Field-effect Flow Control in Polymer Microchannel Networks

NASA Technical Reports Server (NTRS)

Sniadecki, Nathan; Lee, Cheng S.; Beamesderfer, Mike; DeVoe, Don L.

2003-01-01

A new Bio-MEMS electroosmotic flow (EOF) modulator for plastic microchannel networks has been developed. The EOF modulator uses field-effect flow control (FEFC) to adjust the zeta potential at the Parylene C microchannel wall. By setting a differential EOF pumping rate in two of the three microchannels at a T-intersection with EOF modulators, the induced pressure at the intersection generated pumping in the third, field-free microchannel. The EOF modulators are able to change the magnitude and direction of the pressure pumping by inducing either a negative or positive pressure at the intersection. The flow velocity is tracked by neutralized fluorescent microbeads in the microchannels. The proof-of-concept of the EOF modulator described here may be applied to complex plastic ,microchannel networks where individual microchannel flow rates are addressable by localized induced-pressure pumping.

Community Landscapes: An Integrative Approach to Determine Overlapping Network Module Hierarchy, Identify Key Nodes and Predict Network Dynamics

PubMed Central

Kovács, István A.; Palotai, Robin; Szalay, Máté S.; Csermely, Peter

2010-01-01

Background Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Findings Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics. Conclusions/Significance The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction. PMID:20824084

Between “design” and “bricolage”: Genetic networks, levels of selection, and adaptive evolution

PubMed Central

Wilkins, Adam S.

2007-01-01

The extent to which “developmental constraints” in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a “network perspective” may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed. PMID:17494754

Between "design" and "bricolage": genetic networks, levels of selection, and adaptive evolution.

PubMed

Wilkins, Adam S

2007-05-15

The extent to which "developmental constraints" in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a "network perspective" may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed.

Cognitive Radio for Tactical Wireless Communication Networks

DTIC Science & Technology

2011-10-09

Pursley. Demodulator Statistics for Enhanced Soft-Decision Decoding in CDMA Packet Radio Systems, ICC 2010 - 2010 IEEE International Conference on...likelihood ratio (LLR) metrics and distance metrics. In [BPR08], [BoP09], and [BPR11], we investigated direct-sequence spread-spectrum ( DS -SS...modulation formats, which are among the most robust formats for tactical cognitive radio networks. DS -SS modulation with adaptive soft-decision decoding is

Reconfigurable WDM-PON empowered by a low-cost 8-channel directly modulated laser module

NASA Astrophysics Data System (ADS)

Zhang, Yi-ming; Liu, Yu; Zhang, Zhi-ke; Zhao, Ze-ping; Tian, Ye; Zhu, Ning-hua

2017-11-01

A 10 Gbit/s 16-km-long reconfigurable wavelength-division-multiplexing passive optical network (WDM-PON) is presented empowered by a low-cost multi-channel directly modulated laser (DML) module. Compared with the case using discrete devices in conventional scheme, the proposed DML module provides a cost-effective solution with reduced complexity. The clear eye diagram and the bit error rate ( BER) of less than 2×10-7 with a sensitivity of -7 dBm are obtained. Due to the special packaging design, the crosstalk between channels under condition of simultaneous operation can be negligible.

Development of Power Supply Management Module for Radio Signal Repeaters of Automatic Metering Reading System in Variable Solar Density Conditions

NASA Astrophysics Data System (ADS)

Kondratjevs, K.; Zabasta, A.; Selmanovs-Pless, V.

2016-02-01

In recent years, there has been significant research focus that revolves around harvesting and minimising energy consumption by wireless sensor network nodes. When a sensor node is depleted of energy, it becomes unresponsive and disconnected from the network that can significantly influence the performance of the whole network. The purpose of the present research is to create a power supply management module in order to provide stable operating voltage for autonomous operations of radio signal repeaters, sensors or gateways of WSN. The developed management module is composed of a solar panel, lithium battery and power supply management module. The novelty of the research is the management module, which ensures stable and uninterrupted operations of electronic equipment in various power supply modes in different situations, simultaneously ensuring energy protection and sustainability of the module components. The management module is able to provide power supply of 5 V for electronics scheme independently, without power interruption switching between power sources and power flows in different directions.

A high capacity data centre network: simultaneous 4-PAM data at 20 Gbps and 2 GHz phase modulated RF clock signal over a single VCSEL carrier

NASA Astrophysics Data System (ADS)

Isoe, G. M.; Wassin, S.; Gamatham, R. R. G.; Leitch, A. W. R.; Gibbon, T. B.

2017-11-01

Optical fibre communication technologies are playing important roles in data centre networks (DCNs). Techniques for increasing capacity and flexibility for the inter-rack/pod communications in data centres have drawn remarkable attention in recent years. In this work, we propose a low complexity, reliable, alternative technique for increasing DCN capacity and flexibility through multi-signal modulation onto a single mode VCSEL carrier. A 20 Gbps 4-PAM data signal is directly modulated on a single mode 10 GHz bandwidth VCSEL carrier at 1310 nm, therefore, doubling the network bit rate. Carrier spectral efficiency is further maximized by modulating its phase attribute with a 2 GHz reference frequency (RF) clock signal. We, therefore, simultaneously transmit a 20 Gbps 4-PAM data signal and a phase modulated 2 GHz RF signal using a single mode 10 GHz bandwidth VCSEL carrier. It is the first time a single mode 10 GHz bandwidth VCSEL carrier is reported to simultaneously transmit a directly modulated 4-PAM data signal and a phase modulated RF clock signal. A receiver sensitivity of -10. 52 dBm was attained for a 20 Gbps 4-PAM VCSEL transmission. The 2 GHz phase modulated RF clock signal introduced a power budget penalty of 0.21 dB. Simultaneous distribution of both data and timing signals over shared infrastructure significantly increases the aggregated data rate at different optical network units within the DCN, without expensive optics investment. We further demonstrate on the design of a software-defined digital signal processing assisted receiver to efficiently recover the transmitted signal without employing costly receiver hardware.

Controllability and observability analysis for vertex domination centrality in directed networks

NASA Astrophysics Data System (ADS)

Wang, Bingbo; Gao, Lin; Gao, Yong; Deng, Yue; Wang, Yu

2014-06-01

Topological centrality is a significant measure for characterising the relative importance of a node in a complex network. For directed networks that model dynamic processes, however, it is of more practical importance to quantify a vertex's ability to dominate (control or observe) the state of other vertices. In this paper, based on the determination of controllable and observable subspaces under the global minimum-cost condition, we introduce a novel direction-specific index, domination centrality, to assess the intervention capabilities of vertices in a directed network. Statistical studies demonstrate that the domination centrality is, to a great extent, encoded by the underlying network's degree distribution and that most network positions through which one can intervene in a system are vertices with high domination centrality rather than network hubs. To analyse the interaction and functional dependence between vertices when they are used to dominate a network, we define the domination similarity and detect significant functional modules in glossary and metabolic networks through clustering analysis. The experimental results provide strong evidence that our indices are effective and practical in accurately depicting the structure of directed networks.

Controllability and observability analysis for vertex domination centrality in directed networks

PubMed Central

Wang, Bingbo; Gao, Lin; Gao, Yong; Deng, Yue; Wang, Yu

2014-01-01

Topological centrality is a significant measure for characterising the relative importance of a node in a complex network. For directed networks that model dynamic processes, however, it is of more practical importance to quantify a vertex's ability to dominate (control or observe) the state of other vertices. In this paper, based on the determination of controllable and observable subspaces under the global minimum-cost condition, we introduce a novel direction-specific index, domination centrality, to assess the intervention capabilities of vertices in a directed network. Statistical studies demonstrate that the domination centrality is, to a great extent, encoded by the underlying network's degree distribution and that most network positions through which one can intervene in a system are vertices with high domination centrality rather than network hubs. To analyse the interaction and functional dependence between vertices when they are used to dominate a network, we define the domination similarity and detect significant functional modules in glossary and metabolic networks through clustering analysis. The experimental results provide strong evidence that our indices are effective and practical in accurately depicting the structure of directed networks. PMID:24954137

Analysis of global gene expression in Brachypodium distachyon reveals extensive network plasticity in response to abiotic stress.

PubMed

Priest, Henry D; Fox, Samuel E; Rowley, Erik R; Murray, Jessica R; Michael, Todd P; Mockler, Todd C

2014-01-01

Brachypodium distachyon is a close relative of many important cereal crops. Abiotic stress tolerance has a significant impact on productivity of agriculturally important food and feedstock crops. Analysis of the transcriptome of Brachypodium after chilling, high-salinity, drought, and heat stresses revealed diverse differential expression of many transcripts. Weighted Gene Co-Expression Network Analysis revealed 22 distinct gene modules with specific profiles of expression under each stress. Promoter analysis implicated short DNA sequences directly upstream of module members in the regulation of 21 of 22 modules. Functional analysis of module members revealed enrichment in functional terms for 10 of 22 network modules. Analysis of condition-specific correlations between differentially expressed gene pairs revealed extensive plasticity in the expression relationships of gene pairs. Photosynthesis, cell cycle, and cell wall expression modules were down-regulated by all abiotic stresses. Modules which were up-regulated by each abiotic stress fell into diverse and unique gene ontology GO categories. This study provides genomics resources and improves our understanding of abiotic stress responses of Brachypodium.

Directly Phase-Modulated Light Source

NASA Astrophysics Data System (ADS)

Yuan, Z. L.; Fröhlich, B.; Lucamarini, M.; Roberts, G. L.; Dynes, J. F.; Shields, A. J.

2016-07-01

The art of imparting information onto a light wave by optical signal modulation is fundamental to all forms of optical communication. Among many schemes, direct modulation of laser diodes stands out as a simple, robust, and cost-effective method. However, the simultaneous changes in intensity, frequency, and phase have prevented its application in the field of secure quantum communication. Here, we propose and experimentally demonstrate a directly phase-modulated light source which overcomes the main disadvantages associated with direct modulation and is suitable for diverse applications such as coherent communications and quantum cryptography. The source separates the tasks of phase preparation and pulse generation between a pair of semiconductor lasers leading to very pure phase states. Moreover, the cavity-enhanced electro-optic effect enables the first example of subvolt half-wave phase modulation at high signal rates. The source is compact, stable, and versatile, and we show its potential to become the standard transmitter for future quantum communication networks based on attenuated laser pulses.

Shuttle S-band communications technical concepts

NASA Technical Reports Server (NTRS)

Seyl, J. W.; Seibert, W. W.; Porter, J. A.; Eggers, D. S.; Novosad, S. W.; Vang, H. A.; Lenett, S. D.; Lewton, W. A.; Pawlowski, J. F.

1985-01-01

Using the S-band communications system, shuttle orbiter can communicate directly with the Earth via the Ground Spaceflight Tracking and Data Network (GSTDN) or via the Tracking and Data Relay Satellite System (TDRSS). The S-band frequencies provide the primary links for direct Earth and TDRSS communications during all launch and entry/landing phases of shuttle missions. On orbit, S-band links are used when TDRSS Ku-band is not available, when conditions require orbiter attitudes unfavorable to Ku-band communications, or when the payload bay doors are closed. the S-band communications functional requirements, the orbiter hardware configuration, and the NASA S-band communications network are described. The requirements and implementation concepts which resulted in techniques for shuttle S-band hardware development discussed include: (1) digital voice delta modulation; (2) convolutional coding/Viterbi decoding; (3) critical modulation index for phase modulation using a Costas loop (phase-shift keying) receiver; (4) optimum digital data modulation parameters for continuous-wave frequency modulation; (5) intermodulation effects of subcarrier ranging and time-division multiplexing data channels; (6) radiofrequency coverage; and (7) despreading techniques under poor signal-to-noise conditions. Channel performance is reviewed.

Pharmacological modulation of pulvinar resting-state regional oscillations and network dynamics in major depression

PubMed Central

Tadayonnejad, Reza; Ajilore, Olusola; Mickey, Brian J.; Crane, Natania A.; Hsu, David T.; Kumar, Anand; Zubieta, Jon-Kar; Langenecker, Scott A.

2016-01-01

The pulvinar, the largest thalamus nucleus, has rich anatomical connections with several different cortical and subcortical regions suggesting its important involvement in high-level cognitive and emotional functions. Unfortunately, pulvinar dysfunction in psychiatric disorders particularly major depression disorder has not been thoroughly examined to date. In this study we explored the alterations in the baseline regional and network activities of the pulvinar in MDD by applying spectral analysis of resting-state oscillatory activity, functional connectivity and directed (effective) connectivity on resting-state fMRI data acquired from 20 healthy controls and 19 participants with MDD. Furthermore, we tested how pharmacological treatment with duloxetine can modulate the measured local and network variables in ten participants who completed treatment. Our results revealed a frequency-band dependent modulation of power spectrum characteristics of pulvinar regional oscillatory activity. At the network level, we found MDD is associated with aberrant causal interactions between pulvinar and several systems including default-mode and posterior insular networks. It was also shown that duloxetine treatment can correct or overcompensate the pathologic network behavior of the pulvinar. In conclusion, we suggest that pulvinar regional baseline oscillatory activity and its resting-state network dynamics are compromised in MDD and can be modulated therapeutically by pharmacological treatment. PMID:27148894

Capacity upgrade in short-reach optical fibre networks: simultaneous 4-PAM 20 Gbps data and polarization-modulated PPS clock signal using a single VCSEL carrier

NASA Astrophysics Data System (ADS)

Isoe, G. M.; Wassin, S.; Gamatham, R. R. G.; Leitch, A. W. R.; Gibbon, T. B.

2017-11-01

In this work, a four-level pulse amplitude modulation (4-PAM) format with a polarization-modulated pulse per second (PPS) clock signal using a single vertical cavity surface emitting laser (VCSEL) carrier is for the first time experimentally demonstrated. We propose uncomplex alternative technique for increasing capacity and flexibility in short-reach optical communication links through multi-signal modulation onto a single VCSEL carrier. A 20 Gbps 4-PAM data signal is directly modulated onto a single mode 10 GHz bandwidth VCSEL carrier at 1310 nm, therefore, doubling the network bit rate. Carrier spectral efficiency is further maximized by exploiting the inherent orthogonal polarization switching of the VCSEL carrier with changing bias in transmission of a PPS clock signal. We, therefore, simultaneously transmit a 20 Gbps 4-PAM data signal and a polarization-based PPS clock signal using a single VCSEL carrier. It is the first time a signal VCSEL carrier is reported to simultaneously transmit a directly modulated 20 Gbps 4-PAM data signal and a polarization-based PPS clock signal. We further demonstrate on the design of a software-defined digital signal processing (DSP)-assisted receiver as an alternative to costly receiver hardware. Experimental results show that a 3.21 km fibre transmission with simultaneous 20 Gbps 4-PAM data signal and polarization-based PPS clock signal introduced a penalty of 3.76 dB. The contribution of polarization-based PPS clock signal to this penalty was found out to be 0.41 dB. Simultaneous distribution of data and timing clock signals over shared network infrastructure significantly increases the aggregated data rate at different optical network units (ONUs), without costly investment.

Study of dual-polarization OQAM-OFDM PON with direct detection

NASA Astrophysics Data System (ADS)

Luo, Qing-long; Feng, Min; Bai, Cheng-lin; Hu, Wei-sheng

2016-01-01

An offset quadrature amplitude modulation orthogonal frequency-division multiplexing (OQAM-OFDM) passive optical network (PON) architecture with direct detection is brought up to increase the transmission range and improve the system performance. In optical line terminal (OLT), OQAM-OFDM signals at 40 Gbit/s are transmitted as downstream. At each optical network unit (ONU), the optical OQAM-OFDM signal is demodulated with direct detection. The results show that the transmission distance can exceed 20 km with negligible penalty under the experimental conditions.

Integrated metagenomic analysis of the rumen microbiome of cattle reveals key biological mechanisms associated with methane traits.

PubMed

Wang, Haiying; Zheng, Huiru; Browne, Fiona; Roehe, Rainer; Dewhurst, Richard J; Engel, Felix; Hemmje, Matthias; Lu, Xiangwu; Walsh, Paul

2017-07-15

Methane is one of the major contributors to global warming. The rumen microbiota is directly involved in methane production in cattle. The link between variation in rumen microbial communities and host genetics has important applications and implications in bioscience. Having the potential to reveal the full extent of microbial gene diversity and complex microbial interactions, integrated metagenomics and network analysis holds great promise in this endeavour. This study investigates the rumen microbial community in cattle through the integration of metagenomic and network-based approaches. Based on the relative abundance of 1570 microbial genes identified in a metagenomics analysis, the co-abundance network was constructed and functional modules of microbial genes were identified. One of the main contributions is to develop a random matrix theory-based approach to automatically determining the correlation threshold used to construct the co-abundance network. The resulting network, consisting of 549 microbial genes and 3349 connections, exhibits a clear modular structure with certain trait-specific genes highly over-represented in modules. More specifically, all the 20 genes previously identified to be associated with methane emissions are found in a module (hypergeometric test, p<10 -11 ). One third of genes are involved in methane metabolism pathways. The further examination of abundance profiles across 8 samples of genes highlights that the revealed pattern of metagenomics abundance has a strong association with methane emissions. Furthermore, the module is significantly enriched with microbial genes encoding enzymes that are directly involved in methanogenesis (hypergeometric test, p<10 -9 ). Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Detection of Significant Pneumococcal Meningitis Biomarkers by Ego Network.

PubMed

Wang, Qian; Lou, Zhifeng; Zhai, Liansuo; Zhao, Haibin

2017-06-01

To identify significant biomarkers for detection of pneumococcal meningitis based on ego network. Based on the gene expression data of pneumococcal meningitis and global protein-protein interactions (PPIs) data recruited from open access databases, the authors constructed a differential co-expression network (DCN) to identify pneumococcal meningitis biomarkers in a network view. Here EgoNet algorithm was employed to screen the significant ego networks that could accurately distinguish pneumococcal meningitis from healthy controls, by sequentially seeking ego genes, searching candidate ego networks, refinement of candidate ego networks and significance analysis to identify ego networks. Finally, the functional inference of the ego networks was performed to identify significant pathways for pneumococcal meningitis. By differential co-expression analysis, the authors constructed the DCN that covered 1809 genes and 3689 interactions. From the DCN, a total of 90 ego genes were identified. Starting from these ego genes, three significant ego networks (Module 19, Module 70 and Module 71) that could predict clinical outcomes for pneumococcal meningitis were identified by EgoNet algorithm, and the corresponding ego genes were GMNN, MAD2L1 and TPX2, respectively. Pathway analysis showed that these three ego networks were related to CDT1 association with the CDC6:ORC:origin complex, inactivation of APC/C via direct inhibition of the APC/C complex pathway, and DNA strand elongation, respectively. The authors successfully screened three significant ego modules which could accurately predict the clinical outcomes for pneumococcal meningitis and might play important roles in host response to pathogen infection in pneumococcal meningitis.

A new network representation of the metabolism to detect chemical transformation modules.

PubMed

Sorokina, Maria; Medigue, Claudine; Vallenet, David

2015-11-14

Metabolism is generally modeled by directed networks where nodes represent reactions and/or metabolites. In order to explore metabolic pathway conservation and divergence among organisms, previous studies were based on graph alignment to find similar pathways. Few years ago, the concept of chemical transformation modules, also called reaction modules, was introduced and correspond to sequences of chemical transformations which are conserved in metabolism. We propose here a novel graph representation of the metabolic network where reactions sharing a same chemical transformation type are grouped in Reaction Molecular Signatures (RMS). RMS were automatically computed for all reactions and encode changes in atoms and bonds. A reaction network containing all available metabolic knowledge was then reduced by an aggregation of reaction nodes and edges to obtain a RMS network. Paths in this network were explored and a substantial number of conserved chemical transformation modules was detected. Furthermore, this graph-based formalism allows us to define several path scores reflecting different biological conservation meanings. These scores are significantly higher for paths corresponding to known metabolic pathways and were used conjointly to build association rules that should predict metabolic pathway types like biosynthesis or degradation. This representation of metabolism in a RMS network offers new insights to capture relevant metabolic contexts. Furthermore, along with genomic context methods, it should improve the detection of gene clusters corresponding to new metabolic pathways.

Functional cortical network in alpha band correlates with social bargaining.

PubMed

Billeke, Pablo; Zamorano, Francisco; Chavez, Mario; Cosmelli, Diego; Aboitiz, Francisco

2014-01-01

Solving demanding tasks requires fast and flexible coordination among different brain areas. Everyday examples of this are the social dilemmas in which goals tend to clash, requiring one to weigh alternative courses of action in limited time. In spite of this fact, there are few studies that directly address the dynamics of flexible brain network integration during social interaction. To study the preceding, we carried out EEG recordings while subjects played a repeated version of the Ultimatum Game in both human (social) and computer (non-social) conditions. We found phase synchrony (inter-site-phase-clustering) modulation in alpha band that was specific to the human condition and independent of power modulation. The strength and patterns of the inter-site-phase-clustering of the cortical networks were also modulated, and these modulations were mainly in frontal and parietal regions. Moreover, changes in the individuals' alpha network structure correlated with the risk of the offers made only in social conditions. This correlation was independent of changes in power and inter-site-phase-clustering strength. Our results indicate that, when subjects believe they are participating in a social interaction, a specific modulation of functional cortical networks in alpha band takes place, suggesting that phase synchrony of alpha oscillations could serve as a mechanism by which different brain areas flexibly interact in order to adapt ongoing behavior in socially demanding contexts.

Functional Cortical Network in Alpha Band Correlates with Social Bargaining

PubMed Central

Billeke, Pablo; Zamorano, Francisco; Chavez, Mario; Cosmelli, Diego; Aboitiz, Francisco

2014-01-01

Solving demanding tasks requires fast and flexible coordination among different brain areas. Everyday examples of this are the social dilemmas in which goals tend to clash, requiring one to weigh alternative courses of action in limited time. In spite of this fact, there are few studies that directly address the dynamics of flexible brain network integration during social interaction. To study the preceding, we carried out EEG recordings while subjects played a repeated version of the Ultimatum Game in both human (social) and computer (non-social) conditions. We found phase synchrony (inter-site-phase-clustering) modulation in alpha band that was specific to the human condition and independent of power modulation. The strength and patterns of the inter-site-phase-clustering of the cortical networks were also modulated, and these modulations were mainly in frontal and parietal regions. Moreover, changes in the individuals’ alpha network structure correlated with the risk of the offers made only in social conditions. This correlation was independent of changes in power and inter-site-phase-clustering strength. Our results indicate that, when subjects believe they are participating in a social interaction, a specific modulation of functional cortical networks in alpha band takes place, suggesting that phase synchrony of alpha oscillations could serve as a mechanism by which different brain areas flexibly interact in order to adapt ongoing behavior in socially demanding contexts. PMID:25286240

ImNet: a fiber optic network with multistar topology for high-speed data transmission

NASA Astrophysics Data System (ADS)

Vossebuerger, F.; Keizers, Andreas; Soederman, N.; Meyer-Ebrecht, Dietrich

1993-10-01

ImNet is a fiber-optic local area network, which has been developed for high speed image communication in Picture Archiving and Communication Systems (PACS). A comprehensive analysis of image communication requirements in hospitals led to the conclusion that there is a need for networks which are optimized for the transmission of large datafiles. ImNet is optimized for this application in contrast to current-state LANs. ImNet consists of two elements: a link module and a switch module. The point-to-point link module can be up to 4 km by using fiber optic cable. For short distances up to 100 m a cheaper module using shielded twisted pair cable is available. The link module works bi-directionally and handles all protocols up to OSI-Level 3. The data rate per link is up to 140 MBit/s (clock rate 175 MHz). The switch module consists of the control unit and the cross-point-switch array. The array has up to fourteen interfaces for link modules. Up to fourteen data transfers each with a maximal transfer rate of 400 MBit/s can be handled at the same time. Thereby the maximal throughput of a switch module is 5.6 GBit/s. Out of these modules a multi-star network can be built i.e., an arbitrary tree structure of stars. This topology allows multiple transmissions at the same time as long as they do not require identical links. Therefore the overall throughput of ImNet can be a multiple of the datarate per link.

Colorless ONU implementation for WDM-PON using direct-detection optical OFDM

NASA Astrophysics Data System (ADS)

Feng, Min; Luo, Qing-long; Bai, Cheng-lin

2013-03-01

A novel architecture for the colorless optical network unit (ONU) is proposed and experimentally demonstrated with direct-detection optical orthogonal frequency division multiplexing (DDO-OFDM). In this architecture, polarization-division multiplexing is used to reduce the cost at ONU. In optical line terminal (OLT), quadrature amplitude modulation (QAM) intensity-modulated OFDM signal with x-polarization at 10 Gbit/s is transmitted as downstream. At each ONU, the optical OFDM signal is demodulated with direct detection, and γ-polarization signal is modulated for upstream on-off keying (OOK) data at 5 Gbit/s. Simulation results show that the power penalty is negligible for both optical OFDM downstream and the on-off keying upstream signals after over 50 km single-mode fiber (SMF) transmission.

Oxytocin And Vasopressin Modulation Of The Neural Correlates Of Motivation And Emotion: Results From Functional MRI Studies In Awake Rats

PubMed Central

Febo, Marcelo; Ferris, Craig F.

2014-01-01

Oxytocin and vasopressin modulate a range of species typical behavioral functions that include social recognition, maternal-infant attachment, and modulation of memory, offensive aggression, defensive fear reactions, and reward seeking. We have employed novel functional magnetic resonance mapping techniques in awake rats to explore the roles of these neuropeptides in the maternal and non-maternal brain. Results from the functional neuroimaging studies that are summarized here have directly and indirectly confirmed and supported previous findings. Oxytocin is released within the lactating rat brain during suckling stimulation and activates specific subcortical networks in the maternal brain. Both vasopressin and oxytocin modulate brain regions involved unconditioned fear, processing of social stimuli and the expression of agonistic behaviors. Across studies there are relatively consistent brain networks associated with internal motivational drives and emotional states that are modulated by oxytocin and vasopressin. PMID:24486356

An integrative approach to inferring biologically meaningful gene modules.

PubMed

Cho, Ji-Hoon; Wang, Kai; Galas, David J

2011-07-26

The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.

Inspiring Climate Education Excellence (ICEE): Developing self-directed professional development modules for secondary science teachers

NASA Astrophysics Data System (ADS)

Buhr, S. M.; Lynds, S. E.; McCaffrey, M. S.; Morton, E.

2010-12-01

Inspiring Climate Education Excellence (ICEE) is a NASA-funded project to develop online course modules and self-directed learning resources aligned with the Essential Principles of Climate Science. Following a national needs assessment survey and a face to face workshop to pilot test topics, a suite of online modules is being developed suitable for self-directed learning by secondary science teachers. Modules are designed around concepts and topics in which teachers express the most interest and need for instruction. Module design also includes attention to effective teaching strategies, such as awareness of student misconceptions, strategies for forestalling controversy and advice from master teachers on implementation and curriculum development. The resources are being developed in partnership with GLOBE, and the National Science Digital Library (NSDL) and is informed by the work of the Climate Literacy and Energy Awareness Network (CLEAN) project. ICEE will help to meet the professional development needs of teachers, including those participating in the GLOBE Student Climate Research Campaign. Modules and self-directed learning resources will be developed and disseminated in partnership with the National Science Digital Library (NSDL). This presentation introduces the needs assessment and pilot workshop data upon which the modules are based, and describes the modules that are available and in development.

Comparison of Modules of Wild Type and Mutant Huntingtin and TP53 Protein Interaction Networks: Implications in Biological Processes and Functions

PubMed Central

Basu, Mahashweta; Bhattacharyya, Nitai P.; Mohanty, Pradeep K.

2013-01-01

Disease-causing mutations usually change the interacting partners of mutant proteins. In this article, we propose that the biological consequences of mutation are directly related to the alteration of corresponding protein protein interaction networks (PPIN). Mutation of Huntingtin (HTT) which causes Huntington's disease (HD) and mutations to TP53 which is associated with different cancers are studied as two example cases. We construct the PPIN of wild type and mutant proteins separately and identify the structural modules of each of the networks. The functional role of these modules are then assessed by Gene Ontology (GO) enrichment analysis for biological processes (BPs). We find that a large number of significantly enriched () GO terms in mutant PPIN were absent in the wild type PPIN indicating the gain of BPs due to mutation. Similarly some of the GO terms enriched in wild type PPIN cease to exist in the modules of mutant PPIN, representing the loss. GO terms common in modules of mutant and wild type networks indicate both loss and gain of BPs. We further assign relevant biological function(s) to each module by classifying the enriched GO terms associated with it. It turns out that most of these biological functions in HTT networks are already known to be altered in HD and those of TP53 networks are altered in cancers. We argue that gain of BPs, and the corresponding biological functions, are due to new interacting partners acquired by mutant proteins. The methodology we adopt here could be applied to genetic diseases where mutations alter the ability of the protein to interact with other proteins. PMID:23741403

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.

Efficient randomization of biological networks while preserving functional characterization of individual nodes.

PubMed

Iorio, Francesco; Bernardo-Faura, Marti; Gobbi, Andrea; Cokelaer, Thomas; Jurman, Giuseppe; Saez-Rodriguez, Julio

2016-12-20

Networks are popular and powerful tools to describe and model biological processes. Many computational methods have been developed to infer biological networks from literature, high-throughput experiments, and combinations of both. Additionally, a wide range of tools has been developed to map experimental data onto reference biological networks, in order to extract meaningful modules. Many of these methods assess results' significance against null distributions of randomized networks. However, these standard unconstrained randomizations do not preserve the functional characterization of the nodes in the reference networks (i.e. their degrees and connection signs), hence including potential biases in the assessment. Building on our previous work about rewiring bipartite networks, we propose a method for rewiring any type of unweighted networks. In particular we formally demonstrate that the problem of rewiring a signed and directed network preserving its functional connectivity (F-rewiring) reduces to the problem of rewiring two induced bipartite networks. Additionally, we reformulate the lower bound to the iterations' number of the switching-algorithm to make it suitable for the F-rewiring of networks of any size. Finally, we present BiRewire3, an open-source Bioconductor package enabling the F-rewiring of any type of unweighted network. We illustrate its application to a case study about the identification of modules from gene expression data mapped on protein interaction networks, and a second one focused on building logic models from more complex signed-directed reference signaling networks and phosphoproteomic data. BiRewire3 it is freely available at https://www.bioconductor.org/packages/BiRewire/ , and it should have a broad application as it allows an efficient and analytically derived statistical assessment of results from any network biology tool.

A neural-network approach to robotic control

NASA Technical Reports Server (NTRS)

Graham, D. P. W.; Deleuterio, G. M. T.

1993-01-01

An artificial neural-network paradigm for the control of robotic systems is presented. The approach is based on the Cerebellar Model Articulation Controller created by James Albus and incorporates several extensions. First, recognizing the essential structure of multibody equations of motion, two parallel modules are used that directly reflect the dynamical characteristics of multibody systems. Second, the architecture of the proposed network is imbued with a self-organizational capability which improves efficiency and accuracy. Also, the networks can be arranged in hierarchical fashion with each subsequent network providing finer and finer resolution.

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

Locally induced neuronal synchrony precisely propagates to specific cortical areas without rhythm distortion.

PubMed

Toda, Haruo; Kawasaki, Keisuke; Sato, Sho; Horie, Masao; Nakahara, Kiyoshi; Bepari, Asim K; Sawahata, Hirohito; Suzuki, Takafumi; Okado, Haruo; Takebayashi, Hirohide; Hasegawa, Isao

2018-05-16

Propagation of oscillatory spike firing activity at specific frequencies plays an important role in distributed cortical networks. However, there is limited evidence for how such frequency-specific signals are induced or how the signal spectra of the propagating signals are modulated during across-layer (radial) and inter-areal (tangential) neuronal interactions. To directly evaluate the direction specificity of spectral changes in a spiking cortical network, we selectively photostimulated infragranular excitatory neurons in the rat primary visual cortex (V1) at a supra-threshold level with various frequencies, and recorded local field potentials (LFPs) at the infragranular stimulation site, the cortical surface site immediately above the stimulation site in V1, and cortical surface sites outside V1. We found a significant reduction of LFP powers during radial propagation, especially at high-frequency stimulation conditions. Moreover, low-gamma-band dominant rhythms were transiently induced during radial propagation. Contrastingly, inter-areal LFP propagation, directed to specific cortical sites, accompanied no significant signal reduction nor gamma-band power induction. We propose an anisotropic mechanism for signal processing in the spiking cortical network, in which the neuronal rhythms are locally induced/modulated along the radial direction, and then propagate without distortion via intrinsic horizontal connections for spatiotemporally precise, inter-areal communication.

Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network.

PubMed

Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana M; Dan, Bernard; McIntyre, Joseph; Cheron, Guy

2014-01-01

In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.

Laser dynamics: The system dynamics and network theory of optoelectronic integrated circuit design

NASA Astrophysics Data System (ADS)

Tarng, Tom Shinming-T. K.

Laser dynamics is the system dynamics, communication and network theory for the design of opto-electronic integrated circuit (OEIC). Combining the optical network theory and optical communication theory, the system analysis and design for the OEIC fundamental building blocks is considered. These building blocks include the direct current modulation, inject light modulation, wideband filter, super-gain optical amplifier, E/O and O/O optical bistability and current-controlled optical oscillator. Based on the rate equations, the phase diagram and phase portrait analysis is applied to the theoretical studies and numerical simulation. The OEIC system design methodologies are developed for the OEIC design. Stimulating-field-dependent rate equations are used to model the line-width narrowing/broadening mechanism for the CW mode and frequency chirp of semiconductor lasers. The momentary spectra are carrier-density-dependent. Furthermore, the phase portrait analysis and the nonlinear refractive index is used to simulate the single mode frequency chirp. The average spectra of chaos, period doubling, period pulsing, multi-loops and analog modulation are generated and analyzed. The bifurcation-chirp design chart with modulation depth and modulation frequency as parameters is provided for design purpose.

Network models of frequency modulated sweep detection.

PubMed

Skorheim, Steven; Razak, Khaleel; Bazhenov, Maxim

2014-01-01

Frequency modulated (FM) sweeps are common in species-specific vocalizations, including human speech. Auditory neurons selective for the direction and rate of frequency change in FM sweeps are present across species, but the synaptic mechanisms underlying such selectivity are only beginning to be understood. Even less is known about mechanisms of experience-dependent changes in FM sweep selectivity. We present three network models of synaptic mechanisms of FM sweep direction and rate selectivity that explains experimental data: (1) The 'facilitation' model contains frequency selective cells operating as coincidence detectors, summing up multiple excitatory inputs with different time delays. (2) The 'duration tuned' model depends on interactions between delayed excitation and early inhibition. The strength of delayed excitation determines the preferred duration. Inhibitory rebound can reinforce the delayed excitation. (3) The 'inhibitory sideband' model uses frequency selective inputs to a network of excitatory and inhibitory cells. The strength and asymmetry of these connections results in neurons responsive to sweeps in a single direction of sufficient sweep rate. Variations of these properties, can explain the diversity of rate-dependent direction selectivity seen across species. We show that the inhibitory sideband model can be trained using spike timing dependent plasticity (STDP) to develop direction selectivity from a non-selective network. These models provide a means to compare the proposed synaptic and spectrotemporal mechanisms of FM sweep processing and can be utilized to explore cellular mechanisms underlying experience- or training-dependent changes in spectrotemporal processing across animal models. Given the analogy between FM sweeps and visual motion, these models can serve a broader function in studying stimulus movement across sensory epithelia.

An integrative approach to inferring biologically meaningful gene modules

PubMed Central

2011-01-01

Background The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. Results We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. Conclusions The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level. PMID:21791051

Reversible large–scale modification of cortical networks during neuroprosthetic control

PubMed Central

Ganguly, Karunesh; Wallis, Jonathan D.

2012-01-01

Brain-Machine Interfaces (BMI) provide a framework to study cortical dynamics and the neural correlates of learning. Neuroprosthetic control has been associated with tuning changes in specific neurons directly projecting to the BMI (hereafter ‘direct neurons’). However, little is known about the larger network dynamics. By monitoring ensembles of neurons that were either causally linked to BMI control or indirectly involved, here we show that proficient neuroprosthetic control is associated with large-scale modifications to the cortical network in macaque monkeys. Specifically, there were changes in the preferred direction of both direct and indirect neurons. Interestingly, with learning, there was a relative decrease in the net modulation of indirect neural activity in comparison to the direct activity. These widespread differential changes in the direct and indirect population activity were remarkably stable from one day to the next and readily coexisted with the long-standing cortical network for upper limb control. Thus, the process of learning BMI control is associated with differential modification of neural populations based on their specific relation to movement control. PMID:21499255

Reversible large-scale modification of cortical networks during neuroprosthetic control.

PubMed

Ganguly, Karunesh; Dimitrov, Dragan F; Wallis, Jonathan D; Carmena, Jose M

2011-05-01

Brain-machine interfaces (BMIs) provide a framework for studying cortical dynamics and the neural correlates of learning. Neuroprosthetic control has been associated with tuning changes in specific neurons directly projecting to the BMI (hereafter referred to as direct neurons). However, little is known about the larger network dynamics. By monitoring ensembles of neurons that were either causally linked to BMI control or indirectly involved, we found that proficient neuroprosthetic control is associated with large-scale modifications to the cortical network in macaque monkeys. Specifically, there were changes in the preferred direction of both direct and indirect neurons. Notably, with learning, there was a relative decrease in the net modulation of indirect neural activity in comparison with direct activity. These widespread differential changes in the direct and indirect population activity were markedly stable from one day to the next and readily coexisted with the long-standing cortical network for upper limb control. Thus, the process of learning BMI control is associated with differential modification of neural populations based on their specific relation to movement control.

High definition-transcranial direct current stimulation changes older adults' subjective sleep and corresponding resting-state functional connectivity.

PubMed

Sheng, Jing; Xie, Chao; Fan, Dong-Qiong; Lei, Xu; Yu, Jing

2018-07-01

With advanced age, older adults show functional deterioration in sleep. Transcranial direct current stimulation (tDCS), a noninvasive brain stimulation, modulates individuals' behavioral performance in various cognitive domains. However, the modulation effect and neural mechanisms of tDCS on sleep, especially for the elderly population are not clear. Here, we aimed to investigate whether high-definition transcranial direct current stimulation (HD-tDCS) could modulate community-dwelling older adults' subjective sleep and whether these potential improvements are associated with the large-scale brain activity alterations recorded by functional magnetic resonance imaging. Thirty-one older adults were randomly allocated to the HD-tDCS group and the control group. HD-tDCS was applied for 25 min at 1.5 mA per day for two weeks. The anode electrode was placed over the left dorsolateral prefrontal cortex, surrounded by 4 cathodes at 7 cm radius. All participants completed sleep neuropsychological assessments and fMRI scans individually before and after intervention. Behaviorally, we observed a HD-tDCS-induced enhancement of older adults' sleep duration. On the aspect of the corresponding neural alterations, we observed that HD-tDCS decreased the functional connectivity between the default mode network (DMN) and subcortical network. More importantly, the decoupling connectivity of the DMN-subcortical network was correlated with the improvements of subjective sleep in the HD-tDCS group. Our findings add novel behavioral and neural evidences about tDCS-induced sleep improvement in community-dwelling older adults. With further development, tDCS may be used as an alternative treatment for sleep disorders and alleviate the dysfunction of brain networks induced by aging. Copyright © 2018 Elsevier B.V. All rights reserved.

Ultra-high capacity WDM-SDM optical access network with self-homodyne detection downstream and 32QAM-FBMC upstream.

PubMed

Feng, Zhenhua; Xu, Liang; Wu, Qiong; Tang, Ming; Fu, Songnian; Tong, Weijun; Shum, Perry Ping; Liu, Deming

2017-03-20

Towards 100G beyond large-capacity optical access networks, wavelength division multiplexing (WDM) techniques incorporating with space division multiplexing (SDM) and affordable spectrally efficient advanced modulation formats are indispensable. In this paper, we proposed and experimentally demonstrated a cost-efficient multicore fiber (MCF) based hybrid WDM-SDM optical access network with self-homodyne coherent detection (SHCD) based downstream (DS) and direct detection optical filter bank multi carrier (DDO-FBMC) based upstream (US). In the DS experiments, the inner core of the 7-core fiber is used as a dedicated channel to deliver the local oscillator (LO) lights while the other 6 outer cores are used to transmit 4 channels of wavelength multiplexed 200-Gb/s PDM-16QAM-OFDM signals. For US transmission, 4 wavelengths with channel spacing of 100 GHz are intensity modulated with 30 Gb/s 32-QAM-FBMC and directly detected by a ~7 GHz bandwidth receiver after transmission along one of the outer core. The results show that a 4 × 6 × 200-Gb/s DS transmission can be realized over 37 km 7-core fiber without carrier frequency offset (CFO) and phase noise (PN) compensation even using 10 MHz linewidth DFB lasers. The SHCD based on MCF provides a compromise and cost efficient scheme between conventional intradyne coherent detection and intensity modulation and direct detection (IM/DD) schemes. Both US and DS have acceptable BER performance and high spectral efficiency.

Dynamic reorganization of human resting-state networks during visuospatial attention.

PubMed

Spadone, Sara; Della Penna, Stefania; Sestieri, Carlo; Betti, Viviana; Tosoni, Annalisa; Perrucci, Mauro Gianni; Romani, Gian Luca; Corbetta, Maurizio

2015-06-30

Fundamental problems in neuroscience today are understanding how patterns of ongoing spontaneous activity are modified by task performance and whether/how these intrinsic patterns influence task-evoked activation and behavior. We examined these questions by comparing instantaneous functional connectivity (IFC) and directed functional connectivity (DFC) changes in two networks that are strongly correlated and segregated at rest: the visual (VIS) network and the dorsal attention network (DAN). We measured how IFC and DFC during a visuospatial attention task, which requires dynamic selective rerouting of visual information across hemispheres, changed with respect to rest. During the attention task, the two networks remained relatively segregated, and their general pattern of within-network correlation was maintained. However, attention induced a decrease of correlation in the VIS network and an increase of the DAN→VIS IFC and DFC, especially in a top-down direction. In contrast, within the DAN, IFC was not modified by attention, whereas DFC was enhanced. Importantly, IFC modulations were behaviorally relevant. We conclude that a stable backbone of within-network functional connectivity topography remains in place when transitioning between resting wakefulness and attention selection. However, relative decrease of correlation of ongoing "idling" activity in visual cortex and synchronization between frontoparietal and visual cortex were behaviorally relevant, indicating that modulations of resting activity patterns are important for task performance. Higher order resting connectivity in the DAN was relatively unaffected during attention, potentially indicating a role for simultaneous ongoing activity as a "prior" for attention selection.

A WDM-PON with DPSK modulated downstream and OOK modulated upstream signals based on symmetric 10 Gbit/s wavelength reused bidirectional reflective SOA

NASA Astrophysics Data System (ADS)

El-Nahal, Fady I.

2017-01-01

We investigate a wavelength-division-multiplexing passive optical network (WDM-PON) with centralized lightwave and direct detection. The system is demonstrated for symmetric 10 Gbit/s differential phase-shift keying (DPSK) downstream signals and on-off keying (OOK) upstream signals, respectively. A wavelength reused scheme is employed to carry the upstream data by using a reflective semiconductor optical amplifier (RSOA) as an intensity modulator at the optical network unit (ONU). The constant-intensity property of the DPSK modulation format can keep high extinction ratio ( ER) of downstream signal and reduce the crosstalk to the upstream signal. The bit error rate ( BER) performance of our scheme shows that the proposed 10 Gbit/s symmetric WDM-PON can achieve error free transmission over 25-km-long fiber transmission with low power penalty.

Parallel processing by cortical inhibition enables context-dependent behavior.

PubMed

Kuchibhotla, Kishore V; Gill, Jonathan V; Lindsay, Grace W; Papadoyannis, Eleni S; Field, Rachel E; Sten, Tom A Hindmarsh; Miller, Kenneth D; Froemke, Robert C

2017-01-01

Physical features of sensory stimuli are fixed, but sensory perception is context dependent. The precise mechanisms that govern contextual modulation remain unknown. Here, we trained mice to switch between two contexts: passively listening to pure tones and performing a recognition task for the same stimuli. Two-photon imaging showed that many excitatory neurons in auditory cortex were suppressed during behavior, while some cells became more active. Whole-cell recordings showed that excitatory inputs were affected only modestly by context, but inhibition was more sensitive, with PV + , SOM + , and VIP + interneurons balancing inhibition and disinhibition within the network. Cholinergic modulation was involved in context switching, with cholinergic axons increasing activity during behavior and directly depolarizing inhibitory cells. Network modeling captured these findings, but only when modulation coincidently drove all three interneuron subtypes, ruling out either inhibition or disinhibition alone as sole mechanism for active engagement. Parallel processing of cholinergic modulation by cortical interneurons therefore enables context-dependent behavior.

Advanced optical fiber communication systems

NASA Astrophysics Data System (ADS)

Kazovsky, Leonid G.

1994-03-01

Our research is focused on three major aspects of advanced optical fiber communication systems: dynamic wavelength division multiplexing (WDM) networks, fiber nonlinearities, and high dynamic range coherent analog optical links. In the area of WDM networks, we have designed and implemented two high-speed interface boards and measured their throughput and latency. Furthermore, we designed and constructed an experimental PSK/ASK transceiver that simultaneously transmits packet-switched ASK data and circuit-switched PSK data on the same optical carrier. In the area of fiber nonlinearities, we investigated the theoretical impact of modulation frequency on cross-phase modulation (XPM) in dispersive fibers. In the area of high dynamic range coherent analog optical links, we developed theoretical expressions for the RF power transfer ratio (or RF power gain) and the noise figure (NF) of angle-modulated links. We then compared the RF power gains and noise figures of these links to that of an intensity modulated direct detection (DD) link.

Design of an Agent-Based Model to Examine Population-Environment Interactions in Nang Rong District, Thailand.

PubMed

Walsh, Stephen J; Malanson, George P; Entwisle, Barbara; Rindfuss, Ronald R; Mucha, Peter J; Heumann, Benjamin W; McDaniel, Philip M; Frizzelle, Brian G; Verdery, Ashton M; Williams, Nathalie; Xiaozheng, Yao; Ding, Deng

2013-05-01

The design of an Agent-Based Model (ABM) is described that integrates Social and Land Use Modules to examine population-environment interactions in a former agricultural frontier in Northeastern Thailand. The ABM is used to assess household income and wealth derived from agricultural production of lowland, rain-fed paddy rice and upland field crops in Nang Rong District as well as remittances returned to the household from family migrants who are engaged in off-farm employment in urban destinations. The ABM is supported by a longitudinal social survey of nearly 10,000 households, a deep satellite image time-series of land use change trajectories, multi-thematic social and ecological data organized within a GIS, and a suite of software modules that integrate data derived from an agricultural cropping system model (DSSAT - Decision Support for Agrotechnology Transfer) and a land suitability model (MAXENT - Maximum Entropy), in addition to multi-dimensional demographic survey data of individuals and households. The primary modules of the ABM are the Initialization Module, Migration Module, Assets Module, Land Suitability Module, Crop Yield Module, Fertilizer Module, and the Land Use Change Decision Module. The architecture of the ABM is described relative to module function and connectivity through uni-directional or bi-directional links. In general, the Social Modules simulate changes in human population and social networks, as well as changes in population migration and household assets, whereas the Land Use Modules simulate changes in land use types, land suitability, and crop yields. We emphasize the description of the Land Use Modules - the algorithms and interactions between the modules are described relative to the project goals of assessing household income and wealth relative to shifts in land use patterns, household demographics, population migration, social networks, and agricultural activities that collectively occur within a marginalized environment that is subjected to a suite of endogenous and exogenous dynamics.

Design of an Agent-Based Model to Examine Population-Environment Interactions in Nang Rong District, Thailand

PubMed Central

Walsh, Stephen J.; Malanson, George P.; Entwisle, Barbara; Rindfuss, Ronald R.; Mucha, Peter J.; Heumann, Benjamin W.; McDaniel, Philip M.; Frizzelle, Brian G.; Verdery, Ashton M.; Williams, Nathalie; Xiaozheng, Yao; Ding, Deng

2013-01-01

The design of an Agent-Based Model (ABM) is described that integrates Social and Land Use Modules to examine population-environment interactions in a former agricultural frontier in Northeastern Thailand. The ABM is used to assess household income and wealth derived from agricultural production of lowland, rain-fed paddy rice and upland field crops in Nang Rong District as well as remittances returned to the household from family migrants who are engaged in off-farm employment in urban destinations. The ABM is supported by a longitudinal social survey of nearly 10,000 households, a deep satellite image time-series of land use change trajectories, multi-thematic social and ecological data organized within a GIS, and a suite of software modules that integrate data derived from an agricultural cropping system model (DSSAT – Decision Support for Agrotechnology Transfer) and a land suitability model (MAXENT – Maximum Entropy), in addition to multi-dimensional demographic survey data of individuals and households. The primary modules of the ABM are the Initialization Module, Migration Module, Assets Module, Land Suitability Module, Crop Yield Module, Fertilizer Module, and the Land Use Change Decision Module. The architecture of the ABM is described relative to module function and connectivity through uni-directional or bi-directional links. In general, the Social Modules simulate changes in human population and social networks, as well as changes in population migration and household assets, whereas the Land Use Modules simulate changes in land use types, land suitability, and crop yields. We emphasize the description of the Land Use Modules – the algorithms and interactions between the modules are described relative to the project goals of assessing household income and wealth relative to shifts in land use patterns, household demographics, population migration, social networks, and agricultural activities that collectively occur within a marginalized environment that is subjected to a suite of endogenous and exogenous dynamics. PMID:24277975

Oxytocin and vasopressin modulation of the neural correlates of motivation and emotion: results from functional MRI studies in awake rats.

PubMed

Febo, Marcelo; Ferris, Craig F

2014-09-11

Oxytocin and vasopressin modulate a range of species typical behavioral functions that include social recognition, maternal-infant attachment, and modulation of memory, offensive aggression, defensive fear reactions, and reward seeking. We have employed novel functional magnetic resonance mapping techniques in awake rats to explore the roles of these neuropeptides in the maternal and non-maternal brain. Results from the functional neuroimaging studies that are summarized here have directly and indirectly confirmed and supported previous findings. Oxytocin is released within the lactating rat brain during suckling stimulation and activates specific subcortical networks in the maternal brain. Both vasopressin and oxytocin modulate brain regions involved unconditioned fear, processing of social stimuli and the expression of agonistic behaviors. Across studies there are relatively consistent brain networks associated with internal motivational drives and emotional states that are modulated by oxytocin and vasopressin. This article is part of a Special Issue entitled Oxytocin and Social Behav. Copyright © 2014 Elsevier B.V. All rights reserved.

Dynamics of alpha control: Preparatory suppression of posterior alpha oscillations by frontal modulators revealed with combined EEG and event-related optical signal (EROS)

PubMed Central

Mathewson, Kyle E.; Beck, Diane M.; Ro, Tony; Maclin, Edward L.; Low, Kathy A.; Fabiani, Monica; Gratton, Gabriele

2015-01-01

We investigated the dynamics of brain processes facilitating conscious experience of external stimuli. Previously we proposed that alpha (8-12 Hz) oscillations, which fluctuate with both sustained and directed attention, represent a pulsed inhibition of ongoing sensory brain activity. Here we tested the prediction that inhibitory alpha oscillations in visual cortex are modulated by top-down signals from frontoparietal attention networks. We measured modulations in phase-coherent alpha oscillations from superficial frontal, parietal, and occipital cortices using the event-related optical signal (EROS), a measure of neuronal activity affording high spatiotemporal resolution, along with concurrently-recorded electroencephalogram (EEG), while subjects performed a visual target-detection task. The pre-target alpha oscillations measured with EEG and EROS from posterior areas were larger for subsequently undetected targets, supporting alpha's inhibitory role. Using EROS, we localized brain correlates of these awareness-related alpha oscillations measured at the scalp to the cuneus and precuneus. Crucially, EROS alpha suppression correlated with posterior EEG alpha power across subjects. Sorting the EROS data based on EEG alpha power quartiles to investigate alpha modulators revealed that suppression of posterior alpha was preceded by increased activity in regions of the dorsal attention network, and decreased activity in regions of the cingulo-opercular network. Cross-correlations revealed the temporal dynamics of activity within these preparatory networks prior to posterior alpha modulation. The novel combination of EEG and EROS afforded localization of the sources and correlates of alpha oscillations and their temporal relationships, supporting our proposal that top-down control from attention networks modulates both posterior alpha and awareness of visual stimuli. PMID:24702458

Integration Of An MR Image Network Into A Clinical PACS

NASA Astrophysics Data System (ADS)

Ratib, Osman M.; Mankovich, Nicholas J.; Taira, Ricky K.; Cho, Paul S.; Huang, H. K.

1988-06-01

A direct link between a clinical pediatric PACS module and a FONAR MRI image network was implemented. The original MR network combines together the MR scanner, a remote viewing station and a central archiving station. The pediatric PACS directly connects to the archiving unit through an Ethernet TCP-IP network adhering to FONAR's protocol. The PACS communication software developed supports the transfer of patient studies and the patient information directly from the MR archive database to the pediatric PACS. In the first phase of our project we developed a package to transfer data between a VAX-111750 and the IBM PC I AT-based MR archive database through the Ethernet network. This system served as a model for PACS-to-modality network communication. Once testing was complete on this research network, the software and network hardware was moved to the clinical pediatric VAX for full PACS integration. In parallel to the direct transmission of digital images to the Pediatric PACS, a broadband communication system in video format was developed for real-time broadcasting of images originating from the MR console to 8 remote viewing stations distributed in the radiology department. These analog viewing stations allow the radiologists to directly monitor patient positioning and to select the scan levels during a patient examination from remote locations in the radiology department. This paper reports (1) the technical details of this implementation, (2) the merits of this network development scheme, and (3) the performance statistics of the network-to-PACS interface.

Direct biomechanical modeling of trabecular bone using a nonlinear manifold-based volumetric representation

NASA Astrophysics Data System (ADS)

Jin, Dakai; Lu, Jia; Zhang, Xiaoliu; Chen, Cheng; Bai, ErWei; Saha, Punam K.

2017-03-01

Osteoporosis is associated with increased fracture risk. Recent advancement in the area of in vivo imaging allows segmentation of trabecular bone (TB) microstructures, which is a known key determinant of bone strength and fracture risk. An accurate biomechanical modelling of TB micro-architecture provides a comprehensive summary measure of bone strength and fracture risk. In this paper, a new direct TB biomechanical modelling method using nonlinear manifold-based volumetric reconstruction of trabecular network is presented. It is accomplished in two sequential modules. The first module reconstructs a nonlinear manifold-based volumetric representation of TB networks from three-dimensional digital images. Specifically, it starts with the fuzzy digital segmentation of a TB network, and computes its surface and curve skeletons. An individual trabecula is identified as a topological segment in the curve skeleton. Using geometric analysis, smoothing and optimization techniques, the algorithm generates smooth, curved, and continuous representations of individual trabeculae glued at their junctions. Also, the method generates a geometrically consistent TB volume at junctions. In the second module, a direct computational biomechanical stress-strain analysis is applied on the reconstructed TB volume to predict mechanical measures. The accuracy of the method was examined using micro-CT imaging of cadaveric distal tibia specimens (N = 12). A high linear correlation (r = 0.95) between TB volume computed using the new manifold-modelling algorithm and that directly derived from the voxel-based micro-CT images was observed. Young's modulus (YM) was computed using direct mechanical analysis on the TB manifold-model over a cubical volume of interest (VOI), and its correlation with the YM, computed using micro-CT based conventional finite-element analysis over the same VOI, was examined. A moderate linear correlation (r = 0.77) was observed between the two YM measures. This preliminary results show the accuracy of the new nonlinear manifold modelling algorithm for TB, and demonstrate the feasibility of a new direct mechanical strain-strain analysis on a nonlinear manifold model of a highly complex biological structure.

Choline-mediated modulation of hippocampal sharp wave-ripple complexes in vitro.

PubMed

Fischer, Viktoria; Both, Martin; Draguhn, Andreas; Egorov, Alexei V

2014-06-01

The cholinergic system is critically involved in the modulation of cognitive functions, including learning and memory. Acetylcholine acts through muscarinic (mAChRs) and nicotinic receptors (nAChRs), which are both abundantly expressed in the hippocampus. Previous evidence indicates that choline, the precursor and degradation product of Acetylcholine, can itself activate nAChRs and thereby affects intrinsic and synaptic neuronal functions. Here, we asked whether the cellular actions of choline directly affect hippocampal network activity. Using mouse hippocampal slices we found that choline efficiently suppresses spontaneously occurring sharp wave-ripple complexes (SPW-R) and can induce gamma oscillations. In addition, choline reduces synaptic transmission between hippocampal subfields CA3 and CA1. Surprisingly, these effects are mediated by activation of both mAChRs and α7-containing nAChRs. Most nicotinic effects became only apparent after local, fast application of choline, indicating rapid desensitization kinetics of nAChRs. Effects were still present following block of choline uptake and are, therefore, likely because of direct actions of choline at the respective receptors. Together, choline turns out to be a potent regulator of patterned network activity within the hippocampus. These actions may be of importance for understanding state transitions in normal and pathologically altered neuronal networks. In this study we asked whether choline, the precursor and degradation product of acetylcholine, directly affects hippocampal network activity. Using mouse hippocampal slices we found that choline efficiently suppresses spontaneously occurring sharp wave-ripple complexes (SPW-R). In addition, choline reduces synaptic transmission between hippocampal subfields. These effects are mediated by direct activation of muscarinic as well as nicotinic cholinergic pathways. Together, choline turns out to be a potent regulator of patterned activity within hippocampal networks. © 2014 International Society for Neurochemistry.

Implementing MANETS in Android based environment using Wi-Fi direct

NASA Astrophysics Data System (ADS)

Waqas, Muhammad; Babar, Mohammad Inayatullah Khan; Zafar, Mohammad Haseeb

2015-05-01

Packet loss occurs in real-time voice transmission over wireless broadcast Ad-hoc network which creates disruptions in sound. Basic objective of this research is to design a wireless Ad-hoc network based on two Android devices by using the Wireless Fidelity (WIFI) Direct Application Programming Interface (API) and apply the Network Codec, Reed Solomon Code. The network codec is used to encode the data of a music wav file and recover the lost packets if any, packets are dropped using a loss module at the transmitter device to analyze the performance with the objective of retrieving the original file at the receiver device using the network codec. This resulted in faster transmission of the files despite dropped packets. In the end both files had the original formatted music files with complete performance analysis based on the transmission delay.

Modular analysis of biological networks.

PubMed

Kaltenbach, Hans-Michael; Stelling, Jörg

2012-01-01

The analysis of complex biological networks has traditionally relied on decomposition into smaller, semi-autonomous units such as individual signaling pathways. With the increased scope of systems biology (models), rational approaches to modularization have become an important topic. With increasing acceptance of de facto modularity in biology, widely different definitions of what constitutes a module have sparked controversies. Here, we therefore review prominent classes of modular approaches based on formal network representations. Despite some promising research directions, several important theoretical challenges remain open on the way to formal, function-centered modular decompositions for dynamic biological networks.

[Not Available].

PubMed

Yanashima, Ryoji; Kitagawa, Noriyuki; Matsubara, Yoshiya; Weatheritt, Robert; Oka, Kotaro; Kikuchi, Shinichi; Tomita, Masaru; Ishizaki, Shun

2009-01-01

The scale-free and small-world network models reflect the functional units of networks. However, when we investigated the network properties of a signaling pathway using these models, no significant differences were found between the original undirected graphs and the graphs in which inactive proteins were eliminated from the gene expression data. We analyzed signaling networks by focusing on those pathways that best reflected cellular function. Therefore, our analysis of pathways started from the ligands and progressed to transcription factors and cytoskeletal proteins. We employed the Python module to assess the target network. This involved comparing the original and restricted signaling cascades as a directed graph using microarray gene expression profiles of late onset Alzheimer's disease. The most commonly used method of shortest-path analysis neglects to consider the influences of alternative pathways that can affect the activation of transcription factors or cytoskeletal proteins. We therefore introduced included k-shortest paths and k-cycles in our network analysis using the Python modules, which allowed us to attain a reasonable computational time and identify k-shortest paths. This technique reflected results found in vivo and identified pathways not found when shortest path or degree analysis was applied. Our module enabled us to comprehensively analyse the characteristics of biomolecular networks and also enabled analysis of the effects of diseases considering the feedback loop and feedforward loop control structures as an alternative path.

10-Gbps optical duobinary signal generated by bandwidth-limited reflective semiconductor optical amplifier in colorless optical network units and compensated by fiber Bragg grating-based equalizer in optical line terminal

NASA Astrophysics Data System (ADS)

Fu, Meixia; Zhang, Min; Wang, Danshi; Cui, Yue; Han, Huanhuan

2016-10-01

We propose a scheme of optical duobinary-modulated upstream transmission system for reflective semiconductor optical amplifier-based colorless optical network units in 10-Gbps wavelength-division multiplexed passive optical network (WDM-PON), where a fiber Bragg grating (FBG) is adopted as an optical equalizer for better performance. The demodulation module is extremely simple, only needing a binary intensity modulation direct detection receiver. A better received sensitivity of -16.98 dBm at bit rate error (BER)=1.0×10-4 can be achieved at 120 km without FBG, and the BER at the sensitivity of -18.49 dBm can be up to 2.1×10-5 at the transmission distance of 160 km with FBG, which demonstrates the feasibility of our proposed scheme. Moreover, it could be a high cost-effectiveness scheme for WDM-PON in the future.

Few-fJ/bit data transmissions using directly modulated lambda-scale embedded active region photonic-crystal lasers

NASA Astrophysics Data System (ADS)

Takeda, Koji; Sato, Tomonari; Shinya, Akihiko; Nozaki, Kengo; Kobayashi, Wataru; Taniyama, Hideaki; Notomi, Masaya; Hasebe, Koichi; Kakitsuka, Takaaki; Matsuo, Shinji

2013-07-01

A low operating energy is needed for nanocavity lasers designed for on-chip photonic network applications. On-chip nanocavity lasers must be driven by current because they act as light sources driven by electronic circuits. Here, we report the high-speed direct modulation of a lambda-scale embedded active region photonic-crystal (LEAP) laser that holds three records for any type of laser operated at room temperature: a low threshold current of 4.8 µA, a modulation current efficiency of 2.0 GHz µA-0.5 and an operating energy of 4.4 fJ bit-1. Five major technologies make this performance possible: a compact buried heterostructure, a photonic-crystal nanocavity, a lateral p-n junction realized by ion implantation and thermal diffusion, an InAlAs sacrificial layer and current-blocking trenches. We believe that an output power of 2.17 µW and an operating energy of 4.4 fJ bit-1 will enable us to realize on-chip photonic networks in combination with the recently developed highly sensitive receivers.

Abnormal-induced theta activity supports early directed-attention network deficits in progressive MCI.

PubMed

Deiber, Marie-Pierre; Ibañez, Vicente; Missonnier, Pascal; Herrmann, François; Fazio-Costa, Lara; Gold, Gabriel; Giannakopoulos, Panteleimon

2009-09-01

The electroencephalography (EEG) theta frequency band reacts to memory and selective attention paradigms. Global theta oscillatory activity includes a posterior phase-locked component related to stimulus processing and a frontal-induced component modulated by directed attention. To investigate the presence of early deficits in the directed attention-related network in elderly individuals with mild cognitive impairment (MCI), time-frequency analysis at baseline was used to assess global and induced theta oscillatory activity (4-6Hz) during n-back working memory tasks in 29 individuals with MCI and 24 elderly controls (EC). At 1-year follow-up, 13 MCI patients were still stable and 16 had progressed. Baseline task performance was similar in stable and progressive MCI cases. Induced theta activity at baseline was significantly reduced in progressive MCI as compared to EC and stable MCI in all n-back tasks, which were similar in terms of directed attention requirements. While performance is maintained, the decrease of induced theta activity suggests early deficits in the directed-attention network in progressive MCI, whereas this network is functionally preserved in stable MCI.

Cellular telephone-based radiation sensor and wide-area detection network

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2006-12-12

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Potential of OFDM for next generation optical access

NASA Astrophysics Data System (ADS)

Fritzsche, Daniel; Weis, Erik; Breuer, Dirk

2011-01-01

This paper shows the requirements for next generation optical access (NGOA) networks and analyzes the potential of OFDM (orthogonal frequency division multiplexing) for the use in such network scenarios. First, we show the motivation for NGOA systems based on the future requirements on FTTH access systems and list the advantages of OFDM in such scenarios. In the next part, the basics of OFDM and different methods to generate and detect optical OFDM signals are explained and analyzed. At the transmitter side the options include intensity modulation and the more advanced field modulation of the optical OFDM signal. At the receiver there is the choice between direct detection and coherent detection. As the result of this discussion we show our vision of the future use of OFDM in optical access networks.

Cellular telephone-based wide-area radiation detection network

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2009-06-09

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Suppression of pattern dependence in 10 Gbps upstream transmission of WDM-PON with RSOA-based ONUs

NASA Astrophysics Data System (ADS)

Zhang, Min; Wang, Danshi; Cao, Zhihui; Chen, Xue; Huang, Shanguo

2013-11-01

The finite gain recovery time of the reflective semiconductor optical amplifier (RSOA) causes distortion and pattern dependence at high bit rates in colorless optical network units (ONUs) of WDM passive optical network (WDN-PON). We propose and demonstrate a scheme of upstream transmission of 10 Gbps NRZ signals directly modulated via a RSOA in a 25 km single fiber, where we use a fiber Bragg grating (FBG) as an offset filter to suppress the pattern dependence and improve the RSOA modulation bandwidth. Both experimental and simulation results are provided, which are useful results for designing cost-effective colorless transceivers.

Experimental demonstration of large capacity WSDM optical access network with multicore fibers and advanced modulation formats.

PubMed

Li, Borui; Feng, Zhenhua; Tang, Ming; Xu, Zhilin; Fu, Songnian; Wu, Qiong; Deng, Lei; Tong, Weijun; Liu, Shuang; Shum, Perry Ping

2015-05-04

Towards the next generation optical access network supporting large capacity data transmission to enormous number of users covering a wider area, we proposed a hybrid wavelength-space division multiplexing (WSDM) optical access network architecture utilizing multicore fibers with advanced modulation formats. As a proof of concept, we experimentally demonstrated a WSDM optical access network with duplex transmission using our developed and fabricated multicore (7-core) fibers with 58.7km distance. As a cost-effective modulation scheme for access network, the optical OFDM-QPSK signal has been intensity modulated on the downstream transmission in the optical line terminal (OLT) and it was directly detected in the optical network unit (ONU) after MCF transmission. 10 wavelengths with 25GHz channel spacing from an optical comb generator are employed and each wavelength is loaded with 5Gb/s OFDM-QPSK signal. After amplification, power splitting, and fan-in multiplexer, 10-wavelength downstream signal was injected into six outer layer cores simultaneously and the aggregation downstream capacity reaches 300 Gb/s. -16 dBm sensitivity has been achieved for 3.8 × 10^-3 bit error ratio (BER) with 7% Forward Error Correction (FEC) limit for all wavelengths in every core. Upstream signal from ONU side has also been generated and the bidirectional transmission in the same core causes negligible performance degradation to the downstream signal. As a universal platform for wired/wireless data access, our proposed architecture provides additional dimension for high speed mobile signal transmission and we hence demonstrated an upstream delivery of 20Gb/s per wavelength with QPSK modulation formats using the inner core of MCF emulating a mobile backhaul service. The IQ modulated data was coherently detected in the OLT side. -19 dBm sensitivity has been achieved under the FEC limit and more than 18 dB power budget is guaranteed.

Multi terabits/s optical access transport technologies

NASA Astrophysics Data System (ADS)

Binh, Le Nguyen; Wang Tao, Thomas; Livshits, Daniil; Gubenko, Alexey; Karinou, Fotini; Liu Ning, Gordon; Shkolnik, Alexey

2016-02-01

Tremendous efforts have been developed for multi-Tbps over ultra-long distance and metro and access optical networks. With the exponential increase demand on data transmission, storage and serving, especially the 5G wireless access scenarios, the optical Internet networking has evolved to data-center based optical networks pressuring on novel and economical access transmission systems. This paper reports (1) Experimental platforms and transmission techniques employing band-limited optical components operating at 10G for 100G based at 28G baud. Advanced modulation formats such as PAM-4, DMT, duo-binary etc are reported and their advantages and disadvantages are analyzed so as to achieve multi-Tbps optical transmission systems for access inter- and intra- data-centered-based networks; (2) Integrated multi-Tbps combining comb laser sources and micro-ring modulators meeting the required performance for access systems are reported. Ten-sub-carrier quantum dot com lasers are employed in association with wideband optical intensity modulators to demonstrate the feasibility of such sources and integrated micro-ring modulators acting as a combined function of demultiplexing/multiplexing and modulation, hence compactness and economy scale. Under the use of multi-level modulation and direct detection at 56 GBd an aggregate of higher than 2Tbps and even 3Tbps can be achieved by interleaved two comb lasers of 16 sub-carrier lines; (3) Finally the fundamental designs of ultra-compacts flexible filters and switching integrated components based on Si photonics for multi Tera-bps active interconnection are presented. Experimental results on multi-channels transmissions and performances of optical switching matrices and effects on that of data channels are proposed.

