All-fiber optical mode switching based on cascaded mode selective couplers for short-reach MDM networks

Science.gov (United States)

Ren, Fang; Li, Juhao; Wu, Zhongying; Yu, Jinyi; Mo, Qi; Wang, Jianping; He, Yongqi; Chen, Zhangyuan; Li, Zhengbin

2017-04-01

We propose and experimentally demonstrate an all-fiber optical mode switching structure supporting independent switching, exchanging, adding, and dropping functionalities in which each mode can be switched individually. The mode switching structure consists of cascaded mode selective couplers (MSCs) capable of exciting and selecting specific higher order modes in few-mode fibers with high efficiency and one multiport optical switch routing the independent spatial modes to their destinations. The data carried on three different spatial modes can be switched, exchanged, added, and dropped through this all-fiber structure. For this experimental demonstration, optical on-off-keying (OOK) signals at 10-Gb/s carried on three spatial modes are successfully processed with open and clear eye diagrams. The mode switch exhibits power penalties of less than 3.1 dB after through operation, less than 2.7 dB after exchange operation, less than 2.8 dB after switching operation, and less than 1.6 dB after mode adding and dropping operations at the bit-error rate (BER) of 10-3, while all three channels carried on three spatial modes are simultaneously routed. The proposed structure, compatible with current optical switching networks based on single-mode fibers, can potentially be used to expand the switching scalability in advanced and flexible short-reach mode-division multiplexing-based networks.

Default mode network links to visual hallucinations: A comparison between Parkinson's disease and multiple system atrophy.

Science.gov (United States)

Franciotti, Raffaella; Delli Pizzi, Stefano; Perfetti, Bernardo; Tartaro, Armando; Bonanni, Laura; Thomas, Astrid; Weis, Luca; Biundo, Roberta; Antonini, Angelo; Onofrj, Marco

2015-08-01

Studying default mode network activity or connectivity in different parkinsonisms, with or without visual hallucinations, could highlight its roles in clinical phenotypes' expression. Multiple system atrophy is the archetype of parkinsonism without visual hallucinations, variably appearing instead in Parkinson's disease (PD). We aimed to evaluate default mode network functions in multiple system atrophy in comparison with PD. Functional magnetic resonance imaging evaluated default mode network activity and connectivity in 15 multiple system atrophy patients, 15 healthy controls, 15 early PD patients matched for disease duration, 30 severe PD patients (15 with and 15 without visual hallucinations), matched with multiple system atrophy for disease severity. Cortical thickness and neuropsychological evaluations were also performed. Multiple system atrophy had reduced default mode network activity compared with controls and PD with hallucinations, and no differences with PD (early or severe) without hallucinations. In PD with visual hallucinations, activity and connectivity was preserved compared with controls and higher than in other groups. In early PD, connectivity was lower than in controls but higher than in multiple system atrophy and severe PD without hallucinations. Cortical thickness was reduced in severe PD, with and without hallucinations, and correlated only with disease duration. Higher anxiety scores were found in patients without hallucinations. Default mode network activity and connectivity was higher in PD with visual hallucinations and reduced in multiple system atrophy and PD without visual hallucinations. Cortical thickness comparisons suggest that functional, rather than structural, changes underlie the activity and connectivity differences. © 2015 International Parkinson and Movement Disorder Society.

Default mode network abnormalities in posttraumatic stress disorder: A novel network-restricted topology approach.

Science.gov (United States)

Akiki, Teddy J; Averill, Christopher L; Wrocklage, Kristen M; Scott, J Cobb; Averill, Lynnette A; Schweinsburg, Brian; Alexander-Bloch, Aaron; Martini, Brenda; Southwick, Steven M; Krystal, John H; Abdallah, Chadi G

2018-08-01

Disruption in the default mode network (DMN) has been implicated in numerous neuropsychiatric disorders, including posttraumatic stress disorder (PTSD). However, studies have largely been limited to seed-based methods and involved inconsistent definitions of the DMN. Recent advances in neuroimaging and graph theory now permit the systematic exploration of intrinsic brain networks. In this study, we used resting-state functional magnetic resonance imaging (fMRI), diffusion MRI, and graph theoretical analyses to systematically examine the DMN connectivity and its relationship with PTSD symptom severity in a cohort of 65 combat-exposed US Veterans. We employed metrics that index overall connectivity strength, network integration (global efficiency), and network segregation (clustering coefficient). Then, we conducted a modularity and network-based statistical analysis to identify DMN regions of particular importance in PTSD. Finally, structural connectivity analyses were used to probe whether white matter abnormalities are associated with the identified functional DMN changes. We found decreased DMN functional connectivity strength to be associated with increased PTSD symptom severity. Further topological characterization suggests decreased functional integration and increased segregation in subjects with severe PTSD. Modularity analyses suggest a spared connectivity in the posterior DMN community (posterior cingulate, precuneus, angular gyrus) despite overall DMN weakened connections with increasing PTSD severity. Edge-wise network-based statistical analyses revealed a prefrontal dysconnectivity. Analysis of the diffusion networks revealed no alterations in overall strength or prefrontal structural connectivity. DMN abnormalities in patients with severe PTSD symptoms are characterized by decreased overall interconnections. On a finer scale, we found a pattern of prefrontal dysconnectivity, but increased cohesiveness in the posterior DMN community and relative sparing

