.

2015-12-01

The GAGE facility, managed by UNAVCO, currently operates a network of ~460, real-time, high-rate GNSS stations (RT-GNSS). The majority of these RT stations are part of the Earthscope PBO network, which spans the western US Pacific North-American plate boundary. Approximately 50 are distributed throughout the Mexico and Caribbean region funded by the TLALOCNet and COCONet projects. The entire network is processed in real-time at UNAVCO using Precise Point Positioning (PPP). The real-time streams are freely available to all and user demand has grown almost exponentially since 2010. Data usage is multidisciplinary, including tectonic and volcanic deformation studies, meteorological applications, atmospheric science research in addition to use by national, state and commercial entities. 21 RT-GNSS sites in California now include 200-sps accelerometers for the development of Earthquake Early Warning systems. All categories of users of real-time streams have similar requirements, reliable, low-latency, high-rate, and complete data sets. To meet these requirements, UNAVCO tracks the latency and completeness of the incoming raw observations and also is developing tools to monitor the quality of the processed data streams. UNAVCO is currently assessing the precision, accuracy and latency of solutions from various PPP software packages. Also under review are the data formats UNAVCO distributes; for example, the PPP solutions are currently distributed in NMEA format, but other formats such as SEED or GeoJSON may be preferred by different user groups to achieve specific mission objectives. In this presentation we will share our experiences of the challenges involved in the data operations of a continental-scale, multi-project, real-time GNSS network, summarize the network's performance in terms of latency and completeness, and present the comparisons of PPP solutions using different PPP processing techniques.

Recent advancements towards green optical networks

NASA Astrophysics Data System (ADS)

Davidson, Alan; Glesk, Ivan; Buis, Adrianus; Wang, Junjia; Chen, Lawrence

2014-12-01

Recent years have seen a rapid growth in demand for ultra high speed data transmission with end users expecting fast, high bandwidth network access. With this rapid growth in demand, data centres are under pressure to provide ever increasing data rates through their networks and at the same time improve the quality of data handling in terms of reduced latency, increased scalability and improved channel speed for users. However as data rates increase, present technology based on well-established CMOS technology is becoming increasingly difficult to scale and consequently data networks are struggling to satisfy current network demand. In this paper the interrelated issues of electronic scalability, power consumption, limited copper interconnect bandwidth and the limited speed of CMOS electronics will be explored alongside the tremendous bandwidth potential of optical fibre based photonic networks. Some applications of photonics to help alleviate the speed and latency in data networks will be discussed.

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks.

PubMed

Shen, Yiwen; Hattink, Maarten H N; Samadi, Payman; Cheng, Qixiang; Hu, Ziyiz; Gazman, Alexander; Bergman, Keren

2018-04-16

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. We present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly network testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 µs control plane latency for data-center and high performance computing platforms.

Design of a stateless low-latency router architecture for green software-defined networking

NASA Astrophysics Data System (ADS)

Saldaña Cercós, Silvia; Ramos, Ramon M.; Ewald Eller, Ana C.; Martinello, Magnos; Ribeiro, Moisés. R. N.; Manolova Fagertun, Anna; Tafur Monroy, Idelfonso

2015-01-01

Expanding software defined networking (SDN) to transport networks requires new strategies to deal with the large number of flows that future core networks will have to face. New south-bound protocols within SDN have been proposed to benefit from having control plane detached from the data plane offering a cost- and energy-efficient forwarding engine. This paper presents an overview of a new approach named KeyFlow to simultaneously reduce latency, jitter, and power consumption in core network nodes. Results on an emulation platform indicate that round trip time (RTT) can be reduced above 50% compared to the reference protocol OpenFlow, specially when flow tables are densely populated. Jitter reduction has been demonstrated experimentally on a NetFPGA-based platform, and 57.3% power consumption reduction has been achieved.

78 FR 65400 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-31

... currently offers three Ethernet connection options, a 1 Gb connection at a cost of $500 per month, a 10 Gb connection at a cost of $4,000 per month, and a 10 Gb low latency connection at a cost of $7,000 per month... option to enable a more efficient connection to the Exchange. The growth in the size of consolidated and...

SDN based millimetre wave radio over fiber (RoF) network

NASA Astrophysics Data System (ADS)

Amate, Ahmed; Milosavljevic, Milos; Kourtessis, Pandelis; Robinson, Matthew; Senior, John M.

2015-01-01

This paper introduces software-defined, millimeter Wave (mm-Wave) networks with Radio over Fiber (RoF) for the delivery of gigabit connectivity required to develop fifth generation (5G) mobile. This network will enable an effective open access system allowing providers to manage and lease the infrastructure to service providers through unbundling new business models. Exploiting the inherited benefits of RoF, complete base station functionalities are centralized at the edges of the metro and aggregation network, leaving remote radio heads (RRHs) with only tunable filtering and amplification. A Software Defined Network (SDN) Central Controller (SCC) is responsible for managing the resource across several mm-Wave Radio Access Networks (RANs) providing a global view of the several network segments. This ensures flexible resource allocation for reduced overall latency and increased throughput. The SDN based mm-Wave RAN also allows for inter edge node communication. Therefore, certain packets can be routed between different RANs supported by the same edge node, reducing latency. System level simulations of the complete network have shown significant improvement of the overall throughput and SINR for wireless users by providing effective resource allocation and coordination among interfering cells. A new Coordinated Multipoint (CoMP) algorithm exploiting the benefits of the SCC global network view for reduced delay in control message exchange is presented, accounting for a minimum packet delay and limited Channel State Information (CSI) in a Long Term Evolution-Advanced (LTE-A), Cloud RAN (CRAN) configuration. The algorithm does not require detailed CSI feedback from UEs but it rather considers UE location (determined by the eNB) as the required parameter. UE throughput in the target sector is represented using a Cumulative Distributive Function (CDF). The drawn characteristics suggest that there is a significant 60% improvement in UE cell edge throughput following the application, in the coordinating cells, of the new CoMP algorithm. Results also show a further improvement of 36% in cell edge UE throughput when eNBs are centralized in a CRAN backhaul architecture. The SINR distribution of UEs in the cooperating cells has also been evaluated using a box plot. As expected, UEs with CoMP perform better demonstrating an increase of over 2 dB at the median between the transmission scenarios.

Accelerating list management for MPI.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hemmert, K. Scott; Rodrigues, Arun F.; Underwood, Keith Douglas

2005-07-01

The latency and throughput of MPI messages are critically important to a range of parallel scientific applications. In many modern networks, both of these performance characteristics are largely driven by the performance of a processor on the network interface. Because of the semantics of MPI, this embedded processor is forced to traverse a linked list of posted receives each time a message is received. As this list grows long, the latency of message reception grows and the throughput of MPI messages decreases. This paper presents a novel hardware feature to handle list management functions on a network interface. By movingmore » functions such as list insertion, list traversal, and list deletion to the hardware unit, latencies are decreased by up to 20% in the zero length queue case with dramatic improvements in the presence of long queues. Similarly, the throughput is increased by up to 10% in the zero length queue case and by nearly 100% in the presence queues of 30 messages.« less

Method for triggering an action

DOEpatents

Hall, David R.; Bartholomew, David B.; Johnson, Monte L.; Moon, Justin; Koehler, Roger O.

2006-10-17

A method for triggering an action of at least one downhole device on a downhole network integrated into a downhole tool string synchronized to an event comprises determining latency, sending a latency adjusted signal, and performing the action. The latency is determined between a control device and the at least one downhole device. The latency adjusted signal for triggering an action is sent to the downhole device. The action is performed downhole synchronized to the event. A preferred method for determining latency comprises the steps: a control device sends a first signal to the downhole device; after receiving the signal, the downhole device sends a response signal to the control device; and the control device analyzes the time from sending the signal to receiving the response signal.

An Xrootd Italian Federation

NASA Astrophysics Data System (ADS)

Boccali, T.; Donvito, G.; Diacono, D.; Marzulli, G.; Pompili, A.; Della Ricca, G.; Mazzoni, E.; Argiro, S.; Gregori, D.; Grandi, C.; Bonacorsi, D.; Lista, L.; Fabozzi, F.; Barone, L. M.; Santocchia, A.; Riahi, H.; Tricomi, A.; Sgaravatto, M.; Maron, G.

2014-06-01

The Italian community in CMS has built a geographically distributed network in which all the data stored in the Italian region are available to all the users for their everyday work. This activity involves at different level all the CMS centers: the Tier1 at CNAF, all the four Tier2s (Bari, Rome, Legnaro and Pisa), and few Tier3s (Trieste, Perugia, Torino, Catania, Napoli, ...). The federation uses the new network connections as provided by GARR, our NREN (National Research and Education Network), which provides a minimum of 10 Gbit/s to all the sites via the GARR-X[2] project. The federation is currently based on Xrootd[1] technology, and on a Redirector aimed to seamlessly connect all the sites, giving the logical view of a single entity. A special configuration has been put in place for the Tier1, CNAF, where ad-hoc Xrootd changes have been implemented in order to protect the tape system from excessive stress, by not allowing WAN connections to access tape only files, on a file-by-file basis. In order to improve the overall performance while reading files, both in terms of bandwidth and latency, a hierarchy of xrootd redirectors has been implemented. The solution implemented provides a dedicated Redirector where all the INFN sites are registered, without considering their status (T1, T2, or T3 sites). An interesting use case were able to cover via the federation are disk-less Tier3s. The caching solution allows to operate a local storage with minimal human intervention: transfers are automatically done on a single file basis, and the cache is maintained operational by automatic removal of old files.

High-port low-latency optical switch architecture with optical feed-forward buffering for 256-node disaggregated data centers.

PubMed

Terzenidis, Nikos; Moralis-Pegios, Miltiadis; Mourgias-Alexandris, George; Vyrsokinos, Konstantinos; Pleros, Nikos

2018-04-02

Departing from traditional server-centric data center architectures towards disaggregated systems that can offer increased resource utilization at reduced cost and energy envelopes, the use of high-port switching with highly stringent latency and bandwidth requirements becomes a necessity. We present an optical switch architecture exploiting a hybrid broadcast-and-select/wavelength routing scheme with small-scale optical feedforward buffering. The architecture is experimentally demonstrated at 10Gb/s, reporting error-free performance with a power penalty of <2.5dB. Moreover, network simulations for a 256-node system, revealed low-latency values of only 605nsec, at throughput values reaching 80% when employing 2-packet-size optical buffers, while multi-rack network performance was also investigated.

A comparative signaling cost analysis of Macro Mobility scheme in NEMO (MM-NEMO) with mobility management protocol

NASA Astrophysics Data System (ADS)

Islam, Shayla; Abdalla, Aisha H.; Habaebi, Mohamed H.; Latif, Suhaimi A.; Hassan, Wan H.; Hasan, Mohammad K.; Ramli, H. A. M.; Khalifa, Othman O.

2013-12-01

NEMO BSP is an upgraded addition to Mobile IPv6 (MIPv6). As MIPv6 and its enhancements (i.e. HMIPv6) possess some limitations like higher handoff latency, packet loss, NEMO BSP also faces all these shortcomings by inheritance. Network Mobility (NEMO) is involved to handle the movement of Mobile Router (MR) and it's Mobile Network Nodes (MNNs) during handoff. Hence it is essential to upgrade the performance of mobility management protocol to obtain continuous session connectivity with lower delay and packet loss in NEMO environment. The completion of handoff process in NEMO BSP usually takes longer period since MR needs to register its single primary care of address (CoA) with home network that may cause performance degradation of the applications running on Mobile Network Nodes. Moreover, when a change in point of attachment of the mobile network is accompanied by a sudden burst of signaling messages, "Signaling Storm" occurs which eventually results in temporary congestion, packet delays or even packet loss. This effect is particularly significant for wireless environment where a wireless link is not as steady as a wired link since bandwidth is relatively limited in wireless link. Hence, providing continuous Internet connection without any interruption through applying multihoming technique and route optimization mechanism in NEMO are becoming the center of attention to the current researchers. In this paper, we propose a handoff cost model to compare the signaling cost of MM-NEMO with NEMO Basic Support Protocol (NEMO BSP) and HMIPv6.The numerical results shows that the signaling cost for the MM-NEMO scheme is about 69.6 % less than the NEMO-BSP and HMIPv6.

An Investigation on the Role of Spike Latency in an Artificial Olfactory System

PubMed Central

Martinelli, Eugenio; Polese, Davide; Dini, Francesca; Paolesse, Roberto; Filippini, Daniel; Lundström, Ingemar; Di Natale, Corrado

2011-01-01

Experimental studies have shown that the reactions to external stimuli may appear only few hundreds of milliseconds after the physical interaction of the stimulus with the proper receptor. This behavior suggests that neurons transmit the largest meaningful part of their signal in the first spikes, and than that the spike latency is a good descriptor of the information content in biological neural networks. In this paper this property has been investigated in an artificial sensorial system where a single layer of spiking neurons is trained with the data generated by an artificial olfactory platform based on a large array of chemical sensors. The capability to discriminate between distinct chemicals and mixtures of them was studied with spiking neural networks endowed with and without lateral inhibitions and considering as output feature of the network both the spikes latency and the average firing rate. Results show that the average firing rate of the output spikes sequences shows the best separation among the experienced vapors, however the latency code is able in a shorter time to correctly discriminate all the tested volatile compounds. This behavior is qualitatively similar to those recently found in natural olfaction, and noteworthy it provides practical suggestions to tail the measurement conditions of artificial olfactory systems defining for each specific case a proper measurement time. PMID:22194721

Fast Inference of Deep Neural Networks in FPGAs for Particle Physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duarte, Javier; Han, Song; Harris, Philip

Recent results at the Large Hadron Collider (LHC) have pointed to enhanced physics capabilities through the improvement of the real-time event processing techniques. Machine learning methods are ubiquitous and have proven to be very powerful in LHC physics, and particle physics as a whole. However, exploration of the use of such techniques in low-latency, low-power FPGA hardware has only just begun. FPGA-based trigger and data acquisition (DAQ) systems have extremely low, sub-microsecond latency requirements that are unique to particle physics. We present a case study for neural network inference in FPGAs focusing on a classifier for jet substructure which wouldmore » enable, among many other physics scenarios, searches for new dark sector particles and novel measurements of the Higgs boson. While we focus on a specific example, the lessons are far-reaching. We develop a package based on High-Level Synthesis (HLS) called hls4ml to build machine learning models in FPGAs. The use of HLS increases accessibility across a broad user community and allows for a drastic decrease in firmware development time. We map out FPGA resource usage and latency versus neural network hyperparameters to identify the problems in particle physics that would benefit from performing neural network inference with FPGAs. For our example jet substructure model, we fit well within the available resources of modern FPGAs with a latency on the scale of 100 ns.« less

Traffic Adaptive Energy Efficient and Low Latency Medium Access Control for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Yadav, Rajesh; Varma, Shirshu; Malaviya, N.

2008-05-01

Medium access control for wireless sensor networks has been a very active research area in the recent years. The traditional wireless medium access control protocol such as IEEE 802.11 is not suitable for the sensor network application because these are battery powered. The recharging of these sensor nodes is expensive and also not possible. The most of the literature in the medium access for the sensor network focuses on the energy efficiency. The proposed MAC protocol solves the energy inefficiency caused by idle listening, control packet overhead and overhearing taking nodes latency into consideration based on the network traffic. Simulation experiments have been performed to demonstrate the effectiveness of the proposed approach. The validation of the simulation results of the proposed MAC has been done by comparing it with the analytical model. This protocol has been simulated in Network Simulator ns-2.

Traffic Management in ATM Networks Over Satellite Links

NASA Technical Reports Server (NTRS)

Goyal, Rohit; Jain, Raj; Goyal, Mukul; Fahmy, Sonia; Vandalore, Bobby; vonDeak, Thomas

1999-01-01

This report presents a survey of the traffic management Issues in the design and implementation of satellite Asynchronous Transfer Mode (ATM) networks. The report focuses on the efficient transport of Transmission Control Protocol (TCP) traffic over satellite ATM. First, a reference satellite ATM network architecture is presented along with an overview of the service categories available in ATM networks. A delay model for satellite networks and the major components of delay and delay variation are described. A survey of design options for TCP over Unspecified Bit Rate (UBR), Guaranteed Frame Rate (GFR) and Available Bit Rate (ABR) services in ATM is presented. The main focus is on traffic management issues. Several recommendations on the design options for efficiently carrying data services over satellite ATM networks are presented. Most of the results are based on experiments performed on Geosynchronous (GEO) latencies. Some results for Low Earth Orbits (LEO) and Medium Earth Orbit (MEO) latencies are also provided.

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah

PubMed Central

Tian, Le; Latré, Steven

2017-01-01

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks. PMID:28677617

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah.

PubMed

Tian, Le; Khorov, Evgeny; Latré, Steven; Famaey, Jeroen

2017-07-04

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks.

Characterization of Emergent Data Networks Among Long-Tail Data

NASA Astrophysics Data System (ADS)

Elag, Mostafa; Kumar, Praveen; Hedstrom, Margaret; Myers, James; Plale, Beth; Marini, Luigi; McDonald, Robert

2014-05-01

Data curation underpins data-driven scientific advancements. It manages the information flux across multiple users throughout data life cycle as well as increases data sustainability and reusability. The exponential growth in data production spanning across the Earth Science involving individual and small research groups, which is termed as log-tail data, increases the data-knowledge latency among related domains. It has become clear that an advanced framework-agnostic metadata and ontologies for long-tail data is required to increase their visibility to each other, and provide concise and meaningful descriptions that reveal their connectivity. Despite the advancement that has been achieved by various sophisticated data management models in different Earth Science disciplines, it is not always straightforward to derive relationships among long-tail data. Semantic data clustering algorithms and pre-defined logic rules that are oriented toward prediction of possible data relationships, is one method to address these challenges. Our work advances the connectivity of related long-tail data by introducing the design for an ontology-based knowledge management system. In this work, we present the system architecture, its components, and illustrate how it can be used to scrutinize the connectivity among datasets. To demonstrate the capabilities of this "data network" prototype, we implemented this approach within the Sustainable Environment Actionable Data (SEAD) environment, an open-source semantic content repository that provides a RDF database for long-tail data, and show how emergent relationships among datasets can be identified.

Demonstration of application-driven network slicing and orchestration in optical/packet domains: on-demand vDC expansion for Hadoop MapReduce optimization.

PubMed

Kong, Bingxin; Liu, Siqi; Yin, Jie; Li, Shengru; Zhu, Zuqing

2018-05-28

Nowadays, it is common for service providers (SPs) to leverage hybrid clouds to improve the quality-of-service (QoS) of their Big Data applications. However, for achieving guaranteed latency and/or bandwidth in its hybrid cloud, an SP might desire to have a virtual datacenter (vDC) network, in which it can manage and manipulate the network connections freely. To address this requirement, we design and implement a network slicing and orchestration (NSO) system that can create and expand vDCs across optical/packet domains on-demand. Considering Hadoop MapReduce (M/R) as the use-case, we describe the proposed architectures of the system's data, control and management planes, and present the operation procedures for creating, expanding, monitoring and managing a vDC for M/R optimization. The proposed NSO system is then realized in a small-scale network testbed that includes four optical/packet domains, and we conduct experiments in it to demonstrate the whole operations of the data, control and management planes. Our experimental results verify that application-driven on-demand vDC expansion across optical/packet domains can be achieved for M/R optimization, and after being provisioned with a vDC, the SP using the NSO system can fully control the vDC network and further optimize the M/R jobs in it with network orchestration.

78 FR 59391 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-26

... clients to utilize wireless connectivity and obtain the lower latency transmission of data from third... Wireless Connectivity September 20, 2013. Pursuant to Section 19(b)(1) of the Securities Exchange Act of... data feeds via wireless connectivity. The text of the proposed rule change is available on the Exchange...

Instantaneous global spatial interaction? Exploring the Gaussian inequality, distance and Internet pings in a global network

NASA Astrophysics Data System (ADS)

Baker, R. G. V.

2005-12-01

The Internet has been publicly portrayed as a new technological horizon yielding instantaneous interaction to a point where geography no longer matters. This research aims to dispel this impression by applying a dynamic form of trip modelling to investigate pings in a global computer network compiled by the Stanford Linear Accelerator Centre (SLAC) from 1998 to 2004. Internet flows have been predicted to have the same mathematical operators as trips to a supermarket, since they are both periodic and constrained by a distance metric. Both actual and virtual trips are part of a spectrum of origin-destination pairs in the time-space convergence of trip time-lines. Internet interaction is very near to the convergence of these time-lines (at a very small time scale in milliseconds, but with interactions over thousands of kilometres). There is a lag effect and this is formalised by the derivation of Gaussian and gravity inequalities between the time taken (Δ t) and the partitioning of distance (Δ x). This inequality seems to be robust for a regression of Δ t to Δ x in the SLAC data set for each year (1998 to 2004). There is a constant ‘forbidden zone’ in the interaction, underpinned by the fact that pings do not travel faster than the speed of light. Superimposed upon this zone is the network capacity where a linear regression of Δ t to Δ x is a proxy summarising global Internet connectivity for that year. The results suggest that there has been a substantial improvement in connectivity over the period with R 2 increasing steadily from 0.39 to 0.65 from less Gaussian spreading of the ping latencies. Further, the regression line shifts towards the inequality boundary from 1998 to 2004, where the increased slope shows a greater proportional rise in local connectivity over global connectivity. A conclusion is that national geography still does matter in spatial interaction modelling of the Internet.

On the influence of latency estimation on dynamic group communication using overlays

NASA Astrophysics Data System (ADS)

Vik, Knut-Helge; Griwodz, Carsten; Halvorsen, Pål

2009-01-01

Distributed interactive applications tend to have stringent latency requirements and some may have high bandwidth demands. Many of them have also very dynamic user groups for which all-to-all communication is needed. In online multiplayer games, for example, such groups are determined through region-of-interest management in the application. We have investigated a variety of group management approaches for overlay networks in earlier work and shown that several useful tree heuristics exist. However, these heuristics require full knowledge of all overlay link latencies. Since this is not scalable, we investigate the effects that latency estimation techqniues have ton the quality of overlay tree constructions. We do this by evaluating one example of our group management approaches in Planetlab and examing how latency estimation techqniues influence their quality. Specifically, we investigate how two well-known latency estimation techniques, Vivaldi and Netvigator, affect the quality of tree building.

Analysis of HSV viral reactivation in explants of sensory neurons

PubMed Central

Turner, Anne-Marie W.; Kristie, Thomas M.

2014-01-01

As with all Herpesviruses, Herpes simplex virus (HSV) has both a lytic replication phase and a latency-reactivation cycle. During lytic replication, there is an ordered cascade of viral gene expression that leads to the synthesis of infectious viral progeny. In contrast, latency is characterized by the lack of significant lytic gene expression and the absence of infectious virus. Reactivation from latency is characterized by the re-entry of the virus into the lytic replication cycle and the production of recurrent disease. This unit describes the establishment of the mouse sensory neuron model of HSV-1 latency-reactivation as a useful in vivo system for the analysis of mechanisms involved in latency and reactivation. Assays including the determination of viral yields, immunohistochemical/immunofluorescent detection of viral antigens, and mRNA quantitation are used in experiments designed to investigate the network of cellular and viral proteins regulating HSV-1 lytic infection, latency, and reactivation. PMID:25367271

The challenges of archiving networked-based multimedia performances (Performance cryogenics)

NASA Astrophysics Data System (ADS)

Cohen, Elizabeth; Cooperstock, Jeremy; Kyriakakis, Chris

2002-11-01

Music archives and libraries have cultural preservation at the core of their charters. New forms of art often race ahead of the preservation infrastructure. The ability to stream multiple synchronized ultra-low latency streams of audio and video across a continent for a distributed interactive performance such as music and dance with high-definition video and multichannel audio raises a series of challenges for the architects of digital libraries and those responsible for cultural preservation. The archiving of such performances presents numerous challenges that go beyond simply recording each stream. Case studies of storage and subsequent retrieval issues for Internet2 collaborative performances are discussed. The development of shared reality and immersive environments generate issues about, What constitutes an archived performance that occurs across a network (in multiple spaces over time)? What are the families of necessary metadata to reconstruct this virtual world in another venue or era? For example, if the network exhibited changes in latency the performers most likely adapted. In a future recreation, the latency will most likely be completely different. We discuss the parameters of immersive environment acquisition and rendering, network architectures, software architecture, musical/choreographic scores, and environmental acoustics that must be considered to address this problem.

Wireless, Web-Based Interactive Control of Optical Coherence Tomography with Mobile Devices.

PubMed

Mehta, Rajvi; Nankivil, Derek; Zielinski, David J; Waterman, Gar; Keller, Brenton; Limkakeng, Alexander T; Kopper, Regis; Izatt, Joseph A; Kuo, Anthony N

2017-01-01

Optical coherence tomography (OCT) is widely used in ophthalmology clinics and has potential for more general medical settings and remote diagnostics. In anticipation of remote applications, we developed wireless interactive control of an OCT system using mobile devices. A web-based user interface (WebUI) was developed to interact with a handheld OCT system. The WebUI consisted of key OCT displays and controls ported to a webpage using HTML and JavaScript. Client-server relationships were created between the WebUI and the OCT system computer. The WebUI was accessed on a cellular phone mounted to the handheld OCT probe to wirelessly control the OCT system. Twenty subjects were imaged using the WebUI to assess the system. System latency was measured using different connection types (wireless 802.11n only, wireless to remote virtual private network [VPN], and cellular). Using a cellular phone, the WebUI was successfully used to capture posterior eye OCT images in all subjects. Simultaneous interactivity by a remote user on a laptop was also demonstrated. On average, use of the WebUI added only 58, 95, and 170 ms to the system latency using wireless only, wireless to VPN, and cellular connections, respectively. Qualitatively, operator usage was not affected. Using a WebUI, we demonstrated wireless and remote control of an OCT system with mobile devices. The web and open source software tools used in this project make it possible for any mobile device to potentially control an OCT system through a WebUI. This platform can be a basis for remote, teleophthalmology applications using OCT.

Tap Arduino: An Arduino microcontroller for low-latency auditory feedback in sensorimotor synchronization experiments.

PubMed

Schultz, Benjamin G; van Vugt, Floris T

2016-12-01

Timing abilities are often measured by having participants tap their finger along with a metronome and presenting tap-triggered auditory feedback. These experiments predominantly use electronic percussion pads combined with software (e.g., FTAP or Max/MSP) that records responses and delivers auditory feedback. However, these setups involve unknown latencies between tap onset and auditory feedback and can sometimes miss responses or record multiple, superfluous responses for a single tap. These issues may distort measurements of tapping performance or affect the performance of the individual. We present an alternative setup using an Arduino microcontroller that addresses these issues and delivers low-latency auditory feedback. We validated our setup by having participants (N = 6) tap on a force-sensitive resistor pad connected to the Arduino and on an electronic percussion pad with various levels of force and tempi. The Arduino delivered auditory feedback through a pulse-width modulation (PWM) pin connected to a headphone jack or a wave shield component. The Arduino's PWM (M = 0.6 ms, SD = 0.3) and wave shield (M = 2.6 ms, SD = 0.3) demonstrated significantly lower auditory feedback latencies than the percussion pad (M = 9.1 ms, SD = 2.0), FTAP (M = 14.6 ms, SD = 2.8), and Max/MSP (M = 15.8 ms, SD = 3.4). The PWM and wave shield latencies were also significantly less variable than those from FTAP and Max/MSP. The Arduino missed significantly fewer taps, and recorded fewer superfluous responses, than the percussion pad. The Arduino captured all responses, whereas at lower tapping forces, the percussion pad missed more taps. Regardless of tapping force, the Arduino outperformed the percussion pad. Overall, the Arduino is a high-precision, low-latency, portable, and affordable tool for auditory experiments.

Analysis of power management and system latency in wireless sensor networks

NASA Astrophysics Data System (ADS)

Oswald, Matthew T.; Rohwer, Judd A.; Forman, Michael A.

2004-08-01

Successful power management in a wireless sensor network requires optimization of the protocols which affect energy-consumption on each node and the aggregate effects across the larger network. System optimization for a given deployment scenario requires an analysis and trade off of desired node and network features with their associated costs. The sleep protocol for an energy-efficient wireless sensor network for event detection, target classification, and target tracking developed at Sandia National Laboratories is presented. The dynamic source routing (DSR) algorithm is chosen to reduce network maintenance overhead, while providing a self-configuring and self-healing network architecture. A method for determining the optimal sleep time is developed and presented, providing reference data which spans several orders of magnitude. Message timing diagrams show, that a node in a five-node cluster, employing an optimal cyclic single-radio sleep protocol, consumes 3% more energy and incurs a 16-s increase latency than nodes employing the more complex dual-radio STEM protocol.

Intrinsic connections within the pedunculopontine tegmental nucleus are critical to the elaboration of post-ictal antinociception.

PubMed

Mazzei-Silva, Elaine Cristina; de Oliveira, Rithiele Cristina; dos Anjos Garcia, Tayllon; Falconi-Sobrinho, Luiz Luciano; Almada, Rafael Carvalho; Coimbra, Norberto Cysne

2014-08-01

This study investigated the intrinsic connections of a key-structure of the endogenous pain inhibitory system, the pedunculopontine tegmental nucleus (PPTN), in post-ictal antinociceptive process through synaptic inactivation of the PPTN with cobalt chloride. Male Wistar rats (n = 6 or 7 per group), weighing 250-280 g, had the tail-flick baseline recorded and were submitted to a stereotaxic surgery for the introduction of a guide-cannula aiming at the PPTN. After 5 days of postoperative recovery, cobalt chloride (1 mM/0.2 µL) or physiological saline (0.2 µL) were microinjected into the PPTN and after 5 min, the tail-withdrawal latency was measured again at 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, and 120 min after seizures evoked by intraperitoneal injection of pentylenetetrazole (64 mg/kg). The synaptic inactivation of PPTN decreased the post-ictal antinociceptive phenomenon, suggesting the involvement of PPTN intrinsic connections in the modulation of pain, during tonic-clonic seizures. These results showed that the PPTN may be crucially involved in the neural network that organizes the post-ictal analgesia. © 2014 Wiley Periodicals, Inc.

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

NASA Technical Reports Server (NTRS)

Tchorowski, Nicole; Murawski, Robert

2014-01-01

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

Analysis of performance improvements for host and GPU interface of the APENet+ 3D Torus network

NASA Astrophysics Data System (ADS)

Ammendola A, R.; Biagioni, A.; Frezza, O.; Lo Cicero, F.; Lonardo, A.; Paolucci, P. S.; Rossetti, D.; Simula, F.; Tosoratto, L.; Vicini, P.

2014-06-01

APEnet+ is an INFN (Italian Institute for Nuclear Physics) project aiming to develop a custom 3-Dimensional torus interconnect network optimized for hybrid clusters CPU-GPU dedicated to High Performance scientific Computing. The APEnet+ interconnect fabric is built on a FPGA-based PCI-express board with 6 bi-directional off-board links showing 34 Gbps of raw bandwidth per direction, and leverages upon peer-to-peer capabilities of Fermi and Kepler-class NVIDIA GPUs to obtain real zero-copy, GPU-to-GPU low latency transfers. The minimization of APEnet+ transfer latency is achieved through the adoption of RDMA protocol implemented in FPGA with specialized hardware blocks tightly coupled with embedded microprocessor. This architecture provides a high performance low latency offload engine for both trasmit and receive side of data transactions: preliminary results are encouraging, showing 50% of bandwidth increase for large packet size transfers. In this paper we describe the APEnet+ architecture, detailing the hardware implementation and discuss the impact of such RDMA specialized hardware on host interface latency and bandwidth.

Optical interconnection network for parallel access to multi-rank memory in future computing systems.

PubMed

Wang, Kang; Gu, Huaxi; Yang, Yintang; Wang, Kun

2015-08-10

With the number of cores increasing, there is an emerging need for a high-bandwidth low-latency interconnection network, serving core-to-memory communication. In this paper, aiming at the goal of simultaneous access to multi-rank memory, we propose an optical interconnection network for core-to-memory communication. In the proposed network, the wavelength usage is delicately arranged so that cores can communicate with different ranks at the same time and broadcast for flow control can be achieved. A distributed memory controller architecture that works in a pipeline mode is also designed for efficient optical communication and transaction address processes. The scaling method and wavelength assignment for the proposed network are investigated. Compared with traditional electronic bus-based core-to-memory communication, the simulation results based on the PARSEC benchmark show that the bandwidth enhancement and latency reduction are apparent.

Enhanced polychronization in a spiking network with metaplasticity.

PubMed

Guise, Mira; Knott, Alistair; Benuskova, Lubica

2015-01-01

Computational models of metaplasticity have usually focused on the modeling of single synapses (Shouval et al., 2002). In this paper we study the effect of metaplasticity on network behavior. Our guiding assumption is that the primary purpose of metaplasticity is to regulate synaptic plasticity, by increasing it when input is low and decreasing it when input is high. For our experiments we adopt a model of metaplasticity that demonstrably has this effect for a single synapse; our primary interest is in how metaplasticity thus defined affects network-level phenomena. We focus on a network-level phenomenon called polychronicity, that has a potential role in representation and memory. A network with polychronicity has the ability to produce non-synchronous but precisely timed sequences of neural firing events that can arise from strongly connected groups of neurons called polychronous neural groups (Izhikevich et al., 2004). Polychronous groups (PNGs) develop readily when spiking networks are exposed to repeated spatio-temporal stimuli under the influence of spike-timing-dependent plasticity (STDP), but are sensitive to changes in synaptic weight distribution. We use a technique we have recently developed called Response Fingerprinting to show that PNGs formed in the presence of metaplasticity are significantly larger than those with no metaplasticity. A potential mechanism for this enhancement is proposed that links an inherent property of integrator type neurons called spike latency to an increase in the tolerance of PNG neurons to jitter in their inputs.

Functional connectivity between right and left mesial temporal structures.

PubMed

Lacuey, Nuria; Zonjy, Bilal; Kahriman, Emine S; Kaffashi, Farhad; Miller, Jonathan; Lüders, Hans O

2015-09-01

The aim of this study is to investigate functional connectivity between right and left mesial temporal structures using cerebrocerebral evoked potentials. We studied seven patients with drug-resistant focal epilepsy who were explored with stereotactically implanted depth electrodes in bilateral hippocampi. In all patients cerebrocerebral evoked potentials evoked by stimulation of the fornix were evaluated as part of a research project assessing fornix stimulation for control of hippocampal seizures. Stimulation of the fornix elicited responses in the ipsilateral hippocampus in all patients with a mean latency of 4.6 ms (range 2-7 ms). Two patients (29 %) also had contralateral hippocampus responses with a mean latency of 7.5 ms (range 5-12 ms) and without involvement of the contralateral temporal neocortex or amygdala. This study confirms the existence of connections between bilateral mesial temporal structures in some patients and explains seizure discharge spreading between homotopic mesial temporal structures without neocortical involvement.

Novel flat datacenter network architecture based on scalable and flow-controlled optical switch system.

PubMed

Miao, Wang; Luo, Jun; Di Lucente, Stefano; Dorren, Harm; Calabretta, Nicola

2014-02-10

We propose and demonstrate an optical flat datacenter network based on scalable optical switch system with optical flow control. Modular structure with distributed control results in port-count independent optical switch reconfiguration time. RF tone in-band labeling technique allowing parallel processing of the label bits ensures the low latency operation regardless of the switch port-count. Hardware flow control is conducted at optical level by re-using the label wavelength without occupying extra bandwidth, space, and network resources which further improves the performance of latency within a simple structure. Dynamic switching including multicasting operation is validated for a 4 x 4 system. Error free operation of 40 Gb/s data packets has been achieved with only 1 dB penalty. The system could handle an input load up to 0.5 providing a packet loss lower that 10(-5) and an average latency less that 500 ns when a buffer size of 16 packets is employed. Investigation on scalability also indicates that the proposed system could potentially scale up to large port count with limited power penalty.

Low-Latency and Energy-Efficient Data Preservation Mechanism in Low-Duty-Cycle Sensor Networks.

PubMed

Jiang, Chan; Li, Tao-Shen; Liang, Jun-Bin; Wu, Heng

2017-05-06

Similar to traditional wireless sensor networks (WSN), the nodes only have limited memory and energy in low-duty-cycle sensor networks (LDC-WSN). However, different from WSN, the nodes in LDC-WSN often sleep most of their time to preserve their energies. The sleeping feature causes serious data transmission delay. However, each source node that has sensed data needs to quickly disseminate its data to other nodes in the network for redundant storage. Otherwise, data would be lost due to its source node possibly being destroyed by outer forces in a harsh environment. The quick dissemination requirement produces a contradiction with the sleeping delay in the network. How to quickly disseminate all the source data to all the nodes with limited memory in the network for effective preservation is a challenging issue. In this paper, a low-latency and energy-efficient data preservation mechanism in LDC-WSN is proposed. The mechanism is totally distributed. The data can be disseminated to the network with low latency by using a revised probabilistic broadcasting mechanism, and then stored by the nodes with LT (Luby Transform) codes, which are a famous rateless erasure code. After the process of data dissemination and storage completes, some nodes may die due to being destroyed by outer forces. If a mobile sink enters the network at any time and from any place to collect the data, it can recover all of the source data by visiting a small portion of survived nodes in the network. Theoretical analyses and simulation results show that our mechanism outperforms existing mechanisms in the performances of data dissemination delay and energy efficiency.

Robust Networking Architecture and Secure Communication Scheme for Heterogeneous Wireless Sensor Networks

ERIC Educational Resources Information Center

McNeal, McKenzie, III.

2012-01-01

Current networking architectures and communication protocols used for Wireless Sensor Networks (WSNs) have been designed to be energy efficient, low latency, and long network lifetime. One major issue that must be addressed is the security in data communication. Due to the limited capabilities of low cost and small sized sensor nodes, designing…

Evaluating IPv6 Adoption in the Internet

NASA Astrophysics Data System (ADS)

Colitti, Lorenzo; Gunderson, Steinar H.; Kline, Erik; Refice, Tiziana

As IPv4 address space approaches exhaustion, large networks are deploying IPv6 or preparing for deployment. However, there is little data available about the quantity and quality of IPv6 connectivity. We describe a methodology to measure IPv6 adoption from the perspective of a Web site operator and to evaluate the impact that adding IPv6 to a Web site will have on its users. We apply our methodology to the Google Web site and present results collected over the last year. Our data show that IPv6 adoption, while growing significantly, is still low, varies considerably by country, and is heavily influenced by a small number of large deployments. We find that native IPv6 latency is comparable to IPv4 and provide statistics on IPv6 transition mechanisms used.

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks

DOE PAGES

Shen, Yiwen; Hattink, Maarten; Samadi, Payman; ...

2018-04-13

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. Here, we present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly networkmore » testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 microsecond control plane latency for data-center and high performance computing platforms.« less

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, Yiwen; Hattink, Maarten; Samadi, Payman

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. Here, we present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly networkmore » testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 microsecond control plane latency for data-center and high performance computing platforms.« less

A New Cross-By-Pass-Torus Architecture Based on CBP-Mesh and Torus Interconnection for On-Chip Communication.

PubMed

Gulzari, Usman Ali; Sajid, Muhammad; Anjum, Sheraz; Agha, Shahrukh; Torres, Frank Sill

2016-01-01

A Mesh topology is one of the most promising architecture due to its regular and simple structure for on-chip communication. Performance of mesh topology degraded greatly by increasing the network size due to small bisection width and large network diameter. In order to overcome this limitation, many researchers presented modified Mesh design by adding some extra links to improve its performance in terms of network latency and power consumption. The Cross-By-Pass-Mesh was presented by us as an improved version of Mesh topology by intelligent addition of extra links. This paper presents an efficient topology named Cross-By-Pass-Torus for further increase in the performance of the Cross-By-Pass-Mesh topology. The proposed design merges the best features of the Cross-By-Pass-Mesh and Torus, to reduce the network diameter, minimize the average number of hops between nodes, increase the bisection width and to enhance the overall performance of the network. In this paper, the architectural design of the topology is presented and analyzed against similar kind of 2D topologies in terms of average latency, throughput and power consumption. In order to certify the actual behavior of proposed topology, the synthetic traffic trace and five different real embedded application workloads are applied to the proposed as well as other competitor network topologies. The simulation results indicate that Cross-By-Pass-Torus is an efficient candidate among its predecessor's and competitor topologies due to its less average latency and increased throughput at a slight cost in network power and energy for on-chip communication.

Next-generation optical wireless communications for data centers

NASA Astrophysics Data System (ADS)

Arnon, Shlomi

2015-01-01

Data centers collect and process information with a capacity that has been increasing from year to year at an almost exponential pace. Traditional fiber/cable data center network interconnections suffer from bandwidth overload, as well as flexibility and scalability issues. Therefore, a technology-shift from the fiber and cable to wireless has already been initiated in order to meet the required data-rate, flexibility and scalability demands for next-generation data center network interconnects. In addition, the shift to wireless reduces the volume allocated to the cabling/fiber and increases the cooling efficiency. Optical wireless communication (OWC), or free space optics (FSO), is one of the most effective wireless technologies that could be used in future data centers and could provide ultra-high capacity, very high cyber security and minimum latency, due to the low index of refraction of air in comparison to fiber technologies. In this paper we review the main concepts and configurations for next generation OWC for data centers. Two families of technologies are reviewed: the first technology regards interconnects between rack units in the same rack and the second technology regards the data center network that connects the server top of rack (TOR) to the switch. A comparison between different network technologies is presented.

Training Deep Spiking Neural Networks Using Backpropagation.

PubMed

Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

2016-01-01

Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.

A Scalable Multicore Architecture With Heterogeneous Memory Structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs).

PubMed

Moradi, Saber; Qiao, Ning; Stefanini, Fabio; Indiveri, Giacomo

2018-02-01

Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here, we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multicore neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.

Extending the Capabilities of Closed-loop Distributed Engine Control Simulations Using LAN Communication

NASA Technical Reports Server (NTRS)

Aretskin-Hariton, Eliot D.; Zinnecker, Alicia Mae; Culley, Dennis E.

2014-01-01

Distributed Engine Control (DEC) is an enabling technology that has the potential to advance the state-of-the-art in gas turbine engine control. To analyze the capabilities that DEC offers, a Hardware-In-the-Loop (HIL) test bed is being developed at NASA Glenn Research Center. This test bed will support a systems-level analysis of control capabilities in closed-loop engine simulations. The structure of the HIL emulates a virtual test cell by implementing the operator functions, control system, and engine on three separate computers. This implementation increases the flexibility and extensibility of the HIL. Here, a method is discussed for implementing these interfaces by connecting the three platforms over a dedicated Local Area Network (LAN). This approach is verified using the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k), which is typically implemented on one computer. There are marginal differences between the results from simulation of the typical and the three-computer implementation. Additional analysis of the LAN network, including characterization of network load, packet drop, and latency, is presented. The three-computer setup supports the incorporation of complex control models and proprietary engine models into the HIL framework.

Improved Dynamic Lightpath Provisioning for Large Wavelength-Division Multiplexed Backbones

NASA Astrophysics Data System (ADS)

Kong, Huifang; Phillips, Chris

2007-07-01

Technology already exists that would allow future optical networks to support automatic lightpath configuration in response to dynamic traffic demands. Given appropriate commercial drivers, it is possible to foresee carrier network operators migrating away from semipermanent provisioning to enable on-demand short-duration communications. However, with traditional lightpath reservation protocols, a portion of the lightpath is idly held during the signaling propagation phase, which can significantly reduce the lightpath bandwidth efficiency in large wavelength-division multiplexed backbones. This paper proposes a prebooking mechanism to improve the lightpath efficiency over traditional reactive two-way reservation protocols, consequently liberating network resources to support higher traffic loads. The prebooking mechanism predicts the time when the traffic will appear at the optical cross connects, and intelligently schedules the lightpath components such that resources are only consumed as necessary. We describe the proposed signaling procedure for both centralized and distributed control planes and analyze its performance. This paper also investigates the aggregated flow length characteristics with the self-similar incident traffic and examines the effects of traffic prediction on the blocking probability as well as the ability to support latency sensitive traffic in a wide-area environment.

Network-Centric Quantum Communications

NASA Astrophysics Data System (ADS)

Hughes, Richard

2014-03-01

Single-photon quantum communications (QC) offers ``future-proof'' cryptographic security rooted in the laws of physics. Today's quantum-secured communications cannot be compromised by unanticipated future technological advances. But to date, QC has only existed in point-to-point instantiations that have limited ability to address the cyber security challenges of our increasingly networked world. In my talk I will describe a fundamentally new paradigm of network-centric quantum communications (NQC) that leverages the network to bring scalable, QC-based security to user groups that may have no direct user-to-user QC connectivity. With QC links only between each of N users and a trusted network node, NQC brings quantum security to N2 user pairs, and to multi-user groups. I will describe a novel integrated photonics quantum smartcard (``QKarD'') and its operation in a multi-node NQC test bed. The QKarDs are used to implement the quantum cryptographic protocols of quantum identification, quantum key distribution and quantum secret splitting. I will explain how these cryptographic primitives are used to provide key management for encryption, authentication, and non-repudiation for user-to-user communications. My talk will conclude with a description of a recent demonstration that QC can meet both the security and quality-of-service (latency) requirements for electric grid control commands and data. These requirements cannot be met simultaneously with present-day cryptography.

Digoxin reveals a functional connection between HIV-1 integration preference and T-cell activation.

PubMed

Zhyvoloup, Alexander; Melamed, Anat; Anderson, Ian; Planas, Delphine; Lee, Chen-Hsuin; Kriston-Vizi, Janos; Ketteler, Robin; Merritt, Andy; Routy, Jean-Pierre; Ancuta, Petronela; Bangham, Charles R M; Fassati, Ariberto

2017-07-01

HIV-1 integrates more frequently into transcribed genes, however the biological significance of HIV-1 integration targeting has remained elusive. Using a selective high-throughput chemical screen, we discovered that the cardiac glycoside digoxin inhibits wild-type HIV-1 infection more potently than HIV-1 bearing a single point mutation (N74D) in the capsid protein. We confirmed that digoxin repressed viral gene expression by targeting the cellular Na+/K+ ATPase, but this did not explain its selectivity. Parallel RNAseq and integration mapping in infected cells demonstrated that digoxin inhibited expression of genes involved in T-cell activation and cell metabolism. Analysis of >400,000 unique integration sites showed that WT virus integrated more frequently than N74D mutant within or near genes susceptible to repression by digoxin and involved in T-cell activation and cell metabolism. Two main gene networks down-regulated by the drug were CD40L and CD38. Blocking CD40L by neutralizing antibodies selectively inhibited WT virus infection, phenocopying digoxin. Thus the selectivity of digoxin depends on a combination of integration targeting and repression of specific gene networks. The drug unmasked a functional connection between HIV-1 integration and T-cell activation. Our results suggest that HIV-1 evolved integration site selection to couple its early gene expression with the status of target CD4+ T-cells, which may affect latency and viral reactivation.

Measuring and Evaluating TCP Splitting for Cloud Services

NASA Astrophysics Data System (ADS)

Pathak, Abhinav; Wang, Y. Angela; Huang, Cheng; Greenberg, Albert; Hu, Y. Charlie; Kern, Randy; Li, Jin; Ross, Keith W.

In this paper, we examine the benefits of split-TCP proxies, deployed in an operational world-wide network, for accelerating cloud services. We consider a fraction of a network consisting of a large number of satellite datacenters, which host split-TCP proxies, and a smaller number of mega datacenters, which ultimately perform computation or provide storage. Using web search as an exemplary case study, our detailed measurements reveal that a vanilla TCP splitting solution deployed at the satellite DCs reduces the 95 th percentile of latency by as much as 43% when compared to serving queries directly from the mega DCs. Through careful dissection of the measurement results, we characterize how individual components, including proxy stacks, network protocols, packet losses and network load, can impact the latency. Finally, we shed light on further optimizations that can fully realize the potential of the TCP splitting solution.

A performance study of unmanned aerial vehicle-based sensor networks under cyber attack

NASA Astrophysics Data System (ADS)

Puchaty, Ethan M.

In UAV-based sensor networks, an emerging area of interest is the performance of these networks under cyber attack. This study seeks to evaluate the performance trade-offs from a System-of-Systems (SoS) perspective between various UAV communications architecture options in the context two missions: tracking ballistic missiles and tracking insurgents. An agent-based discrete event simulation is used to model a sensor communication network consisting of UAVs, military communications satellites, ground relay stations, and a mission control center. Network susceptibility to cyber attack is modeled with probabilistic failures and induced data variability, with performance metrics focusing on information availability, latency, and trustworthiness. Results demonstrated that using UAVs as routers increased network availability with a minimal latency penalty and communications satellite networks were best for long distance operations. Redundancy in the number of links between communication nodes helped mitigate cyber-caused link failures and add robustness in cases of induced data variability by an adversary. However, when failures were not independent, redundancy and UAV routing were detrimental in some cases to network performance. Sensitivity studies indicated that long cyber-caused downtimes and increasing failure dependencies resulted in build-ups of failures and caused significant degradations in network performance.