Receiver Statistics for Cognitive Radios in Dynamic Spectrum Access Networks

DTIC Science & Technology

2012-02-28

SNR) are employed by many protocols and processes in direct-sequence ( DS ) spread-spectrum packet radio networks, including soft-decision decoding...adaptive modulation protocols, and power adjustment protocols. For DS spread spectrum, we have introduced and evaluated SNR estimators that employ...obtained during demodulation in a binary CDMA receiver. We investigated several methods to apply the proposed metric to the demodulator’s soft-decision

Functional Module Analysis for Gene Coexpression Networks with Network Integration.

PubMed

Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

2015-01-01

Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

Baseline effects of transcranial direct current stimulation on glutamatergic neurotransmission and large-scale network connectivity

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

Hunter, Michael A.; Coffman, Brian A.; Gasparovic, Charles

Transcranial direct current stimulation (tDCS) modulates glutamatergic neurotransmission and can be utilized as a novel treatment intervention for a multitude of populations. However, the exact mechanism by which tDCS modulates the brain's neural architecture, from the micro to macro scales, have yet to be investigated. In this paper, using a within-subjects design, resting-state functional magnetic resonance imaging (rs-fMRI) and proton magnetic resonance spectroscopy ( 1H MRS) were performed immediately before and after the administration of anodal tDCS over right parietal cortex. Group independent component analysis (ICA) was used to decompose fMRI scans into 75 brain networks, from which 12 resting-statemore » networks were identified that had significant voxel-wise functional connectivity to anatomical regions of interest. 1H MRS was used to obtain estimates of combined glutamate and glutamine (Glx) concentrations from bilateral intraparietal sulcus. Paired sample t-tests showed significantly increased Glx under the anodal electrode, but not in homologous regions of the contralateral hemisphere. Increases of within-network connectivity were observed within the superior parietal, inferior parietal, left frontal–parietal, salience and cerebellar intrinsic networks, and decreases in connectivity were observed in the anterior cingulate and the basal ganglia ( p<0.05, FDR-corrected). Individual differences in Glx concentrations predicted network connectivity in most of these networks. Finally, the observed relationships between glutamatergic neurotransmission and network connectivity may be used to guide future tDCS protocols that aim to target and alter neuroplastic mechanisms in healthy individuals as well as those with psychiatric and neurologic disorders.« less

Baseline effects of transcranial direct current stimulation on glutamatergic neurotransmission and large-scale network connectivity

DOE PAGES

Hunter, Michael A.; Coffman, Brian A.; Gasparovic, Charles; ...

2014-10-12

Transcranial direct current stimulation (tDCS) modulates glutamatergic neurotransmission and can be utilized as a novel treatment intervention for a multitude of populations. However, the exact mechanism by which tDCS modulates the brain's neural architecture, from the micro to macro scales, have yet to be investigated. In this paper, using a within-subjects design, resting-state functional magnetic resonance imaging (rs-fMRI) and proton magnetic resonance spectroscopy ( 1H MRS) were performed immediately before and after the administration of anodal tDCS over right parietal cortex. Group independent component analysis (ICA) was used to decompose fMRI scans into 75 brain networks, from which 12 resting-statemore » networks were identified that had significant voxel-wise functional connectivity to anatomical regions of interest. 1H MRS was used to obtain estimates of combined glutamate and glutamine (Glx) concentrations from bilateral intraparietal sulcus. Paired sample t-tests showed significantly increased Glx under the anodal electrode, but not in homologous regions of the contralateral hemisphere. Increases of within-network connectivity were observed within the superior parietal, inferior parietal, left frontal–parietal, salience and cerebellar intrinsic networks, and decreases in connectivity were observed in the anterior cingulate and the basal ganglia ( p<0.05, FDR-corrected). Individual differences in Glx concentrations predicted network connectivity in most of these networks. Finally, the observed relationships between glutamatergic neurotransmission and network connectivity may be used to guide future tDCS protocols that aim to target and alter neuroplastic mechanisms in healthy individuals as well as those with psychiatric and neurologic disorders.« less

Communication using VCSEL laser array

NASA Technical Reports Server (NTRS)

Goorjian, Peter M. (Inventor)

2008-01-01

Ultrafast directional beam switching, using coupled vertical cavity surface emitting lasers (VCSELs) is combined with a light modulator to provide information transfer at bit rates of tens of GHz. This approach is demonstrated to achieve beam switching frequencies of 32-50 GHz in some embodiments and directional beam switching with angular differences of about eight degrees. This switching scheme is likely to be useful for ultrafast optical networks at frequencies much higher than achievable with other approaches. A Mach-Zehnder interferometer, a Fabry-Perot etalon, or a semiconductor-based electro-absorption transmission channel, among others, can be used as a light modulator.

Automated Power-Distribution System

NASA Technical Reports Server (NTRS)

Thomason, Cindy; Anderson, Paul M.; Martin, James A.

1990-01-01

Automated power-distribution system monitors and controls electrical power to modules in network. Handles both 208-V, 20-kHz single-phase alternating current and 120- to 150-V direct current. Power distributed to load modules from power-distribution control units (PDCU's) via subsystem distributors. Ring busses carry power to PDCU's from power source. Needs minimal attention. Detects faults and also protects against them. Potential applications include autonomous land vehicles and automated industrial process systems.

Phase Resetting Reveals Network Dynamics Underlying a Bacterial Cell Cycle

PubMed Central

Lin, Yihan; Li, Ying; Crosson, Sean; Dinner, Aaron R.; Scherer, Norbert F.

2012-01-01

Genomic and proteomic methods yield networks of biological regulatory interactions but do not provide direct insight into how those interactions are organized into functional modules, or how information flows from one module to another. In this work we introduce an approach that provides this complementary information and apply it to the bacterium Caulobacter crescentus, a paradigm for cell-cycle control. Operationally, we use an inducible promoter to express the essential transcriptional regulatory gene ctrA in a periodic, pulsed fashion. This chemical perturbation causes the population of cells to divide synchronously, and we use the resulting advance or delay of the division times of single cells to construct a phase resetting curve. We find that delay is strongly favored over advance. This finding is surprising since it does not follow from the temporal expression profile of CtrA and, in turn, simulations of existing network models. We propose a phenomenological model that suggests that the cell-cycle network comprises two distinct functional modules that oscillate autonomously and couple in a highly asymmetric fashion. These features collectively provide a new mechanism for tight temporal control of the cell cycle in C. crescentus. We discuss how the procedure can serve as the basis for a general approach for probing network dynamics, which we term chemical perturbation spectroscopy (CPS). PMID:23209388

Phase resetting reveals network dynamics underlying a bacterial cell cycle.

PubMed

Lin, Yihan; Li, Ying; Crosson, Sean; Dinner, Aaron R; Scherer, Norbert F

2012-01-01

Genomic and proteomic methods yield networks of biological regulatory interactions but do not provide direct insight into how those interactions are organized into functional modules, or how information flows from one module to another. In this work we introduce an approach that provides this complementary information and apply it to the bacterium Caulobacter crescentus, a paradigm for cell-cycle control. Operationally, we use an inducible promoter to express the essential transcriptional regulatory gene ctrA in a periodic, pulsed fashion. This chemical perturbation causes the population of cells to divide synchronously, and we use the resulting advance or delay of the division times of single cells to construct a phase resetting curve. We find that delay is strongly favored over advance. This finding is surprising since it does not follow from the temporal expression profile of CtrA and, in turn, simulations of existing network models. We propose a phenomenological model that suggests that the cell-cycle network comprises two distinct functional modules that oscillate autonomously and couple in a highly asymmetric fashion. These features collectively provide a new mechanism for tight temporal control of the cell cycle in C. crescentus. We discuss how the procedure can serve as the basis for a general approach for probing network dynamics, which we term chemical perturbation spectroscopy (CPS).

Shifts of Gamma Phase across Primary Visual Cortical Sites Reflect Dynamic Stimulus-Modulated Information Transfer.

PubMed

Besserve, Michel; Lowe, Scott C; Logothetis, Nikos K; Schölkopf, Bernhard; Panzeri, Stefano

2015-01-01

Distributed neural processing likely entails the capability of networks to reconfigure dynamically the directionality and strength of their functional connections. Yet, the neural mechanisms that may allow such dynamic routing of the information flow are not yet fully understood. We investigated the role of gamma band (50-80 Hz) oscillations in transient modulations of communication among neural populations by using measures of direction-specific causal information transfer. We found that the local phase of gamma-band rhythmic activity exerted a stimulus-modulated and spatially-asymmetric directed effect on the firing rate of spatially separated populations within the primary visual cortex. The relationships between gamma phases at different sites (phase shifts) could be described as a stimulus-modulated gamma-band wave propagating along the spatial directions with the largest information transfer. We observed transient stimulus-related changes in the spatial configuration of phases (compatible with changes in direction of gamma wave propagation) accompanied by a relative increase of the amount of information flowing along the instantaneous direction of the gamma wave. These effects were specific to the gamma-band and suggest that the time-varying relationships between gamma phases at different locations mark, and possibly causally mediate, the dynamic reconfiguration of functional connections.

Shifts of Gamma Phase across Primary Visual Cortical Sites Reflect Dynamic Stimulus-Modulated Information Transfer

PubMed Central

Besserve, Michel; Lowe, Scott C.; Logothetis, Nikos K.; Schölkopf, Bernhard; Panzeri, Stefano

2015-01-01

Distributed neural processing likely entails the capability of networks to reconfigure dynamically the directionality and strength of their functional connections. Yet, the neural mechanisms that may allow such dynamic routing of the information flow are not yet fully understood. We investigated the role of gamma band (50–80 Hz) oscillations in transient modulations of communication among neural populations by using measures of direction-specific causal information transfer. We found that the local phase of gamma-band rhythmic activity exerted a stimulus-modulated and spatially-asymmetric directed effect on the firing rate of spatially separated populations within the primary visual cortex. The relationships between gamma phases at different sites (phase shifts) could be described as a stimulus-modulated gamma-band wave propagating along the spatial directions with the largest information transfer. We observed transient stimulus-related changes in the spatial configuration of phases (compatible with changes in direction of gamma wave propagation) accompanied by a relative increase of the amount of information flowing along the instantaneous direction of the gamma wave. These effects were specific to the gamma-band and suggest that the time-varying relationships between gamma phases at different locations mark, and possibly causally mediate, the dynamic reconfiguration of functional connections. PMID:26394205

Hierarchical thinking in network biology: the unbiased modularization of biochemical networks.

PubMed

Papin, Jason A; Reed, Jennifer L; Palsson, Bernhard O

2004-12-01

As reconstructed biochemical reaction networks continue to grow in size and scope, there is a growing need to describe the functional modules within them. Such modules facilitate the study of biological processes by deconstructing complex biological networks into conceptually simple entities. The definition of network modules is often based on intuitive reasoning. As an alternative, methods are being developed for defining biochemical network modules in an unbiased fashion. These unbiased network modules are mathematically derived from the structure of the whole network under consideration.

Symmetric 40-Gb/s TWDM-PON with 51-dB loss budget by using a single SOA as preamplifier, booster and format converter in ONU.

PubMed

Li, Zhengxuan; Yi, Lilin; Hu, Weisheng

2014-10-06

In this paper, we propose to use a semiconductor optical amplifier (SOA) in the optical network unit (ONU) to improve the loss budget in time and wavelength division multiplexed-passive optical network (TWDM-PON) systems. The SOA boosts the upstream signal to increase the output power of the electro-absorption modulated laser (EML) and simultaneously pre-amplifies the downstream signal for sensitivity improvement. The penalty caused by cross gain modulation (XGM) effect is negligible due to the low extinction ratio (ER) of upstream signal and the large wavelength difference between upstream and downstream links. In order to achieve a higher output power, the SOA is driven into its saturation region, where the self-phase modulation (SPM) effect converts the intensity into phase information and realizes on-off-keying (OOK) to phase-shifted-keying (PSK) format conversion. In this way, the pattern effect is eliminated, which releases the requirement of gain-clamping on SOA. To further improve the loss budget of upstream link, an Erbium doped fiber amplifier (EDFA) is used in the optical line terminal (OLT) to pre-amplify the received signal. For the downstream direction, directly modulated laser (DML) is used as the laser source. Taking advantage of its carrier-less characteristic, directly modulated signal shows high tolerance to fiber nonlinearity, which could support a downstream launch power as high as + 16 dBm per channel. In addition, the signal is pre-amplified by the SOA in ONU before being detected, so the sensitivity limitation for downstream link is also removed. As a result, a truly passive symmetric 40-Gb/s TWDM-PON was demonstrated, achieving a link loss budget of 51 dB.

Contextual Modulation is Related to Efficiency in a Spiking Network Model of Visual Cortex.

PubMed

Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo; Vanni, Simo

2015-01-01

In the visual cortex, stimuli outside the classical receptive field (CRF) modulate the neural firing rate, without driving the neuron by themselves. In the primary visual cortex (V1), such contextual modulation can be parametrized with an area summation function (ASF): increasing stimulus size causes first an increase and then a decrease of firing rate before reaching an asymptote. Earlier work has reported increase of sparseness when CRF stimulation is extended to its surroundings. However, there has been no clear connection between the ASF and network efficiency. Here we aimed to investigate possible link between ASF and network efficiency. In this study, we simulated the responses of a biomimetic spiking neural network model of the visual cortex to a set of natural images. We varied the network parameters, and compared the V1 excitatory neuron spike responses to the corresponding responses predicted from earlier single neuron data from primate visual cortex. The network efficiency was quantified with firing rate (which has direct association to neural energy consumption), entropy per spike and population sparseness. All three measures together provided a clear association between the network efficiency and the ASF. The association was clear when varying the horizontal connectivity within V1, which influenced both the efficiency and the distance to ASF, DAS. Given the limitations of our biophysical model, this association is qualitative, but nevertheless suggests that an ASF-like receptive field structure can cause efficient population response.

Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data

PubMed Central

Ping, Yanyan; Deng, Yulan; Wang, Li; Zhang, Hongyi; Zhang, Yong; Xu, Chaohan; Zhao, Hongying; Fan, Huihui; Yu, Fulong; Xiao, Yun; Li, Xia

2015-01-01

The driver genetic aberrations collectively regulate core cellular processes underlying cancer development. However, identifying the modules of driver genetic alterations and characterizing their functional mechanisms are still major challenges for cancer studies. Here, we developed an integrative multi-omics method CMDD to identify the driver modules and their affecting dysregulated genes through characterizing genetic alteration-induced dysregulated networks. Applied to glioblastoma (GBM), the CMDD identified a core gene module of 17 genes, including seven known GBM drivers, and their dysregulated genes. The module showed significant association with shorter survival of GBM. When classifying driver genes in the module into two gene sets according to their genetic alteration patterns, we found that one gene set directly participated in the glioma pathway, while the other indirectly regulated the glioma pathway, mostly, via their dysregulated genes. Both of the two gene sets were significant contributors to survival and helpful for classifying GBM subtypes, suggesting their critical roles in GBM pathogenesis. Also, by applying the CMDD to other six cancers, we identified some novel core modules associated with overall survival of patients. Together, these results demonstrate integrative multi-omics data can identify driver modules and uncover their dysregulated genes, which is useful for interpreting cancer genome. PMID:25653168

Membrane potential dynamics of grid cells

PubMed Central

Domnisoru, Cristina; Kinkhabwala, Amina A.; Tank, David W.

2014-01-01

During navigation, grid cells increase their spike rates in firing fields arranged on a strikingly regular triangular lattice, while their spike timing is often modulated by theta oscillations. Oscillatory interference models of grid cells predict theta amplitude modulations of membrane potential during firing field traversals, while competing attractor network models predict slow depolarizing ramps. Here, using in-vivo whole-cell recordings, we tested these models by directly measuring grid cell intracellular potentials in mice running along linear tracks in virtual reality. Grid cells had large and reproducible ramps of membrane potential depolarization that were the characteristic signature tightly correlated with firing fields. Grid cells also exhibited intracellular theta oscillations that influenced their spike timing. However, the properties of theta amplitude modulations were not consistent with the view that they determine firing field locations. Our results support cellular and network mechanisms in which grid fields are produced by slow ramps, as in attractor models, while theta oscillations control spike timing. PMID:23395984

Compression of Flow Can Reveal Overlapping-Module Organization in Networks

NASA Astrophysics Data System (ADS)

Viamontes Esquivel, Alcides; Rosvall, Martin

2011-10-01

To better understand the organization of overlapping modules in large networks with respect to flow, we introduce the map equation for overlapping modules. In this information-theoretic framework, we use the correspondence between compression and regularity detection. The generalized map equation measures how well we can compress a description of flow in the network when we partition it into modules with possible overlaps. When we minimize the generalized map equation over overlapping network partitions, we detect modules that capture flow and determine which nodes at the boundaries between modules should be classified in multiple modules and to what degree. With a novel greedy-search algorithm, we find that some networks, for example, the neural network of the nematode Caenorhabditis elegans, are best described by modules dominated by hard boundaries, but that others, for example, the sparse European-roads network, have an organization of highly overlapping modules.

The middleware architecture supports heterogeneous network systems for module-based personal robot system

NASA Astrophysics Data System (ADS)

Choo, Seongho; Li, Vitaly; Choi, Dong Hee; Jung, Gi Deck; Park, Hong Seong; Ryuh, Youngsun

2005-12-01

On developing the personal robot system presently, the internal architecture is every module those occupy separated functions are connected through heterogeneous network system. This module-based architecture supports specialization and division of labor at not only designing but also implementation, as an effect of this architecture, it can reduce developing times and costs for modules. Furthermore, because every module is connected among other modules through network systems, we can get easy integrations and synergy effect to apply advanced mutual functions by co-working some modules. In this architecture, one of the most important technologies is the network middleware that takes charge communications among each modules connected through heterogeneous networks systems. The network middleware acts as the human nerve system inside of personal robot system; it relays, transmits, and translates information appropriately between modules that are similar to human organizations. The network middleware supports various hardware platform, heterogeneous network systems (Ethernet, Wireless LAN, USB, IEEE 1394, CAN, CDMA-SMS, RS-232C). This paper discussed some mechanisms about our network middleware to intercommunication and routing among modules, methods for real-time data communication and fault-tolerant network service. There have designed and implemented a layered network middleware scheme, distributed routing management, network monitoring/notification technology on heterogeneous networks for these goals. The main theme is how to make routing information in our network middleware. Additionally, with this routing information table, we appended some features. Now we are designing, making a new version network middleware (we call 'OO M/W') that can support object-oriented operation, also are updating program sources itself for object-oriented architecture. It is lighter, faster, and can support more operation systems and heterogeneous network systems, but other general purposed middlewares like CORBA, UPnP, etc. can support only one network protocol or operating system.

Is My Network Module Preserved and Reproducible?

PubMed Central

Langfelder, Peter; Luo, Rui; Oldham, Michael C.; Horvath, Steve

2011-01-01

In many applications, one is interested in determining which of the properties of a network module change across conditions. For example, to validate the existence of a module, it is desirable to show that it is reproducible (or preserved) in an independent test network. Here we study several types of network preservation statistics that do not require a module assignment in the test network. We distinguish network preservation statistics by the type of the underlying network. Some preservation statistics are defined for a general network (defined by an adjacency matrix) while others are only defined for a correlation network (constructed on the basis of pairwise correlations between numeric variables). Our applications show that the correlation structure facilitates the definition of particularly powerful module preservation statistics. We illustrate that evaluating module preservation is in general different from evaluating cluster preservation. We find that it is advantageous to aggregate multiple preservation statistics into summary preservation statistics. We illustrate the use of these methods in six gene co-expression network applications including 1) preservation of cholesterol biosynthesis pathway in mouse tissues, 2) comparison of human and chimpanzee brain networks, 3) preservation of selected KEGG pathways between human and chimpanzee brain networks, 4) sex differences in human cortical networks, 5) sex differences in mouse liver networks. While we find no evidence for sex specific modules in human cortical networks, we find that several human cortical modules are less preserved in chimpanzees. In particular, apoptosis genes are differentially co-expressed between humans and chimpanzees. Our simulation studies and applications show that module preservation statistics are useful for studying differences between the modular structure of networks. Data, R software and accompanying tutorials can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/ModulePreservation. PMID:21283776

PAM4 based symmetrical 112-Gbps long-reach TWDM-PON

NASA Astrophysics Data System (ADS)

Wu, Liyu; Gao, Fan; Zhang, Minming; Fu, Songnian; Deng, Lei; Choi, Michael; Chang, Donald; Lei, Gordon K. P.; Liu, Deming

2018-02-01

We experimentally demonstrate cost effective symmetrical 112-Gbps long-reach passive optical network (LR-PON) over 70-km standard signal mode fiber (SSMF), based on pulse amplitude modulation (PAM)-4. Four 10G-class directly modulated lasers (DMLs) at C-band are used for achieving 4 × 28-Gbps downstream transmission, while two 18G-class DMLs at O-band are used to realize 2 × 56-Gbps upstream transmission, without any optical amplification in optical distributed network (ODN). Both dispersion compensation fiber (DCF) for downstream signal and praseodymium-doped fiber amplifier (PDFA) for upstream signal are equipped at optical line terminal (OLT). Meanwhile, sparse Volterra filter (SVF) equalizer is proposed to mitigate the transmission impairments with substantial reduction of computation complexity. Finally, we can successfully provide a loss budget of 33 dB per downstream wavelength channel, indicating of 64 optical network units (ONUs) with more than 1.25 Gbps per ONU.

Preface

NASA Astrophysics Data System (ADS)

Zhuge, Qunbi; Chen, Xi

2018-02-01

Global IP traffic is predicted to increase nearly threefold over the next 5 years, driven by emerging high-bandwidth-demanding applications, such as cloud computing, 5G wireless, high-definition video streaming, and virtual reality. This results in a continuously increasing demand on the capacity of backbone optical networks. During the past decade, advanced digital signal processing (DSP), modulation formats, and forward error correction (FEC) were commercially realized to exploit the capacity potential of long-haul fiber channels, and have increased per channel data rate from 10 Gb/s to 400 Gb/s. DSP has played a crucial role in coherent transceivers to accommodate channel impairments including chromatic dispersion (CD), polarization mode dispersion (PMD), laser phase noise, fiber nonlinearities, clock jitter, and so forth. The advance of DSP has also enabled innovations in modulation formats to increase spectral efficiency, improve linear/nonlinear noise tolerance, and realize flexible bandwidth. Moving forward to next generation 1 Tb/s systems on conventional single mode fiber (SMF) platform, more innovations in DSP techniques are needed to further reduce cost per bit, increase network efficiency, and close the gap to the Shannon limit. To further increase capacity per fiber, spatial-division multiplexing (SDM) systems can be used. DSP techniques such as advanced channel equalization methods and distortion compensation can help SDM systems to achieve higher system capacity. In the area of short-reach transmission, the rapid increase of data center network traffic has driven the development of optical technologies for both intra- and inter-data center interconnects (DCI). In particular, DSP has been exploited in intensity-modulation direct detection (IM/DD) systems to realize 400 Gb/s pluggable optical transceivers. In addition, multi-dimensional direct detection modulation schemes are being investigated to increase the data rate per wavelength targeting 1 Tb/s interface.

Concurrent information affects response inhibition processes via the modulation of theta oscillations in cognitive control networks.

PubMed

Chmielewski, Witold X; Mückschel, Moritz; Dippel, Gabriel; Beste, Christian

2016-11-01

Inhibiting responses is a challenge, where the outcome (partly) depends on the situational context. In everyday situations, response inhibition performance might be altered when irrelevant input is presented simultaneously with the information relevant for response inhibition. More specifically, irrelevant concurrent information may either brace or interfere with response-relevant information, depending on whether these inputs are redundant or conflicting. The aim of this study is to investigate neurophysiological mechanisms and the network underlying such modulations using EEG beamforming as method. The results show that in comparison to a baseline condition without concurrent information, response inhibition performance can be aggravated or facilitated by manipulating the extent of conflict via concurrent input. This depends on whether the requirement for cognitive control is high, as in conflicting trials, or whether it is low, as in redundant trials. In line with this, the total theta frequency power decreases in a right hemispheric orbitofrontal response inhibition network including the SFG, MFG, and SMA, when concurrent redundant information facilitates response inhibition processes. Vice versa, theta activity in a left-hemispheric response inhibition network (i.e., SFG, MFG, and IFG) increases, when conflicting concurrent information compromises response inhibition processes. We conclude that concurrent information bi-directionally shifts response inhibition performance and modulates the network architecture underlying theta oscillations which are signaling different levels of the need for cognitive control.

Top-down alpha oscillatory network interactions during visuospatial attention orienting.

PubMed

Doesburg, Sam M; Bedo, Nicolas; Ward, Lawrence M

2016-05-15

Neuroimaging and lesion studies indicate that visual attention is controlled by a distributed network of brain areas. The covert control of visuospatial attention has also been associated with retinotopic modulation of alpha-band oscillations within early visual cortex, which are thought to underlie inhibition of ignored areas of visual space. The relation between distributed networks mediating attention control and more focal oscillatory mechanisms, however, remains unclear. The present study evaluated the hypothesis that alpha-band, directed, network interactions within the attention control network are systematically modulated by the locus of visuospatial attention. We localized brain areas involved in visuospatial attention orienting using magnetoencephalographic (MEG) imaging and investigated alpha-band Granger-causal interactions among activated regions using narrow-band transfer entropy. The deployment of attention to one side of visual space was indexed by lateralization of alpha power changes between about 400ms and 700ms post-cue onset. The changes in alpha power were associated, in the same time period, with lateralization of anterior-to-posterior information flow in the alpha-band from various brain areas involved in attention control, including the anterior cingulate cortex, left middle and inferior frontal gyri, left superior temporal gyrus, and right insula, and inferior parietal lobule, to early visual areas. We interpreted these results to indicate that distributed network interactions mediated by alpha oscillations exert top-down influences on early visual cortex to modulate inhibition of processing for ignored areas of visual space. Copyright © 2016. Published by Elsevier Inc.

Using Fabry-Perot laser diode and reflective semiconductor optical amplifier for long reach WDM-PON system

NASA Astrophysics Data System (ADS)

Yeh, C. H.; Chow, C. W.; Wu, Y. F.; Shih, F. Y.; Chi, S.

2011-10-01

In this investigation, we propose and investigate the simple self-injection locked Fabry-Perot laser diodes (FP-LDs) in optical line terminal (OLT); and wavelength-tunable optical network unit (ONU) using reflective optical semiconductor amplifier (RSOA) and FP-LD laser for downstream and upstream traffic in long reach (LR) wavelength division multiplexed-passive optical network (WDM-PON) respectively. The output performance of the proposed two laser sources in terms of power and side-mode suppression ratio (SMSR) has been discussed. Here, for the downstream traffic, the proposed optical transmitter can be directly modulated at 2.5 Gb/s on-off keying (OOK) format with nearly 0.4 dB power penalty at bit error rate (BER) of 10 -9 through 75 km single-mode fiber (SMF) transmission. Moreover, the proposed upstream transmitter can be directly modulated at 1.25 and 2.5 Gb/s with nearly 0.5 and 1.1 dB power penalty, respectively, at the BER of 10 -9.

Revealing the Hidden Relationship by Sparse Modules in Complex Networks with a Large-Scale Analysis

PubMed Central

Jiao, Qing-Ju; Huang, Yan; Liu, Wei; Wang, Xiao-Fan; Chen, Xiao-Shuang; Shen, Hong-Bin

2013-01-01

One of the remarkable features of networks is module that can provide useful insights into not only network organizations but also functional behaviors between their components. Comprehensive efforts have been devoted to investigating cohesive modules in the past decade. However, it is still not clear whether there are important structural characteristics of the nodes that do not belong to any cohesive module. In order to answer this question, we performed a large-scale analysis on 25 complex networks with different types and scales using our recently developed BTS (bintree seeking) algorithm, which is able to detect both cohesive and sparse modules in the network. Our results reveal that the sparse modules composed by the cohesively isolated nodes widely co-exist with the cohesive modules. Detailed analysis shows that both types of modules provide better characterization for the division of a network into functional units than merely cohesive modules, because the sparse modules possibly re-organize the nodes in the so-called cohesive modules, which lack obvious modular significance, into meaningful groups. Compared with cohesive modules, the sizes of sparse ones are generally smaller. Sparse modules are also found to have preferences in social and biological networks than others. PMID:23762457

An iterative network partition algorithm for accurate identification of dense network modules

PubMed Central

Sun, Siqi; Dong, Xinran; Fu, Yao; Tian, Weidong

2012-01-01

A key step in network analysis is to partition a complex network into dense modules. Currently, modularity is one of the most popular benefit functions used to partition network modules. However, recent studies suggested that it has an inherent limitation in detecting dense network modules. In this study, we observed that despite the limitation, modularity has the advantage of preserving the primary network structure of the undetected modules. Thus, we have developed a simple iterative Network Partition (iNP) algorithm to partition a network. The iNP algorithm provides a general framework in which any modularity-based algorithm can be implemented in the network partition step. Here, we tested iNP with three modularity-based algorithms: multi-step greedy (MSG), spectral clustering and Qcut. Compared with the original three methods, iNP achieved a significant improvement in the quality of network partition in a benchmark study with simulated networks, identified more modules with significantly better enrichment of functionally related genes in both yeast protein complex network and breast cancer gene co-expression network, and discovered more cancer-specific modules in the cancer gene co-expression network. As such, iNP should have a broad application as a general method to assist in the analysis of biological networks. PMID:22121225

Regional GABA Concentrations Modulate Inter-network Resting-state Functional Connectivity.

PubMed

Chen, Xi; Fan, Xiaoying; Hu, Yuzheng; Zuo, Chun; Whitfield-Gabrieli, Susan; Holt, Daphne; Gong, Qiyong; Yang, Yihong; Pizzagalli, Diego A; Du, Fei; Ongur, Dost

2018-03-28

Coordinated activity within and differential activity between large-scale neuronal networks such as the default mode network (DMN) and the control network (CN) is a critical feature of brain organization. The CN usually exhibits activations in response to cognitive tasks while the DMN shows deactivations; in addition, activity between the two networks is anti-correlated at rest. To address this issue, we used functional MRI to measure whole-brain BOLD signal during resting-state and task-evoked conditions, and MR spectroscopy (MRS) to quantify GABA and glutamate concentrations, in nodes within the DMN and CN (MPFC and DLPFC, respectively) in 19 healthy individuals at 3 Tesla. We found that GABA concentrations in the MPFC were significantly associated with DMN deactivation during a working memory task and with anti-correlation between DMN and CN at rest and during task performance, while GABA concentrations in the DLPFC weakly modulated DMN-CN anti-correlation in the opposite direction. Highlighting specificity, glutamate played a less significant role related to brain activity. These findings indicate that GABA in the MPFC is potentially involved in orchestrating between-network brain activity at rest and during task performance.

Modular decomposition of metabolic reaction networks based on flux analysis and pathway projection.

PubMed

Yoon, Jeongah; Si, Yaguang; Nolan, Ryan; Lee, Kyongbum

2007-09-15

The rational decomposition of biochemical networks into sub-structures has emerged as a useful approach to study the design of these complex systems. A biochemical network is characterized by an inhomogeneous connectivity distribution, which gives rise to several organizational features, including modularity. To what extent the connectivity-based modules reflect the functional organization of the network remains to be further explored. In this work, we examine the influence of physiological perturbations on the modular organization of cellular metabolism. Modules were characterized for two model systems, liver and adipocyte primary metabolism, by applying an algorithm for top-down partition of directed graphs with non-uniform edge weights. The weights were set by the engagement of the corresponding reactions as expressed by the flux distribution. For the base case of the fasted rat liver, three modules were found, carrying out the following biochemical transformations: ketone body production, glucose synthesis and transamination. This basic organization was further modified when different flux distributions were applied that describe the liver's metabolic response to whole body inflammation. For the fully mature adipocyte, only a single module was observed, integrating all of the major pathways needed for lipid storage. Weaker levels of integration between the pathways were found for the early stages of adipocyte differentiation. Our results underscore the inhomogeneous distribution of both connectivity and connection strengths, and suggest that global activity data such as the flux distribution can be used to study the organizational flexibility of cellular metabolism. Supplementary data are available at Bioinformatics online.

Widespread receptivity to neuropeptide PDF throughout the neuronal circadian clock network of Drosophila revealed by real-time cyclic AMP imaging.

PubMed

Shafer, Orie T; Kim, Dong Jo; Dunbar-Yaffe, Richard; Nikolaev, Viacheslav O; Lohse, Martin J; Taghert, Paul H

2008-04-24

The neuropeptide PDF is released by sixteen clock neurons in Drosophila and helps maintain circadian activity rhythms by coordinating a network of approximately 150 neuronal clocks. Whether PDF acts directly on elements of this neural network remains unknown. We address this question by adapting Epac1-camps, a genetically encoded cAMP FRET sensor, for use in the living brain. We find that a subset of the PDF-expressing neurons respond to PDF with long-lasting cAMP increases and confirm that such responses require the PDF receptor. In contrast, an unrelated Drosophila neuropeptide, DH31, stimulates large cAMP increases in all PDF-expressing clock neurons. Thus, the network of approximately 150 clock neurons displays widespread, though not uniform, PDF receptivity. This work introduces a sensitive means of measuring cAMP changes in a living brain with subcellular resolution. Specifically, it experimentally confirms the longstanding hypothesis that PDF is a direct modulator of most neurons in the Drosophila clock network.

Topological Alterations and Symptom-Relevant Modules in the Whole-Brain Structural Network in Semantic Dementia.

PubMed

Ding, Junhua; Chen, Keliang; Zhang, Weibin; Li, Ming; Chen, Yan; Yang, Qing; Lv, Yingru; Guo, Qihao; Han, Zaizhu

2017-01-01

Semantic dementia (SD) is characterized by a selective decline in semantic processing. Although the neuropsychological pattern of this disease has been identified, its topological global alterations and symptom-relevant modules in the whole-brain anatomical network have not been fully elucidated. This study aims to explore the topological alteration of anatomical network in SD and reveal the modules associated with semantic deficits in this disease. We first constructed the whole-brain white-matter networks of 20 healthy controls and 19 patients with SD. Then, the network metrics of graph theory were compared between these two groups. Finally, we separated the network of SD patients into different modules and correlated the structural integrity of each module with the severity of the semantic deficits across patients. The network of the SD patients presented a significantly reduced global efficiency, indicating that the long-distance connections were damaged. The network was divided into the following four distinctive modules: the left temporal/occipital/parietal, frontal, right temporal/occipital, and frontal/parietal modules. The first two modules were associated with the semantic deficits of SD. These findings illustrate the skeleton of the neuroanatomical network of SD patients and highlight the key role of the left temporal/occipital/parietal module and the left frontal module in semantic processing.

Proceedings of the Fourth International Mobile Satellite Conference (IMSC 1995)

NASA Technical Reports Server (NTRS)

Rigley, Jack R. (Compiler); Estabrook, Polly (Compiler); Reekie, D. Hugh M. (Editor)

1995-01-01

The theme to the 1995 International Mobile Satellite Conference was 'Mobile Satcom Comes of Age'. The sessions included Modulation, Coding, and Multiple Access; Hybrid Networks - 1; Spacecraft Technology; propagation; Applications and Experiments - 1; Advanced System Concepts and Analysis; Aeronautical Mobile Satellite Communications; Mobile Terminal Antennas; Mobile Terminal Technology; Current and Planned Systems; Direct Broadcast Satellite; The Use of CDMA for LEO and ICO Mobile Satellite Systems; Hybrid Networks - 2; and Applications and Experiments - 2.

FDM and DMT performance comparison in high capacity point-to-point fibre links for intra/inter-datacentre connections

NASA Astrophysics Data System (ADS)

Gatto, A.; Parolari, P.; Boffi, P.

2018-05-01

Frequency division multiplexing (FDM) is attractive to achieve high capacities in multiple access networks characterized by direct modulation and direct detection. In this paper we take into account point-to-point intra- and inter-datacenter connections to understand the performance of FDM operation compared with the ones achievable with standard multiple carrier modulation approach based on discrete multitone (DMT). DMT and FDM allow to match the non-uniform and bandwidth-limited response of the system under test, associated with the employment of low-cost directly-modulated sources, such as VCSELs with high-frequency chirp, and with fibre-propagation in presence of chromatic dispersion. While for very short distances typical of intra-datacentre communications, the huge number of DMT subcarriers permits to increase the transported capacity with respect to the FDM employment, in case of few tens-km reaches typical of inter-datacentre connections, the capabilities of FDM are more evident, providing system performance similar to the case of DMT application.

Scalable Hierarchical Network Management System for Displaying Network Information in Three Dimensions

NASA Technical Reports Server (NTRS)

George, Jude (Inventor); Schlecht, Leslie (Inventor); McCabe, James D. (Inventor); LeKashman, John Jr. (Inventor)

1998-01-01

A network management system has SNMP agents distributed at one or more sites, an input output module at each site, and a server module located at a selected site for communicating with input output modules, each of which is configured for both SNMP and HNMP communications. The server module is configured exclusively for HNMP communications, and it communicates with each input output module according to the HNMP. Non-iconified, informationally complete views are provided of network elements to aid in network management.

Optimization of training sequence for DFT-spread DMT signal in optical access network with direct detection utilizing DML.

PubMed

Li, Fan; Li, Xinying; Yu, Jianjun; Chen, Lin

2014-09-22

We experimentally demonstrated the transmission of 79.86-Gb/s discrete-Fourier-transform spread 32 QAM discrete multi-tone (DFT-spread 32 QAM-DMT) signal over 20-km standard single-mode fiber (SSMF) utilizing directly modulated laser (DML). The experimental results show DFT-spread effectively reduces Peak-to-Average Power Ratio (PAPR) of DMT signal, and also well overcomes narrowband interference and high frequencies power attenuation. We compared different types of training sequence (TS) symbols and found that the optimized TS for channel estimation is the symbol with digital BPSK/QPSK modulation format due to its best performance against optical link noise during channel estimation.

A Biophysical Neural Model To Describe Spatial Visual Attention

NASA Astrophysics Data System (ADS)

Hugues, Etienne; José, Jorge V.

2008-02-01

Visual scenes have enormous spatial and temporal information that are transduced into neural spike trains. Psychophysical experiments indicate that only a small portion of a spatial image is consciously accessible. Electrophysiological experiments in behaving monkeys have revealed a number of modulations of the neural activity in special visual area known as V4, when the animal is paying attention directly towards a particular stimulus location. The nature of the attentional input to V4, however, remains unknown as well as to the mechanisms responsible for these modulations. We use a biophysical neural network model of V4 to address these issues. We first constrain our model to reproduce the experimental results obtained for different external stimulus configurations and without paying attention. To reproduce the known neuronal response variability, we found that the neurons should receive about equal, or balanced, levels of excitatory and inhibitory inputs and whose levels are high as they are in in vivo conditions. Next we consider attentional inputs that can induce and reproduce the observed spiking modulations. We also elucidate the role played by the neural network to generate these modulations.

A Biophysical Neural Model To Describe Spatial Visual Attention

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

Hugues, Etienne; Jose, Jorge V.

2008-02-14

Visual scenes have enormous spatial and temporal information that are transduced into neural spike trains. Psychophysical experiments indicate that only a small portion of a spatial image is consciously accessible. Electrophysiological experiments in behaving monkeys have revealed a number of modulations of the neural activity in special visual area known as V4, when the animal is paying attention directly towards a particular stimulus location. The nature of the attentional input to V4, however, remains unknown as well as to the mechanisms responsible for these modulations. We use a biophysical neural network model of V4 to address these issues. We firstmore » constrain our model to reproduce the experimental results obtained for different external stimulus configurations and without paying attention. To reproduce the known neuronal response variability, we found that the neurons should receive about equal, or balanced, levels of excitatory and inhibitory inputs and whose levels are high as they are in in vivo conditions. Next we consider attentional inputs that can induce and reproduce the observed spiking modulations. We also elucidate the role played by the neural network to generate these modulations.« less

Intracranial spectral amplitude dynamics of perceptual suppression in fronto-insular, occipito-temporal, and primary visual cortex

PubMed Central

Vidal, Juan R.; Perrone-Bertolotti, Marcela; Kahane, Philippe; Lachaux, Jean-Philippe

2015-01-01

If conscious perception requires global information integration across active distant brain networks, how does the loss of conscious perception affect neural processing in these distant networks? Pioneering studies on perceptual suppression (PS) described specific local neural network responses in primary visual cortex, thalamus and lateral prefrontal cortex of the macaque brain. Yet the neural effects of PS have rarely been studied with intracerebral recordings outside these cortices and simultaneously across distant brain areas. Here, we combined (1) a novel experimental paradigm in which we produced a similar perceptual disappearance and also re-appearance by using visual adaptation with transient contrast changes, with (2) electrophysiological observations from human intracranial electrodes sampling wide brain areas. We focused on broadband high-frequency (50–150 Hz, i.e., gamma) and low-frequency (8–24 Hz) neural activity amplitude modulations related to target visibility and invisibility. We report that low-frequency amplitude modulations reflected stimulus visibility in a larger ensemble of recording sites as compared to broadband gamma responses, across distinct brain regions including occipital, temporal and frontal cortices. Moreover, the dynamics of the broadband gamma response distinguished stimulus visibility from stimulus invisibility earlier in anterior insula and inferior frontal gyrus than in temporal regions, suggesting a possible role of fronto-insular cortices in top–down processing for conscious perception. Finally, we report that in primary visual cortex only low-frequency amplitude modulations correlated directly with perceptual status. Interestingly, in this sensory area broadband gamma was not modulated during PS but became positively modulated after 300 ms when stimuli were rendered visible again, suggesting that local networks could be ignited by top–down influences during conscious perception. PMID:25642199

Effective connectivity during processing of facial affect: evidence for multiple parallel pathways.

PubMed

Dima, Danai; Stephan, Klaas E; Roiser, Jonathan P; Friston, Karl J; Frangou, Sophia

2011-10-05

The perception of facial affect engages a distributed cortical network. We used functional magnetic resonance imaging and dynamic causal modeling to characterize effective connectivity during explicit (conscious) categorization of affective stimuli in the human brain. Specifically, we examined the modulation of connectivity from posterior regions of the face-processing network to the lateral ventral prefrontal cortex (VPFC) during affective categorization and we tested for a potential role of the amygdala (AMG) in mediating this modulation. We found that explicit processing of facial affect led to prominent modulation (increase) in the effective connectivity from the inferior occipital gyrus (IOG) to the VPFC, while there was less evidence for modulation of the afferent connections from fusiform gyrus and AMG to VPFC. More specifically, the forward connection from IOG to the VPFC exhibited a selective increase under anger (as opposed to fear or sadness). Furthermore, Bayesian model comparison suggested that the modulation of afferent connections to the VPFC was mediated directly by facial affect, as opposed to an indirect modulation mediated by the AMG. Our results thus suggest that affective information is conveyed to the VPFC along multiple parallel pathways and that AMG activity is not sufficient to account for the gating of information transfer to the VPFC during explicit emotional processing.

Episodic memory in aspects of large-scale brain networks

PubMed Central

Jeong, Woorim; Chung, Chun Kee; Kim, June Sic

2015-01-01

Understanding human episodic memory in aspects of large-scale brain networks has become one of the central themes in neuroscience over the last decade. Traditionally, episodic memory was regarded as mostly relying on medial temporal lobe (MTL) structures. However, recent studies have suggested involvement of more widely distributed cortical network and the importance of its interactive roles in the memory process. Both direct and indirect neuro-modulations of the memory network have been tried in experimental treatments of memory disorders. In this review, we focus on the functional organization of the MTL and other neocortical areas in episodic memory. Task-related neuroimaging studies together with lesion studies suggested that specific sub-regions of the MTL are responsible for specific components of memory. However, recent studies have emphasized that connectivity within MTL structures and even their network dynamics with other cortical areas are essential in the memory process. Resting-state functional network studies also have revealed that memory function is subserved by not only the MTL system but also a distributed network, particularly the default-mode network (DMN). Furthermore, researchers have begun to investigate memory networks throughout the entire brain not restricted to the specific resting-state network (RSN). Altered patterns of functional connectivity (FC) among distributed brain regions were observed in patients with memory impairments. Recently, studies have shown that brain stimulation may impact memory through modulating functional networks, carrying future implications of a novel interventional therapy for memory impairment. PMID:26321939

Topological properties of robust biological and computational networks

PubMed Central

Navlakha, Saket; He, Xin; Faloutsos, Christos; Bar-Joseph, Ziv

2014-01-01

Network robustness is an important principle in biology and engineering. Previous studies of global networks have identified both redundancy and sparseness as topological properties used by robust networks. By focusing on molecular subnetworks, or modules, we show that module topology is tightly linked to the level of environmental variability (noise) the module expects to encounter. Modules internal to the cell that are less exposed to environmental noise are more connected and less robust than external modules. A similar design principle is used by several other biological networks. We propose a simple change to the evolutionary gene duplication model which gives rise to the rich range of module topologies observed within real networks. We apply these observations to evaluate and design communication networks that are specifically optimized for noisy or malicious environments. Combined, joint analysis of biological and computational networks leads to novel algorithms and insights benefiting both fields. PMID:24789562

Finding Correlation between Protein Protein Interaction Modules Using Semantic Web Techniques

NASA Astrophysics Data System (ADS)

Kargar, Mehdi; Moaven, Shahrouz; Abolhassani, Hassan

Many complex networks such as social networks and computer show modular structures, where edges between nodes are much denser within modules than between modules. It is strongly believed that cellular networks are also modular, reflecting the relative independence and coherence of different functional units in a cell. In this paper we used a human curated dataset. In this paper we consider each module in the PPI network as ontology. Using techniques in ontology alignment, we compare each pair of modules in the network. We want to see that is there a correlation between the structure of each module or they have totally different structures. Our results show that there is no correlation between proteins in a protein protein interaction network.

Network Medicine: A Network-based Approach to Human Disease

PubMed Central

Barabási, Albert-László; Gulbahce, Natali; Loscalzo, Joseph

2011-01-01

Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction are essential to identify new diseases genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases. PMID:21164525

Modulation of network pacemaker neurons by oxygen at the anaerobic threshold.

PubMed

Hill, Andrew A V; Simmers, John; Meyrand, Pierre; Massabuau, Jean-Charles

2012-07-01

Previous in vitro and in vivo studies showed that the frequency of rhythmic pyloric network activity in the lobster is modulated directly by oxygen partial pressure (PO(2)). We have extended these results by (1) increasing the period of exposure to low PO(2) and by (2) testing the sensitivity of the pyloric network to changes in PO(2) that are within the narrow range normally experienced by the lobster (1 to 6 kPa). We found that the pyloric network rhythm was indeed altered by changes in PO(2) within the range typically observed in vivo. Furthermore, a previous study showed that the lateral pyloric constrictor motor neuron (LP) contributes to the O(2) sensitivity of the pyloric network. Here, we expanded on this idea by testing the hypothesis that pyloric pacemaker neurons also contribute to pyloric O(2) sensitivity. A 2-h exposure to 1 kPa PO(2), which was twice the period used previously, decreased the frequency of an isolated group of pacemaker neurons, suggesting that changes in the rhythmogenic properties of these cells contribute to pyloric O(2) sensitivity during long-term near-anaerobic (anaerobic threshold, 0.7-1.2 kPa) conditions.

Changing Brain Networks Through Non-invasive Neuromodulation

PubMed Central

To, Wing Ting; De Ridder, Dirk; Hart Jr., John; Vanneste, Sven

2018-01-01

Background/Objective: Non-invasive neuromodulation techniques, such as repetitive Transcranial Magnetic Stimulation (rTMS) and transcranial Direct Current Stimulation (tDCS), have increasingly been investigated for their potential as treatments for neurological and psychiatric disorders. Despite widespread dissemination of these techniques, the underlying therapeutic mechanisms and the ideal stimulation site for a given disorder remain unknown. Increasing evidence support the possibility of non-invasive neuromodulation affecting a brain network rather than just the local stimulation target. In this article, we present evidence in a clinical setting to support the idea that non-invasive neuromodulation changes brain networks. Method: This article addresses the idea that non-invasive neuromodulation modulates brain networks, rather than just the local stimulation target, using neuromodulation studies in tinnitus and major depression as examples. We present studies that support this hypothesis from different perspectives. Main Results/Conclusion: Studies stimulating the same brain region, such as the dorsolateral prefrontal cortex (DLPFC), have shown to be effective for several disorders and studies using different stimulation sites for the same disorder have shown similar results. These findings, as well as results from studies investigating brain network connectivity on both macro and micro levels, suggest that non-invasive neuromodulation affects a brain network rather than just the local stimulation site targeted. We propose that non-invasive neuromodulation should be approached from a network perspective and emphasize the therapeutic potential of this approach through the modulation of targeted brain networks. PMID:29706876

Changing Brain Networks Through Non-invasive Neuromodulation.

PubMed

To, Wing Ting; De Ridder, Dirk; Hart, John; Vanneste, Sven

2018-01-01

Background/Objective : Non-invasive neuromodulation techniques, such as repetitive Transcranial Magnetic Stimulation (rTMS) and transcranial Direct Current Stimulation (tDCS), have increasingly been investigated for their potential as treatments for neurological and psychiatric disorders. Despite widespread dissemination of these techniques, the underlying therapeutic mechanisms and the ideal stimulation site for a given disorder remain unknown. Increasing evidence support the possibility of non-invasive neuromodulation affecting a brain network rather than just the local stimulation target. In this article, we present evidence in a clinical setting to support the idea that non-invasive neuromodulation changes brain networks. Method : This article addresses the idea that non-invasive neuromodulation modulates brain networks, rather than just the local stimulation target, using neuromodulation studies in tinnitus and major depression as examples. We present studies that support this hypothesis from different perspectives. Main Results/Conclusion : Studies stimulating the same brain region, such as the dorsolateral prefrontal cortex (DLPFC), have shown to be effective for several disorders and studies using different stimulation sites for the same disorder have shown similar results. These findings, as well as results from studies investigating brain network connectivity on both macro and micro levels, suggest that non-invasive neuromodulation affects a brain network rather than just the local stimulation site targeted. We propose that non-invasive neuromodulation should be approached from a network perspective and emphasize the therapeutic potential of this approach through the modulation of targeted brain networks.

Cellular telephone-based radiation detection instrument

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2011-06-14

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Hypothesis for cognitive effects of transcranial direct current stimulation: Externally- and internally-directed cognition.

PubMed

Greenwood, Pamela M; Blumberg, Eric J; Scheldrup, Melissa R

2018-03-01

A comprehensive explanation is lacking for the broad array of cognitive effects modulated by transcranial direct current stimulation (tDCS). We advanced the testable hypothesis that tDCS to the default mode network (DMN) increases processing of goals and stored information at the expense of external events. We further hypothesized that tDCS to the dorsal attention network (DAN) increases processing of external events at the expense of goals and stored information. A literature search (PsychINFO) identified 42 empirical studies and 3 meta-analyses examining effects of prefrontal and/or parietal tDCS on tasks that selectively required external and/or internal processing. Most, though not all, of the studies that met our search criteria supported our hypothesis. Three meta-analyses supported our hypothesis. The hypothesis we advanced provides a framework for the design and interpretation of results in light of the role of large-scale intrinsic networks that govern attention. Copyright © 2017 Elsevier Ltd. All rights reserved.

Focused transcranial direct current stimulation (tDCS) over the dorsolateral prefrontal cortex modulates specific domains of self-regulation.

PubMed

Pripfl, Jürgen; Lamm, Claus

2015-02-01

Recent neuroscience theories suggest that different kinds of self-regulation may share a common psychobiological mechanism. However, empirical evidence for a domain general self-regulation mechanism is scarce. The aim of this study was to investigate whether focused anodal transcranial direct current stimulation (tDCS), facilitating the activity of the dorsolateral prefrontal cortex (dlPFC), acts on a domain general self-regulation mechanism and thus modulates both affective and appetitive self-regulation. Twenty smokers participated in this within-subject sham controlled study. Effects of anodal left, anodal right and sham tDCS over the dlPFC on affective picture appraisal and nicotine craving-cue appraisal were assessed. Anodal right tDCS over the dlPFC reduced negative affect in emotion appraisal, but neither modulated regulation of positive emotion appraisal nor of craving appraisal. Anodal left stimulation did not induce any significant effects. The results of our study show that domain specific self-regulation networks are at work in the prefrontal cortex. Focused tDCS modulation of this specific self-regulation network could probably be used during the first phase of nicotine abstinence, during which negative affect might easily result in relapse. These findings have implications for neuroscience models of self-regulation and are of relevance for the development of brain stimulation based treatment methods for neuropsychiatric disorders associated with self-regulation deficits. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Metastability and Inter-Band Frequency Modulation in Networks of Oscillating Spiking Neuron Populations

PubMed Central

Bhowmik, David; Shanahan, Murray

2013-01-01

Groups of neurons firing synchronously are hypothesized to underlie many cognitive functions such as attention, associative learning, memory, and sensory selection. Recent theories suggest that transient periods of synchronization and desynchronization provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in different structures and interacting with each other. This paper explores inter-band frequency modulation between neural oscillators using models of quadratic integrate-and-fire neurons and Hodgkin-Huxley neurons. We vary the structural connectivity in a network of neural oscillators, assess the spectral complexity, and correlate the inter-band frequency modulation. We contrast this correlation against measures of metastable coalition entropy and synchrony. Our results show that oscillations in different neural populations modulate each other so as to change frequency, and that the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Further to this, we locate an area in the connectivity space in which the system directs itself in this way so as to explore a large repertoire of synchronous coalitions. We suggest that such dynamics facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby supports sophisticated cognitive processing in the brain. PMID:23614040

Bayesian module identification from multiple noisy networks.

PubMed

Zamani Dadaneh, Siamak; Qian, Xiaoning

2016-12-01

Module identification has been studied extensively in order to gain deeper understanding of complex systems, such as social networks as well as biological networks. Modules are often defined as groups of vertices in these networks that are topologically cohesive with similar interaction patterns with the rest of the vertices. Most of the existing module identification algorithms assume that the given networks are faithfully measured without errors. However, in many real-world applications, for example, when analyzing protein-protein interaction networks from high-throughput profiling techniques, there is significant noise with both false positive and missing links between vertices. In this paper, we propose a new model for more robust module identification by taking advantage of multiple observed networks with significant noise so that signals in multiple networks can be strengthened and help improve the solution quality by combining information from various sources. We adopt a hierarchical Bayesian model to integrate multiple noisy snapshots that capture the underlying modular structure of the networks under study. By introducing a latent root assignment matrix and its relations to instantaneous module assignments in all the observed networks to capture the underlying modular structure and combine information across multiple networks, an efficient variational Bayes algorithm can be derived to accurately and robustly identify the underlying modules from multiple noisy networks. Experiments on synthetic and protein-protein interaction data sets show that our proposed model enhances both the accuracy and resolution in detecting cohesive modules, and it is less vulnerable to noise in the observed data. In addition, it shows higher power in predicting missing edges compared to individual-network methods.

Modulation of hippocampal rhythms by subthreshold electric fields and network topology

PubMed Central

Berzhanskaya, Julia; Chernyy, Nick; Gluckman, Bruce J.; Schiff, Steven J.; Ascoli, Giorgio A.

2012-01-01

Theta (4–12 Hz) and gamma (30–80 Hz) rhythms are considered important for cortical and hippocampal function. Although several neuron types are implicated in rhythmogenesis, the exact cellular mechanisms remain unknown. Subthreshold electric fields provide a flexible, area-specific tool to modulate neural activity and directly test functional hypotheses. Here we present experimental and computational evidence of the interplay among hippocampal synaptic circuitry, neuronal morphology, external electric fields, and network activity. Electrophysiological data are used to constrain and validate an anatomically and biophysically realistic model of area CA1 containing pyramidal cells and two interneuron types: dendritic- and perisomatic-targeting. We report two lines of results: addressing the network structure capable of generating theta-modulated gamma rhythms, and demonstrating electric field effects on those rhythms. First, theta-modulated gamma rhythms require specific inhibitory connectivity. In one configuration, GABAergic axo-dendritic feedback on pyramidal cells is only effective in proximal but not distal layers. An alternative configuration requires two distinct perisomatic interneuron classes, one exclusively receiving excitatory contacts, the other additionally targeted by inhibition. These observations suggest novel roles for particular classes of oriens and basket cells. The second major finding is that subthreshold electric fields robustly alter the balance between different rhythms. Independent of network configuration, positive electric fields decrease, while negative fields increase the theta/gamma ratio. Moreover, electric fields differentially affect average theta frequency depending on specific synaptic connectivity. These results support the testable prediction that subthreshold electric fields can alter hippocampal rhythms, suggesting new approaches to explore their cognitive functions and underlying circuitry. PMID:23053863

Bridging the gap between modules in isolation and as part of networks: A systems framework for elucidating interaction and regulation of signalling modules

NASA Astrophysics Data System (ADS)

Menon, Govind; Krishnan, J.

2016-07-01

While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks.

Bridging the gap between modules in isolation and as part of networks: A systems framework for elucidating interaction and regulation of signalling modules.

PubMed

Menon, Govind; Krishnan, J

2016-07-21

While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks.

Solving Constraint-Satisfaction Problems with Distributed Neocortical-Like Neuronal Networks.

PubMed

Rutishauser, Ueli; Slotine, Jean-Jacques; Douglas, Rodney J

2018-05-01

Finding actions that satisfy the constraints imposed by both external inputs and internal representations is central to decision making. We demonstrate that some important classes of constraint satisfaction problems (CSPs) can be solved by networks composed of homogeneous cooperative-competitive modules that have connectivity similar to motifs observed in the superficial layers of neocortex. The winner-take-all modules are sparsely coupled by programming neurons that embed the constraints onto the otherwise homogeneous modular computational substrate. We show rules that embed any instance of the CSP's planar four-color graph coloring, maximum independent set, and sudoku on this substrate and provide mathematical proofs that guarantee these graph coloring problems will convergence to a solution. The network is composed of nonsaturating linear threshold neurons. Their lack of right saturation allows the overall network to explore the problem space driven through the unstable dynamics generated by recurrent excitation. The direction of exploration is steered by the constraint neurons. While many problems can be solved using only linear inhibitory constraints, network performance on hard problems benefits significantly when these negative constraints are implemented by nonlinear multiplicative inhibition. Overall, our results demonstrate the importance of instability rather than stability in network computation and offer insight into the computational role of dual inhibitory mechanisms in neural circuits.

Evaluation of Earthquake Detection Performance in Terms of Quality and Speed in SEISCOMP3 Using New Modules Qceval, Npeval and Sceval

NASA Astrophysics Data System (ADS)

Roessler, D.; Weber, B.; Ellguth, E.; Spazier, J.

2017-12-01

The geometry of seismic monitoring networks, site conditions and data availability as well as monitoring targets and strategies typically impose trade-offs between data quality, earthquake detection sensitivity, false detections and alert times. Network detection capabilities typically change with alteration of the seismic noise level by human activity or by varying weather and sea conditions. To give helpful information to operators and maintenance coordinators, gempa developed a range of tools to evaluate earthquake detection and network performance including qceval, npeval and sceval. qceval is a module which analyzes waveform quality parameters in real-time and deactivates and reactivates data streams based on waveform quality thresholds for automatic processing. For example, thresholds can be defined for latency, delay, timing quality, spikes and gaps count and rms. As changes in the automatic processing have a direct influence on detection quality and speed, another tool called "npeval" was designed to calculate in real-time the expected time needed to detect and locate earthquakes by evaluating the effective network geometry. The effective network geometry is derived from the configuration of stations participating in the detection. The detection times are shown as an additional layer on the map and updated in real-time as soon as the effective network geometry changes. Yet another new tool, "sceval", is an automatic module which classifies located seismic events (Origins) in real-time. sceval evaluates the spatial distribution of the stations contributing to an Origin. It confirms or rejects the status of Origins, adds comments or leaves the Origin unclassified. The comments are passed to an additional sceval plug-in where the end user can customize event types. This unique identification of real and fake events in earthquake catalogues allows to lower network detection thresholds. In real-time monitoring situations operators can limit the processing to events with unclassified Origins, reducing their workload. Classified Origins can be treated specifically by other procedures. These modules have been calibrated and fully tested by several complex seismic monitoring networks in the region of Indonesia and Northern Chile.

Signaling networks in joint development

PubMed Central

Salva, Joanna E.; Merrill, Amy E.

2016-01-01

Here we review studies identifying regulatory networks responsible for synovial, cartilaginous, and fibrous joint development. Synovial joints, characterized by the fluid-filled synovial space between the bones, are found in high-mobility regions and are the most common type of joint. Cartilaginous joints unite adjacent bones through either a hyaline cartilage or fibrocartilage intermediate. Fibrous joints, which include the cranial sutures, form a direct union between bones through fibrous connective tissue. We describe how the distinct morphologic and histogenic characteristics of these joint classes are established during embryonic development. Collectively, these studies reveal that despite the heterogeneity of joint strength and mobility, joint development throughout the skeleton utilizes common signaling networks via long-range morphogen gradients and direct cell-cell contact. This suggests that different joint types represent specialized variants of homologous developmental modules. Identifying the unifying aspects of the signaling networks between joint classes allows a more complete understanding of the signaling code for joint formation, which is critical to improving strategies for joint regeneration and repair. PMID:27859991

Network-Assisted Investigation of Combined Causal Signals from Genome-Wide Association Studies in Schizophrenia

PubMed Central

Jia, Peilin; Wang, Lily; Fanous, Ayman H.; Pato, Carlos N.; Edwards, Todd L.; Zhao, Zhongming

2012-01-01

With the recent success of genome-wide association studies (GWAS), a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P meta<1×10−4, including the gene HLA-DQA1 located in the MHC region on chromosome 6, which was reported in previous studies using the largest cohort of schizophrenia patients to date. These results demonstrated our bi-directional network-based strategy is efficient for identifying disease-associated genes with modest signals in GWAS datasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available. PMID:22792057

The Drosophila transcriptional network is structured by microbiota.

PubMed

Dobson, Adam J; Chaston, John M; Douglas, Angela E

2016-11-25

Resident microorganisms (microbiota) have far-reaching effects on the biology of their animal hosts, with major consequences for the host's health and fitness. A full understanding of microbiota-dependent gene regulation requires analysis of the overall architecture of the host transcriptome, by identifying suites of genes that are expressed synchronously. In this study, we investigated the impact of the microbiota on gene coexpression in Drosophila. Our transcriptomic analysis, of 17 lines representative of the global genetic diversity of Drosophila, yielded a total of 11 transcriptional modules of co-expressed genes. For seven of these modules, the strength of the transcriptional network (defined as gene-gene coexpression) differed significantly between flies bearing a defined gut microbiota (gnotobiotic flies) and flies reared under microbiologically sterile conditions (axenic flies). Furthermore, gene coexpression was uniformly stronger in these microbiota-dependent modules than in both the microbiota-independent modules in gnotobiotic flies and all modules in axenic flies, indicating that the presence of the microbiota directs gene regulation in a subset of the transcriptome. The genes constituting the microbiota-dependent transcriptional modules include regulators of growth, metabolism and neurophysiology, previously implicated in mediating phenotypic effects of microbiota on Drosophila phenotype. Together these results provide the first evidence that the microbiota enhances the coexpression of specific and functionally-related genes relative to the animal's intrinsic baseline level of coexpression. Our system-wide analysis demonstrates that the presence of microbiota enhances gene coexpression, thereby structuring the transcriptional network in the animal host. This finding has potentially major implications for understanding of the mechanisms by which microbiota affect host health and fitness, and the ways in which hosts and their resident microbiota coevolve.

Dismissing Attachment Characteristics Dynamically Modulate Brain Networks Subserving Social Aversion.

PubMed

Krause, Anna Linda; Borchardt, Viola; Li, Meng; van Tol, Marie-José; Demenescu, Liliana Ramona; Strauss, Bernhard; Kirchmann, Helmut; Buchheim, Anna; Metzger, Coraline D; Nolte, Tobias; Walter, Martin

2016-01-01

Attachment patterns influence actions, thoughts and feeling through a person's "inner working model". Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest functional magnetic resonance imaging (fMRI)-experiment, presenting auditory narratives prototypical of dismissing attachment representations to investigate their effect on 23 healthy males. We then examined effects of participants' attachment style and childhood trauma on brain state changes using seed-based functional connectivity (FC) analyses, and finally tested whether subjective differences in responsivity to narratives could be predicted by baseline network states. In comparison to a baseline state, we observed increased FC in a previously described "social aversion network" including dorsal anterior cingulated cortex (dACC) and left anterior middle temporal gyrus (aMTG) specifically after exposure to insecure-dismissing attachment narratives. Increased dACC-seeded FC within the social aversion network was positively related to the participants' avoidant attachment style and presence of a history of childhood trauma. Anxious attachment style on the other hand was positively correlated with FC between the dACC and a region outside of the "social aversion network", namely the dorsolateral prefrontal cortex, which suggests decreased network segregation as a function of anxious attachment. Finally, the extent of subjective experience of friendliness towards the dismissing narrative was predicted by low baseline FC-values between hippocampus and inferior parietal lobule (IPL). Taken together, our study demonstrates an activation of networks related to social aversion in terms of increased connectivity after listening to insecure-dismissing attachment narratives. A causal interrelation of brain state changes and subsequent changes in social reactivity was further supported by our observation of direct prediction of neuronal responses by individual attachment and trauma characteristics and reversely prediction of subjective experience by intrinsic functional connections. We consider these findings of activation of within-network and between-network connectivity modulated by inter-individual differences as substantial for the understanding of interpersonal processes, particularly in clinical settings.

Disentangling the co-structure of multilayer interaction networks: degree distribution and module composition in two-layer bipartite networks.

PubMed

Astegiano, Julia; Altermatt, Florian; Massol, François

2017-11-13

Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how biodiversity loss may affect the persistence of multispecies assemblages. Existing methods to analyse multilayer networks often fail to consider network co-structure. We present a new method to evaluate the modular co-structure of multilayer networks through the assessment of species degree co-distribution and network module composition. We focus on modular structure because of its high prevalence among ecological networks. We apply our method to two Lepidoptera-plant networks, one describing caterpillar-plant herbivory interactions and one representing adult Lepidoptera nectaring on flowers, thereby possibly pollinating them. More than 50% of the species established either herbivory or visitation interactions, but not both. These species were over-represented among plants and lepidopterans, and were present in most modules in both networks. Similarity in module composition between networks was high but not different from random expectations. Our method clearly delineates the importance of interpreting multilayer module composition similarity in the light of the constraints imposed by network structure to predict the potential indirect effects of species loss through interconnected modular networks.

Information processing architecture of functionally defined clusters in the macaque cortex.

PubMed

Shen, Kelly; Bezgin, Gleb; Hutchison, R Matthew; Gati, Joseph S; Menon, Ravi S; Everling, Stefan; McIntosh, Anthony R

2012-11-28

Computational and empirical neuroimaging studies have suggested that the anatomical connections between brain regions primarily constrain their functional interactions. Given that the large-scale organization of functional networks is determined by the temporal relationships between brain regions, the structural limitations may extend to the global characteristics of functional networks. Here, we explored the extent to which the functional network community structure is determined by the underlying anatomical architecture. We directly compared macaque (Macaca fascicularis) functional connectivity (FC) assessed using spontaneous blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) to directed anatomical connectivity derived from macaque axonal tract tracing studies. Consistent with previous reports, FC increased with increasing strength of anatomical connection, and FC was also present between regions that had no direct anatomical connection. We observed moderate similarity between the FC of each region and its anatomical connectivity. Notably, anatomical connectivity patterns, as described by structural motifs, were different within and across functional modules: partitioning of the functional network was supported by dense bidirectional anatomical connections within clusters and unidirectional connections between clusters. Together, our data directly demonstrate that the FC patterns observed in resting-state BOLD-fMRI are dictated by the underlying neuroanatomical architecture. Importantly, we show how this architecture contributes to the global organizational principles of both functional specialization and integration.

CUFID-query: accurate network querying through random walk based network flow estimation.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2017-12-28

Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive performance evaluation based on biological networks with known functional modules, we show that CUFID-query outperforms the existing state-of-the-art algorithms in terms of prediction accuracy and biological significance of the predictions.