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

Science.gov (United States)

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

2017-12-01

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

Hypnosis, suggestion, and suggestibility: an integrative model.

Science.gov (United States)

Lynn, Steven Jay; Laurence, Jean-Roch; Kirsch, Irving

2015-01-01

This article elucidates an integrative model of hypnosis that integrates social, cultural, cognitive, and neurophysiological variables at play both in and out of hypnosis and considers their dynamic interaction as determinants of the multifaceted experience of hypnosis. The roles of these variables are examined in the induction and suggestion stages of hypnosis, including how they are related to the experience of involuntariness, one of the hallmarks of hypnosis. It is suggested that studies of the modification of hypnotic suggestibility; cognitive flexibility; response sets and expectancies; the default-mode network; and the search for the neurophysiological correlates of hypnosis, more broadly, in conjunction with research on social psychological variables, hold much promise to further understanding of hypnosis.

Tunable deformation modes shape contractility in active biopolymer networks

Science.gov (United States)

Stam, Samantha; Banerjee, Shiladitya; Weirich, Kim; Freedman, Simon; Dinner, Aaron; Gardel, Margaret

Biological polymer-based materials remodel under active, molecular motor-driven forces to perform diverse physiological roles, such as force transmission and spatial self-organization. Critical to understanding these biomaterials is elucidating the role of microscopic polymer deformations, such as stretching, bending, buckling, and relative sliding, on material remodeling. Here, we report that the shape of motor-driven deformations can be used to identify microscopic deformation modes and determine how they propagate to longer length scales. In cross-linked actin networks with sufficiently low densities of the motor protein myosin II, microscopic network deformations are predominantly uniaxial, or dominated by sliding. However, longer-wavelength modes are mostly biaxial, or dominated by bending and buckling, indicating that deformations with uniaxial shapes do not propagate across length scales significantly larger than that of individual polymers. As the density of myosin II is increased, biaxial modes dominate on all length scales we examine due to buildup of sufficient stress to produce smaller-wavelength buckling. In contrast, when we construct networks from unipolar, rigid actin bundles, we observe uniaxial, sliding-based contractions on 1 to 100 μm length scales. Our results demonstrate the biopolymer mechanics can be used to tune deformation modes which, in turn, control shape changes in active materials.

Adaptive Global Sliding Mode Control for MEMS Gyroscope Using RBF Neural Network

Directory of Open Access Journals (Sweden)

Yundi Chu

2015-01-01

Full Text Available An adaptive global sliding mode control (AGSMC using RBF neural network (RBFNN is proposed for the system identification and tracking control of micro-electro-mechanical system (MEMS gyroscope. Firstly, a new kind of adaptive identification method based on the global sliding mode controller is designed to update and estimate angular velocity and other system parameters of MEMS gyroscope online. Moreover, the output of adaptive neural network control is used to adjust the switch gain of sliding mode control dynamically to approach the upper bound of unknown disturbances. In this way, the switch item of sliding mode control can be converted to the output of continuous neural network which can weaken the chattering in the sliding mode control in contrast to the conventional fixed gain sliding mode control. Simulation results show that the designed control system can get satisfactory tracking performance and effective estimation of unknown parameters of MEMS gyroscope.

Experimental demonstration of time- and mode-division multiplexed passive optical network

Science.gov (United States)

Ren, Fang; Li, Juhao; Tang, Ruizhi; Hu, Tao; Yu, Jinyi; Mo, Qi; He, Yongqi; Chen, Zhangyuan; Li, Zhengbin

2017-07-01

A time- and mode-division multiplexed passive optical network (TMDM-PON) architecture is proposed, in which each optical network unit (ONU) communicates with the optical line terminal (OLT) independently utilizing both different time slots and switched optical linearly polarized (LP) spatial modes. Combination of a mode multiplexer/demultiplexer (MUX/DEUX) and a simple N × 1 optical switch is employed to select the specific LP mode in each ONU. A mode-insensitive power splitter is used for signal broadcast/combination between OLT and ONUs. We theoretically propose a dynamic mode and time slot assignment scheme for TMDM-PON based on inter-ONU priority rating, in which the time delay and packet loss ratio's variation tendency are investigated by simulation. Moreover, we experimentally demonstrate 2-mode TMDM-PON transmission over 10 km FMF with 10-Gb/s on-off keying (OOK) signal and direct detection.