Does an intraneural interface short-term implant for robotic hand control modulate sensorimotor cortical integration? An EEG-TMS co-registration study on a human amputee.

PubMed

Ferreri, F; Ponzo, D; Vollero, L; Guerra, A; Di Pino, G; Petrichella, S; Benvenuto, A; Tombini, M; Rossini, L; Denaro, L; Micera, S; Iannello, G; Guglielmelli, E; Denaro, V; Rossini, P M

2014-01-01

Following limb amputation, central and peripheral nervous system relays partially maintain their functions and can be exploited for interfacing prostheses. The aim of this study is to investigate, for the first time by means of an EEG-TMS co-registration study, whether and how direct bidirectional connection between brain and hand prosthesis impacts on sensorimotor cortical topography. Within an experimental protocol for robotic hand control, a 26 years-old, left-hand amputated male was selected to have implanted four intrafascicular electrodes (tf-LIFEs-4) in the median and ulnar nerves of the stump for 4 weeks. Before tf-LIFE-4s implant (T0) and after the training period, once electrodes have been removed (T1), experimental subject's cortico-cortical excitability, connectivity and plasticity were tested via a neuronavigated EEG-TMS experiment. The statistical analysis clearly demonstrated a significant modulation (with t-test p < 0.0001) of EEG activity between 30 and 100 ms post-stimulus for the stimulation of the right hemisphere. When studying individual latencies in that time range, a global amplitude modulation was found in most of the TMS-evoked potentials; particularly, the GEE analysis showed significant differences between T0 and T1 condition at 30 ms (p < 0.0404), 46 ms (p < 0.0001) and 60 ms (p < 0.007) latencies. Finally, also a clear local decrement in N46 amplitude over C4 was evident. No differences between conditions were observed for the stimulation of the left hemisphere. The results of this study confirm the hypothesis that bidirectional neural interface could redirect cortical areas -deprived of their original input/output functions- toward restorative neuroplasticity. This reorganization strongly involves bi-hemispheric networks and intracortical and transcortical modulation of GABAergic inhibition.

Wireless, Web-Based Interactive Control of Optical Coherence Tomography with Mobile Devices

PubMed Central

Mehta, Rajvi; Nankivil, Derek; Zielinski, David J.; Waterman, Gar; Keller, Brenton; Limkakeng, Alexander T.; Kopper, Regis; Izatt, Joseph A.; Kuo, Anthony N.

2017-01-01

Purpose Optical coherence tomography (OCT) is widely used in ophthalmology clinics and has potential for more general medical settings and remote diagnostics. In anticipation of remote applications, we developed wireless interactive control of an OCT system using mobile devices. Methods A web-based user interface (WebUI) was developed to interact with a handheld OCT system. The WebUI consisted of key OCT displays and controls ported to a webpage using HTML and JavaScript. Client–server relationships were created between the WebUI and the OCT system computer. The WebUI was accessed on a cellular phone mounted to the handheld OCT probe to wirelessly control the OCT system. Twenty subjects were imaged using the WebUI to assess the system. System latency was measured using different connection types (wireless 802.11n only, wireless to remote virtual private network [VPN], and cellular). Results Using a cellular phone, the WebUI was successfully used to capture posterior eye OCT images in all subjects. Simultaneous interactivity by a remote user on a laptop was also demonstrated. On average, use of the WebUI added only 58, 95, and 170 ms to the system latency using wireless only, wireless to VPN, and cellular connections, respectively. Qualitatively, operator usage was not affected. Conclusions Using a WebUI, we demonstrated wireless and remote control of an OCT system with mobile devices. Translational Relevance The web and open source software tools used in this project make it possible for any mobile device to potentially control an OCT system through a WebUI. This platform can be a basis for remote, teleophthalmology applications using OCT. PMID:28138415

Systematic adaptation of data delivery

DOEpatents

Bakken, David Edward

2016-02-02

This disclosure describes, in part, a system management component for use in a power grid data network to systematically adjust the quality of service of data published by publishers and subscribed to by subscribers within the network. In one implementation, subscribers may identify a desired data rate, a minimum acceptable data rate, desired latency, minimum acceptable latency and a priority for each subscription and the system management component may adjust the data rates in real-time to ensure that the power grid data network does not become overloaded and/or fail. In one example, subscriptions with lower priorities may have their quality of service adjusted before subscriptions with higher priorities. In each instance, the quality of service may be maintained, even if reduced, to meet or exceed the minimum acceptable quality of service for the subscription.

Global tree network for computing structures enabling global processing operations

DOEpatents

Blumrich; Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Hoenicke, Dirk; Steinmacher-Burow, Burkhard D.; Takken, Todd E.; Vranas, Pavlos M.

2010-01-19

A system and method for enabling high-speed, low-latency global tree network communications among processing nodes interconnected according to a tree network structure. The global tree network enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the tree via links to facilitate performance of low-latency global processing operations at nodes of the virtual tree and sub-tree structures. The global operations performed include one or more of: broadcast operations downstream from a root node to leaf nodes of a virtual tree, reduction operations upstream from leaf nodes to the root node in the virtual tree, and point-to-point message passing from any node to the root node. The global tree network is configurable to provide global barrier and interrupt functionality in asynchronous or synchronized manner, and, is physically and logically partitionable.

Formation Flying for Satellites and UAVs

NASA Technical Reports Server (NTRS)

Merrill, Garrick; Becker, Chris

2015-01-01

A formation monitoring and control system was developed utilizing mesh networking and decentralized control. Highlights of this system include low latency, seamless addition and removal of vehicles, network relay functionality, and the ability to run on a variety of hardware.

Information-theoretic characterization of dynamic energy systems

NASA Astrophysics Data System (ADS)

Bevis, Troy Lawson

The latter half of the 20th century saw tremendous growth in nearly every aspect of civilization. From the internet to transportation, the various infrastructures relied upon by society has become exponentially more complex. Energy systems are no exception, and today the power grid is one of the largest infrastructures in the history of the world. The growing infrastructure has led to an increase in not only the amount of energy produced, but also an increase in the expectations of the energy systems themselves. The need for a power grid that is reliable, secure, and efficient is apparent, and there have been several initiatives to provide such a system. These increases in expectations have led to a growth in the renewable energy sources that are being integrated into the grid, a change that increases efficiency and disperses the generation throughout the system. Although this change in the grid infrastructure is beneficial, it leads to grand challenges in system level control and operation. As the number of sources increases and becomes geographically distributed, the control systems are no longer local to the system. This means that communication networks must be enhanced to support multiple devices that must communicate reliably. A common solution to these new systems is to use wide area networks for the communication network, as opposed to point-to-point communication. Although the wide area network will support a large number of devices, it generally comes with a compromise in the form of latency in the communication system. Now the device controller has latency injected into the feedback loop of the system. Also, renewable energy sources are largely non-dispatchable generation. That is, they are never guaranteed to be online and supplying the demanded energy. As renewable generation is typically modeled as stochastic process, it would useful to include this behavior in the control system algorithms. The combination of communication latency and stochastic sources are compounded by the dynamics of the grid itself. Loads are constantly changing, as well as the sources; this can sometimes lead to a quick change in system states. There is a need for a metric to be able to take into consideration all of the factors detailed above; it needs to be able to take into consideration the amount of information that is available in the system and the rate that the information is losing its value. In a dynamic system, the information is only valid for a length of time, and the controller must be able to take into account the decay of currently held information. This thesis will present the information theory metrics in a way that is useful for application to dynamic energy systems. A test case involving synchronization of several generators is presented for analysis and application of the theory. The objective is to synchronize all the generators and connect them to a common bus. As the phase shift of each generator is a random process, the effects of latency and information decay can be directly observed. The results of the experiments clearly show that the expected outcomes are observed and that entropy and information theory is a valid metric for timing requirement extraction.

HyspIRI Low Latency Concept and Benchmarks

NASA Technical Reports Server (NTRS)

Mandl, Dan

2010-01-01

Topics include HyspIRI low latency data ops concept, HyspIRI data flow, ongoing efforts, experiment with Web Coverage Processing Service (WCPS) approach to injecting new algorithms into SensorWeb, low fidelity HyspIRI IPM testbed, compute cloud testbed, open cloud testbed environment, Global Lambda Integrated Facility (GLIF) and OCC collaboration with Starlight, delay tolerant network (DTN) protocol benchmarking, and EO-1 configuration for preliminary DTN prototype.

Critical phenomena in communication/computation networks with various topologies and suboptimal to optimal resource allocation

NASA Astrophysics Data System (ADS)

Cogoni, Marco; Busonera, Giovanni; Anedda, Paolo; Zanetti, Gianluigi

2015-01-01

We generalize previous studies on critical phenomena in communication networks [1,2] by adding computational capabilities to the nodes. In our model, a set of tasks with random origin, destination and computational structure is distributed on a computational network, modeled as a graph. By varying the temperature of a Metropolis Montecarlo, we explore the global latency for an optimal to suboptimal resource assignment at a given time instant. By computing the two-point correlation function for the local overload, we study the behavior of the correlation distance (both for links and nodes) while approaching the congested phase: a transition from peaked to spread g(r) is seen above a critical (Montecarlo) temperature Tc. The average latency trend of the system is predicted by averaging over several network traffic realizations while maintaining a spatially detailed information for each node: a sharp decrease of performance is found over Tc independently of the workload. The globally optimized computational resource allocation and network routing defines a baseline for a future comparison of the transition behavior with respect to existing routing strategies [3,4] for different network topologies.

Dual Purpose Simulation: New Data Link Test and Comparison With VDL-2

NASA Technical Reports Server (NTRS)

Robinson, Daryl C.

2005-01-01

While the results of this paper are similar to those of previous research, in this paper technical difficulties present there are eliminated, producing better results, enabling one to more readily see the benefits of Prioritized CSMA (PCSMA). A new analysis section also helps to generalize this research so that it is not limited to exploration of the new concept of PCSMA. Commercially available network simulation software, OPNET version 7.0, simulations are presented involving an important application of the Aeronautical Telecommunications Network (ATN), Controller Pilot Data Link Communications (CPDLC) over the Very High Frequency Data Link Mode 2 (VDL-2). Communication is modeled for essentially all incoming and outgoing nonstop air traffic for just three United States cities: Cleveland, Cincinnati, and Detroit. The simulation involves 111 Air Traffic Control (ATC) ground stations, 32 airports distributed throughout the U.S., which are either sources or destinations for the air traffic landing or departing from the three cities, and also 1,235 equally equipped aircraft taking off, flying realistic free-flight trajectories, and landing in a 24-hr period. Collision-less PCSMA is successfully tested and compared with the traditional CSMA typically associated with VDL- 2. The performance measures include latency, throughput, and packet loss. As expected, PCSMA is much quicker and more efficient than traditional CSMA. These simulation results show the potency of PCSMA for implementing low latency, high throughput and efficient connectivity. Moreover, since PCSMA outperforms traditional CSMA, by simulating with it, we can determine the limits of performance beyond which traditional CSMA may not pass. We are testing a new and better data link that could replace CSMA with relative ease. Work is underway to drastically expand the number of flights to make the simulation more representative of the National Aerospace System.

Framework for analysis of guaranteed QOS systems

NASA Astrophysics Data System (ADS)

Chaudhry, Shailender; Choudhary, Alok

1997-01-01

Multimedia data is isochronous in nature and entails managing and delivering high volumes of data. Multiprocessors with their large processing power, vast memory, and fast interconnects, are an ideal candidate for the implementation of multimedia applications. Initially, multiprocessors were designed to execute scientific programs and thus their architecture was optimized to provide low message latency and efficiently support regular communication patterns. Hence, they have a regular network topology and most use wormhole routing. The design offers the benefits of a simple router, small buffer size, and network latency that is almost independent of path length. Among the various multimedia applications, video on demand (VOD) server is well-suited for implementation using parallel multiprocessors. Logical models for VOD servers are presently mapped onto multiprocessors. Our paper provides a framework for calculating bounds on utilization of system resources with which QoS parameters for each isochronous stream can be guaranteed. Effects of the architecture of multiprocessors, and efficiency of various local models and mapping on particular architectures can be investigated within our framework. Our framework is based on rigorous proofs and provides tight bounds. The results obtained may be used as the basis for admission control tests. To illustrate the versatility of our framework, we provide bounds on utilization for various logical models applied to mesh connected architectures for a video on demand server. Our results show that worm hole routing can lead to packets waiting for transmission of other packets that apparently share no common resources. This situation is analogous to head-of-the-line blocking. We find that the provision of multiple VCs per link and multiple flit buffers improves utilization (even under guaranteed QoS parameters). This analogous to parallel iterative matching.

Dual Purpose Simulation: New Data Link Test and Comparison with VDL-2

NASA Technical Reports Server (NTRS)

Robinson, Daryl C.

2002-01-01

While the results of this paper are similar to those of previous research, in this paper technical difficulties present there are eliminated, producing better results, enabling one to more readily see the benefits of Prioritized CSMA (PCSMA). A new analysis section also helps to generalize this research so that it is not limited to exploration of the new concept of PCSMA. Commercially available network simulation software, OPNET version 7.0, simulations are presented involving an important application of the Aeronautical Telecommunications Network (A TN), Controller Pilot Data Link Communications (CPDLC) over the Very High Frequency Data Link Mode 2 (VDL-2). Communication is modeled for essentially all incoming and outgoing nonstop air traffic for just three United States cities: Cleveland, Cincinnati, and Detroit. The simulation involves 111 Air Traffic Control (ATC) ground stations, 32 airports distributed throughout the U.S., which are either sources or destinations for the air traffic landing or departing from the three cities, and also 1,235 equally equipped aircraft- taking off, flying realistic free- flight trajectories, and landing in a 24-hr period. Collision-less PCSMA is successfully tested and compared with the traditional CSMA typically associated with VDL-2. The performance measures include latency, throughput, and packet loss. As expected, PCSMA is much quicker and more efficient than traditional CSMA. These simulation results show the potency of PC SMA for implementing low latency, high throughput and efficient connectivity. Moreover, since PCSMA out performs traditional CSMA, by simulating with it, we can determine the limits of performance beyond which traditional CSMA may not pass. We are testing a new and better data link that could replace CSMA with relative ease. Work is underway to drastically expand the number of flights to make the simulation more representative of the National Aerospace System.

Data Latency Characteristics Observed Through Diverse Communication Links by the EarthScope USArray Transportable Array

NASA Astrophysics Data System (ADS)

Vernon, F. L.; Eakins, J. A.; Busby, R.

2008-12-01

The USArray Transportable Array has deployed over 600 stations in aggregate over the past four years. All stations communicate in near-real time using ip protocols over a variety of communication links including satellite, cell phone, and DSL. Several different communication providers have been used for each type of communication links. In addition, data are being acquired from several regional networks either directly from a data server or after passing through the IRIS DMC BUD system. We will present results about the latency of data arriving at the UCSD Array Network Facility where the real time data are acquired. Under normal operating conditions the median data latency is several seconds. We will also examine the data return rates through the near-real time systems. In addition we will examine the statistics of over 36,000 events which have automatic event locations and associations. We evaluate the timeliness of these results in the context of seismic early warning systems.

A Fully Implemented 12 × 12 Data Vortex Optical Packet Switching Interconnection Network

NASA Astrophysics Data System (ADS)

Shacham, Assaf; Small, Benjamin A.; Liboiron-Ladouceur, Odile; Bergman, Keren

2005-10-01

A fully functional optical packet switching (OPS) interconnection network based on the data vortex architecture is presented. The photonic switching fabric uniquely capitalizes on the enormous bandwidth advantage of wavelength division multiplexing (WDM) wavelength parallelism while delivering minimal packet transit latency. Utilizing semiconductor optical amplifier (SOA)-based switching nodes and conventional fiber-optic technology, the 12-port system exhibits a capacity of nearly 1 Tb/s. Optical packets containing an eight-wavelength WDM payload with 10 Gb/s per wavelength are routed successfully to all 12 ports while maintaining a bit error rate (BER) of 10-12 or better. Median port-to-port latencies of 110 ns are achieved with a distributed deflection routing network that resolves packet contention on-the-fly without the use of optical buffers and maintains the entire payload path in the optical domain.

The Operational Impacts of the Global Network Enterprise Construct

DTIC Science & Technology

2010-05-14

Board Task Force on Achieving Interoperability in a Net-Centric Environment, xiv. 60 Lolita Baldor, “Military Asserts Right to Return Cyber-Attacks...the commander is aware that applications such video teleconferencing and large file transfers are often not possible with subordinate units...data packets, but if there is latency along the path, services such as video or large file transfers will fail. Latency is the time delay inherent in

Throughput, latency and cost comparisons of microcontroller-based implementations of wireless sensor network (WSN) in high jump sports

NASA Astrophysics Data System (ADS)

Ahmad, Afandi; Roslan, Muhammad Faris; Amira, Abbes

2017-09-01

In high jump sports, approach take-off speed and force during the take-off are two (2) main important parts to gain maximum jump. To measure both parameters, wireless sensor network (WSN) that contains microcontroller and sensor are needed to describe the results of speed and force for jumpers. Most of the microcontroller exhibit transmission issues in terms of throughput, latency and cost. Thus, this study presents the comparison of wireless microcontrollers in terms of throughput, latency and cost, and the microcontroller that have best performances and cost will be implemented in high jump wearable device. In the experiments, three (3) parts have been integrated - input, process and output. Force (for ankle) and global positioning system (GPS) sensor (for body waist) acts as an input for data transmission. These data were then being processed by both microcontrollers, ESP8266 and Arduino Yun Mini to transmit the data from sensors to the server (host-PC) via message queuing telemetry transport (MQTT) protocol. The server acts as receiver and the results was calculated from the MQTT log files. At the end, results obtained have shown ESP8266 microcontroller had been chosen since it achieved high throughput, low latency and 11 times cheaper in term of prices compared to Arduino Yun Mini microcontroller.

Development Status of the Rad-Tolerant TTEthernet Controller

NASA Astrophysics Data System (ADS)

Fidi, Christian; van Masar, Ivan

2016-08-01

The use of switched networking technologies for aerospace and more recently automotive brings additional advantages for space applications like the increase in performance of the overall avionics of a spacecraft. These networks are characterized by a central device (switch) and a point-to-point structure between switch and terminal devices that eases electrical and logical insulation.However, for a use in highly-reliable or highly-available applications as in launchers or satellites systems, these network technologies need to provide built-in determinism and redundancy to fulfill the tight latency and jitter requirements of the avionics control loops and the respective hardware redundancy. Therefore a state of the art networking technology already provides these features and allows the modularity and scalability to be used for the different space applications and would allow combining the deterministic avionics with the high speed payload network in a spacecraft [1].Introducing the time-triggered principle to Ethernet allows combining the open industry standard IEE802.3 Ethernet currently use in almost all GSE platforms, with full control of latency and jitter of the time-triggered approach. To allow the time-triggered data flow over Ethernet, a network- wide synchronization time-base has to be established to allow deriving all network events on a globally known time which is typically done in software in almost all spacecrafts. The additional synchronization service of Time-triggered Ethernet has been implemented as additional quality of service (QoS) on layer 2 of the ISO/OSI network model and been standardized in the SAE AS6802 [3].Within a launcher, the communication system ensured the data exchanges between avionic functions during all phases of the launcher lifecycle which is composed of three areas: AIT operations, ground phase and flight phase. To ensure the use of a single network for the different phases, the network needs to support features like the handling of different traffic classes (critical traffic and non-critical traffic, i.e. TT, RC and BE [2]). Also the compatibility to the IEEE1588 synchronization protocol can be used to connect legacy IEEE1588 equipment for GSE equipment.However this commercially available technology currently used in the aviation-, the industrial- and the automotive market needs to be matured for the use in space applications. Therefore a development of the necessary space-grade components, mainly the switch and the end system is needed.This paper presents the current development status of a radiation tolerant integrated circuit for the use in different space applications. It outlines the different steps needed to be performed to ensure the usability of this digital chip in highly reliable as well as in highly available space applications.

5G small-cell networks leveraging optical technologies with mm-wave massive MIMO and MT-MAC protocols

NASA Astrophysics Data System (ADS)

Papaioannou, S.; Kalfas, G.; Vagionas, C.; Mitsolidou, C.; Maniotis, P.; Miliou, A.; Pleros, N.

2018-01-01

Analog optical fronthaul for 5G network architectures is currently being promoted as a bandwidth- and energy-efficient technology that can sustain the data-rate, latency and energy requirements of the emerging 5G era. This paper deals with a new optical fronthaul architecture that can effectively synergize optical transceiver, optical add/drop multiplexer and optical beamforming integrated photonics towards a DSP-assisted analog fronthaul for seamless and medium-transparent 5G small-cell networks. Its main application targets include dense and Hot-Spot Area networks, promoting the deployment of mmWave massive MIMO Remote Radio Heads (RRHs) that can offer wireless data-rates ranging from 25Gbps up to 400Gbps depending on the fronthaul technology employed. Small-cell access and resource allocation is ensured via a Medium-Transparent (MT-) MAC protocol that enables the transparent communication between the Central Office and the wireless end-users or the lamp-posts via roof-top-located V-band massive MIMO RRHs. The MTMAC is analysed in detail with simulation and analytical theoretical results being in good agreement and confirming its credentials to satisfy 5G network latency requirements by guaranteeing latency values lower than 1 ms for small- to midload conditions. Its extension towards supporting optical beamforming capabilities and mmWave massive MIMO antennas is discussed, while its performance is analysed for different fiber fronthaul link lengths and different optical channel capacities. Finally, different physical layer network architectures supporting the MT-MAC scheme are presented and adapted to different 5G use case scenarios, starting from PON-overlaid fronthaul solutions and gradually moving through Spatial Division Multiplexing up to Wavelength Division Multiplexing transport as the user density increases.

Automated Synthesis of Long Communication Delays for Testing

NASA Technical Reports Server (NTRS)

Seibert, Marc; McKim, James

2005-01-01

Planetary-Ohio Network Emulator (p- ONE) is a computer program for local laboratory testing of high bandwidth data-communication systems subject to long delays in propagation over interplanetary distances. p-ONE is installed on a personal computer connected to two bidirectional Ethernet interfaces, denoted A and B, that represent local-area networks at opposite ends of a long propagation path. Traffic that is to be passed between A and B is encapsulated in IP (Internet Protocol) packets (e.g., User Data Protocol, UDP). Intercepting this traffic between A and B in both directions, p-ONE time-tags each packet and stores it in memory or on the hard disk of the computer for a user-specified interval that equals the propagation delay to be synthesized. At the expiration of its storage time, each such packet is sent to its destination (that is, if it was received from A, it is sent to B, or vice versa). The accuracy of the p-ONE software is very high, with zero packet loss through the system and negligible latency. Optionally, p-ONE can be configured to delay all network traffic to and from all network addresses on each Ethernet interface or to selectively delay traffic between specific addresses or traffic of specific types. p-ONE works well with Linux and is also designed to be compatible with other operating systems.

Coarse-Grain Bandwidth Estimation Techniques for Large-Scale Space Network

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Jennings, Esther

2013-01-01

In this paper, we describe a top-down analysis and simulation approach to size the bandwidths of a store-andforward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. We use these techniques to estimate the wide area network (WAN) bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network.

High-Throughput and Low-Latency Network Communication with NetIO

NASA Astrophysics Data System (ADS)

Schumacher, Jörn; Plessl, Christian; Vandelli, Wainer

2017-10-01

HPC network technologies like Infiniband, TrueScale or OmniPath provide low- latency and high-throughput communication between hosts, which makes them attractive options for data-acquisition systems in large-scale high-energy physics experiments. Like HPC networks, DAQ networks are local and include a well specified number of systems. Unfortunately traditional network communication APIs for HPC clusters like MPI or PGAS exclusively target the HPC community and are not suited well for DAQ applications. It is possible to build distributed DAQ applications using low-level system APIs like Infiniband Verbs, but it requires a non-negligible effort and expert knowledge. At the same time, message services like ZeroMQ have gained popularity in the HEP community. They make it possible to build distributed applications with a high-level approach and provide good performance. Unfortunately, their usage usually limits developers to TCP/IP- based networks. While it is possible to operate a TCP/IP stack on top of Infiniband and OmniPath, this approach may not be very efficient compared to a direct use of native APIs. NetIO is a simple, novel asynchronous message service that can operate on Ethernet, Infiniband and similar network fabrics. In this paper the design and implementation of NetIO is presented and described, and its use is evaluated in comparison to other approaches. NetIO supports different high-level programming models and typical workloads of HEP applications. The ATLAS FELIX project [1] successfully uses NetIO as its central communication platform. The architecture of NetIO is described in this paper, including the user-level API and the internal data-flow design. The paper includes a performance evaluation of NetIO including throughput and latency measurements. The performance is compared against the state-of-the- art ZeroMQ message service. Performance measurements are performed in a lab environment with Ethernet and FDR Infiniband networks.

Polling-Based High-Bit-Rate Packet Transfer in a Microcellular Network to Allow Fast Terminals

NASA Astrophysics Data System (ADS)

Hoa, Phan Thanh; Lambertsen, Gaute; Yamada, Takahiko

A microcellular network will be a good candidate for the future broadband mobile network. It is expected to support high-bit-rate connection for many fast mobile users if the handover is processed fast enough to lessen its impact on QoS requirements. One of the promising techniques is believed to use for the wireless interface in such a microcellular network is the WLAN (Wireless LAN) technique due to its very high wireless channel rate. However, the less capability of mobility support of this technique must be improved to be able to expand its utilization for the microcellular environment. The reason of its less support mobility is large handover latency delay caused by contention-based handover to the new BS (base station) and delay of re-forwarding data from the old to new BS. This paper presents a proposal of multi-polling and dynamic LMC (Logical Macro Cell) to reduce mentioned above delays. Polling frame for an MT (Mobile Terminal) is sent from every BS belonging to the same LMC — a virtual single macro cell that is a multicast group of several adjacent micro-cells in which an MT is communicating. Instead of contending for the medium of a new BS during handover, the MT responds to the polling sent from that new BS to enable the transition. Because only one BS of the LMC receives the polling ACK (acknowledgement) directly from the MT, this ACK frame has to be multicast to all BSs of the same LMC through the terrestrial network to continue sending the next polling cycle at each BS. Moreover, when an MT hands over to a new cell, its current LMC is switched over to a newly corresponding LMC to prevent the future contending for a new LMC. By this way, an MT can do handover between micro-cells of an LMC smoothly because the redundant resource is reserved for it at neighboring cells, no need to contend with others. Our simulation results using the OMNeT++ simulator illustrate the performance achievements of the multi-polling and dynamic LMC scheme in eliminating handover latency, packet loss and keeping mobile users' throughput stable in the high traffic load condition though it causes somewhat overhead on the neighboring cells.

Topology-Aware Performance Optimization and Modeling of Adaptive Mesh Refinement Codes for Exascale

DOE PAGES

Chan, Cy P.; Bachan, John D.; Kenny, Joseph P.; ...

2017-01-26

Here, we introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and executionmore » strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.« less

Topology-Aware Performance Optimization and Modeling of Adaptive Mesh Refinement Codes for Exascale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chan, Cy P.; Bachan, John D.; Kenny, Joseph P.

Here, we introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and executionmore » strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.« less

Design and Analysis of a Low Latency Deterministic Network MAC for Wireless Sensor Networks

PubMed Central

Sahoo, Prasan Kumar; Pattanaik, Sudhir Ranjan; Wu, Shih-Lin

2017-01-01

The IEEE 802.15.4e standard has four different superframe structures for different applications. Use of a low latency deterministic network (LLDN) superframe for the wireless sensor network is one of them, which can operate in a star topology. In this paper, a new channel access mechanism for IEEE 802.15.4e-based LLDN shared slots is proposed, and analytical models are designed based on this channel access mechanism. A prediction model is designed to estimate the possible number of retransmission slots based on the number of failed transmissions. Performance analysis in terms of data transmission reliability, delay, throughput and energy consumption are provided based on our proposed designs. Our designs are validated for simulation and analytical results, and it is observed that the simulation results well match with the analytical ones. Besides, our designs are compared with the IEEE 802.15.4 MAC mechanism, and it is shown that ours outperforms in terms of throughput, energy consumption, delay and reliability. PMID:28937632

Design and Analysis of a Low Latency Deterministic Network MAC for Wireless Sensor Networks.

PubMed

Sahoo, Prasan Kumar; Pattanaik, Sudhir Ranjan; Wu, Shih-Lin

2017-09-22

The IEEE 802.15.4e standard has four different superframe structures for different applications. Use of a low latency deterministic network (LLDN) superframe for the wireless sensor network is one of them, which can operate in a star topology. In this paper, a new channel access mechanism for IEEE 802.15.4e-based LLDN shared slots is proposed, and analytical models are designed based on this channel access mechanism. A prediction model is designed to estimate the possible number of retransmission slots based on the number of failed transmissions. Performance analysis in terms of data transmission reliability, delay, throughput and energy consumption are provided based on our proposed designs. Our designs are validated for simulation and analytical results, and it is observed that the simulation results well match with the analytical ones. Besides, our designs are compared with the IEEE 802.15.4 MAC mechanism, and it is shown that ours outperforms in terms of throughput, energy consumption, delay and reliability.

Optical technologies for the Internet of Things era

NASA Astrophysics Data System (ADS)

Ji, Philip N.

2017-08-01

Internet of Things (IoT) is a network of interrelated physical objects that can collect and exchange data with one another through embedded electronics, software, sensors, over the Internet. It extends Internet connectivity beyond traditional networking devices to a diverse range of physical devices and everyday things that utilize embedded technologies to communicate and interact with the external environment. The IoT brings automation and efficiency improvement to everyday life, business, and society. Therefore IoT applications and market are growing rapidly. Contrary to common belief that IoT is only related to wireless technology, optical technologies actually play important roles in the growth of IoT and contribute to its advancement. Firstly, fiber optics provides the backbone for transporting large amount of data generated by IoT network in the core , metro and access networks, and in building or in the physical object. Secondly, optical switching technologies, including all-optical switching and hybrid optical-electrical switching, enable fast and high bandwidth routing in IoT data processing center. Thirdly, optical sensing and imaging delivers comprehensive information of multiple physical phenomena through monitoring various optical properties such as intensity, phase, wavelength, frequency, polarization, and spectral distribution. In particular, fiber optic sensor has the advantages of high sensitivity, low latency, and long distributed sensing range. It is also immune to electromagnetic interference, and can be implemented in harsh environment. In this paper, the architecture of IoT is described, and the optical technologies and their applications in the IoT networks are discussed with practical examples.

Telescience capability for the Sondre Stromfjord, Greenland, incoherent-scatter radar facility

NASA Astrophysics Data System (ADS)

Zambre, Yadunath B.

1993-01-01

SRI International (SRI) operates an upper-atmospheric research facility in Sondre Stromfjord (Sondrestrom), Greenland. In the past, the facility's remote location and limited logistical support imposed constraints on the research that could be carried out at the site. Campaigns involving multiple instruments were often constrained due to limited space, and experiments requiring coordination with other geographically separated facilities, though possible, were difficult. To provide greater access to the facility, an electronic connection between Sondrestrom and the mainland U.S.A. was established, providing access to the National Science Internet. SRI developed telescience software that sends data from the incoherent scatter radar at the Sondrestrom facility to SRI's offices in Menlo Park, California. This software uses the transmission control protocol (TCP/IP) to transmit the data in near real time between the two locations and the X window system to generate displays of the data in Menlo Park. This is in contrast to using the X window system to display data remotely across a wide-area network. Using CP to transport data over the long distance network has resulted in significantly improved network throughput and latency. While currently used to transport radar data, the telescience software is designed and intended for simultaneous use with other instruments at Sondrestrom and other facilities. Work incorporating additional instruments is currently in progress.

Electrophysiological Mapping of Novel Prefrontal – Cerebellar Pathways

PubMed Central

Watson, Thomas C.; Jones, Matthew W.; Apps, Richard

2009-01-01

Whilst the cerebellum is predominantly considered a sensorimotor control structure, accumulating evidence suggests that it may also subserve non-motor functions during cognition. However, this possibility is not universally accepted, not least because the nature and pattern of links between higher cortical structures and the cerebellum are poorly characterized. We have therefore used in vivo electrophysiological methods in anaesthetized rats to directly investigate connectivity between the medial prefrontal cortex (prelimbic subdivision, PrL) and the cerebellum. Stimulation of deep layers of PrL evoked distinct field potentials in the cerebellar cortex with a mean latency to peak of approximately 35 ms. These responses showed a well-defined topography, and were maximal in lobule VII of the contralateral vermis (a known oculomotor centre); they were not attenuated by local anaesthesia of the overlying M2 motor cortex, though M2 stimulation did evoke field potentials in lobule VII with a shorter latency (approximately 30 ms). Single unit recordings showed that prelimbic cortical stimulation elicits complex spikes in lobule VII Purkinje cells, indicating transmission via a previously undescribed cerebro-olivocerebellar pathway. Our results therefore establish a physiological basis for communication between PrL and the cerebellum. The role(s) of this pathway remain to be resolved, but presumably relate to control of eye movements and/or distributed networks associated with integrated prefrontal cortical functions. PMID:19738932

Extending the farm on external sites: the INFN Tier-1 experience

NASA Astrophysics Data System (ADS)

Boccali, T.; Cavalli, A.; Chiarelli, L.; Chierici, A.; Cesini, D.; Ciaschini, V.; Dal Pra, S.; dell'Agnello, L.; De Girolamo, D.; Falabella, A.; Fattibene, E.; Maron, G.; Prosperini, A.; Sapunenko, V.; Virgilio, S.; Zani, S.

2017-10-01

The Tier-1 at CNAF is the main INFN computing facility offering computing and storage resources to more than 30 different scientific collaborations including the 4 experiments at the LHC. It is also foreseen a huge increase in computing needs in the following years mainly driven by the experiments at the LHC (especially starting with the run 3 from 2021) but also by other upcoming experiments such as CTA[1] While we are considering the upgrade of the infrastructure of our data center, we are also evaluating the possibility of using CPU resources available in other data centres or even leased from commercial cloud providers. Hence, at INFN Tier-1, besides participating to the EU project HNSciCloud, we have also pledged a small amount of computing resources (˜ 2000 cores) located at the Bari ReCaS[2] for the WLCG experiments for 2016 and we are testing the use of resources provided by a commercial cloud provider. While the Bari ReCaS data center is directly connected to the GARR network[3] with the obvious advantage of a low latency and high bandwidth connection, in the case of the commercial provider we rely only on the General Purpose Network. In this paper we describe the set-up phase and the first results of these installations started in the last quarter of 2015, focusing on the issues that we have had to cope with and discussing the measured results in terms of efficiency.

Digoxin reveals a functional connection between HIV-1 integration preference and T-cell activation

PubMed Central

Planas, Delphine; Merritt, Andy; Routy, Jean-Pierre; Ancuta, Petronela; Bangham, Charles R. M.

2017-01-01

HIV-1 integrates more frequently into transcribed genes, however the biological significance of HIV-1 integration targeting has remained elusive. Using a selective high-throughput chemical screen, we discovered that the cardiac glycoside digoxin inhibits wild-type HIV-1 infection more potently than HIV-1 bearing a single point mutation (N74D) in the capsid protein. We confirmed that digoxin repressed viral gene expression by targeting the cellular Na+/K+ ATPase, but this did not explain its selectivity. Parallel RNAseq and integration mapping in infected cells demonstrated that digoxin inhibited expression of genes involved in T-cell activation and cell metabolism. Analysis of >400,000 unique integration sites showed that WT virus integrated more frequently than N74D mutant within or near genes susceptible to repression by digoxin and involved in T-cell activation and cell metabolism. Two main gene networks down-regulated by the drug were CD40L and CD38. Blocking CD40L by neutralizing antibodies selectively inhibited WT virus infection, phenocopying digoxin. Thus the selectivity of digoxin depends on a combination of integration targeting and repression of specific gene networks. The drug unmasked a functional connection between HIV-1 integration and T-cell activation. Our results suggest that HIV-1 evolved integration site selection to couple its early gene expression with the status of target CD4+ T-cells, which may affect latency and viral reactivation. PMID:28727807

SMAC: A soft MAC to reduce control overhead and latency in CDMA-based AMI networks

DOE PAGES

Garlapati, Shravan; Kuruganti, Teja; Buehrer, Michael R.; ...

2015-10-26

The utilization of state-of-the-art 3G cellular CDMA technologies in a utility owned AMI network results in a large amount of control traffic relative to data traffic, increases the average packet delay and hence are not an appropriate choice for smart grid distribution applications. Like the CDG, we consider a utility owned cellular like CDMA network for smart grid distribution applications and classify the distribution smart grid data as scheduled data and random data. Also, we propose SMAC protocol, which changes its mode of operation based on the type of the data being collected to reduce the data collection latency andmore » control overhead when compared to 3G cellular CDMA2000 MAC. The reduction in the data collection latency and control overhead aids in increasing the number of smart meters served by a base station within the periodic data collection interval, which further reduces the number of base stations needed by a utility or reduces the bandwidth needed to collect data from all the smart meters. The reduction in the number of base stations and/or the reduction in the data transmission bandwidth reduces the CAPital EXpenditure (CAPEX) and OPerational EXpenditure (OPEX) of the AMI network. Finally, the proposed SMAC protocol is analyzed using markov chain, analytical expressions for average throughput and average packet delay are derived, and simulation results are also provided to verify the analysis.« less

Development and preliminary validation of an interactive remote physical therapy system.

PubMed

Mishra, Anup K; Skubic, Marjorie; Abbott, Carmen

2015-01-01

In this paper, we present an interactive physical therapy system (IPTS) for remote quantitative assessment of clients in the home. The system consists of two different interactive interfaces connected through a network, for a real-time low latency video conference using audio, video, skeletal, and depth data streams from a Microsoft Kinect. To test the potential of IPTS, experiments were conducted with 5 independent living senior subjects in Kansas City, MO. Also, experiments were conducted in the lab to validate the real-time biomechanical measures calculated using the skeletal data from the Microsoft Xbox 360 Kinect and Microsoft Xbox One Kinect, with ground truth data from a Vicon motion capture system. Good agreements were found in the validation tests. The results show potential capabilities of the IPTS system to provide remote physical therapy to clients, especially older adults, who may find it difficult to visit the clinic.

Efficient image data distribution and management with application to web caching architectures

NASA Astrophysics Data System (ADS)

Han, Keesook J.; Suter, Bruce W.

2003-03-01

We present compact image data structures and associated packet delivery techniques for effective Web caching architectures. Presently, images on a web page are inefficiently stored, using a single image per file. Our approach is to use clustering to merge similar images into a single file in order to exploit the redundancy between images. Our studies indicate that a 30-50% image data size reduction can be achieved by eliminating the redundancies of color indexes. Attached to this file is new metadata to permit an easy extraction of images. This approach will permit a more efficient use of the cache, since a shorter list of cache references will be required. Packet and transmission delays can be reduced by 50% eliminating redundant TCP/IP headers and connection time. Thus, this innovative paradigm for the elimination of redundancy may provide valuable benefits for optimizing packet delivery in IP networks by reducing latency and minimizing the bandwidth requirements.

A Latency-Tolerant Partitioner for Distributed Computing on the Information Power Grid

NASA Technical Reports Server (NTRS)

Das, Sajal K.; Harvey, Daniel J.; Biwas, Rupak; Kwak, Dochan (Technical Monitor)

2001-01-01

NASA's Information Power Grid (IPG) is an infrastructure designed to harness the power of graphically distributed computers, databases, and human expertise, in order to solve large-scale realistic computational problems. This type of a meta-computing environment is necessary to present a unified virtual machine to application developers that hides the intricacies of a highly heterogeneous environment and yet maintains adequate security. In this paper, we present a novel partitioning scheme. called MinEX, that dynamically balances processor workloads while minimizing data movement and runtime communication, for applications that are executed in a parallel distributed fashion on the IPG. We also analyze the conditions that are required for the IPG to be an effective tool for such distributed computations. Our results show that MinEX is a viable load balancer provided the nodes of the IPG are connected by a high-speed asynchronous interconnection network.

Development of a Real-Time GPS/Seismic Displacement Meter: GPS Component

NASA Astrophysics Data System (ADS)

Bock, Y.; Canas, J.; Andrew, A.; Vernon, F.

2002-12-01

We report on the status of the Orange County Real-Time GPS Network (OCRTN), an upgrade of the SCIGN sites in Orange County and Catalina Island to low latency (1 sec), high-rate (1 Hz) data streaming, analysis, and dissemination. The project is a collaborative effort of the California Spatial Reference Center (CSRC) and the Orange County Dept. of Geomatics, with partners from the geophysical community (SCIGN), local and state government, and the private sector. As part of Phase 1 of the project, nine sites are streaming data by dedicated, point-to-point radio modems to a central data server located in Santa Ana. Instantaneous positions are computed for each site. Data are converted from 1 Hz Ashtech binary MBEN format to (1) 1 Hz RTCM format, and (2) decimated (15 sec) RINEX format. A second computer outside a firewall and located in another building at the Orange County's Computer Center is a TCP-based client of RTCM data (messages 18, 19, 3, and 22) from the data server, as well as a TCP-based server of RTCM data to the outside world. An external computer can access the RTCM data from all active sites through an IP socket connection. Data latency, in the best case, is less than 1 sec from real-time. Once a day, the decimated RINEX data are transferred by ftp from the data server to the SOPAC-CSRC archive at Scripps. Data recovery is typically 99-100%. As part of the second phase of the project, the RTCM server provides data to field receivers to perform RTK surveying. On connection to the RTCM server the user gets a list of active stations, and can then choose from which site to retrieve RTCM data. This site then plays the role of the RTK base station and a CDPD-based wireless Internet device plays the role of the normal RTK radio link. If an Internet connection is available, we will demonstrate how the system operates. This system will serve as a prototype for the GPS component of the GPS/seismic displacement meter.

GBU-X bounding requirements for highly flexible munitions

NASA Astrophysics Data System (ADS)

Bagby, Patrick T.; Shaver, Jonathan; White, Reed; Cafarelli, Sergio; Hébert, Anthony J.

2017-04-01

This paper will present the results of an investigation into requirements for existing software and hardware solutions for open digital communication architectures that support weapon subsystem integration. The underlying requirements of such a communication architecture would be to achieve the lowest latency possible at a reasonable cost point with respect to the mission objective of the weapon. The determination of the latency requirements of the open architecture software and hardware were derived through the use of control system and stability margins analyses. Studies were performed on the throughput and latency of different existing communication transport methods. The two architectures that were tested in this study include Data Distribution Service (DDS) and Modular Open Network Architecture (MONARCH). This paper defines what levels of latency can be achieved with current technology and how this capability may translate to future weapons. The requirements moving forward within communications solutions are discussed.

Measurement and reduction of system latency in see-through helmet mounted display (HMD) systems

NASA Astrophysics Data System (ADS)

Vincenzi, Dennis A.; Deaton, John E.; Blickenderfer, Elizabeth L.; Pray, Rick; Williams, Barry; Buker, Timothy J.

2010-04-01

Future military aviation platforms such as the proposed Joint Strike Fighter F-35 will integrate helmet mounted displays (HMDs) with the avionics and weapon systems to the degree that the HMDs will become the aircraft's primary display system. In turn, training of pilot flight skills using HMDs will be essential in future training systems. In order to train these skills using simulation based training, improvements must be made in the integration of HMDs with out-thewindow (OTW) simulations. Currently, problems such as latency contribute to the onset of simulator sickness and provide distractions during training with HMD simulator systems that degrade the training experience. Previous research has used Kalman predictive filters as a means of mitigating the system latency present in these systems. While this approach has yielded some success, more work is needed to develop innovative and improved strategies that reduce system latency as well as to include data collected from the user perspective as a measured variable during test and evaluation of latency reduction strategies. The purpose of this paper is twofold. First, the paper describes a new method to measure and assess system latency from the user perspective. Second, the paper describes use of the testbed to examine the efficacy of an innovative strategy that combines a customized Kalman filter with a neural network approach to mitigate system latency. Results indicate that the combined approach reduced system latency significantly when compared to baseline data and the traditional Kalman filter. Reduced latency errors should mitigate the onset of simulator sickness and ease simulator sickness symptomology. Implications for training systems will be discussed.

Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks

PubMed Central

Jung, Sungmo; Kim, Jong Hyun; Kim, Seoksoo

2012-01-01

Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods. PMID:23202190

Modeling a Million-Node Slim Fly Network Using Parallel Discrete-Event Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolfe, Noah; Carothers, Christopher; Mubarak, Misbah

As supercomputers close in on exascale performance, the increased number of processors and processing power translates to an increased demand on the underlying network interconnect. The Slim Fly network topology, a new lowdiameter and low-latency interconnection network, is gaining interest as one possible solution for next-generation supercomputing interconnect systems. In this paper, we present a high-fidelity Slim Fly it-level model leveraging the Rensselaer Optimistic Simulation System (ROSS) and Co-Design of Exascale Storage (CODES) frameworks. We validate our Slim Fly model with the Kathareios et al. Slim Fly model results provided at moderately sized network scales. We further scale the modelmore » size up to n unprecedented 1 million compute nodes; and through visualization of network simulation metrics such as link bandwidth, packet latency, and port occupancy, we get an insight into the network behavior at the million-node scale. We also show linear strong scaling of the Slim Fly model on an Intel cluster achieving a peak event rate of 36 million events per second using 128 MPI tasks to process 7 billion events. Detailed analysis of the underlying discrete-event simulation performance shows that a million-node Slim Fly model simulation can execute in 198 seconds on the Intel cluster.« less

Probabilistic Neighborhood-Based Data Collection Algorithms for 3D Underwater Acoustic Sensor Networks.

PubMed

Han, Guangjie; Li, Shanshan; Zhu, Chunsheng; Jiang, Jinfang; Zhang, Wenbo

2017-02-08

Marine environmental monitoring provides crucial information and support for the exploitation, utilization, and protection of marine resources. With the rapid development of information technology, the development of three-dimensional underwater acoustic sensor networks (3D UASNs) provides a novel strategy to acquire marine environment information conveniently, efficiently and accurately. However, the specific propagation effects of acoustic communication channel lead to decreased successful information delivery probability with increased distance. Therefore, we investigate two probabilistic neighborhood-based data collection algorithms for 3D UASNs which are based on a probabilistic acoustic communication model instead of the traditional deterministic acoustic communication model. An autonomous underwater vehicle (AUV) is employed to traverse along the designed path to collect data from neighborhoods. For 3D UASNs without prior deployment knowledge, partitioning the network into grids can allow the AUV to visit the central location of each grid for data collection. For 3D UASNs in which the deployment knowledge is known in advance, the AUV only needs to visit several selected locations by constructing a minimum probabilistic neighborhood covering set to reduce data latency. Otherwise, by increasing the transmission rounds, our proposed algorithms can provide a tradeoff between data collection latency and information gain. These algorithms are compared with basic Nearest-neighbor Heuristic algorithm via simulations. Simulation analyses show that our proposed algorithms can efficiently reduce the average data collection completion time, corresponding to a decrease of data latency.

Graphics Processors in HEP Low-Level Trigger Systems

NASA Astrophysics Data System (ADS)

Ammendola, Roberto; Biagioni, Andrea; Chiozzi, Stefano; Cotta Ramusino, Angelo; Cretaro, Paolo; Di Lorenzo, Stefano; Fantechi, Riccardo; Fiorini, Massimiliano; Frezza, Ottorino; Lamanna, Gianluca; Lo Cicero, Francesca; Lonardo, Alessandro; Martinelli, Michele; Neri, Ilaria; Paolucci, Pier Stanislao; Pastorelli, Elena; Piandani, Roberto; Pontisso, Luca; Rossetti, Davide; Simula, Francesco; Sozzi, Marco; Vicini, Piero

2016-11-01

Usage of Graphics Processing Units (GPUs) in the so called general-purpose computing is emerging as an effective approach in several fields of science, although so far applications have been employing GPUs typically for offline computations. Taking into account the steady performance increase of GPU architectures in terms of computing power and I/O capacity, the real-time applications of these devices can thrive in high-energy physics data acquisition and trigger systems. We will examine the use of online parallel computing on GPUs for the synchronous low-level trigger, focusing on tests performed on the trigger system of the CERN NA62 experiment. To successfully integrate GPUs in such an online environment, latencies of all components need analysing, networking being the most critical. To keep it under control, we envisioned NaNet, an FPGA-based PCIe Network Interface Card (NIC) enabling GPUDirect connection. Furthermore, it is assessed how specific trigger algorithms can be parallelized and thus benefit from a GPU implementation, in terms of increased execution speed. Such improvements are particularly relevant for the foreseen Large Hadron Collider (LHC) luminosity upgrade where highly selective algorithms will be essential to maintain sustainable trigger rates with very high pileup.