An Integrated Simulation Module for Cyber-Physical Automation Systems †

PubMed Central

Ferracuti, Francesco; Freddi, Alessandro; Monteriù, Andrea; Prist, Mariorosario

2016-01-01

The integration of Wireless Sensors Networks (WSNs) into Cyber Physical Systems (CPSs) is an important research problem to solve in order to increase the performances, safety, reliability and usability of wireless automation systems. Due to the complexity of real CPSs, emulators and simulators are often used to replace the real control devices and physical connections during the development stage. The most widespread simulators are free, open source, expandable, flexible and fully integrated into mathematical modeling tools; however, the connection at a physical level and the direct interaction with the real process via the WSN are only marginally tackled; moreover, the simulated wireless sensor motes are not able to generate the analogue output typically required for control purposes. A new simulation module for the control of a wireless cyber-physical system is proposed in this paper. The module integrates the COntiki OS JAva Simulator (COOJA), a cross-level wireless sensor network simulator, and the LabVIEW system design software from National Instruments. The proposed software module has been called “GILOO” (Graphical Integration of Labview and cOOja). It allows one to develop and to debug control strategies over the WSN both using virtual or real hardware modules, such as the National Instruments Real-Time Module platform, the CompactRio, the Supervisory Control And Data Acquisition (SCADA), etc. To test the proposed solution, we decided to integrate it with one of the most popular simulators, i.e., the Contiki OS, and wireless motes, i.e., the Sky mote. As a further contribution, the Contiki Sky DAC driver and a new “Advanced Sky GUI” have been proposed and tested in the COOJA Simulator in order to provide the possibility to develop control over the WSN. To test the performances of the proposed GILOO software module, several experimental tests have been made, and interesting preliminary results are reported. The GILOO module has been applied to a smart home mock-up where a networked control has been developed for the LED lighting system. PMID:27164109

An Integrated Simulation Module for Cyber-Physical Automation Systems.

PubMed

Ferracuti, Francesco; Freddi, Alessandro; Monteriù, Andrea; Prist, Mariorosario

2016-05-05

The integration of Wireless Sensors Networks (WSNs) into Cyber Physical Systems (CPSs) is an important research problem to solve in order to increase the performances, safety, reliability and usability of wireless automation systems. Due to the complexity of real CPSs, emulators and simulators are often used to replace the real control devices and physical connections during the development stage. The most widespread simulators are free, open source, expandable, flexible and fully integrated into mathematical modeling tools; however, the connection at a physical level and the direct interaction with the real process via the WSN are only marginally tackled; moreover, the simulated wireless sensor motes are not able to generate the analogue output typically required for control purposes. A new simulation module for the control of a wireless cyber-physical system is proposed in this paper. The module integrates the COntiki OS JAva Simulator (COOJA), a cross-level wireless sensor network simulator, and the LabVIEW system design software from National Instruments. The proposed software module has been called "GILOO" (Graphical Integration of Labview and cOOja). It allows one to develop and to debug control strategies over the WSN both using virtual or real hardware modules, such as the National Instruments Real-Time Module platform, the CompactRio, the Supervisory Control And Data Acquisition (SCADA), etc. To test the proposed solution, we decided to integrate it with one of the most popular simulators, i.e., the Contiki OS, and wireless motes, i.e., the Sky mote. As a further contribution, the Contiki Sky DAC driver and a new "Advanced Sky GUI" have been proposed and tested in the COOJA Simulator in order to provide the possibility to develop control over the WSN. To test the performances of the proposed GILOO software module, several experimental tests have been made, and interesting preliminary results are reported. The GILOO module has been applied to a smart home mock-up where a networked control has been developed for the LED lighting system.

Is a Responsive Default Mode Network Required for Successful Working Memory Task Performance?

PubMed

Čeko, Marta; Gracely, John L; Fitzcharles, Mary-Ann; Seminowicz, David A; Schweinhardt, Petra; Bushnell, M Catherine

2015-08-19

In studies of cognitive processing using tasks with externally directed attention, regions showing increased (external-task-positive) and decreased or "negative" [default-mode network (DMN)] fMRI responses during task performance are dynamically responsive to increasing task difficulty. Responsiveness (modulation of fMRI signal by increasing load) has been linked directly to successful cognitive task performance in external-task-positive regions but not in DMN regions. To investigate whether a responsive DMN is required for successful cognitive performance, we compared healthy human subjects (n = 23) with individuals shown to have decreased DMN engagement (chronic pain patients, n = 28). Subjects performed a multilevel working-memory task (N-back) during fMRI. If a responsive DMN is required for successful performance, patients having reduced DMN responsiveness should show worsened performance; if performance is not reduced, their brains should show compensatory activation in external-task-positive regions or elsewhere. All subjects showed decreased accuracy and increased reaction times with increasing task level, with no significant group differences on either measure at any level. Patients had significantly reduced negative fMRI response (deactivation) of DMN regions (posterior cingulate/precuneus, medial prefrontal cortex). Controls showed expected modulation of DMN deactivation with increasing task difficulty. Patients showed significantly reduced modulation of DMN deactivation by task difficulty, despite their successful task performance. We found no evidence of compensatory neural recruitment in external-task-positive regions or elsewhere. Individual responsiveness of the external-task-positive ventrolateral prefrontal cortex, but not of DMN regions, correlated with task accuracy. These findings suggest that a responsive DMN may not be required for successful cognitive performance; a responsive external-task-positive network may be sufficient. We studied the relationship between responsiveness of the brain to increasing task demand and successful cognitive performance, using chronic pain patients as a probe. fMRI working memory studies show that two main cognitive networks ["external-task positive" and "default-mode network" (DMN)] are responsive to increasing task difficulty. The responsiveness of both of these brain networks is suggested to be required for successful task performance. The responsiveness of external-task-positive regions has been linked directly to successful cognitive task performance, as we also show here. However, pain patients show decreased engagement and responsiveness of the DMN but can perform a working memory task as well as healthy subjects, without demonstrable compensatory neural recruitment. Therefore, a responsive DMN might not be needed for successful cognitive performance. Copyright © 2015 the authors 0270-6474/15/3511596-11$15.00/0.

Interaction of multiple networks modulated by the working memory training based on real-time fMRI

NASA Astrophysics Data System (ADS)

Shen, Jiahui; Zhang, Gaoyan; Zhu, Chaozhe; Yao, Li; Zhao, Xiaojie

2015-03-01

Neuroimaging studies of working memory training have identified the alteration of brain activity as well as the regional interactions within the functional networks such as central executive network (CEN) and default mode network (DMN). However, how the interaction within and between these multiple networks is modulated by the training remains unclear. In this paper, we examined the interaction of three training-induced brain networks during working memory training based on real-time functional magnetic resonance imaging (rtfMRI). Thirty subjects assigned to the experimental and control group respectively participated in two times training separated by seven days. Three networks including silence network (SN), CEN and DMN were identified by the training data with the calculated function connections within each network. Structural equation modeling (SEM) approach was used to construct the directional connectivity patterns. The results showed that the causal influences from the percent signal changes of target ROI to the SN were positively changed in both two groups, as well as the causal influence from the SN to CEN was positively changed in experimental group but negatively changed in control group from the SN to DMN. Further correlation analysis of the changes in each network with the behavioral improvements showed that the changes in SN were stronger positively correlated with the behavioral improvement of letter memory task. These findings indicated that the SN was not only a switch between the target ROI and the other networks in the feedback training but also an essential factor to the behavioral improvement.

Characterization of submillisecond response optical addressing phase modulator based on low light scattering polymer network liquid crystal

NASA Astrophysics Data System (ADS)

Xiangjie, Zhao; Cangli, Liu; Jiazhu, Duan; Dayong, Zhang; Yongquan, Luo

2015-01-01

Optically addressed conventional nematic liquid crystal spatial light modulator has attracted wide research interests. But the slow response speed limited its further application. In this paper, polymer network liquid crystal (PNLC) was proposed to replace the conventional nematic liquid crystal to enhance the response time to the order of submillisecond. The maximum light scattering of the employed PNLC was suppressed to be less than 2% at 1.064 μm by optimizing polymerization conditions and selecting large viscosity liquid crystal as solvent. The occurrence of phase ripple phenomenon due to electron diffusion and drift in photoconductor was found to deteriorate the phase modulation effect of the optical addressed PNLC phase modulator. The wavelength effect and AC voltage frequency effect on the on state dynamic response of phase change was investigated by experimental methods. These effects were interpreted by electron diffusion and drift theory based on the assumption that free electron was inhomogeneously distributed in accordance with the writing beam intensity distribution along the incident direction. The experimental results indicated that the phase ripple could be suppressed by optimizing the wavelength of the writing beam and the driving AC voltage frequency when varying the writing beam intensity to generate phase change in 2π range. The modulation transfer function was also measured.

Transcranial Direct Current Stimulation Targeting Primary Motor Versus Dorsolateral Prefrontal Cortices: Proof-of-Concept Study Investigating Functional Connectivity of Thalamocortical Networks Specific to Sensory-Affective Information Processing.

PubMed

Sankarasubramanian, Vishwanath; Cunningham, David A; Potter-Baker, Kelsey A; Beall, Erik B; Roelle, Sarah M; Varnerin, Nicole M; Machado, Andre G; Jones, Stephen E; Lowe, Mark J; Plow, Ela B

2017-04-01

The pain matrix is comprised of an extensive network of brain structures involved in sensory and/or affective information processing. The thalamus is a key structure constituting the pain matrix. The thalamus serves as a relay center receiving information from multiple ascending pathways and relating information to and from multiple cortical areas. However, it is unknown how thalamocortical networks specific to sensory-affective information processing are functionally integrated. Here, in a proof-of-concept study in healthy humans, we aimed to understand this connectivity using transcranial direct current stimulation (tDCS) targeting primary motor (M1) or dorsolateral prefrontal cortices (DLPFC). We compared changes in functional connectivity (FC) with DLPFC tDCS to changes in FC with M1 tDCS. FC changes were also compared to further investigate its relation with individual's baseline experience of pain. We hypothesized that resting-state FC would change based on tDCS location and would represent known thalamocortical networks. Ten right-handed individuals received a single application of anodal tDCS (1 mA, 20 min) to right M1 and DLPFC in a single-blind, sham-controlled crossover study. FC changes were studied between ventroposterolateral (VPL), the sensory nucleus of thalamus, and cortical areas involved in sensory information processing and between medial dorsal (MD), the affective nucleus, and cortical areas involved in affective information processing. Individual's perception of pain at baseline was assessed using cutaneous heat pain stimuli. We found that anodal M1 tDCS and anodal DLPFC tDCS both increased FC between VPL and sensorimotor cortices, although FC effects were greater with M1 tDCS. Similarly, anodal M1 tDCS and anodal DLPFC tDCS both increased FC between MD and motor cortices, but only DLPFC tDCS modulated FC between MD and affective cortices, like DLPFC. Our findings suggest that M1 stimulation primarily modulates FC of sensory networks, whereas DLPFC stimulation modulates FC of both sensory and affective networks. Our findings when replicated in a larger group of individuals could provide useful evidence that may inform future studies on pain to differentiate between effects of M1 and DLPFC stimulation. Notably, our finding that individuals with high baseline pain thresholds experience greater FC changes with DLPFC tDCS implies the role of DLPFC in pain modulation, particularly pain tolerance.

Transcranial Direct Current Stimulation Targeting Primary Motor Versus Dorsolateral Prefrontal Cortices: Proof-of-Concept Study Investigating Functional Connectivity of Thalamocortical Networks Specific to Sensory-Affective Information Processing

PubMed Central

Sankarasubramanian, Vishwanath; Cunningham, David A.; Potter-Baker, Kelsey A.; Beall, Erik B.; Roelle, Sarah M.; Varnerin, Nicole M.; Machado, Andre G.; Jones, Stephen E.; Lowe, Mark J.

2017-01-01

Abstract The pain matrix is comprised of an extensive network of brain structures involved in sensory and/or affective information processing. The thalamus is a key structure constituting the pain matrix. The thalamus serves as a relay center receiving information from multiple ascending pathways and relating information to and from multiple cortical areas. However, it is unknown how thalamocortical networks specific to sensory-affective information processing are functionally integrated. Here, in a proof-of-concept study in healthy humans, we aimed to understand this connectivity using transcranial direct current stimulation (tDCS) targeting primary motor (M1) or dorsolateral prefrontal cortices (DLPFC). We compared changes in functional connectivity (FC) with DLPFC tDCS to changes in FC with M1 tDCS. FC changes were also compared to further investigate its relation with individual's baseline experience of pain. We hypothesized that resting-state FC would change based on tDCS location and would represent known thalamocortical networks. Ten right-handed individuals received a single application of anodal tDCS (1 mA, 20 min) to right M1 and DLPFC in a single-blind, sham-controlled crossover study. FC changes were studied between ventroposterolateral (VPL), the sensory nucleus of thalamus, and cortical areas involved in sensory information processing and between medial dorsal (MD), the affective nucleus, and cortical areas involved in affective information processing. Individual's perception of pain at baseline was assessed using cutaneous heat pain stimuli. We found that anodal M1 tDCS and anodal DLPFC tDCS both increased FC between VPL and sensorimotor cortices, although FC effects were greater with M1 tDCS. Similarly, anodal M1 tDCS and anodal DLPFC tDCS both increased FC between MD and motor cortices, but only DLPFC tDCS modulated FC between MD and affective cortices, like DLPFC. Our findings suggest that M1 stimulation primarily modulates FC of sensory networks, whereas DLPFC stimulation modulates FC of both sensory and affective networks. Our findings when replicated in a larger group of individuals could provide useful evidence that may inform future studies on pain to differentiate between effects of M1 and DLPFC stimulation. Notably, our finding that individuals with high baseline pain thresholds experience greater FC changes with DLPFC tDCS implies the role of DLPFC in pain modulation, particularly pain tolerance. PMID:28142257

Implementation of orthogonal frequency division multiplexing (OFDM) and advanced signal processing for elastic optical networking in accordance with networking and transmission constraints

NASA Astrophysics Data System (ADS)

Johnson, Stanley

An increasing adoption of digital signal processing (DSP) in optical fiber telecommunication has brought to the fore several interesting DSP enabled modulation formats. One such format is orthogonal frequency division multiplexing (OFDM), which has seen great success in wireless and wired RF applications, and is being actively investigated by several research groups for use in optical fiber telecom. In this dissertation, I present three implementations of OFDM for elastic optical networking and distributed network control. The first is a field programmable gate array (FPGA) based real-time implementation of a version of OFDM conventionally known as intensity modulation and direct detection (IMDD) OFDM. I experimentally demonstrate the ability of this transmission system to dynamically adjust bandwidth and modulation format to meet networking constraints in an automated manner. To the best of my knowledge, this is the first real-time software defined networking (SDN) based control of an OFDM system. In the second OFDM implementation, I experimentally demonstrate a novel OFDM transmission scheme that supports both direct detection and coherent detection receivers simultaneously using the same OFDM transmitter. This interchangeable receiver solution enables a trade-off between bit rate and equipment cost in network deployment and upgrades. I show that the proposed transmission scheme can provide a receiver sensitivity improvement of up to 1.73 dB as compared to IMDD OFDM. I also present two novel polarization analyzer based detection schemes, and study their performance using experiment and simulation. In the third implementation, I present an OFDM pilot-tone based scheme for distributed network control. The first instance of an SDN-based OFDM elastic optical network with pilot-tone assisted distributed control is demonstrated. An improvement in spectral efficiency and a fast reconfiguration time of 30 ms have been achieved in this experiment. Finally, I experimentally demonstrate optical re-timing of a 10.7 Gb/s data stream utilizing the property of bound soliton pairs (or "soliton molecules") to relax to an equilibrium temporal separation after propagation through a nonlinear dispersion alternating fiber span. Pulses offset up to 16 ps from bit center are successfully re-timed. The optical re-timing scheme studied here is a good example of signal processing in the optical domain and such a technique can overcome the bandwidth bottleneck present in DSP. An enhanced version of this re-timing scheme is analyzed using numerical simulations.

Network Medicine: From Cellular Networks to the Human Diseasome

NASA Astrophysics Data System (ADS)

Barabasi, Albert-Laszlo

2014-03-01

Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The tools of network science offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction not only enrich our understanding of complex systems, but are also essential to identify new disease genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases.

Spherical transceivers for ultrafast optical wireless communications

NASA Astrophysics Data System (ADS)

Jin, Xian; Hristovski, Blago A.; Collier, Christopher M.; Geoffroy-Gagnon, Simon; Born, Brandon; Holzman, Jonathan F.

2016-02-01

Optical wireless communications (OWC) offers the potential for high-speed and mobile operation in indoor networks. Such OWC systems often employ a fixed transmitter grid and mobile transceivers, with the mobile transceivers carrying out bi-directional communication via active downlinks (ideally with high-speed signal detection) and passive uplinks (ideally with broad angular retroreflection and high-speed modulation). It can be challenging to integrate all of these bidirectional communication capabilities within the mobile transceivers, however, as there is a simultaneous desire for compact packaging. With this in mind, the work presented here introduces a new form of transceiver for bi-directional OWC systems. The transceiver incorporates radial photoconductive switches (for high-speed signal detection) and a spherical retro-modulator (for broad angular retroreflection and high-speed all-optical modulation). All-optical retromodulation are investigated by way of theoretical models and experimental testing, for spherical retro-modulators comprised of three glasses, N-BK7, N-LASF9, and S-LAH79, having differing levels of refraction and nonlinearity. It is found that the spherical retro-modulator comprised of S-LAH79, with a refractive index of n ≍ 2 and a Kerr nonlinear index of n2 ≍ (1.8 ± 0.1) × 10-15 cm2/W, yields both broad angular retroreflection (over a solid angle of 2π steradians) and ultrafast modulation (over a duration of 120 fs). Such transceivers can become important elements for all-optical implementations in future bi-directional OWC systems.

Dopaminergic modulation of semantic priming in healthy volunteers.

PubMed

Roesch-Ely, Daniela; Weiland, Stephan; Scheffel, Hans; Schwaninger, Markus; Hundemer, Hans-Peter; Kolter, Thomas; Weisbrod, Matthias

2006-09-15

Semantic priming is a function related to prefrontal cortical (PFC) networks and is lateralized. There is evidence that semantic priming underlies dopaminergic modulation. It is known that the D1-receptor is more abundant in prefrontal networks; however, until now there have been no studies investigating the selective modulation of semantic priming with dopamine agonists. Furthermore, D1 receptor dysfunction has been described in schizophrenia, and patients with formal thought disorder seem to have disturbed focusing of associations and increased indirect priming. With a subtraction design, we compared the influence of pergolide (D1/D2 agonist) with bromocriptine (D2 agonist) and placebo, in a randomized, double-blind, crossover design in 40 healthy male volunteers. Subjects performed a lateralized lexical decision task including direct and indirect related prime-target pairs (stimulus onset asynchrony = 750 msec). Only on pergolide a decrease of the indirect priming in the left hemisphere presentations was found. These findings point to a potential selective modulation of agonists with a D1 component on the focusing of semantic associations. The clinical relevance of this study is that it might help the development of therapeutic strategies for treating cognitive deficits in schizophrenia and Parkinson's disease, which are highly relevant to the functional outcome.

Evidence of Rentian Scaling of Functional Modules in Diverse Biological Networks.

PubMed

How, Javier J; Navlakha, Saket

2018-06-12

Biological networks have long been known to be modular, containing sets of nodes that are highly connected internally. Less emphasis, however, has been placed on understanding how intermodule connections are distributed within a network. Here, we borrow ideas from engineered circuit design and study Rentian scaling, which states that the number of external connections between nodes in different modules is related to the number of nodes inside the modules by a power-law relationship. We tested this property in a broad class of molecular networks, including protein interaction networks for six species and gene regulatory networks for 41 human and 25 mouse cell types. Using evolutionarily defined modules corresponding to known biological processes in the cell, we found that all networks displayed Rentian scaling with a broad range of exponents. We also found evidence for Rentian scaling in functional modules in the Caenorhabditis elegans neural network, but, interestingly, not in three different social networks, suggesting that this property does not inevitably emerge. To understand how such scaling may have arisen evolutionarily, we derived a new graph model that can generate Rentian networks given a target Rent exponent and a module decomposition as inputs. Overall, our work uncovers a new principle shared by engineered circuits and biological networks.

Synaptic Effects of Electric Fields

NASA Astrophysics Data System (ADS)

Rahman, Asif

Learning and sensory processing in the brain relies on the effective transmission of information across synapses. The strength and efficacy of synaptic transmission is modifiable through training and can be modulated with noninvasive electrical brain stimulation. Transcranial electrical stimulation (TES), specifically, induces weak intensity and spatially diffuse electric fields in the brain. Despite being weak, electric fields modulate spiking probability and the efficacy of synaptic transmission. These effects critically depend on the direction of the electric field relative to the orientation of the neuron and on the level of endogenous synaptic activity. TES has been used to modulate a wide range of neuropsychiatric indications, for various rehabilitation applications, and cognitive performance in diverse tasks. How can a weak and diffuse electric field, which simultaneously polarizes neurons across the brain, have precise changes in brain function? Designing therapies to maximize desired outcomes and minimize undesired effects presents a challenging problem. A series of experiments and computational models are used to define the anatomical and functional factors leading to specificity of TES. Anatomical specificity derives from guiding current to targeted brain structures and taking advantage of the direction-sensitivity of neurons with respect to the electric field. Functional specificity originates from preferential modulation of neuronal networks that are already active. Diffuse electric fields may recruit connected brain networks involved in a training task and promote plasticity along active synaptic pathways. In vitro, electric fields boost endogenous synaptic plasticity and raise the ceiling for synaptic learning with repeated stimulation sessions. Synapses undergoing strong plasticity are preferentially modulated over weak synapses. Therefore, active circuits that are involved in a task could be more susceptible to stimulation than inactive circuits. Moreover, stimulation polarity has asymmetric effects on synaptic strength making it easier to enhance ongoing plasticity. These results suggest that the susceptibility of brain networks to an electric field depends on the state of synaptic activity. Combining a training task, which activates specific circuits, with TES may lead to functionally-specific effects. Given the simplicity of TES and the complexity of brain function, understanding the mechanisms leading to specificity is fundamental to the rational advancement of TES.

Differential Modulation of Functional Dynamics and Allosteric Interactions in the Hsp90-Cochaperone Complexes with p23 and Aha1: A Computational Study

PubMed Central

Blacklock, Kristin; Verkhivker, Gennady M.

2013-01-01

Allosteric interactions of the molecular chaperone Hsp90 with a large cohort of cochaperones and client proteins allow for molecular communication and event coupling in signal transduction networks. The integration of cochaperones into the Hsp90 system is driven by the regulatory mechanisms that modulate the progression of the ATPase cycle and control the recruitment of the Hsp90 clientele. In this work, we report the results of computational modeling of allosteric regulation in the Hsp90 complexes with the cochaperones p23 and Aha1. By integrating protein docking, biophysical simulations, modeling of allosteric communications, protein structure network analysis and the energy landscape theory we have investigated dynamics and stability of the Hsp90-p23 and Hsp90-Aha1 interactions in direct comparison with the extensive body of structural and functional experiments. The results have revealed that functional dynamics and allosteric interactions of Hsp90 can be selectively modulated by these cochaperones via specific targeting of the regulatory hinge regions that could restrict collective motions and stabilize specific chaperone conformations. The protein structure network parameters have quantified the effects of cochaperones on conformational stability of the Hsp90 complexes and identified dynamically stable communities of residues that can contribute to the strengthening of allosteric interactions. According to our results, p23-mediated changes in the Hsp90 interactions may provide “molecular brakes” that could slow down an efficient transmission of the inter-domain allosteric signals, consistent with the functional role of p23 in partially inhibiting the ATPase cycle. Unlike p23, Aha1-mediated acceleration of the Hsp90-ATPase cycle may be achieved via modulation of the equilibrium motions that facilitate allosteric changes favoring a closed dimerized form of Hsp90. The results of our study have shown that Aha1 and p23 can modulate the Hsp90-ATPase activity and direct the chaperone cycle by exerting the precise control over structural stability, global movements and allosteric communications in Hsp90. PMID:23977182

Understanding network concepts in modules

PubMed Central

2007-01-01

Background Network concepts are increasingly used in biology and genetics. For example, the clustering coefficient has been used to understand network architecture; the connectivity (also known as degree) has been used to screen for cancer targets; and the topological overlap matrix has been used to define modules and to annotate genes. Dozens of potentially useful network concepts are known from graph theory. Results Here we study network concepts in special types of networks, which we refer to as approximately factorizable networks. In these networks, the pairwise connection strength (adjacency) between 2 network nodes can be factored into node specific contributions, named node 'conformity'. The node conformity turns out to be highly related to the connectivity. To provide a formalism for relating network concepts to each other, we define three types of network concepts: fundamental-, conformity-based-, and approximate conformity-based concepts. Fundamental concepts include the standard definitions of connectivity, density, centralization, heterogeneity, clustering coefficient, and topological overlap. The approximate conformity-based analogs of fundamental network concepts have several theoretical advantages. First, they allow one to derive simple relationships between seemingly disparate networks concepts. For example, we derive simple relationships between the clustering coefficient, the heterogeneity, the density, the centralization, and the topological overlap. The second advantage of approximate conformity-based network concepts is that they allow one to show that fundamental network concepts can be approximated by simple functions of the connectivity in module networks. Conclusion Using protein-protein interaction, gene co-expression, and simulated data, we show that a) many networks comprised of module nodes are approximately factorizable and b) in these types of networks, simple relationships exist between seemingly disparate network concepts. Our results are implemented in freely available R software code, which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/ModuleConformity/ModuleNetworks PMID:17547772

Design of EPON far-end equipment based on FTTH

NASA Astrophysics Data System (ADS)

Feng, Xiancheng; Yun, Xiang

2008-12-01

Now, most favors fiber access is mainly the EPON fiber access system. Inheriting from the low cost of Ethernet, usability and bandwidth of optical network, EPON technology is one of the best technologies in fiber access and is adopted by the carriers all over the world widely. According to the scheme analysis to FTTH fan-end equipment, hardware design of ONU is proposed in this paper. The FTTH far-end equipment software design deference modulation design concept, it divides the software designment into 5 function modules: the module of low-layer driver, the module of system management, the module of master/slave communication, and the module of main/Standby switch and the module of command line. The software flow of the host computer is also analyzed. Finally, test is made for Ethernet service performance of FTTH far-end equipment, E1 service performance and the optical path protection switching, and so on. The results of test indicates that all the items are accordance with technical request of far-end ONU equipment and possess good quality and fully reach the requirement of telecommunication level equipment. The far-end equipment of FTTH divides into several parts based on the function: the control module, the exchange module, the UNI interface module, the ONU module, the EPON interface module, the network management debugging module, the voice processing module, the circuit simulation module, the CATV module. In the downstream direction, under the protect condition, we design 2 optical modules. The system can set one group optical module working and another group optical module closure when it is initialized. When the optical fiber line is cut off, the LOS warning comes out. It will cause MUX to replace another group optical module, simultaneously will reset module 3701/3711 and will make it again test the distance, and will give the plug board MPC850 report through the GPIO port. During normal mode, the downstream optical signal is transformed into the electrical signal by the optical module. In the upstream direction, the upstream Ethernet data is retransmitted through the exchange chip BCM5380 to the GMII/MII in module 3701/3711, and then is transmitted to EPON port. The 2MB data are transformed the Ethernet data packet in the plug board TDM, then it's transmitted to the interface MII of the module 3701/3711. The software design of FTTH far-end equipment compiles with modulation design concept. According to the system realization duty, the software is divided into 5 function modules: low-level driver module, system management module, master/slave communication module, the man/Standby switch module and the command line module. The FTTH far-end equipment test, is mainly the Ethernet service performance test, E1 service performance test and the optical path protection switching test and so on the key specification test.

Nonparametric Bayesian inference of the microcanonical stochastic block model

NASA Astrophysics Data System (ADS)

Peixoto, Tiago P.

2017-01-01

A principled approach to characterize the hidden modular structure of networks is to formulate generative models and then infer their parameters from data. When the desired structure is composed of modules or "communities," a suitable choice for this task is the stochastic block model (SBM), where nodes are divided into groups, and the placement of edges is conditioned on the group memberships. Here, we present a nonparametric Bayesian method to infer the modular structure of empirical networks, including the number of modules and their hierarchical organization. We focus on a microcanonical variant of the SBM, where the structure is imposed via hard constraints, i.e., the generated networks are not allowed to violate the patterns imposed by the model. We show how this simple model variation allows simultaneously for two important improvements over more traditional inference approaches: (1) deeper Bayesian hierarchies, with noninformative priors replaced by sequences of priors and hyperpriors, which not only remove limitations that seriously degrade the inference on large networks but also reveal structures at multiple scales; (2) a very efficient inference algorithm that scales well not only for networks with a large number of nodes and edges but also with an unlimited number of modules. We show also how this approach can be used to sample modular hierarchies from the posterior distribution, as well as to perform model selection. We discuss and analyze the differences between sampling from the posterior and simply finding the single parameter estimate that maximizes it. Furthermore, we expose a direct equivalence between our microcanonical approach and alternative derivations based on the canonical SBM.

Holding-time-aware asymmetric spectrum allocation in virtual optical networks

NASA Astrophysics Data System (ADS)

Lyu, Chunjian; Li, Hui; Liu, Yuze; Ji, Yuefeng

2017-10-01

Virtual optical networks (VONs) have been considered as a promising solution to support current high-capacity dynamic traffic and achieve rapid applications deployment. Since most of the network services (e.g., high-definition video service, cloud computing, distributed storage) in VONs are provisioned by dedicated data centers, needing different amount of bandwidth resources in both directions, the network traffic is mostly asymmetric. The common strategy, symmetric provisioning of traffic in optical networks, leads to a waste of spectrum resources in such traffic patterns. In this paper, we design a holding-time-aware asymmetric spectrum allocation module based on SDON architecture and an asymmetric spectrum allocation algorithm based on the module is proposed. For the purpose of reducing spectrum resources' waste, the algorithm attempts to reallocate the idle unidirectional spectrum slots in VONs, which are generated due to the asymmetry of services' bidirectional bandwidth. This part of resources can be exploited by other requests, such as short-time non-VON requests. We also introduce a two-dimensional asymmetric resource model for maintaining idle spectrum resources information of VON in spectrum and time domains. Moreover, a simulation is designed to evaluate the performance of the proposed algorithm, and results show that our proposed asymmetric spectrum allocation algorithm can improve the resource waste and reduce blocking probability.

Reward-Modulated Hebbian Plasticity as Leverage for Partially Embodied Control in Compliant Robotics

PubMed Central

Burms, Jeroen; Caluwaerts, Ken; Dambre, Joni

2015-01-01

In embodied computation (or morphological computation), part of the complexity of motor control is offloaded to the body dynamics. We demonstrate that a simple Hebbian-like learning rule can be used to train systems with (partial) embodiment, and can be extended outside of the scope of traditional neural networks. To this end, we apply the learning rule to optimize the connection weights of recurrent neural networks with different topologies and for various tasks. We then apply this learning rule to a simulated compliant tensegrity robot by optimizing static feedback controllers that directly exploit the dynamics of the robot body. This leads to partially embodied controllers, i.e., hybrid controllers that naturally integrate the computations that are performed by the robot body into a neural network architecture. Our results demonstrate the universal applicability of reward-modulated Hebbian learning. Furthermore, they demonstrate the robustness of systems trained with the learning rule. This study strengthens our belief that compliant robots should or can be seen as computational units, instead of dumb hardware that needs a complex controller. This link between compliant robotics and neural networks is also the main reason for our search for simple universal learning rules for both neural networks and robotics. PMID:26347645

MicroRNAs as Key Effectors in the p53 Network.

PubMed

Goeman, Frauke; Strano, Sabrina; Blandino, Giovanni

2017-01-01

The guardian of the genome p53 is embedded in a fine-spun network of MicroRNAs. p53 is able to activate or repress directly the transcription of MicroRNAs that are participating in the tumor-suppressive mission of p53. On the other hand, the expression of p53 is under tight control of MicroRNAs that are either targeting directly p53 or factors that are modifying its protein level or activity. Although the most important function of p53 is suggested to be transcriptional regulation, there are several nontranscriptional functions described. One of those regards the modulation of MicroRNA biogenesis. Wild-type p53 is increasing the maturation of selected MicroRNAs from the primary transcript to the precursor MiRNA by interacting with the Microprocessor complex. Furthermore, p53 is modulating the mRNA accessibility for certain MicroRNAs by association with the RISC complex and transcriptional regulation of RNA-binding proteins. In this way p53 is able to remodel the MiRNA-mRNA interaction network. As wild-type p53 is employing MicroRNAs to suppress cancer development, gain-of-function mutant p53 proteins use MicroRNAs to confer oncogenic properties like chemoresistance and the ability to drive metastasis. Like its wild-type counterpart mutant p53 is able to regulate MicroRNAs transcriptionally and posttranscriptionally. Mutant p53 affects the MiRNA processing at two cleavage steps through interfering with the Microprocessor complex and by downregulating Dicer and KSRP, a modulator of MiRNA biogenesis. Thus, MicroRNAs are essential components in the p53 pathway, contributing substantially to combat or enhance tumor development depending on the wild-type or mutant p53 context. © 2017 Elsevier Inc. All rights reserved.

Adaptive Plasticity in the Healthy Language Network: Implications for Language Recovery after Stroke

PubMed Central

2016-01-01

Across the last three decades, the application of noninvasive brain stimulation (NIBS) has substantially increased the current knowledge of the brain's potential to undergo rapid short-term reorganization on the systems level. A large number of studies applied transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) in the healthy brain to probe the functional relevance and interaction of specific areas for different cognitive processes. NIBS is also increasingly being used to induce adaptive plasticity in motor and cognitive networks and shape cognitive functions. Recently, NIBS has been combined with electrophysiological techniques to modulate neural oscillations of specific cortical networks. In this review, we will discuss recent advances in the use of NIBS to modulate neural activity and effective connectivity in the healthy language network, with a special focus on the combination of NIBS and neuroimaging or electrophysiological approaches. Moreover, we outline how these results can be transferred to the lesioned brain to unravel the dynamics of reorganization processes in poststroke aphasia. We conclude with a critical discussion on the potential of NIBS to facilitate language recovery after stroke and propose a phase-specific model for the application of NIBS in language rehabilitation. PMID:27830094

Four-fold increase in users of time-wavelength division multiplexing (TWDM) passive optical network (PON) by delayed optical amplitude modulation (AM) upstream

NASA Astrophysics Data System (ADS)

Kachhatiya, Vivek; Prince, Shanthi

2016-12-01

In this paper, we have proposed and simulated optical time division multiplexed passive optical network (TDM-PON) using delayed optical amplitude modulation (AM). Eight upstream wavelengths are demonstrated to show optical time wavelength division multiplexed (TWDM) by combining optical network units (ONU) users data at the remote node (RN). Each ONU generates 2.5 Gb/s user data, and it is modulated using novel return to zero (RZ) delayed AM. Optical TDM aggregates 10 Gb/s data per wavelength from four 2.5 Gb/s upstream user data, which facilitates four different ONU data on the same wavelength as 10 Gb/s per upstream wavelength and, simplify the laser requirements (2.5 Gb/s) at each optical network unit (ONU) transmitter. Upstream optical TWDM-PON is investigated for eight wavelengths with wavelength spacing of 100 GHz. Novel optical TDM for upstream increased the number of the simultaneous user to fourfold from conventional TWDM-PON using delayed AM with a high-quality-factor of received signal. Despite performance degradation due to different fiber reach and dispersion compensation technique, Optical TWDM link shows significant improvement regarding receiver sensitivity when compared with common TWDM link. Hence, it offers optimistic thinking to show optical TDM at this phase as one of the future direction, where complex digital signal processing (DSP) and coherent optical communication are frequently demonstrated to serve the access network. Downstream side conventional TWDM eight wavelengths are multiplexed at the OLT and sent downstream to serve distributed tunable ONU receivers through an optical distribution network (ODN). Each downstream wavelengths are modulated at the peak rate of 10 Gb/s using non-return to zero external modulation (NRZ-EM). The proposed architecture is cost efficient and supports high data rates as well as ;pay as you grow; network for both service providers and the users perspectives. Users are classified into two categories viz home-user and business-user, with an option for easy up-gradation. Proposed architecture operates on next generation passive optical network stage 2 (NG-PON2) wavelength plan, with symmetrical data rate. Downstream performance is investigated by comparing, high power laser source with a conventional laser source and the L-band Erbium-doped fiber amplifier (EDFA) of gain 10 dB and 20 dB. Downstream eight wavelengths perform error-free up to 40 Km fiber reach and 1024 splitting points. Power budget of the proposed architecture incorporates the N1, N2, E1 and E2 optical path loss class.

Bi-directional four quadrant (BDQ4) power converter development

NASA Technical Reports Server (NTRS)

Schwarz, F. C.

1979-01-01

The feasibility for implementation of a concept for direct ac/dc multikilowatt power conversion with bidirectional transfer of energy was investigated. A 10 kHz current carrier was derived directly from a common 60 Hz three phase power system. This carrier was modulated to remove the 360 Hz ripple, inherent in the three phase power supply and then demodulated and processed by a high frequency filter. The resulting dc power was then supplied to a load. The process was implemented without the use of low frequency transformers and filters. This power conversion processes was reversible and can operate in the four quadrants as viewed from any of the two of the converter's ports. Areas of application include: power systems on air and spacecraft; terrestrial traction; integration of solar and wind powered systems with utility networks; HVDC; asynchronous coupling of polyphase networks; heat treatment; industrial machine drives; and power supplies for any use including instrumentation.

DiME: A Scalable Disease Module Identification Algorithm with Application to Glioma Progression

PubMed Central

Liu, Yunpeng; Tennant, Daniel A.; Zhu, Zexuan; Heath, John K.; Yao, Xin; He, Shan

2014-01-01

Disease module is a group of molecular components that interact intensively in the disease specific biological network. Since the connectivity and activity of disease modules may shed light on the molecular mechanisms of pathogenesis and disease progression, their identification becomes one of the most important challenges in network medicine, an emerging paradigm to study complex human disease. This paper proposes a novel algorithm, DiME (Disease Module Extraction), to identify putative disease modules from biological networks. We have developed novel heuristics to optimise Community Extraction, a module criterion originally proposed for social network analysis, to extract topological core modules from biological networks as putative disease modules. In addition, we have incorporated a statistical significance measure, B-score, to evaluate the quality of extracted modules. As an application to complex diseases, we have employed DiME to investigate the molecular mechanisms that underpin the progression of glioma, the most common type of brain tumour. We have built low (grade II) - and high (GBM) - grade glioma co-expression networks from three independent datasets and then applied DiME to extract potential disease modules from both networks for comparison. Examination of the interconnectivity of the identified modules have revealed changes in topology and module activity (expression) between low- and high- grade tumours, which are characteristic of the major shifts in the constitution and physiology of tumour cells during glioma progression. Our results suggest that transcription factors E2F4, AR and ETS1 are potential key regulators in tumour progression. Our DiME compiled software, R/C++ source code, sample data and a tutorial are available at http://www.cs.bham.ac.uk/~szh/DiME. PMID:24523864

Modulating risky decision-making in Parkinson's disease by transcranial direct current stimulation.

PubMed

Benussi, A; Alberici, A; Cantoni, V; Manenti, R; Brambilla, M; Dell'Era, V; Gazzina, S; Manes, M; Cristillo, V; Padovani, A; Cotelli, M; Borroni, B

2017-05-01

Performance on gambling tasks in Parkinson's disease (PD) is of particular interest, as pathological gambling is often associated with dopamine replacement therapy in these patients. We aimed to evaluate the effects of transcranial direct current stimulation (tDCS) over the right dorsolateral prefrontal cortex (DLPFC) in modulating gambling behaviour in PD. We assessed the effects of cathodal tDCS over the right DLPFC during the Iowa Gambling Task in 20 patients with PD, compared with sham stimulation. We then conducted a second experimental design, assessing the effects of anodal tDCS over the right DLPFC. We observed that cathodal tDCS over the right DLPFC increased Iowa Gambling Task scores compared with sham stimulation. In the second experimental design, we did not find significant differences between anodal and sham tDCS. Cathodal tDCS over the right DLPFC possibly reduces the pathological overdrive in frontostriatal networks in patients with PD on dopaminergic medication, thus modulating impulsive and risky decision-making. © 2017 EAN.

40-Gb/s directly-modulated photonic crystal lasers under optical injection-locking

NASA Astrophysics Data System (ADS)

Chen, Chin-Hui; Takeda, Koji; Shinya, Akihiko; Nozaki, Kengo; Sato, Tomonari; Kawaguchi, Yoshihiro; Notomi, Masaya; Matsuo, Shinji

2011-08-01

CMOS integrated circuits (IC) usually requires high data bandwidth for off-chip input/output (I/O) data transport with sufficiently low power consumption in order to overcome pin-count limitation. In order to meet future requirements of photonic network interconnect, we propose an optical output device based on an optical injection-locked photonic crystal (PhC) laser to realize low-power and high-speed off-chip interconnects. This device enables ultralow-power operation and is suitable for highly integrated photonic circuits because of its strong light-matter interaction in the PhC nanocavity and ultra-compact size. High-speed operation is achieved by using the optical injection-locking (OIL) technique, which has been shown as an effective means to enhance modulation bandwidth beyond the relaxation resonance frequency limit. In this paper, we report experimental results of the OIL-PhC laser under various injection conditions and also demonstrate 40-Gb/s large-signal direct modulation with an ultralow energy consumption of 6.6 fJ/bit.

Simultaneous 10 Gbps data and polarization-based pulse-per-second clock transmission using a single VCSEL for high-speed optical fibre access networks

NASA Astrophysics Data System (ADS)

Isoe, G. M.; Wassin, S.; Gamatham, R. R. G.; Leitch, A. W. R.; Gibbon, T. B.

2017-01-01

Access networks based on vertical cavity surface emitting laser (VCSEL) transmitters offer alternative solution in delivering different high bandwidth, cost effective services to the customer premises. Clock and reference frequency distribution is critical for applications such as Coordinated Universal Time (UTC), GPS, banking and big data science projects. Simultaneous distribution of both data and timing signals over shared infrastructure is thus desirable. In this paper, we propose and experimentally demonstrate a novel, cost-effective technique for multi-signal modulation on a single VCSEL transmitter. Two signal types, an intensity modulated 10 Gbps data signal and a polarization-based pulse per second (PPS) clock signal are directly modulated onto a single VCSEL carrier at 1310 nm. Spectral efficiency is maximized by exploiting inherent orthogonal polarization switching of the VCSEL with changing bias in transmission of the PPS signal. A 10 Gbps VCSEL transmission with PPS over 11 km of G.652 fibre introduced a transmission penalty of 0.52 dB. The contribution of PPS to this penalty was found to be 0.08 dB.

Hypothalamic neural systems controlling the female reproductive life cycle: Gonadotropin-releasing hormone, glutamate, and GABA

PubMed Central

Maffucci, Jacqueline A.; Gore, Andrea C.

2009-01-01

The hypothalamic-pituitary-gonadal (HPG) axis undergoes a number of changes throughout the reproductive life cycle that are responsible for the development, puberty, adulthood, and senescence of reproductive systems. This natural progression is dictated by the neural network controlling the hypothalamus including the cells that synthesize and release gonadotropin-releasing hormone (GnRH) and their regulatory neurotransmitters. Glutamate and GABA are the primary excitatory and inhibitory neurotransmitters in the central nervous system, and as such contribute a great deal to modulating this axis throughout the lifetime via their actions on receptors in the hypothalamus, both directly on GnRH neurons as well as indirectly though other hypothalamic neural networks. Interactions among GnRH neurons, glutamate, and GABA, including the regulation of GnRH gene and protein expression, hormone release, and modulation by estrogen, are critical to age-appropriate changes in reproductive function. Here, we present evidence for the modulation of GnRH neurosecretory cells by the balance of glutamate and GABA in the hypothalamus, and the functional consequences of these interactions on reproductive physiology across the life cycle. PMID:19349036

Analysis of remote synchronization in complex networks

NASA Astrophysics Data System (ADS)

Gambuzza, Lucia Valentina; Cardillo, Alessio; Fiasconaro, Alessandro; Fortuna, Luigi; Gómez-Gardeñes, Jesus; Frasca, Mattia

2013-12-01

A novel regime of synchronization, called remote synchronization, where the peripheral nodes form a phase synchronized cluster not including the hub, was recently observed in star motifs [Bergner et al., Phys. Rev. E 85, 026208 (2012)]. We show the existence of a more general dynamical state of remote synchronization in arbitrary networks of coupled oscillators. This state is characterized by the synchronization of pairs of nodes that are not directly connected via a physical link or any sequence of synchronized nodes. This phenomenon is almost negligible in networks of phase oscillators as its underlying mechanism is the modulation of the amplitude of those intermediary nodes between the remotely synchronized units. Our findings thus show the ubiquity and robustness of these states and bridge the gap from their recent observation in simple toy graphs to complex networks.

OLT-centralized sampling frequency offset compensation scheme for OFDM-PON.

PubMed

Chen, Ming; Zhou, Hui; Zheng, Zhiwei; Deng, Rui; Chen, Qinghui; Peng, Miao; Liu, Cuiwei; He, Jing; Chen, Lin; Tang, Xionggui

2017-08-07

We propose an optical line terminal (OLT)-centralized sampling frequency offset (SFO) compensation scheme for adaptively-modulated OFDM-PON systems. By using the proposed SFO scheme, the phase rotation and inter-symbol interference (ISI) caused by SFOs between OLT and multiple optical network units (ONUs) can be centrally compensated in the OLT, which reduces the complexity of ONUs. Firstly, the optimal fast Fourier transform (FFT) size is identified in the intensity-modulated and direct-detection (IMDD) OFDM system in the presence of SFO. Then, the proposed SFO compensation scheme including phase rotation modulation (PRM) and length-adaptive OFDM frame has been experimentally demonstrated in the downlink transmission of an adaptively modulated optical OFDM with the optimal FFT size. The experimental results show that up to ± 300 ppm SFO can be successfully compensated without introducing any receiver performance penalties.

Motivation but not valence modulates neuroticism-dependent cingulate cortex and insula activity.

PubMed

Deng, Yaling; Li, Shijia; Zhou, Renlai; Walter, Martin

2018-04-01

Neuroticism has been found to specifically modulate amygdala activations during differential processing of valence and motivation while other brain networks yet are unexplored for associated effects. The main purpose of this study was to investigate whether neural mechanisms processing valence or motivation are prone to neuroticism in the salience network (SN), a network that is anchored in the anterior cingulate cortex (ACC) and the anterior insula. This study used functional magnetic resonance imaging (fMRI) and an approach/avoid emotional pictures task to investigate brain activations modulated by pictures' valence or motivational status between high and low neurotic individuals. We found that neuroticism-dependent SN and the parahippocampal-fusiform area activations were modulated by motivation but not valence. Valence in contrast interacted with neuroticism in the lateral orbitofrontal cortex. We suggested that neuroticism modulated valence and motivation processing, however, under the influence of the two distinct networks. Neuroticism modulated the motivation through the SN while it modulated the valence through the orbitofrontal networks. © 2018 Wiley Periodicals, Inc.

Dense module enumeration in biological networks

NASA Astrophysics Data System (ADS)

Tsuda, Koji; Georgii, Elisabeth

2009-12-01

Analysis of large networks is a central topic in various research fields including biology, sociology, and web mining. Detection of dense modules (a.k.a. clusters) is an important step to analyze the networks. Though numerous methods have been proposed to this aim, they often lack mathematical rigorousness. Namely, there is no guarantee that all dense modules are detected. Here, we present a novel reverse-search-based method for enumerating all dense modules. Furthermore, constraints from additional data sources such as gene expression profiles or customer profiles can be integrated, so that we can systematically detect dense modules with interesting profiles. We report successful applications in human protein interaction network analyses.

100 Gb/s optical discrete multi-tone transceivers for intra- and inter-datacenter networks

NASA Astrophysics Data System (ADS)

Okabe, Ryo; Tanaka, Toshiki; Nishihara, Masato; Kai, Yutaka; Takahara, Tomoo; Liu, Bo; Li, Lei; Tao, Zhenning; Rasmussen, Jens C.

2016-03-01

Discrete multi-tone (DMT) technology is an attractive modulation technology for short-reach application due to its high spectral efficiency and simple configuration. In this paper, we first explain the features of DMT technology then discuss the impact of fiber dispersion and chirp on the frequency responses of the DMT signal and the importance in the relationship between chirp and the optical transmission band. Next, we explain our experiments of 100-Gb/s DMT transmission of 10 km in the O-band using directly modulated lasers for low-cost application. In an inter-datacenter network of more than several tens of kilometers, fiber dispersion mainly limits system performance. We also discuss our experiment of 100-Gb/s DMT transmission up to 100 km in the C-band without a dispersion compensator by using vestigial sideband spectrum shaping and nonlinear compensation.

A Novel Modulation Classification Approach Using Gabor Filter Network

PubMed Central

Ghauri, Sajjad Ahmed; Qureshi, Ijaz Mansoor; Cheema, Tanveer Ahmed; Malik, Aqdas Naveed

2014-01-01

A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network. Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN). The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64. The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the signal classification part. The Gabor atom parameters are tuned using Delta rule and updating of weights of Gabor filter using least mean square (LMS) algorithm. The simulation results show that proposed novel modulation classification algorithm has high classification accuracy at low signal to noise ratio (SNR) on AWGN channel. PMID:25126603

Attention biases visual activity in visual short-term memory.

PubMed

Kuo, Bo-Cheng; Stokes, Mark G; Murray, Alexandra M; Nobre, Anna Christina

2014-07-01

In the current study, we tested whether representations in visual STM (VSTM) can be biased via top-down attentional modulation of visual activity in retinotopically specific locations. We manipulated attention using retrospective cues presented during the retention interval of a VSTM task. Retrospective cues triggered activity in a large-scale network implicated in attentional control and led to retinotopically specific modulation of activity in early visual areas V1-V4. Importantly, shifts of attention during VSTM maintenance were associated with changes in functional connectivity between pFC and retinotopic regions within V4. Our findings provide new insights into top-down control mechanisms that modulate VSTM representations for flexible and goal-directed maintenance of the most relevant memoranda.

Dynamic characteristics of undoped and p-doped Fabry-Perot InAs/InP quantum dash based ridge waveguide lasers for access/metro networks

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

Mollet, O., E-mail: oriane.mollet@lpn.cnrs.fr; Martinez, A.; Merghem, K.

In this paper, we report the characteristics of InAs/InP quantum dashes (QDash) based lasers emitting around 1.55 μm. An unprecedented high modal gain of ∼100 cm{sup −1} is obtained for an optimized active structure by stacking 12 QDash layers. Directly modulated lasers allowed achieving a modulation bandwidth of ∼10 GHz and a Henry factor around 5. Thanks to p-type doping, the Henry factor value is reduced down to 2.7 while the modulation bandwidth still amounts to ∼10 GHz. This shows that doping of the active region is important to improve the dynamic characteristics of QDash lasers.

Landslide and Flood Warning System Prototypes based on Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Hloupis, George; Stavrakas, Ilias; Triantis, Dimos

2010-05-01

Wireless sensor networks (WSNs) are one of the emerging areas that received great attention during the last few years. This is mainly due to the fact that WSNs have provided scientists with the capability of developing real-time monitoring systems equipped with sensors based on Micro-Electro-Mechanical Systems (MEMS). WSNs have great potential for many applications in environmental monitoring since the sensor nodes that comprised from can host several MEMS sensors (such as temperature, humidity, inertial, pressure, strain-gauge) and transducers (such as position, velocity, acceleration, vibration). The resulting devices are small and inexpensive but with limited memory and computing resources. Each sensor node contains a sensing module which along with an RF transceiver. The communication is broadcast-based since the network topology can change rapidly due to node failures [1]. Sensor nodes can transmit their measurements to central servers through gateway nodes without any processing or they make preliminary calculations locally in order to produce results that will be sent to central servers [2]. Based on the above characteristics, two prototypes using WSNs are presented in this paper: A Landslide detection system and a Flood warning system. Both systems sent their data to central processing server where the core of processing routines exists. Transmission is made using Zigbee and IEEE 802.11b protocol but is capable to use VSAT communication also. Landslide detection system uses structured network topology. Each measuring node comprises of a columnar module that is half buried to the area under investigation. Each sensing module contains a geophone, an inclinometer and a set of strain gauges. Data transmitted to central processing server where possible landslide evolution is monitored. Flood detection system uses unstructured network topology since the failure rate of sensor nodes is expected higher. Each sensing module contains a custom water level sensor (based on plastic optical fiber). Data transmitted directly to server where the early warning algorithms monitor the water level variations in real time. Both sensor nodes use power harvesting techniques in order to extend their battery life as much as possible. [1] Yick J.; Mukherjee, B.; Ghosal, D. Wireless sensor network survey. Comput. Netw. 2008, 52, 2292-2330. [2] Garcia, M.; Bri, D.; Boronat, F.; Lloret, J. A new neighbor selection strategy for group-based wireless sensor networks, In The Fourth International Conference on Networking and Services (ICNS 2008), Gosier, Guadalupe, March 16-21, 2008.

Construct mine environment monitoring system based on wireless mesh network

NASA Astrophysics Data System (ADS)

Chen, Xin; Ge, Gengyu; Liu, Yinmei; Cheng, Aimin; Wu, Jun; Fu, Jun

2018-04-01

The system uses wireless Mesh network as a network transmission medium, and strive to establish an effective and reliable underground environment monitoring system. The system combines wireless network technology and embedded technology to monitor the internal data collected in the mine and send it to the processing center for analysis and environmental assessment. The system can be divided into two parts: the main control network module and the data acquisition terminal, and the SPI bus technology is used for mutual communication between them. Multi-channel acquisition and control interface design Data acquisition and control terminal in the analog signal acquisition module, digital signal acquisition module, and digital signal output module. The main control network module running Linux operating system, in which the transplant SPI driver, USB card driver and AODV routing protocol. As a result, the internal data collection and reporting of the mine are realized.

Integrated Module and Gene-Specific Regulatory Inference Implicates Upstream Signaling Networks

PubMed Central

Roy, Sushmita; Lagree, Stephen; Hou, Zhonggang; Thomson, James A.; Stewart, Ron; Gasch, Audrey P.

2013-01-01

Regulatory networks that control gene expression are important in diverse biological contexts including stress response and development. Each gene's regulatory program is determined by module-level regulation (e.g. co-regulation via the same signaling system), as well as gene-specific determinants that can fine-tune expression. We present a novel approach, Modular regulatory network learning with per gene information (MERLIN), that infers regulatory programs for individual genes while probabilistically constraining these programs to reveal module-level organization of regulatory networks. Using edge-, regulator- and module-based comparisons of simulated networks of known ground truth, we find MERLIN reconstructs regulatory programs of individual genes as well or better than existing approaches of network reconstruction, while additionally identifying modular organization of the regulatory networks. We use MERLIN to dissect global transcriptional behavior in two biological contexts: yeast stress response and human embryonic stem cell differentiation. Regulatory modules inferred by MERLIN capture co-regulatory relationships between signaling proteins and downstream transcription factors thereby revealing the upstream signaling systems controlling transcriptional responses. The inferred networks are enriched for regulators with genetic or physical interactions, supporting the inference, and identify modules of functionally related genes bound by the same transcriptional regulators. Our method combines the strengths of per-gene and per-module methods to reveal new insights into transcriptional regulation in stress and development. PMID:24146602

Activation of YUCCA5 by the Transcription Factor TCP4 Integrates Developmental and Environmental Signals to Promote Hypocotyl Elongation in Arabidopsis.

PubMed

Challa, Krishna Reddy; Aggarwal, Pooja; Nath, Utpal

2016-09-05

Cell expansion is an essential process in plant morphogenesis and is regulated by the coordinated action of environmental stimuli and endogenous factors, such as the phytohormones auxin and brassinosteroid. Although the biosynthetic pathways that generate these hormones and their downstream signaling mechanisms have been extensively studied, the upstream transcriptional network that modulates their levels and connects their action to cell morphogenesis is less clear. Here we show that the miR319-regulated TCP (TEOSINTE BRANCHED 1, CYCLODEA, PROLIFERATING CELL FACTORS) transcription factors, notably TCP4, directly activate YUCCA5 transcription and integrate the auxin response to a brassinosteroid-dependent molecular circuit that promotes cell elongation in Arabidopsis hypocotyls. Further, TCP4 modulates the common transcriptional network downstream to auxin-BR signaling, which is also triggered by environmental cues, such as light, to promote cell expansion. Our study links TCP function with the hormone response during cell morphogenesis and shows that developmental and environmental signals converge on a common transcriptional network to promote cell elongation. {copyright, serif} 2016 American Society of Plant Biologists. All rights reserved.

The Emerging Role of Epigenetics in Stroke

PubMed Central

Qureshi, Irfan A.; Mehler, Mark F.

2013-01-01

The transplantation of exogenous stem cells and the activation of endogenous neural stem and progenitor cells (NSPCs) are promising treatments for stroke. These cells can modulate intrinsic responses to ischemic injury and may even integrate directly into damaged neural networks. However, the neuroprotective and neural regenerative effects that can be mediated by these cells are limited and may even be deleterious. Epigenetic reprogramming represents a novel strategy for enhancing the intrinsic potential of the brain to protect and repair itself by modulating pathologic neural gene expression and promoting the recapitulation of seminal neural developmental processes. In fact, recent evidence suggests that emerging epigenetic mechanisms are critical for orchestrating nearly every aspect of neural development and homeostasis, including brain patterning, neural stem cell maintenance, neurogenesis and gliogenesis, neural subtype specification, and synaptic and neural network connectivity and plasticity. In this review, we survey the therapeutic potential of exogenous stem cells and endogenous NSPCs and highlight innovative technological approaches for designing, developing, and delivering epigenetic therapies for targeted reprogramming of endogenous pools of NSPCs, neural cells at risk, and dysfunctional neural networks to rescue and restore neurologic function in the ischemic brain. PMID:21403016

Spatial reasoning to determine stream network from LANDSAT imagery

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Wang, S.; Elliott, D. B.

1983-01-01

In LANDSAT imagery, spectral and spatial information can be used to detect the drainage network as well as the relative elevation model in mountainous terrain. To do this, mixed information of material reflectance in the original LANDSAT imagery must be separated. From the material reflectance information, big visible rivers can be detected. From the topographic modulation information, ridges and valleys can be detected and assigned relative elevations. A complete elevation model can be generated by interpolating values for nonridge and non-valley pixels. The small streams not detectable from material reflectance information can be located in the valleys with flow direction known from the elevation model. Finally, the flow directions of big visible rivers can be inferred by solving a consistent labeling problem based on a set of spatial reasoning constraints.

Environmental versatility promotes modularity in genome-scale metabolic networks.

PubMed

Samal, Areejit; Wagner, Andreas; Martin, Olivier C

2011-08-24

The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Our work shows that modularity in metabolic networks can be a by-product of functional constraints, e.g., the need to sustain life in multiple environments. This organizational principle is insensitive to the environments we consider and to the number of reactions in a metabolic network. Because we observe this principle not just in one or few biological networks, but in large random samples of networks, we propose that it may be a generic principle of metabolic network organization.

Discovering Multimodal Behavior in Ms. Pac-Man through Evolution of Modular Neural Networks.

PubMed

Schrum, Jacob; Miikkulainen, Risto

2016-03-12

Ms. Pac-Man is a challenging video game in which multiple modes of behavior are required: Ms. Pac-Man must escape ghosts when they are threats and catch them when they are edible, in addition to eating all pills in each level. Past approaches to learning behavior in Ms. Pac-Man have treated the game as a single task to be learned using monolithic policy representations. In contrast, this paper uses a framework called Modular Multi-objective NEAT (MM-NEAT) to evolve modular neural networks. Each module defines a separate behavior. The modules are used at different times according to a policy that can be human-designed (i.e. Multitask) or discovered automatically by evolution. The appropriate number of modules can be fixed or discovered using a genetic operator called Module Mutation. Several versions of Module Mutation are evaluated in this paper. Both fixed modular networks and Module Mutation networks outperform monolithic networks and Multitask networks. Interestingly, the best networks dedicate modules to critical behaviors (such as escaping when surrounded after luring ghosts near a power pill) that do not follow the customary division of the game into chasing edible and escaping threat ghosts. The results demonstrate that MM-NEAT can discover interesting and effective behavior for agents in challenging games.

Discovering Multimodal Behavior in Ms. Pac-Man through Evolution of Modular Neural Networks

PubMed Central

Schrum, Jacob; Miikkulainen, Risto

2015-01-01

Ms. Pac-Man is a challenging video game in which multiple modes of behavior are required: Ms. Pac-Man must escape ghosts when they are threats and catch them when they are edible, in addition to eating all pills in each level. Past approaches to learning behavior in Ms. Pac-Man have treated the game as a single task to be learned using monolithic policy representations. In contrast, this paper uses a framework called Modular Multi-objective NEAT (MM-NEAT) to evolve modular neural networks. Each module defines a separate behavior. The modules are used at different times according to a policy that can be human-designed (i.e. Multitask) or discovered automatically by evolution. The appropriate number of modules can be fixed or discovered using a genetic operator called Module Mutation. Several versions of Module Mutation are evaluated in this paper. Both fixed modular networks and Module Mutation networks outperform monolithic networks and Multitask networks. Interestingly, the best networks dedicate modules to critical behaviors (such as escaping when surrounded after luring ghosts near a power pill) that do not follow the customary division of the game into chasing edible and escaping threat ghosts. The results demonstrate that MM-NEAT can discover interesting and effective behavior for agents in challenging games. PMID:27030803

Distributed reconfigurable control strategies for switching topology networked multi-agent systems.

PubMed

Gallehdari, Z; Meskin, N; Khorasani, K

2017-11-01

In this paper, distributed control reconfiguration strategies for directed switching topology networked multi-agent systems are developed and investigated. The proposed control strategies are invoked when the agents are subject to actuator faults and while the available fault detection and isolation (FDI) modules provide inaccurate and unreliable information on the estimation of faults severities. Our proposed strategies will ensure that the agents reach a consensus while an upper bound on the team performance index is ensured and satisfied. Three types of actuator faults are considered, namely: the loss of effectiveness fault, the outage fault, and the stuck fault. By utilizing quadratic and convex hull (composite) Lyapunov functions, two cooperative and distributed recovery strategies are designed and provided to select the gains of the proposed control laws such that the team objectives are guaranteed. Our proposed reconfigurable control laws are applied to a team of autonomous underwater vehicles (AUVs) under directed switching topologies and subject to simultaneous actuator faults. Simulation results demonstrate the effectiveness of our proposed distributed reconfiguration control laws in compensating for the effects of sudden actuator faults and subject to fault diagnosis module uncertainties and unreliabilities. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Apparatus for fixing latency

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

Hall, David R; Bartholomew, David B; Moon, Justin

2009-09-08

An apparatus for fixing computational latency within a deterministic region on a network comprises a network interface modem, a high priority module and at least one deterministic peripheral device. The network interface modem is in communication with the network. The high priority module is in communication with the network interface modem. The at least one deterministic peripheral device is connected to the high priority module. The high priority module comprises a packet assembler/disassembler, and hardware for performing at least one operation. Also disclosed is an apparatus for executing at least one instruction on a downhole device within a deterministic region,more » the apparatus comprising a control device, a downhole network, and a downhole device. The control device is near the surface of a downhole tool string. The downhole network is integrated into the tool string. The downhole device is in communication with the downhole network.« less

Is a Responsive Default Mode Network Required for Successful Working Memory Task Performance?

PubMed Central

Čeko, Marta; Gracely, John L.; Fitzcharles, Mary-Ann; Seminowicz, David A.; Schweinhardt, Petra

2015-01-01

In studies of cognitive processing using tasks with externally directed attention, regions showing increased (external-task-positive) and decreased or “negative” [default-mode network (DMN)] fMRI responses during task performance are dynamically responsive to increasing task difficulty. Responsiveness (modulation of fMRI signal by increasing load) has been linked directly to successful cognitive task performance in external-task-positive regions but not in DMN regions. To investigate whether a responsive DMN is required for successful cognitive performance, we compared healthy human subjects (n = 23) with individuals shown to have decreased DMN engagement (chronic pain patients, n = 28). Subjects performed a multilevel working-memory task (N-back) during fMRI. If a responsive DMN is required for successful performance, patients having reduced DMN responsiveness should show worsened performance; if performance is not reduced, their brains should show compensatory activation in external-task-positive regions or elsewhere. All subjects showed decreased accuracy and increased reaction times with increasing task level, with no significant group differences on either measure at any level. Patients had significantly reduced negative fMRI response (deactivation) of DMN regions (posterior cingulate/precuneus, medial prefrontal cortex). Controls showed expected modulation of DMN deactivation with increasing task difficulty. Patients showed significantly reduced modulation of DMN deactivation by task difficulty, despite their successful task performance. We found no evidence of compensatory neural recruitment in external-task-positive regions or elsewhere. Individual responsiveness of the external-task-positive ventrolateral prefrontal cortex, but not of DMN regions, correlated with task accuracy. These findings suggest that a responsive DMN may not be required for successful cognitive performance; a responsive external-task-positive network may be sufficient. SIGNIFICANCE STATEMENT We studied the relationship between responsiveness of the brain to increasing task demand and successful cognitive performance, using chronic pain patients as a probe. fMRI working memory studies show that two main cognitive networks [“external-task positive” and “default-mode network” (DMN)] are responsive to increasing task difficulty. The responsiveness of both of these brain networks is suggested to be required for successful task performance. The responsiveness of external-task-positive regions has been linked directly to successful cognitive task performance, as we also show here. However, pain patients show decreased engagement and responsiveness of the DMN but can perform a working memory task as well as healthy subjects, without demonstrable compensatory neural recruitment. Therefore, a responsive DMN might not be needed for successful cognitive performance. PMID:26290236

SeaDataNet network services monitoring: Definition and Implementation of Service availability index

NASA Astrophysics Data System (ADS)

Lykiardopoulos, Angelos; Mpalopoulou, Stavroula; Vavilis, Panagiotis; Pantazi, Maria; Iona, Sissy

2014-05-01

SeaDataNet (SDN) is a standardized system for managing large and diverse data sets collected by the oceanographic fleets and the automatic observation systems. The SeaDataNet network is constituted of national oceanographic data centres of 35 countries, active in data collection. SeaDataNetII project's objective is to upgrade the present SeaDataNet infrastructure into an operationally robust and state-of-the-art infrastructure; therefore Network Monitoring is a step to this direction. The term Network Monitoring describes the use of system that constantly monitors a computer network for slow or failing components and that notifies the network administrator in case of outages. Network monitoring is crucial when implementing widely distributed systems over the Internet and in real-time systems as it detects malfunctions that may occur and notifies the system administrator who can immediately respond and correct the problem. In the framework of SeaDataNet II project a monitoring system was developed in order to monitor the SeaDataNet components. The core system is based on Nagios software. Some plug-ins were developed to support SeaDataNet modules. On the top of Nagios Engine a web portal was developed in order to give access to local administrators of SeaDataNet components, to view detailed logs of their own service(s). Currently the system monitors 35 SeaDataNet Download Managers, 9 SeaDataNet Services, 25 GeoSeas Download Managers and 23 UBSS Download Managers . Taking advantage of the continuous monitoring of SeaDataNet system components a total availability index will be implemented. The term availability can be defined as the ability of a functional unit to be in a state to perform a required function under given conditions at a given instant of time or over a given time interval, assuming that the required external resources are provided. Availability measures can be considered as a are very important benefit becauseT - The availability trends that can be extracted from the stored availability measurements will give an indication of the condition of the service modules. - Will help in planning upgrades planning - and the maintenance of the network service. - It is a prerequisite in case of signing a Service Level Agreement. To construct the service availability index, a method for measuring availability of SeaDataNet network is developed and a database is implemented to store the measured values. Although the measurements of availability of a single component in a network service can be considered as simple (is a percentage of time in a year that the service is available to the users), the ipmlementation of a method to measure the total availability of a composite system can be complicated and there is no a standardized method to deal with it. The method followed to calculate the total availability index in case of SeaDataNet can be described as follows: The whole system was divided in operational modules providing a single service in which the availability can be measured by monitoring portal. Next the dependences between these modules were defined in order to formulate the influence of availability of each module against the whole system. For each module a weight coefficient depending on module's involvement in total system productivity was defined. A mathematical formula was developed to measure the index.

Genes under weaker stabilizing selection increase network evolvability and rapid regulatory adaptation to an environmental shift.