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

International Nuclear Information System (INIS)

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

2015-01-01

Type 2 diabetes mellitus is associated with increased risk for dementia. Patients with impaired cognition often show default-mode network disruption. We aimed to investigate the integrity of a default-mode network in diabetic patients by using independent component analysis, and to explore the relationship between network abnormalities, neurocognitive performance and diabetic variables. Forty-two patients with type 2 diabetes and 42 well-matched healthy controls were included and underwent resting-state functional MRI in a 3 Tesla unit. Independent component analysis was adopted to extract the default-mode network, including its anterior and posterior components. Z-maps of both sub-networks were compared between the two groups and correlated with each clinical variable. Patients showed increased connectivity around the medial prefrontal cortex in the anterior sub-network, but decreased connectivity around the posterior cingulate cortex in the posterior sub-network. The decreased connectivity in the posterior part was significantly correlated with the score on Complex Figure Test-delay recall test (r = 0.359, p = 0.020), the time spent on Trail-Making Test-part B (r = -0.346, p = 0.025) and the insulin resistance level (r = -0.404, p = 0.024). Dissociation pattern in the default-mode network was found in diabetic patients, which might provide powerful new insights into the neural mechanisms that underlie the diabetes-related cognitive decline. (orig.)

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

Energy Technology Data Exchange (ETDEWEB)

Cui, Ying; Jiao, Yun; Chen, Hua-Jun; Ding, Jie; Luo, Bing; Peng, Cheng-Yu; Ju, Sheng-Hong; Teng, Gao-Jun [Medical School of Southeast University, Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Nanjing, Jiangsu (China)

2015-11-15

Type 2 diabetes mellitus is associated with increased risk for dementia. Patients with impaired cognition often show default-mode network disruption. We aimed to investigate the integrity of a default-mode network in diabetic patients by using independent component analysis, and to explore the relationship between network abnormalities, neurocognitive performance and diabetic variables. Forty-two patients with type 2 diabetes and 42 well-matched healthy controls were included and underwent resting-state functional MRI in a 3 Tesla unit. Independent component analysis was adopted to extract the default-mode network, including its anterior and posterior components. Z-maps of both sub-networks were compared between the two groups and correlated with each clinical variable. Patients showed increased connectivity around the medial prefrontal cortex in the anterior sub-network, but decreased connectivity around the posterior cingulate cortex in the posterior sub-network. The decreased connectivity in the posterior part was significantly correlated with the score on Complex Figure Test-delay recall test (r = 0.359, p = 0.020), the time spent on Trail-Making Test-part B (r = -0.346, p = 0.025) and the insulin resistance level (r = -0.404, p = 0.024). Dissociation pattern in the default-mode network was found in diabetic patients, which might provide powerful new insights into the neural mechanisms that underlie the diabetes-related cognitive decline. (orig.)

Modeling the interdependent network based on two-mode networks

Science.gov (United States)

An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian

2017-10-01

Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.

Dynamics of coupled mode solitons in bursting neural networks

Science.gov (United States)

Nfor, N. Oma; Ghomsi, P. Guemkam; Moukam Kakmeni, F. M.

2018-02-01

Using an electrically coupled chain of Hindmarsh-Rose neural models, we analytically derived the nonlinearly coupled complex Ginzburg-Landau equations. This is realized by superimposing the lower and upper cutoff modes of wave propagation and by employing the multiple scale expansions in the semidiscrete approximation. We explore the modified Hirota method to analytically obtain the bright-bright pulse soliton solutions of our nonlinearly coupled equations. With these bright solitons as initial conditions of our numerical scheme, and knowing that electrical signals are the basis of information transfer in the nervous system, it is found that prior to collisions at the boundaries of the network, neural information is purely conveyed by bisolitons at lower cutoff mode. After collision, the bisolitons are completely annihilated and neural information is now relayed by the upper cutoff mode via the propagation of plane waves. It is also shown that the linear gain of the system is inextricably linked to the complex physiological mechanisms of ion mobility, since the speeds and spatial profiles of the coupled nerve impulses vary with the gain. A linear stability analysis performed on the coupled system mainly confirms the instability of plane waves in the neural network, with a glaring example of the transition of weak plane waves into a dark soliton and then static kinks. Numerical simulations have confirmed the annihilation phenomenon subsequent to collision in neural systems. They equally showed that the symmetry breaking of the pulse solution of the system leaves in the network static internal modes, sometime referred to as Goldstone modes.