The benefits of convergence.

PubMed

Chang, Gee-Kung; Cheng, Lin

2016-03-06

A multi-tier radio access network (RAN) combining the strength of fibre-optic and radio access technologies employing adaptive microwave photonics interfaces and radio-over-fibre (RoF) techniques is envisioned for future heterogeneous wireless communications. All-band radio spectrum from 0.1 to 100 GHz will be used to deliver wireless services with high capacity, high link speed and low latency. The multi-tier RAN will improve the cell-edge performance in an integrated heterogeneous environment enabled by fibre-wireless integration and networking for mobile fronthaul/backhaul, resource sharing and all-layer centralization of multiple standards with different frequency bands and modulation formats. In essence, this is a 'no-more-cells' architecture in which carrier aggregation among multiple frequency bands can be easily achieved with seamless handover between cells. In this way, current and future mobile network standards such as 4G and 5G can coexist with optimized and continuous cell coverage using multi-tier RoF regardless of the underlying network topology or protocol. In terms of users' experience, the future-proof approach achieves the goals of system capacity, link speed, latency and continuous heterogeneous cell coverage while overcoming the bandwidth crunch in next-generation communication networks. © 2016 The Author(s).

Interactions between neurons in the frontal cortex and hippocampus in cats trained to select reinforcements of different value in conditions of cholinergic deficiency.

PubMed

Dolbakyan, E E; Merzhanova, G Kh

2007-09-01

An operant food-related conditioned reflex was developed in six cats by the "active choice" protocol: short-latency pedal presses were followed by presentation of low-quality reinforcement (bread-meat mix), while long-latency pedal presses were followed by presentation of high-quality reinforcement (meat). Animals differed in terms of their food-procuring strategies, displaying "self-control," "ambivalence," or "impulsivity." Multineuron activity was recorded from the frontal cortex and hippocampus (field CA3). Cross-correlation analysis of interneuronal interactions within (local networks) and between (distributed networks) study structures showed that the numbers of interneuronal interactions in both local and distributed networks were maximal in animals with "self-control." On the background of systemic administration of the muscarinic cholinoreceptor blockers scopolamine and trihexyphenidyl, the numbers of interneuronal interactions decreased, while "common source" influences increased. This correlated with impairment of the reproduction of the selected strategy, primarily affecting the animals' self-controlled behavior. These results show that the "self-control" strategy is determined by the organization of local and distributed networks in the frontal cortex and hippocampus.

Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity

PubMed Central

Hull, Michael J.; Soffe, Stephen R.; Willshaw, David J.; Roberts, Alan

2016-01-01

What cellular and network properties allow reliable neuronal rhythm generation or firing that can be started and stopped by brief synaptic inputs? We investigate rhythmic activity in an electrically-coupled population of brainstem neurons driving swimming locomotion in young frog tadpoles, and how activity is switched on and off by brief sensory stimulation. We build a computational model of 30 electrically-coupled conditional pacemaker neurons on one side of the tadpole hindbrain and spinal cord. Based on experimental estimates for neuron properties, population sizes, synapse strengths and connections, we show that: long-lasting, mutual, glutamatergic excitation between the neurons allows the network to sustain rhythmic pacemaker firing at swimming frequencies following brief synaptic excitation; activity persists but rhythm breaks down without electrical coupling; NMDA voltage-dependency doubles the range of synaptic feedback strengths generating sustained rhythm. The network can be switched on and off at short latency by brief synaptic excitation and inhibition. We demonstrate that a population of generic Hodgkin-Huxley type neurons coupled by glutamatergic excitatory feedback can generate sustained asynchronous firing switched on and off synaptically. We conclude that networks of neurons with NMDAR mediated feedback excitation can generate self-sustained activity following brief synaptic excitation. The frequency of activity is limited by the kinetics of the neuron membrane channels and can be stopped by brief inhibitory input. Network activity can be rhythmic at lower frequencies if the neurons are electrically coupled. Our key finding is that excitatory synaptic feedback within a population of neurons can produce switchable, stable, sustained firing without synaptic inhibition. PMID:26824331

Low-rank network decomposition reveals structural characteristics of small-world networks

NASA Astrophysics Data System (ADS)

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

2015-12-01

Small-world networks occur naturally throughout biological, technological, and social systems. With their prevalence, it is particularly important to prudently identify small-world networks and further characterize their unique connection structure with respect to network function. In this work we develop a formalism for classifying networks and identifying small-world structure using a decomposition of network connectivity matrices into low-rank and sparse components, corresponding to connections within clusters of highly connected nodes and sparse interconnections between clusters, respectively. We show that the network decomposition is independent of node indexing and define associated bounded measures of connectivity structure, which provide insight into the clustering and regularity of network connections. While many existing network characterizations rely on constructing benchmark networks for comparison or fail to describe the structural properties of relatively densely connected networks, our classification relies only on the intrinsic network structure and is quite robust with respect to changes in connection density, producing stable results across network realizations. Using this framework, we analyze several real-world networks and reveal new structural properties, which are often indiscernible by previously established characterizations of network connectivity.

GAPR2: A DTN Routing Protocol for Communications in Challenged, Degraded, and Denied Environments

DTIC Science & Technology

2015-09-01

Transmission Speed Vs. Latency Figure 4.7: Helsinki Simulation Set 2, High Network Load and Small Buffers Analysis of Delivery Ratio in Helsinki Simulation...ipnsig.org/. [17] MANET routing, class notes for CS4554: Network modeling and analysis . 119 [18] S. Basagni et al. Mobile ad hoc networking . John...Wiley & Sons, 2004. [19] E. Royer et al. A review of current routing protocols for ad hoc mobile wireless networks . Personal Communications, IEEE, 6(2

Multi-layer service function chaining scheduling based on auxiliary graph in IP over optical network

NASA Astrophysics Data System (ADS)

Li, Yixuan; Li, Hui; Liu, Yuze; Ji, Yuefeng

2017-10-01

Software Defined Optical Network (SDON) can be considered as extension of Software Defined Network (SDN) in optical networks. SDON offers a unified control plane and makes optical network an intelligent transport network with dynamic flexibility and service adaptability. For this reason, a comprehensive optical transmission service, able to achieve service differentiation all the way down to the optical transport layer, can be provided to service function chaining (SFC). IP over optical network, as a promising networking architecture to interconnect data centers, is the most widely used scenarios of SFC. In this paper, we offer a flexible and dynamic resource allocation method for diverse SFC service requests in the IP over optical network. To do so, we firstly propose the concept of optical service function (OSF) and a multi-layer SFC model. OSF represents the comprehensive optical transmission service (e.g., multicast, low latency, quality of service, etc.), which can be achieved in multi-layer SFC model. OSF can also be considered as a special SF. Secondly, we design a resource allocation algorithm, which we call OSF-oriented optical service scheduling algorithm. It is able to address multi-layer SFC optical service scheduling and provide comprehensive optical transmission service, while meeting multiple optical transmission requirements (e.g., bandwidth, latency, availability). Moreover, the algorithm exploits the concept of Auxiliary Graph. Finally, we compare our algorithm with the Baseline algorithm in simulation. And simulation results show that our algorithm achieves superior performance than Baseline algorithm in low traffic load condition.

An Analysis of the Feasibility and Applicability of IEEE 802.x Wireless Mesh Networks within the Global Information Grid

DTIC Science & Technology

2004-09-01

MESH VS . SIMPLE AD HOC AND MANET..............................................5 B. DESIRABLE CHARACTERISTICS OF WIRELESS MESH NETWORKS...Comparison of Mesh (top) vs . Traditional Wireless (bottom) .............26 Figure 7. UML Model of SensorML Components (From SenorML Models Paper) ......30...50 Figure 17. Latency Difference Example – OLSR vs . AODV

Interaction of cellular and network mechanisms for efficient pheromone coding in moths.

PubMed

Belmabrouk, Hana; Nowotny, Thomas; Rospars, Jean-Pierre; Martinez, Dominique

2011-12-06

Sensory systems, both in the living and in machines, have to be optimized with respect to their environmental conditions. The pheromone subsystem of the olfactory system of moths is a particularly well-defined example in which rapid variations of odor content in turbulent plumes require fast, concentration-invariant neural representations. It is not clear how cellular and network mechanisms in the moth antennal lobe contribute to coding efficiency. Using computational modeling, we show that intrinsic potassium currents (I(A) and I(SK)) in projection neurons may combine with extrinsic inhibition from local interneurons to implement a dual latency code for both pheromone identity and intensity. The mean latency reflects stimulus intensity, whereas latency differences carry concentration-invariant information about stimulus identity. In accordance with physiological results, the projection neurons exhibit a multiphasic response of inhibition-excitation-inhibition. Together with synaptic inhibition, intrinsic currents I(A) and I(SK) account for the first and second inhibitory phases and contribute to a rapid encoding of pheromone information. The first inhibition plays the role of a reset to limit variability in the time to first spike. The second inhibition prevents responses of excessive duration to allow tracking of intermittent stimuli.

An Emergency Packet Forwarding Scheme for V2V Communication Networks

PubMed Central

2014-01-01

This paper proposes an effective warning message forwarding scheme for cooperative collision avoidance. In an emergency situation, an emergency-detecting vehicle warns the neighbor vehicles via an emergency warning message. Since the transmission range is limited, the warning message is broadcast in a multihop manner. Broadcast packets lead two challenges to forward the warning message in the vehicular network: redundancy of warning messages and competition with nonemergency transmissions. In this paper, we study and address the two major challenges to achieve low latency in delivery of the warning message. To reduce the intervehicle latency and end-to-end latency, which cause chain collisions, we propose a two-way intelligent broadcasting method with an adaptable distance-dependent backoff algorithm. Considering locations of vehicles, the proposed algorithm controls the broadcast of a warning message to reduce redundant EWM messages and adaptively chooses the contention window to compete with nonemergency transmission. Via simulations, we show that our proposed algorithm reduces the probability of rear-end crashes by 70% compared to previous algorithms by reducing the intervehicle delay. We also show that the end-to-end propagation delay of the warning message is reduced by 55%. PMID:25054181

Lateral Prefrontal Cortex Contributes to Fluid Intelligence Through Multinetwork Connectivity.

PubMed

Cole, Michael W; Ito, Takuya; Braver, Todd S

2015-10-01

Our ability to effectively adapt to novel circumstances--as measured by general fluid intelligence--has recently been tied to the global connectivity of lateral prefrontal cortex (LPFC). Global connectivity is a broad measure that summarizes both within-network connectivity and across-network connectivity. We used additional graph theoretical measures to better characterize the nature of LPFC connectivity and its relationship with fluid intelligence. We specifically hypothesized that LPFC is a connector hub with an across-network connectivity that contributes to fluid intelligence independent of within-network connectivity. We verified that LPFC was in the top 10% of brain regions in terms of across-network connectivity, suggesting it is a strong connector hub. Importantly, we found that the LPFC across-network connectivity predicted individuals' fluid intelligence and this correlation remained statistically significant when controlling for global connectivity (which includes within-network connectivity). This supports the conclusion that across-network connectivity independently contributes to the relationship between LPFC connectivity and intelligence. These results suggest that LPFC contributes to fluid intelligence by being a connector hub with a truly global multisystem connectivity throughout the brain.

Digital Video Over Space Systems and Networks

NASA Technical Reports Server (NTRS)

Grubbs, Rodney

2010-01-01

This slide presentation reviews the improvements and challenges that digital video provides over analog video. The use of digital video over IP options and trade offs, link integrity and latency are reviewed.

Dual Purpose Simulation: New Data Link Test and Performance Limit Testing of Currently Deployed Data Link

NASA Technical Reports Server (NTRS)

Robinson, Daryl C.

2002-01-01

While the results of this paper are similar to those of [I], in this paper technical difficulties present in [I] are eliminated, producing better results, enabling one to more readily see the benefits of Prioritized CSMA (PCSMA). A new analysis section also helps to generalize this research so that it is not limited to exploration of the new concept of PCSMA. Commercially available network simulation software, OPNET version 7.0, simulations are presented involving an important application of the Aeronautical Telecommunications Network (ATN), Controller Pilot Data Link Communications (CPDLC) over the Very High Frequency Data Link Mode 2 (VDL-2). Communication is modeled for essentially all incoming and outgoing nonstop air-traffic for just three United States cities: Cleveland, Cincinnati, and Detroit. The simulation involves 111 Air Traffic Control (ATC) ground stations, 32 airports distributed throughout the U.S., which are either sources or destinations for the air traffic landing or departing from the three cities, and also 1,235 equally equipped aircraft-taking off, flying realistic free-flight trajectories, and landing in a 24-hr period. Collision-less PCSMA is successfully tested and compared with the traditional CSMA typically associated with VDL-2. The performance measures include latency, throughput, and packet loss. As expected, PCSMA is much quicker and more efficient than traditional CSMA. These simulation results show the potency of PCSMA for implementing low latency, high throughput and efficient connectivity. Moreover, since PCSMA outperforms traditional CSMA, by simulating with it, we can determine the limits of performance beyond which traditional CSMA may not pass. So we have the tools to determine the traffic-loading conditions where traditional CSMA will fail, and we are testing a new and better data link that could replace it with relative ease. Work is currently being done to drastically expand the number of flights to make the simulation more representative of the National Aerospace System.

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

PubMed

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

2013-12-01

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

Cross stratum resources protection in fog-computing-based radio over fiber networks for 5G services

NASA Astrophysics Data System (ADS)

Guo, Shaoyong; Shao, Sujie; Wang, Yao; Yang, Hui

2017-09-01

In order to meet the requirement of internet of things (IoT) and 5G, the cloud radio access network is a paradigm which converges all base stations computational resources into a cloud baseband unit (BBU) pool, while the distributed radio frequency signals are collected by remote radio head (RRH). A precondition for centralized processing in the BBU pool is an interconnection fronthaul network with high capacity and low delay. However, it has become more complex and frequent in the interaction between RRH and BBU and resource scheduling among BBUs in cloud. Cloud radio over fiber network has been proposed in our previous work already. In order to overcome the complexity and latency, in this paper, we first present a novel cross stratum resources protection (CSRP) architecture in fog-computing-based radio over fiber networks (F-RoFN) for 5G services. Additionally, a cross stratum protection (CSP) scheme considering the network survivability is introduced in the proposed architecture. The CSRP with CSP scheme can effectively pull the remote processing resource locally to implement the cooperative radio resource management, enhance the responsiveness and resilience to the dynamic end-to-end 5G service demands, and globally optimize optical network, wireless and fog resources. The feasibility and efficiency of the proposed architecture with CSP scheme are verified on our software defined networking testbed in terms of service latency, transmission success rate, resource occupation rate and blocking probability.

Probabilistic Neighborhood-Based Data Collection Algorithms for 3D Underwater Acoustic Sensor Networks

PubMed Central

Han, Guangjie; Li, Shanshan; Zhu, Chunsheng; Jiang, Jinfang; Zhang, Wenbo

2017-01-01

Marine environmental monitoring provides crucial information and support for the exploitation, utilization, and protection of marine resources. With the rapid development of information technology, the development of three-dimensional underwater acoustic sensor networks (3D UASNs) provides a novel strategy to acquire marine environment information conveniently, efficiently and accurately. However, the specific propagation effects of acoustic communication channel lead to decreased successful information delivery probability with increased distance. Therefore, we investigate two probabilistic neighborhood-based data collection algorithms for 3D UASNs which are based on a probabilistic acoustic communication model instead of the traditional deterministic acoustic communication model. An autonomous underwater vehicle (AUV) is employed to traverse along the designed path to collect data from neighborhoods. For 3D UASNs without prior deployment knowledge, partitioning the network into grids can allow the AUV to visit the central location of each grid for data collection. For 3D UASNs in which the deployment knowledge is known in advance, the AUV only needs to visit several selected locations by constructing a minimum probabilistic neighborhood covering set to reduce data latency. Otherwise, by increasing the transmission rounds, our proposed algorithms can provide a tradeoff between data collection latency and information gain. These algorithms are compared with basic Nearest-neighbor Heuristic algorithm via simulations. Simulation analyses show that our proposed algorithms can efficiently reduce the average data collection completion time, corresponding to a decrease of data latency. PMID:28208735

Connecting Restricted, High-Availability, or Low-Latency Resources to a Seamless Global Pool for CMS

NASA Astrophysics Data System (ADS)

Balcas, J.; Bockelman, B.; Hufnagel, D.; Hurtado Anampa, K.; Jayatilaka, B.; Khan, F.; Larson, K.; Letts, J.; Mascheroni, M.; Mohapatra, A.; Marra Da Silva, J.; Mason, D.; Perez-Calero Yzquierdo, A.; Piperov, S.; Tiradani, A.; Verguilov, V.; CMS Collaboration

2017-10-01

The connection of diverse and sometimes non-Grid enabled resource types to the CMS Global Pool, which is based on HTCondor and glideinWMS, has been a major goal of CMS. These resources range in type from a high-availability, low latency facility at CERN for urgent calibration studies, called the CAF, to a local user facility at the Fermilab LPC, allocation-based computing resources at NERSC and SDSC, opportunistic resources provided through the Open Science Grid, commercial clouds, and others, as well as access to opportunistic cycles on the CMS High Level Trigger farm. In addition, we have provided the capability to give priority to local users of beyond WLCG pledged resources at CMS sites. Many of the solutions employed to bring these diverse resource types into the Global Pool have common elements, while some are very specific to a particular project. This paper details some of the strategies and solutions used to access these resources through the Global Pool in a seamless manner.

[Neuroeffector connections of multimodal neurons in the African snail (Achatina fulica)].

PubMed

Bugaĭ, V V; Zhuravlev, V L; Safonova, T A

2004-02-01

Using a new method of animal preparation, the efferent connections of giant paired neurons on the dorsal surface of visceral and right parietal ganglia of snail, Achatina fulica, were examined. It was found that spikes in giant neurons d-VLN and d-RPLN evoke postjunctional potentials in different points of the snail body and viscerae (in the heart, in pericardium, in lung cavity and kidney walls, in mantle and body wall muscles, in tentacle retractors and in cephalic artery). The preliminary analysis of synaptic latency and facilitation suggests a direct connections between giant neurons and investigated efferents.

Network connectivity value.

PubMed

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.

Silicon Nanophotonics for Many-Core On-Chip Networks

NASA Astrophysics Data System (ADS)

Mohamed, Moustafa

Number of cores in many-core architectures are scaling to unprecedented levels requiring ever increasing communication capacity. Traditionally, architects follow the path of higher throughput at the expense of latency. This trend has evolved into being problematic for performance in many-core architectures. Moreover, the trends of power consumption is increasing with system scaling mandating nontraditional solutions. Nanophotonics can address these problems, offering benefits in the three frontiers of many-core processor design: Latency, bandwidth, and power. Nanophotonics leverage circuit-switching flow control allowing low latency; in addition, the power consumption of optical links is significantly lower compared to their electrical counterparts at intermediate and long links. Finally, through wave division multiplexing, we can keep the high bandwidth trends without sacrificing the throughput. This thesis focuses on realizing nanophotonics for communication in many-core architectures at different design levels considering reliability challenges that our fabrication and measurements reveal. First, we study how to design on-chip networks for low latency, low power, and high bandwidth by exploiting the full potential of nanophotonics. The design process considers device level limitations and capabilities on one hand, and system level demands in terms of power and performance on the other hand. The design involves the choice of devices, designing the optical link, the topology, the arbitration technique, and the routing mechanism. Next, we address the problem of reliability in on-chip networks. Reliability not only degrades performance but can block communication. Hence, we propose a reliability-aware design flow and present a reliability management technique based on this flow to address reliability in the system. In the proposed flow reliability is modeled and analyzed for at the device, architecture, and system level. Our reliability management technique is superior to existing solutions in terms of power and performance. In fact, our solution can scale to thousand core with low overhead.

A Cross-Layer Duty Cycle MAC Protocol Supporting a Pipeline Feature for Wireless Sensor Networks

PubMed Central

Tong, Fei; Xie, Rong; Shu, Lei; Kim, Young-Chon

2011-01-01

Although the conventional duty cycle MAC protocols for Wireless Sensor Networks (WSNs) such as RMAC perform well in terms of saving energy and reducing end-to-end delivery latency, they were designed independently and require an extra routing protocol in the network layer to provide path information for the MAC layer. In this paper, we propose a new cross-layer duty cycle MAC protocol with data forwarding supporting a pipeline feature (P-MAC) for WSNs. P-MAC first divides the whole network into many grades around the sink. Each node identifies its grade according to its logical hop distance to the sink and simultaneously establishes a sleep/wakeup schedule using the grade information. Those nodes in the same grade keep the same schedule, which is staggered with the schedule of the nodes in the adjacent grade. Then a variation of the RTS/CTS handshake mechanism is used to forward data continuously in a pipeline fashion from the higher grade to the lower grade nodes and finally to the sink. No extra routing overhead is needed, thus increasing the network scalability while maintaining the superiority of duty-cycling. The simulation results in OPNET show that P-MAC has better performance than S-MAC and RMAC in terms of packet delivery latency and energy efficiency. PMID:22163895

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

PubMed

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.

TiD-Introducing and Benchmarking an Event-Delivery System for Brain-Computer Interfaces.

PubMed

Breitwieser, Christian; Tavella, Michele; Schreuder, Martijn; Cincotti, Febo; Leeb, Robert; Muller-Putz, Gernot R

2017-12-01

In this paper, we present and analyze an event distribution system for brain-computer interfaces. Events are commonly used to mark and describe incidents during an experiment and are therefore critical for later data analysis or immediate real-time processing. The presented approach, called Tools for brain-computer interaction interface D (TiD), delivers messages in XML format via a buslike system using transmission control protocol connections or shared memory. A dedicated server dispatches TiD messages to distributed or local clients. The TiD message is designed to be flexible and contains time stamps for event synchronization, whereas events describe incidents, which occur during an experiment. TiD was tested extensively toward stability and latency. The effect of an occurring event jitter was analyzed and benchmarked on a reference implementation under different conditions as gigabit and 100-Mb Ethernet or Wi-Fi with a different number of event receivers. A 3-dB signal attenuation, which occurs when averaging jitter influenced trials aligned by events, is starting to become visible at around 1-2 kHz in the case of a gigabit connection. Mean event distribution times across operating systems are ranging from 0.3 to 0.5ms for a gigabit network connection for 10 6 events. Results for other environmental conditions are available in this paper. References already using TiD for event distribution are provided showing the applicability of TiD for event delivery with distributed or local clients.

Synaptic activation patterns of the perirhinal-entorhinal inter-connections.

PubMed

de Villers-Sidani, E; Tahvildari, B; Alonso, A

2004-01-01

Ample neuropsychological evidence supports the role of rhinal cortices in memory. The perirhinal cortex (PRC) represents one of the main conduits for the bi-directional flow of information between the entorhinal-hippocampal network and the cortical mantle, a process essential in memory formation. However, despite anatomical evidence for a robust reciprocal connectivity between the perirhinal and entorhinal cortices, neurophysiological understanding of this circuitry is lacking. We now present the results of a series of electrophysiological experiments in rats that demonstrate robust synaptic activation patterns of the perirhinal-entorhinal inter-connections. First, using silicon multi-electrode arrays placed under visual guidance in vivo we performed current source density (CSD) analysis of lateral entorhinal cortex (LEC) responses to PRC stimulation, which demonstrated a current sink in layers II-III of the LEC with a latency consistent with monosynaptic activation. To further substantiate and extend this conclusion, we developed a PRC-LEC slice preparation where CSD analysis also revealed a current sink in superficial LEC layers in response to PRC stimulation. Importantly, intracellular recording of superficial LEC layer neurons confirmed that they receive a major monosynaptic excitatory input from the PRC. Finally, CSD analysis of the LEC to PRC projection in vivo also allowed us to document robust feedback synaptic activation of PRC neurons to deep LEC layer activation. We conclude that a clear bidirectional pattern of synaptic interactions exists between the PRC and LEC that would support a dynamic flow of information subserving memory function in the temporal lobe.

TTEthernet for Integrated Spacecraft Networks

NASA Technical Reports Server (NTRS)

Loveless, Andrew

2015-01-01

Aerospace projects have traditionally employed federated avionics architectures, in which each computer system is designed to perform one specific function (e.g. navigation). There are obvious downsides to this approach, including excessive weight (from so much computing hardware), and inefficient processor utilization (since modern processors are capable of performing multiple tasks). There has therefore been a push for integrated modular avionics (IMA), in which common computing platforms can be leveraged for different purposes. This consolidation of multiple vehicle functions to shared computing platforms can significantly reduce spacecraft cost, weight, and design complexity. However, the application of IMA principles introduces significant challenges, as the data network must accommodate traffic of mixed criticality and performance levels - potentially all related to the same shared computer hardware. Because individual network technologies are rarely so competent, the development of truly integrated network architectures often proves unreasonable. Several different types of networks are utilized - each suited to support a specific vehicle function. Critical functions are typically driven by precise timing loops, requiring networks with strict guarantees regarding message latency (i.e. determinism) and fault-tolerance. Alternatively, non-critical systems generally employ data networks prioritizing flexibility and high performance over reliable operation. Switched Ethernet has seen widespread success filling this role in terrestrial applications. Its high speed, flexibility, and the availability of inexpensive commercial off-the-shelf (COTS) components make it desirable for inclusion in spacecraft platforms. Basic Ethernet configurations have been incorporated into several preexisting aerospace projects, including both the Space Shuttle and International Space Station (ISS). However, classical switched Ethernet cannot provide the high level of network determinism required by real-time spacecraft applications. Even with modern advancements, the uncoordinated (i.e. event-driven) nature of Ethernet communication unavoidably leads to message contention within network switches. The arbitration process used to resolve such conflicts introduces variation in the time it takes for messages to be forwarded. TTEthernet1 introduces decentralized clock synchronization to switched Ethernet, enabling message transmission according to a time-triggered (TT) paradigm. A network planning tool is used to allocate each device a finite amount of time in which it may transmit a frame. Each time slot is repeated sequentially to form a periodic communication schedule that is then loaded onto each TTEthernet device (e.g. switches and end systems). Each network participant references the synchronized time in order to dispatch messages at predetermined instances. This schedule guarantees that no contention exists between time-triggered Ethernet frames in the network switches, therefore eliminating the need for arbitration (and the timing variation it causes). Besides time-triggered messaging, TTEthernet networks may provide two additional traffic classes to support communication of different criticality levels. In the rate-constrained (RC) traffic class, the frame payload size and rate of transmission along each communication channel are limited to predetermined maximums. The network switches can therefore be configured to accommodate the known worst-case traffic pattern, and buffer overflows can be eliminated. The best-effort (BE) traffic class behaves akin to classical Ethernet. No guarantees are provided regarding transmission latency or successful message delivery. TTEthernet coordinates transmission of all three traffic classes over the same physical connections, therefore accommodating the full spectrum of traffic criticality levels required in IMA architectures. Common computing platforms (e.g. LRUs) can share networking resources in such a way that failures in non-critical systems (using BE or RC communication modes) cannot impact flight-critical functions (using TT communication). Furthermore, TTEthernet hardware (e.g. switches, cabling) can be shared by both TTEthernet and classical Ethernet traffic.

Analysis of 2D Torus and Hub Topologies of 100Mb/s Ethernet for the Whitney Commodity Computing Testbed

NASA Technical Reports Server (NTRS)

Pedretti, Kevin T.; Fineberg, Samuel A.; Kutler, Paul (Technical Monitor)

1997-01-01

A variety of different network technologies and topologies are currently being evaluated as part of the Whitney Project. This paper reports on the implementation and performance of a Fast Ethernet network configured in a 4x4 2D torus topology in a testbed cluster of 'commodity' Pentium Pro PCs. Several benchmarks were used for performance evaluation: an MPI point to point message passing benchmark, an MPI collective communication benchmark, and the NAS Parallel Benchmarks version 2.2 (NPB2). Our results show that for point to point communication on an unloaded network, the hub and 1 hop routes on the torus have about the same bandwidth and latency. However, the bandwidth decreases and the latency increases on the torus for each additional route hop. Collective communication benchmarks show that the torus provides roughly four times more aggregate bandwidth and eight times faster MPI barrier synchronizations than a hub based network for 16 processor systems. Finally, the SOAPBOX benchmarks, which simulate real-world CFD applications, generally demonstrated substantially better performance on the torus than on the hub. In the few cases the hub was faster, the difference was negligible. In total, our experimental results lead to the conclusion that for Fast Ethernet networks, the torus topology has better performance and scales better than a hub based network.

Performance Analysis of Modified Accelerative Preallocation MAC Protocol for Passive Star-Coupled WDMA Networks

NASA Astrophysics Data System (ADS)

Yun, Changho; Kim, Kiseon

2006-04-01

For the passive star-coupled wavelength-division multiple-access (WDMA) network, a modified accelerative preallocation WDMA (MAP-WDMA) media access control (MAC) protocol is proposed, which is based on AP-WDMA. To show the advantages of MAP-WDMA as an adequate MAC protocol for the network over AP-WDMA, the channel utilization, the channel-access delay, and the latency of MAP-WDMA are investigated and compared with those of AP-WDMA under various data traffic patterns, including uniform, quasi-uniform type, disconnected type, mesh type, and ring type data traffics, as well as the assumption that a given number of network stations is equal to that of channels, in other words, without channel sharing. As a result, the channel utilization of MAP-WDMA can be competitive with respect to that of AP-WDMA at the expense of insignificantly higher latency. Namely, if the number of network stations is small, MAP-WDMA provides better channel utilization for uniform, quasi-uniform-type, and disconnected-type data traffics at all data traffic loads, as well as for mesh and ring-type data traffics at low data traffic loads. Otherwise, MAP-WDMA only outperforms AP-WDMA for the first three data traffics at higher data traffic loads. In the aspect of channel-access delay, MAP-WDMA gives better performance than AP-WDMA, regardless of data traffic patterns and the number of network stations.

Distinctive laterality of neural networks supporting action understanding in left- and right-handed individuals: An EEG coherence study.

PubMed

Kelly, Rachel; Mizelle, J C; Wheaton, Lewis A

2015-08-01

Prior work has demonstrated that perspective and handedness of observed actions can affect action understanding differently in right and left-handed persons, suggesting potential differences in the neural networks underlying action understanding between right and left-handed individuals. We sought to evaluate potential differences in these neural networks using electroencephalography (EEG). Right- and left-handed participants observed images of tool-use actions from egocentric and allocentric perspectives, with right- and left-handed actors performing the actions. Participants judged the outcome of the observed actions, and response accuracy and latency were recorded. Behaviorally, the highest accuracy and shortest latency was found in the egocentric perspective for right- and left-handed observers. Handedness of subject showed an effect on accuracy and latency also, where right-handed observers were faster to respond than left-handed observers, but on average were less accurate. Mu band (8-10 Hz) cortico-cortical coherence analysis indicated that right-handed observers have coherence in the motor dominant left parietal-premotor networks when looking at an egocentric right or allocentric left hands. When looking in an egocentric perspective at a left hand or allocentric right hand, coherence was lateralized to right parietal-premotor areas. In left-handed observers, bilateral parietal-premotor coherence patterns were observed regardless of actor handedness. These findings suggest that the cortical networks involved in understanding action outcomes are dependent on hand dominance, and notably right handed participants seem to utilize motor systems based on the limb seen performing the action. The decreased accuracy for right-handed participants on allocentric images could be due to asymmetrical lateralization of encoding action and motoric dominance, which may interfere with translating allocentric limb action outcomes. Further neurophysiological studies will determine the specific processes of how left- and right-handed participants understand actions. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Temporal Propagation of Intrinsic Brain Activity Associate With the Occurrence of PTSD.

PubMed

Weng, Yifei; Qi, Rongfeng; Chen, Feng; Ke, Jun; Xu, Qiang; Zhong, Yuan; Chen, Lida; Li, Jianjun; Zhang, Zhiqiang; Zhang, Li; Lu, Guangming

2018-01-01

The abnormal brain activity is a pivotal condition for the occurrence of posttraumatic stress disorder. However, the dynamic time features of intrinsic brain activities still remain unclearly in PTSD patients. Our study aims to perform the resting-state lag analysis (RS-LA) method to explore potential propagated patterns of intrinsic brain activities in PTSD patients. We recruited 27 drug-naive patients with PTSD, 33 trauma-exposed controls (TEC), and 30 demographically matched healthy controls (HC) in the final data statistics. Both RS-LA and conventional voxel-wise functional connectivity strength (FCS) methods were employed on the same dataset. Then, Spearman correlation analysis was conducted on time latency values of those abnormal brain regions with the clinical assessments. Compared with HC group, the time latency patterns of PTSD patients significantly shifted toward later in posterior cingulate cortex/precuneus, middle prefrontal cortex, right angular, and left pre- and post-central cortex. The TEC group tended to have similar time latency in right angular. Additionally, significant time latency in right STG was found in PTSD group relative to TEC group. Spearman correlation analysis revealed that the time latency value of mPFC negatively correlated to the PTSD checklist-civilian version scores (PCL_C) in PTSD group ( r = -0.578, P < 0.05). Furthermore, group differences map of FCS exhibited parts of overlapping areas with that of RS-LA, however, less specificity in detecting PTSD patients. In conclusion, apparent alterations of time latency were observed in DMN and primary sensorimotor areas of PTSD patients. These findings provide us with new evidence to explain the neural pathophysiology contributing to PTSD.

AIB-OR: improving onion routing circuit construction using anonymous identity-based cryptosystems.

PubMed

Wang, Changji; Shi, Dongyuan; Xu, Xilei

2015-01-01

The rapid growth of Internet applications has made communication anonymity an increasingly important or even indispensable security requirement. Onion routing has been employed as an infrastructure for anonymous communication over a public network, which provides anonymous connections that are strongly resistant to both eavesdropping and traffic analysis. However, existing onion routing protocols usually exhibit poor performance due to repeated encryption operations. In this paper, we first present an improved anonymous multi-receiver identity-based encryption (AMRIBE) scheme, and an improved identity-based one-way anonymous key agreement (IBOWAKE) protocol. We then propose an efficient onion routing protocol named AIB-OR that provides provable security and strong anonymity. Our main approach is to use our improved AMRIBE scheme and improved IBOWAKE protocol in onion routing circuit construction. Compared with other onion routing protocols, AIB-OR provides high efficiency, scalability, strong anonymity and fault tolerance. Performance measurements from a prototype implementation show that our proposed AIB-OR can achieve high bandwidths and low latencies when deployed over the Internet.

Smart TV-Smartphone Multiscreen Interactive Middleware for Public Displays.

PubMed

Martinez-Pabon, Francisco; Caicedo-Guerrero, Jaime; Ibarra-Samboni, Jhon Jairo; Ramirez-Gonzalez, Gustavo; Hernández-Leo, Davinia

2015-01-01

A new generation of public displays demands high interactive and multiscreen features to enrich people's experience in new pervasive environments. Traditionally, research on public display interaction has involved mobile devices as the main characters during the use of personal area network technologies such as Bluetooth or NFC. However, the emergent Smart TV model arises as an interesting alternative for the implementation of a new generation of public displays. This is due to its intrinsic connection capabilities with surrounding devices like smartphones or tablets. Nonetheless, the different approaches proposed by the most important vendors are still underdeveloped to support multiscreen and interaction capabilities for modern public displays, because most of them are intended for domestic environments. This research proposes multiscreen interactive middleware for public displays, which was developed from the principles of a loosely coupled interaction model, simplicity, stability, concurrency, low latency, and the usage of open standards and technologies. Moreover, a validation prototype is proposed in one of the most interesting public display scenarios: the advertising.

Remote telepresence surgery: the Canadian experience.

PubMed

Anvari, M

2007-04-01

On 28 February 2003, the world's first telerobotic surgical service was established between St. Joseph's Healthcare Hamilton, a teaching hospital affiliated with McMaster University, and North Bay General Hospital, a community hospital 400 km away. The service was designed to provide telerobotic surgery and assistance by expert surgeons to local surgeons in North Bay, and to improve the range and quality of advanced laparoscopic surgeries offered locally. The two surgeons have collaboratively performed 22 remote telepresence surgeries including laparoscopic fundoplications, laparoscopic colon resections, and laparoscopic inguinal hernia repairs. This article describes the important lessons learned, including the telecommunication requirements, the impact from lack of haptic feedback, surgeons' adaptation to latency, and ethical and medicolegal issues. This is currently the largest clinical experience with assisted robotic telepresence surgery (ARTS) in the world, and the lessons learned will help guide the future design and development of telesurgical robotic platforms. It also will guide the establishment of telesurgical networks connecting various centers in the world, allowing for rapid and safe dissemination of new surgical techniques.

AIB-OR: Improving Onion Routing Circuit Construction Using Anonymous Identity-Based Cryptosystems

PubMed Central

Wang, Changji; Shi, Dongyuan; Xu, Xilei

2015-01-01

The rapid growth of Internet applications has made communication anonymity an increasingly important or even indispensable security requirement. Onion routing has been employed as an infrastructure for anonymous communication over a public network, which provides anonymous connections that are strongly resistant to both eavesdropping and traffic analysis. However, existing onion routing protocols usually exhibit poor performance due to repeated encryption operations. In this paper, we first present an improved anonymous multi-receiver identity-based encryption (AMRIBE) scheme, and an improved identity-based one-way anonymous key agreement (IBOWAKE) protocol. We then propose an efficient onion routing protocol named AIB-OR that provides provable security and strong anonymity. Our main approach is to use our improved AMRIBE scheme and improved IBOWAKE protocol in onion routing circuit construction. Compared with other onion routing protocols, AIB-OR provides high efficiency, scalability, strong anonymity and fault tolerance. Performance measurements from a prototype implementation show that our proposed AIB-OR can achieve high bandwidths and low latencies when deployed over the Internet. PMID:25815879

Smart TV-Smartphone Multiscreen Interactive Middleware for Public Displays

PubMed Central

Martinez-Pabon, Francisco; Caicedo-Guerrero, Jaime; Ibarra-Samboni, Jhon Jairo; Ramirez-Gonzalez, Gustavo; Hernández-Leo, Davinia

2015-01-01

A new generation of public displays demands high interactive and multiscreen features to enrich people's experience in new pervasive environments. Traditionally, research on public display interaction has involved mobile devices as the main characters during the use of personal area network technologies such as Bluetooth or NFC. However, the emergent Smart TV model arises as an interesting alternative for the implementation of a new generation of public displays. This is due to its intrinsic connection capabilities with surrounding devices like smartphones or tablets. Nonetheless, the different approaches proposed by the most important vendors are still underdeveloped to support multiscreen and interaction capabilities for modern public displays, because most of them are intended for domestic environments. This research proposes multiscreen interactive middleware for public displays, which was developed from the principles of a loosely coupled interaction model, simplicity, stability, concurrency, low latency, and the usage of open standards and technologies. Moreover, a validation prototype is proposed in one of the most interesting public display scenarios: the advertising. PMID:25950018

Neuronal correlates of a virtual-reality-based passive sensory P300 network.

PubMed

Chen, Chun-Chuan; Syue, Kai-Syun; Li, Kai-Chiun; Yeh, Shih-Ching

2014-01-01

P300, a positive event-related potential (ERP) evoked at around 300 ms after stimulus, can be elicited using an active or passive oddball paradigm. Active P300 requires a person's intentional response, whereas passive P300 does not require an intentional response. Passive P300 has been used in incommunicative patients for consciousness detection and brain computer interface. Active and passive P300 differ in amplitude, but not in latency or scalp distribution. However, no study has addressed the mechanism underlying the production of passive P300. In particular, it remains unclear whether the passive P300 shares an identical active P300 generating network architecture when no response is required. This study aims to explore the hierarchical network of passive sensory P300 production using dynamic causal modelling (DCM) for ERP and a novel virtual reality (VR)-based passive oddball paradigm. Moreover, we investigated the causal relationship of this passive P300 network and the changes in connection strength to address the possible functional roles. A classical ERP analysis was performed to verify that the proposed VR-based game can reliably elicit passive P300. The DCM results suggested that the passive and active P300 share the same parietal-frontal neural network for attentional control and, underlying the passive network, the feed-forward modulation is stronger than the feed-back one. The functional role of this forward modulation may indicate the delivery of sensory information, automatic detection of differences, and stimulus-driven attentional processes involved in performing this passive task. To our best knowledge, this is the first study to address the passive P300 network. The results of this study may provide a reference for future clinical studies on addressing the network alternations under pathological states of incommunicative patients. However, caution is required when comparing patients' analytic results with this study. For example, the task presented here is not applicable to incommunicative patients.

Neuronal Correlates of a Virtual-Reality-Based Passive Sensory P300 Network

PubMed Central

Chen, Chun-Chuan; Syue, Kai-Syun; Li, Kai-Chiun; Yeh, Shih-Ching

2014-01-01

P300, a positive event-related potential (ERP) evoked at around 300 ms after stimulus, can be elicited using an active or passive oddball paradigm. Active P300 requires a person’s intentional response, whereas passive P300 does not require an intentional response. Passive P300 has been used in incommunicative patients for consciousness detection and brain computer interface. Active and passive P300 differ in amplitude, but not in latency or scalp distribution. However, no study has addressed the mechanism underlying the production of passive P300. In particular, it remains unclear whether the passive P300 shares an identical active P300 generating network architecture when no response is required. This study aims to explore the hierarchical network of passive sensory P300 production using dynamic causal modelling (DCM) for ERP and a novel virtual reality (VR)-based passive oddball paradigm. Moreover, we investigated the causal relationship of this passive P300 network and the changes in connection strength to address the possible functional roles. A classical ERP analysis was performed to verify that the proposed VR-based game can reliably elicit passive P300. The DCM results suggested that the passive and active P300 share the same parietal-frontal neural network for attentional control and, underlying the passive network, the feed-forward modulation is stronger than the feed-back one. The functional role of this forward modulation may indicate the delivery of sensory information, automatic detection of differences, and stimulus-driven attentional processes involved in performing this passive task. To our best knowledge, this is the first study to address the passive P300 network. The results of this study may provide a reference for future clinical studies on addressing the network alternations under pathological states of incommunicative patients. However, caution is required when comparing patients’ analytic results with this study. For example, the task presented here is not applicable to incommunicative patients. PMID:25401520

Neural activation patterns and connectivity in visual attention during Number and Non-number processing: An ERP study using the Ishihara pseudoisochromatic plates.

PubMed

Al-Marri, Faraj; Reza, Faruque; Begum, Tahamina; Hitam, Wan Hazabbah Wan; Jin, Goh Khean; Xiang, Jing

2017-10-25

Visual cognitive function is important to build up executive function in daily life. Perception of visual Number form (e.g., Arabic digit) and numerosity (magnitude of the Number) is of interest to cognitive neuroscientists. Neural correlates and the functional measurement of Number representations are complex occurrences when their semantic categories are assimilated with other concepts of shape and colour. Colour perception can be processed further to modulate visual cognition. The Ishihara pseudoisochromatic plates are one of the best and most common screening tools for basic red-green colour vision testing. However, there is a lack of study of visual cognitive function assessment using these pseudoisochromatic plates. We recruited 25 healthy normal trichromat volunteers and extended these studies using a 128-sensor net to record event-related EEG. Subjects were asked to respond by pressing Numbered buttons when they saw the Number and Non-number plates of the Ishihara colour vision test. Amplitudes and latencies of N100 and P300 event related potential (ERP) components were analysed from 19 electrode sites in the international 10-20 system. A brain topographic map, cortical activation patterns and Granger causation (effective connectivity) were analysed from 128 electrode sites. No major significant differences between N100 ERP components in either stimulus indicate early selective attention processing was similar for Number and Non-number plate stimuli, but Non-number plate stimuli evoked significantly higher amplitudes, longer latencies of the P300 ERP component with a slower reaction time compared to Number plate stimuli imply the allocation of attentional load was more in Non-number plate processing. A different pattern of asymmetric scalp voltage map was noticed for P300 components with a higher intensity in the left hemisphere for Number plate tasks and higher intensity in the right hemisphere for Non-number plate tasks. Asymmetric cortical activation and connectivity patterns revealed that Number recognition occurred in the occipital and left frontal areas where as the consequence was limited to the occipital area during the Non-number plate processing. Finally, the results displayed that the visual recognition of Numbers dissociates from the recognition of Non-numbers at the level of defined neural networks. Number recognition was not only a process of visual perception and attention, but it was also related to a higher level of cognitive function, that of language.

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

NASA Astrophysics Data System (ADS)

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.

Small Worldness in Dense and Weighted Connectomes

NASA Astrophysics Data System (ADS)

Colon-Perez, Luis; Couret, Michelle; Triplett, William; Price, Catherine; Mareci, Thomas

2016-05-01

The human brain is a heterogeneous network of connected functional regions; however, most brain network studies assume that all brain connections can be described in a framework of binary connections. The brain is a complex structure of white matter tracts connected by a wide range of tract sizes, which suggests a broad range of connection strengths. Therefore, the assumption that the connections are binary yields an incomplete picture of the brain. Various thresholding methods have been used to remove spurious connections and reduce the graph density in binary networks. But these thresholds are arbitrary and make problematic the comparison of networks created at different thresholds. The heterogeneity of connection strengths can be represented in graph theory by applying weights to the network edges. Using our recently introduced edge weight parameter, we estimated the topological brain network organization using a complimentary weighted connectivity framework to the traditional framework of a binary network. To examine the reproducibility of brain networks in a controlled condition, we studied the topological network organization of a single healthy individual by acquiring 10 repeated diffusion-weighted magnetic resonance image datasets, over a one-month period on the same scanner, and analyzing these networks with deterministic tractography. We applied a threshold to both the binary and weighted networks and determined that the extra degree of freedom that comes with the framework of weighting network connectivity provides a robust result as any threshold level. The proposed weighted connectivity framework provides a stable result and is able to demonstrate the small world property of brain networks in situations where the binary framework is inadequate and unable to demonstrate this network property.

Resting-State Functional Connectivity in Individuals with Down Syndrome and Williams Syndrome Compared with Typically Developing Controls.

PubMed

Vega, Jennifer N; Hohman, Timothy J; Pryweller, Jennifer R; Dykens, Elisabeth M; Thornton-Wells, Tricia A

2015-10-01

The emergence of resting-state functional connectivity (rsFC) analysis, which examines temporal correlations of low-frequency (<0.1 Hz) blood oxygen level-dependent signal fluctuations between brain regions, has dramatically improved our understanding of the functional architecture of the typically developing (TD) human brain. This study examined rsFC in Down syndrome (DS) compared with another neurodevelopmental disorder, Williams syndrome (WS), and TD. Ten subjects with DS, 18 subjects with WS, and 40 subjects with TD each participated in a 3-Tesla MRI scan. We tested for group differences (DS vs. TD, DS vs. WS, and WS vs. TD) in between- and within-network rsFC connectivity for seven functional networks. For the DS group, we also examined associations between rsFC and other cognitive and genetic risk factors. In DS compared with TD, we observed higher levels of between-network connectivity in 6 out 21 network pairs but no differences in within-network connectivity. Participants with WS showed lower levels of within-network connectivity and no significant differences in between-network connectivity relative to DS. Finally, our comparison between WS and TD controls revealed lower within-network connectivity in multiple networks and higher between-network connectivity in one network pair relative to TD controls. While preliminary due to modest sample sizes, our findings suggest a global difference in between-network connectivity in individuals with neurodevelopmental disorders compared with controls and that such a difference is exacerbated across many brain regions in DS. However, this alteration in DS does not appear to extend to within-network connections, and therefore, the altered between-network connectivity must be interpreted within the framework of an intact intra-network pattern of activity. In contrast, WS shows markedly lower levels of within-network connectivity in the default mode network and somatomotor network relative to controls. These findings warrant further investigation using a task-based procedure that may help disentangle the relationship between brain function and cognitive performance across the spectrum of neurodevelopmental disorders.

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

PubMed

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.

Constellation Program Electrical Ground Support Equipment Research and Development

NASA Technical Reports Server (NTRS)

McCoy, Keegan S.

2010-01-01

At the Kennedy Space Center, I engaged in the research and development of electrical ground support equipment for NASA's Constellation Program. Timing characteristics playa crucial role in ground support communications. Latency and jitter are two problems that must be understood so that communications are timely and consistent within the Kennedy Ground Control System (KGCS). I conducted latency and jitter tests using Alien-Bradley programmable logic controllers (PLCs) so that these two intrinsic network properties can be reduced. Time stamping and clock synchronization also play significant roles in launch processing and operations. Using RSLogix 5000 project files and Wireshark network protocol analyzing software, I verified master/slave PLC Ethernet module clock synchronization, master/slave IEEE 1588 communications, and time stamping capabilities. All of the timing and synchronization test results are useful in assessing the current KGCS operational level and determining improvements for the future.