PubMed

Laarits, T; Bordalo, P; Lemos, B

2016-08-01

Regulatory networks play a central role in the modulation of gene expression, the control of cellular differentiation, and the emergence of complex phenotypes. Regulatory networks could constrain or facilitate evolutionary adaptation in gene expression levels. Here, we model the adaptation of regulatory networks and gene expression levels to a shift in the environment that alters the optimal expression level of a single gene. Our analyses show signatures of natural selection on regulatory networks that both constrain and facilitate rapid evolution of gene expression level towards new optima. The analyses are interpreted from the standpoint of neutral expectations and illustrate the challenge to making inferences about network adaptation. Furthermore, we examine the consequence of variable stabilizing selection across genes on the strength and direction of interactions in regulatory networks and in their subsequent adaptation. We observe that directional selection on a highly constrained gene previously under strong stabilizing selection was more efficient when the gene was embedded within a network of partners under relaxed stabilizing selection pressure. The observation leads to the expectation that evolutionarily resilient regulatory networks will contain optimal ratios of genes whose expression is under weak and strong stabilizing selection. Altogether, our results suggest that the variable strengths of stabilizing selection across genes within regulatory networks might itself contribute to the long-term adaptation of complex phenotypes. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Silicon photonic Mach Zehnder modulators for next-generation short-reach optical communication networks

NASA Astrophysics Data System (ADS)

Lacava, C.; Liu, Z.; Thomson, D.; Ke, Li; Fedeli, J. M.; Richardson, D. J.; Reed, G. T.; Petropoulos, P.

2016-02-01

Communication traffic grows relentlessly in today's networks, and with ever more machines connected to the network, this trend is set to continue for the foreseeable future. It is widely accepted that increasingly faster communications are required at the point of the end users, and consequently optical transmission plays a progressively greater role even in short- and medium-reach networks. Silicon photonic technologies are becoming increasingly attractive for such networks, due to their potential for low cost, energetically efficient, high-speed optical components. A representative example is the silicon-based optical modulator, which has been actively studied. Researchers have demonstrated silicon modulators in different types of structures, such as ring resonators or slow light based devices. These approaches have shown remarkably good performance in terms of modulation efficiency, however their operation could be severely affected by temperature drifts or fabrication errors. Mach-Zehnder modulators (MZM), on the other hand, show good performance and resilience to different environmental conditions. In this paper we present a CMOS-compatible compact silicon MZM. We study the application of the modulator to short-reach interconnects by realizing data modulation using some relevant advanced modulation formats, such as 4-level Pulse Amplitude Modulation (PAM-4) and Discrete Multi-Tone (DMT) modulation and compare the performance of the different systems in transmission.

Application of UDWDM technology in FTTH networks

NASA Astrophysics Data System (ADS)

Lamperski, Jan; Stepczak, Piotr

2015-12-01

In the paper we presented results of investigation of an original ultra dense wavelength division technology based on optical comb generator and its implementation for FTTH networks. The optical comb generator used a ring configuration with an acousto-optic frequency shifter (AOFS) which ensured obtaining very stable optical carrier frequency distances. Properties of an optical comb generator module determined stability of the UDWDM transmitter. Key properties of a selective components based on all fiber Fabry-Perot resonant cavity were presented. Operation of direct and coherent detection DWDM systems were shown. New configurations of FTTH UDWDM architecture have been proposed.

Symptom-specific amygdala hyperactivity modulates motor control network in conversion disorder.

PubMed

Hassa, Thomas; Sebastian, Alexandra; Liepert, Joachim; Weiller, Cornelius; Schmidt, Roger; Tüscher, Oliver

2017-01-01

Initial historical accounts as well as recent data suggest that emotion processing is dysfunctional in conversion disorder patients and that this alteration may be the pathomechanistic neurocognitive basis for symptoms in conversion disorder. However, to date evidence of direct interaction of altered negative emotion processing with motor control networks in conversion disorder is still lacking. To specifically study the neural correlates of emotion processing interacting with motor networks we used a task combining emotional and sensorimotor stimuli both separately as well as simultaneously during functional magnetic resonance imaging in a well characterized group of 13 conversion disorder patients with functional hemiparesis and 19 demographically matched healthy controls. We performed voxelwise statistical parametrical mapping for a priori regions of interest within emotion processing and motor control networks. Psychophysiological interaction (PPI) was used to test altered functional connectivity of emotion and motor control networks. Only during simultaneous emotional stimulation and passive movement of the affected hand patients displayed left amygdala hyperactivity. PPI revealed increased functional connectivity in patients between the left amygdala and the (pre-)supplemental motor area and the subthalamic nucleus, key regions within the motor control network. These findings suggest a novel mechanistic direct link between dysregulated emotion processing and motor control circuitry in conversion disorder.

Fault-tolerant battery system employing intra-battery network architecture

DOEpatents

Hagen, Ronald A.; Chen, Kenneth W.; Comte, Christophe; Knudson, Orlin B.; Rouillard, Jean

2000-01-01

A distributed energy storing system employing a communications network is disclosed. A distributed battery system includes a number of energy storing modules, each of which includes a processor and communications interface. In a network mode of operation, a battery computer communicates with each of the module processors over an intra-battery network and cooperates with individual module processors to coordinate module monitoring and control operations. The battery computer monitors a number of battery and module conditions, including the potential and current state of the battery and individual modules, and the conditions of the battery's thermal management system. An over-discharge protection system, equalization adjustment system, and communications system are also controlled by the battery computer. The battery computer logs and reports various status data on battery level conditions which may be reported to a separate system platform computer. A module transitions to a stand-alone mode of operation if the module detects an absence of communication connectivity with the battery computer. A module which operates in a stand-alone mode performs various monitoring and control functions locally within the module to ensure safe and continued operation.

Causal relationship between effective connectivity within the default mode network and mind-wandering regulation and facilitation.

PubMed

Kajimura, Shogo; Kochiyama, Takanori; Nakai, Ryusuke; Abe, Nobuhito; Nomura, Michio

2016-06-01

Transcranial direct current stimulation (tDCS) can modulate mind wandering, which is a shift in the contents of thought away from an ongoing task and/or from events in the external environment to self-generated thoughts and feelings. Although modulation of the mind-wandering propensity is thought to be associated with neural alterations of the lateral prefrontal cortex (LPFC) and regions in the default mode network (DMN), the precise neural mechanisms remain unknown. Using functional magnetic resonance imaging (fMRI), we investigated the causal relationships among tDCS (one electrode placed over the right IPL, which is a core region of the DMN, and another placed over the left LPFC), stimulation-induced directed connection alterations within the DMN, and modulation of the mind-wandering propensity. At the behavioral level, anodal tDCS on the right IPL (with cathodal tDCS on the left LPFC) reduced mind wandering compared to the reversed stimulation. At the neural level, the anodal tDCS on the right IPL decreased the afferent connections of the posterior cingulate cortex (PCC) from the right IPL and the medial prefrontal cortex (mPFC). Furthermore, mediation analysis revealed that the changes in the connections from the right IPL and mPFC correlated with the facilitation and inhibition of mind wandering, respectively. These effects are the result of the heterogeneous function of effective connectivity: the connection from the right IPL to the PCC inhibits mind wandering, whereas the connection from the mPFC to the PCC facilitates mind wandering. The present study is the first to demonstrate the neural mechanisms underlying tDCS modulation of mind-wandering propensity. Copyright © 2016 Elsevier Inc. All rights reserved.

InP on SOI devices for optical communication and optical network on chip

NASA Astrophysics Data System (ADS)

Fedeli, J.-M.; Ben Bakir, B.; Olivier, N.; Grosse, Ph.; Grenouillet, L.; Augendre, E.; Phillippe, P.; Gilbert, K.; Bordel, D.; Harduin, J.

2011-01-01

For about ten years, we have been developing InP on Si devices under different projects focusing first on μlasers then on semicompact lasers. For aiming the integration on a CMOS circuit and for thermal issue, we relied on SiO2 direct bonding of InP unpatterned materials. After the chemical removal of the InP substrate, the heterostructures lie on top of silicon waveguides of an SOI wafer with a separation of about 100nm. Different lasers or photodetectors have been achieved for off-chip optical communication and for intra-chip optical communication within an optical network. For high performance computing with high speed communication between cores, we developed InP microdisk lasers that are coupled to silicon waveguide and produced 100μW of optical power and that can be directly modulated up to 5G at different wavelengths. The optical network is based on wavelength selective circuits with ring resonators. InGaAs photodetectors are evanescently coupled to the silicon waveguide with an efficiency of 0.8A/W. The fabrication has been demonstrated at 200mm wafer scale in a microelectronics clean room for CMOS compatibility. For off-chip communication, silicon on InP evanescent laser have been realized with an innovative design where the cavity is defined in silicon and the gain localized in the QW of bonded InP hererostructure. The investigated devices operate at continuous wave regime with room temperature threshold current below 100 mA, the side mode suppression ratio is as high as 20dB, and the fibercoupled output power is {7mW. Direct modulation can be achieved with already 6G operation.

Microarray and network-based identification of functional modules and pathways of active tuberculosis.

PubMed

Bian, Zhong-Rui; Yin, Juan; Sun, Wen; Lin, Dian-Jie

2017-04-01

Diagnose of active tuberculosis (TB) is challenging and treatment response is also difficult to efficiently monitor. The aim of this study was to use an integrated analysis of microarray and network-based method to the samples from publically available datasets to obtain a diagnostic module set and pathways in active TB. Towards this goal, background protein-protein interactions (PPI) network was generated based on global PPI information and gene expression data, following by identification of differential expression network (DEN) from the background PPI network. Then, ego genes were extracted according to the degree features in DEN. Next, module collection was conducted by ego gene expansion based on EgoNet algorithm. After that, differential expression of modules between active TB and controls was evaluated using random permutation test. Finally, biological significance of differential modules was detected by pathways enrichment analysis based on Reactome database, and Fisher's exact test was implemented to extract differential pathways for active TB. Totally, 47 ego genes and 47 candidate modules were identified from the DEN. By setting the cutoff-criteria of gene size >5 and classification accuracy ≥0.9, 7 ego modules (Module 4, Module 7, Module 9, Module 19, Module 25, Module 38 and Module 43) were extracted, and all of them had the statistical significance between active TB and controls. Then, Fisher's exact test was conducted to capture differential pathways for active TB. Interestingly, genes in Module 4, Module 25, Module 38, and Module 43 were enriched in the same pathway, formation of a pool of free 40S subunits. Significant pathway for Module 7 and Module 9 was eukaryotic translation termination, and for Module 19 was nonsense mediated decay enhanced by the exon junction complex (EJC). Accordingly, differential modules and pathways might be potential biomarkers for treating active TB, and provide valuable clues for better understanding of molecular mechanism of active TB. Copyright © 2017 Elsevier Ltd. All rights reserved.

atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

PubMed

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2016-10-06

Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

Rational modular design of metabolic network for efficient production of plant polyphenol pinosylvin.

PubMed

Wu, Junjun; Zhang, Xia; Zhu, Yingjie; Tan, Qinyu; He, Jiacheng; Dong, Mingsheng

2017-05-03

Efficient biosynthesis of the plant polyphenol pinosylvin, which has numerous applications in nutraceuticals and pharmaceuticals, is necessary to make biological production economically viable. To this end, an efficient Escherichia coli platform for pinosylvin production was developed via a rational modular design approach. Initially, different candidate pathway enzymes were screened to construct de novo pinosylvin pathway directly from D-glucose. A comparative analysis of pathway intermediate pools identified that this initial construct led to the intermediate cinnamic acid accumulation. The pinosylvin synthetic pathway was then divided into two new modules separated at cinnamic acid. Combinatorial optimization of transcriptional and translational levels of these two modules resulted in a 16-fold increase in pinosylvin titer. To further improve the concentration of the limiting precursor malonyl-CoA, the malonyl-CoA synthesis module based on clustered regularly interspaced short palindromic repeats interference was assembled and optimized with other two modules. The final pinosylvin titer was improved to 281 mg/L, which was the highest pinosylvin titer even directly from D-glucose without any additional precursor supplementation. The rational modular design approach described here could bolster our capabilities in synthetic biology for value-added chemical production.

Container-code recognition system based on computer vision and deep neural networks

NASA Astrophysics Data System (ADS)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

Strong-coupling induced damping of spin-echo modulations in magic-angle-spinning NMR: Implications for J coupling measurements in disordered solids

NASA Astrophysics Data System (ADS)

Guerry, Paul; Brown, Steven P.; Smith, Mark E.

2017-10-01

In the context of improving J coupling measurements in disordered solids, strong coupling effects have been investigated in the spin-echo and refocused INADEQUATE spin-echo (REINE) modulations of three- and four-spin systems under magic-angle-spinning (MAS), using density matrix simulations and solid-state NMR experiments on a cadmium phosphate glass. Analytical models are developed for the different modulation regimes, which are shown to be distinguishable in practice using Akaike's information criterion. REINE modulations are shown to be free of the damping that occurs for spin-echo modulations when the observed spin has the same isotropic chemical shift as its neighbour. Damping also occurs when the observed spin is bonded to a strongly-coupled pair. For mid-chain units, the presence of both direct and relayed damping makes both REINE and spin-echo modulations impossible to interpret quantitatively. We nonetheless outline how a qualitative comparison of the modulation curves can provide valuable information on disordered networks, possibly also pertaining to dynamic effects therein.

Hierarchical surface code for network quantum computing with modules of arbitrary size

NASA Astrophysics Data System (ADS)

Li, Ying; Benjamin, Simon C.

2016-10-01

The network paradigm for quantum computing involves interconnecting many modules to form a scalable machine. Typically it is assumed that the links between modules are prone to noise while operations within modules have a significantly higher fidelity. To optimize fault tolerance in such architectures we introduce a hierarchical generalization of the surface code: a small "patch" of the code exists within each module and constitutes a single effective qubit of the logic-level surface code. Errors primarily occur in a two-dimensional subspace, i.e., patch perimeters extruded over time, and the resulting noise threshold for intermodule links can exceed ˜10 % even in the absence of purification. Increasing the number of qubits within each module decreases the number of qubits necessary for encoding a logical qubit. But this advantage is relatively modest, and broadly speaking, a "fine-grained" network of small modules containing only about eight qubits is competitive in total qubit count versus a "course" network with modules containing many hundreds of qubits.

Network Analysis Implicates Alpha-Synuclein (Snca) in the Regulation of Ovariectomy-Induced Bone Loss

PubMed Central

Calabrese, Gina; Mesner, Larry D.; Foley, Patricia L.; Rosen, Clifford J.; Farber, Charles R.

2016-01-01

The postmenopausal period in women is associated with decreased circulating estrogen levels, which accelerate bone loss and increase the risk of fracture. Here, we gained novel insight into the molecular mechanisms mediating bone loss in ovariectomized (OVX) mice, a model of human menopause, using co-expression network analysis. Specifically, we generated a co-expression network consisting of 53 gene modules using expression profiles from intact and OVX mice from a panel of inbred strains. The expression of four modules was altered by OVX, including module 23 whose expression was decreased by OVX across all strains. Module 23 was enriched for genes involved in the response to oxidative stress, a process known to be involved in OVX-induced bone loss. Additionally, module 23 homologs were co-expressed in human bone marrow. Alpha synuclein (Snca) was one of the most highly connected “hub” genes in module 23. We characterized mice deficient in Snca and observed a 40% reduction in OVX-induced bone loss. Furthermore, protection was associated with the altered expression of specific network modules, including module 23. In summary, the results of this study suggest that Snca regulates bone network homeostasis and ovariectomy-induced bone loss. PMID:27378017

Analysis Tools for Interconnected Boolean Networks With Biological Applications.

PubMed

Chaves, Madalena; Tournier, Laurent

2018-01-01

Boolean networks with asynchronous updates are a class of logical models particularly well adapted to describe the dynamics of biological networks with uncertain measures. The state space of these models can be described by an asynchronous state transition graph, which represents all the possible exits from every single state, and gives a global image of all the possible trajectories of the system. In addition, the asynchronous state transition graph can be associated with an absorbing Markov chain, further providing a semi-quantitative framework where it becomes possible to compute probabilities for the different trajectories. For large networks, however, such direct analyses become computationally untractable, given the exponential dimension of the graph. Exploiting the general modularity of biological systems, we have introduced the novel concept of asymptotic graph , computed as an interconnection of several asynchronous transition graphs and recovering all asymptotic behaviors of a large interconnected system from the behavior of its smaller modules. From a modeling point of view, the interconnection of networks is very useful to address for instance the interplay between known biological modules and to test different hypotheses on the nature of their mutual regulatory links. This paper develops two new features of this general methodology: a quantitative dimension is added to the asymptotic graph, through the computation of relative probabilities for each final attractor and a companion cross-graph is introduced to complement the method on a theoretical point of view.

Linear Look-Ahead in Conjunctive Cells: An Entorhinal Mechanism for Vector-Based Navigation

PubMed Central

Kubie, John L.; Fenton, André A.

2012-01-01

The crisp organization of the “firing bumps” of entorhinal grid cells and conjunctive cells leads to the notion that the entorhinal cortex may compute linear navigation routes. Specifically, we propose a process, termed “linear look-ahead,” by which a stationary animal could compute a series of locations in the direction it is facing. We speculate that this computation could be achieved through learned patterns of connection strengths among entorhinal neurons. This paper has three sections. First, we describe the minimal grid cell properties that will be built into our network. Specifically, the network relies on “rigid modules” of neurons, where all members have identical grid scale and orientation, but differ in spatial phase. Additionally, these neurons must be densely interconnected with synapses that are modifiable early in the animal’s life. Second, we investigate whether plasticity during short bouts of locomotion could induce patterns of connections amongst grid cells or conjunctive cells. Finally, we run a simulation to test whether the learned connection patterns can exhibit linear look-ahead. Our results are straightforward. A simulated 30-min walk produces weak strengthening of synapses between grid cells that do not support linear look-ahead. Similar training in a conjunctive cell module produces a small subset of very strong connections between cells. These strong pairs have three properties: the pre- and post-synaptic cells have similar heading direction. The cell pairs have neighboring grid bumps. Finally, the spatial offset of firing bumps of the cell pair is in the direction of the common heading preference. Such a module can produce strong and accurate linear look-ahead starting in any location and extending in any direction. We speculate that this process may: (1) compute linear paths to goals; (2) update grid cell firing during navigation; and (3) stabilize the rigid modules of grid cells and conjunctive cells. PMID:22557948

Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

Protein-protein interaction (PPI) networks carry vital information on the organization of molecular interactions in cellular systems. The identification of functionally relevant modules in PPI networks is one of the most important applications of biological network analysis. Computational analysis is becoming an indispensable tool to understand large-scale biomolecular interaction networks. Several types of computational methods have been developed and employed for the analysis of PPI networks. Of these computational methods, graph comparison and module detection are the two most commonly used strategies. This review summarizes current literature on graph kernel and graph alignment methods for graph comparison strategies, as well as module detection approaches including seed-and-extend, hierarchical clustering, optimization-based, probabilistic, and frequent subgraph methods. Herein, we provide a comprehensive review of the major algorithms employed under each theme, including our recently published frequent subgraph method, for detecting functional modules commonly shared across multiple cancer PPI networks. PMID:24800226

Continuous Attractor Network Model for Conjunctive Position-by-Velocity Tuning of Grid Cells

PubMed Central

Si, Bailu; Romani, Sandro; Tsodyks, Misha

2014-01-01

The spatial responses of many of the cells recorded in layer II of rodent medial entorhinal cortex (MEC) show a triangular grid pattern, which appears to provide an accurate population code for animal spatial position. In layer III, V and VI of the rat MEC, grid cells are also selective to head-direction and are modulated by the speed of the animal. Several putative mechanisms of grid-like maps were proposed, including attractor network dynamics, interactions with theta oscillations or single-unit mechanisms such as firing rate adaptation. In this paper, we present a new attractor network model that accounts for the conjunctive position-by-velocity selectivity of grid cells. Our network model is able to perform robust path integration even when the recurrent connections are subject to random perturbations. PMID:24743341

Community structure in traffic zones based on travel demand

NASA Astrophysics Data System (ADS)

Sun, Li; Ling, Ximan; He, Kun; Tan, Qian

2016-09-01

Large structure in complex networks can be studied by dividing it into communities or modules. Urban traffic system is one of the most critical infrastructures. It can be abstracted into a complex network composed of tightly connected groups. Here, we analyze community structure in urban traffic zones based on the community detection method in network science. Spectral algorithm using the eigenvectors of matrices is employed. Our empirical results indicate that the traffic communities are variant with the travel demand distribution, since in the morning the majority of the passengers are traveling from home to work and in the evening they are traveling a contrary direction. Meanwhile, the origin-destination pairs with large number of trips play a significant role in urban traffic network's community division. The layout of traffic community in a city also depends on the residents' trajectories.

Mapping human brain networks with cortico-cortical evoked potentials

PubMed Central

Keller, Corey J.; Honey, Christopher J.; Mégevand, Pierre; Entz, Laszlo; Ulbert, Istvan; Mehta, Ashesh D.

2014-01-01

The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex. PMID:25180306

Automatic decomposition of kinetic models of signaling networks minimizing the retroactivity among modules.

PubMed

Saez-Rodriguez, Julio; Gayer, Stefan; Ginkel, Martin; Gilles, Ernst Dieter

2008-08-15

The modularity of biochemical networks in general, and signaling networks in particular, has been extensively studied over the past few years. It has been proposed to be a useful property to analyze signaling networks: by decomposing the network into subsystems, more manageable units are obtained that are easier to analyze. While many powerful algorithms are available to identify modules in protein interaction networks, less attention has been paid to signaling networks de.ned as chemical systems. Such a decomposition would be very useful as most quantitative models are de.ned using the latter, more detailed formalism. Here, we introduce a novel method to decompose biochemical networks into modules so that the bidirectional (retroactive) couplings among the modules are minimized. Our approach adapts a method to detect community structures, and applies it to the so-called retroactivity matrix that characterizes the couplings of the network. Only the structure of the network, e.g. in SBML format, is required. Furthermore, the modularized models can be loaded into ProMoT, a modeling tool which supports modular modeling. This allows visualization of the models, exploiting their modularity and easy generation of models of one or several modules for further analysis. The method is applied to several relevant cases, including an entangled model of the EGF-induced MAPK cascade and a comprehensive model of EGF signaling, demonstrating its ability to uncover meaningful modules. Our approach can thus help to analyze large networks, especially when little a priori knowledge on the structure of the network is available. The decomposition algorithms implemented in MATLAB (Mathworks, Inc.) are freely available upon request. ProMoT is freely available at http://www.mpi-magdeburg.mpg.de/projects/promot. Supplementary data are available at Bioinformatics online.

Functional modules by relating protein interaction networks and gene expression.

PubMed

Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Functional modules by relating protein interaction networks and gene expression

PubMed Central

Tornow, Sabine; Mewes, H. W.

2003-01-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships. PMID:14576317

Transcranial Direct Current Stimulation Modulates Neuronal Networks in Attention Deficit Hyperactivity Disorder.

PubMed

Sotnikova, Anna; Soff, Cornelia; Tagliazucchi, Enzo; Becker, Katja; Siniatchkin, Michael

2017-09-01

Anodal transcranial direct current stimulation (tDCS) of the prefrontal cortex has been repeatedly shown to improve working memory (WM). Since patients with attention deficit hyperactivity disorder (ADHD) are characterized by both underactivation of the prefrontal cortex and deficits in WM, the modulation of prefrontal activity with tDCS in ADHD patients may increase their WM performance as well as improve the activation and connectivity of the WM network. In the present study, this hypothesis was tested using a double-blind sham-controlled experimental design. After randomization, sixteen adolescents with ADHD underwent either anodal tDCS over the left dorsolateral prefrontal cortex (DLPFC, 1 mA, 20 min) or sham stimulation with simultaneous fMRI during n-back WM task. Both in one-back and two-back conditions, tDCS led to a greater activation (compared with sham stimulation) of the left DLPFC (under the electrode), left premotor cortex, left supplementary motor cortex, and precuneus. The effects of tDCS were long-lasting and influenced resting state functional connectivity even 20 min after the stimulation, with patterns of strengthened DLPFC connectivity after tDCS outlining the WM network. In summary, anodal tDCS caused increased neuronal activation and connectivity, not only in the brain area under the stimulating electrode (i.e. left DLPFC) but also in other, more remote brain regions. Because of moderate behavioral effects of tDCS, the significance of this technique for ADHD treatment has to be investigated in further studies.

Cortical network reorganization guided by sensory input features.

PubMed

Kilgard, Michael P; Pandya, Pritesh K; Engineer, Navzer D; Moucha, Raluca

2002-12-01

Sensory experience alters the functional organization of cortical networks. Previous studies using behavioral training motivated by aversive or rewarding stimuli have demonstrated that cortical plasticity is specific to salient inputs in the sensory environment. Sensory experience associated with electrical activation of the basal forebrain (BasF) generates similar input specific plasticity. By directly engaging plasticity mechanisms and avoiding extensive behavioral training, BasF stimulation makes it possible to efficiently explore how specific sensory features contribute to cortical plasticity. This review summarizes our observations that cortical networks employ a variety of strategies to improve the representation of the sensory environment. Different combinations of receptive-field, temporal, and spectrotemporal plasticity were generated in primary auditory cortex neurons depending on the pitch, modulation rate, and order of sounds paired with BasF stimulation. Simple tones led to map expansion, while modulated tones altered the maximum cortical following rate. Exposure to complex acoustic sequences led to the development of combination-sensitive responses. This remodeling of cortical response characteristics may reflect changes in intrinsic cellular mechanisms, synaptic efficacy, and local neuronal connectivity. The intricate relationship between the pattern of sensory activation and cortical plasticity suggests that network-level rules alter the functional organization of the cortex to generate the most behaviorally useful representation of the sensory environment.

Ecological modules and roles of species in heathland plant-insect flower visitor networks.

PubMed

Dupont, Yoko L; Olesen, Jens M

2009-03-01

1. Co-existing plants and flower-visiting animals often form complex interaction networks. A long-standing question in ecology and evolutionary biology is how to detect nonrandom subsets (compartments, blocks, modules) of strongly interacting species within such networks. Here we use a network analytical approach to (i) detect modularity in pollination networks, (ii) investigate species composition of modules, and (iii) assess the stability of modules across sites. 2. Interactions between entomophilous plants and their flower-visitors were recorded throughout the flowering season at three heathland sites in Denmark, separated by >or= 10 km. Among sites, plant communities were similar, but composition of flower-visiting insect faunas differed. Visitation frequencies of visitor species were recorded as a measure of insect abundance. 3. Qualitative (presence-absence) interaction networks were tested for modularity. Modules were identified, and species classified into topological roles (peripherals, connectors, or hubs) using 'functional cartography by simulated annealing', a method recently developed by Guimerà & Amaral (2005a). 4. All networks were significantly modular. Each module consisted of 1-6 plant species and 18-54 insect species. Interactions aggregated around one or two hub plant species, which were largely identical at the three study sites. 5. Insect species were categorized in taxonomic groups, mostly at the level of orders. When weighted by visitation frequency, each module was dominated by one or few insect groups. This pattern was consistent across sites. 6. Our study adds support to the conclusion that certain plant species and flower-visitor groups are nonrandomly and repeatedly associated. Within a network, these strongly interacting subgroups of species may exert reciprocal selection pressures on each other. Thus, modules may be candidates for the long-sought key units of co-evolution.

MINE: Module Identification in Networks

PubMed Central

2011-01-01

Background Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of functionally related gene products, is an important challenge in analyzing biological networks. However, existing tools to identify modules are insufficient when applied to dense networks of experimentally derived interaction data. To address this problem, we have developed an agglomerative clustering method that is able to identify highly modular sets of gene products within highly interconnected molecular interaction networks. Results MINE outperforms MCODE, CFinder, NEMO, SPICi, and MCL in identifying non-exclusive, high modularity clusters when applied to the C. elegans protein-protein interaction network. The algorithm generally achieves superior geometric accuracy and modularity for annotated functional categories. In comparison with the most closely related algorithm, MCODE, the top clusters identified by MINE are consistently of higher density and MINE is less likely to designate overlapping modules as a single unit. MINE offers a high level of granularity with a small number of adjustable parameters, enabling users to fine-tune cluster results for input networks with differing topological properties. Conclusions MINE was created in response to the challenge of discovering high quality modules of gene products within highly interconnected biological networks. The algorithm allows a high degree of flexibility and user-customisation of results with few adjustable parameters. MINE outperforms several popular clustering algorithms in identifying modules with high modularity and obtains good overall recall and precision of functional annotations in protein-protein interaction networks from both S. cerevisiae and C. elegans. PMID:21605434

Detecting phenotype-driven transitions in regulatory network structure.

PubMed

Padi, Megha; Quackenbush, John

2018-01-01

Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure. Here, we describe ALPACA (ALtered Partitions Across Community Architectures), a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules. In simulations, ALPACA leads to more nuanced, sensitive, and robust module discovery than currently available network comparison methods. As an application, we use ALPACA to compare transcriptional networks in three contexts: angiogenic and non-angiogenic subtypes of ovarian cancer, human fibroblasts expressing transforming viral oncogenes, and sexual dimorphism in human breast tissue. In each case, ALPACA identifies modules enriched for processes relevant to the phenotype. For example, modules specific to angiogenic ovarian tumors are enriched for genes associated with blood vessel development, and modules found in female breast tissue are enriched for genes involved in estrogen receptor and ERK signaling. The functional relevance of these new modules suggests that not only can ALPACA identify structural changes in complex networks, but also that these changes may be relevant for characterizing biological phenotypes.

Initial experience with a radiology imaging network to newborn and intensive care units.

PubMed

Witt, R M; Cohen, M D; Appledorn, C R

1991-02-01

A digital image network has been installed in the James Whitcomb Riley Hospital for Children on the Indiana University Medical Center to create a limited all digital imaging system. The system is composed of commercial components, Philips/AT&T CommView system, (Philips Medical Systems, Shelton, CT; AT&T Bell Laboratories, West Long Beach, NJ) and connects an existing Philips Computed Radiology (PCR) system to two remote workstations that reside in the intensive care unit and the newborn nursery. The purpose of the system is to display images obtained from the PCR system on the remote workstations for direct viewing by referring clinicians, and to reduce many of their visits to the radiology reading room three floors away. The design criteria includes the ability to centrally control all image management functions on the remote workstations to relieve the clinicians from any image management tasks except for recalling patient images. The principal components of the system are the Philips PCR system, the acquisition module (AM), and the PCR interface to the Data Management Module (DMM). Connected to the DMM are an Enhanced Graphics Display Workstation (EGDW), an optical disk drive, and a network gateway to an ethernet link. The ethernet network is the connection to the two Results Viewing Stations (RVS) and both RVSs are approximately 100 m from the gateway. The DMM acts as an image file server and an image archive device. The DMM manages the image data base and can load images to the EGDW and the two RVSs. The system has met the initial design specifications and can successfully capture images from the PCR and direct them to the RVSs.(ABSTRACT TRUNCATED AT 250 WORDS)

Gain and power optimization of the wireless optical system with multilevel modulation.

PubMed

Liu, Xian

2008-06-01

When used in an outdoor environment to expedite networking access, the performance of wireless optical communication systems is affected by transmitter sway. In the design of such systems, much attention has been paid to developing power-efficient schemes. However, the bandwidth efficiency is also an important issue. One of the most natural approaches to promote bandwidth efficiency is to use multilevel modulation. This leads to multilevel pulse amplitude modulation in the context of intensity modulation and direct detection. We develop a model based on the four-level pulse amplitude modulation. We show that the model can be formulated as an optimization problem in terms of the transmitter power, bit error probability, transmitter gain, and receiver gain. The technical challenges raised by modeling and solving the problem include the analytical and numerical treatments for the improper integrals of the Gaussian functions coupled with the erfc function. The results demonstrate that, at the optimal points, the power penalty paid to the doubled bandwidth efficiency is around 3 dB.

Variable Coding and Modulation Experiment Using NASA's Space Communication and Navigation Testbed

NASA Technical Reports Server (NTRS)

Downey, Joseph A.; Mortensen, Dale J.; Evans, Michael A.; Tollis, Nicholas S.

2016-01-01

National Aeronautics and Space Administration (NASA)'s Space Communication and Navigation Testbed on the International Space Station provides a unique opportunity to evaluate advanced communication techniques in an operational system. The experimental nature of the Testbed allows for rapid demonstrations while using flight hardware in a deployed system within NASA's networks. One example is variable coding and modulation, which is a method to increase data-throughput in a communication link. This paper describes recent flight testing with variable coding and modulation over S-band using a direct-to-earth link between the SCaN Testbed and the Glenn Research Center. The testing leverages the established Digital Video Broadcasting Second Generation (DVB-S2) standard to provide various modulation and coding options. The experiment was conducted in a challenging environment due to the multipath and shadowing caused by the International Space Station structure. Performance of the variable coding and modulation system is evaluated and compared to the capacity of the link, as well as standard NASA waveforms.

Enzymes and other agents that enhance cell wall extensibility

NASA Technical Reports Server (NTRS)

Cosgrove, D. J.

1999-01-01

Polysaccharides and proteins are secreted to the inner surface of the growing cell wall, where they assemble into a network that is mechanically strong, yet remains extensible until the cells cease growth. This review focuses on the agents that directly or indirectly enhance the extensibility properties of growing walls. The properties of expansins, endoglucanases, and xyloglucan transglycosylases are reviewed and their postulated roles in modulating wall extensibility are evaluated. A summary model for wall extension is presented, in which expansin is a primary agent of wall extension, whereas endoglucanases, xyloglucan endotransglycosylase, and other enzymes that alter wall structure act secondarily to modulate expansin action.

Performance analysis of communication links based on VCSEL and silicon photonics technology for high-capacity data-intensive scenario.

PubMed

Boletti, A; Boffi, P; Martelli, P; Ferrario, M; Martinelli, M

2015-01-26

To face the increased demand for bandwidth, cost-effectiveness and simplicity of future Ethernet data communications, a comparison between two different solutions based on directly-modulated VCSEL sources and Silicon Photonics technologies is carried out. Also by exploiting 4-PAM modulation, the transmission of 50-Gb/s and beyond capacity per channel is analyzed by means of BER performance. Applications for optical backplane, very short reach and in case of client-optics networks and intra and inter massive data centers communications (up to 10 km) are taken into account. A comparative analysis based on the power consumption is also proposed.

Transforming growth factor β: a master regulator of the gut microbiota and immune cell interactions.

PubMed

Bauché, David; Marie, Julien C

2017-04-01

The relationship between host organisms and their microbiota has co-evolved towards an inter-dependent network of mutualistic interactions. This interplay is particularly well studied in the gastrointestinal tract, where microbiota and host immune cells can modulate each other directly, as well as indirectly, through the production and release of chemical molecules and signals. In this review, we define the functional impact of transforming growth factor-beta (TGF-β) on this complex interplay, especially through its modulation of the activity of local regulatory T cells (Tregs), type 17 helper (Th17) cells, innate lymphoid cells (ILCs) and B cells.

Graph coarse-graining reveals differences in the module-level structure of functional brain networks.

PubMed

Kujala, Rainer; Glerean, Enrico; Pan, Raj Kumar; Jääskeläinen, Iiro P; Sams, Mikko; Saramäki, Jari

2016-11-01

Networks have become a standard tool for analyzing functional magnetic resonance imaging (fMRI) data. In this approach, brain areas and their functional connections are mapped to the nodes and links of a network. Even though this mapping reduces the complexity of the underlying data, it remains challenging to understand the structure of the resulting networks due to the large number of nodes and links. One solution is to partition networks into modules and then investigate the modules' composition and relationship with brain functioning. While this approach works well for single networks, understanding differences between two networks by comparing their partitions is difficult and alternative approaches are thus necessary. To this end, we present a coarse-graining framework that uses a single set of data-driven modules as a frame of reference, enabling one to zoom out from the node- and link-level details. As a result, differences in the module-level connectivity can be understood in a transparent, statistically verifiable manner. We demonstrate the feasibility of the method by applying it to networks constructed from fMRI data recorded from 13 healthy subjects during rest and movie viewing. While independently partitioning the rest and movie networks is shown to yield little insight, the coarse-graining framework enables one to pinpoint differences in the module-level structure, such as the increased number of intra-module links within the visual cortex during movie viewing. In addition to quantifying differences due to external stimuli, the approach could also be applied in clinical settings, such as comparing patients with healthy controls. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Mapping, Awareness, And Virtualization Network Administrator Training Tool Virtualization Module

DTIC Science & Technology

2016-03-01

AND VIRTUALIZATION NETWORK ADMINISTRATOR TRAINING TOOL VIRTUALIZATION MODULE by Erik W. Berndt March 2016 Thesis Advisor: John Gibson...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE MAPPING, AWARENESS, AND VIRTUALIZATION NETWORK ADMINISTRATOR TRAINING TOOL... VIRTUALIZATION MODULE 5. FUNDING NUMBERS 6. AUTHOR(S) Erik W. Berndt 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School

A new multi-scale method to reveal hierarchical modular structures in biological networks.

PubMed

Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin

2016-11-15

Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.

State-dependent, bidirectional modulation of neural network activity by endocannabinoids.

PubMed

Piet, Richard; Garenne, André; Farrugia, Fanny; Le Masson, Gwendal; Marsicano, Giovanni; Chavis, Pascale; Manzoni, Olivier J

2011-11-16

The endocannabinoid (eCB) system and the cannabinoid CB1 receptor (CB1R) play key roles in the modulation of brain functions. Although actions of eCBs and CB1Rs are well described at the synaptic level, little is known of their modulation of neural activity at the network level. Using microelectrode arrays, we have examined the role of CB1R activation in the modulation of the electrical activity of rat and mice cortical neural networks in vitro. We find that exogenous activation of CB1Rs expressed on glutamatergic neurons decreases the spontaneous activity of cortical neural networks. Moreover, we observe that the net effect of the CB1R antagonist AM251 inversely correlates with the initial level of activity in the network: blocking CB1Rs increases network activity when basal network activity is low, whereas it depresses spontaneous activity when its initial level is high. Our results reveal a complex role of CB1Rs in shaping spontaneous network activity, and suggest that the outcome of endogenous neuromodulation on network function might be state dependent.

Emotion modulation of the startle reflex in essential tremor: Blunted reactivity to unpleasant and pleasant pictures.

PubMed

Lafo, Jacob A; Mikos, Ania; Mangal, Paul C; Scott, Bonnie M; Trifilio, Erin; Okun, Michael S; Bowers, Dawn

2017-01-01

Essential tremor is a highly prevalent movement disorder characterized by kinetic tremor and mild cognitive-executive changes. These features are commonly attributed to abnormal cerebellar changes, resulting in disruption of cerebellar-thalamo-cortical networks. Less attention has been paid to alterations in basic emotion processing in essential tremor, despite known cerebellar-limbic interconnectivity. In the current study, we tested the hypothesis that a psychophysiologic index of emotional reactivity, the emotion modulated startle reflex, would be muted in individuals with essential tremor relative to controls. Participants included 19 essential tremor patients and 18 controls, who viewed standard sets of unpleasant, pleasant, and neutral pictures for six seconds each. During picture viewing, white noise bursts were binaurally presented to elicit startle eyeblinks measured over the orbicularis oculi. Consistent with past literature, controls' startle eyeblink responses were modulated according to picture valence (unpleasant > neutral > pleasant). In essential tremor participants, startle eyeblinks were not modulated by emotion. This modulation failure was not due to medication effects, nor was it due to abnormal appraisal of emotional picture content. Neuroanatomically, it remains unclear whether diminished startle modulation in essential tremor is secondary to aberrant cerebellar input to the amygdala, which is involved in priming the startle response in emotional contexts, or due to more direct disruption between the cerebellum and brainstem startle circuitry. If the former is correct, these findings may be the first to reveal dysregulation of emotional networks in essential tremor. Copyright © 2016 Elsevier Ltd. All rights reserved.

RM-SORN: a reward-modulated self-organizing recurrent neural network.

PubMed

Aswolinskiy, Witali; Pipa, Gordon

2015-01-01

Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain.

Evidence for Functional Networks within the Human Brain's White Matter.

PubMed

Peer, Michael; Nitzan, Mor; Bick, Atira S; Levin, Netta; Arzy, Shahar

2017-07-05

Investigation of the functional macro-scale organization of the human cortex is fundamental in modern neuroscience. Although numerous studies have identified networks of interacting functional modules in the gray-matter, limited research was directed to the functional organization of the white-matter. Recent studies have demonstrated that the white-matter exhibits blood oxygen level-dependent signal fluctuations similar to those of the gray-matter. Here we used these signal fluctuations to investigate whether the white-matter is organized as functional networks by applying a clustering analysis on resting-state functional MRI (RSfMRI) data from white-matter voxels, in 176 subjects (of both sexes). This analysis indicated the existence of 12 symmetrical white-matter functional networks, corresponding to combinations of white-matter tracts identified by diffusion tensor imaging. Six of the networks included interhemispheric commissural bridges traversing the corpus callosum. Signals in white-matter networks correlated with signals from functional gray-matter networks, providing missing knowledge on how these distributed networks communicate across large distances. These findings were replicated in an independent subject group and were corroborated by seed-based analysis in small groups and individual subjects. The identified white-matter functional atlases and analysis codes are available at http://mind.huji.ac.il/white-matter.aspx Our results demonstrate that the white-matter manifests an intrinsic functional organization as interacting networks of functional modules, similarly to the gray-matter, which can be investigated using RSfMRI. The discovery of functional networks within the white-matter may open new avenues of research in cognitive neuroscience and clinical neuropsychiatry. SIGNIFICANCE STATEMENT In recent years, functional MRI (fMRI) has revolutionized all fields of neuroscience, enabling identifications of functional modules and networks in the human brain. However, most fMRI studies ignored a major part of the brain, the white-matter, discarding signals from it as arising from noise. Here we use resting-state fMRI data from 176 subjects to show that signals from the human white-matter contain meaningful information. We identify 12 functional networks composed of interacting long-distance white-matter tracts. Moreover, we show that these networks are highly correlated to resting-state gray-matter networks, highlighting their functional role. Our findings enable reinterpretation of many existing fMRI datasets, and suggest a new way to explore the white-matter role in cognition and its disturbances in neuropsychiatric disorders. Copyright © 2017 the authors 0270-6474/17/376394-14$15.00/0.

Using a Simple Neural Network to Delineate Some Principles of Distributed Economic Choice.

PubMed

Balasubramani, Pragathi P; Moreno-Bote, Rubén; Hayden, Benjamin Y

2018-01-01

The brain uses a mixture of distributed and modular organization to perform computations and generate appropriate actions. While the principles under which the brain might perform computations using modular systems have been more amenable to modeling, the principles by which the brain might make choices using distributed principles have not been explored. Our goal in this perspective is to delineate some of those distributed principles using a neural network method and use its results as a lens through which to reconsider some previously published neurophysiological data. To allow for direct comparison with our own data, we trained the neural network to perform binary risky choices. We find that value correlates are ubiquitous and are always accompanied by non-value information, including spatial information (i.e., no pure value signals). Evaluation, comparison, and selection were not distinct processes; indeed, value signals even in the earliest stages contributed directly, albeit weakly, to action selection. There was no place, other than at the level of action selection, at which dimensions were fully integrated. No units were specialized for specific offers; rather, all units encoded the values of both offers in an anti-correlated format, thus contributing to comparison. Individual network layers corresponded to stages in a continuous rotation from input to output space rather than to functionally distinct modules. While our network is likely to not be a direct reflection of brain processes, we propose that these principles should serve as hypotheses to be tested and evaluated for future studies.

Using a Simple Neural Network to Delineate Some Principles of Distributed Economic Choice

PubMed Central

Balasubramani, Pragathi P.; Moreno-Bote, Rubén; Hayden, Benjamin Y.

2018-01-01

The brain uses a mixture of distributed and modular organization to perform computations and generate appropriate actions. While the principles under which the brain might perform computations using modular systems have been more amenable to modeling, the principles by which the brain might make choices using distributed principles have not been explored. Our goal in this perspective is to delineate some of those distributed principles using a neural network method and use its results as a lens through which to reconsider some previously published neurophysiological data. To allow for direct comparison with our own data, we trained the neural network to perform binary risky choices. We find that value correlates are ubiquitous and are always accompanied by non-value information, including spatial information (i.e., no pure value signals). Evaluation, comparison, and selection were not distinct processes; indeed, value signals even in the earliest stages contributed directly, albeit weakly, to action selection. There was no place, other than at the level of action selection, at which dimensions were fully integrated. No units were specialized for specific offers; rather, all units encoded the values of both offers in an anti-correlated format, thus contributing to comparison. Individual network layers corresponded to stages in a continuous rotation from input to output space rather than to functionally distinct modules. While our network is likely to not be a direct reflection of brain processes, we propose that these principles should serve as hypotheses to be tested and evaluated for future studies. PMID:29643773

Dynamic Neural Networks Supporting Memory Retrieval

PubMed Central

St. Jacques, Peggy L.; Kragel, Philip A.; Rubin, David C.

2011-01-01

How do separate neural networks interact to support complex cognitive processes such as remembrance of the personal past? Autobiographical memory (AM) retrieval recruits a consistent pattern of activation that potentially comprises multiple neural networks. However, it is unclear how such large-scale neural networks interact and are modulated by properties of the memory retrieval process. In the present functional MRI (fMRI) study, we combined independent component analysis (ICA) and dynamic causal modeling (DCM) to understand the neural networks supporting AM retrieval. ICA revealed four task-related components consistent with the previous literature: 1) Medial Prefrontal Cortex (PFC) Network, associated with self-referential processes, 2) Medial Temporal Lobe (MTL) Network, associated with memory, 3) Frontoparietal Network, associated with strategic search, and 4) Cingulooperculum Network, associated with goal maintenance. DCM analysis revealed that the medial PFC network drove activation within the system, consistent with the importance of this network to AM retrieval. Additionally, memory accessibility and recollection uniquely altered connectivity between these neural networks. Recollection modulated the influence of the medial PFC on the MTL network during elaboration, suggesting that greater connectivity among subsystems of the default network supports greater re-experience. In contrast, memory accessibility modulated the influence of frontoparietal and MTL networks on the medial PFC network, suggesting that ease of retrieval involves greater fluency among the multiple networks contributing to AM. These results show the integration between neural networks supporting AM retrieval and the modulation of network connectivity by behavior. PMID:21550407

Long-reach transmission experiment of a wavelength division multiplexed-passive optical networks transmitter based on reflective semiconductor optical amplifiers

NASA Astrophysics Data System (ADS)

Jeon, Sie-Wook; Kim, Youngbok; Park, Chang-Soo

2012-01-01

We propose and demonstrate a long-reach wavelength division multiplexed-passive optical networks (WDM-PON) based on reflective semiconductor optical amplifiers (RSOAs) with easy maintenance of the optical source. Unlike previous studies the proposed WDM-PON uses two RSOAs: one for wavelength-selected light generation to provide a constant seed light to the second RSOA, the other for active external modulation. This method is free from intensity-fluctuated power penalties inherent to directly modulated single-RSOA sources, making long-reach transmission possible. Also, the wavelength of the modulated signal can easily be changed for the same RSOA by replacing the external feedback reflector, such as a fiber Bragg grating, or via thermal tuning. The seed light has a high-side-mode suppression ratio (SMSR) of 45 dB, and the bit error rate (BER) curve reveals that the upstream 1.25-Gb/s nonreturn-to-zero (NRZ) signal with a pseudo-random binary sequence (PRBS) of length of 215-1 has power penalties of 0.22 and 0.69 dB at BERs of 10-9 after 55-km and 110-km transmission due to fiber dispersion, respectively.

The rat corticospinal system is functionally and anatomically segregated.

PubMed

Olivares-Moreno, Rafael; Moreno-Lopez, Yunuen; Concha, Luis; Martínez-Lorenzana, Guadalupe; Condés-Lara, Miguel; Cordero-Erausquin, Matilde; Rojas-Piloni, Gerardo

2017-12-01

The descending corticospinal (CS) projection has been considered a key element for motor control, which results from direct and indirect modulation of spinal cord pre-motor interneurons in the intermediate gray matter of the spinal cord, which, in turn, influences motoneurons in the ventral horn. The CS tract (CST) is also involved in a selective and complex modulation of sensory information in the dorsal horn. However, little is known about the spinal network engaged by the CST and the organization of CS projections that may encode different cortical outputs to the spinal cord. This study addresses the issue of whether the CS system exerts parallel control on different spinal networks, which together participate in sensorimotor integration. Here, we show that in the adult rat, two different and partially intermingled CS neurons in the sensorimotor cortex activate, with different time latencies, distinct spinal cord neurons located in the dorsal horn and intermediate zone of the same segment. The fact that different populations of CS neurons project in a segregated manner suggests that CST is composed of subsystems controlling different spinal cord circuits that modulate motor outputs and sensory inputs in a coordinated manner.

Evolutionarily Repurposed Networks Reveal the Well-Known Antifungal Drug Thiabendazole to Be a Novel Vascular Disrupting Agent

PubMed Central

Cha, Hye Ji; Byrom, Michelle; Mead, Paul E.; Ellington, Andrew D.; Wallingford, John B.; Marcotte, Edward M.

2012-01-01

Studies in diverse organisms have revealed a surprising depth to the evolutionary conservation of genetic modules. For example, a systematic analysis of such conserved modules has recently shown that genes in yeast that maintain cell walls have been repurposed in vertebrates to regulate vein and artery growth. We reasoned that by analyzing this particular module, we might identify small molecules targeting the yeast pathway that also act as angiogenesis inhibitors suitable for chemotherapy. This insight led to the finding that thiabendazole, an orally available antifungal drug in clinical use for 40 years, also potently inhibits angiogenesis in animal models and in human cells. Moreover, in vivo time-lapse imaging revealed that thiabendazole reversibly disassembles newly established blood vessels, marking it as vascular disrupting agent (VDA) and thus as a potential complementary therapeutic for use in combination with current anti-angiogenic therapies. Importantly, we also show that thiabendazole slows tumor growth and decreases vascular density in preclinical fibrosarcoma xenografts. Thus, an exploration of the evolutionary repurposing of gene networks has led directly to the identification of a potential new therapeutic application for an inexpensive drug that is already approved for clinical use in humans. PMID:22927795

Noninvasive Brain Stimulation in Pediatric Attention-Deficit Hyperactivity Disorder (ADHD): A Review.

PubMed

Rubio, Belen; Boes, Aaron D; Laganiere, Simon; Rotenberg, Alexander; Jeurissen, Danique; Pascual-Leone, Alvaro

2016-05-01

Attention-deficit hyperactivity disorder (ADHD) is one of the most prevalent neurodevelopmental disorders in the pediatric population. The clinical management of ADHD is currently limited by a lack of reliable diagnostic biomarkers and inadequate therapy for a minority of patients who do not respond to standard pharmacotherapy. There is optimism that noninvasive brain stimulation may help to address these limitations. Transcranial magnetic stimulation and transcranial direct current stimulation are 2 methods of noninvasive brain stimulation that modulate cortical excitability and brain network activity. Transcranial magnetic stimulation can be used diagnostically to probe cortical neurophysiology, whereas daily use of repetitive transcranial magnetic stimulation or transcranial direct current stimulation can induce long-lasting and potentially therapeutic changes in targeted networks. In this review, we highlight research showing the potential diagnostic and therapeutic applications of transcranial magnetic stimulation and transcranial direct current stimulation in pediatric ADHD. We also discuss the safety and ethics of using these tools in the pediatric population. © The Author(s) 2015.

A Modularity-Based Method Reveals Mixed Modules from Chemical-Gene Heterogeneous Network

PubMed Central

Song, Jianglong; Tang, Shihuan; Liu, Xi; Gao, Yibo; Yang, Hongjun; Lu, Peng

2015-01-01

For a multicomponent therapy, molecular network is essential to uncover its specific mode of action from a holistic perspective. The molecular system of a Traditional Chinese Medicine (TCM) formula can be represented by a 2-class heterogeneous network (2-HN), which typically includes chemical similarities, chemical-target interactions and gene interactions. An important premise of uncovering the molecular mechanism is to identify mixed modules from complex chemical-gene heterogeneous network of a TCM formula. We thus proposed a novel method (MixMod) based on mixed modularity to detect accurate mixed modules from 2-HNs. At first, we compared MixMod with Clauset-Newman-Moore algorithm (CNM), Markov Cluster algorithm (MCL), Infomap and Louvain on benchmark 2-HNs with known module structure. Results showed that MixMod was superior to other methods when 2-HNs had promiscuous module structure. Then these methods were tested on a real drug-target network, in which 88 disease clusters were regarded as real modules. MixMod could identify the most accurate mixed modules from the drug-target 2-HN (normalized mutual information 0.62 and classification accuracy 0.4524). In the end, MixMod was applied to the 2-HN of Buchang naoxintong capsule (BNC) and detected 49 mixed modules. By using enrichment analysis, we investigated five mixed modules that contained primary constituents of BNC intestinal absorption liquid. As a matter of fact, the findings of in vitro experiments using BNC intestinal absorption liquid were found to highly accord with previous analysis. Therefore, MixMod is an effective method to detect accurate mixed modules from chemical-gene heterogeneous networks and further uncover the molecular mechanism of multicomponent therapies, especially TCM formulae. PMID:25927435

Identification and functional analysis of a core gene module associated with hepatitis C virus-induced human hepatocellular carcinoma progression.

PubMed

Bai, Gaobo; Zheng, Wenling; Ma, Wenli

2018-05-01

Hepatitis C virus (HCV)-induced human hepatocellular carcinoma (HCC) progression may be due to a complex multi-step processes. The developmental mechanism of these processes is worth investigating for the prevention, diagnosis and therapy of HCC. The aim of the present study was to investigate the molecular mechanism underlying the progression of HCV-induced hepatocarcinogenesis. First, the dynamic gene module, consisting of key genes associated with progression between the normal stage and HCC, was identified using the Weighted Gene Co-expression Network Analysis tool from R language. By defining those genes in the module as seeds, the change of co-expression in differentially expressed gene sets in two consecutive stages of pathological progression was examined. Finally, interaction pairs of HCV viral proteins and their directly targeted proteins in the identified module were extracted from the literature and a comprehensive interaction dataset from yeast two-hybrid experiments. By combining the interactions between HCV and their targets, and protein-protein interactions in the Search Tool for the Retrieval of Interacting Genes database (STRING), the HCV-key genes interaction network was constructed and visualized using Cytoscape software 3.2. As a result, a module containing 44 key genes was identified to be associated with HCC progression, due to the dynamic features and functions of those genes in the module. Several important differentially co-expressed gene pairs were identified between non-HCC and HCC stages. In the key genes, cyclin dependent kinase 1 (CDK1), NDC80, cyclin A2 (CCNA2) and rac GTPase activating protein 1 (RACGAP1) were shown to be targeted by the HCV nonstructural proteins NS5A, NS3 and NS5B, respectively. The four genes perform an intermediary role between the HCV viral proteins and the dysfunctional module in the HCV key genes interaction network. These findings provided valuable information for understanding the mechanism of HCV-induced HCC progression and for seeking drug targets for the therapy and prevention of HCC.

Human connectome module pattern detection using a new multi-graph MinMax cut model.

PubMed

De, Wang; Wang, Yang; Nie, Feiping; Yan, Jingwen; Cai, Weidong; Saykin, Andrew J; Shen, Li; Huang, Heng

2014-01-01

Many recent scientific efforts have been devoted to constructing the human connectome using Diffusion Tensor Imaging (DTI) data for understanding the large-scale brain networks that underlie higher-level cognition in human. However, suitable computational network analysis tools are still lacking in human connectome research. To address this problem, we propose a novel multi-graph min-max cut model to detect the consistent network modules from the brain connectivity networks of all studied subjects. A new multi-graph MinMax cut model is introduced to solve this challenging computational neuroscience problem and the efficient optimization algorithm is derived. In the identified connectome module patterns, each network module shows similar connectivity patterns in all subjects, which potentially associate to specific brain functions shared by all subjects. We validate our method by analyzing the weighted fiber connectivity networks. The promising empirical results demonstrate the effectiveness of our method.

Dispatching packets on a global combining network of a parallel computer

DOEpatents

Almasi, Gheorghe [Ardsley, NY; Archer, Charles J [Rochester, MN

2011-07-19

Methods, apparatus, and products are disclosed for dispatching packets on a global combining network of a parallel computer comprising a plurality of nodes connected for data communications using the network capable of performing collective operations and point to point operations that include: receiving, by an origin system messaging module on an origin node from an origin application messaging module on the origin node, a storage identifier and an operation identifier, the storage identifier specifying storage containing an application message for transmission to a target node, and the operation identifier specifying a message passing operation; packetizing, by the origin system messaging module, the application message into network packets for transmission to the target node, each network packet specifying the operation identifier and an operation type for the message passing operation specified by the operation identifier; and transmitting, by the origin system messaging module, the network packets to the target node.

Modular structure of functional networks in olfactory memory.

PubMed

Meunier, David; Fonlupt, Pierre; Saive, Anne-Lise; Plailly, Jane; Ravel, Nadine; Royet, Jean-Pierre

2014-07-15

Graph theory enables the study of systems by describing those systems as a set of nodes and edges. Graph theory has been widely applied to characterize the overall structure of data sets in the social, technological, and biological sciences, including neuroscience. Modular structure decomposition enables the definition of sub-networks whose components are gathered in the same module and work together closely, while working weakly with components from other modules. This processing is of interest for studying memory, a cognitive process that is widely distributed. We propose a new method to identify modular structure in task-related functional magnetic resonance imaging (fMRI) networks. The modular structure was obtained directly from correlation coefficients and thus retained information about both signs and weights. The method was applied to functional data acquired during a yes-no odor recognition memory task performed by young and elderly adults. Four response categories were explored: correct (Hit) and incorrect (False alarm, FA) recognition and correct and incorrect rejection. We extracted time series data for 36 areas as a function of response categories and age groups and calculated condition-based weighted correlation matrices. Overall, condition-based modular partitions were more homogeneous in young than elderly subjects. Using partition similarity-based statistics and a posteriori statistical analyses, we demonstrated that several areas, including the hippocampus, caudate nucleus, and anterior cingulate gyrus, belonged to the same module more frequently during Hit than during all other conditions. Modularity values were negatively correlated with memory scores in the Hit condition and positively correlated with bias scores (liberal/conservative attitude) in the Hit and FA conditions. We further demonstrated that the proportion of positive and negative links between areas of different modules (i.e., the proportion of correlated and anti-correlated areas) accounted for most of the observed differences in signed modularity. Taken together, our results provided some evidence that the neural networks involved in odor recognition memory are organized into modules and that these modular partitions are linked to behavioral performance and individual strategies. Copyright © 2014 Elsevier Inc. All rights reserved.

A biological approach to assembling tissue modules through endothelial capillary network formation.

PubMed

Riesberg, Jeremiah J; Shen, Wei

2015-09-01

To create functional tissues having complex structures, bottom-up approaches to assembling small tissue modules into larger constructs have been emerging. Most of these approaches are based on chemical reactions or physical interactions at the interface between tissue modules. Here we report a biological assembly approach to integrate small tissue modules through endothelial capillary network formation. When adjacent tissue modules contain appropriate extracellular matrix materials and cell types that support robust endothelial capillary network formation, capillary tubules form and grow across the interface, resulting in assembly of the modules into a single, larger construct. It was shown that capillary networks formed in modules of dense fibrin gels seeded with human umbilical vein endothelial cells (HUVECs) and mesenchymal stem cells (MSCs); adjacent modules were firmly assembled into an integrated construct having a strain to failure of 117 ± 26%, a tensile strength of 2208 ± 83 Pa and a Young's modulus of 2548 ± 574 Pa. Under the same culture conditions, capillary networks were absent in modules of dense fibrin gels seeded with either HUVECs or MSCs alone; adjacent modules disconnected even when handled gently. This biological assembly approach eliminates the need for chemical reactions or physical interactions and their associated limitations. In addition, the integrated constructs are prevascularized, and therefore this bottom-up assembly approach may also help address the issue of vascularization, another key challenge in tissue engineering. Copyright © 2015 John Wiley & Sons, Ltd.

Measuring the regulation of keratin filament network dynamics

PubMed Central

Moch, Marcin; Herberich, Gerlind; Aach, Til; Leube, Rudolf E.; Windoffer, Reinhard

2013-01-01

The organization of the keratin intermediate filament cytoskeleton is closely linked to epithelial function. To study keratin network plasticity and its regulation at different levels, tools are needed to localize and measure local network dynamics. In this paper, we present image analysis methods designed to determine the speed and direction of keratin filament motion and to identify locations of keratin filament polymerization and depolymerization at subcellular resolution. Using these methods, we have analyzed time-lapse fluorescence recordings of fluorescent keratin 13 in human vulva carcinoma-derived A431 cells. The fluorescent keratins integrated into the endogenous keratin cytoskeleton, and thereby served as reliable markers of keratin dynamics. We found that increased times after seeding correlated with down-regulation of inward-directed keratin filament movement. Bulk flow analyses further revealed that keratin filament polymerization in the cell periphery and keratin depolymerization in the more central cytoplasm were both reduced. Treating these cells and other human keratinocyte-derived cells with EGF reversed all these processes within a few minutes, coinciding with increased keratin phosphorylation. These results highlight the value of the newly developed tools for identifying modulators of keratin filament network dynamics and characterizing their mode of action, which, in turn, contributes to understanding the close link between keratin filament network plasticity and epithelial physiology. PMID:23757496

Assessing cortical synchronization during transcranial direct current stimulation: A graph-theoretical analysis.

PubMed

Mancini, Matteo; Brignani, Debora; Conforto, Silvia; Mauri, Piercarlo; Miniussi, Carlo; Pellicciari, Maria Concetta

2016-10-15

Transcranial direct current stimulation (tDCS) is a neuromodulation technique that can alter cortical excitability and modulate behaviour in a polarity-dependent way. Despite the widespread use of this method in the neuroscience field, its effects on ongoing local or global (network level) neuronal activity are still not foreseeable. A way to shed light on the neuronal mechanisms underlying the cortical connectivity changes induced by tDCS is provided by the combination of tDCS with electroencephalography (EEG). In this study, twelve healthy subjects underwent online tDCS-EEG recording (i.e., simultaneous), during resting-state, using 19 EEG channels. The protocol involved anodal, cathodal and sham stimulation conditions, with the active and the reference electrodes in the left frontocentral area (FC3) and on the forehead over the right eyebrow, respectively. The data were processed using a network model, based on graph theory and the synchronization likelihood. The resulting graphs were analysed for four frequency bands (theta, alpha, beta and gamma) to evaluate the presence of tDCS-induced differences in synchronization patterns and graph theory measures. The resting state network connectivity resulted altered during tDCS, in a polarity-specific manner for theta and alpha bands. Anodal tDCS weakened synchronization with respect to the baseline over the fronto-central areas in the left hemisphere, for theta band (p<0.05). In contrast, during cathodal tDCS a significant increase in inter-hemispheric synchronization connectivity was observed over the centro-parietal, centro-occipital and parieto-occipital areas for the alpha band (p<0.05). Local graph measures showed a tDCS-induced polarity-specific differences that regarded modifications of network activities rather than specific region properties. Our results show that applying tDCS during the resting state modulates local synchronization as well as network properties in slow frequency bands, in a polarity-specific manner. Copyright © 2016 Elsevier Inc. All rights reserved.

Default Network Modulation and Large-Scale Network Interactivity in Healthy Young and Old Adults

PubMed Central

Schacter, Daniel L.

2012-01-01

We investigated age-related changes in default, attention, and control network activity and their interactions in young and old adults. Brain activity during autobiographical and visuospatial planning was assessed using multivariate analysis and with intrinsic connectivity networks as regions of interest. In both groups, autobiographical planning engaged the default network while visuospatial planning engaged the attention network, consistent with a competition between the domains of internalized and externalized cognition. The control network was engaged for both planning tasks. In young subjects, the control network coupled with the default network during autobiographical planning and with the attention network during visuospatial planning. In old subjects, default-to-control network coupling was observed during both planning tasks, and old adults failed to deactivate the default network during visuospatial planning. This failure is not indicative of default network dysfunction per se, evidenced by default network engagement during autobiographical planning. Rather, a failure to modulate the default network in old adults is indicative of a lower degree of flexible network interactivity and reduced dynamic range of network modulation to changing task demands. PMID:22128194

Application of neural networks to software quality modeling of a very large telecommunications system.

PubMed

Khoshgoftaar, T M; Allen, E B; Hudepohl, J P; Aud, S J

1997-01-01

Society relies on telecommunications to such an extent that telecommunications software must have high reliability. Enhanced measurement for early risk assessment of latent defects (EMERALD) is a joint project of Nortel and Bell Canada for improving the reliability of telecommunications software products. This paper reports a case study of neural-network modeling techniques developed for the EMERALD system. The resulting neural network is currently in the prototype testing phase at Nortel. Neural-network models can be used to identify fault-prone modules for extra attention early in development, and thus reduce the risk of operational problems with those modules. We modeled a subset of modules representing over seven million lines of code from a very large telecommunications software system. The set consisted of those modules reused with changes from the previous release. The dependent variable was membership in the class of fault-prone modules. The independent variables were principal components of nine measures of software design attributes. We compared the neural-network model with a nonparametric discriminant model and found the neural-network model had better predictive accuracy.

Gene co-expression network analysis in Rhodobacter capsulatus and application to comparative expression analysis of Rhodobacter sphaeroides

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

Pena-Castillo, Lourdes; Mercer, Ryan; Gurinovich, Anastasia

2014-08-28

The genus Rhodobacter contains purple nonsulfur bacteria found mostly in freshwater environments. Representative strains of two Rhodobacter species, R. capsulatus and R. sphaeroides, have had their genomes fully sequenced and both have been the subject of transcriptional profiling studies. Gene co-expression networks can be used to identify modules of genes with similar expression profiles. Functional analysis of gene modules can then associate co-expressed genes with biological pathways, and network statistics can determine the degree of module preservation in related networks. In this paper, we constructed an R. capsulatus gene co-expression network, performed functional analysis of identified gene modules, and investigatedmore » preservation of these modules in R. capsulatus proteomics data and in R. sphaeroides transcriptomics data. Results: The analysis identified 40 gene co-expression modules in R. capsulatus. Investigation of the module gene contents and expression profiles revealed patterns that were validated based on previous studies supporting the biological relevance of these modules. We identified two R. capsulatus gene modules preserved in the protein abundance data. We also identified several gene modules preserved between both Rhodobacter species, which indicate that these cellular processes are conserved between the species and are candidates for functional information transfer between species. Many gene modules were non-preserved, providing insight into processes that differentiate the two species. In addition, using Local Network Similarity (LNS), a recently proposed metric for expression divergence, we assessed the expression conservation of between-species pairs of orthologs, and within-species gene-protein expression profiles. Conclusions: Our analyses provide new sources of information for functional annotation in R. capsulatus because uncharacterized genes in modules are now connected with groups of genes that constitute a joint functional annotation. We identified R. capsulatus modules enriched with genes for ribosomal proteins, porphyrin and bacteriochlorophyll anabolism, and biosynthesis of secondary metabolites to be preserved in R. sphaeroides whereas modules related to RcGTA production and signalling showed lack of preservation in R. sphaeroides. In addition, we demonstrated that network statistics may also be applied within-species to identify congruence between mRNA expression and protein abundance data for which simple correlation measurements have previously had mixed results.« less

Rhythmic control of endocannabinoids in the rat pineal gland.

PubMed

Koch, Marco; Ferreirós, Nerea; Geisslinger, Gerd; Dehghani, Faramarz; Korf, Horst-Werner

2015-01-01

Endocannabinoids modulate neuroendocrine networks by directly targeting cannabinoid receptors. The time-hormone melatonin synchronizes these networks with external light condition and guarantees time-sensitive and ecologically well-adapted behaviors. Here, the endocannabinoid arachidonoyl ethanolamide (AEA) showed rhythmic changes in rat pineal glands with higher levels during the light-period and reduced amounts at the onset of darkness. Norepinephrine, the essential stimulus for nocturnal melatonin biosynthesis, acutely down-regulated AEA and other endocannabinoids in cultured pineal glands. These temporal dynamics suggest that AEA exerts time-dependent autocrine and/or paracrine functions within the pineal. Moreover, endocananbinoids may be released from the pineal into the CSF or blood stream.

Semantic integration to identify overlapping functional modules in protein interaction networks

PubMed Central

Cho, Young-Rae; Hwang, Woochang; Ramanathan, Murali; Zhang, Aidong

2007-01-01

Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO) annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification. PMID:17650343

Oxytocin receptors modulate a social salience neural network in male prairie voles.