Altered default mode network activity in patient with anxiety disorders: An fMRI study

International Nuclear Information System (INIS)

Zhao Xiaohu; Wang Peijun; Li Chunbo; Hu Zhenghui; Xi Qian; Wu Wenyuan; Tang Xiaowei

2007-01-01

Anxiety disorder, a common mental disorder in our clinical practice, is characterized by unprovoked anxiety. Medial prefrontal cortex (MPFC) and posterior cingulate cortex (PCC), which closely involved in emotional processing, are critical regions in the default mode network. We used functional magnetic resonance imaging (fMRI) to investigate whether default mode network activity is altered in patients with anxiety disorder. Ten anxiety patients and 10 healthy controls underwent fMRI while listening to emotionally neutral words alternating with rest (Experiment 1) and threat-related words alternating with emotionally neutral words (Experiment 2). In Experiment 1, regions of deactivation were observed in patients and controls. In Experiment 2, regions of deactivation were observed only in patients. The observed deactivation patterns in the two experiments, which included MPFC, PCC, and inferior parietal cortex, were similar and consistent with the default model network. Less deactivation in MPFC and greater deactivation in PCC were observed for patients group comparing to controls in Experiment 1. Our observations suggest that the default model network is altered in anxiety patients and dysfunction in MPFC and PCC may play an important role in anxiety psychopathology

Synchronization of uncertain time-varying network based on sliding mode control technique

Science.gov (United States)

Lü, Ling; Li, Chengren; Bai, Suyuan; Li, Gang; Rong, Tingting; Gao, Yan; Yan, Zhe

2017-09-01

We research synchronization of uncertain time-varying network based on sliding mode control technique. The sliding mode control technique is first modified so that it can be applied to network synchronization. Further, by choosing the appropriate sliding surface, the identification law of uncertain parameter, the adaptive law of the time-varying coupling matrix element and the control input of network are designed, it is sure that the uncertain time-varying network can synchronize effectively the synchronization target. At last, we perform some numerical simulations to demonstrate the effectiveness of the proposed results.

Emotional faces and the default mode network.

Science.gov (United States)

Sreenivas, S; Boehm, S G; Linden, D E J

2012-01-11

The default-mode network (DMN) of the human brain has become a central topic of cognitive neuroscience research. Although alterations in its resting state activity and in its recruitment during tasks have been reported for several mental and neurodegenerative disorders, its role in emotion processing has received relatively little attention. We investigated brain responses to different categories of emotional faces with functional magnetic resonance imaging (fMRI) and found deactivation in ventromedial prefrontal cortex (VMPFC), posterior cingulate gyrus (PC) and cuneus. This deactivation was modulated by emotional category and was less prominent for happy than for sad faces. These deactivated areas along the midline conformed to areas of the DMN. We also observed emotion-dependent deactivation of the left middle frontal gyrus, which is not a classical component of the DMN. Conversely, several areas in a fronto-parietal network commonly linked with attention were differentially activated by emotion categories. Functional connectivity patterns, as obtained by correlation of activation levels, also varied between emotions. VMPFC, PC or cuneus served as hubs between the DMN-type areas and the fronto-parietal network. These data support recent suggestions that the DMN is not a unitary system but differentiates according to task and even type of stimulus. The emotion-specific differential pattern of DMN deactivation may be explored further in patients with mood disorder, where the quest for biological markers of emotional biases is still ongoing. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Dual-mode ultraflow access networks: a hybrid solution for the access bottleneck

Science.gov (United States)

Kazovsky, Leonid G.; Shen, Thomas Shunrong; Dhaini, Ahmad R.; Yin, Shuang; De Leenheer, Marc; Detwiler, Benjamin A.

2013-12-01

Optical Flow Switching (OFS) is a promising solution for large Internet data transfers. In this paper, we introduce UltraFlow Access, a novel optical access network architecture that offers dual-mode service to its end-users: IP and OFS. With UltraFlow Access, we design and implement a new dual-mode control plane and a new dual-mode network stack to ensure efficient connection setup and reliable and optimal data transmission. We study the impact of the UltraFlow system's design on the network throughput. Our experimental results show that with an optimized system design, near optimal (around 10 Gb/s) OFS data throughput can be attained when the line rate is 10Gb/s.