Social network models predict movement and connectivity in ecological landscapes

USGS Publications Warehouse

Fletcher, R.J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, W.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.

Acquisition de donnees a haute resolution et faible latence dediee aux capteurs avioniques de position

NASA Astrophysics Data System (ADS)

Koubaa, Zied

The communication network and the detection mechanisms are two critical systems in a plane. Their performance has a direct impact on aircrafts. This is of particular interest for avionics designers, who have increasingly invested more and more in the development of these elements. As a part of a project in this domain, we introduce the design and the development of a smart interface for position sensors dedicated to flights (Smart Sensor Interface - SSI). This interface will serve to connect sensors of different technologies (electromagnetic, optical and MEMS) to the new communication network, AFDX. The role of this interface is to generate an appropriate excitation signal for certain types of sensors (R/LVDT), and to treat, demodulate, and digitize their output signals. The proposed interface is thus composed of a Signal Acquisition Path (SAP) and an Excitation Signal Generation (ESG). By adopting the Integrated Modular Avionics architecture (IMA), we can minimize the size of the classic interface, reduce its energy consumption and improve its reliability and its performance. The focus of our design is particularly on the Data Acquisition Path (DAP). An Architecture characterized by a high resolution (14 bits) and a low latency (1.2 ms) of this module is introduced and developed in this prestigious work. This architecture was developed after a wellconducted study of existing solutions found in literature work and a detailed analysis of the problems arise in the design and implementation of this system (DAP). The conversion of the sensor signal into a digital signal is the most important step in acquiring data, as it sets the resolution of the acquired information and generates the majority of its latency. This module can also affect the reliability and stability of the system. Among different models and architectures, the Delta-Sigma analog-to-digital converter (ADC) is preferred for this application (for better resolution). This converter is formed by an analog circuit (modulator) followed by digital filters. The complexity of the implementation, the processing delay and the output resolution are all susceptible to change depending on the architecture of these filters. Thus, the main problem while designing such a system arises in the opposing evolution of the resolution and latency parameters; the improvement or evolution of one, results in the destruction of the other. Therefore, our work aims to provide one or more method to optimize the latency caused by the CAN while maintaining the same resolution of the desired data (14 bits). This optimization takes into account the objective of integrating the DAP in modules of small size and low power consumption. This proposed solution was implemented in order to validate the design of the conception of the interface. We are also interested to achieve the proposed solution and validate our design. The obtained results will be evaluated after following the manufacturing strategy. The data acquisition unit is made up of two electronic components. The first component is an integrated circuit, which uses CMOS 0.13mum IBM technology and contains the analog part of CAN (SigmaDelta modulator). The second component is a Virtex-6 FPGA, which allows one to acquire the necessary digital processing required for the acquisition and conversion of the sensor signal. In the final version of the interface, our analog portion will be integrated with the analog portion of GSE in the same chip. The integrated digital logic in the (FPGA) role will thus provide digital data to the ESG module in order to generate the excitation signal.

SVANET: A smart vehicular ad hoc network for efficient data transmission with wireless sensors.

PubMed

Sahoo, Prasan Kumar; Chiang, Ming-Jer; Wu, Shih-Lin

2014-11-25

Wireless sensors can sense any event, such as accidents, as well as icy roads, and can forward the rescue/warning messages through intermediate vehicles for any necessary help. In this paper, we propose a smart vehicular ad hoc network (SVANET) architecture that uses wireless sensors to detect events and vehicles to transmit the safety and non-safety messages efficiently by using different service channels and one control channel with different priorities. We have developed a data transmission protocol for the vehicles in the highway, in which data can be forwarded with the help of vehicles if they are connected with each other or data can be forwarded with the help of nearby wireless sensors. Our data transmission protocol is designed to increase the driving safety, to prevent accidents and to utilize channels efficiently by adjusting the control and service channel time intervals dynamically. Besides, our protocol can transmit information to vehicles in advance, so that drivers can decide an alternate route in case of traffic congestion. For various data sharing, we design a method that can select a few leader nodes among vehicles running along a highway to broadcast data efficiently. Simulation results show that our protocol can outperform the existing standard in terms of the end to end packet delivery ratio and latency.

SVANET: A Smart Vehicular Ad Hoc Network for Efficient Data Transmission with Wireless Sensors

PubMed Central

Sahoo, Prasan Kumar; Chiang, Ming-Jer; Wu, Shih-Lin

2014-01-01

Wireless sensors can sense any event, such as accidents, as well as icy roads, and can forward the rescue/warning messages through intermediate vehicles for any necessary help. In this paper, we propose a smart vehicular ad hoc network (SVANET) architecture that uses wireless sensors to detect events and vehicles to transmit the safety and non-safety messages efficiently by using different service channels and one control channel with different priorities. We have developed a data transmission protocol for the vehicles in the highway, in which data can be forwarded with the help of vehicles if they are connected with each other or data can be forwarded with the help of nearby wireless sensors. Our data transmission protocol is designed to increase the driving safety, to prevent accidents and to utilize channels efficiently by adjusting the control and service channel time intervals dynamically. Besides, our protocol can transmit information to vehicles in advance, so that drivers can decide an alternate route in case of traffic congestion. For various data sharing, we design a method that can select a few leader nodes among vehicles running along a highway to broadcast data efficiently. Simulation results show that our protocol can outperform the existing standard in terms of the end to end packet delivery ratio and latency. PMID:25429409

Reconfigurable PCI Express cards for low-latency data transport in HEP experiments

NASA Astrophysics Data System (ADS)

Ammendola, R.; Biagioni, A.; Cretaro, P.; Frezza, O.; Lamanna, G.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Paolucci, P. S.; Pastorelli, E.; Pontisso, L.; Simula, F.; Vicini, P.

2017-01-01

State-of-the-art technology supports the High Energy Physics community in addressing the problem of managing an overwhelming amount of experimental data. From the point of view of communication between the detectors' readout system and computing nodes, the critical issues are the following: latency, moving data in a deterministic and low amount of time; bandwidth, guaranteeing the maximum capability of the link and communication protocol adopted; endpoint consolidation, tight aggregation of channels on a single board. This contribution describes the status and performances of the NaNet project, whose goal is the design of a family of FPGA-based PCIe network interface cards. The efforts of the team are focused on implementing a low-latency, real-time data transport mechanism between the board network multi-channel system and CPU and GPU accelerators memories on the host. Several opportunities concerning technical solutions and scientific applications have been explored: NaNet-1 with a single GbE I/O interface, and NaNet-10, offering four 10GbE ports, for activities related to the GPU-based real-time trigger of NA62 experiment at CERN; NaNet ^3 , with four 2.5Gbit optical channels, developed for the KM3NeT-ITALIA underwater neutrino telescope.

Effects of structured nontarget stimuli on saccadic latency.

PubMed

White, Brian J; Gegenfurtner, Karl R; Kerzel, Dirk

2005-06-01

It has been suggested that the remote distractor effect is the result of nontarget stimulation of a central region representing a collicular fixation zone near the time of target onset. The distributed network of the cells responsible for this effect is believed to extend over a large area, responding to distractors < or =10 deg in the periphery. Several studies also implicate the superior colliculus as the substrate behind an inhibited saccadic response arising from a display change. We investigated this further by using a patch of pink noise of various sizes as a nontarget stimulus. We show that the onset of a small patch (2.3 x 2.3 deg) of centrally displayed pink noise can produce a significant increase in saccadic latency to a simultaneously presented peripheral Gabor target. In contrast, a large patch (36 x 36 deg) of pink noise did not increase latency despite the fact that it also stimulated the region representing the fixation zone. Furthermore, only the large patch of noise facilitated latency when presented before target onset. We also examined the effect of patch sizes between these two extremes and found a steady decrease in latency as patch size increased. This confirms that nontarget stimulation of the region representing the fixation zone near the time of target onset is not in itself sufficient to produce the increase in latency typically found with remote distractors. The results are consistent with the idea that only a spatially confined object leads to a discharge of collicular fixation neurons.

Age differences in the functional interactions among the default, frontoparietal control, and dorsal attention networks.

PubMed

Grady, Cheryl; Sarraf, Saman; Saverino, Cristina; Campbell, Karen

2016-05-01

Older adults typically show weaker functional connectivity (FC) within brain networks compared with young adults, but stronger functional connections between networks. Our primary aim here was to use a graph theoretical approach to identify age differences in the FC of 3 networks-default mode network (DMN), dorsal attention network, and frontoparietal control (FPC)-during rest and task conditions and test the hypothesis that age differences in the FPC would influence age differences in the other networks, consistent with its role as a cognitive "switch." At rest, older adults showed lower clustering values compared with the young, and both groups showed more between-network connections involving the FPC than the other 2 networks, but this difference was greater in the older adults. Connectivity within the DMN was reduced in older compared with younger adults. Consistent with our hypothesis, between-network connections of the FPC at rest predicted the age-related reduction in connectivity within the DMN. There was no age difference in within-network FC during the task (after removing the specific task effect), but between-network connections were greater in older adults than in young adults for the FPC and dorsal attention network. In addition, age reductions were found in almost all the graph metrics during the task condition, including clustering and modularity. Finally, age differences in between-network connectivity of the FPC during both rest and task predicted cognitive performance. These findings provide additional evidence of less within-network but greater between-network FC in older adults during rest but also show that these age differences can be altered by the residual influence of task demands on background connectivity. Our results also support a role for the FPC as the regulator of other brain networks in the service of cognition. Critically, the link between age differences in inter-network connections of the FPC and DMN connectivity, and the link between FPC connectivity and performance, support the hypothesis that FC of the FPC influences the expression of age differences in other networks, as well as differences in cognitive function. Copyright © 2016 Elsevier Inc. All rights reserved.

Electronic Sleep Stage Classifiers: A Survey and VLSI Design Methodology.

PubMed

Kassiri, Hossein; Chemparathy, Aditi; Salam, M Tariqus; Boyce, Richard; Adamantidis, Antoine; Genov, Roman

2017-02-01

First, existing sleep stage classifier sensors and algorithms are reviewed and compared in terms of classification accuracy, level of automation, implementation complexity, invasiveness, and targeted application. Next, the implementation of a miniature microsystem for low-latency automatic sleep stage classification in rodents is presented. The classification algorithm uses one EMG (electromyogram) and two EEG (electroencephalogram) signals as inputs in order to detect REM (rapid eye movement) sleep, and is optimized for low complexity and low power consumption. It is implemented in an on-board low-power FPGA connected to a multi-channel neural recording IC, to achieve low-latency (order of 1 ms or less) classification. Off-line experimental results using pre-recorded signals from nine mice show REM detection sensitivity and specificity of 81.69% and 93.86%, respectively, with the maximum latency of 39 [Formula: see text]. The device is designed to be used in a non-disruptive closed-loop REM sleep suppression microsystem, for future studies of the effects of REM sleep deprivation on memory consolidation.

Network Sampling and Classification:An Investigation of Network Model Representations

PubMed Central

Airoldi, Edoardo M.; Bai, Xue; Carley, Kathleen M.

2011-01-01

Methods for generating a random sample of networks with desired properties are important tools for the analysis of social, biological, and information networks. Algorithm-based approaches to sampling networks have received a great deal of attention in recent literature. Most of these algorithms are based on simple intuitions that associate the full features of connectivity patterns with specific values of only one or two network metrics. Substantive conclusions are crucially dependent on this association holding true. However, the extent to which this simple intuition holds true is not yet known. In this paper, we examine the association between the connectivity patterns that a network sampling algorithm aims to generate and the connectivity patterns of the generated networks, measured by an existing set of popular network metrics. We find that different network sampling algorithms can yield networks with similar connectivity patterns. We also find that the alternative algorithms for the same connectivity pattern can yield networks with different connectivity patterns. We argue that conclusions based on simulated network studies must focus on the full features of the connectivity patterns of a network instead of on the limited set of network metrics for a specific network type. This fact has important implications for network data analysis: for instance, implications related to the way significance is currently assessed. PMID:21666773

A Novel Characterization of Amalgamated Networks in Natural Systems

PubMed Central

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

2015-01-01

Densely-connected networks are prominent among natural systems, exhibiting structural characteristics often optimized for biological function. To reveal such features in highly-connected networks, we introduce a new network characterization determined by a decomposition of network-connectivity into low-rank and sparse components. Based on these components, we discover a new class of networks we define as amalgamated networks, which exhibit large functional groups and dense connectivity. Analyzing recent experimental findings on cerebral cortex, food-web, and gene regulatory networks, we establish the unique importance of amalgamated networks in fostering biologically advantageous properties, including rapid communication among nodes, structural stability under attacks, and separation of network activity into distinct functional modules. We further observe that our network characterization is scalable with network size and connectivity, thereby identifying robust features significant to diverse physical systems, which are typically undetectable by conventional characterizations of connectivity. We expect that studying the amalgamation properties of biological networks may offer new insights into understanding their structure-function relationships. PMID:26035066

Functional communication within a perceptual network processing letters and pseudoletters.

PubMed

Herdman, Anthony T

2011-10-01

Many studies have identified regions within human ventral visual stream to be important for object identification and categorization; however, knowledge of how perceptual information is communicated within the visual network is still limited. Current theories posit that if a high correspondence between incoming sensory information and internal representations exists, then the object is rapidly identified, and if there is not, then the object requires extra detailed processing. Event-related responses from the present magnetoencephalography study showed two main effects. The N1m peak latencies were approximately 15 milliseconds earlier to familiar letters than to unfamiliar pseudoletters, and the N2m was more negative to pseudoletters than to letters. Event-related beamforming analyses identified these effects to be within bilateral visual cortices with a right lateralization for the N2m effect. Furthermore, functional connectivity analyses revealed that gamma-band (50-80 Hz) oscillatory phase synchronizations among occipital regions were greater to letters than to pseudoletters (around 85 milliseconds). However, during a later time interval between 245 and 375 milliseconds, pseudoletters elicited greater gamma-band phase synchronizations among a more distributed occipital network than did letters. These findings indicate that familiar object processing begins by at least 85 milliseconds, which could represent an initial match to an internal template. In addition, unfamiliar object processing persisted longer than that for familiar objects, which could reflect greater attention to inexperienced objects to determine their identity and/or to consolidate a new template to aid in future identification.

Decreased functional connectivity to posterior cingulate cortex in major depressive disorder.

PubMed

Yang, Rui; Gao, Chengge; Wu, Xiaoping; Yang, Junle; Li, Shengbin; Cheng, Hu

2016-09-30

The default mode network (DMN) and its interaction with other key networks such as the salience network and executive network are keys to understand psychiatric and neurological disorders including major depressive disorder (MDD). In this study, we combined independent component analysis and seed based connectivity analysis to study the posterior default mode network between 20 patients with MDD and 25 normal controls, as well as pre-treatment and post-treatment conditions of the patients. Both correlated and anti-correlated networks centered at the posterior cingulate cortex (PCC) were examined (PCC+ and PCC-). Our results showed aberrant functional connectivity of the PCC+ and PCC- networks between patients and normal controls. Specifically, normal controls exhibited significantly higher connectivity between the PCC and frontal/temporal regions for the PCC+ network and stronger connectivity strength between the PCC and the insula/middle frontal cortex for the PCC- network. The overall connectivity strength of the PCC+ and PCC- networks was also significantly lower in MDD. Because the PCC is a hub in the DMN that interacts with other networks, our result suggested a stronger interaction between the DMN and the salience network but a weak interaction between the DMN and the executive network in MDD. The treatment using sertraline did increase the functional connectivity strength, especially in the PCC+ network. Despite a large inter-subject variability in the overall connectivity strengths and change of the PCC network in response to the treatment, a high correlation between change of connectivity strength and the Hamilton depression score was observed for both the PCC+ and PCC- network. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Towards Optimal Connectivity on Multi-layered Networks.

PubMed

Chen, Chen; He, Jingrui; Bliss, Nadya; Tong, Hanghang

2017-10-01

Networks are prevalent in many high impact domains. Moreover, cross-domain interactions are frequently observed in many applications, which naturally form the dependencies between different networks. Such kind of highly coupled network systems are referred to as multi-layered networks , and have been used to characterize various complex systems, including critical infrastructure networks, cyber-physical systems, collaboration platforms, biological systems and many more. Different from single-layered networks where the functionality of their nodes is mainly affected by within-layer connections, multi-layered networks are more vulnerable to disturbance as the impact can be amplified through cross-layer dependencies, leading to the cascade failure to the entire system. To manipulate the connectivity in multi-layered networks, some recent methods have been proposed based on two-layered networks with specific types of connectivity measures. In this paper, we address the above challenges in multiple dimensions. First, we propose a family of connectivity measures (SUBLINE) that unifies a wide range of classic network connectivity measures. Third, we reveal that the connectivity measures in SUBLINE family enjoy diminishing returns property , which guarantees a near-optimal solution with linear complexity for the connectivity optimization problem. Finally, we evaluate our proposed algorithm on real data sets to demonstrate its effectiveness and efficiency.

Integrated Circuit Chip Improves Network Efficiency

NASA Technical Reports Server (NTRS)

2008-01-01

Prior to 1999 and the development of SpaceWire, a standard for high-speed links for computer networks managed by the European Space Agency (ESA), there was no high-speed communications protocol for flight electronics. Onboard computers, processing units, and other electronics had to be designed for individual projects and then redesigned for subsequent projects, which increased development periods, costs, and risks. After adopting the SpaceWire protocol in 2000, NASA implemented the standard on the Swift mission, a gamma ray burst-alert telescope launched in November 2004. Scientists and developers on the James Webb Space Telescope further developed the network version of SpaceWire. In essence, SpaceWire enables more science missions at a lower cost, because it provides a standard interface between flight electronics components; new systems need not be custom built to accommodate individual missions, so electronics can be reused. New protocols are helping to standardize higher layers of computer communication. Goddard Space Flight Center improved on the ESA-developed SpaceWire by enabling standard protocols, which included defining quality of service and supporting plug-and-play capabilities. Goddard upgraded SpaceWire to make the routers more efficient and reliable, with features including redundant cables, simultaneous discrete broadcast pulses, prevention of network blockage, and improved verification. Redundant cables simplify management because the user does not need to worry about which connection is available, and simultaneous broadcast signals allow multiple users to broadcast low-latency side-band signal pulses across the network using the same resources for data communication. Additional features have been added to the SpaceWire switch to prevent network blockage so that more robust networks can be designed. Goddard s verification environment for the link-and-switch implementation continuously randomizes and tests different parts, constantly anticipating situations, which helps improve communications reliability. It has been tested in many different implementations for compatibility.

Intelligent routing protocol for ad hoc wireless network

NASA Astrophysics Data System (ADS)

Peng, Chaorong; Chen, Chang Wen

2006-05-01

A novel routing scheme for mobile ad hoc networks (MANETs), which combines hybrid and multi-inter-routing path properties with a distributed topology discovery route mechanism using control agents is proposed in this paper. In recent years, a variety of hybrid routing protocols for Mobile Ad hoc wireless networks (MANETs) have been developed. Which is proactively maintains routing information for a local neighborhood, while reactively acquiring routes to destinations beyond the global. The hybrid protocol reduces routing discovery latency and the end-to-end delay by providing high connectivity without requiring much of the scarce network capacity. On the other side the hybrid routing protocols in MANETs likes Zone Routing Protocol still need route "re-discover" time when a route between zones link break. Sine the topology update information needs to be broadcast routing request on local zone. Due to this delay, the routing protocol may not be applicable for real-time data and multimedia communication. We utilize the advantages of a clustering organization and multi-routing path in routing protocol to achieve several goals at the same time. Firstly, IRP efficiently saves network bandwidth and reduces route reconstruction time when a routing path fails. The IRP protocol does not require global periodic routing advertisements, local control agents will automatically monitor and repair broke links. Secondly, it efficiently reduces congestion and traffic "bottlenecks" for ClusterHeads in clustering network. Thirdly, it reduces significant overheads associated with maintaining clusters. Fourthly, it improves clusters stability due to dynamic topology changing frequently. In this paper, we present the Intelligent Routing Protocol. First, we discuss the problem of routing in ad hoc networks and the motivation of IRP. We describe the hierarchical architecture of IRP. We describe the routing process and illustrate it with an example. Further, we describe the control manage mechanisms, which are used to control active route and reduce the traffic amount in the route discovery procedure. Finial, the numerical experiments are given to show the effectiveness of IRP routing protocol.

Gaze-Aware Streaming Solutions for the Next Generation of Mobile VR Experiences.

PubMed

Lungaro, Pietro; Sjoberg, Rickard; Valero, Alfredo Jose Fanghella; Mittal, Ashutosh; Tollmar, Konrad

2018-04-01

This paper presents a novel approach to content delivery for video streaming services. It exploits information from connected eye-trackers embedded in the next generation of VR Head Mounted Displays (HMDs). The proposed solution aims to deliver high visual quality, in real time, around the users' fixations points while lowering the quality everywhere else. The goal of the proposed approach is to substantially reduce the overall bandwidth requirements for supporting VR video experiences while delivering high levels of user perceived quality. The prerequisites to achieve these results are: (1) mechanisms that can cope with different degrees of latency in the system and (2) solutions that support fast adaptation of video quality in different parts of a frame, without requiring a large increase in bitrate. A novel codec configuration, capable of supporting near-instantaneous video quality adaptation in specific portions of a video frame, is presented. The proposed method exploits in-built properties of HEVC encoders and while it introduces a moderate amount of error, these errors are indetectable by users. Fast adaptation is the key to enable gaze-aware streaming and its reduction in bandwidth. A testbed implementing gaze-aware streaming, together with a prototype HMD with in-built eye tracker, is presented and was used for testing with real users. The studies quantified the bandwidth savings achievable by the proposed approach and characterize the relationships between Quality of Experience (QoE) and network latency. The results showed that up to 83% less bandwidth is required to deliver high QoE levels to the users, as compared to conventional solutions.

Arithmetic functions in torus and tree networks

DOEpatents

Bhanot, Gyan; Blumrich, Matthias A.; Chen, Dong; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Steinmacher-Burow, Burkhard D.; Vranas, Pavlos M.

2007-12-25

Methods and systems for performing arithmetic functions. In accordance with a first aspect of the invention, methods and apparatus are provided, working in conjunction of software algorithms and hardware implementation of class network routing, to achieve a very significant reduction in the time required for global arithmetic operation on the torus. Therefore, it leads to greater scalability of applications running on large parallel machines. The invention involves three steps in improving the efficiency and accuracy of global operations: (1) Ensuring, when necessary, that all the nodes do the global operation on the data in the same order and so obtain a unique answer, independent of roundoff error; (2) Using the topology of the torus to minimize the number of hops and the bidirectional capabilities of the network to reduce the number of time steps in the data transfer operation to an absolute minimum; and (3) Using class function routing to reduce latency in the data transfer. With the method of this invention, every single element is injected into the network only once and it will be stored and forwarded without any further software overhead. In accordance with a second aspect of the invention, methods and systems are provided to efficiently implement global arithmetic operations on a network that supports the global combining operations. The latency of doing such global operations are greatly reduced by using these methods.

The Temporal Propagation of Intrinsic Brain Activity Associate With the Occurrence of PTSD

PubMed Central

Weng, Yifei; Qi, Rongfeng; Chen, Feng; Ke, Jun; Xu, Qiang; Zhong, Yuan; Chen, Lida; Li, Jianjun; Zhang, Zhiqiang; Zhang, Li; Lu, Guangming

2018-01-01

The abnormal brain activity is a pivotal condition for the occurrence of posttraumatic stress disorder. However, the dynamic time features of intrinsic brain activities still remain unclearly in PTSD patients. Our study aims to perform the resting-state lag analysis (RS-LA) method to explore potential propagated patterns of intrinsic brain activities in PTSD patients. We recruited 27 drug-naive patients with PTSD, 33 trauma-exposed controls (TEC), and 30 demographically matched healthy controls (HC) in the final data statistics. Both RS-LA and conventional voxel-wise functional connectivity strength (FCS) methods were employed on the same dataset. Then, Spearman correlation analysis was conducted on time latency values of those abnormal brain regions with the clinical assessments. Compared with HC group, the time latency patterns of PTSD patients significantly shifted toward later in posterior cingulate cortex/precuneus, middle prefrontal cortex, right angular, and left pre- and post-central cortex. The TEC group tended to have similar time latency in right angular. Additionally, significant time latency in right STG was found in PTSD group relative to TEC group. Spearman correlation analysis revealed that the time latency value of mPFC negatively correlated to the PTSD checklist-civilian version scores (PCL_C) in PTSD group (r = −0.578, P < 0.05). Furthermore, group differences map of FCS exhibited parts of overlapping areas with that of RS-LA, however, less specificity in detecting PTSD patients. In conclusion, apparent alterations of time latency were observed in DMN and primary sensorimotor areas of PTSD patients. These findings provide us with new evidence to explain the neural pathophysiology contributing to PTSD. PMID:29887811

Understanding and Analyzing Latency of Near Real-time Satellite Data

NASA Astrophysics Data System (ADS)

Han, W.; Jochum, M.; Brust, J.

2016-12-01

Acquiring and disseminating time-sensitive satellite data in a timely manner is much concerned by researchers and decision makers of weather forecast, severe weather warning, disaster and emergency response, environmental monitoring, and so on. Understanding and analyzing the latency of near real-time satellite data is very useful and helpful to explore the whole data transmission flow, indentify the possible issues, and connect data providers and users better. The STAR (Center for Satellite Applications and Research of NOAA) Central Data Repository (SCDR) is a central repository to acquire, manipulate, and disseminate various types of near real-time satellite datasets to internal and external users. In this system, important timestamps, including observation beginning/end, processing, uploading, downloading, and ingestion, are retrieved and organized in the database, so the time length of each transmission phase can be figured out easily. Open source NoSQL database MongoDB is selected to manage the timestamp information because of features of dynamic schema, aggregation and data processing. A user-friendly user interface is developed to visualize and characterize the latency interactively. Taking the Himawari-8 HSD (Himawari Standard Data) file as an example, the data transmission phases, including creating HSD file from satellite observation, uploading the file to HimawariCloud, updating file link in the webpage, downloading and ingesting the file to SCDR, are worked out from the above mentioned timestamps. The latencies can be observed by time of period, day of week, or hour of day in chart or table format, and the anomaly latencies can be detected and reported through the user interface. Latency analysis provides data providers and users actionable insight on how to improve the data transmission of near real-time satellite data, and enhance its acquisition and management.

Mobility and Cloud: Operating in Intermittent, Austere Network Conditions

DTIC Science & Technology

2014-09-01

consume information, and are connected to cloud-based servers over wired or wireless network connections. For mobile clients, this connection, by...near future. In addition to intermittent connectivity issues, many wireless networks introduce additional delay due to excessive buffering. This can...requirements, commercial cloud applications have grown at a fast rate. Similar to other mobile systems, navy ships connected over wireless networks

A Network of Direct Broadcast Antenna Systems to Provide Real-Time Infrared and Microwave Sounder Data for Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Gumley, L.

2013-12-01

The Space Science and Engineering Center at the University of Wisconsin-Madison is creating a network of direct broadcast satellite data reception stations to acquire and process infrared and microwave sounder data in real-time from polar orbiting meteorological satellites and deliver the resulting products to NOAA with low latency for assimilation in NCEP numerical weather prediction models. The network will include 4 antenna sites that will be operated directly by SSEC, including Madison WI, Honolulu HI, Miami FL, and Mayaguez PR. The network will also include partner antenna sites not directly controlled by SSEC, including Corvallis OR, Monterey CA, Suitland MD, Fairbanks AK, and Guam. All of the antenna sites will have a combined X/L-band reception system capable of receiving data via direct broadcast from polar orbiting satellites including Suomi NPP and JPSS-1, Metop-A/B, POES,Terra, and Aqua. Each site will collect raw data from these satellites locally, process it to Level 1 (SDR) and Level 2 (EDR) products, and transmit the products back to SSEC for delivery to NOAA/NCEP. The primary purpose of the antenna systems is to provide real-time infrared and microwave sounder data from Metop and Suomi-NPP to NOAA to support data assimilation for NOAA/NCEP operational numerical weather prediction models. At present, NOAA/NCEP use of advanced infrared (CrIS, IASI, AIRS) and microwave (ATMS, AMSU) sounder data over North America in NWP data assimilation is limited because of the latency of the products in relation to the cutoff times for assimilation runs. This network will deliver infrared and microwave sounder data to NCEP with the lowest latency possible, via the reception and processing of data received via direct broadcast. CIMSS/SSEC is managing the procurement and installation of the antenna systems at the two new sites, and will operate the stations remotely. NOAA will establish the reception priorities (Metop and SNPP will be at the highest priority) and SSEC will set the reception schedule to acquire data from these satellites, and any other satellites at lower priority as determined jointly by NOAA, CIMSS/SSEC, and the antenna site hosts. SSEC is providing a product generation server at each site (where applicable) as part of the installed hardware to create satellite products in real-time. The host locations will provide the necessary network resources to enable infrared sounder (CrIS, IASI, and AIRS) and microwave sounder (ATMS and AMSU) data to be sent back to SSEC (and hence to NOAA/NCEP) with low latency (< 15 minutes). This presentation will described how the network realizes the goal of providing data to end users within 15 minutes of observation, and will give examples of the positive impact already observed on NCEP forecast model skill from assimilating real-time infrared and microwave sounder data in the NAM regional domain.

Reduced functional connectivity within and between ‘social’ resting state networks in autism spectrum conditions

PubMed Central

Stoyanova, Raliza S.; Baron-Cohen, Simon; Calder, Andrew J.

2013-01-01

Individuals with Autism Spectrum Conditions (ASC) have difficulties in social interaction and communication, which is reflected in hypoactivation of brain regions engaged in social processing, such as medial prefrontal cortex (mPFC), amygdala and insula. Resting state studies in ASC have identified reduced connectivity of the default mode network (DMN), which includes mPFC, suggesting that other resting state networks incorporating ‘social’ brain regions may also be abnormal. Using Seed-based Connectivity and Group Independent Component Analysis (ICA) approaches, we looked at resting functional connectivity in ASC between specific ‘social’ brain regions, as well as within and between whole networks incorporating these regions. We found reduced functional connectivity within the DMN in individuals with ASC, using both ICA and seed-based approaches. Two further networks identified by ICA, the salience network, incorporating the insula and a medial temporal lobe network, incorporating the amygdala, showed reduced inter-network connectivity. This was underlined by reduced seed-based connectivity between the insula and amygdala. The results demonstrate significantly reduced functional connectivity within and between resting state networks incorporating ‘social’ brain regions. This reduced connectivity may result in difficulties in communication and integration of information across these networks, which could contribute to the impaired processing of social signals in ASC. PMID:22563003

Visual Evoked Potentials in Infants With Diffuse Periventricular Leukomalacia.

PubMed

Carbajal-Valenzuela, Cintli Carolina; Santiago-Rodríguez, Efraín; Harmony, Thalía; Fernández-Bouzas, Antonio

2014-10-01

Periventricular leukomalacia (PVL) is characterized by necrosis of the cerebral white matter in the dorsolateral portions of the lateral ventricles. PVL causes motor, sensory, and cognitive deficits. The aim of this study was to analyze the conduction characteristics of the visual pathway in infants with diffuse PVL using visual evoked potentials (VEPs). We studied 11 healthy infants (mean age 3.3 ± 1.3 months) and 17 with diffuse PVL (mean age 2.9 ± 0.8 months and mean gestational age 31.9 ± 3.1 weeks). The N75, P100, and N135 wave latencies; the interwave N75-P100 and P100-N135 latencies; and the N75-P100 and P100-N135 amplitudes were measured in the occipital leads. VEPs were recorded during binocular stimulation at an angle of 120' from the Fz-Oz lead. Healthy children had mean N75, P100, and N135 wave latencies of 84.4 ± 5.8, 143.4 ± 30.6 and 222.9 ± 40.4 ms, respectively. The mean interwave N75-P100 and P100-N135 latencies were 59.0 ± 28.6 and 79.5 ± 13.6 ms, respectively. Compared with the healthy group, infants with PVL had longer N75 and N135 latencies at 92.3 ± 15.3 (P = .05) and 265.0 ms ± 60.3 (P = .05), respectively. The interwave latency P100-N135 (105.5 ± 29.1 ms; P = .017) was longer in children with PVL than in healthy infants. Infants with diffuse PVL had mild alterations in their N75, P100 and, particularly, their N135 latencies. These increases in P100-N135 interwave latencies could be because of damage to the geniculocortical pathways and V2-V3 networks. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Camouflage Traffic: Minimizing Message Delay for Smart Grid Applications under Jamming

DTIC Science & Technology

2014-04-01

technologies. To facilitate efficient information exchange, wireless networks have been proposed to be widely used in the smart grid. However, the jamming...attack that constantly broadcasts radio interference is a primary security threat to prevent the deployment of wireless networks in the smart grid. Hence... wireless communications, while at the same time providing latency guarantee for control messages. An open question is how to minimize message delay for

A framework using cluster-based hybrid network architecture for collaborative virtual surgery.

PubMed

Qin, Jing; Choi, Kup-Sze; Poon, Wai-Sang; Heng, Pheng-Ann

2009-12-01

Research on collaborative virtual environments (CVEs) opens the opportunity for simulating the cooperative work in surgical operations. It is however a challenging task to implement a high performance collaborative surgical simulation system because of the difficulty in maintaining state consistency with minimum network latencies, especially when sophisticated deformable models and haptics are involved. In this paper, an integrated framework using cluster-based hybrid network architecture is proposed to support collaborative virtual surgery. Multicast transmission is employed to transmit updated information among participants in order to reduce network latencies, while system consistency is maintained by an administrative server. Reliable multicast is implemented using distributed message acknowledgment based on cluster cooperation and sliding window technique. The robustness of the framework is guaranteed by the failure detection chain which enables smooth transition when participants join and leave the collaboration, including normal and involuntary leaving. Communication overhead is further reduced by implementing a number of management approaches such as computational policies and collaborative mechanisms. The feasibility of the proposed framework is demonstrated by successfully extending an existing standalone orthopedic surgery trainer into a collaborative simulation system. A series of experiments have been conducted to evaluate the system performance. The results demonstrate that the proposed framework is capable of supporting collaborative surgical simulation.

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

PubMed

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

2018-03-26

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

The Pet Connection. Use of pets as sentinels to better integrate data on endocrine health effects of persistent environmental contaminants.

EPA Science Inventory

Many pets, cats in particular, spend virtually all their lives within the family domicile, thus paralleling their owner’s low-level but chronic exposure to a variety of indoor contaminants. Owing to their shorter life-spans and shorter latency periods, associations between contam...

Switch-connected HyperX network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Dong; Heidelberger, Philip

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,more » other of the N ports are connected to at least one of the global switches.« less

Adaptive Code Division Multiple Access Protocol for Wireless Network-on-Chip Architectures

NASA Astrophysics Data System (ADS)

Vijayakumaran, Vineeth

Massive levels of integration following Moore's Law ushered in a paradigm shift in the way on-chip interconnections were designed. With higher and higher number of cores on the same die traditional bus based interconnections are no longer a scalable communication infrastructure. On-chip networks were proposed enabled a scalable plug-and-play mechanism for interconnecting hundreds of cores on the same chip. Wired interconnects between the cores in a traditional Network-on-Chip (NoC) system, becomes a bottleneck with increase in the number of cores thereby increasing the latency and energy to transmit signals over them. Hence, there has been many alternative emerging interconnect technologies proposed, namely, 3D, photonic and multi-band RF interconnects. Although they provide better connectivity, higher speed and higher bandwidth compared to wired interconnects; they also face challenges with heat dissipation and manufacturing difficulties. On-chip wireless interconnects is one other alternative proposed which doesn't need physical interconnection layout as data travels over the wireless medium. They are integrated into a hybrid NOC architecture consisting of both wired and wireless links, which provides higher bandwidth, lower latency, lesser area overhead and reduced energy dissipation in communication. However, as the bandwidth of the wireless channels is limited, an efficient media access control (MAC) scheme is required to enhance the utilization of the available bandwidth. This thesis proposes using a multiple access mechanism such as Code Division Multiple Access (CDMA) to enable multiple transmitter-receiver pairs to send data over the wireless channel simultaneously. It will be shown that such a hybrid wireless NoC with an efficient CDMA based MAC protocol can significantly increase the performance of the system while lowering the energy dissipation in data transfer. In this work it is shown that the wireless NoC with the proposed CDMA based MAC protocol outperformed the wired counterparts and several other wireless architectures proposed in literature in terms of bandwidth and packet energy dissipation. Significant gains were observed in packet energy dissipation and bandwidth even with scaling the system to higher number of cores. Non-uniform traffic simulations showed that the proposed CDMA-WiNoC was consistent in bandwidth across all traffic patterns. It is also shown that the CDMA based MAC scheme does not introduce additional reliability concerns in data transfer over the on-chip wireless interconnects.

Contention Modeling for Multithreaded Distributed Shared Memory Machines: The Cray XMT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Secchi, Simone; Tumeo, Antonino; Villa, Oreste

Distributed Shared Memory (DSM) machines are a wide class of multi-processor computing systems where a large virtually-shared address space is mapped on a network of physically distributed memories. High memory latency and network contention are two of the main factors that limit performance scaling of such architectures. Modern high-performance computing DSM systems have evolved toward exploitation of massive hardware multi-threading and fine-grained memory hashing to tolerate irregular latencies, avoid network hot-spots and enable high scaling. In order to model the performance of such large-scale machines, parallel simulation has been proved to be a promising approach to achieve good accuracy inmore » reasonable times. One of the most critical factors in solving the simulation speed-accuracy trade-off is network modeling. The Cray XMT is a massively multi-threaded supercomputing architecture that belongs to the DSM class, since it implements a globally-shared address space abstraction on top of a physically distributed memory substrate. In this paper, we discuss the development of a contention-aware network model intended to be integrated in a full-system XMT simulator. We start by measuring the effects of network contention in a 128-processor XMT machine and then investigate the trade-off that exists between simulation accuracy and speed, by comparing three network models which operate at different levels of accuracy. The comparison and model validation is performed by executing a string-matching algorithm on the full-system simulator and on the XMT, using three datasets that generate noticeably different contention patterns.« less

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

PubMed Central

Rich, Scott; Zochowski, Michal; Booth, Victoria

2017-01-01

The interconnectivity between excitatory and inhibitory neural networks informs mechanisms by which rhythmic bursts of excitatory activity can be produced in the brain. One such mechanism, Pyramidal Interneuron Network Gamma (PING), relies primarily upon reciprocal connectivity between the excitatory and inhibitory networks, while also including intra-connectivity of inhibitory cells. The causal relationship between excitatory activity and the subsequent burst of inhibitory activity is of paramount importance to the mechanism and has been well studied. However, the role of the intra-connectivity of the inhibitory network, while important for PING, has not been studied in detail, as most analyses of PING simply assume that inhibitory intra-connectivity is strong enough to suppress subsequent firing following the initial inhibitory burst. In this paper we investigate the role that the strength of inhibitory intra-connectivity plays in determining the dynamics of PING-style networks. We show that networks with weak inhibitory intra-connectivity exhibit variations in burst dynamics of both the excitatory and inhibitory cells that are not obtained with strong inhibitory intra-connectivity. Networks with weak inhibitory intra-connectivity exhibit excitatory rhythmic bursts with weak excitatory-to-inhibitory synapses for which classical PING networks would show no rhythmic activity. Additionally, variations in dynamics of these networks as the excitatory-to-inhibitory synaptic weight increases illustrates the important role that consistent pattern formation in the inhibitory cells serves in maintaining organized and periodic excitatory bursts. Finally, motivated by these results and the known diversity of interneurons, we show that a PING-style network with two inhibitory subnetworks, one strongly intra-connected and one weakly intra-connected, exhibits organized and periodic excitatory activity over a larger parameter regime than networks with a homogeneous inhibitory population. Taken together, these results serve to better articulate the role of inhibitory intra-connectivity in generating PING-like rhythms, while also revealing how heterogeneity amongst inhibitory synapses might make such rhythms more robust to a variety of network parameters. PMID:29326558

Synchronization from Second Order Network Connectivity Statistics

PubMed Central

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

Performance of the High Sensitivity Open Source Multi-GNSS Assisted GNSS Reference Server.

NASA Astrophysics Data System (ADS)

Sarwar, Ali; Rizos, Chris; Glennon, Eamonn

2015-06-01

The Open Source GNSS Reference Server (OSGRS) exploits the GNSS Reference Interface Protocol (GRIP) to provide assistance data to GPS receivers. Assistance can be in terms of signal acquisition and in the processing of the measurement data. The data transfer protocol is based on Extensible Mark-up Language (XML) schema. The first version of the OSGRS required a direct hardware connection to a GPS device to acquire the data necessary to generate the appropriate assistance. Scenarios of interest for the OSGRS users are weak signal strength indoors, obstructed outdoors or heavy multipath environments. This paper describes an improved version of OSGRS that provides alternative assistance support from a number of Global Navigation Satellite Systems (GNSS). The underlying protocol to transfer GNSS assistance data from global casters is the Networked Transport of RTCM (Radio Technical Commission for Maritime Services) over Internet Protocol (NTRIP), and/or the RINEX (Receiver Independent Exchange) format. This expands the assistance and support model of the OSGRS to globally available GNSS data servers connected via internet casters. A variety of formats and versions of RINEX and RTCM streams become available, which strengthens the assistance provisioning capability of the OSGRS platform. The prime motivation for this work was to enhance the system architecture of the OSGRS to take advantage of globally available GNSS data sources. Open source software architectures and assistance models provide acquisition and data processing assistance for GNSS receivers operating in weak signal environments. This paper describes test scenarios to benchmark the OSGRSv2 performance against other Assisted-GNSS solutions. Benchmarking devices include the SPOT satellite messenger, MS-Based & MS-Assisted GNSS, HSGNSS (SiRFstar-III) and Wireless Sensor Networks Assisted-GNSS. Benchmarked parameters include the number of tracked satellites, the Time to Fix First (TTFF), navigation availability and accuracy. Three different configurations of Multi-GNSS assistance servers were used, namely Cloud-Client-Server, the Demilitarized Zone (DMZ) Client-Server and PC-Client-Server; with respect to the connectivity location of client and server. The impact on the performance based on server and/or client initiation, hardware capability, network latency, processing delay and computation times with their storage, scalability, processing and load sharing capabilities, were analysed. The performance of the OSGRS is compared against commercial GNSS, Assisted-GNSS and WSN-enabled GNSS devices. The OSGRS system demonstrated lower TTFF and higher availability.

Investigating Functional Regeneration in Organotypic Spinal Cord Co-cultures Grown on Multi-electrode Arrays.

PubMed

Heidemann, Martina; Streit, Jürg; Tscherter, Anne

2015-09-23

Adult higher vertebrates have a limited potential to recover from spinal cord injury. Recently, evidence emerged that propriospinal connections are a promising target for intervention to improve functional regeneration. So far, no in vitro model exists that grants the possibility to examine functional recovery of propriospinal fibers. Therefore, a representative model that is based on two organotypic spinal cord sections of embryonic rat, cultured next to each other on multi-electrode arrays (MEAs) was developed. These slices grow and, within a few days in vitro, fuse along the sides facing each other. The design of the used MEAs permits the performance of lesions with a scalpel blade through this fusion site without inflicting damage on the MEAs. The slices show spontaneous activity, usually organized in network activity bursts, and spatial and temporal activity parameters such as the location of burst origins, speed and direction of their propagation and latencies between bursts can be characterized. Using these features, it is also possible to assess functional connection of the slices by calculating the amount of synchronized bursts between the two sides. Furthermore, the slices can be morphologically analyzed by performing immunohistochemical stainings after the recordings. Several advantages of the used techniques are combined in this model: the slices largely preserve the original tissue architecture with intact local synaptic circuitry, the tissue is easily and repeatedly accessible and neuronal activity can be detected simultaneously and non-invasively in a large number of spots at high temporal resolution. These features allow the investigation of functional regeneration of intraspinal connections in isolation in vitro in a sophisticated and efficient way.

Node Redeployment Algorithm Based on Stratified Connected Tree for Underwater Sensor Networks

PubMed Central

Liu, Jun; Jiang, Peng; Wu, Feng; Yu, Shanen; Song, Chunyue

2016-01-01

During the underwater sensor networks (UWSNs) operation, node drift with water environment causes network topology changes. Periodic node location examination and adjustment are needed to maintain good network monitoring quality as long as possible. In this paper, a node redeployment algorithm based on stratified connected tree for UWSNs is proposed. At every network adjustment moment, self-examination and adjustment on node locations are performed firstly. If a node is outside the monitored space, it returns to the last location recorded in its memory along straight line. Later, the network topology is stratified into a connected tree that takes the sink node as the root node by broadcasting ready information level by level, which can improve the network connectivity rate. Finally, with synthetically considering network coverage and connectivity rates, and node movement distance, the sink node performs centralized optimization on locations of leaf nodes in the stratified connected tree. Simulation results show that the proposed redeployment algorithm can not only keep the number of nodes in the monitored space as much as possible and maintain good network coverage and connectivity rates during network operation, but also reduce node movement distance during node redeployment and prolong the network lifetime. PMID:28029124

Modulating Intrinsic Connectivity: Adjacent Subregions within Supplementary Motor Cortex, Dorsolateral Prefrontal Cortex, and Parietal Cortex Connect to Separate Functional Networks during Task and Also Connect during Rest

PubMed Central

Roth, Jennifer K.; Johnson, Marcia K.; Tokoglu, Fuyuze; Murphy, Isabella; Constable, R. Todd

2014-01-01

Supplementary motor area (SMA), the inferior frontal junction (IFJ), superior frontal junction (SFJ) and parietal cortex are active in many cognitive tasks. In a previous study, we found that subregions of each of these major areas were differentially active in component processes of executive function during working memory tasks. In the present study, each of these subregions was used as a seed in a whole brain functional connectivity analysis of working memory and resting state data. These regions show functional connectivity to different networks, thus supporting the parcellation of these major regions into functional subregions. Many regions showing significant connectivity during the working memory residual data (with task events regressed from the data) were also significantly connected during rest suggesting that these network connections to subregions within major regions of cortex are intrinsic. For some of these connections, task demands modulate activity in these intrinsic networks. Approximately half of the connections significant during task were significant during rest, indicating that some of the connections are intrinsic while others are recruited only in the service of the task. Furthermore, the network connections to traditional ‘task positive’ and ‘task negative’ (a.k.a ‘default mode’) regions shift from positive connectivity to negative connectivity depending on task demands. These findings demonstrate that such task-identified subregions are part of distinct networks, and that these networks have different patterns of connectivity for task as they do during rest, engaging connections both to task positive and task negative regions. These results have implications for understanding the parcellation of commonly active regions into more specific functional networks. PMID:24637793

Global Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks

DTIC Science & Technology

2014-03-31

Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks M.M. Asadi H. Mahboubi A...2014 Global Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks Contract Report # AMBUSH.1.1 Contract...pi j /= 0. The sensor network considered in this work is composed of underwater sensors , which use acoustic waves for

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

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

PubMed

Solé-Padullés, Cristina; Castro-Fornieles, Josefina; de la Serna, Elena; Calvo, Rosa; Baeza, Inmaculada; Moya, Jaime; Lázaro, Luisa; Rosa, Mireia; Bargalló, Nuria; Sugranyes, Gisela

2016-02-01

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. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Digital image analysis to quantify carbide networks in ultrahigh carbon steels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hecht, Matthew D.; Webler, Bryan A.; Picard, Yoosuf N., E-mail: ypicard@cmu.edu

A method has been developed and demonstrated to quantify the degree of carbide network connectivity in ultrahigh carbon steels through digital image processing and analysis of experimental micrographs. It was shown that the network connectivity and carbon content can be correlated to toughness for various ultrahigh carbon steel specimens. The image analysis approach first involved segmenting the carbide network and pearlite matrix into binary contrast representations via a grayscale intensity thresholding operation. Next, the carbide network pixels were skeletonized and parceled into braches and nodes, allowing the determination of a connectivity index for the carbide network. Intermediate image processing stepsmore » to remove noise and fill voids in the network are also detailed. The connectivity indexes of scanning electron micrographs were consistent in both secondary and backscattered electron imaging modes, as well as across two different (50 × and 100 ×) magnifications. Results from ultrahigh carbon steels reported here along with other results from the literature generally showed lower connectivity indexes correlated with higher Charpy impact energy (toughness). A deviation from this trend was observed at higher connectivity indexes, consistent with a percolation threshold for crack propagation across the carbide network. - Highlights: • A method for carbide network analysis in steels is proposed and demonstrated. • ImageJ method extracts a network connectivity index from micrographs. • Connectivity index consistent in different imaging conditions and magnifications. • Impact energy may plateau when a critical network connectivity is exceeded.« less

Dynamics of Intersubject Brain Networks during Anxious Anticipation

PubMed Central

Najafi, Mahshid; Kinnison, Joshua; Pessoa, Luiz

2017-01-01

How do large-scale brain networks reorganize during the waxing and waning of anxious anticipation? Here, threat was dynamically modulated during human functional MRI as two circles slowly meandered on the screen; if they touched, an unpleasant shock was delivered. We employed intersubject correlation analysis, which allowed the investigation of network-level functional connectivity across brains, and sought to determine how network connectivity changed during periods of approach (circles moving closer) and periods of retreat (circles moving apart). Analysis of positive connection weights revealed that dynamic threat altered connectivity within and between the salience, executive, and task-negative networks. For example, dynamic functional connectivity increased within the salience network during approach and decreased during retreat. The opposite pattern was found for the functional connectivity between the salience and task-negative networks: decreases during approach and increases during approach. Functional connections between subcortical regions and the salience network also changed dynamically during approach and retreat periods. Subcortical regions exhibiting such changes included the putative periaqueductal gray, putative habenula, and putative bed nucleus of the stria terminalis. Additional analysis of negative functional connections revealed dynamic changes, too. For example, negative weights within the salience network decreased during approach and increased during retreat, opposite what was found for positive weights. Together, our findings unraveled dynamic features of functional connectivity of large-scale networks and subcortical regions across participants while threat levels varied continuously, and demonstrate the potential of characterizing emotional processing at the level of dynamic networks. PMID:29209184

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

PubMed

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

2016-11-01

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

Earthquake Complex Network Analysis Before and After the Mw 8.2 Earthquake in Iquique, Chile

NASA Astrophysics Data System (ADS)

Pasten, D.