PubMed

Johnson, Zachary V; Walum, Hasse; Xiao, Yao; Riefkohl, Paula C; Young, Larry J

2017-01-01

Social behavior is regulated by conserved neural networks across vertebrates. Variation in the organization of neuropeptide systems across these networks is thought to contribute to individual and species diversity in network function during social contexts. For example, oxytocin (OT) is an ancient neuropeptide that binds to OT receptors (OTRs) in the brain and modulates social and reproductive behavior across vertebrate species, including humans. Central OTRs exhibit extraordinarily diverse expression patterns that are associated with individual and species differences in social behavior. In voles, OTR density in the nucleus accumbens (NAc)-a region important for social and reward learning-is associated with individual and species variation in social attachment behavior. Here we test whether OTRs in the NAc modulate a social salience network (SSN)-a network of interconnected brain nuclei thought to encode valence and incentive salience of sociosensory cues-during a social context in the socially monogamous male prairie vole. Using a selective OTR antagonist, we test whether activation of OTRs in the NAc during sociosexual interaction and mating modulates expression of the immediate early gene product Fos across nuclei of the SSN. We show that blockade of endogenous OTR signaling in the NAc during sociosexual interaction and mating does not strongly modulate levels of Fos expression in individual nodes of the network, but strongly modulates patterns of correlated Fos expression between the NAc and other SSN nuclei. Published by Elsevier Inc.

Multi-equilibrium property of metabolic networks: SSI module.

PubMed

Lei, Hong-Bo; Zhang, Ji-Feng; Chen, Luonan

2011-06-20

Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI) metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module.

Multi-equilibrium property of metabolic networks: SSI module

PubMed Central

2011-01-01

Background Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI) metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. Results In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. Conclusions In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module. PMID:21689474

INFORMAS (International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support): summary and future directions.

PubMed

Kumanyika, S

2013-10-01

This supplement presents the foundational elements for INFORMAS (International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support). As explained in the overview article by Swinburn and colleagues, INFORMAS has a compelling rationale and has set forth clear objectives, outcomes, principles and frameworks for monitoring and benchmarking key aspects of food environments and the policies and actions that influence the healthiness of food environments. This summary highlights the proposed monitoring approaches for the 10 interrelated INFORMAS modules: public and private sector policies and actions; key aspects of food environments (food composition, labelling, promotion, provision, retail, prices, and trade and investment) and population outcomes (diet quality). This ambitious effort should be feasible when approached in a step-wise manner, taking into account existing monitoring efforts, data sources, country contexts and capacity, and when adequately resourced. After protocol development and pilot testing of the modules, INFORMAS aims to be a sustainable, low-cost monitoring framework. Future directions relate to institutionalization, implementation and, ultimately, to leveraging INFORMAS data in ways that will bring key drivers of food environments into alignment with public health goals. © 2013 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of the International Association for the Study of Obesity.

Melatonin, Noncoding RNAs, Messenger RNA Stability and Epigenetics—Evidence, Hints, Gaps and Perspectives

PubMed Central

Hardeland, Rüdiger

2014-01-01

Melatonin is a highly pleiotropic regulator molecule, which influences numerous functions in almost every organ and, thus, up- or down-regulates many genes, frequently in a circadian manner. Our understanding of the mechanisms controlling gene expression is actually now expanding to a previously unforeseen extent. In addition to classic actions of transcription factors, gene expression is induced, suppressed or modulated by a number of RNAs and proteins, such as miRNAs, lncRNAs, piRNAs, antisense transcripts, deadenylases, DNA methyltransferases, histone methylation complexes, histone demethylases, histone acetyltransferases and histone deacetylases. Direct or indirect evidence for involvement of melatonin in this network of players has originated in different fields, including studies on central and peripheral circadian oscillators, shift work, cancer, inflammation, oxidative stress, aging, energy expenditure/obesity, diabetes type 2, neuropsychiatric disorders, and neurogenesis. Some of the novel modulators have also been shown to participate in the control of melatonin biosynthesis and melatonin receptor expression. Future work will need to augment the body of evidence on direct epigenetic actions of melatonin and to systematically investigate its role within the network of oscillating epigenetic factors. Moreover, it will be necessary to discriminate between effects observed under conditions of well-operating and deregulated circadian clocks, and to explore the possibilities of correcting epigenetic malprogramming by melatonin. PMID:25310649

Sex differences in how social networks and relationship quality influence experimental pain sensitivity.

PubMed

Vigil, Jacob M; Rowell, Lauren N; Chouteau, Simone; Chavez, Alexandre; Jaramillo, Elisa; Neal, Michael; Waid, David

2013-01-01

This is the first study to examine how both structural and functional components of individuals' social networks may moderate the association between biological sex and experimental pain sensitivity. One hundred and fifty-two healthy adults (mean age = 22yrs., 53% males) were measured for cold pressor task (CPT) pain sensitivity (i.e., intensity ratings) and core aspects of social networks (e.g., proportion of friends vs. family, affection, affirmation, and aid). Results showed consistent sex differences in how social network structures and intimate relationship functioning modulated pain sensitivity. Females showed higher pain sensitivity when their social networks consisted of a higher proportion of intimate types of relationship partners (e.g., kin vs. non kin), when they had known their network partners for a longer period of time, and when they reported higher levels of logistical support from their significant other (e.g., romantic partner). Conversely, males showed distinct patterns in the opposite direction, including an association between higher levels of logistical support from one's significant other and lower CPT pain intensity. These findings show for the first time that the direction of sex differences in exogenous pain sensitivity is likely dependent on fundamental components of the individual's social environment. The utility of a social-signaling perspective of pain behaviors for examining, comparing, and interpreting individual and group differences in experimental and clinical pain reports is discussed.

Sex Differences in How Social Networks and Relationship Quality Influence Experimental Pain Sensitivity

PubMed Central

Vigil, Jacob M.; Rowell, Lauren N.; Chouteau, Simone; Chavez, Alexandre; Jaramillo, Elisa; Neal, Michael; Waid, David

2013-01-01

This is the first study to examine how both structural and functional components of individuals’ social networks may moderate the association between biological sex and experimental pain sensitivity. One hundred and fifty-two healthy adults (mean age = 22yrs., 53% males) were measured for cold pressor task (CPT) pain sensitivity (i.e., intensity ratings) and core aspects of social networks (e.g., proportion of friends vs. family, affection, affirmation, and aid). Results showed consistent sex differences in how social network structures and intimate relationship functioning modulated pain sensitivity. Females showed higher pain sensitivity when their social networks consisted of a higher proportion of intimate types of relationship partners (e.g., kin vs. non kin), when they had known their network partners for a longer period of time, and when they reported higher levels of logistical support from their significant other (e.g., romantic partner). Conversely, males showed distinct patterns in the opposite direction, including an association between higher levels of logistical support from one’s significant other and lower CPT pain intensity. These findings show for the first time that the direction of sex differences in exogenous pain sensitivity is likely dependent on fundamental components of the individual’s social environment. The utility of a social-signaling perspective of pain behaviors for examining, comparing, and interpreting individual and group differences in experimental and clinical pain reports is discussed. PMID:24223836

Coarse-graining and self-dissimilarity of complex networks

NASA Astrophysics Data System (ADS)

Itzkovitz, Shalev; Levitt, Reuven; Kashtan, Nadav; Milo, Ron; Itzkovitz, Michael; Alon, Uri

2005-01-01

Can complex engineered and biological networks be coarse-grained into smaller and more understandable versions in which each node represents an entire pattern in the original network? To address this, we define coarse-graining units as connectivity patterns which can serve as the nodes of a coarse-grained network and present algorithms to detect them. We use this approach to systematically reverse-engineer electronic circuits, forming understandable high-level maps from incomprehensible transistor wiring: first, a coarse-grained version in which each node is a gate made of several transistors is established. Then the coarse-grained network is itself coarse-grained, resulting in a high-level blueprint in which each node is a circuit module made of many gates. We apply our approach also to a mammalian protein signal-transduction network, to find a simplified coarse-grained network with three main signaling channels that resemble multi-layered perceptrons made of cross-interacting MAP-kinase cascades. We find that both biological and electronic networks are “self-dissimilar,” with different network motifs at each level. The present approach may be used to simplify a variety of directed and nondirected, natural and designed networks.

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

PubMed Central

2011-01-01

Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis. PMID:22784571

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network.

PubMed

Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

2011-01-01

Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

Network-based machine learning and graph theory algorithms for precision oncology.

PubMed

Zhang, Wei; Chien, Jeremy; Yong, Jeongsik; Kuang, Rui

2017-01-01

Network-based analytics plays an increasingly important role in precision oncology. Growing evidence in recent studies suggests that cancer can be better understood through mutated or dysregulated pathways or networks rather than individual mutations and that the efficacy of repositioned drugs can be inferred from disease modules in molecular networks. This article reviews network-based machine learning and graph theory algorithms for integrative analysis of personal genomic data and biomedical knowledge bases to identify tumor-specific molecular mechanisms, candidate targets and repositioned drugs for personalized treatment. The review focuses on the algorithmic design and mathematical formulation of these methods to facilitate applications and implementations of network-based analysis in the practice of precision oncology. We review the methods applied in three scenarios to integrate genomic data and network models in different analysis pipelines, and we examine three categories of network-based approaches for repositioning drugs in drug-disease-gene networks. In addition, we perform a comprehensive subnetwork/pathway analysis of mutations in 31 cancer genome projects in the Cancer Genome Atlas and present a detailed case study on ovarian cancer. Finally, we discuss interesting observations, potential pitfalls and future directions in network-based precision oncology.

Compact Feeding Network for Array Radiations of Spoof Surface Plasmon Polaritons

NASA Astrophysics Data System (ADS)

Xu, Jun Jun; Yin, Jia Yuan; Zhang, Hao Chi; Cui, Tie Jun

2016-03-01

We propose a splitter feeding network for array radiations of spoof surface plasmon polaritons (SPPs), which are guided by ultrathin corrugated metallic strips. Based on the coupled mode theory, SPP fields along a single waveguide in a certain frequency range can be readily coupled into two adjacent branch waveguides with the same propagation constants. We propose to load U-shaped particles anti-symmetrically at the ends of such two branch waveguides, showing a high integration degree of the feeding network. By controlling linear phase modulations produced by the U-shaped particle chain, we demonstrate theoretically and experimentally that the SPP fields based on bound modes can be efficiently radiated to far fields in broadside direction. The proposed method shows that the symmetry of electromagnetic field modes can be exploited to the SPP transmission network, providing potential solutions to compact power dividers and combiners for microwave and optical devices and systems.

Optical interconnect for large-scale systems

NASA Astrophysics Data System (ADS)

Dress, William

2013-02-01

This paper presents a switchless, optical interconnect module that serves as a node in a network of identical distribution modules for large-scale systems. Thousands to millions of hosts or endpoints may be interconnected by a network of such modules, avoiding the need for multi-level switches. Several common network topologies are reviewed and their scaling properties assessed. The concept of message-flow routing is discussed in conjunction with the unique properties enabled by the optical distribution module where it is shown how top-down software control (global routing tables, spanning-tree algorithms) may be avoided.

Different Types of Laughter Modulate Connectivity within Distinct Parts of the Laughter Perception Network

PubMed Central

Ethofer, Thomas; Brück, Carolin; Alter, Kai; Grodd, Wolfgang; Kreifelts, Benjamin

2013-01-01

Laughter is an ancient signal of social communication among humans and non-human primates. Laughter types with complex social functions (e.g., taunt and joy) presumably evolved from the unequivocal and reflex-like social bonding signal of tickling laughter already present in non-human primates. Here, we investigated the modulations of cerebral connectivity associated with different laughter types as well as the effects of attention shifts between implicit and explicit processing of social information conveyed by laughter using functional magnetic resonance imaging (fMRI). Complex social laughter types and tickling laughter were found to modulate connectivity in two distinguishable but partially overlapping parts of the laughter perception network irrespective of task instructions. Connectivity changes, presumably related to the higher acoustic complexity of tickling laughter, occurred between areas in the prefrontal cortex and the auditory association cortex, potentially reflecting higher demands on acoustic analysis associated with increased information load on auditory attention, working memory, evaluation and response selection processes. In contrast, the higher degree of socio-relational information in complex social laughter types was linked to increases of connectivity between auditory association cortices, the right dorsolateral prefrontal cortex and brain areas associated with mentalizing as well as areas in the visual associative cortex. These modulations might reflect automatic analysis of acoustic features, attention direction to informative aspects of the laughter signal and the retention of those in working memory during evaluation processes. These processes may be associated with visual imagery supporting the formation of inferences on the intentions of our social counterparts. Here, the right dorsolateral precentral cortex appears as a network node potentially linking the functions of auditory and visual associative sensory cortices with those of the mentalizing-associated anterior mediofrontal cortex during the decoding of social information in laughter. PMID:23667619

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

PubMed

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

2013-01-01

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

The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository.

PubMed

McDonald, Amalia R; Muraskin, Jordan; Dam, Nicholas T Van; Froehlich, Caroline; Puccio, Benjamin; Pellman, John; Bauer, Clemens C C; Akeyson, Alexis; Breland, Melissa M; Calhoun, Vince D; Carter, Steven; Chang, Tiffany P; Gessner, Chelsea; Gianonne, Alyssa; Giavasis, Steven; Glass, Jamie; Homann, Steven; King, Margaret; Kramer, Melissa; Landis, Drew; Lieval, Alexis; Lisinski, Jonathan; Mackay-Brandt, Anna; Miller, Brittny; Panek, Laura; Reed, Hayley; Santiago, Christine; Schoell, Eszter; Sinnig, Richard; Sital, Melissa; Taverna, Elise; Tobe, Russell; Trautman, Kristin; Varghese, Betty; Walden, Lauren; Wang, Runtang; Waters, Abigail B; Wood, Dylan C; Castellanos, F Xavier; Leventhal, Bennett; Colcombe, Stanley J; LaConte, Stephen; Milham, Michael P; Craddock, R Cameron

2017-02-01

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants. Each session includes acquisition of one whole-brain anatomical scan and whole-brain echo-planar imaging (EPI) scans, acquired during the aforementioned tasks and resting state. The data includes several self-report measures related to perseverative thinking, emotion regulation, and imaginative processes, along with a behavioral measure of rapid visual information processing. Technical validation of the data confirms that the tasks deactivate and activate the DMN as expected. Group level analysis of the neurofeedback data indicates that the participants are able to modulate their DMN with considerable inter-subject variability. Preliminary analysis of behavioral responses and specifically self-reported sleep indicate that as many as 73 participants may need to be excluded from an analysis depending on the hypothesis being tested. The present data are linked to the enhanced Nathan Kline Institute, Rockland Sample and builds on the comprehensive neuroimaging and deep phenotyping available therein. As limited information is presently available about individual differences in the capacity to directly modulate the default mode network, these data provide a unique opportunity to examine DMN modulation ability in relation to numerous phenotypic characteristics. Copyright © 2016 Elsevier Inc. All rights reserved.

Applications of 1.55 μm optically injection-locked VCSELs in wavelength division multiplexed passive optical networks

NASA Astrophysics Data System (ADS)

Wong, Elaine; Zhao, Xiaoxue; Chang-Hasnain, Connie J.; Hofmann, Werner; Amann, Marcus C.

2007-11-01

In this paper, we will discuss the utilization of optically injection-locked (OIL) 1.55 μm vertical-cavity surface-emitting lasers (VCSELs) for operation as low-cost, stable, directly modulated, and potentially uncooled transmitters, whereby the injection-locking master source is furnished by modulated downstream signals. Such a transmitter will find useful application in wavelength division multiplexed passive optical networks (WDM-PONs) which is actively being developed to meet the ever-increasing bandwidth demands of end users. Our scheme eliminates the need for external injection locking optical sources, external modulators, and wavelength stabilization circuitry. We show through experiments that the injection-locked VCSEL favors low injection powers and responds only strongly to the carrier but not the modulated data of the downstream signal. Further, we will discuss results from experimental studies performed on the dependence of OIL-VCSELs in bidirectional networks on the degree of Rayleigh backscattered signal and extinction ratio. We show that error-free upstream performance can be achieved when the upstream signal to Rayleigh backscattering ratio is greater than 13.4 dB, and with minimal dependence on the downstream extinction ratio. We will also review a fault monitoring and localization scheme based on a highly-sensitive yet low-cost monitor comprising a low output power broadband source and low bandwidth detectors. The proposed scheme benefits from the high reflectivity top distributed Bragg reflector mirror of the OIL-VCSEL, incurring only a minimal penalty on the upstream transmissions of the existing infrastructure. Such a scheme provides fault monitoring without having to further invest in the upgrade of customer premises.

Re-modulated technology of WDM-PON employing different DQPSK downstream signals

NASA Astrophysics Data System (ADS)

Gao, Chao; Xin, Xiang-jun; Yu, Chong-xiu

2012-11-01

This paper proposes a kind of modulation architecture for wavelength-division-multiplexing passive optical network (WDMPON) employing optical differential quadrature phase shift keying (DQPSK) downstream signals and two different modulation formats of re-modulated upstream signals. At the optical line terminal (OLT), 10 Gbit/s signal is modulated with DQPSK. At the optical network unit (ONU), part of the downstream signal is re-modulated with on-off keying (OOK) or inverse-return-to-zero (IRZ). Simulation results show the impact on the system employing NRZ, RZ and carrier-suppressed return-to-zero (CSRZ). The analyses also reflect that the architecture can restrain chromatic dispersion and channel crosstalk, which makes it the best architecture of access network in the future.

Characterization of submillisecond response optical addressing phase modulator based on low light scattering polymer network liquid crystal

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

Xiangjie, Zhao, E-mail: zxjdouble@163.com, E-mail: zxjdouble@gmail.com; Cangli, Liu; Jiazhu, Duan

Optically addressed conventional nematic liquid crystal spatial light modulator has attracted wide research interests. But the slow response speed limited its further application. In this paper, polymer network liquid crystal (PNLC) was proposed to replace the conventional nematic liquid crystal to enhance the response time to the order of submillisecond. The maximum light scattering of the employed PNLC was suppressed to be less than 2% at 1.064 μm by optimizing polymerization conditions and selecting large viscosity liquid crystal as solvent. The occurrence of phase ripple phenomenon due to electron diffusion and drift in photoconductor was found to deteriorate the phase modulationmore » effect of the optical addressed PNLC phase modulator. The wavelength effect and AC voltage frequency effect on the on state dynamic response of phase change was investigated by experimental methods. These effects were interpreted by electron diffusion and drift theory based on the assumption that free electron was inhomogeneously distributed in accordance with the writing beam intensity distribution along the incident direction. The experimental results indicated that the phase ripple could be suppressed by optimizing the wavelength of the writing beam and the driving AC voltage frequency when varying the writing beam intensity to generate phase change in 2π range. The modulation transfer function was also measured.« less

Investigating Focal Connectivity Deficits in Alzheimer's Disease Using Directional Brain Networks Derived from Resting-State fMRI

PubMed Central

Zhao, Sinan; Rangaprakash, D; Venkataraman, Archana; Liang, Peipeng; Deshpande, Gopikrishna

2017-01-01

Connectivity analysis of resting-state fMRI has been widely used to identify biomarkers of Alzheimer's disease (AD) based on brain network aberrations. However, it is not straightforward to interpret such connectivity results since our understanding of brain functioning relies on regional properties (activations and morphometric changes) more than connections. Further, from an interventional standpoint, it is easier to modulate the activity of regions (using brain stimulation, neurofeedback, etc.) rather than connections. Therefore, we employed a novel approach for identifying focal directed connectivity deficits in AD compared to healthy controls. In brief, we present a model of directed connectivity (using Granger causality) that characterizes the coupling among different regions in healthy controls and Alzheimer's disease. We then characterized group differences using a (between-subject) generative model of pathology, which generates latent connectivity variables that best explain the (within-subject) directed connectivity. Crucially, our generative model at the second (between-subject) level explains connectivity in terms of local or regionally specific abnormalities. This allows one to explain disconnections among multiple regions in terms of regionally specific pathology; thereby offering a target for therapeutic intervention. Two foci were identified, locus coeruleus in the brain stem and right orbitofrontal cortex. Corresponding disrupted connectivity network associated with the foci showed that the brainstem is the critical focus of disruption in AD. We further partitioned the aberrant connectomic network into four unique sub-networks, which likely leads to symptoms commonly observed in AD. Our findings suggest that fMRI studies of AD, which have been largely cortico-centric, could in future investigate the role of brain stem in AD. PMID:28729831

INfORM: Inference of NetwOrk Response Modules.

PubMed

Marwah, Veer Singh; Kinaret, Pia Anneli Sofia; Serra, Angela; Scala, Giovanni; Lauerma, Antti; Fortino, Vittorio; Greco, Dario

2018-06-15

Detecting and interpreting responsive modules from gene expression data by using network-based approaches is a common but laborious task. It often requires the application of several computational methods implemented in different software packages, forcing biologists to compile complex analytical pipelines. Here we introduce INfORM (Inference of NetwOrk Response Modules), an R shiny application that enables non-expert users to detect, evaluate and select gene modules with high statistical and biological significance. INfORM is a comprehensive tool for the identification of biologically meaningful response modules from consensus gene networks inferred by using multiple algorithms. It is accessible through an intuitive graphical user interface allowing for a level of abstraction from the computational steps. INfORM is freely available for academic use at https://github.com/Greco-Lab/INfORM. Supplementary data are available at Bioinformatics online.

Noncoherent Physical-Layer Network Coding with FSK Modulation: Relay Receiver Design Issues

DTIC Science & Technology

2011-03-01

222 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 59, NO. 9, SEPTEMBER 2011 2595 Noncoherent Physical-Layer Network Coding with FSK Modulation: Relay... noncoherent reception, channel estima- tion. I. INTRODUCTION IN the two-way relay channel (TWRC), a pair of sourceterminals exchange information...2011 4. TITLE AND SUBTITLE Noncoherent Physical-Layer Network Coding with FSK Modulation:Relay Receiver Design Issues 5a. CONTRACT NUMBER 5b

Hybrid optical CDMA-FSO communications network under spatially correlated gamma-gamma scintillation.

PubMed

Jurado-Navas, Antonio; Raddo, Thiago R; Garrido-Balsells, José María; Borges, Ben-Hur V; Olmos, Juan José Vegas; Monroy, Idelfonso Tafur

2016-07-25

In this paper, we propose a new hybrid network solution based on asynchronous optical code-division multiple-access (OCDMA) and free-space optical (FSO) technologies for last-mile access networks, where fiber deployment is impractical. The architecture of the proposed hybrid OCDMA-FSO network is thoroughly described. The users access the network in a fully asynchronous manner by means of assigned fast frequency hopping (FFH)-based codes. In the FSO receiver, an equal gain-combining technique is employed along with intensity modulation and direct detection. New analytical formalisms for evaluating the average bit error rate (ABER) performance are also proposed. These formalisms, based on the spatially correlated gamma-gamma statistical model, are derived considering three distinct scenarios, namely, uncorrelated, totally correlated, and partially correlated channels. Numerical results show that users can successfully achieve error-free ABER levels for the three scenarios considered as long as forward error correction (FEC) algorithms are employed. Therefore, OCDMA-FSO networks can be a prospective alternative to deliver high-speed communication services to access networks with deficient fiber infrastructure.

Genome-wide protein-protein interactions and protein function exploration in cyanobacteria

PubMed Central

Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu

2015-01-01

Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and “interologs” in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria. PMID:26490033

WGCNA: an R package for weighted correlation network analysis.

PubMed

Langfelder, Peter; Horvath, Steve

2008-12-29

Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.

Delta-9-Tetrahydrocannabinol Potentiates Fear Memory Salience Through Functional Modulation of Mesolimbic Dopaminergic Activity States.

PubMed

Fitoussi, Aurelie; Zunder, Jordan; Tan, Huibing; Laviolette, Steven R

2018-05-18

Chronic or acute exposure to delta-9-tetrahydrocannabinol (THC), the main psychoactive compound in cannabis, has been associated with numerous neuropsychiatric side-effects, including dysregulation of emotional processing and associative memory formation. Clinical and pre-clinical evidence suggests that the effects of THC are due to the ability to modulate mesolimbic dopamine (DA) activity states in the nucleus accumbens (NAc) and ventral tegmental area (VTA). Nevertheless, the mechanisms by which THC modulates mesolimbic DA function and emotional processing are not well understood. Using an olfactory associative fear memory procedure combined with in vivo neuronal electrophysiology, we examined the effects of direct THC microinfusions targeting the shell region of the NAc (NASh) and examined how THC may modulate the processing of fear-related emotional memory and concomitant activity states of the mesolimbic DA system. We report that intra-NASh THC dose-dependently potentiates the emotional salience of normally sub-threshold fear-conditioning cues. These effects were dependent upon intra-VTA transmission through GABAergic receptor mechanisms and intra-NASh DAergic transmission. Furthermore, doses of intra-NASh THC that potentiated fear memory salience were found to modulate intra-VTA neuronal network activity by increasing the spontaneous firing and bursting frequency of DAergic neurons whilst decreasing the activity levels of a subpopulation of putative GABAergic VTA neurons. These findings demonstrate that THC can act directly in the NASh to modulate mesolimbic activity states and induce disturbances in emotional salience and memory formation through modulation of VTA DAergic transmission. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Slotline fed microstrip antenna array modules

NASA Technical Reports Server (NTRS)

Lo, Y. T.; Oberhart, M. L.; Brenneman, J. S.; Aoyagi, P.; Moore, J.; Lee, R. Q. H.

1988-01-01

A feed network comprised of a combination of coplanar waveguide and slot transmission line is described for use in an array module of four microstrip elements. Examples of the module incorporating such networks are presented as well as experimentally obtained impedance and radiation characteristics.

Altered brain network modules induce helplessness in major depressive disorder.

PubMed

Peng, Daihui; Shi, Feng; Shen, Ting; Peng, Ziwen; Zhang, Chen; Liu, Xiaohua; Qiu, Meihui; Liu, Jun; Jiang, Kaida; Fang, Yiru; Shen, Dinggang

2014-10-01

The abnormal brain functional connectivity (FC) has been assumed to be a pathophysiological aspect of major depressive disorder (MDD). However, it is poorly understood, regarding the underlying patterns of global FC network and their relationships with the clinical characteristics of MDD. Resting-state functional magnetic resonance imaging data were acquired from 16 first episode, medication-naïve MDD patients and 16 healthy control subjects. The global FC network was constructed using 90 brain regions. The global topological patterns, e.g., small-worldness and modularity, and their relationships with depressive characteristics were investigated. Furthermore, the participant coefficient and module degree of MDD patients were measured to reflect the regional roles in module network, and the impairment of FC was examined by network based statistic. Small-world property was not altered in MDD. However, MDD patients exhibited 5 atypically reorganized modules compared to the controls. A positive relationship was also found among MDD patients between the intra-module I and helplessness factor evaluated via the Hamilton Depression Scale. Specifically, eight regions exhibited the abnormal participant coefficient or module degree, e.g., left superior orbital frontal cortex and right amygdala. The decreased FC was identified among the sub-network of 24 brain regions, e.g., frontal cortex, supplementary motor area, amygdala, thalamus, and hippocampus. The limited size of MDD samples precluded meaningful study of distinct clinical characteristics in relation to aberrant FC. The results revealed altered patterns of brain module network at the global level in MDD patients, which might contribute to the feelings of helplessness. Copyright © 2014 Elsevier B.V. All rights reserved.

Altered brain network modules induce helplessness in major depressive disorder

PubMed Central

Peng, Daihui; Shi, Feng; Shen, Ting; Peng, Ziwen; Zhang, Chen; Liu, Xiaohua; Qiu, Meihui; Liu, Jun; Jiang, Kaida; Shen, Dinggang

2017-01-01

Objective The abnormal brain functional connectivity (FC) has been assumed to be a pathophysiological aspect of major depressive disorder (MDD). However, it is poorly understood, regarding the underlying patterns of global FC network and their relationships with the clinical characteristics of MDD. Methods Resting-state functional magnetic resonance imaging data were acquired from 16 first episode, medication-naïve MDD patients and 16 healthy control subjects. The global FC network was constructed using 90 brain regions. The global topological patterns, e.g., small-worldness and modularity, and their relationships with depressive characteristics were investigated. Furthermore, the participant coefficient and module degree of MDD patients were measured to reflect the regional roles in module network, and the impairment of FC was examined by network based statistic. Results Small-world property was not altered in MDD. However, MDD patients exhibited 5 atypically reorganized modules compared to the controls. A positive relationship was also found among MDD patients between the intra-module I and helplessness factor evaluated via the Hamilton Depression Scale. Specifically, eight regions exhibited the abnormal participant coefficient or module degree, e.g., left superior orbital frontal cortex and right amygdala. The decreased FC was identified among the sub-network of 24 brain regions, e.g., frontal cortex, supplementary motor area, amygdala, thalamus, and hippocampus. Limitation The limited size of MDD samples precluded meaningful study of distinct clinical characteristics in relation to aberrant FC. Conclusions The results revealed altered patterns of brain module network at the global level in MDD patients, which might contribute to the feelings of helplessness. PMID:25033474

Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit.

PubMed

Eriksson, O; Brinne, B; Zhou, Y; Björkegren, J; Tegnér, J

2009-03-01

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a 'tearing-and-zooming' approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits. [Includes supplementary material].

Modulation for emergent networks: serotonin and dopamine.

PubMed

Weng, Juyang; Paslaski, Stephen; Daly, James; VanDam, Courtland; Brown, Jacob

2013-05-01

In autonomous learning, value-sensitive experiences can improve the efficiency of learning. A learning network needs be motivated so that the limited computational resources and the limited lifetime are devoted to events that are of high value for the agent to compete in its environment. The neuromodulatory system of the brain is mainly responsible for developing such a motivation system. Although reinforcement learning has been extensively studied, many existing models are symbolic whose internal nodes or modules have preset meanings. Neural networks have been used to automatically generate internal emergent representations. However, modeling an emergent motivational system for neural networks is still a great challenge. By emergent, we mean that the internal representations emerge autonomously through interactions with the external environments. This work proposes a generic emergent modulatory system for emergent networks, which includes two subsystems - the serotonin system and the dopamine system. The former signals a large class of stimuli that are intrinsically aversive (e.g., stress or pain). The latter signals a large class of stimuli that are intrinsically appetitive (e.g., pleasure or sweet). We experimented with this motivational system for two settings. The first is a visual recognition setting to investigate how such a system can learn through interactions with a teacher, who does not directly give answers, but only punishments and rewards. The second is a setting for wandering in the presence of a friend and a foe. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dismissing Attachment Characteristics Dynamically Modulate Brain Networks Subserving Social Aversion

PubMed Central

Krause, Anna Linda; Borchardt, Viola; Li, Meng; van Tol, Marie-José; Demenescu, Liliana Ramona; Strauss, Bernhard; Kirchmann, Helmut; Buchheim, Anna; Metzger, Coraline D.; Nolte, Tobias; Walter, Martin

2016-01-01

Attachment patterns influence actions, thoughts and feeling through a person’s “inner working model”. Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest functional magnetic resonance imaging (fMRI)-experiment, presenting auditory narratives prototypical of dismissing attachment representations to investigate their effect on 23 healthy males. We then examined effects of participants’ attachment style and childhood trauma on brain state changes using seed-based functional connectivity (FC) analyses, and finally tested whether subjective differences in responsivity to narratives could be predicted by baseline network states. In comparison to a baseline state, we observed increased FC in a previously described “social aversion network” including dorsal anterior cingulated cortex (dACC) and left anterior middle temporal gyrus (aMTG) specifically after exposure to insecure-dismissing attachment narratives. Increased dACC-seeded FC within the social aversion network was positively related to the participants’ avoidant attachment style and presence of a history of childhood trauma. Anxious attachment style on the other hand was positively correlated with FC between the dACC and a region outside of the “social aversion network”, namely the dorsolateral prefrontal cortex, which suggests decreased network segregation as a function of anxious attachment. Finally, the extent of subjective experience of friendliness towards the dismissing narrative was predicted by low baseline FC-values between hippocampus and inferior parietal lobule (IPL). Taken together, our study demonstrates an activation of networks related to social aversion in terms of increased connectivity after listening to insecure-dismissing attachment narratives. A causal interrelation of brain state changes and subsequent changes in social reactivity was further supported by our observation of direct prediction of neuronal responses by individual attachment and trauma characteristics and reversely prediction of subjective experience by intrinsic functional connections. We consider these findings of activation of within-network and between-network connectivity modulated by inter-individual differences as substantial for the understanding of interpersonal processes, particularly in clinical settings. PMID:27014016

Silicon Modulators, Switches and Sub-systems for Optical Interconnect

NASA Astrophysics Data System (ADS)

Li, Qi

Silicon photonics is emerging as a promising platform for manufacturing and integrating photonic devices for light generation, modulation, switching and detection. The compatibility with existing CMOS microelectronic foundries and high index contrast in silicon could enable low cost and high performance photonic systems, which find many applications in optical communication, data center networking and photonic network-on-chip. This thesis first develops and demonstrates several experimental work on high speed silicon modulators and switches with record performance and novel functionality. A 8x40 Gb/s transmitter based on silicon microrings is first presented. Then an end-to-end link using microrings for Binary Phase Shift Keying (BPSK) modulation and demodulation is shown, and its performance with conventional BPSK modulation/ demodulation techniques is compared. Next, a silicon traveling-wave Mach- Zehnder modulator is demonstrated at data rate up to 56 Gb/s for OOK modulation and 48 Gb/s for BPSK modulation, showing its capability at high speed communication systems. Then a single silicon microring is shown with 2x2 full crossbar switching functionality, enabling optical interconnects with ultra small footprint. Then several other experiments in the silicon platform are presented, including a fully integrated in-band Optical Signal to Noise Ratio (OSNR) monitor, characterization of optical power upper bound in a silicon microring modulator, and wavelength conversion in a dispersion-engineered waveguide. The last part of this thesis is on network-level application of photonics, specically a broadcast-and-select network based on star coupler is introduced, and its scalability performance is studied. Finally a novel switch architecture for data center networks is discussed, and its benefits as a disaggregated network are presented.

A network approach for modulating memory processes via direct and indirect brain stimulation: Toward a causal approach for the neural basis of memory.

PubMed

Kim, Kamin; Ekstrom, Arne D; Tandon, Nitin

2016-10-01

Electrical stimulation of the brain is a unique tool to perturb endogenous neural signals, allowing us to evaluate the necessity of given neural processes to cognitive processing. An important issue, gaining increasing interest in the literature, is whether and how stimulation can be employed to selectively improve or disrupt declarative memory processes. Here, we provide a comprehensive review of both invasive and non-invasive stimulation studies aimed at modulating memory performance. The majority of past studies suggest that invasive stimulation of the hippocampus impairs memory performance; similarly, most non-invasive studies show that disrupting frontal or parietal regions also impairs memory performance, suggesting that these regions also play necessary roles in declarative memory. On the other hand, a handful of both invasive and non-invasive studies have also suggested modest improvements in memory performance following stimulation. These studies typically target brain regions connected to the hippocampus or other memory "hubs," which may affect endogenous activity in connected areas like the hippocampus, suggesting that to augment declarative memory, altering the broader endogenous memory network activity is critical. Together, studies reporting memory improvements/impairments are consistent with the idea that a network of distinct brain "hubs" may be crucial for successful memory encoding and retrieval rather than a single primary hub such as the hippocampus. Thus, it is important to consider neurostimulation from the network perspective, rather than from a purely localizationalist viewpoint. We conclude by proposing a novel approach to neurostimulation for declarative memory modulation that aims to facilitate interactions between multiple brain "nodes" underlying memory rather than considering individual brain regions in isolation. Copyright © 2016. Published by Elsevier Inc.

Solar thermal power systems point-focusing distributed receiver technology project. Volume 2: Detailed report

NASA Technical Reports Server (NTRS)

1980-01-01

The accomplishments of the Point-Focusing Distributed Receiver Technology Project during fiscal year 1979 are detailed. Present studies involve designs of modular units that collect and concentrate solar energy via highly reflective, parabolic-shaped dishes. The concentrated energy is then converted to heat in a working fluid, such as hot gas. In modules designed to produce heat for industrial applications, a flexible line conveys the heated fluid from the module to a heat transfer network. In modules designed to produce electricity the fluid carries the heat directly to an engine in a power conversion unit located at the focus of the concentrator. The engine is mechanically linked to an electric generator. A Brayton-cycle engine is currently being developed as the most promising electrical energy converter to meet near-future needs.

Mapping human brain networks with cortico-cortical evoked potentials.

PubMed

Keller, Corey J; Honey, Christopher J; Mégevand, Pierre; Entz, Laszlo; Ulbert, Istvan; Mehta, Ashesh D

2014-10-05

The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Modulation format identification aided hitless flexible coherent transceiver.

PubMed

Xiang, Meng; Zhuge, Qunbi; Qiu, Meng; Zhou, Xingyu; Zhang, Fangyuan; Tang, Ming; Liu, Deming; Fu, Songnian; Plant, David V

2016-07-11

We propose a hitless flexible coherent transceiver enabled by a novel modulation format identification (MFI) scheme for dynamic agile optical networks. The modulation format transparent digital signal processing (DSP) is realized by a block-wise decision-directed least-mean-square (DD-LMS) equalizer for channel tracking, and a pilot symbol aided superscalar phase locked loop (PLL) for carrier phase estimation (CPE). For the MFI, the modulation format information is encoded onto the pilot symbols initially used for CPE. Therefore, the proposed MFI method does not require extra overhead. Moreover, it can identify arbitrary modulation formats including multi-dimensional formats, and it enables tracking of the format change for short data blocks. The performance of the proposed hitless flexible coherent transceiver is successfully evaluated with five modulation formats including QPSK, 16QAM, 64QAM, Hybrid QPSK/8QAM and set-partitioning (SP)-512-QAM. We show that the proposed MFI method induces a negligible performance penalty. Moreover, we experimentally demonstrate that such a hitless transceiver can adapt to fast block-by-block modulation format switching. Finally, the performance improvement of the proposed MFI method is experimentally verified with respect to other commonly used MFI methods.

Modulation and detection of single neuron activity using spin transfer nano-oscillators

NASA Astrophysics Data System (ADS)

Algarin, Jose Miguel; Ramaswamy, Bharath; Venuti, Lucy; Swierzbinski, Matthew; Villar, Pablo; Chen, Yu-Jin; Krivorotov, Ilya; Weinberg, Irving N.; Herberholz, Jens; Araneda, Ricardo; Shapiro, Benjamin; Waks, Edo

2017-09-01

The brain is a complex network of interconnected circuits that exchange electrical signals with each other. These electrical signals provide insight on how neural circuits code information, and give rise to sensations, thoughts, emotions and actions. Currents methods to detect and modulate these electrical signals use implanted electrodes or optical fields with light sensitive dyes in the brain. These techniques require complex surgeries or suffer low resolution. In this talk we explore a new method to both image and stimulate single neurons using spintronics. We propose using a Spin Transfer Nano-Oscillators (STNOs) as a nanoscale sensor that converts neuronal action potentials to microwave field oscillations that can be detected wirelessly by magnetic induction. We will describe our recent proof-of-concept demonstration of both detection and wireless modulation of neuronal activity using STNOs. For detection we use electrodes to connect a STNO to a lateral giant crayfish neuron. When we stimulate the neuron, the STNO responds to the neuronal activity with a corresponding microwave signal. For modulation, we stimulate the STNOs wirelessly using an inductively coupled solenoid. The STNO rectifies the induced microwave signal to produce a direct voltage. This direct voltage from the STNO, when applied in the vicinity of a mammalian neuron, changes the frequency of electrical signals produced by the neuron.

Hippocampal Ripple Oscillations and Inhibition-First Network Models: Frequency Dynamics and Response to GABA Modulators.

PubMed

Donoso, José R; Schmitz, Dietmar; Maier, Nikolaus; Kempter, Richard

2018-03-21

Hippocampal ripples are involved in memory consolidation, but the mechanisms underlying their generation remain unclear. Models relying on interneuron networks in the CA1 region disagree on the predominant source of excitation to interneurons: either "direct," via the Schaffer collaterals that provide feedforward input from CA3 to CA1, or "indirect," via the local pyramidal cells in CA1, which are embedded in a recurrent excitatory-inhibitory network. Here, we used physiologically constrained computational models of basket-cell networks to investigate how they respond to different conditions of transient, noisy excitation. We found that direct excitation of interneurons could evoke ripples (140-220 Hz) that exhibited intraripple frequency accommodation and were frequency-insensitive to GABA modulators, as previously shown in in vitro experiments. In addition, the indirect excitation of the basket-cell network enabled the expression of intraripple frequency accommodation in the fast-gamma range (90-140 Hz), as in vivo In our model, intraripple frequency accommodation results from a hysteresis phenomenon in which the frequency responds differentially to the rising and descending phases of the transient excitation. Such a phenomenon predicts a maximum oscillation frequency occurring several milliseconds before the peak of excitation. We confirmed this prediction for ripples in brain slices from male mice. These results suggest that ripple and fast-gamma episodes are produced by the same interneuron network that is recruited via different excitatory input pathways, which could be supported by the previously reported intralaminar connectivity bias between basket cells and functionally distinct subpopulations of pyramidal cells in CA1. Together, our findings unify competing inhibition-first models of rhythm generation in the hippocampus. SIGNIFICANCE STATEMENT The hippocampus is a part of the brain of humans and other mammals that is critical for the acquisition and consolidation of memories. During deep sleep and resting periods, the hippocampus generates high-frequency (∼200 Hz) oscillations called ripples, which are important for memory consolidation. The mechanisms underlying ripple generation are not well understood. A prominent hypothesis holds that the ripples are generated by local recurrent networks of inhibitory neurons. Using computational models and experiments in brain slices from rodents, we show that the dynamics of interneuron networks clarify several previously unexplained characteristics of ripple oscillations, which advances our understanding of hippocampus-dependent memory consolidation. Copyright © 2018 the authors 0270-6474/18/383125-23$15.00/0.

Dual regulation of gene expression mediated by extended MAPK activation and salicylic acid contributes to robust innate immunity in Arabidopsis thaliana.

PubMed

Tsuda, Kenichi; Mine, Akira; Bethke, Gerit; Igarashi, Daisuke; Botanga, Christopher J; Tsuda, Yayoi; Glazebrook, Jane; Sato, Masanao; Katagiri, Fumiaki

2013-01-01

Network robustness is a crucial property of the plant immune signaling network because pathogens are under a strong selection pressure to perturb plant network components to dampen plant immune responses. Nevertheless, modulation of network robustness is an area of network biology that has rarely been explored. While two modes of plant immunity, Effector-Triggered Immunity (ETI) and Pattern-Triggered Immunity (PTI), extensively share signaling machinery, the network output is much more robust against perturbations during ETI than PTI, suggesting modulation of network robustness. Here, we report a molecular mechanism underlying the modulation of the network robustness in Arabidopsis thaliana. The salicylic acid (SA) signaling sector regulates a major portion of the plant immune response and is important in immunity against biotrophic and hemibiotrophic pathogens. In Arabidopsis, SA signaling was required for the proper regulation of the vast majority of SA-responsive genes during PTI. However, during ETI, regulation of most SA-responsive genes, including the canonical SA marker gene PR1, could be controlled by SA-independent mechanisms as well as by SA. The activation of the two immune-related MAPKs, MPK3 and MPK6, persisted for several hours during ETI but less than one hour during PTI. Sustained MAPK activation was sufficient to confer SA-independent regulation of most SA-responsive genes. Furthermore, the MPK3 and SA signaling sectors were compensatory to each other for inhibition of bacterial growth as well as for PR1 expression during ETI. These results indicate that the duration of the MAPK activation is a critical determinant for modulation of robustness of the immune signaling network. Our findings with the plant immune signaling network imply that the robustness level of a biological network can be modulated by the activities of network components.

WGCNA: an R package for weighted correlation network analysis

PubMed Central

Langfelder, Peter; Horvath, Steve

2008-01-01

Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at . PMID:19114008

Active module identification in intracellular networks using a memetic algorithm with a new binary decoding scheme.

PubMed

Li, Dong; Pan, Zhisong; Hu, Guyu; Zhu, Zexuan; He, Shan

2017-03-14

Active modules are connected regions in biological network which show significant changes in expression over particular conditions. The identification of such modules is important since it may reveal the regulatory and signaling mechanisms that associate with a given cellular response. In this paper, we propose a novel active module identification algorithm based on a memetic algorithm. We propose a novel encoding/decoding scheme to ensure the connectedness of the identified active modules. Based on the scheme, we also design and incorporate a local search operator into the memetic algorithm to improve its performance. The effectiveness of proposed algorithm is validated on both small and large protein interaction networks.

Modular sensor network node

DOEpatents

Davis, Jesse Harper Zehring [Berkeley, CA; Stark, Jr., Douglas Paul; Kershaw, Christopher Patrick [Hayward, CA; Kyker, Ronald Dean [Livermore, CA

2008-06-10

A distributed wireless sensor network node is disclosed. The wireless sensor network node includes a plurality of sensor modules coupled to a system bus and configured to sense a parameter. The parameter may be an object, an event or any other parameter. The node collects data representative of the parameter. The node also includes a communication module coupled to the system bus and configured to allow the node to communicate with other nodes. The node also includes a processing module coupled to the system bus and adapted to receive the data from the sensor module and operable to analyze the data. The node also includes a power module connected to the system bus and operable to generate a regulated voltage.

Small-molecule RORγt antagonists inhibit T helper 17 cell transcriptional network by divergent mechanisms.

PubMed

Xiao, Sheng; Yosef, Nir; Yang, Jianfei; Wang, Yonghui; Zhou, Ling; Zhu, Chen; Wu, Chuan; Baloglu, Erkan; Schmidt, Darby; Ramesh, Radha; Lobera, Mercedes; Sundrud, Mark S; Tsai, Pei-Yun; Xiang, Zhijun; Wang, Jinsong; Xu, Yan; Lin, Xichen; Kretschmer, Karsten; Rahl, Peter B; Young, Richard A; Zhong, Zhong; Hafler, David A; Regev, Aviv; Ghosh, Shomir; Marson, Alexander; Kuchroo, Vijay K

2014-04-17

We identified three retinoid-related orphan receptor gamma t (RORγt)-specific inhibitors that suppress T helper 17 (Th17) cell responses, including Th17-cell-mediated autoimmune disease. We systemically characterized RORγt binding in the presence and absence of drugs with corresponding whole-genome transcriptome sequencing. RORγt acts as a direct activator of Th17 cell signature genes and a direct repressor of signature genes from other T cell lineages; its strongest transcriptional effects are on cis-regulatory sites containing the RORα binding motif. RORγt is central in a densely interconnected regulatory network that shapes the balance of T cell differentiation. Here, the three inhibitors modulated the RORγt-dependent transcriptional network to varying extents and through distinct mechanisms. Whereas one inhibitor displaced RORγt from its target loci, the other two inhibitors affected transcription predominantly without removing DNA binding. Our work illustrates the power of a system-scale analysis of transcriptional regulation to characterize potential therapeutic compounds that inhibit pathogenic Th17 cells and suppress autoimmunity. Copyright © 2014 Elsevier Inc. All rights reserved.

Multiple supervised residual network for osteosarcoma segmentation in CT images.

PubMed

Zhang, Rui; Huang, Lin; Xia, Wei; Zhang, Bo; Qiu, Bensheng; Gao, Xin

2018-01-01

Automatic and accurate segmentation of osteosarcoma region in CT images can help doctor make a reasonable treatment plan, thus improving cure rate. In this paper, a multiple supervised residual network (MSRN) was proposed for osteosarcoma image segmentation. Three supervised side output modules were added to the residual network. The shallow side output module could extract image shape features, such as edge features and texture features. The deep side output module could extract semantic features. The side output module could compute the loss value between output probability map and ground truth and back-propagate the loss information. Then, the parameters of residual network could be modified by gradient descent method. This could guide the multi-scale feature learning of the network. The final segmentation results were obtained by fusing the results output by the three side output modules. A total of 1900 CT images from 15 osteosarcoma patients were used to train the network and a total of 405 CT images from another 8 osteosarcoma patients were used to test the network. Results indicated that MSRN enabled a dice similarity coefficient (DSC) of 89.22%, a sensitivity of 88.74% and a F1-measure of 0.9305, which were larger than those obtained by fully convolutional network (FCN) and U-net. Thus, MSRN for osteosarcoma segmentation could give more accurate results than FCN and U-Net. Copyright © 2018 Elsevier Ltd. All rights reserved.

Interface Control Document for the EMPACT Module that Estimates Electric Power Transmission System Response to EMP-Caused Damage

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

Werley, Kenneth Alan; Mccown, Andrew William

The EPREP code is designed to evaluate the effects of an Electro-Magnetic Pulse (EMP) on the electric power transmission system. The EPREP code embodies an umbrella framework that allows a user to set up analysis conditions and to examine analysis results. The code links to three major physics/engineering modules. The first module describes the EM wave in space and time. The second module evaluates the damage caused by the wave on specific electric power (EP) transmission system components. The third module evaluates the consequence of the damaged network on its (reduced) ability to provide electric power to meet demand. Thismore » third module is the focus of the present paper. The EMPACT code serves as the third module. The EMPACT name denotes EMP effects on Alternating Current Transmission systems. The EMPACT algorithms compute electric power transmission network flow solutions under severely damaged network conditions. Initial solutions are often characterized by unacceptible network conditions including line overloads and bad voltages. The EMPACT code contains algorithms to adjust optimally network parameters to eliminate network problems while minimizing outages. System adjustments include automatically adjusting control equipment (generator V control, variable transformers, and variable shunts), as well as non-automatic control of generator power settings and minimal load shedding. The goal is to evaluate the minimal loss of customer load under equilibrium (steady-state) conditions during peak demand.« less

Disease networks. Uncovering disease-disease relationships through the incomplete interactome.

PubMed

Menche, Jörg; Sharma, Amitabh; Kitsak, Maksim; Ghiassian, Susan Dina; Vidal, Marc; Loscalzo, Joseph; Barabási, Albert-László

2015-02-20

According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct. These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes. Copyright © 2015, American Association for the Advancement of Science.

Linear motif-mediated interactions have contributed to the evolution of modularity in complex protein interaction networks.

PubMed

Kim, Inhae; Lee, Heetak; Han, Seong Kyu; Kim, Sanguk

2014-10-01

The modular architecture of protein-protein interaction (PPI) networks is evident in diverse species with a wide range of complexity. However, the molecular components that lead to the evolution of modularity in PPI networks have not been clearly identified. Here, we show that weak domain-linear motif interactions (DLIs) are more likely to connect different biological modules than strong domain-domain interactions (DDIs). This molecular division of labor is essential for the evolution of modularity in the complex PPI networks of diverse eukaryotic species. In particular, DLIs may compensate for the reduction in module boundaries that originate from increased connections between different modules in complex PPI networks. In addition, we show that the identification of biological modules can be greatly improved by including molecular characteristics of protein interactions. Our findings suggest that transient interactions have played a unique role in shaping the architecture and modularity of biological networks over the course of evolution.

Network module detection: Affinity search technique with the multi-node topological overlap measure

PubMed Central

Li, Ai; Horvath, Steve

2009-01-01

Background Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. Findings We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Conclusion Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: PMID:19619323

Network module detection: Affinity search technique with the multi-node topological overlap measure.

PubMed

Li, Ai; Horvath, Steve

2009-07-20

Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/

BinTree Seeking: A Novel Approach to Mine Both Bi-Sparse and Cohesive Modules in Protein Interaction Networks

PubMed Central

Shen, Hong-Bin

2011-01-01

Modern science of networks has brought significant advances to our understanding of complex systems biology. As a representative model of systems biology, Protein Interaction Networks (PINs) are characterized by a remarkable modular structures, reflecting functional associations between their components. Many methods were proposed to capture cohesive modules so that there is a higher density of edges within modules than those across them. Recent studies reveal that cohesively interacting modules of proteins is not a universal organizing principle in PINs, which has opened up new avenues for revisiting functional modules in PINs. In this paper, functional clusters in PINs are found to be able to form unorthodox structures defined as bi-sparse module. In contrast to the traditional cohesive module, the nodes in the bi-sparse module are sparsely connected internally and densely connected with other bi-sparse or cohesive modules. We present a novel protocol called the BinTree Seeking (BTS) for mining both bi-sparse and cohesive modules in PINs based on Edge Density of Module (EDM) and matrix theory. BTS detects modules by depicting links and nodes rather than nodes alone and its derivation procedure is totally performed on adjacency matrix of networks. The number of modules in a PIN can be automatically determined in the proposed BTS approach. BTS is tested on three real PINs and the results demonstrate that functional modules in PINs are not dominantly cohesive but can be sparse. BTS software and the supporting information are available at: www.csbio.sjtu.edu.cn/bioinf/BTS/. PMID:22140454

Thalamocortical integration of instrumental learning and performance and their disintegration in addiction.

PubMed

Balleine, Bernard W; Morris, Richard W; Leung, Beatrice K

2015-12-02

A recent focus of addiction research has been on the effect of drug exposure on the neural processes that mediate the acquisition and performance of goal-directed instrumental actions. Deficits in goal-directed control and a consequent dysregulation of habit learning processes have been described as resulting in compulsive drug seeking. Similarly, considerable research has focussed on the motivational and emotional changes that drugs produce and that result in changes in the incentive processes that modulate goal-directed performance. Although these areas have developed independently, we argue that the effects they described are likely not independent. Here we hypothesize that these changes result from a core deficit in the way the learning and performance factors that support goal-directed action are integrated at a neural level to maintain behavioural control. A dorsal basal ganglia stream mediating goal-directed learning and a ventral stream mediating various performance factors find several points of integration in the cortical basal ganglia system, most notably in the thalamocortical network linking basal ganglia output to a variety of cortical control centres. Recent research in humans and other animals is reviewed suggesting that learning and performance factors are integrated in a network centred on the mediodorsal thalamus and that disintegration in this network may provide the basis for a 'switch' from recreational to dysregulated drug seeking resulting in the well documented changes associated with addiction. Copyright © 2014 Elsevier B.V. All rights reserved.

Identification of Unstable Network Modules Reveals Disease Modules Associated with the Progression of Alzheimer’s Disease

PubMed Central

Kikuchi, Masataka; Ogishima, Soichi; Miyamoto, Tadashi; Miyashita, Akinori; Kuwano, Ryozo; Nakaya, Jun; Tanaka, Hiroshi

2013-01-01

Alzheimer’s disease (AD), the most common cause of dementia, is associated with aging, and it leads to neuron death. Deposits of amyloid β and aberrantly phosphorylated tau protein are known as pathological hallmarks of AD, but the underlying mechanisms have not yet been revealed. A high-throughput gene expression analysis previously showed that differentially expressed genes accompanying the progression of AD were more down-regulated than up-regulated in the later stages of AD. This suggested that the molecular networks and their constituent modules collapsed along with AD progression. In this study, by using gene expression profiles and protein interaction networks (PINs), we identified the PINs expressed in three brain regions: the entorhinal cortex (EC), hippocampus (HIP) and superior frontal gyrus (SFG). Dividing the expressed PINs into modules, we examined the stability of the modules with AD progression and with normal aging. We found that in the AD modules, the constituent proteins, interactions and cellular functions were not maintained between consecutive stages through all brain regions. Interestingly, the modules were collapsed with AD progression, specifically in the EC region. By identifying the modules that were affected by AD pathology, we found the transcriptional regulation-associated modules that interact with the proteasome-associated module via UCHL5 hub protein, which is a deubiquitinating enzyme. Considering PINs as a system made of network modules, we found that the modules relevant to the transcriptional regulation are disrupted in the EC region, which affects the ubiquitin-proteasome system. PMID:24348898

The biometric-based module of smart grid system

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Ermoshkina, A.

2015-10-01

Within Smart Grid concept the flexible biometric-based module base on Principal Component Analysis (PCA) and selective Neural Network is developed. The formation of the selective Neural Network the biometric-based module uses the method which includes three main stages: preliminary processing of the image, face localization and face recognition. Experiments on the Yale face database show that (i) selective Neural Network exhibits promising classification capability for face detection, recognition problems; and (ii) the proposed biometric-based module achieves near real-time face detection, recognition speed and the competitive performance, as compared to some existing subspaces-based methods.

To cut or not to cut? Assessing the modular structure of brain networks.

PubMed

Chang, Yu-Teng; Pantazis, Dimitrios; Leahy, Richard M

2014-05-01

A wealth of methods has been developed to identify natural divisions of brain networks into groups or modules, with one of the most prominent being modularity. Compared with the popularity of methods to detect community structure, only a few methods exist to statistically control for spurious modules, relying almost exclusively on resampling techniques. It is well known that even random networks can exhibit high modularity because of incidental concentration of edges, even though they have no underlying organizational structure. Consequently, interpretation of community structure is confounded by the lack of principled and computationally tractable approaches to statistically control for spurious modules. In this paper we show that the modularity of random networks follows a transformed version of the Tracy-Widom distribution, providing for the first time a link between module detection and random matrix theory. We compute parametric formulas for the distribution of modularity for random networks as a function of network size and edge variance, and show that we can efficiently control for false positives in brain and other real-world networks. Copyright © 2014 Elsevier Inc. All rights reserved.

Distinct sets of locomotor modules control the speed and modes of human locomotion

PubMed Central

Yokoyama, Hikaru; Ogawa, Tetsuya; Kawashima, Noritaka; Shinya, Masahiro; Nakazawa, Kimitaka

2016-01-01

Although recent vertebrate studies have revealed that different spinal networks are recruited in locomotor mode- and speed-dependent manners, it is unknown whether humans share similar neural mechanisms. Here, we tested whether speed- and mode-dependence in the recruitment of human locomotor networks exists or not by statistically extracting locomotor networks. From electromyographic activity during walking and running over a wide speed range, locomotor modules generating basic patterns of muscle activities were extracted using non-negative matrix factorization. The results showed that the number of modules changed depending on the modes and speeds. Different combinations of modules were extracted during walking and running, and at different speeds even during the same locomotor mode. These results strongly suggest that, in humans, different spinal locomotor networks are recruited while walking and running, and even in the same locomotor mode different networks are probably recruited at different speeds. PMID:27805015

Fear conditioning is associated with dynamic directed functional interactions between and within the human amygdala, hippocampus, and frontal lobe.

PubMed

Liu, C C; Crone, N E; Franaszczuk, P J; Cheng, D T; Schretlen, D S; Lenz, F A

2011-08-25

The current model of fear conditioning suggests that it is mediated through modules involving the amygdala (AMY), hippocampus (HIP), and frontal lobe (FL). We now test the hypothesis that habituation and acquisition stages of a fear conditioning protocol are characterized by different event-related causal interactions (ERCs) within and between these modules. The protocol used the painful cutaneous laser as the unconditioned stimulus and ERC was estimated by analysis of local field potentials recorded through electrodes implanted for investigation of epilepsy. During the prestimulus interval of the habituation stage FL>AMY ERC interactions were common. For comparison, in the poststimulus interval of the habituation stage, only a subdivision of the FL (dorsolateral prefrontal cortex, dlPFC) still exerted the FL>AMY ERC interaction (dlFC>AMY). For a further comparison, during the poststimulus interval of the acquisition stage, the dlPFC>AMY interaction persisted and an AMY>FL interaction appeared. In addition to these ERC interactions between modules, the results also show ERC interactions within modules. During the poststimulus interval, HIP>HIP ERC interactions were more common during acquisition, and deep hippocampal contacts exerted causal interactions on superficial contacts, possibly explained by connectivity between the perihippocampal gyrus and the HIP. During the prestimulus interval of the habituation stage, AMY>AMY ERC interactions were commonly found, while interactions between the deep and superficial AMY (indirect pathway) were independent of intervals and stages. These results suggest that the network subserving fear includes distributed or widespread modules, some of which are themselves "local networks." ERC interactions between and within modules can be either static or change dynamically across intervals or stages of fear conditioning. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

Protein complexes and functional modules in molecular networks

NASA Astrophysics Data System (ADS)

Spirin, Victor; Mirny, Leonid A.

2003-10-01

Proteins, nucleic acids, and small molecules form a dense network of molecular interactions in a cell. Molecules are nodes of this network, and the interactions between them are edges. The architecture of molecular networks can reveal important principles of cellular organization and function, similarly to the way that protein structure tells us about the function and organization of a protein. Computational analysis of molecular networks has been primarily concerned with node degree [Wagner, A. & Fell, D. A. (2001) Proc. R. Soc. London Ser. B 268, 1803-1810; Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. & Barabasi, A. L. (2000) Nature 407, 651-654] or degree correlation [Maslov, S. & Sneppen, K. (2002) Science 296, 910-913], and hence focused on single/two-body properties of these networks. Here, by analyzing the multibody structure of the network of protein-protein interactions, we discovered molecular modules that are densely connected within themselves but sparsely connected with the rest of the network. Comparison with experimental data and functional annotation of genes showed two types of modules: (i) protein complexes (splicing machinery, transcription factors, etc.) and (ii) dynamic functional units (signaling cascades, cell-cycle regulation, etc.). Discovered modules are highly statistically significant, as is evident from comparison with random graphs, and are robust to noise in the data. Our results provide strong support for the network modularity principle introduced by Hartwell et al. [Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. (1999) Nature 402, C47-C52], suggesting that found modules constitute the "building blocks" of molecular networks.

Network interactions underlying mirror feedback in stroke: A dynamic causal modeling study.

PubMed

Saleh, Soha; Yarossi, Mathew; Manuweera, Thushini; Adamovich, Sergei; Tunik, Eugene

2017-01-01

Mirror visual feedback (MVF) is potentially a powerful tool to facilitate recovery of disordered movement and stimulate activation of under-active brain areas due to stroke. The neural mechanisms underlying MVF have therefore been a focus of recent inquiry. Although it is known that sensorimotor areas can be activated via mirror feedback, the network interactions driving this effect remain unknown. The aim of the current study was to fill this gap by using dynamic causal modeling to test the interactions between regions in the frontal and parietal lobes that may be important for modulating the activation of the ipsilesional motor cortex during mirror visual feedback of unaffected hand movement in stroke patients. Our intent was to distinguish between two theoretical neural mechanisms that might mediate ipsilateral activation in response to mirror-feedback: transfer of information between bilateral motor cortices versus recruitment of regions comprising an action observation network which in turn modulate the motor cortex. In an event-related fMRI design, fourteen chronic stroke subjects performed goal-directed finger flexion movements with their unaffected hand while observing real-time visual feedback of the corresponding (veridical) or opposite (mirror) hand in virtual reality. Among 30 plausible network models that were tested, the winning model revealed significant mirror feedback-based modulation of the ipsilesional motor cortex arising from the contralesional parietal cortex, in a region along the rostral extent of the intraparietal sulcus. No winning model was identified for the veridical feedback condition. We discuss our findings in the context of supporting the latter hypothesis, that mirror feedback-based activation of motor cortex may be attributed to engagement of a contralateral (contralesional) action observation network. These findings may have important implications for identifying putative cortical areas, which may be targeted with non-invasive brain stimulation as a means of potentiating the effects of mirror training.

Protein thermal denaturation is modulated by central residues in the protein structure network.

PubMed

Souza, Valquiria P; Ikegami, Cecília M; Arantes, Guilherme M; Marana, Sandro R

2016-03-01

Network structural analysis, known as residue interaction networks or graphs (RIN or RIG, respectively) or protein structural networks or graphs (PSN or PSG, respectively), comprises a useful tool for detecting important residues for protein function, stability, folding and allostery. In RIN, the tertiary structure is represented by a network in which residues (nodes) are connected by interactions (edges). Such structural networks have consistently presented a few central residues that are important for shortening the pathways linking any two residues in a protein structure. To experimentally demonstrate that central residues effectively participate in protein properties, mutations were directed to seven central residues of the β-glucosidase Sfβgly (β-D-glucoside glucohydrolase; EC 3.2.1.21). These mutations reduced the thermal stability of the enzyme, as evaluated by changes in transition temperature (Tm ) and the denaturation rate at 45 °C. Moreover, mutations directed to the vicinity of a central residue also caused significant decreases in the Tm of Sfβgly and clearly increased the unfolding rate constant at 45 °C. However, mutations at noncentral residues or at surrounding residues did not affect the thermal stability of Sfβgly. Therefore, the data reported in the present study suggest that the perturbation of the central residues reduced the stability of the native structure of Sfβgly. These results are in agreement with previous findings showing that networks are robust, whereas attacks on central nodes cause network failure. Finally, the present study demonstrates that central residues underlie the functional properties of proteins. © 2016 Federation of European Biochemical Societies.

Network-dependent modulation of brain activity during sleep.

PubMed

Watanabe, Takamitsu; Kan, Shigeyuki; Koike, Takahiko; Misaki, Masaya; Konishi, Seiki; Miyauchi, Satoru; Miyahsita, Yasushi; Masuda, Naoki

2014-09-01

Brain activity dynamically changes even during sleep. A line of neuroimaging studies has reported changes in functional connectivity and regional activity across different sleep stages such as slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. However, it remains unclear whether and how the large-scale network activity of human brains changes within a given sleep stage. Here, we investigated modulation of network activity within sleep stages by applying the pairwise maximum entropy model to brain activity obtained by functional magnetic resonance imaging from sleeping healthy subjects. We found that the brain activity of individual brain regions and functional interactions between pairs of regions significantly increased in the default-mode network during SWS and decreased during REM sleep. In contrast, the network activity of the fronto-parietal and sensory-motor networks showed the opposite pattern. Furthermore, in the three networks, the amount of the activity changes throughout REM sleep was negatively correlated with that throughout SWS. The present findings suggest that the brain activity is dynamically modulated even in a sleep stage and that the pattern of modulation depends on the type of the large-scale brain networks. Copyright © 2014 Elsevier Inc. All rights reserved.

Connectivity Neurofeedback Training Can Differentially Change Functional Connectivity and Cognitive Performance.

PubMed

Yamashita, Ayumu; Hayasaka, Shunsuke; Kawato, Mitsuo; Imamizu, Hiroshi

2017-10-01

Advances in functional magnetic resonance imaging have made it possible to provide real-time feedback on brain activity. Neurofeedback has been applied to therapeutic interventions for psychiatric disorders. Since many studies have shown that most psychiatric disorders exhibit abnormal brain networks, a novel experimental paradigm named connectivity neurofeedback, which can directly modulate a brain network, has emerged as a promising approach to treat psychiatric disorders. Here, we investigated the hypothesis that connectivity neurofeedback can induce the aimed direction of change in functional connectivity, and the differential change in cognitive performance according to the direction of change in connectivity. We selected the connectivity between the left primary motor cortex and the left lateral parietal cortex as the target. Subjects were divided into 2 groups, in which only the direction of change (an increase or a decrease in correlation) in the experimentally manipulated connectivity differed between the groups. As a result, subjects successfully induced the expected connectivity changes in either of the 2 directions. Furthermore, cognitive performance significantly and differentially changed from preneurofeedback to postneurofeedback training between the 2 groups. These findings indicate that connectivity neurofeedback can induce the aimed direction of change in connectivity and also a differential change in cognitive performance. © The Author 2017. Published by Oxford University Press.

Right hemisphere dominance directly predicts both baseline V1 cortical excitability and the degree of top-down modulation exerted over low-level brain structures.

PubMed

Arshad, Q; Siddiqui, S; Ramachandran, S; Goga, U; Bonsu, A; Patel, M; Roberts, R E; Nigmatullina, Y; Malhotra, P; Bronstein, A M

2015-12-17

Right hemisphere dominance for visuo-spatial attention is characteristically observed in most right-handed individuals. This dominance has been attributed to both an anatomically larger right fronto-parietal network and the existence of asymmetric parietal interhemispheric connections. Previously it has been demonstrated that interhemispheric conflict, which induces left hemisphere inhibition, results in the modulation of both (i) the excitability of the early visual cortex (V1) and (ii) the brainstem-mediated vestibular-ocular reflex (VOR) via top-down control mechanisms. However to date, it remains unknown whether the degree of an individual's right hemisphere dominance for visuospatial function can influence, (i) the baseline excitability of the visual cortex and (ii) the extent to which the right hemisphere can exert top-down modulation. We directly tested this by correlating line bisection error (or pseudoneglect), taken as a measure of right hemisphere dominance, with both (i) visual cortical excitability measured using phosphene perception elicited via single-pulse occipital trans-cranial magnetic stimulation (TMS) and (ii) the degree of trans-cranial direct current stimulation (tDCS)-mediated VOR suppression, following left hemisphere inhibition. We found that those individuals with greater right hemisphere dominance had a less excitable early visual cortex at baseline and demonstrated a greater degree of vestibular nystagmus suppression following left hemisphere cathodal tDCS. To conclude, our results provide the first demonstration that individual differences in right hemisphere dominance can directly predict both the baseline excitability of low-level brain structures and the degree of top-down modulation exerted over them. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

PyPathway: Python Package for Biological Network Analysis and Visualization.

PubMed

Xu, Yang; Luo, Xiao-Chun

2018-05-01

Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.

Adaptive threshold hunting for the effects of transcranial direct current stimulation on primary motor cortex inhibition.

PubMed

Mooney, Ronan A; Cirillo, John; Byblow, Winston D

2018-06-01

Primary motor cortex excitability can be modulated by anodal and cathodal transcranial direct current stimulation (tDCS). These neuromodulatory effects may, in part, be dependent on modulation within gamma-aminobutyric acid (GABA)-mediated inhibitory networks. GABAergic function can be quantified non-invasively using adaptive threshold hunting paired-pulse transcranial magnetic stimulation (TMS). The previous studies have used TMS with posterior-anterior (PA) induced current to assess tDCS effects on inhibition. However, TMS with anterior-posterior (AP) induced current in the brain provides a more robust measure of GABA-mediated inhibition. The aim of the present study was to assess the modulation of corticomotor excitability and inhibition after anodal and cathodal tDCS using TMS with PA- and AP-induced current. In 16 young adults (26 ± 1 years), we investigated the response to anodal, cathodal, and sham tDCS in a repeated-measures double-blinded crossover design. Adaptive threshold hunting paired-pulse TMS with PA- and AP-induced current was used to examine separate interneuronal populations within M1 and their influence on corticomotor excitability and short- and long-interval inhibition (SICI and LICI) for up to 60 min after tDCS. Unexpectedly, cathodal tDCS increased corticomotor excitability assessed with AP (P = 0.047) but not PA stimulation (P = 0.74). SICI AP was reduced after anodal tDCS compared with sham (P = 0.040). Pearson's correlations indicated that SICI AP and LICI AP modulation was associated with corticomotor excitability after anodal (P = 0.027) and cathodal tDCS (P = 0.042). The after-effects of tDCS on corticomotor excitability may depend on the direction of the TMS-induced current used to make assessments, and on modulation within GABA-mediated inhibitory circuits.

Modulators of 14-3-3 Protein–Protein Interactions

PubMed Central

2017-01-01

Direct interactions between proteins are essential for the regulation of their functions in biological pathways. Targeting the complex network of protein–protein interactions (PPIs) has now been widely recognized as an attractive means to therapeutically intervene in disease states. Even though this is a challenging endeavor and PPIs have long been regarded as “undruggable” targets, the last two decades have seen an increasing number of successful examples of PPI modulators, resulting in growing interest in this field. PPI modulation requires novel approaches and the integrated efforts of multiple disciplines to be a fruitful strategy. This perspective focuses on the hub-protein 14-3-3, which has several hundred identified protein interaction partners, and is therefore involved in a wide range of cellular processes and diseases. Here, we aim to provide an integrated overview of the approaches explored for the modulation of 14-3-3 PPIs and review the examples resulting from these efforts in both inhibiting and stabilizing specific 14-3-3 protein complexes by small molecules, peptide mimetics, and natural products. PMID:28968506

A superconducting direct-current limiter with a power of up to 8 MVA

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

Fisher, L. M.; Alferov, D. F., E-mail: DFAlferov@niitfa.ru; Akhmetgareev, M. R.

2016-12-15

A resistive switching superconducting fault current limiter (SFCL) for DC networks with a nominal voltage of 3.5 kV and a nominal current of 2 kA was developed, produced, and tested. The SFCL has two main units—an assembly of superconducting modules and a high-speed vacuum circuit breaker. The assembly of superconducting modules consists of nine (3 × 3) parallel–series connected modules. Each module contains four parallel-connected 2G high-temperature superconducting (HTS) tapes. The results of SFCL tests in the short-circuit emulation mode with a maximum current rise rate of 1300 A/ms are presented. The SFCL is capable of limiting the current atmore » a level of 7 kA and break it 8 ms after the current-limiting mode begins. The average temperature of HTS tapes during the current-limiting mode increases to 210 K. After the current is interrupted, the superconductivity recovery time does not exceed 1 s.« less

A superconducting direct-current limiter with a power of up to 8 MVA

NASA Astrophysics Data System (ADS)

Fisher, L. M.; Alferov, D. F.; Akhmetgareev, M. R.; Budovskii, A. I.; Evsin, D. V.; Voloshin, I. F.; Kalinov, A. V.

2016-12-01

A resistive switching superconducting fault current limiter (SFCL) for DC networks with a nominal voltage of 3.5 kV and a nominal current of 2 kA was developed, produced, and tested. The SFCL has two main units—an assembly of superconducting modules and a high-speed vacuum circuit breaker. The assembly of superconducting modules consists of nine (3 × 3) parallel-series connected modules. Each module contains four parallel-connected 2G high-temperature superconducting (HTS) tapes. The results of SFCL tests in the short-circuit emulation mode with a maximum current rise rate of 1300 A/ms are presented. The SFCL is capable of limiting the current at a level of 7 kA and break it 8 ms after the current-limiting mode begins. The average temperature of HTS tapes during the current-limiting mode increases to 210 K. After the current is interrupted, the superconductivity recovery time does not exceed 1 s.

Ad hoc Laser networks component technology for modular spacecraft

NASA Astrophysics Data System (ADS)

Huang, Xiujun; Shi, Dele; Ma, Zongfeng; Shen, Jingshi

2016-03-01

Distributed reconfigurable satellite is a new kind of spacecraft system, which is based on a flexible platform of modularization and standardization. Based on the module data flow analysis of the spacecraft, this paper proposes a network component of ad hoc Laser networks architecture. Low speed control network with high speed load network of Microwave-Laser communication mode, no mesh network mode, to improve the flexibility of the network. Ad hoc Laser networks component technology was developed, and carried out the related performance testing and experiment. The results showed that ad hoc Laser networks components can meet the demand of future networking between the module of spacecraft.

Ad hoc laser networks component technology for modular spacecraft

NASA Astrophysics Data System (ADS)

Huang, Xiujun; Shi, Dele; Shen, Jingshi

2017-10-01

Distributed reconfigurable satellite is a new kind of spacecraft system, which is based on a flexible platform of modularization and standardization. Based on the module data flow analysis of the spacecraft, this paper proposes a network component of ad hoc Laser networks architecture. Low speed control network with high speed load network of Microwave-Laser communication mode, no mesh network mode, to improve the flexibility of the network. Ad hoc Laser networks component technology was developed, and carried out the related performance testing and experiment. The results showed that ad hoc Laser networks components can meet the demand of future networking between the module of spacecraft.

Intrinsic functional network architecture of human semantic processing: Modules and hubs.

PubMed

Xu, Yangwen; Lin, Qixiang; Han, Zaizhu; He, Yong; Bi, Yanchao

2016-05-15

Semantic processing entails the activation of widely distributed brain areas across the temporal, parietal, and frontal lobes. To understand the functional structure of this semantic system, we examined its intrinsic functional connectivity pattern using a database of 146 participants. Focusing on areas consistently activated during semantic processing generated from a meta-analysis of 120 neuroimaging studies (Binder et al., 2009), we found that these regions were organized into three stable modules corresponding to the default mode network (Module DMN), the left perisylvian network (Module PSN), and the left frontoparietal network (Module FPN). These three dissociable modules were integrated by multiple connector hubs-the left angular gyrus (AG) and the left superior/middle frontal gyrus linking all three modules, the left anterior temporal lobe linking Modules DMN and PSN, the left posterior portion of dorsal intraparietal sulcus (IPS) linking Modules DMN and FPN, and the left posterior middle temporal gyrus (MTG) linking Modules PSN and FPN. Provincial hubs, which converge local information within each system, were also identified: the bilateral posterior cingulate cortices/precuneus, the bilateral border area of the posterior AG and the superior lateral occipital gyrus for Module DMN; the left supramarginal gyrus, the middle part of the left MTG and the left orbital inferior frontal gyrus (IFG) for Module FPN; and the left triangular IFG and the left IPS for Module FPN. A neuro-functional model for semantic processing was derived based on these findings, incorporating the interactions of memory, language, and control. Copyright © 2016 Elsevier Inc. All rights reserved.

Monoamines and neuropeptides interact to inhibit aversive behaviour in Caenorhabditis elegans.

PubMed

Mills, Holly; Wragg, Rachel; Hapiak, Vera; Castelletto, Michelle; Zahratka, Jeffrey; Harris, Gareth; Summers, Philip; Korchnak, Amanda; Law, Wenjing; Bamber, Bruce; Komuniecki, Richard

2012-02-01

Pain modulation is complex, but noradrenergic signalling promotes anti-nociception, with α(2)-adrenergic agonists used clinically. To better understand the noradrenergic/peptidergic modulation of nociception, we examined the octopaminergic inhibition of aversive behaviour initiated by the Caenorhabditis elegans nociceptive ASH sensory neurons. Octopamine (OA), the invertebrate counterpart of norepinephrine, modulates sensory-mediated reversal through three α-adrenergic-like OA receptors. OCTR-1 and SER-3 antagonistically modulate ASH signalling directly, with OCTR-1 signalling mediated by Gα(o). In contrast, SER-6 inhibits aversive responses by stimulating the release of an array of 'inhibitory' neuropeptides that activate receptors on sensory neurons mediating attraction or repulsion, suggesting that peptidergic signalling may integrate multiple sensory inputs to modulate locomotory transitions. These studies highlight the complexity of octopaminergic/peptidergic interactions, the role of OA in activating global peptidergic signalling cascades and the similarities of this modulatory network to the noradrenergic inhibition of nociception in mammals, where norepinephrine suppresses chronic pain through inhibitory α(2)-adrenoreceptors on afferent nociceptors and stimulatory α(1)-receptors on inhibitory peptidergic interneurons.

Monoamines and neuropeptides interact to inhibit aversive behaviour in Caenorhabditis elegans

PubMed Central

Mills, Holly; Wragg, Rachel; Hapiak, Vera; Castelletto, Michelle; Zahratka, Jeffrey; Harris, Gareth; Summers, Philip; Korchnak, Amanda; Law, Wenjing; Bamber, Bruce; Komuniecki, Richard

2012-01-01

Pain modulation is complex, but noradrenergic signalling promotes anti-nociception, with α2-adrenergic agonists used clinically. To better understand the noradrenergic/peptidergic modulation of nociception, we examined the octopaminergic inhibition of aversive behaviour initiated by the Caenorhabditis elegans nociceptive ASH sensory neurons. Octopamine (OA), the invertebrate counterpart of norepinephrine, modulates sensory-mediated reversal through three α-adrenergic-like OA receptors. OCTR-1 and SER-3 antagonistically modulate ASH signalling directly, with OCTR-1 signalling mediated by Gαo. In contrast, SER-6 inhibits aversive responses by stimulating the release of an array of ‘inhibitory' neuropeptides that activate receptors on sensory neurons mediating attraction or repulsion, suggesting that peptidergic signalling may integrate multiple sensory inputs to modulate locomotory transitions. These studies highlight the complexity of octopaminergic/peptidergic interactions, the role of OA in activating global peptidergic signalling cascades and the similarities of this modulatory network to the noradrenergic inhibition of nociception in mammals, where norepinephrine suppresses chronic pain through inhibitory α2-adrenoreceptors on afferent nociceptors and stimulatory α1-receptors on inhibitory peptidergic interneurons. PMID:22124329

Human tracking over camera networks: a review

NASA Astrophysics Data System (ADS)

Hou, Li; Wan, Wanggen; Hwang, Jenq-Neng; Muhammad, Rizwan; Yang, Mingyang; Han, Kang

2017-12-01

In recent years, automated human tracking over camera networks is getting essential for video surveillance. The tasks of tracking human over camera networks are not only inherently challenging due to changing human appearance, but also have enormous potentials for a wide range of practical applications, ranging from security surveillance to retail and health care. This review paper surveys the most widely used techniques and recent advances for human tracking over camera networks. Two important functional modules for the human tracking over camera networks are addressed, including human tracking within a camera and human tracking across non-overlapping cameras. The core techniques of human tracking within a camera are discussed based on two aspects, i.e., generative trackers and discriminative trackers. The core techniques of human tracking across non-overlapping cameras are then discussed based on the aspects of human re-identification, camera-link model-based tracking and graph model-based tracking. Our survey aims to address existing problems, challenges, and future research directions based on the analyses of the current progress made toward human tracking techniques over camera networks.

The Georgetown University Library Information System (LIS): a minicomputer-based integrated library system.

PubMed Central

Broering, N C

1983-01-01

Georgetown University's Library Information System (LIS), an integrated library system designed and implemented at the Dahlgren Memorial Library, is broadly described from an administrative point of view. LIS' functional components consist of eight "user-friendly" modules: catalog, circulation, serials, bibliographic management (including Mini-MEDLINE), acquisitions, accounting, networking, and computer-assisted instruction. This article touches on emerging library services, user education, and computer information services, which are also changing the role of staff librarians. The computer's networking capability brings the library directly to users through personal or institutional computers at remote sites. The proposed Integrated Medical Center Information System at Georgetown University will include interface with LIS through a network mechanism. LIS is being replicated at other libraries, and a microcomputer version is being tested for use in a hospital setting. PMID:6688749

Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

PubMed

He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

2012-06-25

Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the computational time significantly while keeping high prediction accuracy.

Modulation aware cluster size optimisation in wireless sensor networks

NASA Astrophysics Data System (ADS)

Sriram Naik, M.; Kumar, Vinay

2017-07-01

Wireless sensor networks (WSNs) play a great role because of their numerous advantages to the mankind. The main challenge with WSNs is the energy efficiency. In this paper, we have focused on the energy minimisation with the help of cluster size optimisation along with consideration of modulation effect when the nodes are not able to communicate using baseband communication technique. Cluster size optimisations is important technique to improve the performance of WSNs. It provides improvement in energy efficiency, network scalability, network lifetime and latency. We have proposed analytical expression for cluster size optimisation using traditional sensing model of nodes for square sensing field with consideration of modulation effects. Energy minimisation can be achieved by changing the modulation schemes such as BPSK, 16-QAM, QPSK, 64-QAM, etc., so we are considering the effect of different modulation techniques in the cluster formation. The nodes in the sensing fields are random and uniformly deployed. It is also observed that placement of base station at centre of scenario enables very less number of modulation schemes to work in energy efficient manner but when base station placed at the corner of the sensing field, it enable large number of modulation schemes to work in energy efficient manner.

Array processor architecture connection network

NASA Technical Reports Server (NTRS)

Barnes, George H. (Inventor); Lundstrom, Stephen F. (Inventor); Shafer, Philip E. (Inventor)

1982-01-01

A connection network is disclosed for use between a parallel array of processors and a parallel array of memory modules for establishing non-conflicting data communications paths between requested memory modules and requesting processors. The connection network includes a plurality of switching elements interposed between the processor array and the memory modules array in an Omega networking architecture. Each switching element includes a first and a second processor side port, a first and a second memory module side port, and control logic circuitry for providing data connections between the first and second processor ports and the first and second memory module ports. The control logic circuitry includes strobe logic for examining data arriving at the first and the second processor ports to indicate when the data arriving is requesting data from a requesting processor to a requested memory module. Further, connection circuitry is associated with the strobe logic for examining requesting data arriving at the first and the second processor ports for providing a data connection therefrom to the first and the second memory module ports in response thereto when the data connection so provided does not conflict with a pre-established data connection currently in use.

Enhancement of human cognitive performance using transcranial magnetic stimulation (TMS)

PubMed Central

Luber, Bruce; Lisanby, and Sarah H.

2014-01-01

Here we review the usefulness of transcranial magnetic stimulation (TMS) in modulating cortical networks in ways that might produce performance enhancements in healthy human subjects. To date over sixty studies have reported significant improvements in speed and accuracy in a variety of tasks involving perceptual, motor, and executive processing. Two basic categories of enhancement mechanisms are suggested by this literature: direct modulation of a cortical region or network that leads to more efficient processing, and addition-by-subtraction, which is disruption of processing which competes or distracts from task performance. Potential applications of TMS cognitive enhancement, including research into cortical function, rehabilitation therapy in neurological and psychiatric illness, and accelerated skill acquisition in healthy individuals are discussed, as are methods of optimizing the magnitude and duration of TMS-induced performance enhancement, such as improvement of targeting through further integration of brain imaging with TMS. One technique, combining multiple sessions of TMS with concurrent TMS/task performance to induce Hebbian-like learning, appears to be promising for prolonging enhancement effects. While further refinements in the application of TMS to cognitive enhancement can still be made, and questions remain regarding the mechanisms underlying the observed effects, this appears to be a fruitful area of investigation that may shed light on the basic mechanisms of cognitive function and their therapeutic modulation. PMID:23770409

Enhanced noise tolerance for 10 Gb/s Bi-directional cross-wavelength reuse colorless WDM-PON by using spectrally shaped OFDM signals

NASA Astrophysics Data System (ADS)

Choudhury, Pallab K.

2018-05-01

Spectrally shaped orthogonal frequency division multiplexing (OFDM) signal for symmetric 10 Gb/s cross-wavelength reuse reflective semiconductor optical amplifier (RSOA) based colorless wavelength division multiplexed passive optical network (WDM-PON) is proposed and further analyzed to support broadband services of next generation high speed optical access networks. The generated OFDM signal has subcarriers in separate frequency ranges for downstream and upstream, such that the re-modulation noise can be effectively minimized in upstream data receiver. Moreover, the cross wavelength reuse approach improves the tolerance against Rayleigh backscattering noise due to the propagation of different wavelengths in the same feeder fiber. The proposed WDM-PON is successfully demonstrated for 25 km fiber with 16-QAM (quadrature amplitude modulation) OFDM signal having bandwidth of 2.5 GHz for 10 Gb/s operation and subcarrier frequencies in 3-5.5 GHz and DC-2.5 GHz for downstream (DS) and upstream (US) transmission respectively. The result shows that the proposed scheme maintains a good bit error rate (BER) performance below the forward error correction (FEC) limit of 3.8 × 10-3 at acceptable receiver sensitivity and provides a high resilience against re-modulation and Rayleigh backscattering noises as well as chromatic dispersion.

Visual gene developer: a fully programmable bioinformatics software for synthetic gene optimization.

PubMed

Jung, Sang-Kyu; McDonald, Karen

2011-08-16

Direct gene synthesis is becoming more popular owing to decreases in gene synthesis pricing. Compared with using natural genes, gene synthesis provides a good opportunity to optimize gene sequence for specific applications. In order to facilitate gene optimization, we have developed a stand-alone software called Visual Gene Developer. The software not only provides general functions for gene analysis and optimization along with an interactive user-friendly interface, but also includes unique features such as programming capability, dedicated mRNA secondary structure prediction, artificial neural network modeling, network & multi-threaded computing, and user-accessible programming modules. The software allows a user to analyze and optimize a sequence using main menu functions or specialized module windows. Alternatively, gene optimization can be initiated by designing a gene construct and configuring an optimization strategy. A user can choose several predefined or user-defined algorithms to design a complicated strategy. The software provides expandable functionality as platform software supporting module development using popular script languages such as VBScript and JScript in the software programming environment. Visual Gene Developer is useful for both researchers who want to quickly analyze and optimize genes, and those who are interested in developing and testing new algorithms in bioinformatics. The software is available for free download at http://www.visualgenedeveloper.net.

Selective Attention to Semantic and Syntactic Features Modulates Sentence Processing Networks in Anterior Temporal Cortex

PubMed Central

Rogalsky, Corianne

2009-01-01

Numerous studies have identified an anterior temporal lobe (ATL) region that responds preferentially to sentence-level stimuli. It is unclear, however, whether this activity reflects a response to syntactic computations or some form of semantic integration. This distinction is difficult to investigate with the stimulus manipulations and anomaly detection paradigms traditionally implemented. The present functional magnetic resonance imaging study addresses this question via a selective attention paradigm. Subjects monitored for occasional semantic anomalies or occasional syntactic errors, thus directing their attention to semantic integration, or syntactic properties of the sentences. The hemodynamic response in the sentence-selective ATL region (defined with a localizer scan) was examined during anomaly/error-free sentences only, to avoid confounds due to error detection. The majority of the sentence-specific region of interest was equally modulated by attention to syntactic or compositional semantic features, whereas a smaller subregion was only modulated by the semantic task. We suggest that the sentence-specific ATL region is sensitive to both syntactic and integrative semantic functions during sentence processing, with a smaller portion of this area preferentially involved in the later. This study also suggests that selective attention paradigms may be effective tools to investigate the functional diversity of networks involved in sentence processing. PMID:18669589

Visual gene developer: a fully programmable bioinformatics software for synthetic gene optimization

PubMed Central

2011-01-01

Background Direct gene synthesis is becoming more popular owing to decreases in gene synthesis pricing. Compared with using natural genes, gene synthesis provides a good opportunity to optimize gene sequence for specific applications. In order to facilitate gene optimization, we have developed a stand-alone software called Visual Gene Developer. Results The software not only provides general functions for gene analysis and optimization along with an interactive user-friendly interface, but also includes unique features such as programming capability, dedicated mRNA secondary structure prediction, artificial neural network modeling, network & multi-threaded computing, and user-accessible programming modules. The software allows a user to analyze and optimize a sequence using main menu functions or specialized module windows. Alternatively, gene optimization can be initiated by designing a gene construct and configuring an optimization strategy. A user can choose several predefined or user-defined algorithms to design a complicated strategy. The software provides expandable functionality as platform software supporting module development using popular script languages such as VBScript and JScript in the software programming environment. Conclusion Visual Gene Developer is useful for both researchers who want to quickly analyze and optimize genes, and those who are interested in developing and testing new algorithms in bioinformatics. The software is available for free download at http://www.visualgenedeveloper.net. PMID:21846353

A novel network module for medical devices.

PubMed

Chen, Ping-Yu

2008-01-01

In order to allow medical devices to upload the vital signs to a server on a network without manually configuring for end-users, a new network module is proposed. The proposed network module, called Medical Hub (MH), functions as a bridge to fetch the data from all connecting medical devices, and then upload these data to the server. When powering on, the MH can immediately establish network configuration automatically. Network Address Translation (NAT) traversal is also supported by the MH with the UPnP Internet Gateway Device (IGD) methodology. Besides the network configuration, other configuration in the MH is automatically established by using the remote management protocol TR-069. On the other hand, a mechanism for updating software automatically according to the variant connected medical device is proposed. With this mechanism, newcome medical devices can be detected and supported by the MH without manual operation.

Low frequency steady-state brain responses modulate large scale functional networks in a frequency-specific means.

PubMed

Wang, Yi-Feng; Long, Zhiliang; Cui, Qian; Liu, Feng; Jing, Xiu-Juan; Chen, Heng; Guo, Xiao-Nan; Yan, Jin H; Chen, Hua-Fu

2016-01-01

Neural oscillations are essential for brain functions. Research has suggested that the frequency of neural oscillations is lower for more integrative and remote communications. In this vein, some resting-state studies have suggested that large scale networks function in the very low frequency range (<1 Hz). However, it is difficult to determine the frequency characteristics of brain networks because both resting-state studies and conventional frequency tagging approaches cannot simultaneously capture multiple large scale networks in controllable cognitive activities. In this preliminary study, we aimed to examine whether large scale networks can be modulated by task-induced low frequency steady-state brain responses (lfSSBRs) in a frequency-specific pattern. In a revised attention network test, the lfSSBRs were evoked in the triple network system and sensory-motor system, indicating that large scale networks can be modulated in a frequency tagging way. Furthermore, the inter- and intranetwork synchronizations as well as coherence were increased at the fundamental frequency and the first harmonic rather than at other frequency bands, indicating a frequency-specific modulation of information communication. However, there was no difference among attention conditions, indicating that lfSSBRs modulate the general attention state much stronger than distinguishing attention conditions. This study provides insights into the advantage and mechanism of lfSSBRs. More importantly, it paves a new way to investigate frequency-specific large scale brain activities. © 2015 Wiley Periodicals, Inc.

Preservation affinity in consensus modules among stages of HIV-1 progression.

PubMed

Mosaddek Hossain, Sk Md; Ray, Sumanta; Mukhopadhyay, Anirban

2017-03-20

Analysis of gene expression data provides valuable insights into disease mechanism. Investigating relationship among co-expression modules of different stages is a meaningful tool to understand the way in which a disease progresses. Identifying topological preservation of modular structure also contributes to that understanding. HIV-1 disease provides a well-documented progression pattern through three stages of infection: acute, chronic and non-progressor. In this article, we have developed a novel framework to describe the relationship among the consensus (or shared) co-expression modules for each pair of HIV-1 infection stages. The consensus modules are identified to assess the preservation of network properties. We have investigated the preservation patterns of co-expression networks during HIV-1 disease progression through an eigengene-based approach. We discovered that the expression patterns of consensus modules have a strong preservation during the transitions of three infection stages. In particular, it is noticed that between acute and non-progressor stages the preservation is slightly more than the other pair of stages. Moreover, we have constructed eigengene networks for the identified consensus modules and observed the preservation structure among them. Some consensus modules are marked as preserved in two pairs of stages and are analyzed further to form a higher order meta-network consisting of a group of preserved modules. Additionally, we observed that module membership (MM) values of genes within a module are consistent with the preservation characteristics. The MM values of genes within a pair of preserved modules show strong correlation patterns across two infection stages. We have performed an extensive analysis to discover preservation pattern of co-expression network constructed from microarray gene expression data of three different HIV-1 progression stages. The preservation pattern is investigated through identification of consensus modules in each pair of infection stages. It is observed that the preservation of the expression pattern of consensus modules remains more prominent during the transition of infection from acute stage to non-progressor stage. Additionally, we observed that the module membership values of genes are coherent with preserved modules across the HIV-1 progression stages.

Identification of functional modules using network topology and high-throughput data.

PubMed

Ulitsky, Igor; Shamir, Ron

2007-01-26

With the advent of systems biology, biological knowledge is often represented today by networks. These include regulatory and metabolic networks, protein-protein interaction networks, and many others. At the same time, high-throughput genomics and proteomics techniques generate very large data sets, which require sophisticated computational analysis. Usually, separate and different analysis methodologies are applied to each of the two data types. An integrated investigation of network and high-throughput information together can improve the quality of the analysis by accounting simultaneously for topological network properties alongside intrinsic features of the high-throughput data. We describe a novel algorithmic framework for this challenge. We first transform the high-throughput data into similarity values, (e.g., by computing pairwise similarity of gene expression patterns from microarray data). Then, given a network of genes or proteins and similarity values between some of them, we seek connected sub-networks (or modules) that manifest high similarity. We develop algorithms for this problem and evaluate their performance on the osmotic shock response network in S. cerevisiae and on the human cell cycle network. We demonstrate that focused, biologically meaningful and relevant functional modules are obtained. In comparison with extant algorithms, our approach has higher sensitivity and higher specificity. We have demonstrated that our method can accurately identify functional modules. Hence, it carries the promise to be highly useful in analysis of high throughput data.

Correlation between Academic and Skills-Based Tests in Computer Networks

ERIC Educational Resources Information Center

Buchanan, William

2006-01-01

Computing-related programmes and modules have many problems, especially related to large class sizes, large-scale plagiarism, module franchising, and an increased requirement from students for increased amounts of hands-on, practical work. This paper presents a practical computer networks module which uses a mixture of online examinations and a…

Generation of oscillating gene regulatory network motifs

NASA Astrophysics Data System (ADS)

van Dorp, M.; Lannoo, B.; Carlon, E.

2013-07-01

Using an improved version of an evolutionary algorithm originally proposed by François and Hakim [Proc. Natl. Acad. Sci. USAPNASA60027-842410.1073/pnas.0304532101 101, 580 (2004)], we generated small gene regulatory networks in which the concentration of a target protein oscillates in time. These networks may serve as candidates for oscillatory modules to be found in larger regulatory networks and protein interaction networks. The algorithm was run for 105 times to produce a large set of oscillating modules, which were systematically classified and analyzed. The robustness of the oscillations against variations of the kinetic rates was also determined, to filter out the least robust cases. Furthermore, we show that the set of evolved networks can serve as a database of models whose behavior can be compared to experimentally observed oscillations. The algorithm found three smallest (core) oscillators in which nonlinearities and number of components are minimal. Two of those are two-gene modules: the mixed feedback loop, already discussed in the literature, and an autorepressed gene coupled with a heterodimer. The third one is a single gene module which is competitively regulated by a monomer and a dimer. The evolutionary algorithm also generated larger oscillating networks, which are in part extensions of the three core modules and in part genuinely new modules. The latter includes oscillators which do not rely on feedback induced by transcription factors, but are purely of post-transcriptional type. Analysis of post-transcriptional mechanisms of oscillation may provide useful information for circadian clock research, as recent experiments showed that circadian rhythms are maintained even in the absence of transcription.

SABRE: a method for assessing the stability of gene modules in complex tissues and subject populations.

PubMed

Shannon, Casey P; Chen, Virginia; Takhar, Mandeep; Hollander, Zsuzsanna; Balshaw, Robert; McManus, Bruce M; Tebbutt, Scott J; Sin, Don D; Ng, Raymond T

2016-11-14

Gene network inference (GNI) algorithms can be used to identify sets of coordinately expressed genes, termed network modules from whole transcriptome gene expression data. The identification of such modules has become a popular approach to systems biology, with important applications in translational research. Although diverse computational and statistical approaches have been devised to identify such modules, their performance behavior is still not fully understood, particularly in complex human tissues. Given human heterogeneity, one important question is how the outputs of these computational methods are sensitive to the input sample set, or stability. A related question is how this sensitivity depends on the size of the sample set. We describe here the SABRE (Similarity Across Bootstrap RE-sampling) procedure for assessing the stability of gene network modules using a re-sampling strategy, introduce a novel criterion for identifying stable modules, and demonstrate the utility of this approach in a clinically-relevant cohort, using two different gene network module discovery algorithms. The stability of modules increased as sample size increased and stable modules were more likely to be replicated in larger sets of samples. Random modules derived from permutated gene expression data were consistently unstable, as assessed by SABRE, and provide a useful baseline value for our proposed stability criterion. Gene module sets identified by different algorithms varied with respect to their stability, as assessed by SABRE. Finally, stable modules were more readily annotated in various curated gene set databases. The SABRE procedure and proposed stability criterion may provide guidance when designing systems biology studies in complex human disease and tissues.

Visual search, visual streams, and visual architectures.

PubMed

Green, M

1991-10-01

Most psychological, physiological, and computational models of early vision suggest that retinal information is divided into a parallel set of feature modules. The dominant theories of visual search assume that these modules form a "blackboard" architecture: a set of independent representations that communicate only through a central processor. A review of research shows that blackboard-based theories, such as feature-integration theory, cannot easily explain the existing data. The experimental evidence is more consistent with a "network" architecture, which stresses that: (1) feature modules are directly connected to one another, (2) features and their locations are represented together, (3) feature detection and integration are not distinct processing stages, and (4) no executive control process, such as focal attention, is needed to integrate features. Attention is not a spotlight that synthesizes objects from raw features. Instead, it is better to conceptualize attention as an aperture which masks irrelevant visual information.

Dual-drive Mach-Zehnder modulator-based reconfigurable and transparent spectral conversion for dense wavelength division multiplexing transmissions

NASA Astrophysics Data System (ADS)

Mao, Mingzhi; Qian, Chen; Cao, Bingyao; Zhang, Qianwu; Song, Yingxiong; Wang, Min

2017-09-01

A digital signal process enabled dual-drive Mach-Zehnder modulator (DD-MZM)-based spectral converter is proposed and extensively investigated to realize dynamically reconfigurable and high transparent spectral conversion. As another important innovation point of the paper, to optimize the converter performance, the optimum operation conditions of the proposed converter are deduced, statistically simulated, and experimentally verified. The optimum conditions supported-converter performances are verified by detail numerical simulations and experiments in intensity-modulation and direct-detection-based network in terms of frequency detuning range-dependent conversion efficiency, strict operation transparency for user signal characteristics, impact of parasitic components on the conversion performance, as well as the converted component waveform are almost nondistortion. It is also found that the converter has the high robustness to the input signal power, optical signal-to-noise ratio variations, extinction ratio, and driving signal frequency.

Emotional Intent Modulates The Neural Substrates Of Creativity: An fMRI Study of Emotionally Targeted Improvisation in Jazz Musicians.

PubMed

McPherson, Malinda J; Barrett, Frederick S; Lopez-Gonzalez, Monica; Jiradejvong, Patpong; Limb, Charles J

2016-01-04

Emotion is a primary motivator for creative behaviors, yet the interaction between the neural systems involved in creativity and those involved in emotion has not been studied. In the current study, we addressed this gap by using fMRI to examine piano improvisation in response to emotional cues. We showed twelve professional jazz pianists photographs of an actress representing a positive, negative or ambiguous emotion. Using a non-ferromagnetic thirty-five key keyboard, the pianists improvised music that they felt represented the emotion expressed in the photographs. Here we show that activity in prefrontal and other brain networks involved in creativity is highly modulated by emotional context. Furthermore, emotional intent directly modulated functional connectivity of limbic and paralimbic areas such as the amygdala and insula. These findings suggest that emotion and creativity are tightly linked, and that the neural mechanisms underlying creativity may depend on emotional state.

Effects of Transcranial Direct Current Stimulation on Neural Networks in Young and Older Adults

PubMed

Martin, Andrew K; Meinzer, Marcus; Lindenberg, Robert; Sieg, Mira M; Nachtigall, Laura; Flöel, Agnes

2017-11-01

Transcranial direct current stimulation (tDCS) may be a viable tool to improve motor and cognitive function in advanced age. However, although a number of studies have demonstrated improved cognitive performance in older adults, other studies have failed to show restorative effects. The neural effects of beneficial stimulation response in both age groups is lacking. In the current study, tDCS was administered during simultaneous fMRI in 42 healthy young and older participants. Semantic word generation and motor speech baseline tasks were used to investigate behavioral and neural effects of uni- and bihemispheric motor cortex tDCS in a three-way, crossover, sham tDCS controlled design. Independent components analysis assessed differences in task-related activity between the two age groups and tDCS effects at the network level. We also explored whether laterality of language network organization was effected by tDCS. Behaviorally, both active tDCS conditions significantly improved semantic word retrieval performance in young and older adults and were comparable between groups and stimulation conditions. Network-level tDCS effects were identified in the ventral and dorsal anterior cingulate networks in the combined sample during semantic fluency and motor speech tasks. In addition, a shift toward enhanced left laterality was identified in the older adults for both active stimulation conditions. Thus, tDCS results in common network-level modulations and behavioral improvements for both age groups, with an additional effect of increasing left laterality in older adults.

Excavation of attractor modules for nasopharyngeal carcinoma via integrating systemic module inference with attract method.

PubMed

Jiang, T; Jiang, C-Y; Shu, J-H; Xu, Y-J

2017-07-10

The molecular mechanism of nasopharyngeal carcinoma (NPC) is poorly understood and effective therapeutic approaches are needed. This research aimed to excavate the attractor modules involved in the progression of NPC and provide further understanding of the underlying mechanism of NPC. Based on the gene expression data of NPC, two specific protein-protein interaction networks for NPC and control conditions were re-weighted using Pearson correlation coefficient. Then, a systematic tracking of candidate modules was conducted on the re-weighted networks via cliques algorithm, and a total of 19 and 38 modules were separately identified from NPC and control networks, respectively. Among them, 8 pairs of modules with similar gene composition were selected, and 2 attractor modules were identified via the attract method. Functional analysis indicated that these two attractor modules participate in one common bioprocess of cell division. Based on the strategy of integrating systemic module inference with the attract method, we successfully identified 2 attractor modules. These attractor modules might play important roles in the molecular pathogenesis of NPC via affecting the bioprocess of cell division in a conjunct way. Further research is needed to explore the correlations between cell division and NPC.

The dark side of the alpha rhythm: fMRI evidence for induced alpha modulation during complete darkness.

PubMed

Ben-Simon, Eti; Podlipsky, Ilana; Okon-Singer, Hadas; Gruberger, Michal; Cvetkovic, Dean; Intrator, Nathan; Hendler, Talma

2013-03-01

The unique role of the EEG alpha rhythm in different states of cortical activity is still debated. The main theories regarding alpha function posit either sensory processing or attention allocation as the main processes governing its modulation. Closing and opening eyes, a well-known manipulation of the alpha rhythm, could be regarded as attention allocation from inward to outward focus though during light is also accompanied by visual change. To disentangle the effects of attention allocation and sensory visual input on alpha modulation, 14 healthy subjects were asked to open and close their eyes during conditions of light and of complete darkness while simultaneous recordings of EEG and fMRI were acquired. Thus, during complete darkness the eyes-open condition is not related to visual input but only to attention allocation, allowing direct examination of its role in alpha modulation. A data-driven ridge regression classifier was applied to the EEG data in order to ascertain the contribution of the alpha rhythm to eyes-open/eyes-closed inference in both lighting conditions. Classifier results revealed significant alpha contribution during both light and dark conditions, suggesting that alpha rhythm modulation is closely linked to the change in the direction of attention regardless of the presence of visual sensory input. Furthermore, fMRI activation maps derived from an alpha modulation time-course during the complete darkness condition exhibited a right frontal cortical network associated with attention allocation. These findings support the importance of top-down processes such as attention allocation to alpha rhythm modulation, possibly as a prerequisite to its known bottom-up processing of sensory input. © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Identification of a gene module associated with BMD through the integration of network analysis and genome-wide association data.

PubMed

Farber, Charles R

2010-11-01

Bone mineral density (BMD) is influenced by a complex network of gene interactions; therefore, elucidating the relationships between genes and how those genes, in turn, influence BMD is critical for developing a comprehensive understanding of osteoporosis. To investigate the role of transcriptional networks in the regulation of BMD, we performed a weighted gene coexpression network analysis (WGCNA) using microarray expression data on monocytes from young individuals with low or high BMD. WGCNA groups genes into modules based on patterns of gene coexpression. and our analysis identified 11 gene modules. We observed that the overall expression of one module (referred to as module 9) was significantly higher in the low-BMD group (p = .03). Module 9 was highly enriched for genes belonging to the immune system-related gene ontology (GO) category "response to virus" (p = 7.6 × 10(-11)). Using publically available genome-wide association study data, we independently validated the importance of module 9 by demonstrating that highly connected module 9 hubs were more likely, relative to less highly connected genes, to be genetically associated with BMD. This study highlights the advantages of systems-level analyses to uncover coexpression modules associated with bone mass and suggests that particular monocyte expression patterns may mediate differences in BMD. © 2010 American Society for Bone and Mineral Research.

A system's view of metro and regional optical networks

NASA Astrophysics Data System (ADS)

Lam, Cedric F.; Way, Winston I.

2009-01-01

Developments in fiber optic communications have been rejuvenated after the glut of the overcapacity at the turn of the century. The boom of video-centric network applications finally resulted in another wave of vast build-outs of broadband access networks such as FTTH, DOCSIS 3.0 and WI-FI systems, which in turn also drove up the bandwidth demands in metro and regional WDM networks. These new developments have rekindled research interests on technologies not only to meet the surging demand, but also to upgrade legacy network infrastructures in an evolutionary manner without disrupting existing services and incurring significant capital penalties. Standard bodies such as IEEE, ITU and OIF have formed task forces to ratify 100Gb/s interface standards. Thanks to the seemingly unlimited bandwidth in single-mode fibers, advances in optical networks has traditionally been fueled by more capable physical components such as more powerful laser, cleaner and wider bandwidth optical amplifier, faster modulator and photo-detectors, etc. In the meanwhile, the mainstream modulation technique for fiber optic communication systems has remained the most rudimentary form of on-off keying (OOK) and direct power detection for a very long period of time because spectral efficiency had never been a concern. This scenario, however, is no longer valid as demand for bandwidth is pushing the limit of current of current WDM technologies. In terms of spectral use, all the 100-GHz ITU grids in the C-band have been populated with 10Gb/s wavelengths in most of the WDM transport networks, and we are exhausting the power and bandwidth offered on existing fiber plant EDFAs. Beyond 10Gb/s, increasing the transmission to 40Gb/s by brute force OOK approach incurs significant penalties due to chromatic and polarization mode dispersion. With conventional modulation schemes, transmission impairments at 40Gb/s speed and above already become such difficult challenges that the efforts to manage these problem have severely hindered the rate of return on the investment from an economical viewpoint, let alone 100Gb/s transmission. In addition, to enable fast turn-up of new services and reduce network operation costs, carriers are also deploying reconfigurable optical add/drop multiplexers (ROADMs) and transparent optical networks. ROADMs impose more impairments to transmitted signals and are important considerations in designing backbone transmission links. Recently, advanced modulation schemes have been investigated in both the academia and industry as ways to improve the spectral efficiency and alleviate transmission impairments. Signal processing techniques familiar to traditional telecommunication engineers are also playing more and more important roles in optical communications because of the fast advance in mixed signal processing and growing abundance of computational power. In this invited talk, we review the current challenges faced in upgrading existing 10Gb/s metro and regional WDM networks and the potential solutions to enable 40 and 100Gb/s wavelength services.

Corrected and Republished from: BCL11A Is a Critical Component of a Transcriptional Network That Activates Recombinase Activating Gene Expression and V(D)J Recombination

PubMed Central

Lee, Baeck-Seung; Lee, Bum-Kyu; Iyer, Vishwanath R.; Sleckman, Barry P.; Shaffer, Arthur L.; Ippolito, Gregory C.

2017-01-01

ABSTRACT Recombination activating gene 1 (RAG1) and RAG2 are critical enzymes for initiating variable-diversity-joining [V(D)J] segment recombination, an essential process for antigen receptor expression and lymphocyte development. The BCL11A transcription factor is required for B cell and plasmacytoid dendritic cell (pDC) development, but its molecular function(s) in early B cell fate specification and commitment is unknown. We show here that the major B cell isoform, BCL11A-XL, binds directly to the RAG1 promoter as well as directly to regulatory regions of transcription factors previously implicated in both B cell and pDC development to activate RAG1 and RAG2 gene transcription in pro- and pre-B cells. We employed BCL11A overexpression with recombination substrates to demonstrate direct consequences of BCL11A/RAG modulation on V(D)J recombination. We conclude that BCL11A is a critical component of a transcriptional network that regulates B cell fate by controlling V(D)J recombination. PMID:29038163

ModuleRole: a tool for modulization, role determination and visualization in protein-protein interaction networks.

PubMed

Li, Guipeng; Li, Ming; Zhang, Yiwei; Wang, Dong; Li, Rong; Guimerà, Roger; Gao, Juntao Tony; Zhang, Michael Q

2014-01-01

Rapidly increasing amounts of (physical and genetic) protein-protein interaction (PPI) data are produced by various high-throughput techniques, and interpretation of these data remains a major challenge. In order to gain insight into the organization and structure of the resultant large complex networks formed by interacting molecules, using simulated annealing, a method based on the node connectivity, we developed ModuleRole, a user-friendly web server tool which finds modules in PPI network and defines the roles for every node, and produces files for visualization in Cytoscape and Pajek. For given proteins, it analyzes the PPI network from BioGRID database, finds and visualizes the modules these proteins form, and then defines the role every node plays in this network, based on two topological parameters Participation Coefficient and Z-score. This is the first program which provides interactive and very friendly interface for biologists to find and visualize modules and roles of proteins in PPI network. It can be tested online at the website http://www.bioinfo.org/modulerole/index.php, which is free and open to all users and there is no login requirement, with demo data provided by "User Guide" in the menu Help. Non-server application of this program is considered for high-throughput data with more than 200 nodes or user's own interaction datasets. Users are able to bookmark the web link to the result page and access at a later time. As an interactive and highly customizable application, ModuleRole requires no expert knowledge in graph theory on the user side and can be used in both Linux and Windows system, thus a very useful tool for biologist to analyze and visualize PPI networks from databases such as BioGRID. ModuleRole is implemented in Java and C, and is freely available at http://www.bioinfo.org/modulerole/index.php. Supplementary information (user guide, demo data) is also available at this website. API for ModuleRole used for this program can be obtained upon request.

Mathematical modeling and computational prediction of cancer drug resistance.

PubMed

Sun, Xiaoqiang; Hu, Bin

2017-06-23

Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of computational methods for studying drug resistance, including inferring drug-induced signaling networks, multiscale modeling, drug combinations and precision medicine. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Network modulation during complex syntactic processing

PubMed Central

den Ouden, Dirk-Bart; Saur, Dorothee; Mader, Wolfgang; Schelter, Björn; Lukic, Sladjana; Wali, Eisha; Timmer, Jens; Thompson, Cynthia K.

2011-01-01

Complex sentence processing is supported by a left-lateralized neural network including inferior frontal cortex and posterior superior temporal cortex. This study investigates the pattern of connectivity and information flow within this network. We used fMRI BOLD data derived from 12 healthy participants reported in an earlier study (Thompson, C. K., Den Ouden, D. B., Bonakdarpour, B., Garibaldi, K., & Parrish, T. B. (2010b). Neural plasticity and treatment-induced recovery of sentence processing in agrammatism. Neuropsychologia, 48(11), 3211-3227) to identify activation peaks associated with object-cleft over syntactically less complex subject-cleft processing. Directed Partial Correlation Analysis was conducted on time series extracted from participant-specific activation peaks and showed evidence of functional connectivity between four regions, linearly between premotor cortex, inferior frontal gyrus, posterior superior temporal sulcus and anterior middle temporal gyrus. This pattern served as the basis for Dynamic Causal Modeling of networks with a driving input to posterior superior temporal cortex, which likely supports thematic role assignment, and networks with a driving input to inferior frontal cortex, a core region associated with syntactic computation. The optimal model was determined through both frequentist and Bayesian model selection and turned out to reflect a network with a primary drive from inferior frontal cortex and modulation of the connection between inferior frontal and posterior superior temporal cortex by complex sentence processing. The winning model also showed a substantive role for a feedback mechanism from posterior superior temporal cortex back to inferior frontal cortex. We suggest that complex syntactic processing is driven by word-order analysis, supported by inferior frontal cortex, in an interactive relation with posterior superior temporal cortex, which supports verb argument structure processing. PMID:21820518

Hubless satellite communications networks

NASA Technical Reports Server (NTRS)

Robinson, Peter Alan

1994-01-01

Frequency Comb Multiple Access (FCMA) is a new combined modulation and multiple access method which will allow cheap hubless Very Small Aperture Terminal (VSAT) networks to be constructed. Theoretical results show bandwidth efficiency and power efficiency improvements over other modulation and multiple access methods. Costs of the VSAT network are reduced dramatically since a hub station is not required.

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.

A software sensor model based on hybrid fuzzy neural network for rapid estimation water quality in Guangzhou section of Pearl River, China.

PubMed

Zhou, Chunshan; Zhang, Chao; Tian, Di; Wang, Ke; Huang, Mingzhi; Liu, Yanbiao

2018-01-02

In order to manage water resources, a software sensor model was designed to estimate water quality using a hybrid fuzzy neural network (FNN) in Guangzhou section of Pearl River, China. The software sensor system was composed of data storage module, fuzzy decision-making module, neural network module and fuzzy reasoning generator module. Fuzzy subtractive clustering was employed to capture the character of model, and optimize network architecture for enhancing network performance. The results indicate that, on basis of available on-line measured variables, the software sensor model can accurately predict water quality according to the relationship between chemical oxygen demand (COD) and dissolved oxygen (DO), pH and NH 4 + -N. Owing to its ability in recognizing time series patterns and non-linear characteristics, the software sensor-based FNN is obviously superior to the traditional neural network model, and its R (correlation coefficient), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 0.8931, 10.9051 and 0.4634, respectively.

Resonant tunneling diode oscillators for optical communications

NASA Astrophysics Data System (ADS)

Watson, Scott; Zhang, Weikang; Wang, Jue; Al-Khalidi, Abdullah; Cantu, Horacio; Figueiredo, Jose; Wasige, Edward; Kelly, Anthony E.

2017-08-01

The ability to use resonant tunneling diodes (RTDs) as both transmitters and receivers is an emerging topic, especially with regards to wireless communications. Successful data transmission has been achieved using electronic RTDs with carrier frequencies exceeding 0.3 THz. Specific optical-based RTDs, which act as photodetectors, have been developed by adjusting the device structure to include a light absorption layer and small optical windows on top of the device to allow direct optical access. This also allows the optical signal to directly modulate the RTD oscillation. Both types of RTD oscillators will allow for seamless integration of high frequency radio and optical fiber networks.

Assessing Robustness Properties in Dynamic Discovery of Ad Hoc Network Services (Briefing Charts)

DTIC Science & Technology

2001-10-04

JINI entities in directed -- discovery mode. It is part of the SCM_Discovery -- Module. Sends Unicast messages to SCMs on list of -- SCMS to be...discovered until all SCMS are found. -- Receives updates from SCM DB of discovered SCMs and -- removes SCMs accordingly -- NOTE: Failure and...For All (SM, SD, SCM ): (SM, SD) IsElementOf SCM registered-services (CC1) implies SCM IsElementOf SM discovered- SCMs For All

Large-Scale Network Analysis of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Comparative Study.

PubMed

Kaushal, Mayank; Oni-Orisan, Akinwunmi; Chen, Gang; Li, Wenjun; Leschke, Jack; Ward, Doug; Kalinosky, Benjamin; Budde, Matthew; Schmit, Brian; Li, Shi-Jiang; Muqeet, Vaishnavi; Kurpad, Shekar

2017-09-01

Network analysis based on graph theory depicts the brain as a complex network that allows inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects, fifteen subjects with chronic complete cervical SCI and 15 neurologically intact controls were scanned. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI). Correlation analysis was performed between every ROI pair to construct connectivity matrices and ROIs were categorized into distinct modules. Subsequently, local efficiency (LE) and global efficiency (GE) network metrics were calculated at incremental cost thresholds. The application of a modularity algorithm organized the whole-brain resting-state functional network of the SCI and the control subjects into nine and seven modules, respectively. The individual modules differed across groups in terms of the number and the composition of constituent nodes. LE demonstrated statistically significant decrease at multiple cost levels in SCI subjects. GE did not differ significantly between the two groups. The demonstration of modular architecture in both groups highlights the applicability of large-scale network analysis in studying complex brain networks. Comparing modules across groups revealed differences in number and membership of constituent nodes, indicating modular reorganization due to neural plasticity.

Elimination of spiral waves in a locally connected chaotic neural network by a dynamic phase space constraint.

PubMed

Li, Yang; Oku, Makito; He, Guoguang; Aihara, Kazuyuki

2017-04-01

In this study, a method is proposed that eliminates spiral waves in a locally connected chaotic neural network (CNN) under some simplified conditions, using a dynamic phase space constraint (DPSC) as a control method. In this method, a control signal is constructed from the feedback internal states of the neurons to detect phase singularities based on their amplitude reduction, before modulating a threshold value to truncate the refractory internal states of the neurons and terminate the spirals. Simulations showed that with appropriate parameter settings, the network was directed from a spiral wave state into either a plane wave (PW) state or a synchronized oscillation (SO) state, where the control vanished automatically and left the original CNN model unaltered. Each type of state had a characteristic oscillation frequency, where spiral wave states had the highest, and the intra-control dynamics was dominated by low-frequency components, thereby indicating slow adjustments to the state variables. In addition, the PW-inducing and SO-inducing control processes were distinct, where the former generally had longer durations but smaller average proportions of affected neurons in the network. Furthermore, variations in the control parameter allowed partial selectivity of the control results, which were accompanied by modulation of the control processes. The results of this study broaden the applicability of DPSC to chaos control and they may also facilitate the utilization of locally connected CNNs in memory retrieval and the exploration of traveling wave dynamics in biological neural networks. Copyright © 2017 Elsevier Ltd. All rights reserved.

Regulatory network analysis of Epstein-Barr virus identifies functional modules and hub genes involved in infectious mononucleosis.

PubMed

Poorebrahim, Mansour; Salarian, Ali; Najafi, Saeideh; Abazari, Mohammad Foad; Aleagha, Maryam Nouri; Dadras, Mohammad Nasr; Jazayeri, Seyed Mohammad; Ataei, Atousa; Poortahmasebi, Vahdat

2017-05-01

Epstein-Barr virus (EBV) is the most common cause of infectious mononucleosis (IM) and establishes lifetime infection associated with a variety of cancers and autoimmune diseases. The aim of this study was to develop an integrative gene regulatory network (GRN) approach and overlying gene expression data to identify the representative subnetworks for IM and EBV latent infection (LI). After identifying differentially expressed genes (DEGs) in both IM and LI gene expression profiles, functional annotations were applied using gene ontology (GO) and BiNGO tools, and construction of GRNs, topological analysis and identification of modules were carried out using several plugins of Cytoscape. In parallel, a human-EBV GRN was generated using the Hu-Vir database for further analyses. Our analysis revealed that the majority of DEGs in both IM and LI were involved in cell-cycle and DNA repair processes. However, these genes showed a significant negative correlation in the IM and LI states. Furthermore, cyclin-dependent kinase 2 (CDK2) - a hub gene with the highest centrality score - appeared to be the key player in cell cycle regulation in IM disease. The most significant functional modules in the IM and LI states were involved in the regulation of the cell cycle and apoptosis, respectively. Human-EBV network analysis revealed several direct targets of EBV proteins during IM disease. Our study provides an important first report on the response to IM/LI EBV infection in humans. An important aspect of our data was the upregulation of genes associated with cell cycle progression and proliferation.

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

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

PubMed Central

Qin, Wei; Tian, Jie; Bai, Lijun; Pan, Xiaohong; Yang, Lin; Chen, Peng; Dai, Jianping; Ai, Lin; Zhao, Baixiao; Gong, Qiyong; Wang, Wei; von Deneen, Karen M; Liu, Yijun

2008-01-01

Background Recently, increasing evidence has indicated that the primary acupuncture effects are mediated by the central nervous system. However, specific brain networks underpinning these effects remain unclear. Results In the present study using fMRI, we employed a within-condition interregional covariance analysis method to investigate functional connectivity of brain networks involved in acupuncture. The fMRI experiment was performed before, during and after acupuncture manipulations on healthy volunteers at an acupuncture point, which was previously implicated in a neural pathway for pain modulation. We first identified significant fMRI signal changes during acupuncture stimulation in the left amygdala, which was subsequently selected as a functional reference for connectivity analyses. Our results have demonstrated that there is a brain network associated with the amygdala during a resting condition. This network encompasses the brain structures that are implicated in both pain sensation and pain modulation. We also found that such a pain-related network could be modulated by both verum acupuncture and sham acupuncture. Furthermore, compared with a sham acupuncture, the verum acupuncture induced a higher level of correlations among the amygdala-associated network. Conclusion Our findings indicate that acupuncture may change this amygdala-specific brain network into a functional state that underlies pain perception and pain modulation. PMID:19014532

Identifying module biomarkers from gastric cancer by differential correlation network

PubMed Central

Liu, Xiaoping; Chang, Xiao

2016-01-01

Gastric cancer (stomach cancer) is a severe disease caused by dysregulation of many functionally correlated genes or pathways instead of the mutation of individual genes. Systematic identification of gastric cancer biomarkers can provide insights into the mechanisms underlying this deadly disease and help in the development of new drugs. In this paper, we present a novel network-based approach to predict module biomarkers of gastric cancer that can effectively distinguish the disease from normal samples. Specifically, by assuming that gastric cancer has mainly resulted from dysfunction of biomolecular networks rather than individual genes in an organism, the genes in the module biomarkers are potentially related to gastric cancer. Finally, we identified a module biomarker with 27 genes, and by comparing the module biomarker with known gastric cancer biomarkers, we found that our module biomarker exhibited a greater ability to diagnose the samples with gastric cancer. PMID:27703371

Optimal design of reverse osmosis module networks

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

Maskan, F.; Wiley, D.E.; Johnston, L.P.M.

2000-05-01

The structure of individual reverse osmosis modules, the configuration of the module network, and the operating conditions were optimized for seawater and brackish water desalination. The system model included simple mathematical equations to predict the performance of the reverse osmosis modules. The optimization problem was formulated as a constrained multivariable nonlinear optimization. The objective function was the annual profit for the system, consisting of the profit obtained from the permeate, capital cost for the process units, and operating costs associated with energy consumption and maintenance. Optimization of several dual-stage reverse osmosis systems were investigated and compared. It was found thatmore » optimal network designs are the ones that produce the most permeate. It may be possible to achieve economic improvements by refining current membrane module designs and their operating pressures.« less

Phonological experience modulates voice discrimination: Evidence from functional brain networks analysis.

PubMed

Hu, Xueping; Wang, Xiangpeng; Gu, Yan; Luo, Pei; Yin, Shouhang; Wang, Lijun; Fu, Chao; Qiao, Lei; Du, Yi; Chen, Antao

2017-10-01

Numerous behavioral studies have found a modulation effect of phonological experience on voice discrimination. However, the neural substrates underpinning this phenomenon are poorly understood. Here we manipulated language familiarity to test the hypothesis that phonological experience affects voice discrimination via mediating the engagement of multiple perceptual and cognitive resources. The results showed that during voice discrimination, the activation of several prefrontal regions was modulated by language familiarity. More importantly, the same effect was observed concerning the functional connectivity from the fronto-parietal network to the voice-identity network (VIN), and from the default mode network to the VIN. Our findings indicate that phonological experience could bias the recruitment of cognitive control and information retrieval/comparison processes during voice discrimination. Therefore, the study unravels the neural substrates subserving the modulation effect of phonological experience on voice discrimination, and provides new insights into studying voice discrimination from the perspective of network interactions. Copyright © 2017. Published by Elsevier Inc.

Resilience of networks formed of interdependent modular networks

NASA Astrophysics Data System (ADS)

Shekhtman, Louis M.; Shai, Saray; Havlin, Shlomo

2015-12-01

Many infrastructure networks have a modular structure and are also interdependent with other infrastructures. While significant research has explored the resilience of interdependent networks, there has been no analysis of the effects of modularity. Here we develop a theoretical framework for attacks on interdependent modular networks and support our results through simulations. We focus, for simplicity, on the case where each network has the same number of communities and the dependency links are restricted to be between pairs of communities of different networks. This is particularly realistic for modeling infrastructure across cities. Each city has its own infrastructures and different infrastructures are dependent only within the city. However, each infrastructure is connected within and between cities. For example, a power grid will connect many cities as will a communication network, yet a power station and communication tower that are interdependent will likely be in the same city. It has previously been shown that single networks are very susceptible to the failure of the interconnected nodes (between communities) (Shai et al 2014 arXiv:1404.4748) and that attacks on these nodes are even more crippling than attacks based on betweenness (da Cunha et al 2015 arXiv:1502.00353). In our example of cities these nodes have long range links which are more likely to fail. For both treelike and looplike interdependent modular networks we find distinct regimes depending on the number of modules, m. (i) In the case where there are fewer modules with strong intraconnections, the system first separates into modules in an abrupt first-order transition and then each module undergoes a second percolation transition. (ii) When there are more modules with many interconnections between them, the system undergoes a single transition. Overall, we find that modular structure can significantly influence the type of transitions observed in interdependent networks and should be considered in attempts to make interdependent networks more resilient.

Modular architecture for robotics and teleoperation

DOEpatents

Anderson, Robert J.

1996-12-03

Systems and methods for modularization and discretization of real-time robot, telerobot and teleoperation systems using passive, network based control laws. Modules consist of network one-ports and two-ports. Wave variables and position information are passed between modules. The behavior of each module is decomposed into uncoupled linear-time-invariant, and coupled, nonlinear memoryless elements and then are separately discretized.

Activity recognition using dynamic multiple sensor fusion in body sensor networks.

PubMed

Gao, Lei; Bourke, Alan K; Nelson, John

2012-01-01

Multiple sensor fusion is a main research direction for activity recognition. However, there are two challenges in those systems: the energy consumption due to the wireless transmission and the classifier design because of the dynamic feature vector. This paper proposes a multi-sensor fusion framework, which consists of the sensor selection module and the hierarchical classifier. The sensor selection module adopts the convex optimization to select the sensor subset in real time. The hierarchical classifier combines the Decision Tree classifier with the Naïve Bayes classifier. The dataset collected from 8 subjects, who performed 8 scenario activities, was used to evaluate the proposed system. The results show that the proposed system can obviously reduce the energy consumption while guaranteeing the recognition accuracy.

24-26  GHz radio-over-fiber and free-space optics for fifth-generation systems.

PubMed

Bohata, Jan; Komanec, Matěj; Spáčil, Jan; Ghassemlooy, Zabih; Zvánovec, Stanislav; Slavík, Radan

2018-03-01

This Letter outlines radio-over-fiber combined with radio-over-free-space optics (RoFSO) and radio frequency free-space transmission, which is of particular relevance for fifth-generation networks. Here, the frequency band of 24-26 GHz is adopted to demonstrate a low-cost, compact, and high-energy-efficient solution based on the direct intensity modulation and direct detection scheme. For our proof-of-concept demonstration, we use 64 quadrature amplitude modulation with a 100 MHz bandwidth. We assess the link performance by exposing the RoFSO section to atmospheric turbulence conditions. Further, we show that the measured minimum error vector magnitude (EVM) is 4.7% and also verify that the proposed system with the free-space-optics link span of 100 m under strong turbulence can deliver an acceptable EVM of <9% with signal-to-noise ratio levels of 22 dB and 10 dB with and without turbulence, respectively.

Direct EUV/X-Ray Modulation of the Ionosphere During the August 2017 Total Solar Eclipse

NASA Astrophysics Data System (ADS)

Mrak, Sebastijan; Semeter, Joshua; Drob, Douglas; Huba, J. D.

2018-05-01

The great American total solar eclipse of 21 August 2017 offered a fortuitous opportunity to study the response of the atmosphere and ionosphere using a myriad of ground instruments. We have used the network of U.S. Global Positioning System receivers to examine perturbations in maps of ionospheric total electron content (TEC). Coherent large-scale variations in TEC have been interpreted by others as gravity wave-induced traveling ionospheric disturbances. However, the solar disk had two active regions at that time, one near the center of the disk and one at the edge, which resulted in an irregular illumination pattern in the extreme ultraviolet (EUV)/X-ray bands. Using detailed EUV occultation maps calculated from the National Aeronautics and Space Administration Solar Dynamics Observatory Atmospheric Imaging Assembly images, we show excellent agreement between TEC perturbations and computed gradients in EUV illumination. The results strongly suggest that prominent large-scale TEC disturbances were consequences of direct EUV modulation, rather than gravity wave-induced traveling ionospheric disturbances.

Integrative Analysis of Many Weighted Co-Expression Networks Using Tensor Computation

PubMed Central

Li, Wenyuan; Liu, Chun-Chi; Zhang, Tong; Li, Haifeng; Waterman, Michael S.; Zhou, Xianghong Jasmine

2011-01-01

The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks. PMID:21698123

Handheld portable real-time tracking and communications device

DOEpatents

Wiseman, James M [Albuquerque, NM; Riblett, Jr., Loren E.; Green, Karl L [Albuquerque, NM; Hunter, John A [Albuquerque, NM; Cook, III, Robert N.; Stevens, James R [Arlington, VA

2012-05-22

Portable handheld real-time tracking and communications devices include; a controller module, communications module including global positioning and mesh network radio module, data transfer and storage module, and a user interface module enclosed in a water-resistant enclosure. Real-time tracking and communications devices can be used by protective force, security and first responder personnel to provide situational awareness allowing for enhance coordination and effectiveness in rapid response situations. Such devices communicate to other authorized devices via mobile ad-hoc wireless networks, and do not require fixed infrastructure for their operation.

A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.

PubMed

Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

2016-01-01

Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.

A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder

PubMed Central

Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

2016-01-01

Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive. PMID:28018162

Oscillatory motor network activity during rest and movement: an fNIRS study

PubMed Central

Bajaj, Sahil; Drake, Daniel; Butler, Andrew J.; Dhamala, Mukesh

2014-01-01

Coherent network oscillations (<0.1 Hz) linking distributed brain regions are commonly observed in the brain during both rest and task conditions. What oscillatory network exists and how network oscillations change in connectivity strength, frequency and direction when going from rest to explicit task are topics of recent inquiry. Here, we study network oscillations within the sensorimotor regions of able-bodied individuals using hemodynamic activity as measured by functional near-infrared spectroscopy (fNIRS). Using spectral interdependency methods, we examined how the supplementary motor area (SMA), the left premotor cortex (LPMC) and the left primary motor cortex (LM1) are bound as a network during extended resting state (RS) and between-tasks resting state (btRS), and how the activity of the network changes as participants execute left, right, and bilateral hand (LH, RH, and BH) finger movements. We found: (i) power, coherence and Granger causality (GC) spectra had significant peaks within the frequency band (0.01–0.04 Hz) during RS whereas the peaks shifted to a bit higher frequency range (0.04–0.08 Hz) during btRS and finger movement tasks, (ii) there was significant bidirectional connectivity between all the nodes during RS and unidirectional connectivity from the LM1 to SMA and LM1 to LPMC during btRS, and (iii) the connections from SMA to LM1 and from LPMC to LM1 were significantly modulated in LH, RH, and BH finger movements relative to btRS. The unidirectional connectivity from SMA to LM1 just before the actual task changed to the bidirectional connectivity during LH and BH finger movement. The uni-directionality could be associated with movement suppression and the bi-directionality with preparation, sensorimotor update and controlled execution. These results underscore that fNIRS is an effective tool for monitoring spectral signatures of brain activity, which may serve as an important precursor before monitoring the recovery progress following brain injury. PMID:24550793

Analysis of the dynamic co-expression network of heart regeneration in the zebrafish

PubMed Central

Rodius, Sophie; Androsova, Ganna; Götz, Lou; Liechti, Robin; Crespo, Isaac; Merz, Susanne; Nazarov, Petr V.; de Klein, Niek; Jeanty, Céline; González-Rosa, Juan M.; Muller, Arnaud; Bernardin, Francois; Niclou, Simone P.; Vallar, Laurent; Mercader, Nadia; Ibberson, Mark; Xenarios, Ioannis; Azuaje, Francisco

2016-01-01

The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration. PMID:27241320

Analysis of the dynamic co-expression network of heart regeneration in the zebrafish

NASA Astrophysics Data System (ADS)

Rodius, Sophie; Androsova, Ganna; Götz, Lou; Liechti, Robin; Crespo, Isaac; Merz, Susanne; Nazarov, Petr V.; de Klein, Niek; Jeanty, Céline; González-Rosa, Juan M.; Muller, Arnaud; Bernardin, Francois; Niclou, Simone P.; Vallar, Laurent; Mercader, Nadia; Ibberson, Mark; Xenarios, Ioannis; Azuaje, Francisco

2016-05-01

The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration.

A Network-Based Classification Model for Deriving Novel Drug-Disease Associations and Assessing Their Molecular Actions

PubMed Central

Oh, Min; Ahn, Jaegyoon; Yoon, Youngmi

2014-01-01

The growing number and variety of genetic network datasets increases the feasibility of understanding how drugs and diseases are associated at the molecular level. Properly selected features of the network representations of existing drug-disease associations can be used to infer novel indications of existing drugs. To find new drug-disease associations, we generated an integrative genetic network using combinations of interactions, including protein-protein interactions and gene regulatory network datasets. Within this network, network adjacencies of drug-drug and disease-disease were quantified using a scored path between target sets of them. Furthermore, the common topological module of drugs or diseases was extracted, and thereby the distance between topological drug-module and disease (or disease-module and drug) was quantified. These quantified scores were used as features for the prediction of novel drug-disease associations. Our classifiers using Random Forest, Multilayer Perceptron and C4.5 showed a high specificity and sensitivity (AUC score of 0.855, 0.828 and 0.797 respectively) in predicting novel drug indications, and displayed a better performance than other methods with limited drug and disease properties. Our predictions and current clinical trials overlap significantly across the different phases of drug development. We also identified and visualized the topological modules of predicted drug indications for certain types of cancers, and for Alzheimer’s disease. Within the network, those modules show potential pathways that illustrate the mechanisms of new drug indications, including propranolol as a potential anticancer agent and telmisartan as treatment for Alzheimer’s disease. PMID:25356910

Direct evidence that an extended hydrogen-bonding network influences activation of pyridoxal 5'-phosphate in aspartate aminotransferase

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

Dajnowicz, Steven; Parks, Jerry M.; Hu, Xiche

We used pyridoxal 5'-phosphate (PLP) is a fundamental, multifunctional enzyme cofactor to catalyze a wide variety of chemical reactions involved in amino acid metabolism. PLP-dependent enzymes optimize specific chemical reactions by modulating the electronic states of PLP through distinct active site environments. In aspartate aminotransferase (AAT), an extended hydrogen bond network is coupled to the pyridinyl nitrogen of the PLP, influencing the electrophilicity of the cofactor. This network, which involves residues Asp-222, His-143, Thr-139, His-189, and structural waters, is located at the edge of PLP opposite the reactive Schiff base. We demonstrate that this hydrogen bond network directly influences themore » protonation state of the pyridine nitrogen of PLP, which affects the rates of catalysis. We analyzed perturbations caused by single- and double-mutant variants using steady-state kinetics, high resolution X-ray crystallography, and quantum chemical calculations. Protonation of the pyridinyl nitrogen to form a pyridinium cation induces electronic delocalization in the PLP, which correlates with the enhancement in catalytic rate in AAT. Therefore, PLP activation is controlled by the proximity of the pyridinyl nitrogen to the hydrogen bond microenvironment. Quantum chemical calculations indicate that Asp-222, which is directly coupled to the pyridinyl nitrogen, increases the pKa of the pyridine nitrogen and stabilizes the pyridinium cation. His-143 and His-189 also increase the pKa of the pyridine nitrogen but, more significantly, influence the position of the proton that resides between Asp-222 and the pyridinyl nitrogen. Our findings indicate that the second shell residues directly enhance the rate of catalysis in AAT.« less

Direct evidence that an extended hydrogen-bonding network influences activation of pyridoxal 5'-phosphate in aspartate aminotransferase

DOE PAGES

Dajnowicz, Steven; Parks, Jerry M.; Hu, Xiche; ...