2017-12-01

The earthquake complex networks have shown that they are abble to find specific features in seismic data set. In space, this networkshave shown a scale-free behavior for the probability distribution of connectivity, in directed networks and theyhave shown a small-world behavior, for the undirected networks.In this work, we present an earthquake complex network analysis for the large earthquake Mw 8.2 in the north ofChile (near to Iquique) in April, 2014. An earthquake complex network is made dividing the three dimensional space intocubic cells, if one of this cells contain an hypocenter, we name this cell like a node. The connections between nodes aregenerated in time. We follow the time sequence of seismic events and we are making the connections betweennodes. Now, we have two different networks: a directed and an undirected network. Thedirected network takes in consideration the time-direction of the connections, that is very important for the connectivityof the network: we are considering the connectivity, ki of the i-th node, like the number of connections going out ofthe node i plus the self-connections (if two seismic events occurred successive in time in the same cubic cell, we havea self-connection). The undirected network is made removing the direction of the connections and the self-connectionsfrom the directed network. For undirected networks, we are considering only if two nodes are or not connected.We have built a directed complex network and an undirected complex network, before and after the large earthquake in Iquique. We have used magnitudes greater than Mw = 1.0 and Mw = 3.0. We found that this method can recognize the influence of thissmall seismic events in the behavior of the network and we found that the size of the cell used to build the network isanother important factor to recognize the influence of the large earthquake in this complex system. This method alsoshows a difference in the values of the critical exponent γ (for the probability distribution of connectivity in the directednetwork) before and after the large earthquake, but this method does not show a change in the clustering behavior ofthe undirected network, before and after the large earthquake, showing a small-world behavior for the network beforeand after of this large seismic event.

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

PubMed

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.

Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

PubMed Central

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-brain functional connectivity networks. To investigate the causal role of these networks in attention, we examined their response to a dose of methylphenidate, a common and effective treatment for attention-deficit/hyperactivity disorder, in healthy adults. As predicted, individuals on methylphenidate showed connectivity signatures of better sustained attention: higher high-attention and lower low-attention network strength than controls. These results suggest that methylphenidate acts by modulating strength in functional brain networks related to attention, and that changing whole-brain connectivity patterns may improve attention. PMID:27629707

Methylphenidate Modulates Functional Network Connectivity to Enhance Attention.

PubMed

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

2016-09-14

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. Recent work identified a promising neuromarker of sustained attention based on whole-brain functional connectivity networks. To investigate the causal role of these networks in attention, we examined their response to a dose of methylphenidate, a common and effective treatment for attention-deficit/hyperactivity disorder, in healthy adults. As predicted, individuals on methylphenidate showed connectivity signatures of better sustained attention: higher high-attention and lower low-attention network strength than controls. These results suggest that methylphenidate acts by modulating strength in functional brain networks related to attention, and that changing whole-brain connectivity patterns may improve attention. Copyright © 2016 the authors 0270-6474/16/369547-11$15.00/0.

"Missing links" in borderline personality disorder: loss of neural synchrony relates to lack of emotion regulation and impulse control.

PubMed

Williams, Leanne M; Sidis, Anna; Gordon, Evian; Meares, Russell A

2006-05-01

Symptoms of borderline personality disorder (BPD) may reflect distinct breakdowns in the integration of posterior and frontal brain networks. We used a high temporal resolution measure (40-Hz gamma phase synchrony) of brain activity to examine the connectivity of brain function in BPD. Unmedicated patients with BPD (n = 15) and age-and sex-matched healthy control subjects (n = 15) undertook a task requiring discrimination of salient from background tones. In response to salient stimuli, the magnitude and latency of peak gamma phase synchrony for early (0-150 ms post stimulus) and late (250-500 ms post stimulus) phases were calculated for frontal and posterior regions and for left and right hemispheres. We recorded skin conductance responses (SCRs) and reaction time (RT) simultaneously to examine the contribution of arousal and performance. Compared with controls, patients with BPD had a significant delay in early posterior gamma synchrony and a reduction in right hemisphere late gamma synchrony in response to salient stimuli. Both SCR onset and RT were also delayed in BPD, but independently from differences in synchrony. The delay in posterior synchrony was associated with cognitive symptoms, and reduced right hemisphere synchrony was associated with impulsivity. These findings suggest that distinct impairments in the functional connectivity of neural systems for orienting to salient input underlie core dimensions of cognitive disturbance and poor impulse control in BPD.

Implementation of Phased Array Antenna Technology Providing a Wireless Local Area Network to Enhance Port Security and Maritime Interdiction Operations

DTIC Science & Technology

2009-09-01

boarding team, COTS, WLAN, smart antenna, OpenVPN application, wireless base station, OFDM, latency, point-to-point wireless link. 16. PRICE CODE 17...16 c. SSL/TLS .................................17 2. OpenVPN ......................................17 III. EXPERIMENT METHODOLOGY...network frame at Layer 2 has already been secured by encryption at a higher level. 2. OpenVPN OpenVPN is open source software that provides a VPN

Immersive Molecular Visualization with Omnidirectional Stereoscopic Ray Tracing and Remote Rendering

PubMed Central

Stone, John E.; Sherman, William R.; Schulten, Klaus

2016-01-01

Immersive molecular visualization provides the viewer with intuitive perception of complex structures and spatial relationships that are of critical interest to structural biologists. The recent availability of commodity head mounted displays (HMDs) provides a compelling opportunity for widespread adoption of immersive visualization by molecular scientists, but HMDs pose additional challenges due to the need for low-latency, high-frame-rate rendering. State-of-the-art molecular dynamics simulations produce terabytes of data that can be impractical to transfer from remote supercomputers, necessitating routine use of remote visualization. Hardware-accelerated video encoding has profoundly increased frame rates and image resolution for remote visualization, however round-trip network latencies would cause simulator sickness when using HMDs. We present a novel two-phase rendering approach that overcomes network latencies with the combination of omnidirectional stereoscopic progressive ray tracing and high performance rasterization, and its implementation within VMD, a widely used molecular visualization and analysis tool. The new rendering approach enables immersive molecular visualization with rendering techniques such as shadows, ambient occlusion lighting, depth-of-field, and high quality transparency, that are particularly helpful for the study of large biomolecular complexes. We describe ray tracing algorithms that are used to optimize interactivity and quality, and we report key performance metrics of the system. The new techniques can also benefit many other application domains. PMID:27747138

Changes in P3b Latency and Amplitude Reflect Expertise Acquisition in a Football Visuomotor Learning Task.

PubMed

Morgan, Kyle K; Luu, Phan; Tucker, Don M

2016-01-01

Learning is not a unitary phenomenon. Rather, learning progresses through stages, with the stages reflecting different challenges that require the support of specific cognitive processes that reflect the functions of different brain networks. A theory of general learning proposes that learning can be divided into early and late stages controlled by corticolimbic networks located in frontal and posterior brain regions, respectively. Recent human studies using dense-array EEG (dEEG) support these results by showing progressive increases in P3b amplitude (an Event Related Potential with estimated sources in posterior cingulate cortex and hippocampus) as participants acquire a new visuomotor skill. In the present study, the P3b was used to track the learning and performance of participants as they identify defensive football formations and make an appropriate response. Participants acquired the task over three days, and P3b latency and amplitude significantly changed when participants learned the task. As participants demonstrated further proficiency with extensive training, amplitude and latency changes in the P3b continued to closely mirror performance improvements. Source localization results across all days suggest that an important source generator of the P3b is located in the posterior cingulate cortex. Results from the study support prior findings and further suggest that the careful analysis of covert learning mechanisms and their underlying electrical signatures are a robust index of task competency.

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset

PubMed Central

Guo, Hao; Liu, Lei; Chen, Junjie; Xu, Yong; Jie, Xiang

2017-01-01

Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks. As an unbiased method, the minimum spanning tree simplifies high-order network structure while preserving its core framework. The dynamic characteristics of time series are not lost with this approach, and the neurological interpretation of the network is guaranteed. Simultaneously, we propose a multi-parameter optimization framework that involves extracting discriminative features from the minimum spanning tree high-order functional connectivity networks. Compared with the conventional methods, our resting-state fMRI classification method based on minimum spanning tree high-order functional connectivity networks greatly improved the diagnostic accuracy for Alzheimer's disease. PMID:29249926

Cyberinfrastructure for the NSF Ocean Observatories Initiative

NASA Astrophysics Data System (ADS)

Orcutt, J. A.; Vernon, F. L.; Arrott, M.; Chave, A.; Schofield, O.; Peach, C.; Krueger, I.; Meisinger, M.

2008-12-01

The Ocean Observatories Initiative (OOI) is an environmental observatory covering a diversity of oceanic environments, ranging from the coastal to the deep ocean. The physical infrastructure comprises a combination of seafloor cables, buoys and autonomous vehicles. It is currently in the final design phase, with construction planned to begin in mid-2010 and deployment phased over five years. The Consortium for Ocean Leadership manages this Major Research Equipment and Facilities Construction program with subcontracts to Scripps Institution of Oceanography, University of Washington and Woods Hole Oceanographic Institution. High-level requirements for the CI include the delivery of near-real-time data with minimal latencies, open data, data analysis and data assimilation into models, and subsequent interactive modification of the network (including autonomous vehicles) by the cyberinfrastructure. Network connections include a heterogeneous combination of fiber optics, acoustic modems, and Iridium satellite telemetry. The cyberinfrastructure design loosely couples services that exist throughout the network and share common software and middleware as necessary. In this sense, the system appears to be identical at all scales, so it is self-similar or fractal by design. The system provides near-real-time access to data and developed knowledge by the OOI's Education and Public Engagement program, to the physical infrastructure by the marine operators and to the larger community including scientists, the public, schools and decision makers. Social networking is employed to facilitate the virtual organization that builds, operates and maintains the OOI as well as providing a variety of interfaces to the data and knowledge generated by the program. We are working closely with NOAA to exchange near-real-time data through interfaces to their Data Interchange Facility (DIF) program within the Integrated Ocean Observing System (IOOS). Efficiencies have been emphasized through the use of university and commercial computing clouds.

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

PubMed Central

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

Multiple Resting-State Networks Are Associated With Tremors and Cognitive Features in Essential Tremor.

PubMed

Fang, Weidong; Chen, Huiyue; Wang, Hansheng; Zhang, Han; Liu, Mengqi; Puneet, Munankami; Lv, Fajin; Cheng, Oumei; Wang, Xuefeng; Lu, Xiurong; Luo, Tianyou

2015-12-01

The heterogeneous clinical features of essential tremor indicate that the dysfunctions of this syndrome are not confined to motor networks, but extend to nonmotor networks. Currently, these neural network dysfunctions in essential tremor remain unclear. In this study, independent component analysis of resting-state functional MRI was used to study these neural network mechanisms. Thirty-five essential tremor patients and 35 matched healthy controls with clinical and neuropsychological tests were included, and eight resting-state networks were identified. After considering the structure and head-motion factors and testing the reliability of the selected resting-state networks, we assessed the functional connectivity changes within or between resting-state networks. Finally, image-behavior correlation analysis was performed. Compared to healthy controls, essential tremor patients displayed increased functional connectivity in the sensorimotor and salience networks and decreased functional connectivity in the cerebellum network. Additionally, increased functional network connectivity was observed between anterior and posterior default mode networks, and a decreased functional network connectivity was noted between the cerebellum network and the sensorimotor and posterior default mode networks. Importantly, the functional connectivity changes within and between these resting-state networks were correlated with the tremor severity and total cognitive scores of essential tremor patients. The findings of this study provide the first evidence that functional connectivity changes within and between multiple resting-state networks are associated with tremors and cognitive features of essential tremor, and this work demonstrates a potential approach for identifying the underlying neural network mechanisms of this syndrome. © 2015 International Parkinson and Movement Disorder Society.

Sandia Compact Sensor Node (SCSN) v. 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

HARRINGTON, JOHN

2009-01-07

The SCSN communication protocol is implemented in software and incorporates elements of Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), and Carrier Sense Multiple Access (CSMA) to reduce radio message collisions, latency, and power consumption. Alarm messages are expeditiously routed to a central node as a 'star' network with minimum overhead. Other messages can be routed along network links between any two nodes so that peer-to-peer communication is possible. Broadcast messages can be composed that flood the entire network or just specific portions with minimal radio traffic and latency. Two-way communication with sensor nodes, which sleep most ofmore » the time to conserve battery life, can occur at seven second intervals. SCSN software also incorporates special algorithms to minimize superfluous radio traffic that can result from excessive intrusion alarm messages. A built-in seismic detector is implemented with a geophone and software that distinguishes between pedestrian and vehicular targets. Other external sensors can be attached to a SCSN using supervised interface lines that are controlled by software. All software is written in the ANSI C language for ease of development, maintenance, and portability.« less

Modeling infection transmission in primate networks to predict centrality-based risk.

PubMed

Romano, Valéria; Duboscq, Julie; Sarabian, Cécile; Thomas, Elodie; Sueur, Cédric; MacIntosh, Andrew J J

2016-07-01

Social structure can theoretically regulate disease risk by mediating exposure to pathogens via social proximity and contact. Investigating the role of central individuals within a network may help predict infectious agent transmission as well as implement disease control strategies, but little is known about such dynamics in real primate networks. We combined social network analysis and a modeling approach to better understand transmission of a theoretical infectious agent in wild Japanese macaques, highly social animals which form extended but highly differentiated social networks. We collected focal data from adult females living on the islands of Koshima and Yakushima, Japan. Individual identities as well as grooming networks were included in a Markov graph-based simulation. In this model, the probability that an individual will transmit an infectious agent depends on the strength of its relationships with other group members. Similarly, its probability of being infected depends on its relationships with already infected group members. We correlated: (i) the percentage of subjects infected during a latency-constrained epidemic; (ii) the mean latency to complete transmission; (iii) the probability that an individual is infected first among all group members; and (iv) each individual's mean rank in the chain of transmission with different individual network centralities (eigenvector, strength, betweenness). Our results support the hypothesis that more central individuals transmit infections in a shorter amount of time and to more subjects but also become infected more quickly than less central individuals. However, we also observed that the spread of infectious agents on the Yakushima network did not always differ from expectations of spread on random networks. Generalizations about the importance of observed social networks in pathogen flow should thus be made with caution, since individual characteristics in some real world networks appear less relevant than they are in others in predicting disease spread. Am. J. Primatol. 78:767-779, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

78 FR 39383 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-01

... centers.\\4\\ \\4\\ The vendors supporting wireless transmission of CME data will install equipment on... wireless connectivity and obtain the lower latency transmission of data from third parties and NASDAQ that... Proposed Rule Change 1. Purpose Wireless technology has been in existence for many years, used primarily by...

Neural network classification of clinical neurophysiological data for acute care monitoring

NASA Technical Reports Server (NTRS)

Sgro, Joseph

1994-01-01

The purpose of neurophysiological monitoring of the 'acute care' patient is to allow the accurate recognition of changing or deteriorating neurological function as close to the moment of occurrence as possible, thus permitting immediate intervention. Results confirm that: (1) neural networks are able to accurately identify electroencephalogram (EEG) patterns and evoked potential (EP) wave components, and measuring EP waveform latencies and amplitudes; (2) neural networks are able to accurately detect EP and EEG recordings that have been contaminated by noise; (3) the best performance was obtained consistently with the back propagation network for EP and the HONN for EEG's; (4) neural network performed consistently better than other methods evaluated; and (5) neural network EEG and EP analyses are readily performed on multichannel data.

Software-defined Radio Based Measurement Platform for Wireless Networks

PubMed Central

Chao, I-Chun; Lee, Kang B.; Candell, Richard; Proctor, Frederick; Shen, Chien-Chung; Lin, Shinn-Yan

2015-01-01

End-to-end latency is critical to many distributed applications and services that are based on computer networks. There has been a dramatic push to adopt wireless networking technologies and protocols (such as WiFi, ZigBee, WirelessHART, Bluetooth, ISA100.11a, etc.) into time-critical applications. Examples of such applications include industrial automation, telecommunications, power utility, and financial services. While performance measurement of wired networks has been extensively studied, measuring and quantifying the performance of wireless networks face new challenges and demand different approaches and techniques. In this paper, we describe the design of a measurement platform based on the technologies of software-defined radio (SDR) and IEEE 1588 Precision Time Protocol (PTP) for evaluating the performance of wireless networks. PMID:27891210

Software-defined Radio Based Measurement Platform for Wireless Networks.

PubMed

Chao, I-Chun; Lee, Kang B; Candell, Richard; Proctor, Frederick; Shen, Chien-Chung; Lin, Shinn-Yan

2015-10-01

End-to-end latency is critical to many distributed applications and services that are based on computer networks. There has been a dramatic push to adopt wireless networking technologies and protocols (such as WiFi, ZigBee, WirelessHART, Bluetooth, ISA100.11a, etc. ) into time-critical applications. Examples of such applications include industrial automation, telecommunications, power utility, and financial services. While performance measurement of wired networks has been extensively studied, measuring and quantifying the performance of wireless networks face new challenges and demand different approaches and techniques. In this paper, we describe the design of a measurement platform based on the technologies of software-defined radio (SDR) and IEEE 1588 Precision Time Protocol (PTP) for evaluating the performance of wireless networks.

Asymmetry of temporal auditory T-complex: right ear-left hemisphere advantage in Tb timing in children.

PubMed

Bruneau, Nicole; Bidet-Caulet, Aurélie; Roux, Sylvie; Bonnet-Brilhault, Frédérique; Gomot, Marie

2015-02-01

To investigate brain asymmetry of the temporal auditory evoked potentials (T-complex) in response to monaural stimulation in children compared to adults. Ten children (7 to 9 years) and ten young adults participated in the study. All were right-handed. The auditory stimuli used were tones (1100 Hz, 70 dB SPL, 50 ms duration) delivered monaurally (right, left ear) at four different levels of stimulus onset asynchrony (700-1100-1500-3000 ms). Latency and amplitude of responses were measured at left and right temporal sites according to the ear stimulated. Peaks of the three successive deflections (Na-Ta-Tb) of the T-complex were greater in amplitude and better defined in children than in adults. Amplitude measurements in children indicated that Na culminates on the left hemisphere whatever the ear stimulated whereas Ta and Tb culminate on the right hemisphere but for left ear stimuli only. Peak latency displayed different patterns of asymmetry. Na and Ta displayed shorter latencies for contralateral stimulation. The original finding was that Tb peak latency was the shortest at the left temporal site for right ear stimulation in children. Amplitude increased and/or peak latency decreased with increasing SOA, however no interaction effect was found with recording site or with ear stimulated. Our main original result indicates a right ear-left hemisphere timing advantage for Tb peak in children. The Tb peak would therefore be a good candidate as an electrophysiological marker of ear advantage effects during dichotic stimulation and of functional inter-hemisphere interactions and connectivity in children. Copyright © 2014. Published by Elsevier B.V.

Memory Network For Distributed Data Processors

NASA Technical Reports Server (NTRS)

Bolen, David; Jensen, Dean; Millard, ED; Robinson, Dave; Scanlon, George

1992-01-01

Universal Memory Network (UMN) is modular, digital data-communication system enabling computers with differing bus architectures to share 32-bit-wide data between locations up to 3 km apart with less than one millisecond of latency. Makes it possible to design sophisticated real-time and near-real-time data-processing systems without data-transfer "bottlenecks". This enterprise network permits transmission of volume of data equivalent to an encyclopedia each second. Facilities benefiting from Universal Memory Network include telemetry stations, simulation facilities, power-plants, and large laboratories or any facility sharing very large volumes of data. Main hub of UMN is reflection center including smaller hubs called Shared Memory Interfaces.

RXIO: Design and implementation of high performance RDMA-capable GridFTP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Yuan; Yu, Weikuan; Vetter, Jeffrey S.

2011-12-21

For its low-latency, high bandwidth, and low CPU utilization, Remote Direct Memory Access (RDMA) has established itself as an effective data movement technology in many networking environments. However, the transport protocols of grid run-time systems, such as GridFTP in Globus, are not yet capable of utilizing RDMA. In this study, we examine the architecture of GridFTP for the feasibility of enabling RDMA. An RDMA-capable XIO (RXIO) framework is designed and implemented to extend its XIO system and match the characteristics of RDMA. Our experimental results demonstrate that RDMA can significantly improve the performance of GridFTP, reducing the latency by 32%more » and increasing the bandwidth by more than three times. In achieving such performance improvements, RDMA dramatically cuts down CPU utilization of GridFTP clients and servers. In conclusion, these results demonstrate that RXIO can effectively exploit the benefits of RDMA for GridFTP. It offers a good prototype to further leverage GridFTP on wide-area RDMA networks.« less

A smart checkpointing scheme for improving the reliability of clustering routing protocols.

PubMed

Min, Hong; Jung, Jinman; Kim, Bongjae; Cho, Yookun; Heo, Junyoung; Yi, Sangho; Hong, Jiman

2010-01-01

In wireless sensor networks, system architectures and applications are designed to consider both resource constraints and scalability, because such networks are composed of numerous sensor nodes with various sensors and actuators, small memories, low-power microprocessors, radio modules, and batteries. Clustering routing protocols based on data aggregation schemes aimed at minimizing packet numbers have been proposed to meet these requirements. In clustering routing protocols, the cluster head plays an important role. The cluster head collects data from its member nodes and aggregates the collected data. To improve reliability and reduce recovery latency, we propose a checkpointing scheme for the cluster head. In the proposed scheme, backup nodes monitor and checkpoint the current state of the cluster head periodically. We also derive the checkpointing interval that maximizes reliability while using the same amount of energy consumed by clustering routing protocols that operate without checkpointing. Experimental comparisons with existing non-checkpointing schemes show that our scheme reduces both energy consumption and recovery latency.

NaNet: a configurable NIC bridging the gap between HPC and real-time HEP GPU computing

NASA Astrophysics Data System (ADS)

Lonardo, A.; Ameli, F.; Ammendola, R.; Biagioni, A.; Cotta Ramusino, A.; Fiorini, M.; Frezza, O.; Lamanna, G.; Lo Cicero, F.; Martinelli, M.; Neri, I.; Paolucci, P. S.; Pastorelli, E.; Pontisso, L.; Rossetti, D.; Simeone, F.; Simula, F.; Sozzi, M.; Tosoratto, L.; Vicini, P.

2015-04-01

NaNet is a FPGA-based PCIe Network Interface Card (NIC) design with GPUDirect and Remote Direct Memory Access (RDMA) capabilities featuring a configurable and extensible set of network channels. The design currently supports both standard—Gbe (1000BASE-T) and 10GbE (10Base-R)—and custom—34 Gbps APElink and 2.5 Gbps deterministic latency KM3link—channels, but its modularity allows for straightforward inclusion of other link technologies. The GPUDirect feature combined with a transport layer offload module and a data stream processing stage makes NaNet a low-latency NIC suitable for real-time GPU processing. In this paper we describe the NaNet architecture and its performances, exhibiting two of its use cases: the GPU-based low-level trigger for the RICH detector in the NA62 experiment at CERN and the on-/off-shore data transport system for the KM3NeT-IT underwater neutrino telescope.

A Smart Checkpointing Scheme for Improving the Reliability of Clustering Routing Protocols

PubMed Central

Min, Hong; Jung, Jinman; Kim, Bongjae; Cho, Yookun; Heo, Junyoung; Yi, Sangho; Hong, Jiman

2010-01-01

In wireless sensor networks, system architectures and applications are designed to consider both resource constraints and scalability, because such networks are composed of numerous sensor nodes with various sensors and actuators, small memories, low-power microprocessors, radio modules, and batteries. Clustering routing protocols based on data aggregation schemes aimed at minimizing packet numbers have been proposed to meet these requirements. In clustering routing protocols, the cluster head plays an important role. The cluster head collects data from its member nodes and aggregates the collected data. To improve reliability and reduce recovery latency, we propose a checkpointing scheme for the cluster head. In the proposed scheme, backup nodes monitor and checkpoint the current state of the cluster head periodically. We also derive the checkpointing interval that maximizes reliability while using the same amount of energy consumed by clustering routing protocols that operate without checkpointing. Experimental comparisons with existing non-checkpointing schemes show that our scheme reduces both energy consumption and recovery latency. PMID:22163389

Low latency network and distributed storage for next generation HPC systems: the ExaNeSt project

NASA Astrophysics Data System (ADS)

Ammendola, R.; Biagioni, A.; Cretaro, P.; Frezza, O.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Paolucci, P. S.; Pastorelli, E.; Pisani, F.; Simula, F.; Vicini, P.; Navaridas, J.; Chaix, F.; Chrysos, N.; Katevenis, M.; Papaeustathiou, V.

2017-10-01

With processor architecture evolution, the HPC market has undergone a paradigm shift. The adoption of low-cost, Linux-based clusters extended the reach of HPC from its roots in modelling and simulation of complex physical systems to a broader range of industries, from biotechnology, cloud computing, computer analytics and big data challenges to manufacturing sectors. In this perspective, the near future HPC systems can be envisioned as composed of millions of low-power computing cores, densely packed — meaning cooling by appropriate technology — with a tightly interconnected, low latency and high performance network and equipped with a distributed storage architecture. Each of these features — dense packing, distributed storage and high performance interconnect — represents a challenge, made all the harder by the need to solve them at the same time. These challenges lie as stumbling blocks along the road towards Exascale-class systems; the ExaNeSt project acknowledges them and tasks itself with investigating ways around them.

Node property of weighted networks considering connectability to nodes within two degrees of separation.

PubMed

Amano, Sun-Ichi; Ogawa, Ken-Ichiro; Miyake, Yoshihiro

2018-05-31

Weighted networks have been extensively studied because they can represent various phenomena in which the diversity of edges is essential. To investigate the properties of weighted networks, various centrality measures have been proposed, such as strength, weighted clustering coefficients, and weighted betweenness centrality. In such measures, only direct connections or entire network connectivity from arbitrary nodes have been used to calculate the connectivity of each node. However, in weighted networks composed of autonomous elements such as humans, middle ranges from each node are also considered to be meaningful for characterizing each node's connectability. In this study, we define a new node property in weighted networks to consider connectability to nodes within a range of two degrees of separation, then apply this new centrality to face-to-face human communication networks in corporate organizations. Our results show that the proposed centrality distinguishes inherent communities corresponding to the job types in each organization with a high degree of accuracy. This indicates the possibility that connectability to nodes within two degrees of separation reveals potential trends of weighted networks that are not apparent from conventional measures.

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

Code of Federal Regulations, 2010 CFR

2010-10-01

... network. 68.201 Section 68.201 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES (CONTINUED) CONNECTION OF TERMINAL EQUIPMENT TO THE TELEPHONE NETWORK Terminal Equipment Approval Procedures § 68.201 Connection to the public switched telephone network. Terminal equipment may...

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

Code of Federal Regulations, 2011 CFR

2011-10-01

... network. 68.201 Section 68.201 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES (CONTINUED) CONNECTION OF TERMINAL EQUIPMENT TO THE TELEPHONE NETWORK Terminal Equipment Approval Procedures § 68.201 Connection to the public switched telephone network. Terminal equipment may...

Intrinsic Amygdala-Cortical Functional Connectivity Predicts Social Network Size in Humans

PubMed Central

Bickart, Kevin C.; Hollenbeck, Mark C.; Barrett, Lisa Feldman; Dickerson, Bradford C.

2012-01-01

Using resting-state functional MRI data from two independent samples of healthy adults, we parsed the amygdala’s intrinsic connectivity into three partially-distinct large-scale networks that strongly resemble the known anatomical organization of amygdala connectivity in rodents and monkeys. Moreover, in a third independent sample, we discovered that people who fostered and maintained larger and more complex social networks not only had larger amygdala volumes, but also amygdalae with stronger intrinsic connectivity within two of these networks, one putatively subserving perceptual abilities and one subserving affiliative behaviors. Our findings were anatomically specific to amygdalar circuitry in that individual differences in social network size and complexity could not be explained by the strength of intrinsic connectivity between nodes within two networks that do not typically involve the amygdala (i.e., the mentalizing and mirror networks), and were behaviorally specific in that amygdala connectivity did not correlate with other self-report measures of sociality. PMID:23077058

Earthquake Complex Network applied along the Chilean Subduction Zone.

NASA Astrophysics Data System (ADS)

Martin, F.; Pasten, D.; Comte, D.

2017-12-01

In recent years the earthquake complex networks have been used as a useful tool to describe and characterize the behavior of seismicity. The earthquake complex network is built in space, dividing the three dimensional space in cubic cells. If the cubic cell contains a hypocenter, we call this cell like a node. The connections between nodes follows the time sequence of the occurrence of the seismic events. In this sense, we have a spatio-temporal configuration of a specific region using the seismicity in that zone. In this work, we are applying complex networks to characterize the subduction zone along the coast of Chile using two networks: a directed and an undirected network. The directed network takes in consideration the time-direction of the connections, that is very important for the connectivity of the network: we are considering the connectivity, ki of the i-th node, like the number of connections going out from the node i and we add the self-connections (if two seismic events occurred successive in time in the same cubic cell, we have a self-connection). The undirected network is the result of remove the direction of the connections and the self-connections from the directed network. These two networks were building using seismic data events recorded by CSN (Chilean Seismological Center) in Chile. This analysis includes the last largest earthquakes occurred in Iquique (April 2014) and in Illapel (September 2015). The result for the directed network shows a change in the value of the critical exponent along the Chilean coast. The result for the undirected network shows a small-world behavior without important changes in the topology of the network. Therefore, the complex network analysis shows a new form to characterize the Chilean subduction zone with a simple method that could be compared with another methods to obtain more details about the behavior of the seismicity in this region.

Patient-specific connectivity pattern of epileptic network in frontal lobe epilepsy

PubMed Central

Luo, Cheng; An, Dongmei; Yao, Dezhong; Gotman, Jean

2014-01-01

There is evidence that focal epilepsy may involve the dysfunction of a brain network in addition to the focal region. To delineate the characteristics of this epileptic network, we collected EEG/fMRI data from 23 patients with frontal lobe epilepsy. For each patient, EEG/fMRI analysis was first performed to determine the BOLD response to epileptic spikes. The maximum activation cluster in the frontal lobe was then chosen as the seed to identify the epileptic network in fMRI data. Functional connectivity analysis seeded at the same region was also performed in 63 healthy control subjects. Nine features were used to evaluate the differences of epileptic network patterns in three connection levels between patients and controls. Compared with control subjects, patients showed overall more functional connections between the epileptogenic region and the rest of the brain and higher laterality. However, the significantly increased connections were located in the neighborhood of the seed, but the connections between the seed and remote regions actually decreased. Comparing fMRI runs with interictal epileptic discharges (IEDs) and without IEDs, the patient-specific connectivity pattern was not changed significantly. These findings regarding patient-specific connectivity patterns of epileptic networks in FLE reflect local high connectivity and connections with distant regions differing from those of healthy controls. Moreover, the difference between the two groups in most features was observed in the strictest of the three connection levels. The abnormally high connectivity might reflect a predominant attribute of the epileptic network, which may facilitate propagation of epileptic activity among regions in the network. PMID:24936418

High-performance, scalable optical network-on-chip architectures

NASA Astrophysics Data System (ADS)

Tan, Xianfang

The rapid advance of technology enables a large number of processing cores to be integrated into a single chip which is called a Chip Multiprocessor (CMP) or a Multiprocessor System-on-Chip (MPSoC) design. The on-chip interconnection network, which is the communication infrastructure for these processing cores, plays a central role in a many-core system. With the continuously increasing complexity of many-core systems, traditional metallic wired electronic networks-on-chip (NoC) became a bottleneck because of the unbearable latency in data transmission and extremely high energy consumption on chip. Optical networks-on-chip (ONoC) has been proposed as a promising alternative paradigm for electronic NoC with the benefits of optical signaling communication such as extremely high bandwidth, negligible latency, and low power consumption. This dissertation focus on the design of high-performance and scalable ONoC architectures and the contributions are highlighted as follow: 1. A micro-ring resonator (MRR)-based Generic Wavelength-routed Optical Router (GWOR) is proposed. A method for developing any sized GWOR is introduced. GWOR is a scalable non-blocking ONoC architecture with simple structure, low cost and high power efficiency compared to existing ONoC designs. 2. To expand the bandwidth and improve the fault tolerance of the GWOR, a redundant GWOR architecture is designed by cascading different type of GWORs into one network. 3. The redundant GWOR built with MRR-based comb switches is proposed. Comb switches can expand the bandwidth while keep the topology of GWOR unchanged by replacing the general MRRs with comb switches. 4. A butterfly fat tree (BFT)-based hybrid optoelectronic NoC (HONoC) architecture is developed in which GWORs are used for global communication and electronic routers are used for local communication. The proposed HONoC uses less numbers of electronic routers and links than its counterpart of electronic BFT-based NoC. It takes the advantages of GWOR in optical communication and BFT in non-uniform traffic communication and three-dimension (3D) implementation. 5. A cycle-accurate NoC simulator is developed to evaluate the performance of proposed HONoC architectures. It is a comprehensive platform that can simulate both electronic and optical NoCs. Different size HONoC architectures are evaluated in terms of throughput, latency and energy dissipation. Simulation results confirm that HONoC achieves good network performance with lower power consumption.

Mobile Device Applications for the Visualization of Functional Connectivity Networks and EEG Electrodes: iBraiN and iBraiNEEG.

PubMed

Rojas, Gonzalo M; Fuentes, Jorge A; Gálvez, Marcelo

2016-01-01

Multiple functional MRI (fMRI)-based functional connectivity networks were obtained by Yeo et al. (2011), and the visualization of these complex networks is a difficult task. Also, the combination of functional connectivity networks determined by fMRI with electroencephalography (EEG) data could be a very useful tool. Mobile devices are becoming increasingly common among users, and for this reason, we describe here two applications for Android and iOS mobile devices: one that shows in an interactive way the seven Yeo functional connectivity networks, and another application that shows the relative position of 10-20 EEG electrodes with Yeo's seven functional connectivity networks.

Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing.

PubMed

Chhatwal, Jasmeer P; Schultz, Aaron P; Johnson, Keith A; Hedden, Trey; Jaimes, Sehily; Benzinger, Tammie L S; Jack, Clifford; Ances, Beau M; Ringman, John M; Marcus, Daniel S; Ghetti, Bernardino; Farlow, Martin R; Danek, Adrian; Levin, Johannes; Yakushev, Igor; Laske, Christoph; Koeppe, Robert A; Galasko, Douglas R; Xiong, Chengjie; Masters, Colin L; Schofield, Peter R; Kinnunen, Kirsi M; Salloway, Stephen; Martins, Ralph N; McDade, Eric; Cairns, Nigel J; Buckles, Virginia D; Morris, John C; Bateman, Randall; Sperling, Reisa A

2018-05-01

Converging evidence from structural, metabolic and functional connectivity MRI suggests that neurodegenerative diseases, such as Alzheimer's disease, target specific neural networks. However, age-related network changes commonly co-occur with neuropathological cascades, limiting efforts to disentangle disease-specific alterations in network function from those associated with normal ageing. Here we elucidate the differential effects of ageing and Alzheimer's disease pathology through simultaneous analyses of two functional connectivity MRI datasets: (i) young participants harbouring highly-penetrant mutations leading to autosomal-dominant Alzheimer's disease from the Dominantly Inherited Alzheimer's Network (DIAN), an Alzheimer's disease cohort in which age-related comorbidities are minimal and likelihood of progression along an Alzheimer's disease trajectory is extremely high; and (ii) young and elderly participants from the Harvard Aging Brain Study, a cohort in which imaging biomarkers of amyloid burden and neurodegeneration can be used to disambiguate ageing alone from preclinical Alzheimer's disease. Consonant with prior reports, we observed the preferential degradation of cognitive (especially the default and dorsal attention networks) over motor and sensory networks in early autosomal-dominant Alzheimer's disease, and found that this distinctive degradation pattern was magnified in more advanced stages of disease. Importantly, a nascent form of the pattern observed across the autosomal-dominant Alzheimer's disease spectrum was also detectable in clinically normal elderly with clear biomarker evidence of Alzheimer's disease pathology (preclinical Alzheimer's disease). At the more granular level of individual connections between node pairs, we observed that connections within cognitive networks were preferentially targeted in Alzheimer's disease (with between network connections relatively spared), and that connections between positively coupled nodes (correlations) were preferentially degraded as compared to connections between negatively coupled nodes (anti-correlations). In contrast, ageing in the absence of Alzheimer's disease biomarkers was characterized by a far less network-specific degradation across cognitive and sensory networks, of between- and within-network connections, and of connections between positively and negatively coupled nodes. We go on to demonstrate that formalizing the differential patterns of network degradation in ageing and Alzheimer's disease may have the practical benefit of yielding connectivity measurements that highlight early Alzheimer's disease-related connectivity changes over those due to age-related processes. Together, the contrasting patterns of connectivity in Alzheimer's disease and ageing add to prior work arguing against Alzheimer's disease as a form of accelerated ageing, and suggest multi-network composite functional connectivity MRI metrics may be useful in the detection of early Alzheimer's disease-specific alterations co-occurring with age-related connectivity changes. More broadly, our findings are consistent with a specific pattern of network degradation associated with the spreading of Alzheimer's disease pathology within targeted neural networks.

A friend request from dear old dad: associations between parent-child social networking and adolescent outcomes.

PubMed

Coyne, Sarah M; Padilla-Walker, Laura M; Day, Randal D; Harper, James; Stockdale, Laura

2014-01-01

This study examined the relationship between parent-child social networking, connection, and outcomes for adolescents. Participants (491 adolescents and their parents) completed a number of questionnaires on social networking use, feelings of connection, and behavioral outcomes. Social networking with parents was associated with increased connection between parents and adolescents. Feelings of connection then mediated the relationship between social networking with parents and behavioral outcomes, including higher prosocial behavior and lower relational aggression and internalizing behavior. Conversely, adolescent social networking use without parents was associated with negative outcomes, such as increased relational aggression, internalizing behaviors, delinquency, and decreased feelings of connection. These results indicate that although high levels of social networking use may be problematic for some individuals, social networking with parents may potentially strengthen parent-child relationships and then lead to positive outcomes for adolescents.

Maintaining Limited-Range Connectivity Among Second-Order Agents

DTIC Science & Technology

2016-07-07

we consider ad-hoc networks of robotic agents with double integrator dynamics. For such networks, the connectivity maintenance problems are: (i) do...hoc networks of mobile autonomous agents. This loose ter- minology refers to groups of robotic agents with limited mobility and communica- tion...connectivity can be preserved. 3.1. Networks of robotic agents with second-order dynamics and the connectivity maintenance problem. We begin by

Coherent periodic activity in excitatory Erdös-Renyi neural networks: the role of network connectivity.

PubMed

Tattini, Lorenzo; Olmi, Simona; Torcini, Alessandro

2012-06-01

In this article, we investigate the role of connectivity in promoting coherent activity in excitatory neural networks. In particular, we would like to understand if the onset of collective oscillations can be related to a minimal average connectivity and how this critical connectivity depends on the number of neurons in the networks. For these purposes, we consider an excitatory random network of leaky integrate-and-fire pulse coupled neurons. The neurons are connected as in a directed Erdös-Renyi graph with average connectivity scaling as a power law with the number of neurons in the network. The scaling is controlled by a parameter γ, which allows to pass from massively connected to sparse networks and therefore to modify the topology of the system. At a macroscopic level, we observe two distinct dynamical phases: an asynchronous state corresponding to a desynchronized dynamics of the neurons and a regime of partial synchronization (PS) associated with a coherent periodic activity of the network. At low connectivity, the system is in an asynchronous state, while PS emerges above a certain critical average connectivity (c). For sufficiently large networks, (c) saturates to a constant value suggesting that a minimal average connectivity is sufficient to observe coherent activity in systems of any size irrespectively of the kind of considered network: sparse or massively connected. However, this value depends on the nature of the synapses: reliable or unreliable. For unreliable synapses, the critical value required to observe the onset of macroscopic behaviors is noticeably smaller than for reliable synaptic transmission. Due to the disorder present in the system, for finite number of neurons we have inhomogeneities in the neuronal behaviors, inducing a weak form of chaos, which vanishes in the thermodynamic limit. In such a limit, the disordered systems exhibit regular (non chaotic) dynamics and their properties correspond to that of a homogeneous fully connected network for any γ-value. Apart for the peculiar exception of sparse networks, which remain intrinsically inhomogeneous at any system size.

Altered intrinsic and extrinsic connectivity in schizophrenia.

PubMed

Zhou, Yuan; Zeidman, Peter; Wu, Shihao; Razi, Adeel; Chen, Cheng; Yang, Liuqing; Zou, Jilin; Wang, Gaohua; Wang, Huiling; Friston, Karl J

2018-01-01

Schizophrenia is a disorder characterized by functional dysconnectivity among distributed brain regions. However, it is unclear how causal influences among large-scale brain networks are disrupted in schizophrenia. In this study, we used dynamic causal modeling (DCM) to assess the hypothesis that there is aberrant directed (effective) connectivity within and between three key large-scale brain networks (the dorsal attention network, the salience network and the default mode network) in schizophrenia during a working memory task. Functional MRI data during an n-back task from 40 patients with schizophrenia and 62 healthy controls were analyzed. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes, we found that intrinsic (within-region) and extrinsic (between-region) effective connectivity involving prefrontal regions were abnormal in schizophrenia. Specifically, in patients (i) inhibitory self-connections in prefrontal regions of the dorsal attention network were decreased across task conditions; (ii) extrinsic connectivity between regions of the default mode network was increased; specifically, from posterior cingulate cortex to the medial prefrontal cortex; (iii) between-network extrinsic connections involving the prefrontal cortex were altered; (iv) connections within networks and between networks were correlated with the severity of clinical symptoms and impaired cognition beyond working memory. In short, this study revealed the predominance of reduced synaptic efficacy of prefrontal efferents and afferents in the pathophysiology of schizophrenia.

Large-Scale Hypoconnectivity Between Resting-State Functional Networks in Unmedicated Adolescent Major Depressive Disorder.

PubMed

Sacchet, Matthew D; Ho, Tiffany C; Connolly, Colm G; Tymofiyeva, Olga; Lewinn, Kaja Z; Han, Laura Km; Blom, Eva H; Tapert, Susan F; Max, Jeffrey E; Frank, Guido Kw; Paulus, Martin P; Simmons, Alan N; Gotlib, Ian H; Yang, Tony T

2016-11-01

Major depressive disorder (MDD) often emerges during adolescence, a critical period of brain development. Recent resting-state fMRI studies of adults suggest that MDD is associated with abnormalities within and between resting-state networks (RSNs). Here we tested whether adolescent MDD is characterized by abnormalities in interactions among RSNs. Participants were 55 unmedicated adolescents diagnosed with MDD and 56 matched healthy controls. Functional connectivity was mapped using resting-state fMRI. We used the network-based statistic (NBS) to compare large-scale connectivity between groups and also compared the groups on graph metrics. We further assessed whether group differences identified using nodes defined from functionally defined RSNs were also evident when using anatomically defined nodes. In addition, we examined relations between network abnormalities and depression severity and duration. Finally, we compared intranetwork connectivity between groups and assessed the replication of previously reported MDD-related abnormalities in connectivity. The NBS indicated that, compared with controls, depressed adolescents exhibited reduced connectivity (p<0.024, corrected) between a specific set of RSNs, including components of the attention, central executive, salience, and default mode networks. The NBS did not identify group differences in network connectivity when using anatomically defined nodes. Longer duration of depression was significantly correlated with reduced connectivity in this set of network interactions (p=0.020, corrected), specifically with reduced connectivity between components of the dorsal attention network. The dorsal attention network was also characterized by reduced intranetwork connectivity in the MDD group. Finally, we replicated previously reported abnormal connectivity in individuals with MDD. In summary, adolescents with MDD show hypoconnectivity between large-scale brain networks compared with healthy controls. Given that connectivity among these networks typically increases during adolescent neurodevelopment, these results suggest that adolescent depression is associated with abnormalities in neural systems that are still developing during this critical period.

Large-Scale Hypoconnectivity Between Resting-State Functional Networks in Unmedicated Adolescent Major Depressive Disorder

PubMed Central

Sacchet, Matthew D; Ho, Tiffany C; Connolly, Colm G; Tymofiyeva, Olga; Lewinn, Kaja Z; Han, Laura KM; Blom, Eva H; Tapert, Susan F; Max, Jeffrey E; Frank, Guido KW; Paulus, Martin P; Simmons, Alan N; Gotlib, Ian H; Yang, Tony T

2016-01-01

Major depressive disorder (MDD) often emerges during adolescence, a critical period of brain development. Recent resting-state fMRI studies of adults suggest that MDD is associated with abnormalities within and between resting-state networks (RSNs). Here we tested whether adolescent MDD is characterized by abnormalities in interactions among RSNs. Participants were 55 unmedicated adolescents diagnosed with MDD and 56 matched healthy controls. Functional connectivity was mapped using resting-state fMRI. We used the network-based statistic (NBS) to compare large-scale connectivity between groups and also compared the groups on graph metrics. We further assessed whether group differences identified using nodes defined from functionally defined RSNs were also evident when using anatomically defined nodes. In addition, we examined relations between network abnormalities and depression severity and duration. Finally, we compared intranetwork connectivity between groups and assessed the replication of previously reported MDD-related abnormalities in connectivity. The NBS indicated that, compared with controls, depressed adolescents exhibited reduced connectivity (p<0.024, corrected) between a specific set of RSNs, including components of the attention, central executive, salience, and default mode networks. The NBS did not identify group differences in network connectivity when using anatomically defined nodes. Longer duration of depression was significantly correlated with reduced connectivity in this set of network interactions (p=0.020, corrected), specifically with reduced connectivity between components of the dorsal attention network. The dorsal attention network was also characterized by reduced intranetwork connectivity in the MDD group. Finally, we replicated previously reported abnormal connectivity in individuals with MDD. In summary, adolescents with MDD show hypoconnectivity between large-scale brain networks compared with healthy controls. Given that connectivity among these networks typically increases during adolescent neurodevelopment, these results suggest that adolescent depression is associated with abnormalities in neural systems that are still developing during this critical period. PMID:27238621

Simulating synchronization in neuronal networks

NASA Astrophysics Data System (ADS)

Fink, Christian G.

2016-06-01

We discuss several techniques used in simulating neuronal networks by exploring how a network's connectivity structure affects its propensity for synchronous spiking. Network connectivity is generated using the Watts-Strogatz small-world algorithm, and two key measures of network structure are described. These measures quantify structural characteristics that influence collective neuronal spiking, which is simulated using the leaky integrate-and-fire model. Simulations show that adding a small number of random connections to an otherwise lattice-like connectivity structure leads to a dramatic increase in neuronal synchronization.

Brain network dysregulation, emotion, and complaints after mild traumatic brain injury.

PubMed

van der Horn, Harm J; Liemburg, Edith J; Scheenen, Myrthe E; de Koning, Myrthe E; Marsman, Jan-Bernard C; Spikman, Jacoba M; van der Naalt, Joukje

2016-04-01

To assess the role of brain networks in emotion regulation and post-traumatic complaints in the sub-acute phase after non-complicated mild traumatic brain injury (mTBI). Fifty-four patients with mTBI (34 with and 20 without complaints) and 20 healthy controls (group-matched for age, sex, education, and handedness) were included. Resting-state fMRI was performed at four weeks post-injury. Static and dynamic functional connectivity were studied within and between the default mode, executive (frontoparietal and bilateral frontal network), and salience network. The hospital anxiety and depression scale (HADS) was used to measure anxiety (HADS-A) and depression (HADS-D). Regarding within-network functional connectivity, none of the selected brain networks were different between groups. Regarding between-network interactions, patients with complaints exhibited lower functional connectivity between the bilateral frontal and salience network compared to patients without complaints. In the total patient group, higher HADS-D scores were related to lower functional connectivity between the bilateral frontal network and both the right frontoparietal and salience network, and to higher connectivity between the right frontoparietal and salience network. Furthermore, whereas higher HADS-D scores were associated with lower connectivity within the parietal midline areas of the bilateral frontal network, higher HADS-A scores were related to lower connectivity within medial prefrontal areas of the bilateral frontal network. Functional interactions of the executive and salience networks were related to emotion regulation and complaints after mTBI, with a key role for the bilateral frontal network. These findings may have implications for future studies on the effect of psychological interventions. © 2016 Wiley Periodicals, Inc.

Reciprocity in spatial evolutionary public goods game on double-layered network

NASA Astrophysics Data System (ADS)

Kim, Jinho; Yook, Soon-Hyung; Kim, Yup

2016-08-01

Spatial evolutionary games have mainly been studied on a single, isolated network. However, in real world systems, many interaction topologies are not isolated but many different types of networks are inter-connected to each other. In this study, we investigate the spatial evolutionary public goods game (SEPGG) on double-layered random networks (DRN). Based on the mean-field type arguments and numerical simulations, we find that SEPGG on DRN shows very rich interesting phenomena, especially, depending on the size of each layer, intra-connectivity, and inter-connected couplings, the network reciprocity of SEPGG on DRN can be drastically enhanced through the inter-connected coupling. Furthermore, SEPGG on DRN can provide a more general framework which includes the evolutionary dynamics on multiplex networks and inter-connected networks at the same time.

Reciprocity in spatial evolutionary public goods game on double-layered network

PubMed Central

Kim, Jinho; Yook, Soon-Hyung; Kim, Yup

2016-01-01

Spatial evolutionary games have mainly been studied on a single, isolated network. However, in real world systems, many interaction topologies are not isolated but many different types of networks are inter-connected to each other. In this study, we investigate the spatial evolutionary public goods game (SEPGG) on double-layered random networks (DRN). Based on the mean-field type arguments and numerical simulations, we find that SEPGG on DRN shows very rich interesting phenomena, especially, depending on the size of each layer, intra-connectivity, and inter-connected couplings, the network reciprocity of SEPGG on DRN can be drastically enhanced through the inter-connected coupling. Furthermore, SEPGG on DRN can provide a more general framework which includes the evolutionary dynamics on multiplex networks and inter-connected networks at the same time. PMID:27503801

An adaptive transmission protocol for managing dynamic shared states in collaborative surgical simulation.

PubMed

Qin, J; Choi, K S; Ho, Simon S M; Heng, P A

2008-01-01

A force prediction algorithm is proposed to facilitate virtual-reality (VR) based collaborative surgical simulation by reducing the effect of network latencies. State regeneration is used to correct the estimated prediction. This algorithm is incorporated into an adaptive transmission protocol in which auxiliary features such as view synchronization and coupling control are equipped to ensure the system consistency. We implemented this protocol using multi-threaded technique on a cluster-based network architecture.

White-matter functional networks changes in patients with schizophrenia.

PubMed

Jiang, Yuchao; Luo, Cheng; Li, Xuan; Li, Yingjia; Yang, Hang; Li, Jianfu; Chang, Xin; Li, Hechun; Yang, Huanghao; Wang, Jijun; Duan, Mingjun; Yao, Dezhong

2018-04-13

Resting-state functional MRI (rsfMRI) is a useful technique for investigating the functional organization of human gray-matter in neuroscience and neuropsychiatry. Nevertheless, most studies have demonstrated the functional connectivity and/or task-related functional activity in the gray-matter. White-matter functional networks have been investigated in healthy subjects. Schizophrenia has been hypothesized to be a brain disorder involving insufficient or ineffective communication associated with white-matter abnormalities. However, previous studies have mainly examined the structural architecture of white-matter using MRI or diffusion tensor imaging and failed to uncover any dysfunctional connectivity within the white-matter on rsfMRI. The current study used rsfMRI to evaluate white-matter functional connectivity in a large cohort of ninety-seven schizophrenia patients and 126 healthy controls. Ten large-scale white-matter networks were identified by a cluster analysis of voxel-based white-matter functional connectivity and classified into superficial, middle and deep layers of networks. Evaluation of the spontaneous oscillation of white-matter networks and the functional connectivity between them showed that patients with schizophrenia had decreased amplitudes of low-frequency oscillation and increased functional connectivity in the superficial perception-motor networks. Additionally, we examined the interactions between white-matter and gray-matter networks. The superficial perception-motor white-matter network had decreased functional connectivity with the cortical perception-motor gray-matter networks. In contrast, the middle and deep white-matter networks had increased functional connectivity with the superficial perception-motor white-matter network and the cortical perception-motor gray-matter network. Thus, we presumed that the disrupted association between the gray-matter and white-matter networks in the perception-motor system may be compensated for through the middle-deep white-matter networks, which may be the foundation of the extensively disrupted connections in schizophrenia. Copyright © 2018 Elsevier Inc. All rights reserved.

Topologically invariant macroscopic statistics in balanced networks of conductance-based integrate-and-fire neurons.

PubMed

Yger, Pierre; El Boustani, Sami; Destexhe, Alain; Frégnac, Yves

2011-10-01

The relationship between the dynamics of neural networks and their patterns of connectivity is far from clear, despite its importance for understanding functional properties. Here, we have studied sparsely-connected networks of conductance-based integrate-and-fire (IF) neurons with balanced excitatory and inhibitory connections and with finite axonal propagation speed. We focused on the genesis of states with highly irregular spiking activity and synchronous firing patterns at low rates, called slow Synchronous Irregular (SI) states. In such balanced networks, we examined the "macroscopic" properties of the spiking activity, such as ensemble correlations and mean firing rates, for different intracortical connectivity profiles ranging from randomly connected networks to networks with Gaussian-distributed local connectivity. We systematically computed the distance-dependent correlations at the extracellular (spiking) and intracellular (membrane potential) levels between randomly assigned pairs of neurons. The main finding is that such properties, when they are averaged at a macroscopic scale, are invariant with respect to the different connectivity patterns, provided the excitatory-inhibitory balance is the same. In particular, the same correlation structure holds for different connectivity profiles. In addition, we examined the response of such networks to external input, and found that the correlation landscape can be modulated by the mean level of synchrony imposed by the external drive. This modulation was found again to be independent of the external connectivity profile. We conclude that first and second-order "mean-field" statistics of such networks do not depend on the details of the connectivity at a microscopic scale. This study is an encouraging step toward a mean-field description of topological neuronal networks.

Bimanual Motor Coordination in Older Adults Is Associated with Increased Functional Brain Connectivity – A Graph-Theoretical Analysis

PubMed Central

Heitger, Marcus H.; Goble, Daniel J.; Dhollander, Thijs; Dupont, Patrick; Caeyenberghs, Karen; Leemans, Alexander; Sunaert, Stefan; Swinnen, Stephan P.

2013-01-01

In bimanual coordination, older and younger adults activate a common cerebral network but the elderly also have additional activation in a secondary network of brain areas to master task performance. It remains unclear whether the functional connectivity within these primary and secondary motor networks differs between the old and the young and whether task difficulty modulates connectivity. We applied graph-theoretical network analysis (GTNA) to task-driven fMRI data in 16 elderly and 16 young participants using a bimanual coordination task including in-phase and anti-phase flexion/extension wrist movements. Network nodes for the GTNA comprised task-relevant brain areas as defined by fMRI activation foci. The elderly matched the motor performance of the young but showed an increased functional connectivity in both networks across a wide range of connectivity metrics, i.e., higher mean connectivity degree, connection strength, network density and efficiency, together with shorter mean communication path length between the network nodes and also a lower betweenness centrality. More difficult movements showed an increased connectivity in both groups. The network connectivity of both groups had “small world” character. The present findings indicate (a) that bimanual coordination in the aging brain is associated with a higher functional connectivity even between areas also activated in young adults, independently from task difficulty, and (b) that adequate motor coordination in the context of task-driven bimanual control in older adults may not be solely due to additional neural recruitment but also to aging-related changes of functional relationships between brain regions. PMID:23637982

Resting-State Connectivity of the Left Frontal Cortex to the Default Mode and Dorsal Attention Network Supports Reserve in Mild Cognitive Impairment.

PubMed

Franzmeier, Nicolai; Göttler, Jens; Grimmer, Timo; Drzezga, Alexander; Áraque-Caballero, Miguel A; Simon-Vermot, Lee; Taylor, Alexander N W; Bürger, Katharina; Catak, Cihan; Janowitz, Daniel; Müller, Claudia; Duering, Marco; Sorg, Christian; Ewers, Michael

2017-01-01

Reserve refers to the phenomenon of relatively preserved cognition in disproportion to the extent of neuropathology, e.g., in Alzheimer's disease. A putative functional neural substrate underlying reserve is global functional connectivity of the left lateral frontal cortex (LFC, Brodmann Area 6/44). Resting-state fMRI-assessed global LFC-connectivity is associated with protective factors (education) and better maintenance of memory in mild cognitive impairment (MCI). Since the LFC is a hub of the fronto-parietal control network that regulates the activity of other networks, the question arises whether LFC-connectivity to specific networks rather than the whole-brain may underlie reserve. We assessed resting-state fMRI in 24 MCI and 16 healthy controls (HC) and in an independent validation sample (23 MCI/32 HC). Seed-based LFC-connectivity to seven major resting-state networks (i.e., fronto-parietal, limbic, dorsal-attention, somatomotor, default-mode, ventral-attention, visual) was computed, reserve was quantified as residualized memory performance after accounting for age and hippocampal atrophy. In both samples of MCI, LFC-activity was anti-correlated with the default-mode network (DMN), but positively correlated with the dorsal-attention network (DAN). Greater education predicted stronger LFC-DMN-connectivity (anti-correlation) and LFC-DAN-connectivity. Stronger LFC-DMN and LFC-DAN-connectivity each predicted higher reserve, consistently in both MCI samples. No associations were detected for LFC-connectivity to other networks. These novel results extend our previous findings on global functional connectivity of the LFC, showing that LFC-connectivity specifically to the DAN and DMN, two core memory networks, enhances reserve in the memory domain in MCI.

Development of large-scale functional brain networks in children.

PubMed

Supekar, Kaustubh; Musen, Mark; Menon, Vinod

2009-07-01

The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y) and 22 young-adults (ages 19-22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

Development of Large-Scale Functional Brain Networks in Children

PubMed Central

Supekar, Kaustubh; Musen, Mark; Menon, Vinod

2009-01-01

The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7–9 y) and 22 young-adults (ages 19–22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar “small-world” organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism. PMID:19621066

Intrinsic network connectivity and own body perception in gender dysphoria.

PubMed

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.

Nonrandom network connectivity comes in pairs.

PubMed

Hoffmann, Felix Z; Triesch, Jochen

2017-01-01

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, P ij = P ji , 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.

Epigenetic Principles and Mechanisms Underlying Nervous System Functions in Health and Disease

PubMed Central

Mehler, Mark F.

2009-01-01

Epigenetics and epigenomic medicine encompass a new science of brain and behavior that are already providing unique insights into the mechanisms underlying brain development, evolution, neuronal and network plasticity and homeostasis, senescence, the etiology of diverse neurological diseases and neural regenerative processes. Epigenetic mechanisms include DNA methylation, histone modifications, nucleosome repositioning, higher-order chromatin remodeling, non-coding RNAs, and RNA and DNA editing. RNA is centrally involved in directing these processes, implying that the transcriptional state of the cell is the primary determinant of epigenetic memory. This transcriptional state can be modified by internal and external cues affecting gene expression and post-transcriptional processing, but also by RNA and DNA editing through activity-dependent intracellular transport and modulation of RNAs and RNA regulatory supercomplexes, and through trans-neuronal and systemic trafficking of functional RNA subclasses. These integrated processes promote dynamic reorganization of nuclear architecture and the genomic landscape to modulate functional gene and neural networks with complex temporal and spatial trajectories. Epigenetics represents the long sought after molecular interface mediating gene-environmental interactions during critical periods throughout the lifecycle. The discipline of environmental epigenomics has begun to identify combinatorial profiles of environmental stressors modulating the latency, initiation and progression of specific neurological disorders, and more selective disease biomarkers and graded molecular responses to emerging therapeutic interventions. Pharmacoepigenomic therapies will promote accelerated recovery of impaired and seemingly irrevocably lost cognitive, behavioral, sensorimotor functions through epigenetic reprogramming of endogenous regional neural stem cell fate decisions, targeted tissue remodeling and restoration of neural network integrity, plasticity and connectivity. PMID:18940229

Interhemispheric Functional Brain Connectivity in Neonates with Prenatal Alcohol Exposure: Preliminary Findings.

PubMed

Donald, Kirsten A; Ipser, Jonathan C; Howells, Fleur M; Roos, Annerine; Fouche, Jean-Paul; Riley, Edward P; Koen, Nastassja; Woods, Roger P; Biswal, Bharat; Zar, Heather J; Narr, Katherine L; Stein, Dan J

2016-01-01

Children exposed to alcohol in utero demonstrate reduced white matter microstructural integrity. While early evidence suggests altered functional brain connectivity in the lateralization of motor networks in school-age children with prenatal alcohol exposure (PAE), the specific effects of alcohol exposure on the establishment of intrinsic connectivity in early infancy have not been explored. Sixty subjects received functional imaging at 2 to 4 weeks of age for 6 to 8 minutes during quiet natural sleep. Thirteen alcohol-exposed (PAE) and 14 age-matched control (CTRL) participants with usable data were included in a multivariate model of connectivity between sensorimotor intrinsic functional connectivity networks. Seed-based analyses of group differences in interhemispheric connectivity of intrinsic motor networks were also conducted. The Dubowitz neurological assessment was performed at the imaging visit. Alcohol exposure was associated with significant increases in connectivity between somatosensory, motor networks, brainstem/thalamic, and striatal intrinsic networks. Reductions in interhemispheric connectivity of motor and somatosensory networks did not reach significance. Although results are preliminary, findings suggest PAE may disrupt the temporal coherence in blood oxygenation utilization in intrinsic networks underlying motor performance in newborn infants. Studies that employ longitudinal designs to investigate the effects of in utero alcohol exposure on the evolving resting-state networks will be key in establishing the distribution and timing of connectivity disturbances already described in older children. Copyright © 2016 by the Research Society on Alcoholism.

The Anatomical Distance of Functional Connections Predicts Brain Network Topology in Health and Schizophrenia

PubMed Central

Vértes, Petra E.; Stidd, Reva; Lalonde, François; Clasen, Liv; Rapoport, Judith; Giedd, Jay; Bullmore, Edward T.; Gogtay, Nitin

2013-01-01

The human brain is a topologically complex network embedded in anatomical space. Here, we systematically explored relationships between functional connectivity, complex network topology, and anatomical (Euclidean) distance between connected brain regions, in the resting-state functional magnetic resonance imaging brain networks of 20 healthy volunteers and 19 patients with childhood-onset schizophrenia (COS). Normal between-subject differences in average distance of connected edges in brain graphs were strongly associated with variation in topological properties of functional networks. In addition, a club or subset of connector hubs was identified, in lateral temporal, parietal, dorsal prefrontal, and medial prefrontal/cingulate cortical regions. In COS, there was reduced strength of functional connectivity over short distances especially, and therefore, global mean connection distance of thresholded graphs was significantly greater than normal. As predicted from relationships between spatial and topological properties of normal networks, this disorder-related proportional increase in connection distance was associated with reduced clustering and modularity and increased global efficiency of COS networks. Between-group differences in connection distance were localized specifically to connector hubs of multimodal association cortex. In relation to the neurodevelopmental pathogenesis of schizophrenia, we argue that the data are consistent with the interpretation that spatial and topological disturbances of functional network organization could arise from excessive “pruning” of short-distance functional connections in schizophrenia. PMID:22275481

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

NASA Astrophysics Data System (ADS)

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.

An indirect component in the evoked compound action potential of the vagal nerve.

PubMed

Ordelman, Simone C M A; Kornet, Lilian; Cornelussen, Richard; Buschman, Hendrik P J; Veltink, Peter H

2010-12-01

The vagal nerve plays a vital role in the regulation of the cardiovascular system. It not only regulates the heart but also sends sensory information from the heart back to the brain. We hypothesize that the evoked vagal nerve compound action potential contains components that are indirect via the brain stem or coming via the neural network on the heart. In an experimental study of 15 pigs, we identified four components in the evoked compound action potentials. The fourth component was found to be an indirect component, which came from the periphery. The latency of the indirect component increased when heart rate and contractility were decreased by burst stimulation (P = 0.01; n = 7). When heart rate and contractility were increased by dobutamine administration, the latency of the indirect component decreased (P = 0.01; n = 9). This showed that the latency of the indirect component of the evoked compound action potentials may relate to the state of the cardiovascular system.

Electrophysiological signatures of atypical intrinsic brain connectivity networks in autism

NASA Astrophysics Data System (ADS)

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.

Evaluation of a Cyber Security System for Hospital Network.

PubMed

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.

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network.

PubMed

Guo, Hao; Qin, Mengna; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional methods for processing high-order functional connectivity networks generally include the clustering method, which reduces data dimensionality. As a result, such networks cannot be effectively interpreted in the context of neurology. Additionally, due to the large scale of high-order functional connectivity networks, it can be computationally very expensive to use complex network or graph theory to calculate certain topological properties. Here, we propose a novel method of generating a high-order minimum spanning tree functional connectivity network. This method increases the neurological significance of the high-order functional connectivity network, reduces network computing consumption, and produces a network scale that is conducive to subsequent network analysis. To ensure the quality of the topological information in the network structure, we used frequent subgraph mining technology to capture the discriminative subnetworks as features and combined this with quantifiable local network features. Then we applied a multikernel learning technique to the corresponding selected features to obtain the final classification results. We evaluated our proposed method using a data set containing 38 patients with major depressive disorder and 28 healthy controls. The experimental results showed a classification accuracy of up to 97.54%.

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network

PubMed Central

Qin, Mengna; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional methods for processing high-order functional connectivity networks generally include the clustering method, which reduces data dimensionality. As a result, such networks cannot be effectively interpreted in the context of neurology. Additionally, due to the large scale of high-order functional connectivity networks, it can be computationally very expensive to use complex network or graph theory to calculate certain topological properties. Here, we propose a novel method of generating a high-order minimum spanning tree functional connectivity network. This method increases the neurological significance of the high-order functional connectivity network, reduces network computing consumption, and produces a network scale that is conducive to subsequent network analysis. To ensure the quality of the topological information in the network structure, we used frequent subgraph mining technology to capture the discriminative subnetworks as features and combined this with quantifiable local network features. Then we applied a multikernel learning technique to the corresponding selected features to obtain the final classification results. We evaluated our proposed method using a data set containing 38 patients with major depressive disorder and 28 healthy controls. The experimental results showed a classification accuracy of up to 97.54%. PMID:29387141

Topographical maps as complex networks

NASA Astrophysics Data System (ADS)

da Fontoura Costa, Luciano; Diambra, Luis

2005-02-01

The neuronal networks in the mammalian cortex are characterized by the coexistence of hierarchy, modularity, short and long range interactions, spatial correlations, and topographical connections. Particularly interesting, the latter type of organization implies special demands on developing systems in order to achieve precise maps preserving spatial adjacencies, even at the expense of isometry. Although the object of intensive biological research, the elucidation of the main anatomic-functional purposes of the ubiquitous topographical connections in the mammalian brain remains an elusive issue. The present work reports on how recent results from complex network formalism can be used to quantify and model the effect of topographical connections between neuronal cells over the connectivity of the network. While the topographical mapping between two cortical modules is achieved by connecting nearest cells from each module, four kinds of network models are adopted for implementing intramodular connections, including random, preferential-attachment, short-range, and long-range networks. It is shown that, though spatially uniform and simple, topographical connections between modules can lead to major changes in the network properties in some specific cases, depending on intramodular connections schemes, fostering more effective intercommunication between the involved neuronal cells and modules. The possible implications of such effects on cortical operation are discussed.

Surname complex network for Brazil and Portugal

NASA Astrophysics Data System (ADS)

Ferreira, G. D.; Viswanathan, G. M.; da Silva, L. R.; Herrmann, H. J.

2018-06-01

We present a study of social networks based on the analysis of Brazilian and Portuguese family names (surnames). We construct networks whose nodes are names of families and whose edges represent parental relations between two families. From these networks we extract the connectivity distribution, clustering coefficient, shortest path and centrality. We find that the connectivity distribution follows an approximate power law. We associate the number of hubs, centrality and entropy to the degree of miscegenation in the societies in both countries. Our results show that Portuguese society has a higher miscegenation degree than Brazilian society. All networks analyzed lead to approximate inverse square power laws in the degree distribution. We conclude that the thermodynamic limit is reached for small networks (3 or 4 thousand nodes). The assortative mixing of all networks is negative, showing that the more connected vertices are connected to vertices with lower connectivity. Finally, the network of surnames presents some small world characteristics.

Transport Protocols for Wireless Mesh Networks

NASA Astrophysics Data System (ADS)

Eddie Law, K. L.

Transmission control protocol (TCP) provides reliable connection-oriented services between any two end systems on the Internet. With TCP congestion control algorithm, multiple TCP connections can share network and link resources simultaneously. These TCP congestion control mechanisms have been operating effectively in wired networks. However, performance of TCP connections degrades rapidly in wireless and lossy networks. To sustain the throughput performance of TCP connections in wireless networks, design modifications may be required accordingly in the TCP flow control algorithm, and potentially, in association with other protocols in other layers for proper adaptations. In this chapter, we explain the limitations of the latest TCP congestion control algorithm, and then review some popular designs for TCP connections to operate effectively in wireless mesh network infrastructure.

Mobile Device Applications for the Visualization of Functional Connectivity Networks and EEG Electrodes: iBraiN and iBraiNEEG

PubMed Central

Rojas, Gonzalo M.; Fuentes, Jorge A.; Gálvez, Marcelo

2016-01-01

Multiple functional MRI (fMRI)-based functional connectivity networks were obtained by Yeo et al. (2011), and the visualization of these complex networks is a difficult task. Also, the combination of functional connectivity networks determined by fMRI with electroencephalography (EEG) data could be a very useful tool. Mobile devices are becoming increasingly common among users, and for this reason, we describe here two applications for Android and iOS mobile devices: one that shows in an interactive way the seven Yeo functional connectivity networks, and another application that shows the relative position of 10–20 EEG electrodes with Yeo’s seven functional connectivity networks. PMID:27807416

Resting-State Network Topology Differentiates Task Signals across the Adult Life Span.

PubMed

Chan, Micaela Y; Alhazmi, Fahd H; Park, Denise C; Savalia, Neil K; Wig, Gagan S

2017-03-08

Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20-89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system ("non-connector" nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems ("connector" nodes). This "activation selectivity" was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the "dedifferentiation" in brain activity observed in aging. SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across individuals, we hypothesized that individual differences in network connectivity would relate to differences in brain activity. Using functional MRI in a group of individuals sampled across the adult life span (20-89 years), we measured correlations at rest and related the functional connectivity patterns to measurements of functional activity during two independent tasks. Brain activity varied in relation to connectivity patterns revealed by large-scale network analysis. This relationship tracked the differences in connectivity patterns accompanied by older age, providing important evidence for a link between the topology of areal connectivity measured at rest and the functional recruitment of these areas during task performance. Copyright © 2017 Chan et al.

Link-quality measurement and reporting in wireless sensor networks.

PubMed

Chehri, Abdellah; Jeon, Gwanggil; Choi, Byoungjo

2013-03-04

Wireless Sensor networks (WSNs) are created by small hardware devices that possess the necessary functionalities to measure and exchange a variety of environmental data in their deployment setting. In this paper, we discuss the experiments in deploying a testbed as a first step towards creating a fully functional heterogeneous wireless network-based underground monitoring system. The system is mainly composed of mobile and static ZigBee nodes, which are deployed on the underground mine galleries for measuring ambient temperature. In addition, we describe the measured results of link characteristics such as received signal strength, latency and throughput for different scenarios.

Link-Quality Measurement and Reporting in Wireless Sensor Networks

PubMed Central

Chehri, Abdellah; Jeon, Gwanggil; Choi, Byoungjo

2013-01-01

Wireless Sensor networks (WSNs) are created by small hardware devices that possess the necessary functionalities to measure and exchange a variety of environmental data in their deployment setting. In this paper, we discuss the experiments in deploying a testbed as a first step towards creating a fully functional heterogeneous wireless network-based underground monitoring system. The system is mainly composed of mobile and static ZigBee nodes, which are deployed on the underground mine galleries for measuring ambient temperature. In addition, we describe the measured results of link characteristics such as received signal strength, latency and throughput for different scenarios. PMID:23459389

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

PubMed

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

2011-10-01

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

Population coding in sparsely connected networks of noisy neurons.

PubMed

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.

HTMT-class Latency Tolerant Parallel Architecture for Petaflops Scale Computation

NASA Technical Reports Server (NTRS)

Sterling, Thomas; Bergman, Larry

2000-01-01

Computational Aero Sciences and other numeric intensive computation disciplines demand computing throughputs substantially greater than the Teraflops scale systems only now becoming available. The related fields of fluids, structures, thermal, combustion, and dynamic controls are among the interdisciplinary areas that in combination with sufficient resolution and advanced adaptive techniques may force performance requirements towards Petaflops. This will be especially true for compute intensive models such as Navier-Stokes are or when such system models are only part of a larger design optimization computation involving many design points. Yet recent experience with conventional MPP configurations comprising commodity processing and memory components has shown that larger scale frequently results in higher programming difficulty and lower system efficiency. While important advances in system software and algorithms techniques have had some impact on efficiency and programmability for certain classes of problems, in general it is unlikely that software alone will resolve the challenges to higher scalability. As in the past, future generations of high-end computers may require a combination of hardware architecture and system software advances to enable efficient operation at a Petaflops level. The NASA led HTMT project has engaged the talents of a broad interdisciplinary team to develop a new strategy in high-end system architecture to deliver petaflops scale computing in the 2004/5 timeframe. The Hybrid-Technology, MultiThreaded parallel computer architecture incorporates several advanced technologies in combination with an innovative dynamic adaptive scheduling mechanism to provide unprecedented performance and efficiency within practical constraints of cost, complexity, and power consumption. The emerging superconductor Rapid Single Flux Quantum electronics can operate at 100 GHz (the record is 770 GHz) and one percent of the power required by convention semiconductor logic. Wave Division Multiplexing optical communications can approach a peak per fiber bandwidth of 1 Tbps and the new Data Vortex network topology employing this technology can connect tens of thousands of ports providing a bi-section bandwidth on the order of a Petabyte per second with latencies well below 100 nanoseconds, even under heavy loads. Processor-in-Memory (PIM) technology combines logic and memory on the same chip exposing the internal bandwidth of the memory row buffers at low latency. And holographic storage photorefractive storage technologies provide high-density memory with access a thousand times faster than conventional disk technologies. Together these technologies enable a new class of shared memory system architecture with a peak performance in the range of a Petaflops but size and power requirements comparable to today's largest Teraflops scale systems. To achieve high-sustained performance, HTMT combines an advanced multithreading processor architecture with a memory-driven coarse-grained latency management strategy called "percolation", yielding high efficiency while reducing the much of the parallel programming burden. This paper will present the basic system architecture characteristics made possible through this series of advanced technologies and then give a detailed description of the new percolation approach to runtime latency management.

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

PubMed

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 the mediodorsal and ventrolateral thalamus may be candidate targets for modulating abnormal network behavior underlying LGS, potentially via emerging thalamic neurostimulation therapies. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Resting-state networks associated with cognitive processing show more age-related decline than those associated with emotional processing.

PubMed

Nashiro, Kaoru; Sakaki, Michiko; Braskie, Meredith N; Mather, Mara

2017-06-01

Correlations in activity across disparate brain regions during rest reveal functional networks in the brain. Although previous studies largely agree that there is an age-related decline in the "default mode network," how age affects other resting-state networks, such as emotion-related networks, is still controversial. Here we used a dual-regression approach to investigate age-related alterations in resting-state networks. The results revealed age-related disruptions in functional connectivity in all 5 identified cognitive networks, namely the default mode network, cognitive-auditory, cognitive-speech (or speech-related somatosensory), and right and left frontoparietal networks, whereas such age effects were not observed in the 3 identified emotion networks. In addition, we observed age-related decline in functional connectivity in 3 visual and 3 motor/visuospatial networks. Older adults showed greater functional connectivity in regions outside 4 out of the 5 identified cognitive networks, consistent with the dedifferentiation effect previously observed in task-based functional magnetic resonance imaging studies. Both reduced within-network connectivity and increased out-of-network connectivity were correlated with poor cognitive performance, providing potential biomarkers for cognitive aging. Copyright © 2017 Elsevier Inc. All rights reserved.

The effect of the neural activity on topological properties of growing neural networks.

PubMed

Gafarov, F M; Gafarova, V R

2016-09-01

The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

Connectivity patterns in cognitive control networks predict naturalistic multitasking ability.

PubMed

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.

Intelligence and information processing during a visual search task in children: an event-related potential study.

PubMed

Zhang, Qiong; Shi, Jiannong; Luo, Yuejia; Zhao, Daheng; Yang, Jie

2006-05-15

To investigate the differences in event-related potential parameters related to children's intelligence, we selected 15 individuals from an experimental class of intellectually gifted children and 13 intellectually average children as control to finish three types of visual search tasks (Chinese words, English letters and Arabic numbers). We recorded the electroencephalogram and calculated the peak latencies and amplitudes. Our results suggest comparatively increased P3 amplitudes and shorter P3 latencies in brighter individuals than in less intelligent individuals, but this expected neural efficiency effect interacted with task content. The differences were explained by a more spatially and temporally coordinated neural network for more intelligent children.

Beyond the Arcuate Fasciculus: Consensus and Controversy in the Connectional Anatomy of Language

ERIC Educational Resources Information Center

Dick, Anthony Steven; Tremblay, Pascale

2012-01-01

The growing consensus that language is distributed into large-scale cortical and subcortical networks has brought with it an increasing focus on the connectional anatomy of language, or how particular fibre pathways connect regions within the language network. Understanding connectivity of the language network could provide critical insights into…

Altered Whole-Brain and Network-Based Functional Connectivity in Parkinson's Disease.

PubMed

de Schipper, Laura J; Hafkemeijer, Anne; van der Grond, Jeroen; Marinus, Johan; Henselmans, Johanna M L; van Hilten, Jacobus J

2018-01-01

Background: Functional imaging methods, such as resting-state functional magnetic resonance imaging, reflect changes in neural connectivity and may help to assess the widespread consequences of disease-specific network changes in Parkinson's disease. In this study we used a relatively new graph analysis approach in functional imaging: eigenvector centrality mapping. This model-free method, applied to all voxels in the brain, identifies prominent regions in the brain network hierarchy and detects localized differences between patient populations. In other neurological disorders, eigenvector centrality mapping has been linked to changes in functional connectivity in certain nodes of brain networks. Objectives: Examining changes in functional brain connectivity architecture on a whole brain and network level in patients with Parkinson's disease. Methods: Whole brain resting-state functional architecture was studied with a recently introduced graph analysis approach (eigenvector centrality mapping). Functional connectivity was further investigated in relation to eight known resting-state networks. Cross-sectional analyses included group comparison of functional connectivity measures of Parkinson's disease patients ( n = 107) with control subjects ( n = 58) and correlations with clinical data, including motor and cognitive impairment and a composite measure of predominantly non-dopaminergic symptoms. Results: Eigenvector centrality mapping revealed that frontoparietal regions were more prominent in the whole-brain network function in patients compared to control subjects, while frontal and occipital brain areas were less prominent in patients. Using standard resting-state networks, we found predominantly increased functional connectivity, namely within sensorimotor system and visual networks in patients. Regional group differences in functional connectivity of both techniques between patients and control subjects partly overlapped for highly connected posterior brain regions, in particular in the posterior cingulate cortex and precuneus. Clinico-functional imaging relations were not found. Conclusions: Changes on the level of functional brain connectivity architecture might provide a different perspective of pathological consequences of Parkinson's disease. The involvement of specific, highly connected (hub) brain regions may influence whole brain functional network architecture in Parkinson's disease.

Effects of local and global network connectivity on synergistic epidemics

NASA Astrophysics Data System (ADS)

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.

Effects of local and global network connectivity on synergistic epidemics.

PubMed

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.

Immunization of complex networks

NASA Astrophysics Data System (ADS)

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2002-03-01

Complex networks such as the sexual partnership web or the Internet often show a high degree of redundancy and heterogeneity in their connectivity properties. This peculiar connectivity provides an ideal environment for the spreading of infective agents. Here we show that the random uniform immunization of individuals does not lead to the eradication of infections in all complex networks. Namely, networks with scale-free properties do not acquire global immunity from major epidemic outbreaks even in the presence of unrealistically high densities of randomly immunized individuals. The absence of any critical immunization threshold is due to the unbounded connectivity fluctuations of scale-free networks. Successful immunization strategies can be developed only by taking into account the inhomogeneous connectivity properties of scale-free networks. In particular, targeted immunization schemes, based on the nodes' connectivity hierarchy, sharply lower the network's vulnerability to epidemic attacks.

The effects of neuron morphology on graph theoretic measures of network connectivity: the analysis of a two-level statistical model.

PubMed

Aćimović, Jugoslava; Mäki-Marttunen, Tuomo; Linne, Marja-Leena

2015-01-01

We developed a two-level statistical model that addresses the question of how properties of neurite morphology shape the large-scale network connectivity. We adopted a low-dimensional statistical description of neurites. From the neurite model description we derived the expected number of synapses, node degree, and the effective radius, the maximal distance between two neurons expected to form at least one synapse. We related these quantities to the network connectivity described using standard measures from graph theory, such as motif counts, clustering coefficient, minimal path length, and small-world coefficient. These measures are used in a neuroscience context to study phenomena from synaptic connectivity in the small neuronal networks to large scale functional connectivity in the cortex. For these measures we provide analytical solutions that clearly relate different model properties. Neurites that sparsely cover space lead to a small effective radius. If the effective radius is small compared to the overall neuron size the obtained networks share similarities with the uniform random networks as each neuron connects to a small number of distant neurons. Large neurites with densely packed branches lead to a large effective radius. If this effective radius is large compared to the neuron size, the obtained networks have many local connections. In between these extremes, the networks maximize the variability of connection repertoires. The presented approach connects the properties of neuron morphology with large scale network properties without requiring heavy simulations with many model parameters. The two-steps procedure provides an easier interpretation of the role of each modeled parameter. The model is flexible and each of its components can be further expanded. We identified a range of model parameters that maximizes variability in network connectivity, the property that might affect network capacity to exhibit different dynamical regimes.

Self-reference, emotion inhibition and somatosensory disturbance: preliminary investigation of network perturbations in conversion disorder.

PubMed

Monsa, R; Peer, M; Arzy, S

2018-06-01

Conversion disorder (CD), or functional neurological disorder, is manifested as a neurological disturbance that is not macroscopically visible on clinical structural neuroimaging and is instead ascribed to underlying psychological stress. Known for many years in neuropsychiatry, a comprehensive explanation of the way in which psychological stress leads to a neurological deficit of a structural-like origin is still lacking. We applied whole-brain network-based data-driven analyses on resting-state functional magnetic resonance imaging, recorded in seven patients with acute-onset, stroke-like CD with unilateral paresis and hypoesthesia as compared with 15 age-matched healthy controls. We used a clustering analysis to measure functional connectivity (FC) strength within 10 different brain networks, as well as between these networks. Finally, we tested FC of specific brain regions that are known to be involved in CD. We found a significant increase in FC strength only within the default-mode network (DMN), which manages self-referential processing. Examination of inter-connectivity between networks showed a structure of disturbed connectivity, which included decreased connectivity between the DMN and limbic/salience network, increased connectivity between the limbic/salience network and body-related temporo-parieto-occipital junction network, decreased connectivity between the temporo-parieto-occipital junction and memory-related medial temporal lobe, and decreased connectivity between the medial temporal lobe and sensorimotor network. Region-specific FC analysis showed increased connectivity between the hippocampus and DMN. These preliminary results of disturbances in brain networks related to memory, emotions and self-referential processing, and networks involved in motor planning and execution, suggest a role of these cognitive functions in the psychopathology of CD. © 2018 EAN.

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

PubMed

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.

Damage spreading in spatial and small-world random Boolean networks

NASA Astrophysics Data System (ADS)

Lu, Qiming; Teuscher, Christof

2014-02-01

The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the Hamming distance at very low connectivities (K¯≪1) and that the critical connectivity of stability Ks changes compared to random networks. At higher K¯, this scaling remains unchanged. We also show that the Hamming distance of spatially local networks scales with a power law as the system size N increases, but with a different exponent for local and small-world networks. The scaling arguments for small-world networks are obtained with respect to the system sizes and strength of spatially local connections. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.

Designing connected marine reserves in the face of global warming.

PubMed

Álvarez-Romero, Jorge G; Munguía-Vega, Adrián; Beger, Maria; Del Mar Mancha-Cisneros, Maria; Suárez-Castillo, Alvin N; Gurney, Georgina G; Pressey, Robert L; Gerber, Leah R; Morzaria-Luna, Hem Nalini; Reyes-Bonilla, Héctor; Adams, Vanessa M; Kolb, Melanie; Graham, Erin M; VanDerWal, Jeremy; Castillo-López, Alejandro; Hinojosa-Arango, Gustavo; Petatán-Ramírez, David; Moreno-Baez, Marcia; Godínez-Reyes, Carlos R; Torre, Jorge

2018-02-01

Marine reserves are widely used to protect species important for conservation and fisheries and to help maintain ecological processes that sustain their populations, including recruitment and dispersal. Achieving these goals requires well-connected networks of marine reserves that maximize larval connectivity, thus allowing exchanges between populations and recolonization after local disturbances. However, global warming can disrupt connectivity by shortening potential dispersal pathways through changes in larval physiology. These changes can compromise the performance of marine reserve networks, thus requiring adjusting their design to account for ocean warming. To date, empirical approaches to marine prioritization have not considered larval connectivity as affected by global warming. Here, we develop a framework for designing marine reserve networks that integrates graph theory and changes in larval connectivity due to potential reductions in planktonic larval duration (PLD) associated with ocean warming, given current socioeconomic constraints. Using the Gulf of California as case study, we assess the benefits and costs of adjusting networks to account for connectivity, with and without ocean warming. We compare reserve networks designed to achieve representation of species and ecosystems with networks designed to also maximize connectivity under current and future ocean-warming scenarios. Our results indicate that current larval connectivity could be reduced significantly under ocean warming because of shortened PLDs. Given the potential changes in connectivity, we show that our graph-theoretical approach based on centrality (eigenvector and distance-weighted fragmentation) of habitat patches can help design better-connected marine reserve networks for the future with equivalent costs. We found that maintaining dispersal connectivity incidentally through representation-only reserve design is unlikely, particularly in regions with strong asymmetric patterns of dispersal connectivity. Our results support previous studies suggesting that, given potential reductions in PLD due to ocean warming, future marine reserve networks would require more and/or larger reserves in closer proximity to maintain larval connectivity. © 2017 John Wiley & Sons Ltd.

Using social media to create a professional network between physician-trainees and the American Society of Nephrology.

PubMed

Shariff, Afreen I; Fang, Xiangming; Desai, Tejas

2013-07-01

Twitter is the fastest growing social media network. It offers participants the ability to network with other individuals. Medical societies are interested in helping individuals network to boost recruitment, encourage collaboration, and assist in job placement. We hypothesized that the American Society of Nephrology (ASN) successfully used Twitter to create a network between participants and itself to stay connected with its members. Tweets from 3 Twitter networking sessions during Kidney Week 2011 were analyzed for content. These messages were used to create a network between all participants of the networking sessions. The network was analyzed for strength and influence by calculating clustering coefficients (CC) and eigenvector centrality (EC) scores, respectively. Eight moderators and 9 trainees authored 376 Twitter messages. Most tweets by trainees (64%) and moderators (61%) discussed 1 of 3 themes: networking, education, or navigating Kidney Week 2011. A total of 25 online network connections were established during the 3 sessions; 20% were bidirectional. The CC for the network was 0.300. All moderators formed at least 1 connection, but 7 of the 9 trainees failed to make any connections. ASN made 5 unidirectional and 0 bidirectional connections with a low EC of 0.108. ASN was unable to form powerful connections with trainees through Twitter, but medical societies should not be discouraged by the results reported in this investigation. As societies become more familiar with Twitter and understand the mechanisms to develop connections, these societies will have a greater influence within increasingly stronger networks. Copyright © 2013 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Network topology and functional connectivity disturbances precede the onset of Huntington’s disease

PubMed Central

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

2015-01-01

Cognitive, motor and psychiatric changes in prodromal Huntington’s disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington’s disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington’s disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington’s disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls (n = 16) and prodromal Huntington’s disease individuals (n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease burden increased. These disturbances were often related to long-range connections involving peripheral nodes and interhemispheric connections. A strong association was found between weaker connectivity and decreased rich-club organization, indicating that whole-brain simple connectivity partially expressed disturbances in the communication of highly-connected hubs. However, network topology and network-based statistic connectivity metrics did not correlate with key markers of executive dysfunction (Stroop Test, Trail Making Test) in prodromal Huntington’s disease, which instead were related to whole-brain connectivity disturbances in nodes (right inferior parietal, right thalamus, left anterior cingulate) that exhibited multiple aberrant connections and that mediate executive control. Altogether, our results show for the first time a largely disease burden-dependent functional reorganization of whole-brain networks in prodromal Huntington’s disease. Both analytic approaches provided a unique window into brain reorganization that was not related to brain atrophy or motor symptoms. Longitudinal studies currently in progress will chart the course of functional changes to determine the most sensitive markers of disease progression. PMID:26059655

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

PubMed

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 burden increased. These disturbances were often related to long-range connections involving peripheral nodes and interhemispheric connections. A strong association was found between weaker connectivity and decreased rich-club organization, indicating that whole-brain simple connectivity partially expressed disturbances in the communication of highly-connected hubs. However, network topology and network-based statistic connectivity metrics did not correlate with key markers of executive dysfunction (Stroop Test, Trail Making Test) in prodromal Huntington's disease, which instead were related to whole-brain connectivity disturbances in nodes (right inferior parietal, right thalamus, left anterior cingulate) that exhibited multiple aberrant connections and that mediate executive control. Altogether, our results show for the first time a largely disease burden-dependent functional reorganization of whole-brain networks in prodromal Huntington's disease. Both analytic approaches provided a unique window into brain reorganization that was not related to brain atrophy or motor symptoms. Longitudinal studies currently in progress will chart the course of functional changes to determine the most sensitive markers of disease progression. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Reaction Time and Self-Report Psychopathological Assessment: Convergent and Discriminant Validity.

ERIC Educational Resources Information Center

Holden, Ronald R.; Fekken, G. Cynthia

The processing of incoming psychological information along the network, or schemata, of self-knowledge was studied to determine the convergent and discriminant validity of the patterns of schemata-specific response latencies. Fifty-three female and 52 male university students completed the Basic Personality Inventory (BPI). BPI scales assess…

Ultrascalable petaflop parallel supercomputer

DOEpatents

Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Chiu, George [Cross River, NY; Cipolla, Thomas M [Katonah, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Hall, Shawn [Pleasantville, NY; Haring, Rudolf A [Cortlandt Manor, NY; Heidelberger, Philip [Cortlandt Manor, NY; Kopcsay, Gerard V [Yorktown Heights, NY; Ohmacht, Martin [Yorktown Heights, NY; Salapura, Valentina [Chappaqua, NY; Sugavanam, Krishnan [Mahopac, NY; Takken, Todd [Brewster, NY

2010-07-20

A massively parallel supercomputer of petaOPS-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC) having up to four processing elements. The ASIC nodes are interconnected by multiple independent networks that optimally maximize the throughput of packet communications between nodes with minimal latency. The multiple networks may include three high-speed networks for parallel algorithm message passing including a Torus, collective network, and a Global Asynchronous network that provides global barrier and notification functions. These multiple independent networks may be collaboratively or independently utilized according to the needs or phases of an algorithm for optimizing algorithm processing performance. The use of a DMA engine is provided to facilitate message passing among the nodes without the expenditure of processing resources at the node.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Integration of Network Topological and Connectivity Properties for Neuroimaging Classification

PubMed Central

Jie, Biao; Gao, Wei; Wang, Qian; Wee, Chong-Yaw

2014-01-01

Rapid advances in neuroimaging techniques have provided an efficient and noninvasive way for exploring the structural and functional connectivity of the human brain. Quantitative measurement of abnormality of brain connectivity in patients with neurodegenerative diseases, such as mild cognitive impairment (MCI) and Alzheimer’s disease (AD), have also been widely reported, especially at a group level. Recently, machine learning techniques have been applied to the study of AD and MCI, i.e., to identify the individuals with AD/MCI from the healthy controls (HCs). However, most existing methods focus on using only a single property of a connectivity network, although multiple network properties, such as local connectivity and global topological properties, can potentially be used. In this paper, by employing multikernel based approach, we propose a novel connectivity based framework to integrate multiple properties of connectivity network for improving the classification performance. Specifically, two different types of kernels (i.e., vector-based kernel and graph kernel) are used to quantify two different yet complementary properties of the network, i.e., local connectivity and global topological properties. Then, multikernel learning (MKL) technique is adopted to fuse these heterogeneous kernels for neuroimaging classification. We test the performance of our proposed method on two different data sets. First, we test it on the functional connectivity networks of 12 MCI and 25 HC subjects. The results show that our method achieves significant performance improvement over those using only one type of network property. Specifically, our method achieves a classification accuracy of 91.9%, which is 10.8% better than those by single network-property-based methods. Then, we test our method for gender classification on a large set of functional connectivity networks with 133 infants scanned at birth, 1 year, and 2 years, also demonstrating very promising results. PMID:24108708

Intrinsic functional connectivity alterations in progressive supranuclear palsy: Differential effects in frontal cortex, motor, and midbrain networks.

PubMed

Rosskopf, Johannes; Gorges, Martin; Müller, Hans-Peter; Lulé, Dorothée; Uttner, Ingo; Ludolph, Albert C; Pinkhardt, Elmar; Juengling, Freimut D; Kassubek, Jan

2017-07-01

The topography of functional network changes in progressive supranuclear palsy can be mapped by intrinsic functional connectivity MRI. The objective of this study was to study functional connectivity and its clinical and behavioral correlates in dedicated networks comprising the cognition-related default mode and the motor and midbrain functional networks in patients with PSP. Whole-brain-based "resting-state" functional MRI and high-resolution T1-weighted magnetic resonance imaging data together with neuropsychological and video-oculographic data from 34 PSP patients (22 with Richardson subtype and 12 with parkinsonian subtype) and 35 matched healthy controls were subjected to network-based functional connectivity and voxel-based morphometry analysis. After correction for global patterns of brain atrophy, the group comparison between PSP patients and controls revealed significantly decreased functional connectivity (P < 0.05, corrected) in the prefrontal cortex, which was significantly correlated with cognitive performance (P = 0.006). Of note, midbrain network connectivity in PSP patients showed increased connectivity with the thalamus, on the one hand, whereas, on the other hand, lower functional connectivity within the midbrain was significantly correlated with vertical gaze impairment, as quantified by video-oculography (P = 0.004). PSP Richardson subtype showed significantly increased functional motor network connectivity with the medial prefrontal gyrus. PSP-associated neurodegeneration was attributed to both decreased and increased functional connectivity. Decreasing functional connectivity was associated with worse behavioral performance (ie, dementia severity and gaze palsy), whereas the pattern of increased functional connectivity may be a potential adaptive mechanism. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Stability of a giant connected component in a complex network

NASA Astrophysics Data System (ADS)

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.

Autonomous Optimization of Targeted Stimulation of Neuronal Networks

PubMed Central

Kumar, Sreedhar S.; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin

2016-01-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable ‘state’ to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers. PMID:27509295

Autonomous Optimization of Targeted Stimulation of Neuronal Networks.

PubMed

Kumar, Sreedhar S; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin; Egert, Ulrich

2016-08-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable 'state' to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers.

An efficient and reliable geographic routing protocol based on partial network coding for underwater sensor networks.