2017-02-23

We used pyridoxal 5'-phosphate (PLP) is a fundamental, multifunctional enzyme cofactor to catalyze a wide variety of chemical reactions involved in amino acid metabolism. PLP-dependent enzymes optimize specific chemical reactions by modulating the electronic states of PLP through distinct active site environments. In aspartate aminotransferase (AAT), an extended hydrogen bond network is coupled to the pyridinyl nitrogen of the PLP, influencing the electrophilicity of the cofactor. This network, which involves residues Asp-222, His-143, Thr-139, His-189, and structural waters, is located at the edge of PLP opposite the reactive Schiff base. We demonstrate that this hydrogen bond network directly influences themore » protonation state of the pyridine nitrogen of PLP, which affects the rates of catalysis. We analyzed perturbations caused by single- and double-mutant variants using steady-state kinetics, high resolution X-ray crystallography, and quantum chemical calculations. Protonation of the pyridinyl nitrogen to form a pyridinium cation induces electronic delocalization in the PLP, which correlates with the enhancement in catalytic rate in AAT. Therefore, PLP activation is controlled by the proximity of the pyridinyl nitrogen to the hydrogen bond microenvironment. Quantum chemical calculations indicate that Asp-222, which is directly coupled to the pyridinyl nitrogen, increases the pKa of the pyridine nitrogen and stabilizes the pyridinium cation. His-143 and His-189 also increase the pKa of the pyridine nitrogen but, more significantly, influence the position of the proton that resides between Asp-222 and the pyridinyl nitrogen. Our findings indicate that the second shell residues directly enhance the rate of catalysis in AAT.« less

Molecular Correlates of Cortical Network Modulation by Long-Term Sensory Experience in the Adult Rat Barrel Cortex

ERIC Educational Resources Information Center

Vallès, Astrid; Granic, Ivica; De Weerd, Peter; Martens, Gerard J. M.

2014-01-01

Modulation of cortical network connectivity is crucial for an adaptive response to experience. In the rat barrel cortex, long-term sensory stimulation induces cortical network modifications and neuronal response changes of which the molecular basis is unknown. Here, we show that long-term somatosensory stimulation by enriched environment…

Implementation of quantum key distribution network simulation module in the network simulator NS-3

NASA Astrophysics Data System (ADS)

Mehic, Miralem; Maurhart, Oliver; Rass, Stefan; Voznak, Miroslav

2017-10-01

As the research in quantum key distribution (QKD) technology grows larger and becomes more complex, the need for highly accurate and scalable simulation technologies becomes important to assess the practical feasibility and foresee difficulties in the practical implementation of theoretical achievements. Due to the specificity of the QKD link which requires optical and Internet connection between the network nodes, to deploy a complete testbed containing multiple network hosts and links to validate and verify a certain network algorithm or protocol would be very costly. Network simulators in these circumstances save vast amounts of money and time in accomplishing such a task. The simulation environment offers the creation of complex network topologies, a high degree of control and repeatable experiments, which in turn allows researchers to conduct experiments and confirm their results. In this paper, we described the design of the QKD network simulation module which was developed in the network simulator of version 3 (NS-3). The module supports simulation of the QKD network in an overlay mode or in a single TCP/IP mode. Therefore, it can be used to simulate other network technologies regardless of QKD.

Differential network as an indicator of osteoporosis with network entropy.

PubMed

Ma, Lili; Du, Hongmei; Chen, Guangdong

2018-07-01

Osteoporosis is a common skeletal disorder characterized by a decrease in bone mass and density. The peak bone mass (PBM) is a significant determinant of osteoporosis. To gain insights into the indicating effect of PBM to osteoporosis, this study focused on characterizing the PBM networks and identifying key genes. One biological data set with 12 monocyte low PBM samples and 11 high PBM samples was derived to construct protein-protein interaction networks (PPINs). Based on clique-merging, module-identification algorithm was used to identify modules from PPINs. The systematic calculation and comparison were performed to test whether the network entropy can discriminate the low PBM network from high PBM network. We constructed 32 destination networks with 66 modules divided from monocyte low and high PBM networks. Among them, network 11 was the only significantly differential one (P<0.05) with 8 nodes and 28 edges. All genes belonged to precursors of osteoclasts, which were related to calcium transport as well as blood monocytes. In conclusion, based on the entropy in PBM PPINs, the differential network appears to be a novel therapeutic indicator for osteoporosis during the bone monocyte progression; these findings are helpful in disclosing the pathogenetic mechanisms of osteoporosis.

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens

PubMed Central

Chasman, Deborah; Walters, Kevin B.; Lopes, Tiago J. S.; Eisfeld, Amie J.; Kawaoka, Yoshihiro; Roy, Sushmita

2016-01-01

Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection. PMID:27403523

Research on virtual network load balancing based on OpenFlow

NASA Astrophysics Data System (ADS)

Peng, Rong; Ding, Lei

2017-08-01

The Network based on OpenFlow technology separate the control module and data forwarding module. Global deployment of load balancing strategy through network view of control plane is fast and of high efficiency. This paper proposes a Weighted Round-Robin Scheduling algorithm for virtual network and a load balancing plan for server load based on OpenFlow. Load of service nodes and load balancing tasks distribution algorithm will be taken into account.

Beyond Fine Tuning: Adding capacity to leverage few labels

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

Hodas, Nathan O.; Shaffer, Kyle J.; Yankov, Artem

2017-12-09

In this paper we present a technique to train neural network models on small amounts of data. Current methods for training neural networks on small amounts of rich data typically rely on strategies such as fine-tuning a pre-trained neural networks or the use of domain-specific hand-engineered features. Here we take the approach of treating network layers, or entire networks, as modules and combine pre-trained modules with untrained modules, to learn the shift in distributions between data sets. The central impact of using a modular approach comes from adding new representations to a network, as opposed to replacing representations via fine-tuning.more » Using this technique, we are able surpass results using standard fine-tuning transfer learning approaches, and we are also able to significantly increase performance over such approaches when using smaller amounts of data.« less

Submillisecond-response polymer network liquid crystal phase modulators at 1.06-μm wavelength

NASA Astrophysics Data System (ADS)

Sun, Jie; Xianyu, Haiqing; Chen, Yuan; Wu, Shin-Tson

2011-07-01

A fast-response and scattering-free polymer network liquid crystal (PNLC) light modulator is demonstrated at λ = 1.06 μm wavelength. A decay time of 117 μs for 2π phase modulation is obtained at 70 °C, which is ˜ 650 × faster than that of the host nematic LCs. The major tradeoff is the increased operating voltage. Potential applications include spatial light modulators and adaptive optics.

Rhythms of Consciousness: Binocular Rivalry Reveals Large-Scale Oscillatory Network Dynamics Mediating Visual Perception

PubMed Central

Doesburg, Sam M.; Green, Jessica J.; McDonald, John J.; Ward, Lawrence M.

2009-01-01

Consciousness has been proposed to emerge from functionally integrated large-scale ensembles of gamma-synchronous neural populations that form and dissolve at a frequency in the theta band. We propose that discrete moments of perceptual experience are implemented by transient gamma-band synchronization of relevant cortical regions, and that disintegration and reintegration of these assemblies is time-locked to ongoing theta oscillations. In support of this hypothesis we provide evidence that (1) perceptual switching during binocular rivalry is time-locked to gamma-band synchronizations which recur at a theta rate, indicating that the onset of new conscious percepts coincides with the emergence of a new gamma-synchronous assembly that is locked to an ongoing theta rhythm; (2) localization of the generators of these gamma rhythms reveals recurrent prefrontal and parietal sources; (3) theta modulation of gamma-band synchronization is observed between and within the activated brain regions. These results suggest that ongoing theta-modulated-gamma mechanisms periodically reintegrate a large-scale prefrontal-parietal network critical for perceptual experience. Moreover, activation and network inclusion of inferior temporal cortex and motor cortex uniquely occurs on the cycle immediately preceding responses signaling perceptual switching. This suggests that the essential prefrontal-parietal oscillatory network is expanded to include additional cortical regions relevant to tasks and perceptions furnishing consciousness at that moment, in this case image processing and response initiation, and that these activations occur within a time frame consistent with the notion that conscious processes directly affect behaviour. PMID:19582165

Network analysis reveals that bacteria and fungi form modules that correlate independently with soil parameters.

PubMed

de Menezes, Alexandre B; Prendergast-Miller, Miranda T; Richardson, Alan E; Toscas, Peter; Farrell, Mark; Macdonald, Lynne M; Baker, Geoff; Wark, Tim; Thrall, Peter H

2015-08-01

Network and multivariate statistical analyses were performed to determine interactions between bacterial and fungal community terminal restriction length polymorphisms as well as soil properties in paired woodland and pasture sites. Canonical correspondence analysis (CCA) revealed that shifts in woodland community composition correlated with soil dissolved organic carbon, while changes in pasture community composition correlated with moisture, nitrogen and phosphorus. Weighted correlation network analysis detected two distinct microbial modules per land use. Bacterial and fungal ribotypes did not group separately, rather all modules comprised of both bacterial and fungal ribotypes. Woodland modules had a similar fungal : bacterial ribotype ratio, while in the pasture, one module was fungal dominated. There was no correspondence between pasture and woodland modules in their ribotype composition. The modules had different relationships to soil variables, and these contrasts were not detected without the use of network analysis. This study demonstrated that fungi and bacteria, components of the soil microbial communities usually treated as separate functional groups as in a CCA approach, were co-correlated and formed distinct associations in these adjacent habitats. Understanding these distinct modular associations may shed more light on their niche space in the soil environment, and allow a more realistic description of soil microbial ecology and function. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

CommWalker: correctly evaluating modules in molecular networks in light of annotation bias.

PubMed

Luecken, M D; Page, M J T; Crosby, A J; Mason, S; Reinert, G; Deane, C M

2018-03-15

Detecting novel functional modules in molecular networks is an important step in biological research. In the absence of gold standard functional modules, functional annotations are often used to verify whether detected modules/communities have biological meaning. However, as we show, the uneven distribution of functional annotations means that such evaluation methods favor communities of well-studied proteins. We propose a novel framework for the evaluation of communities as functional modules. Our proposed framework, CommWalker, takes communities as inputs and evaluates them in their local network environment by performing short random walks. We test CommWalker's ability to overcome annotation bias using input communities from four community detection methods on two protein interaction networks. We find that modules accepted by CommWalker are similarly co-expressed as those accepted by current methods. Crucially, CommWalker performs well not only in well-annotated regions, but also in regions otherwise obscured by poor annotation. CommWalker community prioritization both faithfully captures well-validated communities and identifies functional modules that may correspond to more novel biology. The CommWalker algorithm is freely available at opig.stats.ox.ac.uk/resources or as a docker image on the Docker Hub at hub.docker.com/r/lueckenmd/commwalker/. deane@stats.ox.ac.uk. Supplementary data are available at Bioinformatics online.

Differential network analysis reveals the genome-wide landscape of estrogen receptor modulation in hormonal cancers

PubMed Central

Hsiao, Tzu-Hung; Chiu, Yu-Chiao; Hsu, Pei-Yin; Lu, Tzu-Pin; Lai, Liang-Chuan; Tsai, Mong-Hsun; Huang, Tim H.-M.; Chuang, Eric Y.; Chen, Yidong

2016-01-01

Several mutual information (MI)-based algorithms have been developed to identify dynamic gene-gene and function-function interactions governed by key modulators (genes, proteins, etc.). Due to intensive computation, however, these methods rely heavily on prior knowledge and are limited in genome-wide analysis. We present the modulated gene/gene set interaction (MAGIC) analysis to systematically identify genome-wide modulation of interaction networks. Based on a novel statistical test employing conjugate Fisher transformations of correlation coefficients, MAGIC features fast computation and adaption to variations of clinical cohorts. In simulated datasets MAGIC achieved greatly improved computation efficiency and overall superior performance than the MI-based method. We applied MAGIC to construct the estrogen receptor (ER) modulated gene and gene set (representing biological function) interaction networks in breast cancer. Several novel interaction hubs and functional interactions were discovered. ER+ dependent interaction between TGFβ and NFκB was further shown to be associated with patient survival. The findings were verified in independent datasets. Using MAGIC, we also assessed the essential roles of ER modulation in another hormonal cancer, ovarian cancer. Overall, MAGIC is a systematic framework for comprehensively identifying and constructing the modulated interaction networks in a whole-genome landscape. MATLAB implementation of MAGIC is available for academic uses at https://github.com/chiuyc/MAGIC. PMID:26972162

Seismogeodesy for rapid earthquake and tsunami characterization

NASA Astrophysics Data System (ADS)

Bock, Y.

2016-12-01

Rapid estimation of earthquake magnitude and fault mechanism is critical for earthquake and tsunami warning systems. Traditionally, the monitoring of earthquakes and tsunamis has been based on seismic networks for estimating earthquake magnitude and slip, and tide gauges and deep-ocean buoys for direct measurement of tsunami waves. These methods are well developed for ocean basin-wide warnings but are not timely enough to protect vulnerable populations and infrastructure from the effects of local tsunamis, where waves may arrive within 15-30 minutes of earthquake onset time. Direct measurements of displacements by GPS networks at subduction zones allow for rapid magnitude and slip estimation in the near-source region, that are not affected by instrumental limitations and magnitude saturation experienced by local seismic networks. However, GPS displacements by themselves are too noisy for strict earthquake early warning (P-wave detection). Optimally combining high-rate GPS and seismic data (in particular, accelerometers that do not clip), referred to as seismogeodesy, provides a broadband instrument that does not clip in the near field, is impervious to magnitude saturation, and provides accurate real-time static and dynamic displacements and velocities in real time. Here we describe a NASA-funded effort to integrate GPS and seismogeodetic observations as part of NOAA's Tsunami Warning Centers in Alaska and Hawaii. It consists of a series of plug-in modules that allow for a hierarchy of rapid seismogeodetic products, including automatic P-wave picking, hypocenter estimation, S-wave prediction, magnitude scaling relationships based on P-wave amplitude (Pd) and peak ground displacement (PGD), finite-source CMT solutions and fault slip models as input for tsunami warnings and models. For the NOAA/NASA project, the modules are being integrated into an existing USGS Earthworm environment, currently limited to traditional seismic data. We are focused on a network of dozens of seismogeodetic stations available through the Pacific Northwest Seismic Network (University of Washington), the Plate Boundary Observatory (UNAVCO) and the Pacific Northwest Geodetic Array (Central Washington University) as the basis for local tsunami warnings for a large subduction zone earthquake in Cascadia.

Critical components of the pluripotency network are targets for the p300/CBP interacting protein (p/CIP) in embryonic stem cells.

PubMed

Chitilian, J M; Thillainadesan, G; Manias, J L; Chang, W Y; Walker, E; Isovic, M; Stanford, W L; Torchia, J

2014-01-01

p/CIP, also known as steroid receptor coactivator 3 (SRC-3)/Nuclear Receptor Coactivator 3 (NCoA3), is a transcriptional coactivator that binds liganded nuclear hormone receptors, as well as other transcription factors, and facilitates transcription through direct recruitment of accessory factors. We have found that p/CIP is highly expressed in undifferentiated mouse embryonic stem cells (mESCs) and is downregulated during differentiation. siRNA-mediated knockdown of p/CIP decreased transcript levels of Nanog, but not Oct4 or Sox2. Microarray expression analysis showed that Klf4, Tbx3, and Dax-1 are significantly downregulated in mESCs when p/CIP is knocked down. Subsequent chromatin immunoprecipitation (ChIP) analysis demonstrated that Tbx3, Klf4, and Dax-1 are direct transcriptional targets of p/CIP. Using the piggyBac transposition system, a mouse ESC line that expresses Flag-p/CIP in a doxycycline-dependent manner was generated. p/CIP overexpression increased the level of target genes and promoted the formation of undifferentiated colonies. Collectively, these results indicate that p/CIP contributes to the maintenance of ESC pluripotency through direct regulation of essential pluripotency genes. To better understand the mechanism by which p/CIP functions in ESC pluripotency, we integrated our ChIP and transcriptome data with published protein-protein interaction and promoter occupancy data to draft a p/CIP gene regulatory network. The p/CIP gene regulatory network identifies various feed-forward modules including one in which p/CIP activates members of the extended pluripotency network, demonstrating that p/CIP is a component of this extended network. © AlphaMed Press.

Probabilistic resource allocation system with self-adaptive capability

NASA Technical Reports Server (NTRS)

Yufik, Yan M. (Inventor)

1996-01-01

A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and directed links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Reliability values are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

Time-evolving genetic networks reveal a NAC troika that negatively regulates leaf senescence in Arabidopsis.

PubMed

Kim, Hyo Jung; Park, Ji-Hwan; Kim, Jingil; Kim, Jung Ju; Hong, Sunghyun; Kim, Jeongsik; Kim, Jin Hee; Woo, Hye Ryun; Hyeon, Changbong; Lim, Pyung Ok; Nam, Hong Gil; Hwang, Daehee

2018-05-22

Senescence is controlled by time-evolving networks that describe the temporal transition of interactions among senescence regulators. Here, we present time-evolving networks for NAM/ATAF/CUC (NAC) transcription factors in Arabidopsis during leaf aging. The most evident characteristic of these time-dependent networks was a shift from positive to negative regulation among NACs at a presenescent stage. ANAC017, ANAC082, and ANAC090, referred to as a "NAC troika," govern the positive-to-negative regulatory shift. Knockout of the NAC troika accelerated senescence and the induction of other NAC s, whereas overexpression of the NAC troika had the opposite effects. Transcriptome and molecular analyses revealed shared suppression of senescence-promoting processes by the NAC troika, including salicylic acid (SA) and reactive oxygen species (ROS) responses, but with predominant regulation of SA and ROS responses by ANAC090 and ANAC017, respectively. Our time-evolving networks provide a unique regulatory module of presenescent repressors that direct the timely induction of senescence-promoting processes at the presenescent stage of leaf aging. Copyright © 2018 the Author(s). Published by PNAS.

Time-evolving genetic networks reveal a NAC troika that negatively regulates leaf senescence in Arabidopsis

PubMed Central

Kim, Hyo Jung; Park, Ji-Hwan; Kim, Jingil; Kim, Jung Ju; Hong, Sunghyun; Kim, Jin Hee; Woo, Hye Ryun; Lim, Pyung Ok; Nam, Hong Gil; Hwang, Daehee

2018-01-01

Senescence is controlled by time-evolving networks that describe the temporal transition of interactions among senescence regulators. Here, we present time-evolving networks for NAM/ATAF/CUC (NAC) transcription factors in Arabidopsis during leaf aging. The most evident characteristic of these time-dependent networks was a shift from positive to negative regulation among NACs at a presenescent stage. ANAC017, ANAC082, and ANAC090, referred to as a “NAC troika,” govern the positive-to-negative regulatory shift. Knockout of the NAC troika accelerated senescence and the induction of other NACs, whereas overexpression of the NAC troika had the opposite effects. Transcriptome and molecular analyses revealed shared suppression of senescence-promoting processes by the NAC troika, including salicylic acid (SA) and reactive oxygen species (ROS) responses, but with predominant regulation of SA and ROS responses by ANAC090 and ANAC017, respectively. Our time-evolving networks provide a unique regulatory module of presenescent repressors that direct the timely induction of senescence-promoting processes at the presenescent stage of leaf aging. PMID:29735710

A simple model for constant storage modulus of poly (lactic acid)/poly (ethylene oxide)/carbon nanotubes nanocomposites at low frequencies assuming the properties of interphase regions and networks.

PubMed

Zare, Yasser; Rhim, Sungsoo; Garmabi, Hamid; Rhee, Kyong Yop

2018-04-01

The networks of nanoparticles in nanocomposites cause solid-like behavior demonstrating a constant storage modulus at low frequencies. This study examines the storage modulus of poly (lactic acid)/poly (ethylene oxide)/carbon nanotubes (CNT) nanocomposites. The experimental data of the storage modulus in the plateau regions are obtained by a frequency sweep test. In addition, a simple model is developed to predict the constant storage modulus assuming the properties of the interphase regions and the CNT networks. The model calculations are compared with the experimental results, and the parametric analyses are applied to validate the predictability of the developed model. The calculations properly agree with the experimental data at all polymer and CNT concentrations. Moreover, all parameters acceptably modulate the constant storage modulus. The percentage of the networked CNT, the modulus of networks, and the thickness and modulus of the interphase regions directly govern the storage modulus of nanocomposites. The outputs reveal the important roles of the interphase properties in the storage modulus. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prior knowledge based mining functional modules from Yeast PPI networks with gene ontology

PubMed Central

2010-01-01

Background In the literature, there are fruitful algorithmic approaches for identification functional modules in protein-protein interactions (PPI) networks. Because of accumulation of large-scale interaction data on multiple organisms and non-recording interaction data in the existing PPI database, it is still emergent to design novel computational techniques that can be able to correctly and scalably analyze interaction data sets. Indeed there are a number of large scale biological data sets providing indirect evidence for protein-protein interaction relationships. Results The main aim of this paper is to present a prior knowledge based mining strategy to identify functional modules from PPI networks with the aid of Gene Ontology. Higher similarity value in Gene Ontology means that two gene products are more functionally related to each other, so it is better to group such gene products into one functional module. We study (i) to encode the functional pairs into the existing PPI networks; and (ii) to use these functional pairs as pairwise constraints to supervise the existing functional module identification algorithms. Topology-based modularity metric and complex annotation in MIPs will be used to evaluate the identified functional modules by these two approaches. Conclusions The experimental results on Yeast PPI networks and GO have shown that the prior knowledge based learning methods perform better than the existing algorithms. PMID:21172053

300 Gb/s IM/DD based SDM-WDM-PON with laserless ONUs.

PubMed

Bao, Fangdi; Morioka, Toshio; Oxenløwe, Leif K; Hu, Hao

2018-04-02

A low-cost, high-speed SDM-WDM-PON architecture is proposed by using a multi-core fiber (MCF) and intensity modulation/directly detection (IM/DD). One of the MCF cores is used for sending laser sources from optical line terminal (OLT) to optical network unit (ONU), thus facilitating laserless and colorless ONUs, and providing ease of network management and maintenance. In addition, the wavelengths of the ONUs are controlled on the OLT side, which also enables flexible optical networks. Thanks to the low inter-core crosstalk of a MCF, downstream (DS) and upstream (US) signals are transmitted independently in different cores of the MCF, not only increasing the aggregated capacity but also avoiding the Rayleigh backscattering noise. Finally, a proof-of-principle experiment is performed by using a 7-core fiber, achieving 300 /120 Gb/s aggregated capacity for DS and US (3 × cores, 4 × wavelengths, 25/10 Gb/s per wavelength), respectively.

Multi-service small-cell cloud wired/wireless access network based on tunable optical frequency comb

NASA Astrophysics Data System (ADS)

Xiang, Yu; Zhou, Kun; Yang, Liu; Pan, Lei; Liao, Zhen-wan; Zhang, Qiang

2015-11-01

In this paper, we demonstrate a novel multi-service wired/wireless integrated access architecture of cloud radio access network (C-RAN) based on radio-over-fiber passive optical network (RoF-PON) system, which utilizes scalable multiple- frequency millimeter-wave (MF-MMW) generation based on tunable optical frequency comb (TOFC). In the baseband unit (BBU) pool, the generated optical comb lines are modulated into wired, RoF and WiFi/WiMAX signals, respectively. The multi-frequency RoF signals are generated by beating the optical comb line pairs in the small cell. The WiFi/WiMAX signals are demodulated after passing through the band pass filter (BPF) and band stop filter (BSF), respectively, whereas the wired signal can be received directly. The feasibility and scalability of the proposed multi-service wired/wireless integrated C-RAN are confirmed by the simulations.

Tunable single-photon multi-channel quantum router based on an optomechanical system

NASA Astrophysics Data System (ADS)

Ma, Peng-Cheng; Yan, Lei-Lei; Zhang, Jian; Chen, Gui-Bin; Li, Xiao-Wei; Zhan, You-Bang

2018-01-01

Routing of photons plays a key role in optical communication networks and quantum networks. Although the quantum routing of signals has been investigated for various systems, both in theory and experiment, the general form of a quantum router with multi-output terminals still needs to be explored. Here, we propose an experimentally accessible tunable single-photon multi-channel routing scheme using an optomechanics cavity which is Coulomb coupled to a nanomechanical resonator. The router can extract single photons from the coherent input signal and directly modulate them into three different output channels. More importantly, the two output signal frequencies can be selected by adjusting the Coulomb coupling strength. For application purposes, we justify that there is insignificant influence from the vacuum and thermal noises on the performance of the router under cryogenic conditions. Our proposal may pave a new avenue towards multi-channel routers and quantum networks.

5–HT and 5–HT-SO4, but not tryptophan or 5-HIAA levels in single feeding neurons track animal hunger state

PubMed Central

Hatcher, N. G.; Zhang, X.; Stuart, J. N.; Moroz, L. L.; Sweedler, J. V.; Gillette, R.

2014-01-01

Serotonin (5-HT) is an intrinsic modulator of neural network excitation states in gastropod molluscs. 5-HT and related indole metabolites were measured in single, well-characterized serotonergic neurons of the feeding motor network of the predatory sea-slug Pleurobranchaea californica. Indole amounts were compared between paired hungry and satiated animals. Levels of 5-HT and its metabolite 5-HT-SO4 in the metacerebral giant neurons were observed in amounts approximately four-fold and two-fold, respectively, below unfed partners 24 h after a satiating meal. Intracellular levels of 5-hydroxyindole acetic acid and of free tryptophan did not differ significantly with hunger state. These data demonstrate that neurotransmitter levels and their metabolites can vary in goal-directed neural networks in a manner that follows internal state. PMID:18036151

Tweaked residual convolutional network for face alignment

NASA Astrophysics Data System (ADS)

Du, Wenchao; Li, Ke; Zhao, Qijun; Zhang, Yi; Chen, Hu

2017-08-01

We propose a novel Tweaked Residual Convolutional Network approach for face alignment with two-level convolutional networks architecture. Specifically, the first-level Tweaked Convolutional Network (TCN) module predicts the landmark quickly but accurately enough as a preliminary, by taking low-resolution version of the detected face holistically as the input. The following Residual Convolutional Networks (RCN) module progressively refines the landmark by taking as input the local patch extracted around the predicted landmark, particularly, which allows the Convolutional Neural Network (CNN) to extract local shape-indexed features to fine tune landmark position. Extensive evaluations show that the proposed Tweaked Residual Convolutional Network approach outperforms existing methods.

Modularity, pollination systems, and interaction turnover in plant-pollinator networks across space.

PubMed

Carstensen, Daniel W; Sabatino, Malena; Morellato, Leonor Patricia C

2016-05-01

Mutualistic interaction networks have been shown to be structurally conserved over space and time while pairwise interactions show high variability. In such networks, modularity is the division of species into compartments, or modules, where species within modules share more interactions with each other than they do with species from other modules. Such a modular structure is common in mutualistic networks and several evolutionary and ecological mechanisms have been proposed as underlying drivers. One prominent explanation is the existence of pollination syndromes where flowers tend to attract certain pollinators as determined by a set of traits. We investigate the modularity of seven community level plant-pollinator networks sampled in rupestrian grasslands, or campos rupestres, in SE Brazil. Defining pollination systems as corresponding groups of flower syndromes and pollinator functional groups, we test the two hypotheses that (1) interacting species from the same pollination system are more often assigned to the same module than interacting species from different pollination systems and; that (2) interactions between species from the same pollination system are more consistent across space than interactions between species from different pollination systems. Specifically we ask (1) whether networks are consistently modular across space; (2) whether interactions among species of the same pollination system occur more often inside modules, compared to interactions among species of different pollination systems, and finally; (3) whether the spatial variation in interaction identity, i.e., spatial interaction rewiring, is affected by trait complementarity among species as indicated by pollination systems. We confirm that networks are consistently modular across space and that interactions within pollination systems principally occur inside modules. Despite a strong tendency, we did not find a significant effect of pollination systems on the spatial consistency of pairwise interactions. These results indicate that the spatial rewiring of interactions could be constrained by pollination systems, resulting in conserved network structures in spite of high variation in pairwise interactions. Our findings suggest a relevant role of pollination systems in structuring plant-pollinator networks and we argue that structural patterns at the sub-network level can help us to fully understand how and why interactions vary across space and time.

Fast Fragmentation of Networks Using Module-Based Attacks

PubMed Central

Requião da Cunha, Bruno; González-Avella, Juan Carlos; Gonçalves, Sebastián

2015-01-01

In the multidisciplinary field of Network Science, optimization of procedures for efficiently breaking complex networks is attracting much attention from a practical point of view. In this contribution, we present a module-based method to efficiently fragment complex networks. The procedure firstly identifies topological communities through which the network can be represented using a well established heuristic algorithm of community finding. Then only the nodes that participate of inter-community links are removed in descending order of their betweenness centrality. We illustrate the method by applying it to a variety of examples in the social, infrastructure, and biological fields. It is shown that the module-based approach always outperforms targeted attacks to vertices based on node degree or betweenness centrality rankings, with gains in efficiency strongly related to the modularity of the network. Remarkably, in the US power grid case, by deleting 3% of the nodes, the proposed method breaks the original network in fragments which are twenty times smaller in size than the fragments left by betweenness-based attack. PMID:26569610

Network architecture of the cerebral nuclei (basal ganglia) association and commissural connectome.

PubMed

Swanson, Larry W; Sporns, Olaf; Hahn, Joel D

2016-10-04

The cerebral nuclei form the ventral division of the cerebral hemisphere and are thought to play an important role in neural systems controlling somatic movement and motivation. Network analysis was used to define global architectural features of intrinsic cerebral nuclei circuitry in one hemisphere (association connections) and between hemispheres (commissural connections). The analysis was based on more than 4,000 reports of histologically defined axonal connections involving all 45 gray matter regions of the rat cerebral nuclei and revealed the existence of four asymmetrically interconnected modules. The modules form four topographically distinct longitudinal columns that only partly correspond to previous interpretations of cerebral nuclei structure-function organization. The network of connections within and between modules in one hemisphere or the other is quite dense (about 40% of all possible connections), whereas the network of connections between hemispheres is weak and sparse (only about 5% of all possible connections). Particularly highly interconnected regions (rich club and hubs within it) form a topologically continuous band extending through two of the modules. Connection path lengths among numerous pairs of regions, and among some of the network's modules, are relatively long, thus accounting for low global efficiency in network communication. These results provide a starting point for reexamining the connectional organization of the cerebral hemispheres as a whole (right and left cerebral cortex and cerebral nuclei together) and their relation to the rest of the nervous system.

Network based management for multiplexed electric vehicle charging

DOEpatents

Gadh, Rajit; Chung, Ching Yen; Qui, Li

2017-04-11

A system for multiplexing charging of electric vehicles, comprising a server coupled to a plurality of charging control modules over a network. Each of said charging modules being connected to a voltage source such that each charging control module is configured to regulate distribution of voltage from the voltage source to an electric vehicle coupled to the charging control module. Data collection and control software is provided on the server for identifying a plurality of electric vehicles coupled to the plurality of charging control modules and selectively distributing charging of the plurality of charging control modules to multiplex distribution of voltage to the plurality of electric vehicles.

Using a network modularity analysis to inform management of a rare endemic plant in the northern Great Plains, USA

USGS Publications Warehouse

Larson, Diane L.; Droege, Sam; Rabie, Paul A.; Larson, Jennifer L.; Devalez, Jelle; Haar, Milton; McDermott-Kubeczko, Margaret

2014-01-01

1. Analyses of flower-visitor interaction networks allow application of community-level information to conservation problems, but management recommendations that ensue from such analyses are not well characterized. Results of modularity analyses, which detect groups of species (modules) that interact more with each other than with species outside their module, may be particularly applicable to management concerns. 2. We conducted modularity analyses of networks surrounding a rare endemic annual plant, Eriogonum visheri, at Badlands National Park, USA, in 2010 and 2011. Plant species visited were determined by pollen on insect bodies and by flower species upon which insects were captured. Roles within modules (network hub, module hub, connector and peripheral, in decreasing order of network structural importance) were determined for each species. 3. Relationships demonstrated by the modularity analysis, in concert with knowledge of pollen species carried by insects, allowed us to infer effects of two invasive species on E. visheri. Sharing a module increased risk of interspecific pollen transfer to E. visheri. Control of invasive Salsola tragus, which shared a module with E. visheri, is therefore a prudent management objective, but lack of control of invasive Melilotus officinalis, which occupied a different module, is unlikely to negatively affect pollination of E. visheri. Eriogonum pauciflorum may occupy a key position in this network, supporting insects from the E. visheri module when E. visheri is less abundant. 4. Year-to-year variation in species' roles suggests management decisions must be based on observations over several years. Information on pollen deposition on stigmas would greatly strengthen inferences made from the modularity analysis. 5. Synthesis and applications: Assessing the consequences of pollination, whether at the community or individual level, is inherently time-consuming. A trade-off exists: rather than an estimate of fitness effects, the network approach provides a broad understanding of the relationships among insect visitors and other plant species that may affect the focal rare plant. Knowledge of such relationships allows managers to detect, target and prioritize control of only the important subset of invasive species present and identify other species that may augment a rare species' population stability, such as E. pauciflorum in our study.

Applying ADLs to Assess Emerging Industry Specifications for Dynamic Discovery of Ad Hoc Network Services

DTIC Science & Technology

2001-01-31

function of Jini, UPnP, SLP, Bluetooth , and HAVi • Projected specific UML models for Jini, UPnP, and SLP • Developed a Rapide Model of Jini...is used by all JINI entities in directed -- discovery mode. It is part of the SCM_Discovery -- Module. Sends Unicast messages to SCMs on list of... SCMS to be discovered until all SCMS are found. -- Receives updates from SCM DB of discovered SCMs and -- removes SCMs accordingly -- NOTE

Stability and structural properties of gene regulation networks with coregulation rules.

PubMed

Warrell, Jonathan; Mhlanga, Musa

2017-05-07

Coregulation of the expression of groups of genes has been extensively demonstrated empirically in bacterial and eukaryotic systems. Such coregulation can arise through the use of shared regulatory motifs, which allow the coordinated expression of modules (and module groups) of functionally related genes across the genome. Coregulation can also arise through the physical association of multi-gene complexes through chromosomal looping, which are then transcribed together. We present a general formalism for modeling coregulation rules in the framework of Random Boolean Networks (RBN), and develop specific models for transcription factor networks with modular structure (including module groups, and multi-input modules (MIM) with autoregulation) and multi-gene complexes (including hierarchical differentiation between multi-gene complex members). We develop a mean-field approach to analyse the dynamical stability of large networks incorporating coregulation, and show that autoregulated MIM and hierarchical gene-complex models can achieve greater stability than networks without coregulation whose rules have matching activation frequency. We provide further analysis of the stability of small networks of both kinds through simulations. We also characterize several general properties of the transients and attractors in the hierarchical coregulation model, and show using simulations that the steady-state distribution factorizes hierarchically as a Bayesian network in a Markov Jump Process analogue of the RBN model. Copyright © 2017. Published by Elsevier Ltd.

Network-Based Disease Module Discovery by a Novel Seed Connector Algorithm with Pathobiological Implications.

PubMed

Wang, Rui-Sheng; Loscalzo, Joseph

2018-05-20

Understanding the genetic basis of complex diseases is challenging. Prior work shows that disease-related proteins do not typically function in isolation. Rather, they often interact with each other to form a network module that underlies dysfunctional mechanistic pathways. Identifying such disease modules will provide insights into a systems-level understanding of molecular mechanisms of diseases. Owing to the incompleteness of our knowledge of disease proteins and limited information on the biological mediators of pathobiological processes, the key proteins (seed proteins) for many diseases appear scattered over the human protein-protein interactome and form a few small branches, rather than coherent network modules. In this paper, we develop a network-based algorithm, called the Seed Connector algorithm (SCA), to pinpoint disease modules by adding as few additional linking proteins (seed connectors) to the seed protein pool as possible. Such seed connectors are hidden disease module elements that are critical for interpreting the functional context of disease proteins. The SCA aims to connect seed disease proteins so that disease mechanisms and pathways can be decoded based on predicted coherent network modules. We validate the algorithm using a large corpus of 70 complex diseases and binding targets of over 200 drugs, and demonstrate the biological relevance of the seed connectors. Lastly, as a specific proof of concept, we apply the SCA to a set of seed proteins for coronary artery disease derived from a meta-analysis of large-scale genome-wide association studies and obtain a coronary artery disease module enriched with important disease-related signaling pathways and drug targets not previously recognized. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prior knowledge guided active modules identification: an integrated multi-objective approach.

PubMed

Chen, Weiqi; Liu, Jing; He, Shan

2017-03-14

Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or disease states. A prior information guided active module identification approach is proposed to detect modules that are both active and enriched by prior knowledge. We formulate the active module identification problem as a multi-objective optimisation problem, which consists two conflicting objective functions of maximising the coverage of known biological pathways and the activity of the active module simultaneously. Network is constructed from protein-protein interaction database. A beta-uniform-mixture model is used to estimate the distribution of p-values and generate scores for activity measurement from microarray data. A multi-objective evolutionary algorithm is used to search for Pareto optimal solutions. We also incorporate a novel constraints based on algebraic connectivity to ensure the connectedness of the identified active modules. Application of proposed algorithm on a small yeast molecular network shows that it can identify modules with high activities and with more cross-talk nodes between related functional groups. The Pareto solutions generated by the algorithm provides solutions with different trade-off between prior knowledge and novel information from data. The approach is then applied on microarray data from diclofenac-treated yeast cells to build network and identify modules to elucidate the molecular mechanisms of diclofenac toxicity and resistance. Gene ontology analysis is applied to the identified modules for biological interpretation. Integrating knowledge of functional groups into the identification of active module is an effective method and provides a flexible control of balance between pure data-driven method and prior information guidance.

Effects of contextual relevance on pragmatic inference during conversation: An fMRI study.

PubMed

Feng, Wangshu; Wu, Yue; Jan, Catherine; Yu, Hongbo; Jiang, Xiaoming; Zhou, Xiaolin

2017-08-01

Contextual relevance, which is vital for understanding conversational implicatures (CI), engages both the frontal-temporal language and theory-of-mind networks. Here we investigate how contextual relevance affects CI processing and regulates the connectivity between CI-processing-related brain regions. Participants listened to dialogues in which the level of contextual relevance to dialogue-final utterance (reply) was manipulated. This utterance was either direct, indirect but relevant, irrelevant with contextual hint, or irrelevant with no contextual hint. Results indicated that compared with direct replies, indirect replies showed increased activations in bilateral IFG, bilateral MTG, bilateral TPJ, dmPFC, and precuneus, and increased connectivity between rTPJ/dmPFC and both IFG and MTG. Moreover, irrelevant replies activated right MTG along an anterior-posterior gradient as a function of the level of irrelevance. Our study provides novel evidence concerning how the language and theory-of-mind networks interact for pragmatic inference and how the processing of CI is modulated by level of contextual relevance. Copyright © 2017 Elsevier Inc. All rights reserved.

Technology Developments Integrating a Space Network Communications Testbed

NASA Technical Reports Server (NTRS)

Kwong, Winston; Jennings, Esther; Clare, Loren; Leang, Dee

2006-01-01

As future manned and robotic space explorations missions involve more complex systems, it is essential to verify, validate, and optimize such systems through simulation and emulation in a low cost testbed environment. The goal of such a testbed is to perform detailed testing of advanced space and ground communications networks, technologies, and client applications that are essential for future space exploration missions. We describe the development of new technologies enhancing our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) that enable its integration in a distributed space communications testbed. MACHETE combines orbital modeling, link analysis, and protocol and service modeling to quantify system performance based on comprehensive considerations of different aspects of space missions. It can simulate entire networks and can interface with external (testbed) systems. The key technology developments enabling the integration of MACHETE into a distributed testbed are the Monitor and Control module and the QualNet IP Network Emulator module. Specifically, the Monitor and Control module establishes a standard interface mechanism to centralize the management of each testbed component. The QualNet IP Network Emulator module allows externally generated network traffic to be passed through MACHETE to experience simulated network behaviors such as propagation delay, data loss, orbital effects and other communications characteristics, including entire network behaviors. We report a successful integration of MACHETE with a space communication testbed modeling a lunar exploration scenario. This document is the viewgraph slides of the presentation.

Conserved Non-Coding Regulatory Signatures in Arabidopsis Co-Expressed Gene Modules

PubMed Central

Spangler, Jacob B.; Ficklin, Stephen P.; Luo, Feng; Freeling, Michael; Feltus, F. Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome. PMID:23024789

Conserved non-coding regulatory signatures in Arabidopsis co-expressed gene modules.

PubMed

Spangler, Jacob B; Ficklin, Stephen P; Luo, Feng; Freeling, Michael; Feltus, F Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome.

Differential reward responses during competition against in- and out-of-network others.

PubMed

Fareri, Dominic S; Delgado, Mauricio R

2014-04-01

Social interactions occur within a variety of different contexts--cooperative/competitive--and often involve members of our social network. Here, we investigated whether social network modulated the value placed on positive outcomes during a competitive context. Eighteen human participants played a simple card-guessing game with three different competitors: a close friend (in-network), a confederate (out-of-network) and a random number generator (non-social condition) while undergoing functional magnetic resonance imaging. Neuroimaging results at the time of outcome receipt demonstrated a significant main effect of competitor across multiple regions of medial prefrontal cortex, with Blood Oxygen Level Dependent (BOLD) responses strongest when competing against one's friend compared with all other conditions. Striatal BOLD responses demonstrated a more general sensitivity to positive compared with negative monetary outcomes, which an exploratory analysis revealed to be stronger when interacting with social, compared with non-social, competitors. Interestingly, a Granger causality analysis indicated directed influences sent from an medial prefrontal cortex (mPFC) region, which shows social network differentiation of outcomes, and the ventral striatum bilaterally. Our results suggest that when competing against others of varying degrees of social network, mPFC differentially values these outcomes, perhaps treating in-network outcomes as more informative, leaving the striatum to more general value computations.

Differential reward responses during competition against in- and out-of-network others

PubMed Central

Fareri, Dominic S.

2014-01-01

Social interactions occur within a variety of different contexts––cooperative/competitive––and often involve members of our social network. Here, we investigated whether social network modulated the value placed on positive outcomes during a competitive context. Eighteen human participants played a simple card-guessing game with three different competitors: a close friend (in-network), a confederate (out-of-network) and a random number generator (non-social condition) while undergoing functional magnetic resonance imaging. Neuroimaging results at the time of outcome receipt demonstrated a significant main effect of competitor across multiple regions of medial prefrontal cortex, with Blood Oxygen Level Dependent (BOLD) responses strongest when competing against one’s friend compared with all other conditions. Striatal BOLD responses demonstrated a more general sensitivity to positive compared with negative monetary outcomes, which an exploratory analysis revealed to be stronger when interacting with social, compared with non-social, competitors. Interestingly, a Granger causality analysis indicated directed influences sent from an medial prefrontal cortex (mPFC) region, which shows social network differentiation of outcomes, and the ventral striatum bilaterally. Our results suggest that when competing against others of varying degrees of social network, mPFC differentially values these outcomes, perhaps treating in-network outcomes as more informative, leaving the striatum to more general value computations. PMID:23314007

Neural net target-tracking system using structured laser patterns

NASA Astrophysics Data System (ADS)

Cho, Jae-Wan; Lee, Yong-Bum; Lee, Nam-Ho; Park, Soon-Yong; Lee, Jongmin; Choi, Gapchu; Baek, Sunghyun; Park, Dong-Sun

1996-06-01

In this paper, we describe a robot endeffector tracking system using sensory information from recently-announced structured pattern laser diodes, which can generate images with several different types of structured pattern. The neural network approach is employed to recognize the robot endeffector covering the situation of three types of motion: translation, scaling and rotation. Features for the neural network to detect the position of the endeffector are extracted from the preprocessed images. Artificial neural networks are used to store models and to match with unknown input features recognizing the position of the robot endeffector. Since a minimal number of samples are used for different directions of the robot endeffector in the system, an artificial neural network with the generalization capability can be utilized for unknown input features. A feedforward neural network with the generalization capability can be utilized for unknown input features. A feedforward neural network trained with the back propagation learning is used to detect the position of the robot endeffector. Another feedforward neural network module is used to estimate the motion from a sequence of images and to control movements of the robot endeffector. COmbining the tow neural networks for recognizing the robot endeffector and estimating the motion with the preprocessing stage, the whole system keeps tracking of the robot endeffector effectively.

System for adjusting frequency of electrical output pulses derived from an oscillator

DOEpatents

Bartholomew, David B.

2006-11-14

A system for setting and adjusting a frequency of electrical output pulses derived from an oscillator in a network is disclosed. The system comprises an accumulator module configured to receive pulses from an oscillator and to output an accumulated value. An adjustor module is configured to store an adjustor value used to correct local oscillator drift. A digital adder adds values from the accumulator module to values stored in the adjustor module and outputs their sums to the accumulator module, where they are stored. The digital adder also outputs an electrical pulse to a logic module. The logic module is in electrical communication with the adjustor module and the network. The logic module may change the value stored in the adjustor module to compensate for local oscillator drift or change the frequency of output pulses. The logic module may also keep time and calculate drift.

Convergence of flexor reflex and corticospinal inputs on tibialis anterior network in humans.

PubMed

Mackey, Ann S; Uttaro, Denise; McDonough, Maureen P; Krivis, Lisa I; Knikou, Maria

2016-01-01

Integration between descending and ascending inputs at supraspinal and spinal levels is a key characteristic of neural control of movement. In this study, we characterized convergence of the flexor reflex and corticospinal inputs on the tibialis anterior (TA) network in healthy human subjects. Specifically, we characterized the modulation profiles of the spinal TA flexor reflex following subthreshold and suprathreshold transcranial magnetic stimulation (TMS). We also characterized the modulation profiles of the TA motor evoked potentials (MEPs) following medial arch foot stimulation at sensory and above reflex threshold. TA flexor reflexes were evoked following stimulation of the medial arch of the foot with a 30 ms pulse train at innocuous intensities. TA MEPs were evoked following TMS of the leg motor cortex area. TMS at 0.7 and at 1.2 MEP resting threshold increased the TA flexor reflex when TMS was delivered 40-100 ms after foot stimulation, and decreased the TA flexor reflex when TMS was delivered 25-110 ms before foot stimulation. Foot stimulation at sensory and above flexor reflex threshold induced a similar time-dependent modulation in resting TA MEPs, that were facilitated when foot stimulation was delivered 40-100 ms before TMS. The flexor reflex and MEPs recorded from the medial hamstring muscle were modulated in a similar manner to that observed for the TA flexor reflex and MEP. Cutaneomuscular afferents from the distal foot can increase the output of the leg motor cortex area. Descending motor volleys that directly or indirectly depolarize flexor motoneurons increase the output of the spinal FRA interneuronal network. The parallel facilitation of flexor MEPs and flexor reflexes is likely cortical in origin. Afferent mediated facilitation of corticospinal excitability can be utilized to strengthen motor cortex output in neurological disorders. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

CAN-DOO: The Climate Action Network through Direct Observations and Outreach

NASA Astrophysics Data System (ADS)

Taubman, B.; Sherman, J. P.; Perry, L. B.; Markham, J.; Kelly, G.

2011-12-01

The urgency of climate change demands a greater understanding of our climate system, not only by the leaders of today, but by the scientists, policy makers, and citizens of tomorrow. Unfortunately, a large segment of the population currently possesses inadequate knowledge of climate science. In direct response to a need for greater scientific literacy with respect to climate science, researchers from Appalachian State University's Appalachian Atmospheric Interdisciplinary Research (AppalAIR) group, with support from NASA, have developed CAN-DOO: the Climate Action Network through Direct Observations and Outreach. CAN-DOO addresses climate science literacy by 1) Developing the infrastructure for sustaining and expanding public outreach through long-term climate measurements capable of complementing existing NASA measurements, 2) Enhancing public awareness of climate science and NASA's role in advancing our understanding of the Earth System, and 3) Introducing Science, Technology, Engineering, and Mathematics principles to homeschooled, public school, and Appalachian State University students through applied climate science activities. Project partners include the Grandfather Mountain Stewardship Foundation, Pisgah Astronomical Research Institute, and local elementary schools. In partnership with Grandfather Mountain, climate science awareness is promoted through citizen science activities, interactive public displays, and staff training. CAN-DOO engages students by involving them in the entire scientific investigative process as applied to climate science. We introduce local elementary and middle school students, homeschooled students throughout North Carolina, and undergraduate students in a new Global Climate Change course and select other courses at Appalachian State University to instrument assembly, measurement techniques, data collection, hypothesis testing, and drawing conclusions. Results are placed in the proper context via comparisons with other student data products, local research-grade measurements, and NASA measurements. Several educational modules have been developed that address specific topics in climate science. The modules are scalable and have been successfully implemented at levels ranging from 2nd grade through first-year graduate as well as with citizen science groups. They also can be applied in user-desired segments to a variety of Earth Science units. In this paper, we will introduce the project activities and present results from the first year of observations and outreach, with a special emphasis on two of the developed modules, the surface energy balance and aerosol optical depth module.

Analysis of bHLH coding genes using gene co-expression network approach.

PubMed

Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

2016-07-01

Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes were identified showing multiple connections with other genes in the same cluster. Seed genes were found to be vary in different time periods of stress. These analyzed seed genes may be utilized further as marker genes for developing the stress tolerant plant species.

The Missing Part of Seed Dispersal Networks: Structure and Robustness of Bat-Fruit Interactions

PubMed Central

Mello, Marco Aurelio Ribeiro; Marquitti, Flávia Maria Darcie; Guimarães, Paulo Roberto; Kalko, Elisabeth Klara Viktoria; Jordano, Pedro; de Aguiar, Marcus Aloizio Martinez

2011-01-01

Mutualistic networks are crucial to the maintenance of ecosystem services. Unfortunately, what we know about seed dispersal networks is based only on bird-fruit interactions. Therefore, we aimed at filling part of this gap by investigating bat-fruit networks. It is known from population studies that: (i) some bat species depend more on fruits than others, and (ii) that some specialized frugivorous bats prefer particular plant genera. We tested whether those preferences affected the structure and robustness of the whole network and the functional roles of species. Nine bat-fruit datasets from the literature were analyzed and all networks showed lower complementary specialization (H2' = 0.37±0.10, mean ± SD) and similar nestedness (NODF = 0.56±0.12) than pollination networks. All networks were modular (M = 0.32±0.07), and had on average four cohesive subgroups (modules) of tightly connected bats and plants. The composition of those modules followed the genus-genus associations observed at population level (Artibeus-Ficus, Carollia-Piper, and Sturnira-Solanum), although a few of those plant genera were dispersed also by other bats. Bat-fruit networks showed high robustness to simulated cumulative removals of both bats (R = 0.55±0.10) and plants (R = 0.68±0.09). Primary frugivores interacted with a larger proportion of the plants available and also occupied more central positions; furthermore, their extinction caused larger changes in network structure. We conclude that bat-fruit networks are highly cohesive and robust mutualistic systems, in which redundancy is high within modules, although modules are complementary to each other. Dietary specialization seems to be an important structuring factor that affects the topology, the guild structure and functional roles in bat-fruit networks. PMID:21386981

The missing part of seed dispersal networks: structure and robustness of bat-fruit interactions.

PubMed

Mello, Marco Aurelio Ribeiro; Marquitti, Flávia Maria Darcie; Guimarães, Paulo Roberto; Kalko, Elisabeth Klara Viktoria; Jordano, Pedro; de Aguiar, Marcus Aloizio Martinez

2011-02-28

Mutualistic networks are crucial to the maintenance of ecosystem services. Unfortunately, what we know about seed dispersal networks is based only on bird-fruit interactions. Therefore, we aimed at filling part of this gap by investigating bat-fruit networks. It is known from population studies that: (i) some bat species depend more on fruits than others, and (ii) that some specialized frugivorous bats prefer particular plant genera. We tested whether those preferences affected the structure and robustness of the whole network and the functional roles of species. Nine bat-fruit datasets from the literature were analyzed and all networks showed lower complementary specialization (H(2)' = 0.37±0.10, mean ± SD) and similar nestedness (NODF = 0.56±0.12) than pollination networks. All networks were modular (M = 0.32±0.07), and had on average four cohesive subgroups (modules) of tightly connected bats and plants. The composition of those modules followed the genus-genus associations observed at population level (Artibeus-Ficus, Carollia-Piper, and Sturnira-Solanum), although a few of those plant genera were dispersed also by other bats. Bat-fruit networks showed high robustness to simulated cumulative removals of both bats (R = 0.55±0.10) and plants (R = 0.68±0.09). Primary frugivores interacted with a larger proportion of the plants available and also occupied more central positions; furthermore, their extinction caused larger changes in network structure. We conclude that bat-fruit networks are highly cohesive and robust mutualistic systems, in which redundancy is high within modules, although modules are complementary to each other. Dietary specialization seems to be an important structuring factor that affects the topology, the guild structure and functional roles in bat-fruit networks.

In-situ trainable intrusion detection system

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

Symons, Christopher T.; Beaver, Justin M.; Gillen, Rob

A computer implemented method detects intrusions using a computer by analyzing network traffic. The method includes a semi-supervised learning module connected to a network node. The learning module uses labeled and unlabeled data to train a semi-supervised machine learning sensor. The method records events that include a feature set made up of unauthorized intrusions and benign computer requests. The method identifies at least some of the benign computer requests that occur during the recording of the events while treating the remainder of the data as unlabeled. The method trains the semi-supervised learning module at the network node in-situ, such thatmore » the semi-supervised learning modules may identify malicious traffic without relying on specific rules, signatures, or anomaly detection.« less

A FRAMEWORK FOR ATTRIBUTE-BASED COMMUNITY DETECTION WITH APPLICATIONS TO INTEGRATED FUNCTIONAL GENOMICS.

PubMed

Yu, Han; Hageman Blair, Rachael

2016-01-01

Understanding community structure in networks has received considerable attention in recent years. Detecting and leveraging community structure holds promise for understanding and potentially intervening with the spread of influence. Network features of this type have important implications in a number of research areas, including, marketing, social networks, and biology. However, an overwhelming majority of traditional approaches to community detection cannot readily incorporate information of node attributes. Integrating structural and attribute information is a major challenge. We propose a exible iterative method; inverse regularized Markov Clustering (irMCL), to network clustering via the manipulation of the transition probability matrix (aka stochastic flow) corresponding to a graph. Similar to traditional Markov Clustering, irMCL iterates between "expand" and "inflate" operations, which aim to strengthen the intra-cluster flow, while weakening the inter-cluster flow. Attribute information is directly incorporated into the iterative method through a sigmoid (logistic function) that naturally dampens attribute influence that is contradictory to the stochastic flow through the network. We demonstrate advantages and the exibility of our approach using simulations and real data. We highlight an application that integrates breast cancer gene expression data set and a functional network defined via KEGG pathways reveal significant modules for survival.

Attenuation correction for brain PET imaging using deep neural network based on dixon and ZTE MR images.

PubMed

Gong, Kuang; Yang, Jaewon; Kim, Kyungsang; El Fakhri, Georges; Seo, Youngho; Li, Quanzheng

2018-05-23

Positron Emission Tomography (PET) is a functional imaging modality widely used in neuroscience studies. To obtain meaningful quantitative results from PET images, attenuation correction is necessary during image reconstruction. For PET/MR hybrid systems, PET attenuation is challenging as Magnetic Resonance (MR) images do not reflect attenuation coefficients directly. To address this issue, we present deep neural network methods to derive the continuous attenuation coefficients for brain PET imaging from MR images. With only Dixon MR images as the network input, the existing U-net structure was adopted and analysis using forty patient data sets shows it is superior than other Dixon based methods. When both Dixon and zero echo time (ZTE) images are available, we have proposed a modified U-net structure, named GroupU-net, to efficiently make use of both Dixon and ZTE information through group convolution modules when the network goes deeper. Quantitative analysis based on fourteen real patient data sets demonstrates that both network approaches can perform better than the standard methods, and the proposed network structure can further reduce the PET quantification error compared to the U-net structure. © 2018 Institute of Physics and Engineering in Medicine.

Dynamic security contingency screening and ranking using neural networks.

PubMed

Mansour, Y; Vaahedi, E; El-Sharkawi, M A

1997-01-01

This paper summarizes BC Hydro's experience in applying neural networks to dynamic security contingency screening and ranking. The idea is to use the information on the prevailing operating condition and directly provide contingency screening and ranking using a trained neural network. To train the two neural networks for the large scale systems of BC Hydro and Hydro Quebec, in total 1691 detailed transient stability simulation were conducted, 1158 for BC Hydro system and 533 for the Hydro Quebec system. The simulation program was equipped with the energy margin calculation module (second kick) to measure the energy margin in each run. The first set of results showed poor performance for the neural networks in assessing the dynamic security. However a number of corrective measures improved the results significantly. These corrective measures included: 1) the effectiveness of output; 2) the number of outputs; 3) the type of features (static versus dynamic); 4) the number of features; 5) system partitioning; and 6) the ratio of training samples to features. The final results obtained using the large scale systems of BC Hydro and Hydro Quebec demonstrates a good potential for neural network in dynamic security assessment contingency screening and ranking.

Adolescent Development of Value-Guided Goal Pursuit.

PubMed

Davidow, Juliet Y; Insel, Catherine; Somerville, Leah H

2018-06-04

Adolescents are challenged to orchestrate goal-directed actions in increasingly independent and consequential ways. In doing so, it is advantageous to use information about value to select which goals to pursue and how much effort to devote to them. Here, we examine age-related changes in how individuals use value signals to orchestrate goal-directed behavior. Drawing on emerging literature on value-guided cognitive control and reinforcement learning, we demonstrate how value and task difficulty modulate the execution of goal-directed action in complex ways across development from childhood to adulthood. We propose that the scope of value-guided goal pursuit expands with age to include increasingly challenging cognitive demands, and scaffolds on the emergence of functional integration within brain networks supporting valuation, cognition, and action. Copyright © 2018 Elsevier Ltd. All rights reserved.

480 Mbit/s UWB bi-directional radio over fiber CWDM PON using ultra-low cost and power VCSELs.

PubMed

Quinlan, Terence; Morant, Maria; Dudley, Sandra; Llorente, Roberto; Walker, Stuart

2011-12-12

Radio-over-fiber (RoF) schemes offer the possibility of permitting direct access to native format services for the domestic user. A low power requirement and cost effectiveness are crucial to both the service provider and the end user. Here, we present an ultra-low cost and power RoF scheme using direct modulation of commercially-available 1344 nm and 1547 nm VCSELs by band-group 1 UWB wireless signals (ECMA-368) at near broadcast power levels. As a result, greatly simplified electrical-optical-electrical conversion is accomplished. A successful demonstration over a transmission distance of 20.1 km is described using a SSMF, CWDM optical network. EVMs of better than -18.3 dB were achieved. © 2011 Optical Society of America

128 Gb/s TWDM PON system using dispersion-supported transmission method

NASA Astrophysics Data System (ADS)

Bindhaiq, Salem; Zulkifli, Nadiatulhuda; Supa'at, Abusahmah M.; Idrus, Sevia M.; Salleh, M. S.

2017-11-01

Time and wavelength division multiplexed passive optical network (TWDM-PON) trend is considered as the most extraordinary trend of the next generation solution to accommodate exponential traffic growth for converged new services. In this paper, we briefly review recent progress on TWDM-PON system through the use of low cost directly modulated lasers (DMLs) transmission for various line rate transmissions to date. Furthermore, through simulation, we propose and evaluate a cost effective way to upgrade TWDM-PON up to a symmetric capacity of 128 Gb/s using fiber Bragg gratings (FBGs) in optical line terminal (OLT) as a paramount dispersion manager in high speed light-wave systems in both upstream and downstream directions. A low cost and potential chirpless directed modulated grating laser (DMGL) is employed for downstream link and DML with a single delay-interferometer (DI) is employed for upstream link. After illustrating the demonstrated system architecture and configuration, we present the results and analysis to prove the system feasibility. The results show that a successful transmission is achieved over 40 km single mode fiber with a power budget of 33.7 dB, which could support 1:256 splitting ratio.

60-GHz Millimeter-wave Over Fiber with Directly Modulated Dual-mode Laser Diode

PubMed Central

Tsai, Cheng-Ting; Lin, Chi-Hsiang; Lin, Chun-Ting; Chi, Yu-Chieh; Lin, Gong-Ru

2016-01-01

A directly modulated dual-mode laser diode (DMLD) with third-order intermodulation distortion (IMD3) suppression is proposed for a 60-GHz millimeter-wave over fiber (MMWoF) architecture, enabling new fiber-wireless communication access to cover 4-km single-mode-fiber (SMF) and 3-m wireless 16-QAM OFDM transmissions. By dual-mode injection-locking, the throughput degradation of the DMLD is mitigated with saturation effect to reduce its threshold, IMD3 power and relative intensity noise to 7.7 mA, −85 dBm and −110.4 dBc/Hz, respectively, providing huge spurious-free dynamic range of 85.8 dB/Hz2/3. This operation suppresses the noise floor of the DMLD carried QPSK-OFDM spectrum by 5 dB. The optical receiving power is optimized to restrict the power fading effect for improving the bit error rate to 1.9 × 10−3 and the receiving power penalty to 1.1 dB. Such DMLD based hybrid architecture for 60-GHz MMW fiber-wireless access can directly cover the current optical and wireless networks for next-generation indoor and short-reach mobile communications. PMID:27297267

From Saccharomyces cerevisiae to human: The important gene co-expression modules.

PubMed

Liu, Wei; Li, Li; Ye, Hua; Chen, Haiwei; Shen, Weibiao; Zhong, Yuexian; Tian, Tian; He, Huaqin

2017-08-01

Network-based systems biology has become an important method for analyzing high-throughput gene expression data and gene function mining. Yeast has long been a popular model organism for biomedical research. In the current study, a weighted gene co-expression network analysis algorithm was applied to construct a gene co-expression network in Saccharomyces cerevisiae . Seventeen stable gene co-expression modules were detected from 2,814 S. cerevisiae microarray data. Further characterization of these modules with the Database for Annotation, Visualization and Integrated Discovery tool indicated that these modules were associated with certain biological processes, such as heat response, cell cycle, translational regulation, mitochondrion oxidative phosphorylation, amino acid metabolism and autophagy. Hub genes were also screened by intra-modular connectivity. Finally, the module conservation was evaluated in a human disease microarray dataset. Functional modules were identified in budding yeast, some of which are associated with patient survival. The current study provided a paradigm for single cell microorganisms and potentially other organisms.

Modulators for the S-band test linac at DESY

NASA Astrophysics Data System (ADS)

Bieler, M.; Choroba, S.; Hameister, J.; Lewin, H.-Ch.

1995-07-01

The development of adequate modulators for high peak power klystrons is one of the focus points for linear collider R&D programs. For the DESY/THD S-band linear collider study 150 MW rf-pulse power at 50 Hz repetition rate and 3 μs pulse duration is required [1]. Two different modulator schemes are under investigation. One is the conventional line type pulser, using a pulse forming network and a step up transformer, the other one is a hard tube pulser, using a dc power source at the full klystron voltage and a switch tube. This paper is focused on the modulator development for the S-band Test Linac at DESY. After a short overview over the test linac and a brief description of the 150 MW S-band klystron the circuitry of the line type pulse (LTP) is given. A hard tube pulser (HTP), which switches the high voltage directly from a storage capacitor to the klystron, has been built up at DESY. Circuitry and the results of the commissioning of the switch tube are reported.

Soft-Input Soft-Output Modules for the Construction and Distributed Iterative Decoding of Code Networks

NASA Technical Reports Server (NTRS)

Benedetto, S.; Divsalar, D.; Montorsi, G.; Pollara, F.

1998-01-01

Soft-input soft-output building blocks (modules) are presented to construct and iteratively decode in a distributed fashion code networks, a new concept that includes, and generalizes, various forms of concatenated coding schemes.

SPADnet: a fully digital, scalable, and networked photonic component for time-of-flight PET applications

NASA Astrophysics Data System (ADS)

Bruschini, Claudio; Charbon, Edoardo; Veerappan, Chockalingam; Braga, Leo H. C.; Massari, Nicola; Perenzoni, Matteo; Gasparini, Leonardo; Stoppa, David; Walker, Richard; Erdogan, Ahmet; Henderson, Robert K.; East, Steve; Grant, Lindsay; Játékos, Balázs; Ujhelyi, Ferenc; Erdei, Gábor; Lörincz, Emöke; André, Luc; Maingault, Laurent; Jacolin, David; Verger, L.; Gros d'Aillon, Eric; Major, Peter; Papp, Zoltan; Nemeth, Gabor

2014-05-01

The SPADnet FP7 European project is aimed at a new generation of fully digital, scalable and networked photonic components to enable large area image sensors, with primary target gamma-ray and coincidence detection in (Time-of- Flight) Positron Emission Tomography (PET). SPADnet relies on standard CMOS technology, therefore allowing for MRI compatibility. SPADnet innovates in several areas of PET systems, from optical coupling to single-photon sensor architectures, from intelligent ring networks to reconstruction algorithms. It is built around a natively digital, intelligent SPAD (Single-Photon Avalanche Diode)-based sensor device which comprises an array of 8×16 pixels, each composed of 4 mini-SiPMs with in situ time-to-digital conversion, a multi-ring network to filter, carry, and process data produced by the sensors at 2Gbps, and a 130nm CMOS process enabling mass-production of photonic modules that are optically interfaced to scintillator crystals. A few tens of sensor devices are tightly abutted on a single PCB to form a so-called sensor tile, thanks to TSV (Through Silicon Via) connections to their backside (replacing conventional wire bonding). The sensor tile is in turn interfaced to an FPGA-based PCB on its back. The resulting photonic module acts as an autonomous sensing and computing unit, individually detecting gamma photons as well as thermal and Compton events. It determines in real time basic information for each scintillation event, such as exact time of arrival, position and energy, and communicates it to its peers in the field of view. Coincidence detection does therefore occur directly in the ring itself, in a differed and distributed manner to ensure scalability. The selected true coincidence events are then collected by a snooper module, from which they are transferred to an external reconstruction computer using Gigabit Ethernet.

Distributed multisensory integration in a recurrent network model through supervised learning

NASA Astrophysics Data System (ADS)

Wang, He; Wong, K. Y. Michael

Sensory integration between different modalities has been extensively studied. It is suggested that the brain integrates signals from different modalities in a Bayesian optimal way. However, how the Bayesian rule is implemented in a neural network remains under debate. In this work we propose a biologically plausible recurrent network model, which can perform Bayesian multisensory integration after trained by supervised learning. Our model is composed of two modules, each for one modality. We assume that each module is a recurrent network, whose activity represents the posterior distribution of each stimulus. The feedforward input on each module is the likelihood of each modality. Two modules are integrated through cross-links, which are feedforward connections from the other modality, and reciprocal connections, which are recurrent connections between different modules. By stochastic gradient descent, we successfully trained the feedforward and recurrent coupling matrices simultaneously, both of which resembles the Mexican-hat. We also find that there are more than one set of coupling matrices that can approximate the Bayesian theorem well. Specifically, reciprocal connections and cross-links will compensate each other if one of them is removed. Even though trained with two inputs, the network's performance with only one input is in good accordance with what is predicted by the Bayesian theorem.

Intelligent deflection routing in buffer-less networks.

PubMed

Haeri, Soroush; Trajković, Ljiljana

2015-02-01

Deflection routing is employed to ameliorate packet loss caused by contention in buffer-less architectures such as optical burst-switched networks. The main goal of deflection routing is to successfully deflect a packet based only on a limited knowledge that network nodes possess about their environment. In this paper, we present a framework that introduces intelligence to deflection routing (iDef). iDef decouples the design of the signaling infrastructure from the underlying learning algorithm. It consists of a signaling and a decision-making module. Signaling module implements a feedback management protocol while the decision-making module implements a reinforcement learning algorithm. We also propose several learning-based deflection routing protocols, implement them in iDef using the ns-3 network simulator, and compare their performance.

Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis

PubMed Central

2018-01-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that ‘leftover’ proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module allows cells to tune where endocytosis occurs, providing sensitive control over cargo uptake via clathrin-coated vesicles. PMID:29518071

Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis.

PubMed

Holland, David O; Johnson, Margaret E

2018-03-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that 'leftover' proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module allows cells to tune where endocytosis occurs, providing sensitive control over cargo uptake via clathrin-coated vesicles.

Dynamics of neuromodulatory feedback determines frequency modulation in a reduced respiratory network: a computational study.

PubMed

Toporikova, Natalia; Butera, Robert J

2013-02-01

Neuromodulators, such as amines and neuropeptides, alter the activity of neurons and neuronal networks. In this work, we investigate how neuromodulators, which activate G(q)-protein second messenger systems, can modulate the bursting frequency of neurons in a critical portion of the respiratory neural network, the pre-Bötzinger complex (preBötC). These neurons are a vital part of the ponto-medullary neuronal network, which generates a stable respiratory rhythm whose frequency is regulated by neuromodulator release from the nearby Raphe nucleus. Using a simulated 50-cell network of excitatory preBötC neurons with a heterogeneous distribution of persistent sodium conductance and Ca(2+), we determined conditions for frequency modulation in such a network by simulating interaction between Raphe and preBötC nuclei. We found that the positive feedback between the Raphe excitability and preBötC activity induces frequency modulation in the preBötC neurons. In addition, the frequency of the respiratory rhythm can be regulated via phasic release of excitatory neuromodulators from the Raphe nucleus. We predict that the application of a G(q) antagonist will eliminate this frequency modulation by the Raphe and keep the network frequency constant and low. In contrast, application of a G(q) agonist will result in a high frequency for all levels of Raphe stimulation. Our modeling results also suggest that high [K(+)] requirement in respiratory brain slice experiments may serve as a compensatory mechanism for low neuromodulatory tone. Copyright © 2012 Elsevier B.V. All rights reserved.

Emergence of system roles in normative neurodevelopment

PubMed Central

Gu, Shi; Satterthwaite, Theodore D.; Medaglia, John D.; Yang, Muzhi; Gur, Raquel E.; Gur, Ruben C.; Bassett, Danielle S.

2015-01-01

Adult human cognition is supported by systems of brain regions, or modules, that are functionally coherent at rest and collectively activated by distinct task requirements. However, an understanding of how the formation of these modules supports evolving cognitive capabilities has not been delineated. Here, we quantify the formation of network modules in a sample of 780 youth (aged 8–22 y) who were studied as part of the Philadelphia Neurodevelopmental Cohort. We demonstrate that the brain’s functional network organization changes in youth through a process of modular evolution that is governed by the specific cognitive roles of each system, as defined by the balance of within- vs. between-module connectivity. Moreover, individual variability in these roles is correlated with cognitive performance. Collectively, these results suggest that dynamic maturation of network modules in youth may be a critical driver for the development of cognition. PMID:26483477

Photonic Quantum Networks formed from NV− centers

PubMed Central

Nemoto, Kae; Trupke, Michael; Devitt, Simon J.; Scharfenberger, Burkhard; Buczak, Kathrin; Schmiedmayer, Jörg; Munro, William J.

2016-01-01

In this article we present a simple repeater scheme based on the negatively-charged nitrogen vacancy centre in diamond. Each repeater node is built from modules comprising an optical cavity containing a single NV−, with one nuclear spin from 15N as quantum memory. The module uses only deterministic processes and interactions to achieve high fidelity operations (>99%), and modules are connected by optical fiber. In the repeater node architecture, the processes between modules by photons can be in principle deterministic, however current limitations on optical components lead the processes to be probabilistic but heralded. Our resource-modest repeater architecture contains two modules at each node, and the repeater nodes are then connected by entangled photon pairs. We discuss the performance of such a quantum repeater network with modest resources and then incorporate more resource-intense strategies step by step. Our architecture should allow large-scale quantum information networks with existing or near future technology. PMID:27215433

Photonic Quantum Networks formed from NV(-) centers.

PubMed

Nemoto, Kae; Trupke, Michael; Devitt, Simon J; Scharfenberger, Burkhard; Buczak, Kathrin; Schmiedmayer, Jörg; Munro, William J

2016-05-24

In this article we present a simple repeater scheme based on the negatively-charged nitrogen vacancy centre in diamond. Each repeater node is built from modules comprising an optical cavity containing a single NV(-), with one nuclear spin from (15)N as quantum memory. The module uses only deterministic processes and interactions to achieve high fidelity operations (>99%), and modules are connected by optical fiber. In the repeater node architecture, the processes between modules by photons can be in principle deterministic, however current limitations on optical components lead the processes to be probabilistic but heralded. Our resource-modest repeater architecture contains two modules at each node, and the repeater nodes are then connected by entangled photon pairs. We discuss the performance of such a quantum repeater network with modest resources and then incorporate more resource-intense strategies step by step. Our architecture should allow large-scale quantum information networks with existing or near future technology.

Ubiquitous health monitoring system for multiple users using a ZigBee and WLAN dual-network.

PubMed

Cha, Yong Dae; Yoon, Gilwon

2009-11-01

A ubiquitous health monitoring system for multiple users was developed based on a ZigBee and wireless local area network (WLAN) dual-network. A compact biosignal monitoring unit (BMU) for measuring electrocardiogram (ECG), photoplethysmogram (PPG), and temperature was also developed. A single 8-bit microcontroller operated the BMU including most of digital filtering and wireless communication. The BMU with its case was reduced to 55 x 35 x 15 mm and 33 g. In routine use, vital signs of 6 bytes/sec (heart rate, temperature, pulse transit time) per each user were transmitted through a ZigBee module even though all the real-time data were recorded in a secure digital memory of the BMU. In an emergency or when need arises, a channel of a particular user was switched to another ZigBee module, called the emergency module, that sent all ECG and PPG waveforms in real time. Each emergency ZigBee module handled up to a few users. Data from multiple users were wirelessly received by the ZigBee receiver modules in a controller called ZigBee-WLAN gateway, where the ZigBee modules were connected to a WLAN module. This WLAN module sent all data wirelessly to a monitoring center. Operating the dual modes of ZigBee/WLAN utilized an advantage of ZigBee by handling multiple users with minimum power consumption, and overcame the ZigBee limitation of low data rate. This dual-network system for LAN is economically competitive and reliable.

Serotonin receptor 1A–modulated phosphorylation of glycine receptor α3 controls breathing in mice

PubMed Central

Manzke, Till; Niebert, Marcus; Koch, Uwe R.; Caley, Alex; Vogelgesang, Steffen; Hülsmann, Swen; Ponimaskin, Evgeni; Müller, Ulrike; Smart, Trevor G.; Harvey, Robert J.; Richter, Diethelm W.

2010-01-01

Rhythmic breathing movements originate from a dispersed neuronal network in the medulla and pons. Here, we demonstrate that rhythmic activity of this respiratory network is affected by the phosphorylation status of the inhibitory glycine receptor α3 subtype (GlyRα3), which controls glutamatergic and glycinergic neuronal discharges, subject to serotonergic modulation. Serotonin receptor type 1A–specific (5-HTR1A–specific) modulation directly induced dephosphorylation of GlyRα3 receptors, which augmented inhibitory glycine-activated chloride currents in HEK293 cells coexpressing 5-HTR1A and GlyRα3. The 5-HTR1A–GlyRα3 signaling pathway was distinct from opioid receptor signaling and efficiently counteracted opioid-induced depression of breathing and consequential apnea in mice. Paradoxically, this rescue of breathing originated from enhanced glycinergic synaptic inhibition of glutamatergic and glycinergic neurons and caused disinhibition of their target neurons. Together, these effects changed respiratory phase alternations and ensured rhythmic breathing in vivo. GlyRα3-deficient mice had an irregular respiratory rhythm under baseline conditions, and systemic 5-HTR1A activation failed to remedy opioid-induced respiratory depression in these mice. Delineation of this 5-HTR1A–GlyRα3 signaling pathway offers a mechanistic basis for pharmacological treatment of opioid-induced apnea and other breathing disturbances caused by disorders of inhibitory synaptic transmission, such as hyperekplexia, hypoxia/ischemia, and brainstem infarction. PMID:20978350

SNE Industrial Fieldbus Interface

NASA Technical Reports Server (NTRS)

Lucena, Angel; Raines, Matthew; Oostdyk, Rebecca; Mata, Carlos

2011-01-01

Programmable logic controllers (PLCs) have very limited diagnostic and no prognostic capabilities, while current smart sensor designs do not have the capability to communicate over Fieldbus networks. The aim is to interface smart sensors with PLCs so that health and status information, such as failure mode identification and measurement tolerance, can be communicated via an industrial Fieldbus such as ControlNet. The SNE Industrial Fieldbus Interface (SIFI) is an embedded device that acts as a communication module in a networked smart sensor. The purpose is to enable a smart sensor to communicate health and status information to other devices, such as PLCs, via an industrial Fieldbus networking protocol. The SNE (Smart Network Element) is attached to a commercial off-the-shelf Any bus-S interface module through the SIFI. Numerous Anybus-S modules are available, each one designed to interface with a specific Fieldbus. Development of the SIFI focused on communications using the ControlNet protocol, but any of the Anybus-S modules can be used. The SIFI communicates with the Any-bus module via a data buffer and mailbox system on the Anybus module, and supplies power to the module. The Anybus module transmits and receives data on the Fieldbus using the proper protocol. The SIFI is intended to be connected to other existing SNE modules in order to monitor the health and status of a transducer. The SIFI can also monitor aspects of its own health using an onboard watchdog timer and voltage monitors. The SIFI also has the hardware to drive a touchscreen LCD (liquid crystal display) unit for manual configuration and status monitoring.

Systems-level analysis of risk genes reveals the modular nature of schizophrenia.

PubMed

Liu, Jiewei; Li, Ming; Luo, Xiong-Jian; Su, Bing

2018-05-19

Schizophrenia (SCZ) is a complex mental disorder with high heritability. Genetic studies (especially recent genome-wide association studies) have identified many risk genes for schizophrenia. However, the physical interactions among the proteins encoded by schizophrenia risk genes remain elusive and it is not known whether the identified risk genes converge on common molecular networks or pathways. Here we systematically investigated the network characteristics of schizophrenia risk genes using the high-confidence protein-protein interactions (PPI) from the human interactome. We found that schizophrenia risk genes encode a densely interconnected PPI network (P = 4.15 × 10 -31 ). Compared with the background genes, the schizophrenia risk genes in the interactome have significantly higher degree (P = 5.39 × 10 -11 ), closeness centrality (P = 7.56 × 10 -11 ), betweeness centrality (P = 1.29 × 10 -11 ), clustering coefficient (P = 2.22 × 10 -2 ), and shorter average shortest path length (P = 7.56 × 10 -11 ). Based on the densely interconnected PPI network, we identified 48 hub genes and 4 modules formed by highly interconnected schizophrenia genes. We showed that the proteins encoded by schizophrenia hub genes have significantly more direct physical interactions. Gene ontology (GO) analysis revealed that cell adhesion, cell cycle, immune system response, and GABR-receptor complex categories were enriched in the modules formed by highly interconnected schizophrenia risk genes. Our study reveals that schizophrenia risk genes encode a densely interconnected molecular network and demonstrates the modular nature of schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

Multi-omic integrated networks connect DNA methylation and miRNA with skeletal muscle plasticity to chronic exercise in Type 2 diabetic obesity

PubMed Central

Page, Rachel A.; Sukala, William R.; Giri, Mamta; Ghimbovschi, Svetlana D.; Hayat, Irum; Cheema, Birinder S.; Lys, Isabelle; Leikis, Murray; Sheard, Phillip W.; Wakefield, St. John; Breier, Bernhard; Hathout, Yetrib; Brown, Kristy; Marathi, Ramya; Orkunoglu-Suer, Funda E.; Devaney, Joseph M.; Leiken, Benjamin; Many, Gina; Krebs, Jeremy; Hopkins, Will G.; Hoffman, Eric P.

2014-01-01

Epigenomic regulation of the transcriptome by DNA methylation and posttranscriptional gene silencing by miRNAs are potential environmental modulators of skeletal muscle plasticity to chronic exercise in healthy and diseased populations. We utilized transcriptome networks to connect exercise-induced differential methylation and miRNA with functional skeletal muscle plasticity. Biopsies of the vastus lateralis were collected from middle-aged Polynesian men and women with morbid obesity (44 kg/m2 ± 10) and Type 2 diabetes before and following 16 wk of resistance (n = 9) or endurance training (n = 8). Longitudinal transcriptome, methylome, and microRNA (miRNA) responses were obtained via microarray, filtered by novel effect-size based false discovery rate probe selection preceding bioinformatic interrogation. Metabolic and microvascular transcriptome topology dominated the network landscape following endurance exercise. Lipid and glucose metabolism modules were connected to: microRNA (miR)-29a; promoter region hypomethylation of nuclear receptor factor (NRF1) and fatty acid transporter (SLC27A4), and hypermethylation of fatty acid synthase, and to exon hypomethylation of 6-phosphofructo-2-kinase and Ser/Thr protein kinase. Directional change in the endurance networks was validated by lower intramyocellular lipid, increased capillarity, GLUT4, hexokinase, and mitochondrial enzyme activity and proteome. Resistance training also lowered lipid and increased enzyme activity and caused GLUT4 promoter hypomethylation; however, training was inconsequential to GLUT4, capillarity, and metabolic transcriptome. miR-195 connected to negative regulation of vascular development. To conclude, integrated molecular network modelling revealed differential DNA methylation and miRNA expression changes occur in skeletal muscle in response to chronic exercise training that are most pronounced with endurance training and topographically associated with functional metabolic and microvascular plasticity relevant to diabetes rehabilitation. PMID:25138607

Advanced digital signal processing for short-haul and access network

NASA Astrophysics Data System (ADS)

Zhang, Junwen; Yu, Jianjun; Chi, Nan

2016-02-01

Digital signal processing (DSP) has been proved to be a successful technology recently in high speed and high spectrum-efficiency optical short-haul and access network, which enables high performances based on digital equalizations and compensations. In this paper, we investigate advanced DSP at the transmitter and receiver side for signal pre-equalization and post-equalization in an optical access network. A novel DSP-based digital and optical pre-equalization scheme has been proposed for bandwidth-limited high speed short-distance communication system, which is based on the feedback of receiver-side adaptive equalizers, such as least-mean-squares (LMS) algorithm and constant or multi-modulus algorithms (CMA, MMA). Based on this scheme, we experimentally demonstrate 400GE on a single optical carrier based on the highest ETDM 120-GBaud PDM-PAM-4 signal, using one external modulator and coherent detection. A line rate of 480-Gb/s is achieved, which enables 20% forward-error correction (FEC) overhead to keep the 400-Gb/s net information rate. The performance after fiber transmission shows large margin for both short range and metro/regional networks. We also extend the advanced DSP for short haul optical access networks by using high order QAMs. We propose and demonstrate a high speed multi-band CAP-WDM-PON system on intensity modulation, direct detection and digital equalizations. A hybrid modified cascaded MMA post-equalization schemes are used to equalize the multi-band CAP-mQAM signals. Using this scheme, we successfully demonstrates 550Gb/s high capacity WDMPON system with 11 WDM channels, 55 sub-bands, and 10-Gb/s per user in the downstream over 40-km SMF.

Neuromodulatory changes in short-term synaptic dynamics may be mediated by two distinct mechanisms of presynaptic calcium entry.

PubMed

Oh, Myongkeun; Zhao, Shunbing; Matveev, Victor; Nadim, Farzan

2012-12-01

Although synaptic output is known to be modulated by changes in presynaptic calcium channels, additional pathways for calcium entry into the presynaptic terminal, such as non-selective channels, could contribute to modulation of short term synaptic dynamics. We address this issue using computational modeling. The neuropeptide proctolin modulates the inhibitory synapse from the lateral pyloric (LP) to the pyloric dilator (PD) neuron, two slow-wave bursting neurons in the pyloric network of the crab Cancer borealis. Proctolin enhances the strength of this synapse and also changes its dynamics. Whereas in control saline the synapse shows depression independent of the amplitude of the presynaptic LP signal, in proctolin, with high-amplitude presynaptic LP stimulation the synapse remains depressing while low-amplitude stimulation causes facilitation. We use simple calcium-dependent release models to explore two alternative mechanisms underlying these modulatory effects. In the first model, proctolin directly targets calcium channels by changing their activation kinetics which results in gradual accumulation of calcium with low-amplitude presynaptic stimulation, leading to facilitation. The second model uses the fact that proctolin is known to activate a non-specific cation current I ( MI ). In this model, we assume that the MI channels have some permeability to calcium, modeled to be a result of slow conformation change after binding calcium. This generates a gradual increase in calcium influx into the presynaptic terminals through the modulatory channel similar to that described in the first model. Each of these models can explain the modulation of the synapse by proctolin but with different consequences for network activity.

Steady-state kinetic modeling constrains cellular resting states and dynamic behavior.

PubMed

Purvis, Jeremy E; Radhakrishnan, Ravi; Diamond, Scott L

2009-03-01

A defining characteristic of living cells is the ability to respond dynamically to external stimuli while maintaining homeostasis under resting conditions. Capturing both of these features in a single kinetic model is difficult because the model must be able to reproduce both behaviors using the same set of molecular components. Here, we show how combining small, well-defined steady-state networks provides an efficient means of constructing large-scale kinetic models that exhibit realistic resting and dynamic behaviors. By requiring each kinetic module to be homeostatic (at steady state under resting conditions), the method proceeds by (i) computing steady-state solutions to a system of ordinary differential equations for each module, (ii) applying principal component analysis to each set of solutions to capture the steady-state solution space of each module network, and (iii) combining optimal search directions from all modules to form a global steady-state space that is searched for accurate simulation of the time-dependent behavior of the whole system upon perturbation. Importantly, this stepwise approach retains the nonlinear rate expressions that govern each reaction in the system and enforces constraints on the range of allowable concentration states for the full-scale model. These constraints not only reduce the computational cost of fitting experimental time-series data but can also provide insight into limitations on system concentrations and architecture. To demonstrate application of the method, we show how small kinetic perturbations in a modular model of platelet P2Y(1) signaling can cause widespread compensatory effects on cellular resting states.

Network analysis of the genomic basis of the placebo effect

PubMed Central

Wang, Rui-Sheng; Hall, Kathryn T.; Giulianini, Franco; Passow, Dani; Kaptchuk, Ted J.

2017-01-01

The placebo effect is a phenomenon in which patients who are given an inactive treatment (e.g., inert pill) show a perceived or actual improvement in a medical condition. Placebo effects in clinical trials have been investigated for many years especially because placebo treatments often serve as the control arm of randomized clinical trial designs. Recent observations suggest that placebo effects may be modified by genetics. This observation has given rise to the term “placebome,” which refers to a group of genome-related mediators that affect an individual’s response to placebo treatments. In this study, we conduct a network analysis of the placebome and identify a placebome module in the comprehensive human interactome using a seed-connector algorithm. The placebome module is significantly enriched with neurotransmitter signaling pathways and brain-specific proteins. We validate the placebome module using a large cohort of the Women’s Genome Health Study (WGHS) trial and demonstrate that the placebome module is significantly enriched with genes whose SNPs modify the outcome in the placebo arm of the trial. To gain insights into placebo effects in different diseases and drug treatments, we use a network proximity measure to examine the closeness of the placebome module to different disease modules and drug target modules. The results demonstrate that the network proximity of the placebome module to disease modules in the interactome significantly correlates with the strength of the placebo effect in the corresponding diseases. The proximity of the placebome module to molecular pathways affected by certain drug classes indicates the existence of placebo-drug interactions. This study is helpful for understanding the molecular mechanisms mediating the placebo response, and sets the stage for minimizing its effects in clinical trials and for developing therapeutic strategies that intentionally engage it. PMID:28570268

A sub-millimeter resolution PET detector module using a multi-pixel photon counter array

NASA Astrophysics Data System (ADS)

Song, Tae Yong; Wu, Heyu; Komarov, Sergey; Siegel, Stefan B.; Tai, Yuan-Chuan

2010-05-01

A PET block detector module using an array of sub-millimeter lutetium oxyorthosilicate (LSO) crystals read out by an array of surface-mount, semiconductor photosensors has been developed. The detector consists of a LSO array, a custom acrylic light guide, a 3 × 3 multi-pixel photon counter (MPPC) array (S10362-11-050P, Hamamatsu Photonics, Japan) and a readout board with a charge division resistor network. The LSO array consists of 100 crystals, each measuring 0.8 × 0.8 × 3 mm3 and arranged in 0.86 mm pitches. A Monte Carlo simulation was used to aid the design and fabrication of a custom light guide to control distribution of scintillation light over the surface of the MPPC array. The output signals of the nine MPPC are multiplexed by a charge division resistor network to generate four position-encoded analog outputs. Flood image, energy resolution and timing resolution measurements were performed using standard NIM electronics. The linearity of the detector response was investigated using gamma-ray sources of different energies. The 10 × 10 array of 0.8 mm LSO crystals was clearly resolved in the flood image. The average energy resolution and standard deviation were 20.0% full-width at half-maximum (FWHM) and ±5.0%, respectively, at 511 keV. The timing resolution of a single MPPC coupled to a LSO crystal was found to be 857 ps FWHM, and the value for the central region of detector module was 1182 ps FWHM when ±10% energy window was applied. The nonlinear response of a single MPPC when used to read out a single LSO was observed among the corner crystals of the proposed detector module. However, the central region of the detector module exhibits significantly less nonlinearity (6.5% for 511 keV). These results demonstrate that (1) a charge-sharing resistor network can effectively multiplex MPPC signals and reduce the number of output signals without significantly degrading the performance of a PET detector and (2) a custom light guide to permit light sharing among multiple MPPC and to diffuse and direct scintillation light can reduce the nonlinearity of the detector response within the limited dynamic range of a typical MPPC. As a result, the proposed PET detector module has the potential to be refined for use in high-resolution PET insert applications.

A sub-millimeter resolution PET detector module using a multi-pixel photon counter array.

PubMed

Song, Tae Yong; Wu, Heyu; Komarov, Sergey; Siegel, Stefan B; Tai, Yuan-Chuan

2010-05-07

A PET block detector module using an array of sub-millimeter lutetium oxyorthosilicate (LSO) crystals read out by an array of surface-mount, semiconductor photosensors has been developed. The detector consists of a LSO array, a custom acrylic light guide, a 3 x 3 multi-pixel photon counter (MPPC) array (S10362-11-050P, Hamamatsu Photonics, Japan) and a readout board with a charge division resistor network. The LSO array consists of 100 crystals, each measuring 0.8 x 0.8 x 3 mm(3) and arranged in 0.86 mm pitches. A Monte Carlo simulation was used to aid the design and fabrication of a custom light guide to control distribution of scintillation light over the surface of the MPPC array. The output signals of the nine MPPC are multiplexed by a charge division resistor network to generate four position-encoded analog outputs. Flood image, energy resolution and timing resolution measurements were performed using standard NIM electronics. The linearity of the detector response was investigated using gamma-ray sources of different energies. The 10 x 10 array of 0.8 mm LSO crystals was clearly resolved in the flood image. The average energy resolution and standard deviation were 20.0% full-width at half-maximum (FWHM) and +/-5.0%, respectively, at 511 keV. The timing resolution of a single MPPC coupled to a LSO crystal was found to be 857 ps FWHM, and the value for the central region of detector module was 1182 ps FWHM when +/-10% energy window was applied. The nonlinear response of a single MPPC when used to read out a single LSO was observed among the corner crystals of the proposed detector module. However, the central region of the detector module exhibits significantly less nonlinearity (6.5% for 511 keV). These results demonstrate that (1) a charge-sharing resistor network can effectively multiplex MPPC signals and reduce the number of output signals without significantly degrading the performance of a PET detector and (2) a custom light guide to permit light sharing among multiple MPPC and to diffuse and direct scintillation light can reduce the nonlinearity of the detector response within the limited dynamic range of a typical MPPC. As a result, the proposed PET detector module has the potential to be refined for use in high-resolution PET insert applications.

A sub-millimeter resolution PET detector module using a multi-pixel photon counter array

PubMed Central

Song, Tae Yong; Wu, Heyu; Komarov, Sergey; Siegel, Stefan B; Tai, Yuan-Chuan

2010-01-01

A PET block detector module using an array of sub-millimeter lutetium oxyorthosilicate (LSO) crystals read out by an array of surface-mount, semiconductor photosensors has been developed. The detector consists of a LSO array, a custom acrylic light guide, a 3 × 3 multi-pixel photon counter (MPPC) array (S10362-11-050P, Hamamatsu Photonics, Japan) and a readout board with a charge division resistor network. The LSO array consists of 100 crystals, each measuring 0.8 × 0.8 × 3 mm3 and arranged in 0.86 mm pitches. A Monte Carlo simulation was used to aid the design and fabrication of a custom light guide to control distribution of scintillation light over the surface of the MPPC array. The output signals of the nine MPPC are multiplexed by a charge division resistor network to generate four position-encoded analog outputs. Flood image, energy resolution and timing resolution measurements were performed using standard NIM electronics. The linearity of the detector response was investigated using gamma-ray sources of different energies. The 10 × 10 array of 0.8 mm LSO crystals was clearly resolved in the flood image. The average energy resolution and standard deviation were 20.0% full-width at half-maximum (FWHM) and ±5.0%, respectively, at 511 keV. The timing resolution of a single MPPC coupled to a LSO crystal was found to be 857 ps FWHM, and the value for the central region of detector module was 1182 ps FWHM when ±10% energy window was applied. The nonlinear response of a single MPPC when used to read out a single LSO was observed among the corner crystals of the proposed detector module. However, the central region of the detector module exhibits significantly less nonlinearity (6.5% for 511 keV). These results demonstrate that (1) a charge-sharing resistor network can effectively multiplex MPPC signals and reduce the number of output signals without significantly degrading the performance of a PET detector and (2) a custom light guide to permit light sharing among multiple MPPC and to diffuse and direct scintillation light can reduce the nonlinearity of the detector response within the limited dynamic range of a typical MPPC. As a result, the proposed PET detector module has the potential to be refined for use in high-resolution PET insert applications. PMID:20393236

External modulation of the sustained attention network in traumatic brain injury.

PubMed

Richard, Nadine M; O'Connor, Charlene; Dey, Ayan; Robertson, Ian H; Levine, Brian

2018-05-07

Traumatic brain injury (TBI) is associated with impairments in processing speed as well as higher-level cognitive functions that depend on distributed neural networks, such as regulating and sustaining attention. Although exogenous alerting cues have been shown to support patients in sustaining attentive, goal-directed behavior, the neural correlates of this rehabilitative effect are unclear. The purpose of this study was to explore the effects of moderate to severe TBI on activity and functional connectivity in the well-documented right-lateralized frontal-subcortical-parietal sustained attention network, and to assess the effects of alerting cues. Using multivariate analysis of fMRI data, TBI patients and matched neurologically healthy (NH) comparison participants were scanned as they performed the Sustained Attention to Response Task (SART) in 60-s blocks, with or without exogenous cueing through brief auditory alerting tones. Results documented inefficient voluntary control of attention in the TBI patients, with reduced functional connectivity in the sustained attention network relative to NH participants. When alerting cues were present during the SART, however, functional connectivity increased and became comparable to activity patterns seen in the NH group. These findings provide novel evidence of a neural mechanism for the facilitatory effects of alerting cues on goal-directed behavior in patients with damaged attentional brain systems, and support their use in cognitive rehabilitation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Neural coding in graphs of bidirectional associative memories.

PubMed

Bouchain, A David; Palm, Günther

2012-01-24

In the last years we have developed large neural network models for the realization of complex cognitive tasks in a neural network architecture that resembles the network of the cerebral cortex. We have used networks of several cortical modules that contain two populations of neurons (one excitatory, one inhibitory). The excitatory populations in these so-called "cortical networks" are organized as a graph of Bidirectional Associative Memories (BAMs), where edges of the graph correspond to BAMs connecting two neural modules and nodes of the graph correspond to excitatory populations with associative feedback connections (and inhibitory interneurons). The neural code in each of these modules consists essentially of the firing pattern of the excitatory population, where mainly it is the subset of active neurons that codes the contents to be represented. The overall activity can be used to distinguish different properties of the patterns that are represented which we need to distinguish and control when performing complex tasks like language understanding with these cortical networks. The most important pattern properties or situations are: exactly fitting or matching input, incomplete information or partially matching pattern, superposition of several patterns, conflicting information, and new information that is to be learned. We show simple simulations of these situations in one area or module and discuss how to distinguish these situations based on the overall internal activation of the module. This article is part of a Special Issue entitled "Neural Coding". Copyright © 2011 Elsevier B.V. All rights reserved.

A Functional and Regulatory Network Associated with PIP Expression in Human Breast Cancer

PubMed Central

Debily, Marie-Anne; Marhomy, Sandrine El; Boulanger, Virginie; Eveno, Eric; Mariage-Samson, Régine; Camarca, Alessandra; Auffray, Charles; Piatier-Tonneau, Dominique; Imbeaud, Sandrine

2009-01-01

Background The PIP (prolactin-inducible protein) gene has been shown to be expressed in breast cancers, with contradictory results concerning its implication. As both the physiological role and the molecular pathways in which PIP is involved are poorly understood, we conducted combined gene expression profiling and network analysis studies on selected breast cancer cell lines presenting distinct PIP expression levels and hormonal receptor status, to explore the functional and regulatory network of PIP co-modulated genes. Principal Findings Microarray analysis allowed identification of genes co-modulated with PIP independently of modulations resulting from hormonal treatment or cell line heterogeneity. Relevant clusters of genes that can discriminate between [PIP+] and [PIP−] cells were identified. Functional and regulatory network analyses based on a knowledge database revealed a master network of PIP co-modulated genes, including many interconnecting oncogenes and tumor suppressor genes, half of which were detected as differentially expressed through high-precision measurements. The network identified appears associated with an inhibition of proliferation coupled with an increase of apoptosis and an enhancement of cell adhesion in breast cancer cell lines, and contains many genes with a STAT5 regulatory motif in their promoters. Conclusions Our global exploratory approach identified biological pathways modulated along with PIP expression, providing further support for its good prognostic value of disease-free survival in breast cancer. Moreover, our data pointed to the importance of a regulatory subnetwork associated with PIP expression in which STAT5 appears as a potential transcriptional regulator. PMID:19262752

Signed weighted gene co-expression network analysis of transcriptional regulation in murine embryonic stem cells

PubMed Central

Mason, Mike J; Fan, Guoping; Plath, Kathrin; Zhou, Qing; Horvath, Steve

2009-01-01

Background Recent work has revealed that a core group of transcription factors (TFs) regulates the key characteristics of embryonic stem (ES) cells: pluripotency and self-renewal. Current efforts focus on identifying genes that play important roles in maintaining pluripotency and self-renewal in ES cells and aim to understand the interactions among these genes. To that end, we investigated the use of unsigned and signed network analysis to identify pluripotency and differentiation related genes. Results We show that signed networks provide a better systems level understanding of the regulatory mechanisms of ES cells than unsigned networks, using two independent murine ES cell expression data sets. Specifically, using signed weighted gene co-expression network analysis (WGCNA), we found a pluripotency module and a differentiation module, which are not identified in unsigned networks. We confirmed the importance of these modules by incorporating genome-wide TF binding data for key ES cell regulators. Interestingly, we find that the pluripotency module is enriched with genes related to DNA damage repair and mitochondrial function in addition to transcriptional regulation. Using a connectivity measure of module membership, we not only identify known regulators of ES cells but also show that Mrpl15, Msh6, Nrf1, Nup133, Ppif, Rbpj, Sh3gl2, and Zfp39, among other genes, have important roles in maintaining ES cell pluripotency and self-renewal. We also report highly significant relationships between module membership and epigenetic modifications (histone modifications and promoter CpG methylation status), which are known to play a role in controlling gene expression during ES cell self-renewal and differentiation. Conclusion Our systems biologic re-analysis of gene expression, transcription factor binding, epigenetic and gene ontology data provides a novel integrative view of ES cell biology. PMID:19619308

Global Landscape of a Co-Expressed Gene Network in Barley and its Application to Gene Discovery in Triticeae Crops

PubMed Central

Mochida, Keiichi; Uehara-Yamaguchi, Yukiko; Yoshida, Takuhiro; Sakurai, Tetsuya; Shinozaki, Kazuo

2011-01-01

Accumulated transcriptome data can be used to investigate regulatory networks of genes involved in various biological systems. Co-expression analysis data sets generated from comprehensively collected transcriptome data sets now represent efficient resources that are capable of facilitating the discovery of genes with closely correlated expression patterns. In order to construct a co-expression network for barley, we analyzed 45 publicly available experimental series, which are composed of 1,347 sets of GeneChip data for barley. On the basis of a gene-to-gene weighted correlation coefficient, we constructed a global barley co-expression network and classified it into clusters of subnetwork modules. The resulting clusters are candidates for functional regulatory modules in the barley transcriptome. To annotate each of the modules, we performed comparative annotation using genes in Arabidopsis and Brachypodium distachyon. On the basis of a comparative analysis between barley and two model species, we investigated functional properties from the representative distributions of the gene ontology (GO) terms. Modules putatively involved in drought stress response and cellulose biogenesis have been identified. These modules are discussed to demonstrate the effectiveness of the co-expression analysis. Furthermore, we applied the data set of co-expressed genes coupled with comparative analysis in attempts to discover potentially Triticeae-specific network modules. These results demonstrate that analysis of the co-expression network of the barley transcriptome together with comparative analysis should promote the process of gene discovery in barley. Furthermore, the insights obtained should be transferable to investigations of Triticeae plants. The associated data set generated in this analysis is publicly accessible at http://coexpression.psc.riken.jp/barley/. PMID:21441235

Upgrade of an optical network unit in a 40 Gb/s time and wavelength-division multiplexed passive optical network using an upstream tunable colorless laser

NASA Astrophysics Data System (ADS)

Bindhaiq, Salem; Supa'at, Abu Sahmah M.; Zulkifli, Nadiatulhuda; Shaddad, Redhwan Q.; Mataria, Abdallah

2014-07-01

A high data transmission rate is the main requirement for next-generation telecommunication networks. A design for a 40 Gb/s time and wavelength-division multiplexed passive optical network (TWDM-PON) for next-generation passive optical network stage 2 is presented. The use of a modulated grating Y-branch (MG-Y) laser is proposed as an upstream tunable colorless laser source to upgrade the optical network unit. The electronically tuned MG-Y externally modulated laser with a 10 Gb/s modulation rate is applied to a TWDM-PON and presented across a 3.2-nm tuning range. The performance of the proposed laser is analyzed in terms of bit error rate, eye diagram, and optical signal-to-noise ratio. The proposed TWDM-PON achieved an aggregated data rate of 40 Gb/s along 40 km of bidirectional fiber at a 1:128 splitting ratio without amplification and dispersion compensation.

A Systems Approach Identifies Networks and Genes Linking Sleep and Stress: Implications for Neuropsychiatric Disorders

PubMed Central

Jiang, Peng; Scarpa, Joseph R.; Fitzpatrick, Karrie; Losic, Bojan; Gao, Vance D.; Hao, Ke; Summa, Keith C.; Yang, He S.; Zhang, Bin; Allada, Ravi; Vitaterna, Martha H.; Turek, Fred W.; Kasarskis, Andrew

2016-01-01

SUMMARY Sleep dysfunction and stress susceptibility are co-morbid complex traits, which often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multi-level organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J×A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests the interplay between sleep, stress, and neuropathology emerge from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework to interrogate the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders. PMID:25921536

Bidirectional control of absence seizures by the basal ganglia: a computational evidence.

PubMed

Chen, Mingming; Guo, Daqing; Wang, Tiebin; Jing, Wei; Xia, Yang; Xu, Peng; Luo, Cheng; Valdes-Sosa, Pedro A; Yao, Dezhong

2014-03-01

Absence epilepsy is believed to be associated with the abnormal interactions between the cerebral cortex and thalamus. Besides the direct coupling, anatomical evidence indicates that the cerebral cortex and thalamus also communicate indirectly through an important intermediate bridge-basal ganglia. It has been thus postulated that the basal ganglia might play key roles in the modulation of absence seizures, but the relevant biophysical mechanisms are still not completely established. Using a biophysically based model, we demonstrate here that the typical absence seizure activities can be controlled and modulated by the direct GABAergic projections from the substantia nigra pars reticulata (SNr) to either the thalamic reticular nucleus (TRN) or the specific relay nuclei (SRN) of thalamus, through different biophysical mechanisms. Under certain conditions, these two types of seizure control are observed to coexist in the same network. More importantly, due to the competition between the inhibitory SNr-TRN and SNr-SRN pathways, we find that both decreasing and increasing the activation of SNr neurons from the normal level may considerably suppress the generation of spike-and-slow wave discharges in the coexistence region. Overall, these results highlight the bidirectional functional roles of basal ganglia in controlling and modulating absence seizures, and might provide novel insights into the therapeutic treatments of this brain disorder.

Electrical Stimulation Modulates High γ Activity and Human Memory Performance

PubMed Central

Berry, Brent M.; Miller, Laura R.; Khadjevand, Fatemeh; Ezzyat, Youssef; Wanda, Paul; Sperling, Michael R.; Lega, Bradley; Stead, S. Matt

2018-01-01

Direct electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation in four brain regions known to support declarative memory: hippocampus (HP), parahippocampal region (PH) neocortex, prefrontal cortex (PF), and lateral temporal cortex (TC). Intracranial EEG recordings with stimulation were collected from 22 patients during performance of verbal memory tasks. We found that high γ (62–118 Hz) activity induced by word presentation was modulated by electrical stimulation. This modulatory effect was greatest for trials with “poor” memory encoding. The high γ modulation correlated with the behavioral effect of stimulation in a given brain region: it was negative, i.e., the induced high γ activity was decreased, in the regions where stimulation decreased memory performance, and positive in the lateral TC where memory enhancement was observed. Our results suggest that the effect of electrical stimulation on high γ activity induced by word presentation may be a useful biomarker for mapping memory networks and guiding therapeutic brain stimulation. PMID:29404403

Bidirectional Control of Absence Seizures by the Basal Ganglia: A Computational Evidence

PubMed Central

Wang, Tiebin; Jing, Wei; Xia, Yang; Xu, Peng; Luo, Cheng; Valdes-Sosa, Pedro A.; Yao, Dezhong

2014-01-01

Absence epilepsy is believed to be associated with the abnormal interactions between the cerebral cortex and thalamus. Besides the direct coupling, anatomical evidence indicates that the cerebral cortex and thalamus also communicate indirectly through an important intermediate bridge–basal ganglia. It has been thus postulated that the basal ganglia might play key roles in the modulation of absence seizures, but the relevant biophysical mechanisms are still not completely established. Using a biophysically based model, we demonstrate here that the typical absence seizure activities can be controlled and modulated by the direct GABAergic projections from the substantia nigra pars reticulata (SNr) to either the thalamic reticular nucleus (TRN) or the specific relay nuclei (SRN) of thalamus, through different biophysical mechanisms. Under certain conditions, these two types of seizure control are observed to coexist in the same network. More importantly, due to the competition between the inhibitory SNr-TRN and SNr-SRN pathways, we find that both decreasing and increasing the activation of SNr neurons from the normal level may considerably suppress the generation of spike-and-slow wave discharges in the coexistence region. Overall, these results highlight the bidirectional functional roles of basal ganglia in controlling and modulating absence seizures, and might provide novel insights into the therapeutic treatments of this brain disorder. PMID:24626189

Modular analysis of the probabilistic genetic interaction network.

PubMed

Hou, Lin; Wang, Lin; Qian, Minping; Li, Dong; Tang, Chao; Zhu, Yunping; Deng, Minghua; Li, Fangting

2011-03-15

Epistatic Miniarray Profiles (EMAP) has enabled the mapping of large-scale genetic interaction networks; however, the quantitative information gained from EMAP cannot be fully exploited since the data are usually interpreted as a discrete network based on an arbitrary hard threshold. To address such limitations, we adopted a mixture modeling procedure to construct a probabilistic genetic interaction network and then implemented a Bayesian approach to identify densely interacting modules in the probabilistic network. Mixture modeling has been demonstrated as an effective soft-threshold technique of EMAP measures. The Bayesian approach was applied to an EMAP dataset studying the early secretory pathway in Saccharomyces cerevisiae. Twenty-seven modules were identified, and 14 of those were enriched by gold standard functional gene sets. We also conducted a detailed comparison with state-of-the-art algorithms, hierarchical cluster and Markov clustering. The experimental results show that the Bayesian approach outperforms others in efficiently recovering biologically significant modules.

Design of a MIMD neural network processor

NASA Astrophysics Data System (ADS)

Saeks, Richard E.; Priddy, Kevin L.; Pap, Robert M.; Stowell, S.

1994-03-01

The Accurate Automation Corporation (AAC) neural network processor (NNP) module is a fully programmable multiple instruction multiple data (MIMD) parallel processor optimized for the implementation of neural networks. The AAC NNP design fully exploits the intrinsic sparseness of neural network topologies. Moreover, by using a MIMD parallel processing architecture one can update multiple neurons in parallel with efficiency approaching 100 percent as the size of the network increases. Each AAC NNP module has 8 K neurons and 32 K interconnections and is capable of 140,000,000 connections per second with an eight processor array capable of over one billion connections per second.

A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks.

PubMed

Gallos, Lazaros K; Makse, Hernán A; Sigman, Mariano

2012-02-21

The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are "large-world" self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the "strength of weak ties" crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain.

A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks

PubMed Central

Gallos, Lazaros K.; Makse, Hernán A.; Sigman, Mariano

2012-01-01

The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are “large-world” self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the “strength of weak ties” crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain. PMID:22308319

The psychedelic state induced by ayahuasca modulates the activity and connectivity of the default mode network.

PubMed

Palhano-Fontes, Fernanda; Andrade, Katia C; Tofoli, Luis F; Santos, Antonio C; Crippa, Jose Alexandre S; Hallak, Jaime E C; Ribeiro, Sidarta; de Araujo, Draulio B

2015-01-01

The experiences induced by psychedelics share a wide variety of subjective features, related to the complex changes in perception and cognition induced by this class of drugs. A remarkable increase in introspection is at the core of these altered states of consciousness. Self-oriented mental activity has been consistently linked to the Default Mode Network (DMN), a set of brain regions more active during rest than during the execution of a goal-directed task. Here we used fMRI technique to inspect the DMN during the psychedelic state induced by Ayahuasca in ten experienced subjects. Ayahuasca is a potion traditionally used by Amazonian Amerindians composed by a mixture of compounds that increase monoaminergic transmission. In particular, we examined whether Ayahuasca changes the activity and connectivity of the DMN and the connection between the DMN and the task-positive network (TPN). Ayahuasca caused a significant decrease in activity through most parts of the DMN, including its most consistent hubs: the Posterior Cingulate Cortex (PCC)/Precuneus and the medial Prefrontal Cortex (mPFC). Functional connectivity within the PCC/Precuneus decreased after Ayahuasca intake. No significant change was observed in the DMN-TPN orthogonality. Altogether, our results support the notion that the altered state of consciousness induced by Ayahuasca, like those induced by psilocybin (another serotonergic psychedelic), meditation and sleep, is linked to the modulation of the activity and the connectivity of the DMN.

Redox Regulation of Plant Development

PubMed Central

Considine, Michael J.

2014-01-01

Abstract Significance: We provide a conceptual framework for the interactions between the cellular redox signaling hub and the phytohormone signaling network that controls plant growth and development to maximize plant productivity under stress-free situations, while limiting growth and altering development on exposure to stress. Recent Advances: Enhanced cellular oxidation plays a key role in the regulation of plant growth and stress responses. Oxidative signals or cycles of oxidation and reduction are crucial for the alleviation of dormancy and quiescence, activating the cell cycle and triggering genetic and epigenetic control that underpin growth and differentiation responses to changing environmental conditions. Critical Issues: The redox signaling hub interfaces directly with the phytohormone network in the synergistic control of growth and its modulation in response to environmental stress, but a few components have been identified. Accumulating evidence points to a complex interplay of phytohormone and redox controls that operate at multiple levels. For simplicity, we focus here on redox-dependent processes that control root growth and development and bud burst. Future Directions: The multiple roles of reactive oxygen species in the control of plant growth and development have been identified, but increasing emphasis should now be placed on the functions of redox-regulated proteins, along with the central roles of reductants such as NAD(P)H, thioredoxins, glutathione, glutaredoxins, peroxiredoxins, ascorbate, and reduced ferredoxin in the regulation of the genetic and epigenetic factors that modulate the growth and vigor of crop plants, particularly within an agricultural context. Antioxid. Redox Signal. 21, 1305–1326. PMID:24180689

Identification of HDA15-PIF1 as a key repression module directing the transcriptional network of seed germination in the dark.

PubMed

Gu, Dachuan; Chen, Chia-Yang; Zhao, Minglei; Zhao, Linmao; Duan, Xuewu; Duan, Jun; Wu, Keqiang; Liu, Xuncheng

2017-07-07

Light is a major external factor in regulating seed germination. Photoreceptor phytochrome B (PHYB) plays a predominant role in promoting seed germination in the initial phase after imbibition, partially by repressing phytochrome-interacting factor1 (PIF1). However, the mechanism underlying the PHYB-PIF1-mediated transcription regulation remains largely unclear. Here, we identified that histone deacetylase15 (HDA15) is a negative component of PHYB-dependent seed germination. Overexpression of HDA15 in Arabidopsis inhibits PHYB-dependent seed germination, whereas loss of function of HDA15 increases PHYB-dependent seed germination. Genetic evidence indicated that HDA15 acts downstream of PHYB and represses seed germination dependent on PIF1. Furthermore, HDA15 interacts with PIF1 both in vitro and in vivo. Genome-wide transcriptome analysis revealed that HDA15 and PIF1 co-regulate the transcription of the light-responsive genes involved in multiple hormonal signaling pathways and cellular processes in germinating seeds in the dark. In addition, PIF1 recruits HDA15 to the promoter regions of target genes and represses their expression by decreasing the histone H3 acetylation levels in the dark. Taken together, our analysis uncovered the role of histone deacetylation in the light-regulated seed germination process and identified that HDA15-PIF1 acts as a key repression module directing the transcription network of seed germination. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of HDA15-PIF1 as a key repression module directing the transcriptional network of seed germination in the dark

PubMed Central

Gu, Dachuan; Chen, Chia-Yang; Zhao, Minglei; Zhao, Linmao; Duan, Xuewu

2017-01-01

Abstract Light is a major external factor in regulating seed germination. Photoreceptor phytochrome B (PHYB) plays a predominant role in promoting seed germination in the initial phase after imbibition, partially by repressing phytochrome-interacting factor1 (PIF1). However, the mechanism underlying the PHYB-PIF1-mediated transcription regulation remains largely unclear. Here, we identified that histone deacetylase15 (HDA15) is a negative component of PHYB-dependent seed germination. Overexpression of HDA15 in Arabidopsis inhibits PHYB-dependent seed germination, whereas loss of function of HDA15 increases PHYB-dependent seed germination. Genetic evidence indicated that HDA15 acts downstream of PHYB and represses seed germination dependent on PIF1. Furthermore, HDA15 interacts with PIF1 both in vitro and in vivo. Genome-wide transcriptome analysis revealed that HDA15 and PIF1 co-regulate the transcription of the light-responsive genes involved in multiple hormonal signaling pathways and cellular processes in germinating seeds in the dark. In addition, PIF1 recruits HDA15 to the promoter regions of target genes and represses their expression by decreasing the histone H3 acetylation levels in the dark. Taken together, our analysis uncovered the role of histone deacetylation in the light-regulated seed germination process and identified that HDA15-PIF1 acts as a key repression module directing the transcription network of seed germination. PMID:28444370

Upstream capacity upgrade in TDM-PON using RSOA based tunable fiber ring laser.

PubMed

Yi, Lilin; Li, Zhengxuan; Dong, Yi; Xiao, Shilin; Chen, Jian; Hu, Weisheng

2012-04-23

An upstream multi-wavelength shared (UMWS) time division multiplexing passive optical network (TDM-PON) is presented by using a reflective semiconductor amplifier (RSOA) and tunable optical filter (TOF) based directly modulated fiber ring laser as upstream laser source. The stable laser operation is easily achieved no matter what the bandwidth and shape of the TOF is and it can be directly modulated when the RSOA is driven at its saturation region. In this UMWS TDM-PON system, an individual wavelength can be assigned to the user who has a high bandwidth demand by tuning the central wavelength of the TOF in its upgraded optical network unit (ONU), while others maintain their traditional ONU structure and share the bandwidth via time slots, which greatly and dynamically upgrades the upstream capacity. We experimentally demonstrated the bidirectional transmission of downstream data at 10-Gb/s and upstream data at 1.25-Gb/s per wavelength over 25-km single mode fiber (SMF) with almost no power penalty at both ends. A stable performance is observed for the upstream wavelength tuned from 1530 nm to 1595 nm. Moreover, due to the high extinction ratio (ER) of the upstream signal, the burst-mode transmitting is successfully presented and a better time-division multiplexing performance can be obtained by turning off the unused lasers thanks to the rapid formation of the laser in the fiber ring. © 2012 Optical Society of America

Autonomic Intelligent Cyber Sensor to Support Industrial Control Network Awareness

DOE PAGES

Vollmer, Todd; Manic, Milos; Linda, Ondrej

2013-06-01

The proliferation of digital devices in a networked industrial ecosystem, along with an exponential growth in complexity and scope, has resulted in elevated security concerns and management complexity issues. This paper describes a novel architecture utilizing concepts of Autonomic computing and a SOAP based IF-MAP external communication layer to create a network security sensor. This approach simplifies integration of legacy software and supports a secure, scalable, self-managed framework. The contribution of this paper is two-fold: 1) A flexible two level communication layer based on Autonomic computing and Service Oriented Architecture is detailed and 2) Three complementary modules that dynamically reconfiguremore » in response to a changing environment are presented. One module utilizes clustering and fuzzy logic to monitor traffic for abnormal behavior. Another module passively monitors network traffic and deploys deceptive virtual network hosts. These components of the sensor system were implemented in C++ and PERL and utilize a common internal D-Bus communication mechanism. A proof of concept prototype was deployed on a mixed-use test network showing the possible real world applicability. In testing, 45 of the 46 network attached devices were recognized and 10 of the 12 emulated devices were created with specific Operating System and port configurations. Additionally the anomaly detection algorithm achieved a 99.9% recognition rate. All output from the modules were correctly distributed using the common communication structure.« less

Construction of local gene network for revealing different liver function of rats fed deep-fried oil with or without resistant starch.

PubMed

Wang, Zhiwei; Liao, Tianqi; Zhou, Zhongkai; Wang, Yuyang; Diao, Yongjia; Strappe, Padraig; Prenzler, Paul; Ayton, Jamie; Blanchard, Chris

2016-09-06

To study the mechanism underlying the liver damage induced by deep-fried oil (DO) consumption and the beneficial effects from resistant starch (RS) supplement, differential gene expression and pathway network were analyzed based on RNA sequencing data from rats. The up/down regulated genes and corresponding signaling pathways were used to construct a novel local gene network (LGN). The topology of the network showed characteristics of small-world network, with some pathways demonstrating a high degree. Some changes in genes led to a larger probability occurrence of disease or infection with DO intake. More importantly, the main pathways were found to be almost the same between the two LGNs (30 pathways overlapped in total 48) with gene expression profile. This finding may indicate that RS supplement in DO-containing diet may mainly regulate the genes that related to DO damage, and RS in the diet may provide direct signals to the liver cells and modulate its effect through a network involving complex gene regulatory events. It is the first attempt to reveal the mechanism of the attenuation of liver dysfunction from RS supplement in the DO-containing diet using differential gene expression and pathway network. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Exploration and Modulation of Brain Network Interactions with Noninvasive Brain Stimulation in Combination with Neuroimaging

PubMed Central

Shafi, Mouhsin M.; Westover, M. Brandon; Fox, Michael D.; Pascual-Leone, Alvaro

2012-01-01

Much recent work in systems neuroscience has focused on how dynamic interactions between different cortical regions underlie complex brain functions such as motor coordination, language, and emotional regulation. Various studies using neuroimaging and neurophysiologic techniques have suggested that in many neuropsychiatric disorders, these dynamic brain networks are dysregulated. Here we review the utility of combined noninvasive brain stimulation and neuroimaging approaches towards greater understanding of dynamic brain networks in health and disease. Brain stimulation techniques, such as transcranial magnetic stimulation and transcranial direct current stimulation, use electromagnetic principles to noninvasively alter brain activity, and induce focal but also network effects beyond the stimulation site. When combined with brain imaging techniques such as functional MRI, PET and EEG, these brain stimulation techniques enable a causal assessment of the interaction between different network components, and their respective functional roles. The same techniques can also be applied to explore hypotheses regarding the changes in functional connectivity that occur during task performance and in various disease states such as stroke, depression and schizophrenia. Finally, in diseases characterized by pathologic alterations in either the excitability within a single region or in the activity of distributed networks, such techniques provide a potential mechanism to alter cortical network function and architectures in a beneficial manner. PMID:22429242

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

PubMed

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

2010-10-25

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

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

PubMed

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

2013-05-01

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

Subgenual anterior cingulate cortex controls sadness-induced modulations of cognitive and emotional network hubs.

PubMed

Ramirez-Mahaluf, Juan P; Perramon, Joan; Otal, Begonya; Villoslada, Pablo; Compte, Albert

2018-06-04

The regulation of cognitive and emotional processes is critical for proper executive functions and social behavior, but its specific mechanisms remain unknown. Here, we addressed this issue by studying with functional magnetic resonance imaging the changes in network topology that underlie competitive interactions between emotional and cognitive networks in healthy participants. Our behavioral paradigm contrasted periods with high emotional and cognitive demands by including a sadness provocation task followed by a spatial working memory task. The sharp contrast between successive tasks was designed to enhance the separability of emotional and cognitive networks and reveal areas that regulate the flow of information between them (hubs). By applying graph analysis methods on functional connectivity between 20 regions of interest in 22 participants we identified two main brain network modules, one dorsal and one ventral, and their hub areas: the left dorsolateral prefrontal cortex (dlPFC) and the left medial frontal pole (mFP). These hub areas did not modulate their mutual functional connectivity following sadness but they did so through an interposed area, the subgenual anterior cingulate cortex (sACC). Our results identify dlPFC and mFP as areas regulating interactions between emotional and cognitive networks, and suggest that their modulation by sadness experience is mediated by sACC.

Striatal GABA-MRS predicts response inhibition performance and its cortical electrophysiological correlates.

PubMed

Quetscher, Clara; Yildiz, Ali; Dharmadhikari, Shalmali; Glaubitz, Benjamin; Schmidt-Wilcke, Tobias; Dydak, Ulrike; Beste, Christian

2015-11-01

Response inhibition processes are important for performance monitoring and are mediated via a network constituted by different cortical areas and basal ganglia nuclei. At the basal ganglia level, striatal GABAergic medium spiny neurons are known to be important for response selection, but the importance of the striatal GABAergic system for response inhibition processes remains elusive. Using a novel combination of behavior al, EEG and magnetic resonance spectroscopy (MRS) data, we examine the relevance of the striatal GABAergic system for response inhibition processes. The study shows that striatal GABA levels modulate the efficacy of response inhibition processes. Higher striatal GABA levels were related to better response inhibition performance. We show that striatal GABA modulate specific subprocesses of response inhibition related to pre-motor inhibitory processes through the modulation of neuronal synchronization processes. To our knowledge, this is the first study providing direct evidence for the relevance of the striatal GABAergic system for response inhibition functions and their cortical electrophysiological correlates in humans.

Emotional Intent Modulates The Neural Substrates Of Creativity: An fMRI Study of Emotionally Targeted Improvisation in Jazz Musicians

PubMed Central

McPherson, Malinda J.; Barrett, Frederick S.; Lopez-Gonzalez, Monica; Jiradejvong, Patpong; Limb, Charles J.

2016-01-01

Emotion is a primary motivator for creative behaviors, yet the interaction between the neural systems involved in creativity and those involved in emotion has not been studied. In the current study, we addressed this gap by using fMRI to examine piano improvisation in response to emotional cues. We showed twelve professional jazz pianists photographs of an actress representing a positive, negative or ambiguous emotion. Using a non-ferromagnetic thirty-five key keyboard, the pianists improvised music that they felt represented the emotion expressed in the photographs. Here we show that activity in prefrontal and other brain networks involved in creativity is highly modulated by emotional context. Furthermore, emotional intent directly modulated functional connectivity of limbic and paralimbic areas such as the amygdala and insula. These findings suggest that emotion and creativity are tightly linked, and that the neural mechanisms underlying creativity may depend on emotional state. PMID:26725925

Synthesizing a novel genetic sequential logic circuit: a push-on push-off switch

PubMed Central

Lou, Chunbo; Liu, Xili; Ni, Ming; Huang, Yiqi; Huang, Qiushi; Huang, Longwen; Jiang, Lingli; Lu, Dan; Wang, Mingcong; Liu, Chang; Chen, Daizhuo; Chen, Chongyi; Chen, Xiaoyue; Yang, Le; Ma, Haisu; Chen, Jianguo; Ouyang, Qi

2010-01-01

Design and synthesis of basic functional circuits are the fundamental tasks of synthetic biologists. Before it is possible to engineer higher-order genetic networks that can perform complex functions, a toolkit of basic devices must be developed. Among those devices, sequential logic circuits are expected to be the foundation of the genetic information-processing systems. In this study, we report the design and construction of a genetic sequential logic circuit in Escherichia coli. It can generate different outputs in response to the same input signal on the basis of its internal state, and ‘memorize' the output. The circuit is composed of two parts: (1) a bistable switch memory module and (2) a double-repressed promoter NOR gate module. The two modules were individually rationally designed, and they were coupled together by fine-tuning the interconnecting parts through directed evolution. After fine-tuning, the circuit could be repeatedly, alternatively triggered by the same input signal; it functions as a push-on push-off switch. PMID:20212522

Synthesizing a novel genetic sequential logic circuit: a push-on push-off switch.

PubMed

Lou, Chunbo; Liu, Xili; Ni, Ming; Huang, Yiqi; Huang, Qiushi; Huang, Longwen; Jiang, Lingli; Lu, Dan; Wang, Mingcong; Liu, Chang; Chen, Daizhuo; Chen, Chongyi; Chen, Xiaoyue; Yang, Le; Ma, Haisu; Chen, Jianguo; Ouyang, Qi

2010-01-01

Design and synthesis of basic functional circuits are the fundamental tasks of synthetic biologists. Before it is possible to engineer higher-order genetic networks that can perform complex functions, a toolkit of basic devices must be developed. Among those devices, sequential logic circuits are expected to be the foundation of the genetic information-processing systems. In this study, we report the design and construction of a genetic sequential logic circuit in Escherichia coli. It can generate different outputs in response to the same input signal on the basis of its internal state, and 'memorize' the output. The circuit is composed of two parts: (1) a bistable switch memory module and (2) a double-repressed promoter NOR gate module. The two modules were individually rationally designed, and they were coupled together by fine-tuning the interconnecting parts through directed evolution. After fine-tuning, the circuit could be repeatedly, alternatively triggered by the same input signal; it functions as a push-on push-off switch.

Short-term PV/T module temperature prediction based on PCA-RBF neural network

NASA Astrophysics Data System (ADS)

Li, Jiyong; Zhao, Zhendong; Li, Yisheng; Xiao, Jing; Tang, Yunfeng

2018-02-01

Aiming at the non-linearity and large inertia of temperature control in PV/T system, short-term temperature prediction of PV/T module is proposed, to make the PV/T system controller run forward according to the short-term forecasting situation to optimize control effect. Based on the analysis of the correlation between PV/T module temperature and meteorological factors, and the temperature of adjacent time series, the principal component analysis (PCA) method is used to pre-process the original input sample data. Combined with the RBF neural network theory, the simulation results show that the PCA method makes the prediction accuracy of the network model higher and the generalization performance stronger than that of the RBF neural network without the main component extraction.

Understanding and predicting binding between human leukocyte antigens (HLAs) and peptides by network analysis.

PubMed

Luo, Heng; Ye, Hao; Ng, Hui; Shi, Leming; Tong, Weida; Mattes, William; Mendrick, Donna; Hong, Huixiao

2015-01-01

As the major histocompatibility complex (MHC), human leukocyte antigens (HLAs) are one of the most polymorphic genes in humans. Patients carrying certain HLA alleles may develop adverse drug reactions (ADRs) after taking specific drugs. Peptides play an important role in HLA related ADRs as they are the necessary co-binders of HLAs with drugs. Many experimental data have been generated for understanding HLA-peptide binding. However, efficiently utilizing the data for understanding and accurately predicting HLA-peptide binding is challenging. Therefore, we developed a network analysis based method to understand and predict HLA-peptide binding. Qualitative Class I HLA-peptide binding data were harvested and prepared from four major databases. An HLA-peptide binding network was constructed from this dataset and modules were identified by the fast greedy modularity optimization algorithm. To examine the significance of signals in the yielded models, the modularity was compared with the modularity values generated from 1,000 random networks. The peptides and HLAs in the modules were characterized by similarity analysis. The neighbor-edges based and unbiased leverage algorithm (Nebula) was developed for predicting HLA-peptide binding. Leave-one-out (LOO) validations and two-fold cross-validations were conducted to evaluate the performance of Nebula using the constructed HLA-peptide binding network. Nine modules were identified from analyzing the HLA-peptide binding network with a highest modularity compared to all the random networks. Peptide length and functional side chains of amino acids at certain positions of the peptides were different among the modules. HLA sequences were module dependent to some extent. Nebula archived an overall prediction accuracy of 0.816 in the LOO validations and average accuracy of 0.795 in the two-fold cross-validations and outperformed the method reported in the literature. Network analysis is a useful approach for analyzing large and sparse datasets such as the HLA-peptide binding dataset. The modules identified from the network analysis clustered peptides and HLAs with similar sequences and properties of amino acids. Nebula performed well in the predictions of HLA-peptide binding. We demonstrated that network analysis coupled with Nebula is an efficient approach to understand and predict HLA-peptide binding interactions and thus, could further our understanding of ADRs.

Understanding and predicting binding between human leukocyte antigens (HLAs) and peptides by network analysis

PubMed Central

2015-01-01

Background As the major histocompatibility complex (MHC), human leukocyte antigens (HLAs) are one of the most polymorphic genes in humans. Patients carrying certain HLA alleles may develop adverse drug reactions (ADRs) after taking specific drugs. Peptides play an important role in HLA related ADRs as they are the necessary co-binders of HLAs with drugs. Many experimental data have been generated for understanding HLA-peptide binding. However, efficiently utilizing the data for understanding and accurately predicting HLA-peptide binding is challenging. Therefore, we developed a network analysis based method to understand and predict HLA-peptide binding. Methods Qualitative Class I HLA-peptide binding data were harvested and prepared from four major databases. An HLA-peptide binding network was constructed from this dataset and modules were identified by the fast greedy modularity optimization algorithm. To examine the significance of signals in the yielded models, the modularity was compared with the modularity values generated from 1,000 random networks. The peptides and HLAs in the modules were characterized by similarity analysis. The neighbor-edges based and unbiased leverage algorithm (Nebula) was developed for predicting HLA-peptide binding. Leave-one-out (LOO) validations and two-fold cross-validations were conducted to evaluate the performance of Nebula using the constructed HLA-peptide binding network. Results Nine modules were identified from analyzing the HLA-peptide binding network with a highest modularity compared to all the random networks. Peptide length and functional side chains of amino acids at certain positions of the peptides were different among the modules. HLA sequences were module dependent to some extent. Nebula archived an overall prediction accuracy of 0.816 in the LOO validations and average accuracy of 0.795 in the two-fold cross-validations and outperformed the method reported in the literature. Conclusions Network analysis is a useful approach for analyzing large and sparse datasets such as the HLA-peptide binding dataset. The modules identified from the network analysis clustered peptides and HLAs with similar sequences and properties of amino acids. Nebula performed well in the predictions of HLA-peptide binding. We demonstrated that network analysis coupled with Nebula is an efficient approach to understand and predict HLA-peptide binding interactions and thus, could further our understanding of ADRs. PMID:26424483

Effects of Modulation Techniques (Manchester Code, NRZ or RZ) on the Operation of Hybrid WDM/TDM Passive Optical Networks

PubMed Central

Nyachionjeka, Kumbirayi

2014-01-01

In this paper, the performance and feasibility of a hybrid wavelength division multiplexing/time division multiplexing passive optical network (WDM/TDM PON) system with 128 optical network units (ONUs) is analysed. In this system, triple play services (video, voice and data) are successfully communicated through a distance of up to 28 km. Moreover, we analysed and compared the performance of various modulation formats for different distances in the proposed hybrid WDM/TDM PON. NRZ rectangular emerged as the most appropriate modulation format for triple play transmission in the proposed hybrid PON. PMID:27382633

Functional connectivity of default mode network components: correlation, anticorrelation, and causality

PubMed Central

Uddin, Lucina Q.; Clare Kelly, A. M.; Biswal, Bharat B.; Castellanos, F. Xavier; Milham, Michael P.

2013-01-01

The default mode network (DMN), based in ventromedial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC), exhibits higher metabolic activity at rest than during performance of externally-oriented cognitive tasks. Recent studies have suggested that competitive relationships between the DMN and various task-positive networks involved in task performance are intrinsically represented in the brain in the form of strong negative correlations (anticorrelations) between spontaneous fluctuations in these networks. Most neuroimaging studies characterize the DMN as a homogenous network, thus few have examined the differential contributions of DMN components to such competitive relationships. Here we examined functional differentiation within the default mode network, with an emphasis on understanding competitive relationships between this and other networks. We used a seed correlation approach on resting-state data to assess differences in functional connectivity between these two regions and their anticorrelated networks. While the positively correlated networks for the vmPFC and PCC seeds largely overlapped, the anticorrelated networks for each showed striking differences. Activity in vmPFC negatively predicted activity in parietal visual spatial and temporal attention networks, whereas activity in PCC negatively predicted activity in prefrontal-based motor control circuits. Granger causality analyses suggest that vmPFC and PCC exert greater influence on their anticorrelated networks than the other way around, suggesting that these two default mode nodes may directly modulate activity in task-positive networks. Thus, the two major nodes comprising the default mode network are differentiated with respect to the specific brain systems with which they interact, suggesting greater heterogeneity within this network than is commonly appreciated. PMID:18219617

All-optical virtual private network system in OFDM based long-reach PON using RSOA re-modulation technique

NASA Astrophysics Data System (ADS)

Kim, Chang-Hun; Jung, Sang-Min; Kang, Su-Min; Han, Sang-Kook

2015-01-01

We propose an all-optical virtual private network (VPN) system in an orthogonal frequency division multiplexing (OFDM) based long reach PON (LR-PON). In the optical access network field, technologies based on fundamental upstream (U/S) and downstream (D/S) have been actively researched to accommodate explosion of data capacity. However, data transmission among the end users which is arisen from cloud computing, file-sharing and interactive game takes a large weight inside of internet traffic. Moreover, this traffic is predicted to increase more if Internet of Things (IoT) services are activated. In a conventional PON, VPN data is transmitted through ONU-OLT-ONU via U/S and D/S carriers. It leads to waste of bandwidth and energy due to O-E-O conversion in the OLT and round-trip propagation between OLT and remote node (RN). Also, it causes inevitable load to the OLT for electrical buffer, scheduling and routing. The network inefficiency becomes more critical in a LR-PON which has been researched as an effort to reduce CAPEX and OPEX through metro-access consolidation. In the proposed system, the VPN data is separated from conventional U/S and re-modulated on the D/S carrier by using RSOA in the ONUs to avoid bandwidth consumption of U/S and D/S unlike in previously reported system. Moreover, the transmitted VPN data is re-directed to the ONUs by wavelength selective reflector device in the RN without passing through the OLT. Experimental demonstration for the VPN communication system in an OFDM based LR-PON has been verified.

A modular neural network scheme applied to fault diagnosis in electric power systems.

PubMed

Flores, Agustín; Quiles, Eduardo; García, Emilio; Morant, Francisco; Correcher, Antonio

2014-01-01

This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.

A Modular Neural Network Scheme Applied to Fault Diagnosis in Electric Power Systems

PubMed Central

Flores, Agustín; Morant, Francisco

2014-01-01

This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system. PMID:25610897