PubMed

Hao, Kun; Jin, Zhigang; Shen, Haifeng; Wang, Ying

2015-05-28

Efficient routing protocols for data packet delivery are crucial to underwater sensor networks (UWSNs). However, communication in UWSNs is a challenging task because of the characteristics of the acoustic channel. Network coding is a promising technique for efficient data packet delivery thanks to the broadcast nature of acoustic channels and the relatively high computation capabilities of the sensor nodes. In this work, we present GPNC, a novel geographic routing protocol for UWSNs that incorporates partial network coding to encode data packets and uses sensor nodes' location information to greedily forward data packets to sink nodes. GPNC can effectively reduce network delays and retransmissions of redundant packets causing additional network energy consumption. Simulation results show that GPNC can significantly improve network throughput and packet delivery ratio, while reducing energy consumption and network latency when compared with other routing protocols.

Class network routing

DOEpatents

Bhanot, Gyan [Princeton, NJ; Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Takken, Todd E [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2009-09-08

Class network routing is implemented in a network such as a computer network comprising a plurality of parallel compute processors at nodes thereof. Class network routing allows a compute processor to broadcast a message to a range (one or more) of other compute processors in the computer network, such as processors in a column or a row. Normally this type of operation requires a separate message to be sent to each processor. With class network routing pursuant to the invention, a single message is sufficient, which generally reduces the total number of messages in the network as well as the latency to do a broadcast. Class network routing is also applied to dense matrix inversion algorithms on distributed memory parallel supercomputers with hardware class function (multicast) capability. This is achieved by exploiting the fact that the communication patterns of dense matrix inversion can be served by hardware class functions, which results in faster execution times.

Psychophysiological whole-brain network clustering based on connectivity dynamics analysis in naturalistic conditions.

PubMed

Raz, Gal; Shpigelman, Lavi; Jacob, Yael; Gonen, Tal; Benjamini, Yoav; Hendler, Talma

2016-12-01

We introduce a novel method for delineating context-dependent functional brain networks whose connectivity dynamics are synchronized with the occurrence of a specific psychophysiological process of interest. In this method of context-related network dynamics analysis (CRNDA), a continuous psychophysiological index serves as a reference for clustering the whole-brain into functional networks. We applied CRNDA to fMRI data recorded during the viewing of a sadness-inducing film clip. The method reliably demarcated networks in which temporal patterns of connectivity related to the time series of reported emotional intensity. Our work successfully replicated the link between network connectivity and emotion rating in an independent sample group for seven of the networks. The demarcated networks have clear common functional denominators. Three of these networks overlap with distinct empathy-related networks, previously identified in distinct sets of studies. The other networks are related to sensorimotor processing, language, attention, and working memory. The results indicate that CRNDA, a data-driven method for network clustering that is sensitive to transient connectivity patterns, can productively and reliably demarcate networks that follow psychologically meaningful processes. Hum Brain Mapp 37:4654-4672, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

US computer research networks: Domestic and international telecommunications capacity requirements

NASA Technical Reports Server (NTRS)

Kratochvil, D.; Sood, D.

1990-01-01

The future telecommunications capacity and connectivity requirements of the United States (US) research and development (R&D) community raise two concerns. First, would there be adequate privately-owned communications capacity to meet the ever-increasing requirements of the US R&D community for domestic and international connectivity? Second, is the method of piecemeal implementation of communications facilities by individual researchers cost effective when viewed from an integrated perspective? To address the capacity issue, Contel recently completed a study for NASA identifying the current domestic R&D telecommunications capacity and connectivity requirements, and projecting the same to the years 1991, 1996, 2000, and 2010. The work reported here extends the scope of an earlier study by factoring in the impact of international connectivity requirements on capacity and connectivity forecasts. Most researchers in foreign countries, as is the case with US researchers, rely on regional, national or continent-wide networks to collaborate with each other, and their US counterparts. The US researchers' international connectivity requirements, therefore, stem from the need to link the US domestic research networks to foreign research networks. The number of links and, more importantly, the speeds of links are invariably determined by the characteristics of the networks being linked. The major thrust of this study, therefore, was to identify and characterize the foreign research networks, to quantify the current status of their connectivity to the US networks, and to project growth in the connectivity requirements to years 1991, 1996, 2000, and 2010 so that a composite picture of the US research networks in the same years could be forecasted. The current (1990) US integrated research network, and its connectivity to foreign research networks is shown. As an example of projections, the same for the year 2010 is shown.

Topological relationships between brain and social networks.

PubMed

Sakata, Shuzo; Yamamori, Tetsuo

2007-01-01

Brains are complex networks. Previously, we revealed that specific connected structures are either significantly abundant or rare in cortical networks. However, it remains unknown whether systems from other disciplines have similar architectures to brains. By applying network-theoretical methods, here we show topological similarities between brain and social networks. We found that the statistical relevance of specific tied structures differs between social "friendship" and "disliking" networks, suggesting relation-type-specific topology of social networks. Surprisingly, overrepresented connected structures in brain networks are more similar to those in the friendship networks than to those in other networks. We found that balanced and imbalanced reciprocal connections between nodes are significantly abundant and rare, respectively, whereas these results are unpredictable by simply counting mutual connections. We interpret these results as evidence of positive selection of balanced mutuality between nodes. These results also imply the existence of underlying common principles behind the organization of brain and social networks.

Sensitivity of marine protected area network connectivity to atmospheric variability

NASA Astrophysics Data System (ADS)

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.

Low latency messages on distributed memory multiprocessors

NASA Technical Reports Server (NTRS)

Rosing, Matthew; Saltz, Joel

1993-01-01

Many of the issues in developing an efficient interface for communication on distributed memory machines are described and a portable interface is proposed. Although the hardware component of message latency is less than one microsecond on many distributed memory machines, the software latency associated with sending and receiving typed messages is on the order of 50 microseconds. The reason for this imbalance is that the software interface does not match the hardware. By changing the interface to match the hardware more closely, applications with fine grained communication can be put on these machines. Based on several tests that were run on the iPSC/860, an interface that will better match current distributed memory machines is proposed. The model used in the proposed interface consists of a computation processor and a communication processor on each node. Communication between these processors and other nodes in the system is done through a buffered network. Information that is transmitted is either data or procedures to be executed on the remote processor. The dual processor system is better suited for efficiently handling asynchronous communications compared to a single processor system. The ability to send data or procedure is very flexible for minimizing message latency, based on the type of communication being performed. The test performed and the proposed interface are described.

Algorithms and Libraries

NASA Technical Reports Server (NTRS)

Dongarra, Jack

1998-01-01

This exploratory study initiated our inquiry into algorithms and applications that would benefit by latency tolerant approach to algorithm building, including the construction of new algorithms where appropriate. In a multithreaded execution, when a processor reaches a point where remote memory access is necessary, the request is sent out on the network and a context--switch occurs to a new thread of computation. This effectively masks a long and unpredictable latency due to remote loads, thereby providing tolerance to remote access latency. We began to develop standards to profile various algorithm and application parameters, such as the degree of parallelism, granularity, precision, instruction set mix, interprocessor communication, latency etc. These tools will continue to develop and evolve as the Information Power Grid environment matures. To provide a richer context for this research, the project also focused on issues of fault-tolerance and computation migration of numerical algorithms and software. During the initial phase we tried to increase our understanding of the bottlenecks in single processor performance. Our work began by developing an approach for the automatic generation and optimization of numerical software for processors with deep memory hierarchies and pipelined functional units. Based on the results we achieved in this study we are planning to study other architectures of interest, including development of cost models, and developing code generators appropriate to these architectures.

Attractor neural networks with resource-efficient synaptic connectivity

NASA Astrophysics Data System (ADS)

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.

Introduction to a system for implementing neural net connections on SIMD architectures

NASA Technical Reports Server (NTRS)

Tomboulian, Sherryl

1988-01-01

Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized communication. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network.

Introduction to a system for implementing neural net connections on SIMD architectures

NASA Technical Reports Server (NTRS)

Tomboulian, Sherryl

1988-01-01

Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized elements. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network.

Performance Evaluation of IEEE 802.11ah Networks With High-Throughput Bidirectional Traffic.

PubMed

Šljivo, Amina; Kerkhove, Dwight; Tian, Le; Famaey, Jeroen; Munteanu, Adrian; Moerman, Ingrid; Hoebeke, Jeroen; De Poorter, Eli

2018-01-23

So far, existing sub-GHz wireless communication technologies focused on low-bandwidth, long-range communication with large numbers of constrained devices. Although these characteristics are fine for many Internet of Things (IoT) applications, more demanding application requirements could not be met and legacy Internet technologies such as Transmission Control Protocol/Internet Protocol (TCP/IP) could not be used. This has changed with the advent of the new IEEE 802.11ah Wi-Fi standard, which is much more suitable for reliable bidirectional communication and high-throughput applications over a wide area (up to 1 km). The standard offers great possibilities for network performance optimization through a number of physical- and link-layer configurable features. However, given that the optimal configuration parameters depend on traffic patterns, the standard does not dictate how to determine them. Such a large number of configuration options can lead to sub-optimal or even incorrect configurations. Therefore, we investigated how two key mechanisms, Restricted Access Window (RAW) grouping and Traffic Indication Map (TIM) segmentation, influence scalability, throughput, latency and energy efficiency in the presence of bidirectional TCP/IP traffic. We considered both high-throughput video streaming traffic and large-scale reliable sensing traffic and investigated TCP behavior in both scenarios when the link layer introduces long delays. This article presents the relations between attainable throughput per station and attainable number of stations, as well as the influence of RAW, TIM and TCP parameters on both. We found that up to 20 continuously streaming IP-cameras can be reliably connected via IEEE 802.11ah with a maximum average data rate of 160 kbps, whereas 10 IP-cameras can achieve average data rates of up to 255 kbps over 200 m. Up to 6960 stations transmitting every 60 s can be connected over 1 km with no lost packets. The presented results enable the fine tuning of RAW and TIM parameters for throughput-demanding reliable applications (i.e., video streaming, firmware updates) on one hand, and very dense low-throughput reliable networks with bidirectional traffic on the other hand.

Performance Evaluation of IEEE 802.11ah Networks With High-Throughput Bidirectional Traffic

PubMed Central

Kerkhove, Dwight; Tian, Le; Munteanu, Adrian; De Poorter, Eli

2018-01-01

So far, existing sub-GHz wireless communication technologies focused on low-bandwidth, long-range communication with large numbers of constrained devices. Although these characteristics are fine for many Internet of Things (IoT) applications, more demanding application requirements could not be met and legacy Internet technologies such as Transmission Control Protocol/Internet Protocol (TCP/IP) could not be used. This has changed with the advent of the new IEEE 802.11ah Wi-Fi standard, which is much more suitable for reliable bidirectional communication and high-throughput applications over a wide area (up to 1 km). The standard offers great possibilities for network performance optimization through a number of physical- and link-layer configurable features. However, given that the optimal configuration parameters depend on traffic patterns, the standard does not dictate how to determine them. Such a large number of configuration options can lead to sub-optimal or even incorrect configurations. Therefore, we investigated how two key mechanisms, Restricted Access Window (RAW) grouping and Traffic Indication Map (TIM) segmentation, influence scalability, throughput, latency and energy efficiency in the presence of bidirectional TCP/IP traffic. We considered both high-throughput video streaming traffic and large-scale reliable sensing traffic and investigated TCP behavior in both scenarios when the link layer introduces long delays. This article presents the relations between attainable throughput per station and attainable number of stations, as well as the influence of RAW, TIM and TCP parameters on both. We found that up to 20 continuously streaming IP-cameras can be reliably connected via IEEE 802.11ah with a maximum average data rate of 160 kbps, whereas 10 IP-cameras can achieve average data rates of up to 255 kbps over 200 m. Up to 6960 stations transmitting every 60 s can be connected over 1 km with no lost packets. The presented results enable the fine tuning of RAW and TIM parameters for throughput-demanding reliable applications (i.e., video streaming, firmware updates) on one hand, and very dense low-throughput reliable networks with bidirectional traffic on the other hand. PMID:29360798

Identification of the connections in biologically inspired neural networks

NASA Technical Reports Server (NTRS)

Demuth, H.; Leung, K.; Beale, M.; Hicklin, J.

1990-01-01

We developed an identification method to find the strength of the connections between neurons from their behavior in small biologically-inspired artificial neural networks. That is, given the network external inputs and the temporal firing pattern of the neurons, we can calculate a solution for the strengths of the connections between neurons and the initial neuron activations if a solution exists. The method determines directly if there is a solution to a particular neural network problem. No training of the network is required. It should be noted that this is a first pass at the solution of a difficult problem. The neuron and network models chosen are related to biology but do not contain all of its complexities, some of which we hope to add to the model in future work. A variety of new results have been obtained. First, the method has been tailored to produce connection weight matrix solutions for networks with important features of biological neural (bioneural) networks. Second, a computationally efficient method of finding a robust central solution has been developed. This later method also enables us to find the most consistent solution in the presence of noisy data. Prospects of applying our method to identify bioneural network connections are exciting because such connections are almost impossible to measure in the laboratory. Knowledge of such connections would facilitate an understanding of bioneural networks and would allow the construction of the electronic counterparts of bioneural networks on very large scale integrated (VLSI) circuits.

Effect of planning for connectivity on linear reserve networks.

PubMed

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

2013-08-01

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

A Longitudinal Study on Resting State Functional Connectivity in Behavioral Variant Frontotemporal Dementia and Alzheimer's Disease.

PubMed

Hafkemeijer, Anne; Möller, Christiane; Dopper, Elise G P; Jiskoot, Lize C; van den Berg-Huysmans, Annette A; van Swieten, John C; van der Flier, Wiesje M; Vrenken, Hugo; Pijnenburg, Yolande A L; Barkhof, Frederik; Scheltens, Philip; van der Grond, Jeroen; Rombouts, Serge A R B

2017-01-01

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are the most common types of early-onset dementia. We applied longitudinal resting state functional magnetic resonance imaging (fMRI) to delineate functional brain connections relevant for disease progression and diagnostic accuracy. We used two-center resting state fMRI data of 20 AD patients (65.1±8.0 years), 12 bvFTD patients (64.7±5.4 years), and 22 control subjects (63.8±5.0 years) at baseline and 1.8-year follow-up. We used whole-network and voxel-based network-to-region analyses to study group differences in functional connectivity at baseline and follow-up, and longitudinal changes in connectivity within and between groups. At baseline, connectivity between paracingulate gyrus and executive control network, between cuneal cortex and medial visual network, and between paracingulate gyrus and salience network was higher in AD compared with controls. These differences were also present after 1.8 years. At follow-up, connectivity between angular gyrus and right frontoparietal network, and between paracingulate gyrus and default mode network was lower in bvFTD compared with controls, and lower compared with AD between anterior cingulate gyrus and executive control network, and between lateral occipital cortex and medial visual network. Over time, connectivity decreased in AD between precuneus and right frontoparietal network and in bvFTD between inferior frontal gyrus and left frontoparietal network. Longitudinal changes in connectivity between supramarginal gyrus and right frontoparietal network differ between both patient groups and controls. We found disease-specific brain regions with longitudinal connectivity changes. This suggests the potential of longitudinal resting state fMRI to delineate regions relevant for disease progression and for diagnostic accuracy, although no group differences in longitudinal changes in the direct comparison of AD and bvFTD were found.

PTEN Loss Increases the Connectivity of Fast Synaptic Motifs and Functional Connectivity in a Developing Hippocampal Network.

PubMed

Barrows, Caitlynn M; McCabe, Matthew P; Chen, Hongmei; Swann, John W; Weston, Matthew C

2017-09-06

Changes in synaptic strength and connectivity are thought to be a major mechanism through which many gene variants cause neurological disease. Hyperactivation of the PI3K-mTOR signaling network, via loss of function of repressors such as PTEN, causes epilepsy in humans and animal models, and altered mTOR signaling may contribute to a broad range of neurological diseases. Changes in synaptic transmission have been reported in animal models of PTEN loss; however, the full extent of these changes, and their effect on network function, is still unknown. To better understand the scope of these changes, we recorded from pairs of mouse hippocampal neurons cultured in a two-neuron microcircuit configuration that allowed us to characterize all four major connection types within the hippocampus. Loss of PTEN caused changes in excitatory and inhibitory connectivity, and these changes were postsynaptic, presynaptic, and transynaptic, suggesting that disruption of PTEN has the potential to affect most connection types in the hippocampal circuit. Given the complexity of the changes at the synaptic level, we measured changes in network behavior after deleting Pten from neurons in an organotypic hippocampal slice network. Slices containing Pten -deleted neurons showed increased recruitment of neurons into network bursts. Importantly, these changes were not confined to Pten -deleted neurons, but involved the entire network, suggesting that the extensive changes in synaptic connectivity rewire the entire network in such a way that promotes a widespread increase in functional connectivity. SIGNIFICANCE STATEMENT Homozygous deletion of the Pten gene in neuronal subpopulations in the mouse serves as a valuable model of epilepsy caused by mTOR hyperactivation. To better understand how gene deletions lead to altered neuronal activity, we investigated the synaptic and network effects that occur 1 week after Pten deletion. PTEN loss increased the connectivity of all four types of hippocampal synaptic connections, including two forms of increased inhibition of inhibition, and increased network functional connectivity. These data suggest that single gene mutations that cause neurological diseases such as epilepsy may affect a surprising range of connection types. Moreover, given the robustness of homeostatic plasticity, these diverse effects on connection types may be necessary to cause network phenotypes such as increased synchrony. Copyright © 2017 the authors 0270-6474/17/378595-17$15.00/0.

PTEN Loss Increases the Connectivity of Fast Synaptic Motifs and Functional Connectivity in a Developing Hippocampal Network

PubMed Central

McCabe, Matthew P.; Chen, Hongmei; Swann, John W.

2017-01-01

Changes in synaptic strength and connectivity are thought to be a major mechanism through which many gene variants cause neurological disease. Hyperactivation of the PI3K-mTOR signaling network, via loss of function of repressors such as PTEN, causes epilepsy in humans and animal models, and altered mTOR signaling may contribute to a broad range of neurological diseases. Changes in synaptic transmission have been reported in animal models of PTEN loss; however, the full extent of these changes, and their effect on network function, is still unknown. To better understand the scope of these changes, we recorded from pairs of mouse hippocampal neurons cultured in a two-neuron microcircuit configuration that allowed us to characterize all four major connection types within the hippocampus. Loss of PTEN caused changes in excitatory and inhibitory connectivity, and these changes were postsynaptic, presynaptic, and transynaptic, suggesting that disruption of PTEN has the potential to affect most connection types in the hippocampal circuit. Given the complexity of the changes at the synaptic level, we measured changes in network behavior after deleting Pten from neurons in an organotypic hippocampal slice network. Slices containing Pten-deleted neurons showed increased recruitment of neurons into network bursts. Importantly, these changes were not confined to Pten-deleted neurons, but involved the entire network, suggesting that the extensive changes in synaptic connectivity rewire the entire network in such a way that promotes a widespread increase in functional connectivity. SIGNIFICANCE STATEMENT Homozygous deletion of the Pten gene in neuronal subpopulations in the mouse serves as a valuable model of epilepsy caused by mTOR hyperactivation. To better understand how gene deletions lead to altered neuronal activity, we investigated the synaptic and network effects that occur 1 week after Pten deletion. PTEN loss increased the connectivity of all four types of hippocampal synaptic connections, including two forms of increased inhibition of inhibition, and increased network functional connectivity. These data suggest that single gene mutations that cause neurological diseases such as epilepsy may affect a surprising range of connection types. Moreover, given the robustness of homeostatic plasticity, these diverse effects on connection types may be necessary to cause network phenotypes such as increased synchrony. PMID:28751459

Robo-line storage: Low latency, high capacity storage systems over geographically distributed networks

NASA Technical Reports Server (NTRS)

Katz, Randy H.; Anderson, Thomas E.; Ousterhout, John K.; Patterson, David A.

1991-01-01

Rapid advances in high performance computing are making possible more complete and accurate computer-based modeling of complex physical phenomena, such as weather front interactions, dynamics of chemical reactions, numerical aerodynamic analysis of airframes, and ocean-land-atmosphere interactions. Many of these 'grand challenge' applications are as demanding of the underlying storage system, in terms of their capacity and bandwidth requirements, as they are on the computational power of the processor. A global view of the Earth's ocean chlorophyll and land vegetation requires over 2 terabytes of raw satellite image data. In this paper, we describe our planned research program in high capacity, high bandwidth storage systems. The project has four overall goals. First, we will examine new methods for high capacity storage systems, made possible by low cost, small form factor magnetic and optical tape systems. Second, access to the storage system will be low latency and high bandwidth. To achieve this, we must interleave data transfer at all levels of the storage system, including devices, controllers, servers, and communications links. Latency will be reduced by extensive caching throughout the storage hierarchy. Third, we will provide effective management of a storage hierarchy, extending the techniques already developed for the Log Structured File System. Finally, we will construct a protototype high capacity file server, suitable for use on the National Research and Education Network (NREN). Such research must be a Cornerstone of any coherent program in high performance computing and communications.

Estimating the epidemic threshold on networks by deterministic connections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Kezan, E-mail: lkzzr@sohu.com; Zhu, Guanghu; Fu, Xinchu

2014-12-15

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

Performance issues in management of the Space Station Information System

NASA Technical Reports Server (NTRS)

Johnson, Marjory J.

1988-01-01

The onboard segment of the Space Station Information System (SSIS), called the Data Management System (DMS), will consist of a Fiber Distributed Data Interface (FDDI) token-ring network. The performance of the DMS in scenarios involving two kinds of network management is analyzed. In the first scenario, how the transmission of routine management messages impacts performance of the DMS is examined. In the second scenario, techniques for ensuring low latency of real-time control messages in an emergency are examined.

Integrated communication and control systems. I - Analysis

NASA Technical Reports Server (NTRS)

Halevi, Yoram; Ray, Asok

1988-01-01

The paper presents the results of an ICCS analysis focusing on discrete-time control systems subject to time-varying delays. The present analytical technique is applicable to integrated dynamic systems such as those encountered in advanced aircraft, spacecraft, and the real-time control of robots and machine tools via a high-speed network within an autonomous manufacturing environment. The significance of data latency and missynchronization between individual system components in ICCS networks is discussed in view of the time-varying delays.

Multi-petascale highly efficient parallel supercomputer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asaad, Sameh; Bellofatto, Ralph E.; Blocksome, Michael A.

A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaflop-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC). The ASIC nodes are interconnected by a five dimensional torus network that optimally maximize the throughput of packet communications between nodes and minimize latency. The network implements collective network and a global asynchronous network that provides global barrier and notification functions. Integrated in the node design include a list-based prefetcher. The memory system implements transaction memory, thread level speculation, and multiversioning cache that improves soft error rate at the same time andmore » supports DMA functionality allowing for parallel processing message-passing.« less

End-to-end performance measurement of Internet based medical applications.

PubMed

Dev, P; Harris, D; Gutierrez, D; Shah, A; Senger, S

2002-01-01

We present a method to obtain an end-to-end characterization of the performance of an application over a network. This method is not dependent on any specific application or type of network. The method requires characterization of network parameters, such as latency and packet loss, between the expected server or client endpoints, as well as characterization of the application's constraints on these parameters. A subjective metric is presented that integrates these characterizations and that operates over a wide range of applications and networks. We believe that this method may be of wide applicability as research and educational applications increasingly make use of computation and data servers that are distributed over the Internet.

Electrophysiological analysis of pathways connecting the medial preoptic area with the mesencephalic central grey matter in rats.

PubMed

MacLeod, N K; Mayer, M L

1980-01-01

1. An electrophysiological study of ascending and descending connexions between the dorsal raphe region of the mesencephalic periaqueductal grey matter and the medial preoptic area has been performed in dioestrous female rats anaesthetized with urethane. 2. Extracellular action potentials recorded from 208 neurones in the medial preoptic area were analysed for a change in excitability following stimulation of the periaqueductal grey matter. 174 neurones were also tested for changes in excitability following stimulation of the mediobasal hypothalamus. 3. Stimulation of the periaqueductal grey matter at 1 Hz was rarely effective, but short trains of pulses (three at 100 Hz) usually caused an initial inhibition (62.5% of 208) of both projection identified and adjacent neurones of the medial preoptic area, at latencies of 5--90 msec (mean 34.1 +/- 1.4 msec). Inhibition following stimulation of the mediobasal hypothalamus occurred less frequently (34%) and at shorter latency (mean 12.0 +/- 1.8 msec; n = 48). 4. Less frequently (10.6%) periaqueductal grey matter stimulation caused an initial excitation of preoptic neurones at latencies of 15--180 msec, (mean 35.3 +/- 7.2). Initial excitation following mediobasal hypothalamus stimulation was stronger, occurred more frequently (29%) and at shorter latencies (range 3--60 msec, mean 13.1 +/- 1.5). Following such initial excitation, inhibition of spontaneous or ionophoretically evoked activity occurred more frequently following mediobasal hypothalamic stimulation, than after periaqueductal grey matter stimulation. 5. Twenty-four neurones displayed antidromic invasion following periaqueductal grey matter stimulation. Latencies for invasion ranged from 13 to 50 msec (mean 25.5 +/- 2.0 msec) and are suggestive of an unmyelinated projection. Occasionally an abrupt decrease in latency followed an increase in stimulus intensity. Antidromic invasion from mediobasal hypothalamus was characterized by a shorter latency (mean 12.5 +/- 0.7 msec; n = 43). A period of reduced excitability lasting 40--100 msec followed antidromic invasion from either site. 6. Antidromic responses to paired mediobasal hypothalamic or periaqueductal grey matter stimuli at 5 msec intervals revealed an increased latency of invasion of the second response, due to the partial refractory period of the neurone. Five cells showed a decreased latency of invasion at stimulus separations of 10--150 msec, interpreted as evidence of a supranormal period. Changes in conduction velocity during the supranormal period may give rise to a variable latency of invasion of spontaneously active cells. 7. These results provide evidence for direct, reciprocal connexions between the midbrain central grey and the medial preoptic area. These circuits may play a role in controlling neuroendocrine and behavioural aspects of reproductive functions.

SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

NASA Astrophysics Data System (ADS)

Dong, Suyalatu; Deng, Yan-Bin; Huang, Yong-Chang

2017-10-01

Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network. Supported by National Natural Science Foundation of China under Grant Nos. 11275017 and 11173028

Distributed Dynamic Host Configuration Protocol (D2HCP)

PubMed Central

Villalba, Luis Javier García; Matesanz, Julián García; Orozco, Ana Lucila Sandoval; Díaz, José Duván Márquez

2011-01-01

Mobile Ad Hoc Networks (MANETs) are multihop wireless networks of mobile nodes without any fixed or preexisting infrastructure. The topology of these networks can change randomly due to the unpredictable mobility of nodes and their propagation characteristics. In most networks, including MANETs, each node needs a unique identifier to communicate. This work presents a distributed protocol for dynamic node IP address assignment in MANETs. Nodes of a MANET synchronize from time to time to maintain a record of IP address assignments in the entire network and detect any IP address leaks. The proposed stateful autoconfiguration scheme uses the OLSR proactive routing protocol for synchronization and guarantees unique IP addresses under a variety of network conditions, including message losses and network partitioning. Simulation results show that the protocol incurs low latency and communication overhead for IP address assignment. PMID:22163856

Distributed Dynamic Host Configuration Protocol (D2HCP).

PubMed

Villalba, Luis Javier García; Matesanz, Julián García; Orozco, Ana Lucila Sandoval; Díaz, José Duván Márquez

2011-01-01

Mobile Ad Hoc Networks (MANETs) are multihop wireless networks of mobile nodes without any fixed or preexisting infrastructure. The topology of these networks can change randomly due to the unpredictable mobility of nodes and their propagation characteristics. In most networks, including MANETs, each node needs a unique identifier to communicate. This work presents a distributed protocol for dynamic node IP address assignment in MANETs. Nodes of a MANET synchronize from time to time to maintain a record of IP address assignments in the entire network and detect any IP address leaks. The proposed stateful autoconfiguration scheme uses the OLSR proactive routing protocol for synchronization and guarantees unique IP addresses under a variety of network conditions, including message losses and network partitioning. Simulation results show that the protocol incurs low latency and communication overhead for IP address assignment.

Altered intrinsic organisation of brain networks implicated in attentional processes in adult attention-deficit/hyperactivity disorder: a resting-state study of attention, default mode and salience network connectivity.

PubMed

Sidlauskaite, Justina; Sonuga-Barke, Edmund; Roeyers, Herbert; Wiersema, Jan R

2016-06-01

Deficits in task-related attentional engagement in attention-deficit/hyperactivity disorder (ADHD) have been hypothesised to be due to altered interrelationships between attention, default mode and salience networks. We examined the intrinsic connectivity during rest within and between these networks. Six-minute resting-state scans were obtained. Using a network-based approach, connectivity within and between the dorsal and ventral attention, the default mode and the salience networks was compared between the ADHD and control group. The ADHD group displayed hyperconnectivity between the two attention networks and within the default mode and ventral attention network. The salience network was hypoconnected to the dorsal attention network. There were trends towards hyperconnectivity within the dorsal attention network and between the salience and ventral attention network in ADHD. Connectivity within and between other networks was unrelated to ADHD. Our findings highlight the altered connectivity within and between attention networks, and between them and the salience network in ADHD. One hypothesis to be tested in future studies is that individuals with ADHD are affected by an imbalance between ventral and dorsal attention systems with the former playing a dominant role during task engagement, making individuals with ADHD highly susceptible to distraction by salient task-irrelevant stimuli.

Endocannabinoid Release Modulates Electrical Coupling between CCK Cells Connected via Chemical and Electrical Synapses in CA1

PubMed Central

Iball, Jonathan; Ali, Afia B.

2011-01-01

Electrical coupling between some subclasses of interneurons is thought to promote coordinated firing that generates rhythmic synchronous activity in cortical regions. Synaptic activity of cholecystokinin (CCK) interneurons which co-express cannabinoid type-1 (CB1) receptors are powerful modulators of network activity via the actions of endocannabinoids. We investigated the modulatory actions of endocannabinoids between chemically and electrically connected synapses of CCK cells using paired whole-cell recordings combined with biocytin and double immunofluorescence labeling in acute slices of rat hippocampus at P18–20 days. CA1 stratum radiatum CCK Schaffer collateral-associated cells were coupled electrically with each other as well as CCK basket cells and CCK cells with axonal projections expanding to dentate gyrus. Approximately 50% of electrically coupled cells received facilitating, asynchronously released inhibitory postsynaptic potential (IPSPs) that curtailed the steady-state coupling coefficient by 57%. Tonic CB1 receptor activity which reduces inhibition enhanced electrical coupling between cells that were connected via chemical and electrical synapses. Blocking CB1 receptors with antagonist, AM-251 (5 μM) resulted in the synchronized release of larger IPSPs and this enhanced inhibition further reduced the steady-state coupling coefficient by 85%. Depolarization induced suppression of inhibition (DSI), maintained the asynchronicity of IPSP latency, but reduced IPSP amplitudes by 95% and enhanced the steady-state coupling coefficient by 104% and IPSP duration by 200%. However, DSI did not did not enhance electrical coupling at purely electrical synapses. These data suggest that different morphological subclasses of CCK interneurons are interconnected via gap junctions. The synergy between the chemical and electrical coupling between CCK cells probably plays a role in activity-dependent endocannabinoid modulation of rhythmic synchronization. PMID:22125513

Task-related modulation of effective connectivity during perceptual decision making: dissociation between dorsal and ventral prefrontal cortex.

PubMed

Akaishi, Rei; Ueda, Naoko; Sakai, Katsuyuki

2013-01-01

The dorsal and ventral parts of the lateral prefrontal cortex have been thought to play distinct roles in decision making. Although its dorsal part such as the frontal eye field (FEF) is shown to play roles in accumulation of sensory information during perceptual decision making, the role of the ventral prefrontal cortex (PFv) is not well-documented. Previous studies have suggested that the PFv is involved in selective attention to the task-relevant information and is associated with accuracy of the behavioral performance. It is unknown, however, whether the accumulation and selection processes are anatomically dissociated between the FEF and PFv. Here we show that, by using concurrent TMS and EEG recording, the short-latency (20-40 ms) TMS-evoked potentials after stimulation of the FEF change as a function of the time to behavioral response, whereas those after stimulation of the PFv change depending on whether the response is correct or not. The potentials after stimulation of either region did not show significant interaction between time to response and performance accuracy, suggesting dissociation between the processes subserved by the FEF and PFv networks. The results are consistent with the idea that the network involving the FEF plays a role in information accumulation, whereas the network involving the PFv plays a role in selecting task relevant information. In addition, stimulation of the FEF and PFv induced activation in common regions in the dorsolateral and medial frontal cortices, suggesting convergence of information processed in the two regions. Taken together, the results suggest dissociation between the FEF and PFv networks for their computational roles in perceptual decision making. The study also highlights the advantage of TMS-EEG technique in investigating the computational processes subserved by the neural network in the human brain with a high temporal resolution.

Minimum spanning tree analysis of the human connectome

PubMed Central

Sommer, Iris E.; Bohlken, Marc M.; Tewarie, Prejaas; Draaisma, Laurijn; Zalesky, Andrew; Di Biase, Maria; Brown, Jesse A.; Douw, Linda; Otte, Willem M.; Mandl, René C.W.; Stam, Cornelis J.

2018-01-01

Abstract One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion‐weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null‐model. The MST of individual subjects matched this reference MST for a mean 58%–88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so‐called rich club nodes (a subset of high‐degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical–subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models. PMID:29468769

Enabling Research Network Connectivity to Clouds with Virtual Router Technology

NASA Astrophysics Data System (ADS)

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.

Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks

PubMed Central

Ruiz-Rizzo, Adriana L.; Neitzel, Julia; Müller, Hermann J.; Sorg, Christian; Finke, Kathrin

2018-01-01

Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's “theory of visual attention” (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity. PMID:29662444

Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks.

PubMed

Ruiz-Rizzo, Adriana L; Neitzel, Julia; Müller, Hermann J; Sorg, Christian; Finke, Kathrin

2018-01-01

Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's "theory of visual attention" (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity.

Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer's disease.

PubMed

Chong, Joanna Su Xian; Liu, Siwei; Loke, Yng Miin; Hilal, Saima; Ikram, Mohammad Kamran; Xu, Xin; Tan, Boon Yeow; Venketasubramanian, Narayanaswamy; Chen, Christopher Li-Hsian; Zhou, Juan

2017-11-01

Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer's disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer's disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer's disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks-the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer's disease patients with and without cerebrovascular disease. Alzheimer's disease patients without cerebrovascular disease, but not Alzheimer's disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer's disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer's disease patients with and without cerebrovascular disease. Across Alzheimer's disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer's disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer's disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer's disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer's disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer's disease network degeneration phenotype. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

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

PubMed

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

2016-08-01

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

Node Self-Deployment Algorithm Based on Pigeon Swarm Optimization for Underwater Wireless Sensor Networks

PubMed Central

Yu, Shanen; Xu, Yiming; Jiang, Peng; Wu, Feng; Xu, Huan

2017-01-01

At present, free-to-move node self-deployment algorithms aim at event coverage and cannot improve network coverage under the premise of considering network connectivity, network reliability and network deployment energy consumption. Thus, this study proposes pigeon-based self-deployment algorithm (PSA) for underwater wireless sensor networks to overcome the limitations of these existing algorithms. In PSA, the sink node first finds its one-hop nodes and maximizes the network coverage in its one-hop region. The one-hop nodes subsequently divide the network into layers and cluster in each layer. Each cluster head node constructs a connected path to the sink node to guarantee network connectivity. Finally, the cluster head node regards the ratio of the movement distance of the node to the change in the coverage redundancy ratio as the target function and employs pigeon swarm optimization to determine the positions of the nodes. Simulation results show that PSA improves both network connectivity and network reliability, decreases network deployment energy consumption, and increases network coverage. PMID:28338615

Test-retest reliability of functional connectivity networks during naturalistic fMRI paradigms.

PubMed

Wang, Jiahui; Ren, Yudan; Hu, Xintao; Nguyen, Vinh Thai; Guo, Lei; Han, Junwei; Guo, Christine Cong

2017-04-01

Functional connectivity analysis has become a powerful tool for probing the human brain function and its breakdown in neuropsychiatry disorders. So far, most studies adopted resting-state paradigm to examine functional connectivity networks in the brain, thanks to its low demand and high tolerance that are essential for clinical studies. However, the test-retest reliability of resting-state connectivity measures is moderate, potentially due to its low behavioral constraint. On the other hand, naturalistic neuroimaging paradigms, an emerging approach for cognitive neuroscience with high ecological validity, could potentially improve the reliability of functional connectivity measures. To test this hypothesis, we characterized the test-retest reliability of functional connectivity measures during a natural viewing condition, and benchmarked it against resting-state connectivity measures acquired within the same functional magnetic resonance imaging (fMRI) session. We found that the reliability of connectivity and graph theoretical measures of brain networks is significantly improved during natural viewing conditions over resting-state conditions, with an average increase of almost 50% across various connectivity measures. Not only sensory networks for audio-visual processing become more reliable, higher order brain networks, such as default mode and attention networks, but also appear to show higher reliability during natural viewing. Our results support the use of natural viewing paradigms in estimating functional connectivity of brain networks, and have important implications for clinical application of fMRI. Hum Brain Mapp 38:2226-2241, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Scalable Wrap-Around Shuffle Exchange Network with Deflection Routing

NASA Technical Reports Server (NTRS)

Monacos, Steve P. (Inventor)

1997-01-01

The invention in one embodiment is a communication network including plural non-blocking crossbar nodes, first apparatus for connecting the nodes in a first layer of connecting links, and second apparatus for connecting links independent of the first layer, whereby each layer is connected to the other layer at each point of the nodes. Preferably, each one of the layers of connecting links corresponds to one recirculating network topology that closes in on itself.

The Robustness Analysis of Wireless Sensor Networks under Uncertain Interference

PubMed Central

Deng, Changjian

2013-01-01

Based on the complex network theory, robustness analysis of condition monitoring wireless sensor network under uncertain interference is present. In the evolution of the topology of sensor networks, the density weighted algebraic connectivity is taken into account, and the phenomenon of removing and repairing the link and node in the network is discussed. Numerical simulation is conducted to explore algebraic connectivity characteristics and network robustness performance. It is found that nodes density has the effect on algebraic connectivity distribution in the random graph model; high density nodes carry more connections, use more throughputs, and may be more unreliable. Moreover, the results show that, when network should be more error tolerant or robust by repairing nodes or adding new nodes, the network should be better clustered in median and high scale wireless sensor networks and be meshing topology in small scale networks. PMID:24363613

A Tuned-RF Duty-Cycled Wake-Up Receiver with -90 dBm Sensitivity.

PubMed

Bdiri, Sadok; Derbel, Faouzi; Kanoun, Olfa

2017-12-29

A novel wake-up receiver for wireless sensor networks is introduced. It operates with a modified medium access protocol (MAC), allowing low-energy consumption and practical latency. The ultra-low-power wake-up receiver operates with enhanced duty-cycled listening. The analysis of energy models of the duty-cycle-based communication is presented. All the WuRx blocks are studied to obey the duty-cycle operation. For a mean interval time for the data exchange cycle between a transmitter and a receiver over 1.7 s and a 64-bit wake-up packet detection latency of 32 ms, the average power consumption of the wake-up receiver (WuRx) reaches down to 3 μ W . It also features scalable addressing of more than 512 bit at a data rate of 128 k bit / s -1 . At a wake-up packet error rate of 10 - 2 , the detection sensitivity reaches a minimum of - 90 dBm . The combination of the MAC protocol and the WuRx eases the adoption of different kinds of wireless sensor networks. In low traffic communication, the WuRx dramatically saves more energy than that of a network that is implementing conventional duty-cycling. In this work, a prototype was realized to evaluate the intended performance.

A Tuned-RF Duty-Cycled Wake-Up Receiver with −90 dBm Sensitivity

PubMed Central

Derbel, Faouzi; Kanoun, Olfa

2017-01-01

A novel wake-up receiver for wireless sensor networks is introduced. It operates with a modified medium access protocol (MAC), allowing low-energy consumption and practical latency. The ultra-low-power wake-up receiver operates with enhanced duty-cycled listening. The analysis of energy models of the duty-cycle-based communication is presented. All the WuRx blocks are studied to obey the duty-cycle operation. For a mean interval time for the data exchange cycle between a transmitter and a receiver over 1.7 s and a 64-bit wake-up packet detection latency of 32 ms, the average power consumption of the wake-up receiver (WuRx) reaches down to 3 μW. It also features scalable addressing of more than 512 bit at a data rate of 128kbit/s−1. At a wake-up packet error rate of 10−2, the detection sensitivity reaches a minimum of −90 dBm. The combination of the MAC protocol and the WuRx eases the adoption of different kinds of wireless sensor networks. In low traffic communication, the WuRx dramatically saves more energy than that of a network that is implementing conventional duty-cycling. In this work, a prototype was realized to evaluate the intended performance. PMID:29286345

Functional Connectivity of Cognitive Brain Networks in Schizophrenia during a Working Memory Task

PubMed Central

Godwin, Douglass; Ji, Andrew; Kandala, Sridhar; Mamah, Daniel

2017-01-01

Task-based connectivity studies facilitate the understanding of how the brain functions during cognition, which is commonly impaired in schizophrenia (SZ). Our aim was to investigate functional connectivity during a working memory task in SZ. We hypothesized that the task-negative (default mode) network and the cognitive control (frontoparietal) network would show dysconnectivity. Twenty-five SZ patient and 31 healthy control scans were collected using the customized 3T Siemens Skyra MRI scanner, previously used to collect data for the Human Connectome Project. Blood oxygen level dependent signal during the 0-back and 2-back conditions were extracted within a network-based parcelation scheme. Average functional connectivity was assessed within five brain networks: frontoparietal (FPN), default mode (DMN), cingulo-opercular (CON), dorsal attention (DAN), and ventral attention network; as well as between the DMN or FPN and other networks. For within-FPN connectivity, there was a significant interaction between n-back condition and group (p = 0.015), with decreased connectivity at 0-back in SZ subjects compared to controls. FPN-to-DMN connectivity also showed a significant condition × group effect (p = 0.003), with decreased connectivity at 0-back in SZ. Across groups, connectivity within the CON and DAN were increased during the 2-back condition, while DMN connectivity with either CON or DAN were decreased during the 2-back condition. Our findings support the role of the FPN, CON, and DAN in working memory and indicate that the pattern of FPN functional connectivity differs between SZ patients and control subjects during the course of a working memory task. PMID:29312020

Functional Connectivity of Cognitive Brain Networks in Schizophrenia during a Working Memory Task.

PubMed

Godwin, Douglass; Ji, Andrew; Kandala, Sridhar; Mamah, Daniel

2017-01-01

Task-based connectivity studies facilitate the understanding of how the brain functions during cognition, which is commonly impaired in schizophrenia (SZ). Our aim was to investigate functional connectivity during a working memory task in SZ. We hypothesized that the task-negative (default mode) network and the cognitive control (frontoparietal) network would show dysconnectivity. Twenty-five SZ patient and 31 healthy control scans were collected using the customized 3T Siemens Skyra MRI scanner, previously used to collect data for the Human Connectome Project. Blood oxygen level dependent signal during the 0-back and 2-back conditions were extracted within a network-based parcelation scheme. Average functional connectivity was assessed within five brain networks: frontoparietal (FPN), default mode (DMN), cingulo-opercular (CON), dorsal attention (DAN), and ventral attention network; as well as between the DMN or FPN and other networks. For within-FPN connectivity, there was a significant interaction between n -back condition and group ( p  = 0.015), with decreased connectivity at 0-back in SZ subjects compared to controls. FPN-to-DMN connectivity also showed a significant condition × group effect ( p  = 0.003), with decreased connectivity at 0-back in SZ. Across groups, connectivity within the CON and DAN were increased during the 2-back condition, while DMN connectivity with either CON or DAN were decreased during the 2-back condition. Our findings support the role of the FPN, CON, and DAN in working memory and indicate that the pattern of FPN functional connectivity differs between SZ patients and control subjects during the course of a working memory task.

Cooperative data dissemination to mission sites

NASA Astrophysics Data System (ADS)

Chen, Fangfei; Johnson, Matthew P.; Bar-Noy, Amotz; La Porta, Thomas F.

2010-04-01

Timely dissemination of information to mobile users is vital in many applications. In a critical situation, no network infrastructure may be available for use in dissemination, over and above the on-board storage capability of the mobile users themselves. We consider the following specialized content distribution application: a group of users equipped with wireless devices build an ad hoc network in order cooperatively to retrieve information from certain regions (the mission sites). Each user requires access to some set of information items originating from sources lying within a region. Each user desires low-latency access to its desired data items, upon request (i.e., when pulled). In order to minimize average response time, we allow users to pull data either directly from sources or, when possible, from other nearby users who have already pulled, and continue to carry, the desired data items. That is, we allow for data to be pushed to one user and then pulled by one or more additional users. The total latency experienced by a user vis-vis a certain data item is then in general a combination of the push delay and the pull delay. We assume each delay time is a function of the hop distance between the pair of points in question. Our goal in this paper is to assign data to mobile users, in order to minimize the total cost and the average latency experienced by all the users. In a static setting, we solve this problem in two different schemes, one of which is easy to solve but wasteful, one of which relates to NP-hard problems but is less so. Then in a dynamic setting, we adapt the algorithm for the static setting and develop a new algorithm with respect to users' gradual arrival. In the end we show a trade-off can be made between minimizing the cost and latency.

Reduced brain resting-state network specificity in infants compared with adults.

PubMed

Wylie, Korey P; Rojas, Donald C; Ross, Randal G; Hunter, Sharon K; Maharajh, Keeran; Cornier, Marc-Andre; Tregellas, Jason R

2014-01-01

Infant resting-state networks do not exhibit the same connectivity patterns as those of young children and adults. Current theories of brain development emphasize developmental progression in regional and network specialization. We compared infant and adult functional connectivity, predicting that infants would exhibit less regional specificity and greater internetwork communication compared with adults. Functional magnetic resonance imaging at rest was acquired in 12 healthy, term infants and 17 adults. Resting-state networks were extracted, using independent components analysis, and the resulting components were then compared between the adult and infant groups. Adults exhibited stronger connectivity in the posterior cingulate cortex node of the default mode network, but infants had higher connectivity in medial prefrontal cortex/anterior cingulate cortex than adults. Adult connectivity was typically higher than infant connectivity within structures previously associated with the various networks, whereas infant connectivity was frequently higher outside of these structures. Internetwork communication was significantly higher in infants than in adults. We interpret these findings as consistent with evidence suggesting that resting-state network development is associated with increasing spatial specificity, possibly reflecting the corresponding functional specialization of regions and their interconnections through experience.

Ground-state coding in partially connected neural networks

NASA Technical Reports Server (NTRS)

Baram, Yoram

1989-01-01

Patterns over (-1,0,1) define, by their outer products, partially connected neural networks, consisting of internally strongly connected, externally weakly connected subnetworks. The connectivity patterns may have highly organized structures, such as lattices and fractal trees or nests. Subpatterns over (-1,1) define the subcodes stored in the subnetwork, that agree in their common bits. It is first shown that the code words are locally stable stares of the network, provided that each of the subcodes consists of mutually orthogonal words or of, at most, two words. Then it is shown that if each of the subcodes consists of two orthogonal words, the code words are the unique ground states (absolute minima) of the Hamiltonian associated with the network. The regions of attraction associated with the code words are shown to grow with the number of subnetworks sharing each of the neurons. Depending on the particular network architecture, the code sizes of partially connected networks can be vastly greater than those of fully connected ones and their error correction capabilities can be significantly greater than those of the disconnected subnetworks. The codes associated with lattice-structured and hierarchical networks are discussed in some detail.

Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease

PubMed Central

Chong, Joanna Su Xian; Liu, Siwei; Loke, Yng Miin; Hilal, Saima; Ikram, Mohammad Kamran; Xu, Xin; Tan, Boon Yeow; Venketasubramanian, Narayanaswamy; Chen, Christopher Li-Hsian

2017-01-01

Abstract Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer’s disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer’s disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer’s disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks—the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer’s disease patients with and without cerebrovascular disease. Alzheimer’s disease patients without cerebrovascular disease, but not Alzheimer’s disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer’s disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer’s disease patients with and without cerebrovascular disease. Across Alzheimer’s disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer’s disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer’s disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer’s disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer’s disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer’s disease network degeneration phenotype. PMID:29053778

Noise-induced relations between network connectivity and dynamics

NASA Astrophysics Data System (ADS)

Ching, Emily Sc

Many biological systems of interest can be represented as networks of many nodes that are interacting with one another. Often these systems are subject to external influence or noise. One of the central issues is to understand the relation between dynamics and the interaction pattern of the system or the connectivity structure of the network. In particular, a challenging problem is to infer the network connectivity structure from the dynamics. In this talk, we show that for stochastic dynamical systems subjected to noise, the presence of noise gives rise to mathematical relations between the network connectivity structure and quantities that can be calculated using solely the time-series measurements of the dynamics of the nodes. We present these relations for both undirected networks with bidirectional coupling and directed networks with directional coupling and discuss how such relations can be utilized to infer the network connectivity structure of the systems. Work supported by the Hong Kong Research Grants Council under Grant No. CUHK 14300914.

Consensus between Pipelines in Structural Brain Networks

PubMed Central

Parker, Christopher S.; Deligianni, Fani; Cardoso, M. Jorge; Daga, Pankaj; Modat, Marc; Dayan, Michael; Clark, Chris A.

2014-01-01

Structural brain networks may be reconstructed from diffusion MRI tractography data and have great potential to further our understanding of the topological organisation of brain structure in health and disease. Network reconstruction is complex and involves a series of processesing methods including anatomical parcellation, registration, fiber orientation estimation and whole-brain fiber tractography. Methodological choices at each stage can affect the anatomical accuracy and graph theoretical properties of the reconstructed networks, meaning applying different combinations in a network reconstruction pipeline may produce substantially different networks. Furthermore, the choice of which connections are considered important is unclear. In this study, we assessed the similarity between structural networks obtained using two independent state-of-the-art reconstruction pipelines. We aimed to quantify network similarity and identify the core connections emerging most robustly in both pipelines. Similarity of network connections was compared between pipelines employing different atlases by merging parcels to a common and equivalent node scale. We found a high agreement between the networks across a range of fiber density thresholds. In addition, we identified a robust core of highly connected regions coinciding with a peak in similarity across network density thresholds, and replicated these results with atlases at different node scales. The binary network properties of these core connections were similar between pipelines but showed some differences in atlases across node scales. This study demonstrates the utility of applying multiple structural network reconstrution pipelines to diffusion data in order to identify the most important connections for further study. PMID:25356977

Disrupted Brain Functional Organization in Epilepsy Revealed by Graph Theory Analysis.

PubMed

Song, Jie; Nair, Veena A; Gaggl, Wolfgang; Prabhakaran, Vivek

2015-06-01

The human brain is a complex and dynamic system that can be modeled as a large-scale brain network to better understand the reorganizational changes secondary to epilepsy. In this study, we developed a brain functional network model using graph theory methods applied to resting-state fMRI data acquired from a group of epilepsy patients and age- and gender-matched healthy controls. A brain functional network model was constructed based on resting-state functional connectivity. A minimum spanning tree combined with proportional thresholding approach was used to obtain sparse connectivity matrices for each subject, which formed the basis of brain networks. We examined the brain reorganizational changes in epilepsy thoroughly at the level of the whole brain, the functional network, and individual brain regions. At the whole-brain level, local efficiency was significantly decreased in epilepsy patients compared with the healthy controls. However, global efficiency was significantly increased in epilepsy due to increased number of functional connections between networks (although weakly connected). At the functional network level, there were significant proportions of newly formed connections between the default mode network and other networks and between the subcortical network and other networks. There was a significant proportion of decreasing connections between the cingulo-opercular task control network and other networks. Individual brain regions from different functional networks, however, showed a distinct pattern of reorganizational changes in epilepsy. These findings suggest that epilepsy alters brain efficiency in a consistent pattern at the whole-brain level, yet alters brain functional networks and individual brain regions differently.

Risperidone Effects on Brain Dynamic Connectivity-A Prospective Resting-State fMRI Study in Schizophrenia.

PubMed

Lottman, Kristin K; Kraguljac, Nina V; White, David M; Morgan, Charity J; Calhoun, Vince D; Butt, Allison; Lahti, Adrienne C

2017-01-01

Resting-state functional connectivity studies in schizophrenia evaluating average connectivity over the entire experiment have reported aberrant network integration, but findings are variable. Examining time-varying (dynamic) functional connectivity may help explain some inconsistencies. We assessed dynamic network connectivity using resting-state functional MRI in patients with schizophrenia, while unmedicated ( n  = 34), after 1 week ( n  = 29) and 6 weeks of treatment with risperidone ( n  = 24), as well as matched controls at baseline ( n  = 35) and after 6 weeks ( n  = 19). After identifying 41 independent components (ICs) comprising resting-state networks, sliding window analysis was performed on IC timecourses using an optimal window size validated with linear support vector machines. Windowed correlation matrices were then clustered into three discrete connectivity states (a relatively sparsely connected state, a relatively abundantly connected state, and an intermediately connected state). In unmedicated patients, static connectivity was increased between five pairs of ICs and decreased between two pairs of ICs when compared to controls, dynamic connectivity showed increased connectivity between the thalamus and somatomotor network in one of the three states. State statistics indicated that, in comparison to controls, unmedicated patients had shorter mean dwell times and fraction of time spent in the sparsely connected state, and longer dwell times and fraction of time spent in the intermediately connected state. Risperidone appeared to normalize mean dwell times after 6 weeks, but not fraction of time. Results suggest that static connectivity abnormalities in schizophrenia may partly be related to altered brain network temporal dynamics rather than consistent dysconnectivity within and between functional networks and demonstrate the importance of implementing complementary data analysis techniques.

On the Inference of Functional Circadian Networks Using Granger Causality

PubMed Central

Pourzanjani, Arya; Herzog, Erik D.; Petzold, Linda R.

2015-01-01

Being able to infer one way direct connections in an oscillatory network such as the suprachiastmatic nucleus (SCN) of the mammalian brain using time series data is difficult but crucial to understanding network dynamics. Although techniques have been developed for inferring networks from time series data, there have been no attempts to adapt these techniques to infer directional connections in oscillatory time series, while accurately distinguishing between direct and indirect connections. In this paper an adaptation of Granger Causality is proposed that allows for inference of circadian networks and oscillatory networks in general called Adaptive Frequency Granger Causality (AFGC). Additionally, an extension of this method is proposed to infer networks with large numbers of cells called LASSO AFGC. The method was validated using simulated data from several different networks. For the smaller networks the method was able to identify all one way direct connections without identifying connections that were not present. For larger networks of up to twenty cells the method shows excellent performance in identifying true and false connections; this is quantified by an area-under-the-curve (AUC) 96.88%. We note that this method like other Granger Causality-based methods, is based on the detection of high frequency signals propagating between cell traces. Thus it requires a relatively high sampling rate and a network that can propagate high frequency signals. PMID:26413748

Salience Network Connectivity Modulates Skin Conductance Responses in Predicting Arousal Experience

PubMed Central

Xia, Chenjie; Touroutoglou, Alexandra; Quigley, Karen S.; Barrett, Lisa Feldman; Dickerson, Bradford C.

2017-01-01

Individual differences in arousal experience have been linked to differences in resting-state salience network connectivity strength. In this study, we investigated how adding task-related skin conductance responses (SCR), a measure of sympathetic autonomic nervous system activity, can predict additional variance in arousal experience. Thirty-nine young adults rated their subjective experience of arousal to emotionally evocative images while SCRs were measured. They also underwent a separate resting-state fMRI scan. Greater SCR reactivity (an increased number of task-related SCRs) to emotional images and stronger intrinsic salience network connectivity independently predicted more intense experiences of arousal. Salience network connectivity further moderated the effect of SCR reactivity: In individuals with weak salience network connectivity, SCR reactivity more significantly predicted arousal experience, whereas in those with strong salience network connectivity, SCR reactivity played little role in predicting arousal experience. This interaction illustrates the degeneracy in neural mechanisms driving individual differences in arousal experience and highlights the intricate interplay between connectivity in central visceromotor neural circuitry and peripherally expressed autonomic responses in shaping arousal experience. PMID:27991182

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

NASA Astrophysics Data System (ADS)

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 migration) and indirectly (e.g., stream temperature modeling). Additionally, our results inform management and regulatory needs such as estimating connectivity for entire river networks as a basis for regulation, and identifying the complexity of a shifting baseline in identifying a regulatory basis.

Track-weighted functional connectivity (TW-FC): a tool for characterizing the structural-functional connections in the brain.

PubMed

Calamante, Fernando; Masterton, Richard A J; Tournier, Jacques-Donald; Smith, Robert E; Willats, Lisa; Raffelt, David; Connelly, Alan

2013-04-15

MRI provides a powerful tool for studying the functional and structural connections in the brain non-invasively. The technique of functional connectivity (FC) exploits the intrinsic temporal correlations of slow spontaneous signal fluctuations to characterise brain functional networks. In addition, diffusion MRI fibre-tracking can be used to study the white matter structural connections. In recent years, there has been considerable interest in combining these two techniques to provide an overall structural-functional description of the brain. In this work we applied the recently proposed super-resolution track-weighted imaging (TWI) methodology to demonstrate how whole-brain fibre-tracking data can be combined with FC data to generate a track-weighted (TW) FC map of FC networks. The method was applied to data from 8 healthy volunteers, and illustrated with (i) FC networks obtained using a seeded connectivity-based analysis (seeding in the precuneus/posterior cingulate cortex, PCC, known to be part of the default mode network), and (ii) with FC networks generated using independent component analysis (in particular, the default mode, attention, visual, and sensory-motor networks). TW-FC maps showed high intensity in white matter structures connecting the nodes of the FC networks. For example, the cingulum bundles show the strongest TW-FC values in the PCC seeded-based analysis, due to their major role in the connection between medial frontal cortex and precuneus/posterior cingulate cortex; similarly the superior longitudinal fasciculus was well represented in the attention network, the optic radiations in the visual network, and the corticospinal tract and corpus callosum in the sensory-motor network. The TW-FC maps highlight the white matter connections associated with a given FC network, and their intensity in a given voxel reflects the functional connectivity of the part of the nodes of the network linked by the structural connections traversing that voxel. They therefore contain a different (and novel) image contrast from that of the images used to generate them. The results shown in this study illustrate the potential of the TW-FC approach for the fusion of structural and functional data into a single quantitative image. This technique could therefore have important applications in neuroscience and neurology, such as for voxel-based comparison studies. Copyright © 2012 Elsevier Inc. All rights reserved.

The connectivity structure, giant strong component and centrality of metabolic networks.

PubMed

Ma, Hong-Wu; Zeng, An-Ping

2003-07-22

Structural and functional analysis of genome-based large-scale metabolic networks is important for understanding the design principles and regulation of the metabolism at a system level. The metabolic network is conventionally considered to be highly integrated and very complex. A rational reduction of the metabolic network to its core structure and a deeper understanding of its functional modules are important. In this work, we show that the metabolites in a metabolic network are far from fully connected. A connectivity structure consisting of four major subsets of metabolites and reactions, i.e. a fully connected sub-network, a substrate subset, a product subset and an isolated subset is found to exist in metabolic networks of 65 fully sequenced organisms. The largest fully connected part of a metabolic network, called 'the giant strong component (GSC)', represents the most complicated part and the core of the network and has the feature of scale-free networks. The average path length of the whole network is primarily determined by that of the GSC. For most of the organisms, GSC normally contains less than one-third of the nodes of the network. This connectivity structure is very similar to the 'bow-tie' structure of World Wide Web. Our results indicate that the bow-tie structure may be common for large-scale directed networks. More importantly, the uncovered structure feature makes a structural and functional analysis of large-scale metabolic network more amenable. As shown in this work, comparing the closeness centrality of the nodes in the GSC can identify the most central metabolites of a metabolic network. To quantitatively characterize the overall connection structure of the GSC we introduced the term 'overall closeness centralization index (OCCI)'. OCCI correlates well with the average path length of the GSC and is a useful parameter for a system-level comparison of metabolic networks of different organisms. http://genome.gbf.de/bioinformatics/

Functional network integrity presages cognitive decline in preclinical Alzheimer disease.

PubMed

Buckley, Rachel F; Schultz, Aaron P; Hedden, Trey; Papp, Kathryn V; Hanseeuw, Bernard J; Marshall, Gad; Sepulcre, Jorge; Smith, Emily E; Rentz, Dorene M; Johnson, Keith A; Sperling, Reisa A; Chhatwal, Jasmeer P

2017-07-04

To examine the utility of resting-state functional connectivity MRI (rs-fcMRI) measurements of network integrity as a predictor of future cognitive decline in preclinical Alzheimer disease (AD). A total of 237 clinically normal older adults (aged 63-90 years, Clinical Dementia Rating 0) underwent baseline β-amyloid (Aβ) imaging with Pittsburgh compound B PET and structural and rs-fcMRI. We identified 7 networks for analysis, including 4 cognitive networks (default, salience, dorsal attention, and frontoparietal control) and 3 noncognitive networks (primary visual, extrastriate visual, motor). Using linear and curvilinear mixed models, we used baseline connectivity in these networks to predict longitudinal changes in preclinical Alzheimer cognitive composite (PACC) performance, both alone and interacting with Aβ burden. Median neuropsychological follow-up was 3 years. Baseline connectivity in the default, salience, and control networks predicted longitudinal PACC decline, unlike connectivity in the dorsal attention and all noncognitive networks. Default, salience, and control network connectivity was also synergistic with Aβ burden in predicting decline, with combined higher Aβ and lower connectivity predicting the steepest curvilinear decline in PACC performance. In clinically normal older adults, lower functional connectivity predicted more rapid decline in PACC scores over time, particularly when coupled with increased Aβ burden. Among examined networks, default, salience, and control networks were the strongest predictors of rate of change in PACC scores, with the inflection point of greatest decline beyond the fourth year of follow-up. These results suggest that rs-fcMRI may be a useful predictor of early, AD-related cognitive decline in clinical research settings. © 2017 American Academy of Neurology.

Functional resting-state networks are differentially affected in schizophrenia

PubMed Central

Woodward, Neil D.; Rogers, Baxter; Heckers, Stephan

2011-01-01

Neurobiological theories posit that schizophrenia relates to disturbances in connectivity between brain regions. Resting-state functional magnetic resonance imaging is a powerful tool for examining functional connectivity and has revealed several canonical brain networks, including the default mode, dorsal attention, executive control, and salience networks. The purpose of this study was to examine changes in these networks in schizophrenia. 42 patients with schizophrenia and 61 healthy subjects completed a RS-fMRI scanning session. Seed-based region-of-interest correlation analysis was used to identify the default mode, dorsal attention, executive control, and salience networks. Compared to healthy subjects, individuals with schizophrenia demonstrated greater connectivity between the posterior cingulate cortex, a key hub of the default mode, and the left inferior gyrus, left middle frontal gyrus, and left middle temporal gyrus. Interestingly, these regions were more strongly connected to the executive control network in healthy control subjects. In contrast to the default mode, patients demonstrated less connectivity in the executive control and dorsal attention networks. No differences were observed in the salience network. The results indicate that resting-state networks are differentially affected in schizophrenia. The alterations are characterized by reduced segregation between the default mode and executive control networks in the prefrontal cortex and temporal lobe, and reduced connectivity in the dorsal attention and executive control networks. The changes suggest that the process of functional specialization is altered in schizophrenia. Further work is needed to determine if the alterations are related to disturbances in white matter connectivity, neurodevelopmental abnormalities, and genetic risk for schizophrenia. PMID:21458238

Agent-Based Modeling of China's Rural-Urban Migration and Social Network Structure.

PubMed

Fu, Zhaohao; Hao, Lingxin

2018-01-15

We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k -core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.

Agent-based modeling of China's rural-urban migration and social network structure

NASA Astrophysics Data System (ADS)

Fu, Zhaohao; Hao, Lingxin

2018-01-01

We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k-core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.

Dissociated functional connectivity profiles for motor and attention deficits in acute right-hemisphere stroke

PubMed Central

Ramsey, Lenny; Rengachary, Jennifer; Zinn, Kristi; Siegel, Joshua S.; Metcalf, Nicholas V.; Strube, Michael J.; Snyder, Abraham Z.; Corbetta, Maurizio; Shulman, Gordon L.

2016-01-01

Strokes often cause multiple behavioural deficits that are correlated at the population level. Here, we show that motor and attention deficits are selectively associated with abnormal patterns of resting state functional connectivity in the dorsal attention and motor networks. We measured attention and motor deficits in 44 right hemisphere-damaged patients with a first-time stroke at 1–2 weeks post-onset. The motor battery included tests that evaluated deficits in both upper and lower extremities. The attention battery assessed both spatial and non-spatial attention deficits. Summary measures for motor and attention deficits were identified through principal component analyses on the raw behavioural scores. Functional connectivity in structurally normal cortex was estimated based on the temporal correlation of blood oxygenation level-dependent signals measured at rest with functional magnetic resonance imaging. Any correlation between motor and attention deficits and between functional connectivity in the dorsal attention network and motor networks that might spuriously affect the relationship between each deficit and functional connectivity was statistically removed. We report a double dissociation between abnormal functional connectivity patterns and attention and motor deficits, respectively. Attention deficits were significantly more correlated with abnormal interhemispheric functional connectivity within the dorsal attention network than motor networks, while motor deficits were significantly more correlated with abnormal interhemispheric functional connectivity patterns within the motor networks than dorsal attention network. These findings indicate that functional connectivity patterns in structurally normal cortex following a stroke link abnormal physiology in brain networks to the corresponding behavioural deficits. PMID:27225794

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Synchronization in Complex Networks with Multiple Connections

NASA Astrophysics Data System (ADS)

Wu, Qing-Chu; Fu, Xin-Chu; Sun, Wei-Gang

2010-01-01

In this paper a class of networks with multiple connections are discussed. The multiple connections include two different types of links between nodes in complex networks. For this new model, we give a simple generating procedure. Furthermore, we investigate dynamical synchronization behavior in a delayed two-layer network, giving corresponding theoretical analysis and numerical examples.

Experimental evidence for the effect of habitat loss on the dynamics of migratory networks.

PubMed

Betini, Gustavo S; Fitzpatrick, Mark J; Norris, D Ryan

2015-06-01

Migratory animals present a unique challenge for understanding the consequences of habitat loss on population dynamics because individuals are typically distributed over a series of interconnected breeding and non-breeding sites (termed migratory network). Using replicated breeding and non-breeding populations of Drosophila melanogaster and a mathematical model, we investigated three hypotheses to explain how habitat loss influenced the dynamics of populations in networks with different degrees of connectivity between breeding and non-breeding seasons. We found that habitat loss increased the degree of connectivity in the network and influenced population size at sites that were not directly connected to the site where habitat loss occurred. However, connected networks only buffered global population declines at high levels of habitat loss. Our results demonstrate why knowledge of the patterns of connectivity across a species range is critical for predicting the effects of environmental change and provide empirical evidence for why connected migratory networks are commonly found in nature. © 2015 John Wiley & Sons Ltd/CNRS.

Functional connectivity in the developing brain: A longitudinal study from 4 to 9 months of age

PubMed Central

Damaraju, E.; Caprihan, A.; Lowe, J.R.; Allen, E.A.; Calhoun, V.D.; Phillips, J.P.

2013-01-01

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9 months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9 months. However at 9 months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age. PMID:23994454

Functional connectivity in the developing brain: a longitudinal study from 4 to 9months of age.

PubMed

Damaraju, E; Caprihan, A; Lowe, J R; Allen, E A; Calhoun, V D; Phillips, J P

2014-01-01

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9months. However at 9months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age. © 2013.

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

PubMed Central

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

Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging.

PubMed

Syed, Maleeha F; Lindquist, Martin A; Pillai, Jay J; Agarwal, Shruti; Gujar, Sachin K; Choe, Ann S; Caffo, Brian; Sair, Haris I

2017-12-01

Functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the dynamic conditional correlation model to rs-fMRI data of 20 healthy subjects. k-Means clustering was used to determine an optimal number of discrete connectivity states (k = 10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.

Motor deficits correlate with resting state motor network connectivity in patients with brain tumours

PubMed Central

Mikell, Charles B.; Youngerman, Brett E.; Liston, Conor; Sisti, Michael B.; Bruce, Jeffrey N.; Small, Scott A.; McKhann, Guy M.

2012-01-01

While a tumour in or abutting primary motor cortex leads to motor weakness, how tumours elsewhere in the frontal or parietal lobes affect functional connectivity in a weak patient is less clear. We hypothesized that diminished functional connectivity in a distributed network of motor centres would correlate with motor weakness in subjects with brain masses. Furthermore, we hypothesized that interhemispheric connections would be most vulnerable to subtle disruptions in functional connectivity. We used task-free functional magnetic resonance imaging connectivity to probe motor networks in control subjects and patients with brain tumours (n = 22). Using a control dataset, we developed a method for automated detection of key nodes in the motor network, including the primary motor cortex, supplementary motor area, premotor area and superior parietal lobule, based on the anatomic location of the hand-motor knob in the primary motor cortex. We then calculated functional connectivity between motor network nodes in control subjects, as well as patients with and without brain masses. We used this information to construct weighted, undirected graphs, which were then compared to variables of interest, including performance on a motor task, the grooved pegboard. Strong connectivity was observed within the identified motor networks between all nodes bilaterally, and especially between the primary motor cortex and supplementary motor area. Reduced connectivity was observed in subjects with motor weakness versus subjects with normal strength (P < 0.001). This difference was driven mostly by decreases in interhemispheric connectivity between the primary motor cortices (P < 0.05) and between the left primary motor cortex and the right premotor area (P < 0.05), as well as other premotor area connections. In the subjects without motor weakness, however, performance on the grooved pegboard did not relate to interhemispheric connectivity, but rather was inversely correlated with connectivity between the left premotor area and left supplementary motor area, for both the left and the right hands (P < 0.01). Finally, two subjects who experienced severe weakness following surgery for their brain tumours were followed longitudinally, and the subject who recovered showed reconstitution of her motor network at follow-up. The subject who was persistently weak did not reconstitute his motor network. Motor weakness in subjects with brain tumours that do not involve primary motor structures is associated with decreased connectivity within motor functional networks, particularly interhemispheric connections. Motor networks become weaker as the subjects become weaker, and may become strong again during motor recovery. PMID:22408270

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

PubMed

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

2012-03-01

Abnormal connectivity of the anticorrelated intrinsic networks, the task-negative network (TNN), and the task-positive network (TPN) is implicated in schizophrenia. Comparisons between schizophrenic patients and their unaffected siblings enable further understanding of illness susceptibility and pathophysiology. We examined the resting-state connectivity differences in the intrinsic networks between schizophrenic patients, their unaffected siblings, and healthy controls. Resting-state functional magnetic resonance images were obtained from 25 individuals in each subject group. The posterior cingulate cortex/precuneus and right dorsolateral prefrontal cortex were used as seed regions to identify the TNN and TPN through functional connectivity analysis. Interregional connectivity strengths were analyzed using overlapped intrinsic networks composed of regions common to all subject groups. Schizophrenic patients and their unaffected siblings showed increased connectivity in the TNN between the bilateral inferior temporal gyri. By contrast, schizophrenic patients alone demonstrated increased connectivity between the posterior cingulate cortex/precuneus and left inferior temporal gyrus and between the ventral medial prefrontal cortex and right lateral parietal cortex in the TNN. Schizophrenic patients exhibited increased connectivity between the left dorsolateral prefrontal cortex and right inferior frontal gyrus in the TPN relative to their unaffected siblings, though this trend only approached statistical significance in comparison to healthy controls. Resting-state hyperconnectivity of the intrinsic networks may disrupt network coordination and thereby contribute to the pathophysiology of schizophrenia. Similar, though milder, hyperconnectivity of the TNN in unaffected siblings of schizophrenic patients may contribute to the identification of schizophrenia endophenotypes and ultimately to the determination of schizophrenia risk genes.

Reduced integration and differentiation of the imitation network in autism: A combined functional connectivity magnetic resonance imaging and diffusion-weighted imaging study.

PubMed

Fishman, Inna; Datko, Michael; Cabrera, Yuliana; Carper, Ruth A; Müller, Ralph-Axel

2015-12-01

Converging evidence indicates that brain abnormalities in autism spectrum disorder (ASD) involve atypical network connectivity, but few studies have integrated functional with structural connectivity measures. This multimodal investigation examined functional and structural connectivity of the imitation network in children and adolescents with ASD, and its links with clinical symptoms. Resting state functional magnetic resonance imaging and diffusion-weighted imaging were performed in 35 participants with ASD and 35 typically developing controls, aged 8 to 17 years, matched for age, gender, intelligence quotient, and head motion. Within-network analyses revealed overall reduced functional connectivity (FC) between distributed imitation regions in the ASD group. Whole brain analyses showed that underconnectivity in ASD occurred exclusively in regions belonging to the imitation network, whereas overconnectivity was observed between imitation nodes and extraneous regions. Structurally, reduced fractional anisotropy and increased mean diffusivity were found in white matter tracts directly connecting key imitation regions with atypical FC in ASD. These differences in microstructural organization of white matter correlated with weaker FC and greater ASD symptomatology. Findings demonstrate atypical connectivity of the brain network supporting imitation in ASD, characterized by a highly specific pattern. This pattern of underconnectivity within, but overconnectivity outside the functional network is in contrast with typical development and suggests reduced network integration and differentiation in ASD. Our findings also indicate that atypical connectivity of the imitation network may contribute to ASD clinical symptoms, highlighting the role of this fundamental social cognition ability in the pathophysiology of ASD. © 2015 American Neurological Association.

Minimum spanning tree analysis of the human connectome.

PubMed

van Dellen, Edwin; Sommer, Iris E; Bohlken, Marc M; Tewarie, Prejaas; Draaisma, Laurijn; Zalesky, Andrew; Di Biase, Maria; Brown, Jesse A; Douw, Linda; Otte, Willem M; Mandl, René C W; Stam, Cornelis J

2018-06-01

One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion-weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null-model. The MST of individual subjects matched this reference MST for a mean 58%-88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so-called rich club nodes (a subset of high-degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical-subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Top-Down Network Effective Connectivity in Abstinent Substance Dependent Individuals

PubMed Central

Regner, Michael F.; Saenz, Naomi; Maharajh, Keeran; Yamamoto, Dorothy J.; Mohl, Brianne; Wylie, Korey; Tregellas, Jason; Tanabe, Jody

2016-01-01

Objective We hypothesized that compared to healthy controls, long-term abstinent substance dependent individuals (SDI) will differ in their effective connectivity between large-scale brain networks and demonstrate increased directional information from executive control to interoception-, reward-, and habit-related networks. In addition, using graph theory to compare network efficiencies we predicted decreased small-worldness in SDI compared to controls. Methods 50 SDI and 50 controls of similar sex and age completed psychological surveys and resting state fMRI. fMRI results were analyzed using group independent component analysis; 14 networks-of-interest (NOI) were selected using template matching to a canonical set of resting state networks. The number, direction, and strength of connections between NOI were analyzed with Granger Causality. Within-group thresholds were p<0.005 using a bootstrap permutation. Between group thresholds were p<0.05, FDR-corrected for multiple comparisons. NOI were correlated with behavioral measures, and group-level graph theory measures were compared. Results Compared to controls, SDI showed significantly greater Granger causal connectivity from right executive control network (RECN) to dorsal default mode network (dDMN) and from dDMN to basal ganglia network (BGN). RECN was negatively correlated with impulsivity, behavioral approach, and negative affect; dDMN was positively correlated with impulsivity. Among the 14 NOI, SDI showed greater bidirectional connectivity; controls showed more unidirectional connectivity. SDI demonstrated greater global efficiency and lower local efficiency. Conclusions Increased effective connectivity in long-term abstinent drug users may reflect improved cognitive control over habit and reward processes. Higher global and lower local efficiency across all networks in SDI compared to controls may reflect connectivity changes associated with drug dependence or remission and requires future, longitudinal studies to confirm. PMID:27776135

Energy-efficient boarder node medium access control protocol for wireless sensor networks.

PubMed

Razaque, Abdul; Elleithy, Khaled M

2014-03-12

This paper introduces the design, implementation, and performance analysis of the scalable and mobility-aware hybrid protocol named boarder node medium access control (BN-MAC) for wireless sensor networks (WSNs), which leverages the characteristics of scheduled and contention-based MAC protocols. Like contention-based MAC protocols, BN-MAC achieves high channel utilization, network adaptability under heavy traffic and mobility, and low latency and overhead. Like schedule-based MAC protocols, BN-MAC reduces idle listening time, emissions, and collision handling at low cost at one-hop neighbor nodes and achieves high channel utilization under heavy network loads. BN-MAC is particularly designed for region-wise WSNs. Each region is controlled by a boarder node (BN), which is of paramount importance. The BN coordinates with the remaining nodes within and beyond the region. Unlike other hybrid MAC protocols, BN-MAC incorporates three promising models that further reduce the energy consumption, idle listening time, overhearing, and congestion to improve the throughput and reduce the latency. One of the models used with BN-MAC is automatic active and sleep (AAS), which reduces the ideal listening time. When nodes finish their monitoring process, AAS lets them automatically go into the sleep state to avoid the idle listening state. Another model used in BN-MAC is the intelligent decision-making (IDM) model, which helps the nodes sense the nature of the environment. Based on the nature of the environment, the nodes decide whether to use the active or passive mode. This decision power of the nodes further reduces energy consumption because the nodes turn off the radio of the transceiver in the passive mode. The third model is the least-distance smart neighboring search (LDSNS), which determines the shortest efficient path to the one-hop neighbor and also provides cross-layering support to handle the mobility of the nodes. The BN-MAC also incorporates a semi-synchronous feature with a low duty cycle, which is advantageous for reducing the latency and energy consumption for several WSN application areas to improve the throughput. BN-MAC uses a unique window slot size to enhance the contention resolution issue for improved throughput. BN-MAC also prefers to communicate within a one-hop destination using Anycast, which maintains load balancing to maintain network reliability. BN-MAC is introduced with the goal of supporting four major application areas: monitoring and behavioral areas, controlling natural disasters, human-centric applications, and tracking mobility and static home automation devices from remote places. These application areas require a congestion-free mobility-supported MAC protocol to guarantee reliable data delivery. BN-MAC was evaluated using network simulator-2 (ns2) and compared with other hybrid MAC protocols, such as Zebra medium access control (Z-MAC), advertisement-based MAC (A-MAC), Speck-MAC, adaptive duty cycle SMAC (ADC-SMAC), and low-power real-time medium access control (LPR-MAC). The simulation results indicate that BN-MAC is a robust and energy-efficient protocol that outperforms other hybrid MAC protocols in the context of quality of service (QoS) parameters, such as energy consumption, latency, throughput, channel access time, successful delivery rate, coverage efficiency, and average duty cycle.

Energy-Efficient Boarder Node Medium Access Control Protocol for Wireless Sensor Networks

PubMed Central

Razaque, Abdul; Elleithy, Khaled M.

2014-01-01

This paper introduces the design, implementation, and performance analysis of the scalable and mobility-aware hybrid protocol named boarder node medium access control (BN-MAC) for wireless sensor networks (WSNs), which leverages the characteristics of scheduled and contention-based MAC protocols. Like contention-based MAC protocols, BN-MAC achieves high channel utilization, network adaptability under heavy traffic and mobility, and low latency and overhead. Like schedule-based MAC protocols, BN-MAC reduces idle listening time, emissions, and collision handling at low cost at one-hop neighbor nodes and achieves high channel utilization under heavy network loads. BN-MAC is particularly designed for region-wise WSNs. Each region is controlled by a boarder node (BN), which is of paramount importance. The BN coordinates with the remaining nodes within and beyond the region. Unlike other hybrid MAC protocols, BN-MAC incorporates three promising models that further reduce the energy consumption, idle listening time, overhearing, and congestion to improve the throughput and reduce the latency. One of the models used with BN-MAC is automatic active and sleep (AAS), which reduces the ideal listening time. When nodes finish their monitoring process, AAS lets them automatically go into the sleep state to avoid the idle listening state. Another model used in BN-MAC is the intelligent decision-making (IDM) model, which helps the nodes sense the nature of the environment. Based on the nature of the environment, the nodes decide whether to use the active or passive mode. This decision power of the nodes further reduces energy consumption because the nodes turn off the radio of the transceiver in the passive mode. The third model is the least-distance smart neighboring search (LDSNS), which determines the shortest efficient path to the one-hop neighbor and also provides cross-layering support to handle the mobility of the nodes. The BN-MAC also incorporates a semi-synchronous feature with a low duty cycle, which is advantageous for reducing the latency and energy consumption for several WSN application areas to improve the throughput. BN-MAC uses a unique window slot size to enhance the contention resolution issue for improved throughput. BN-MAC also prefers to communicate within a one-hop destination using Anycast, which maintains load balancing to maintain network reliability. BN-MAC is introduced with the goal of supporting four major application areas: monitoring and behavioral areas, controlling natural disasters, human-centric applications, and tracking mobility and static home automation devices from remote places. These application areas require a congestion-free mobility-supported MAC protocol to guarantee reliable data delivery. BN-MAC was evaluated using network simulator-2 (ns2) and compared with other hybrid MAC protocols, such as Zebra medium access control (Z-MAC), advertisement-based MAC (A-MAC), Speck-MAC, adaptive duty cycle SMAC (ADC-SMAC), and low-power real-time medium access control (LPR-MAC). The simulation results indicate that BN-MAC is a robust and energy-efficient protocol that outperforms other hybrid MAC protocols in the context of quality of service (QoS) parameters, such as energy consumption, latency, throughput, channel access time, successful delivery rate, coverage efficiency, and average duty cycle. PMID:24625737

Electrical and chemical transmission between striatal GABAergic output neurones in rat brain slices

PubMed Central

Venance, Laurent; Glowinski, Jacques; Giaume, Christian

2004-01-01

Basal ganglia are interconnected subcortical nuclei, connected to the thalamus and all cortical areas involved in sensory motor control, limbic functions and cognition. The striatal output neurones (SONs), the major striatal population, are believed to act as detectors and integrators of distributed patterns of cerebral cortex inputs. Despite the key role of SONs in cortico-striatal information processing, little is known about their local interactions. Here, we report the existence and characterization of electrical and GABAergic transmission between SONs in rat brain slices. Tracer coupling (biocytin) incidence was high during the first two postnatal weeks and then decreased (postnatal days (P) 5–25, 60%; P25–30, 29%; n = 61). Electrical coupling was observed between 27% of SON pairs (coupling coefficient: 3.1 ± 0.3%, n = 89 at P15) and as shown by single-cell RT-PCR, several connexin (Cx) mRNAs were found to be expressed (Cx31.1, Cx32, Cx36 and Cx47). GABAergic synaptic transmission (abolished by bicuculline, a GABAA receptor antagonist) observed in 19% of SON pairs (n = 62) was reliable (mean failure rate of 6 ± 3%), precise (variation coefficient of latency, 0.06), strong (IPSC amplitudes of 38 ± 12 pA) and unidirectional. Interestingly, electrical and chemical transmission were mutually exclusive. These results suggest that preferential networks of electrically and chemically connected SONs, might be involved in the channelling of cortico-basal ganglia information processing. PMID:15235091

Structural Connectivity Relates to Perinatal Factors and Functional Impairment at 7 Years in Children Born Very Preterm

PubMed Central

Thompson, Deanne K.; Chen, Jian; Beare, Richard; Adamson, Christopher L.; Ellis, Rachel; Ahmadzai, Zohra M.; Kelly, Claire E.; Lee, Katherine J.; Zalesky, Andrew; Yang, Joseph Y.M.; Hunt, Rodney W.; Cheong, Jeanie L.Y.; Inder, Terrie E.; Doyle, Lex W.; Seal, Marc L.; Anderson, Peter J.

2016-01-01

Objective To use structural connectivity to (1) compare brain networks between typically and atypically developing (very preterm) children, (2) explore associations between potential perinatal developmental disturbances and brain networks, and (3) describe associations between brain networks and functional impairments in very preterm children. Methods 26 full-term and 107 very preterm 7-year-old children (born <30 weeks’ gestational age and/or <1250 g) underwent T1- and diffusion-weighted imaging. Global white matter fiber networks were produced using 80 cortical and subcortical nodes, and edges created using constrained spherical deconvolution-based tractography. Global graph theory metrics were analysed, and regional networks were identified using network-based statistics. Cognitive and motor function were assessed at 7 years of age. Results Compared with full-term children, very preterm children had reduced density, lower global efficiency and higher local efficiency. Those with lower gestational age at birth, infection or higher neonatal brain abnormality score had reduced connectivity. Reduced connectivity within a widespread network was predictive of impaired IQ, while reduced connectivity within the right parietal and temporal lobes was associated with motor impairment in very preterm children. Conclusions This study utilized an innovative structural connectivity pipeline to reveal that children born very preterm have less connected and less complex brain networks compared with typically developing term-born children. Adverse perinatal factors led to disturbances in white matter connectivity, which in turn are associated with impaired functional outcomes, highlighting novel structure-function relationships. PMID:27046108

Perturbed connectivity of the amygdala and its subregions with the central executive and default mode networks in chronic pain.

PubMed

Jiang, Ying; Oathes, Desmond; Hush, Julia; Darnall, Beth; Charvat, Mylea; Mackey, Sean; Etkin, Amit

2016-09-01

Maladaptive responses to pain-related distress, such as pain catastrophizing, amplify the impairments associated with chronic pain. Many of these aspects of chronic pain are similar to affective distress in clinical anxiety disorders. In light of the role of the amygdala in pain and affective distress, disruption of amygdalar functional connectivity in anxiety states, and its implication in the response to noxious stimuli, we investigated amygdala functional connectivity in 17 patients with chronic low back pain and 17 healthy comparison subjects, with respect to normal targets of amygdala subregions (basolateral vs centromedial nuclei), and connectivity to large-scale cognitive-emotional networks, including the default mode network, central executive network, and salience network. We found that patients with chronic pain had exaggerated and abnormal amygdala connectivity with central executive network, which was most exaggerated in patients with the greatest pain catastrophizing. We also found that the normally basolateral-predominant amygdala connectivity to the default mode network was blunted in patients with chronic pain. Our results therefore highlight the importance of the amygdala and its network-level interaction with large-scale cognitive/affective cortical networks in chronic pain, and help link the neurobiological mechanisms of cognitive theories for pain with other clinical states of affective distress.

[Construction and optimization of ecological network for nature reserves in Fujian Province, China].

PubMed

Gu, Fan; Huang, Yi Xiong; Chen, Chuan Ming; Cheng, Dong Liang; Guo, Jia Lei

2017-03-18

The nature reserve is very important to biodiversity maintenance. However, due to the urbanization, the nature reserve has been fragmented with reduction in area, leading to the loss of species diversity. Establishing ecological network can effectively connect the fragmented habitats and plays an important role in species conversation. In this paper, based on deciding habitat patches and the landscape cost surface in ArcGIS, a minimum cumulative resistance model was used to simulate the potential ecological network of Fujian provincial nature reserves. The connectivity and importance of network were analyzed and evaluated based on comparison of connectivity indices (including the integral index of connectivity and probability of connectivity) and gravity model both before and after the potential ecological network construction. The optimum ecological network optimization measures were proposed. The result demonstrated that woodlands, grasslands and wetlands together made up the important part of the nature reserve ecological network. The habitats with large area had a higher degree of importance in the network. After constructing the network, the connectivity level was significantly improved. Although interaction strength between different patches va-ried greatly, the corridors between patches with large interaction were very important. The research could provide scientific reference and basis for nature protection and planning in Fujian Province.

Connectivity: Performance Portable Algorithms for graph connectivity v. 0.1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Slota, George; Rajamanickam, Sivasankaran; Madduri, Kamesh

Graphs occur in several places in real world from road networks, social networks and scientific simulations. Connectivity is a graph analysis software to graph connectivity in modern architectures like multicore CPUs, Xeon Phi and GPUs.

Enhancing robustness of interdependent network by adding connectivity and dependence links

NASA Astrophysics Data System (ADS)

Cui, Pengshuai; Zhu, Peidong; Wang, Ke; Xun, Peng; Xia, Zhuoqun

2018-05-01

Enhancing robustness of interdependent networks by adding connectivity links has been researched extensively, however, few of them are focusing on adding both connectivity and dependence links to enhance robustness. In this paper, we aim to study how to allocate the limited costs reasonably to add both connectivity and dependence links. Firstly, we divide the attackers into stubborn attackers and smart attackers according to whether would they change their attack modes with the changing of network structure; Then by simulations, link addition strategies are given separately according to different attackers, with which we can allocate the limited costs to add connectivity links and dependence links reasonably and achieve more robustness than only adding connectivity links or dependence links. The results show that compared to only adding connectivity links or dependence links, allocating the limited resources reasonably and adding both connectivity links and dependence links could bring more robustness to the interdependent networks.

Genes and gene networks implicated in aggression related behaviour.

PubMed

Malki, Karim; Pain, Oliver; Du Rietz, Ebba; Tosto, Maria Grazia; Paya-Cano, Jose; Sandnabba, Kenneth N; de Boer, Sietse; Schalkwyk, Leonard C; Sluyter, Frans

2014-10-01

Aggressive behaviour is a major cause of mortality and morbidity. Despite of moderate heritability estimates, progress in identifying the genetic factors underlying aggressive behaviour has been limited. There are currently three genetic mouse models of high and low aggression created using selective breeding. This is the first study to offer a global transcriptomic characterization of the prefrontal cortex across all three genetic mouse models of aggression. A systems biology approach has been applied to transcriptomic data across the three pairs of selected inbred mouse strains (Turku Aggressive (TA) and Turku Non-Aggressive (TNA), Short Attack Latency (SAL) and Long Attack Latency (LAL) mice and North Carolina Aggressive (NC900) and North Carolina Non-Aggressive (NC100)), providing novel insight into the neurobiological mechanisms and genetics underlying aggression. First, weighted gene co-expression network analysis (WGCNA) was performed to identify modules of highly correlated genes associated with aggression. Probe sets belonging to gene modules uncovered by WGCNA were carried forward for network analysis using ingenuity pathway analysis (IPA). The RankProd non-parametric algorithm was then used to statistically evaluate expression differences across the genes belonging to modules significantly associated with aggression. IPA uncovered two pathways, involving NF-kB and MAPKs. The secondary RankProd analysis yielded 14 differentially expressed genes, some of which have previously been implicated in pathways associated with aggressive behaviour, such as Adrbk2. The results highlighted plausible candidate genes and gene networks implicated in aggression-related behaviour.

Using EMG to anticipate head motion for virtual-environment applications

NASA Technical Reports Server (NTRS)

Barniv, Yair; Aguilar, Mario; Hasanbelliu, Erion

2005-01-01

In virtual environment (VE) applications, where virtual objects are presented in a see-through head-mounted display, virtual images must be continuously stabilized in space in response to user's head motion. Time delays in head-motion compensation cause virtual objects to "swim" around instead of being stable in space which results in misalignment errors when overlaying virtual and real objects. Visual update delays are a critical technical obstacle for implementing head-mounted displays in applications such as battlefield simulation/training, telerobotics, and telemedicine. Head motion is currently measurable by a head-mounted 6-degrees-of-freedom inertial measurement unit. However, even given this information, overall VE-system latencies cannot be reduced under about 25 ms. We present a novel approach to eliminating latencies, which is premised on the fact that myoelectric signals from a muscle precede its exertion of force, thereby limb or head acceleration. We thus suggest utilizing neck-muscles' myoelectric signals to anticipate head motion. We trained a neural network to map such signals onto equivalent time-advanced inertial outputs. The resulting network can achieve time advances of up to 70 ms.

Cache Scheme Based on Pre-Fetch Operation in ICN

PubMed Central

Duan, Jie; Wang, Xiong; Xu, Shizhong; Liu, Yuanni; Xu, Chuan; Zhao, Guofeng

2016-01-01

Many recent researches focus on ICN (Information-Centric Network), in which named content becomes the first citizen instead of end-host. In ICN, Named content can be further divided into many small sized chunks, and chunk-based communication has merits over content-based communication. The universal in-network cache is one of the fundamental infrastructures for ICN. In this work, a chunk-level cache mechanism based on pre-fetch operation is proposed. The main idea is that, routers with cache store should pre-fetch and cache the next chunks which may be accessed in the near future according to received requests and cache policy for reducing the users’ perceived latency. Two pre-fetch driven modes are present to answer when and how to pre-fetch. The LRU (Least Recently Used) is employed for the cache replacement. Simulation results show that the average user perceived latency and hops can be decreased by employed this cache mechanism based on pre-fetch operation. Furthermore, we also demonstrate that the results are influenced by many factors, such as the cache capacity, Zipf parameters and pre-fetch window size. PMID:27362478

Using EMG to anticipate head motion for virtual-environment applications.

PubMed

Barniv, Yair; Aguilar, Mario; Hasanbelliu, Erion

2005-06-01

In virtual environment (VE) applications, where virtual objects are presented in a see-through head-mounted display, virtual images must be continuously stabilized in space in response to user's head motion. Time delays in head-motion compensation cause virtual objects to "swim" around instead of being stable in space which results in misalignment errors when overlaying virtual and real objects. Visual update delays are a critical technical obstacle for implementing head-mounted displays in applications such as battlefield simulation/training, telerobotics, and telemedicine. Head motion is currently measurable by a head-mounted 6-degrees-of-freedom inertial measurement unit. However, even given this information, overall VE-system latencies cannot be reduced under about 25 ms. We present a novel approach to eliminating latencies, which is premised on the fact that myoelectric signals from a muscle precede its exertion of force, thereby limb or head acceleration. We thus suggest utilizing neck-muscles' myoelectric signals to anticipate head motion. We trained a neural network to map such signals onto equivalent time-advanced inertial outputs. The resulting network can achieve time advances of up to 70 ms.

Spinal Cord Injury Disrupts Resting-State Networks in the Human Brain.

PubMed

Hawasli, Ammar H; Rutlin, Jerrel; Roland, Jarod L; Murphy, Rory K J; Song, Sheng-Kwei; Leuthardt, Eric C; Shimony, Joshua S; Ray, Wilson Z

2018-03-15

Despite 253,000 spinal cord injury (SCI) patients in the United States, little is known about how SCI affects brain networks. Spinal MRI provides only structural information with no insight into functional connectivity. Resting-state functional MRI (RS-fMRI) quantifies network connectivity through the identification of resting-state networks (RSNs) and allows detection of functionally relevant changes during disease. Given the robust network of spinal cord afferents to the brain, we hypothesized that SCI produces meaningful changes in brain RSNs. RS-fMRIs and functional assessments were performed on 10 SCI subjects. Blood oxygen-dependent RS-fMRI sequences were acquired. Seed-based correlation mapping was performed using five RSNs: default-mode (DMN), dorsal-attention (DAN), salience (SAL), control (CON), and somatomotor (SMN). RSNs were compared with normal control subjects using false-discovery rate-corrected two way t tests. SCI reduced brain network connectivity within the SAL, SMN, and DMN and disrupted anti-correlated connectivity between CON and SMN. When divided into separate cohorts, complete but not incomplete SCI disrupted connectivity within SAL, DAN, SMN and DMN and between CON and SMN. Finally, connectivity changed over time after SCI: the primary motor cortex decreased connectivity with the primary somatosensory cortex, the visual cortex decreased connectivity with the primary motor cortex, and the visual cortex decreased connectivity with the sensory parietal cortex. These unique findings demonstrate the functional network plasticity that occurs in the brain as a result of injury to the spinal cord. Connectivity changes after SCI may serve as biomarkers to predict functional recovery following an SCI and guide future therapy.

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

Altered Brain Functional Connectivity in Betel Quid-Dependent Chewers.

PubMed

Huang, Xiaojun; Pu, Weidan; Liu, Haihong; Li, Xinmin; Greenshaw, Andrew J; Dursun, Serdar M; Xue, Zhimin; Liu, Zhening

2017-01-01

Betel quid (BQ) is a common psychoactive substance worldwide with particularly high usage in many Asian countries. This study aimed to explore the effect of BQ use on functional connectivity by comparing global functional brain networks and their subset between BQ chewers and healthy controls (HCs). Resting-state functional magnetic resonance imaging (fMRI) was obtained from 24 betel quid-dependent (BQD) male chewers and 27 healthy male individuals on a 3.0T scanner. We used independent component analysis (ICA) to determine components that represent the brain's functional networks and their spatial aspects of functional connectivity. Two sample t -tests were used to identify the functional connectivity differences in each network between these two groups. Seventeen networks were identified by ICA. Nine of them showed connectivity differences between BQD and HCs (two sample t -tests, p  < 0.001 uncorrected). We found increased functional connectivity in the orbitofrontal, bilateral frontoparietal, frontotemporal, occipital/parietal, frontotemporal/cerebellum, and temporal/limbic networks, and decreased connectivity in the parietal and medial frontal/anterior cingulate networks in the BQD compared to the HCs. The betel quid dependence scale scores were positively related to the increased functional connectivity in the orbitofrontal ( r  = 0.39, p  = 0.03) while negatively related to the decreased functional connectivity in medial frontal/anterior cingulate networks ( r  = -0.35, p  = 0.02). Our findings provide further evidence that BQ chewing may lead to brain functional connectivity changes, which may play a key role in the psychological and physiological effects of BQ.