INTEGRAL INDEX OF OPERATION QUALITY FOR EVALUATION OF IMPACT OF DISTRIBUTIVE GENERATION SOURCES ON ELECTRIC NETWORK MODES

Directory of Open Access Journals (Sweden)

Petro D. Lezhniuk

2017-06-01

Full Text Available Method of operation quality evaluation of electric network, comprising renewable sources of energy (RSE is considered. Integral index that enables to evaluate the impact of RSE on energy losses and its quality as well as balance reliability in electric network is suggested. Mathematical model is constructed, taking into account the assumption that electric network with RSE may be in various operation modes, characterized by different technical economic indices. To determine the integral index of operation quality of electric network with RSE in all possible states tools of Markov processes theory and criterial method are used.

Acupuncture mobilizes the brain's default mode and its anti-correlated network in healthy subjects.

Science.gov (United States)

Hui, Kathleen K S; Marina, Ovidiu; Claunch, Joshua D; Nixon, Erika E; Fang, Jiliang; Liu, Jing; Li, Ming; Napadow, Vitaly; Vangel, Mark; Makris, Nikos; Chan, Suk-Tak; Kwong, Kenneth K; Rosen, Bruce R

2009-09-01

Previous work has shown that acupuncture stimulation evokes deactivation of a limbic-paralimbic-neocortical network (LPNN) as well as activation of somatosensory brain regions. This study explores the activity and functional connectivity of these regions during acupuncture vs. tactile stimulation and vs. acupuncture associated with inadvertent sharp pain. Acupuncture during 201 scans and tactile stimulation during 74 scans for comparison at acupoints LI4, ST36 and LV3 was monitored with fMRI and psychophysical response in 48 healthy subjects. Clusters of deactivated regions in the medial prefrontal, medial parietal and medial temporal lobes as well as activated regions in the sensorimotor and a few paralimbic structures can be identified during acupuncture by general linear model analysis and seed-based cross correlation analysis. Importantly, these clusters showed virtual identity with the default mode network and the anti-correlated task-positive network in response to stimulation. In addition, the amygdala and hypothalamus, structures not routinely reported in the default mode literature, were frequently involved in acupuncture. When acupuncture induced sharp pain, the deactivation was attenuated or became activated instead. Tactile stimulation induced greater activation of the somatosensory regions but less extensive deactivation of the LPNN. These results indicate that the deactivation of the LPNN during acupuncture cannot be completely explained by the demand of attention that is commonly proposed in the default mode literature. Our results suggest that acupuncture mobilizes the anti-correlated functional networks of the brain to mediate its actions, and that the effect is dependent on the psychophysical response.

Default mode network segregation and social deficits in autism spectrum disorder: Evidence from non-medicated children.

Science.gov (United States)

Yerys, Benjamin E; Gordon, Evan M; Abrams, Danielle N; Satterthwaite, Theodore D; Weinblatt, Rachel; Jankowski, Kathryn F; Strang, John; Kenworthy, Lauren; Gaillard, William D; Vaidya, Chandan J

2015-01-01

Functional pathology of the default mode network is posited to be central to social-cognitive impairment in autism spectrum disorders (ASD). Altered functional connectivity of the default mode network's midline core may be a potential endophenotype for social deficits in ASD. Generalizability from prior studies is limited by inclusion of medicated participants and by methods favoring restricted examination of network function. This study measured resting-state functional connectivity in 22 8-13 year-old non-medicated children with ASD and 22 typically developing controls using seed-based and network segregation functional connectivity methods. Relative to controls the ASD group showed both under- and over-functional connectivity within default mode and non-default mode regions, respectively. ASD symptoms correlated negatively with the connection strength of the default mode midline core-medial prefrontal cortex-posterior cingulate cortex. Network segregation analysis with the participation coefficient showed a higher area under the curve for the ASD group. Our findings demonstrate that the default mode network in ASD shows a pattern of poor segregation with both functional connectivity metrics. This study confirms the potential for the functional connection of the midline core as an endophenotype for social deficits. Poor segregation of the default mode network is consistent with an excitation/inhibition imbalance model of ASD.

Random sampling of elementary flux modes in large-scale metabolic networks.

Science.gov (United States)

Machado, Daniel; Soons, Zita; Patil, Kiran Raosaheb; Ferreira, Eugénio C; Rocha, Isabel

2012-09-15

The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set. Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks. Source code for a cross-platform implementation in Python is freely available at http://code.google.com/p/emsampler. dmachado@deb.uminho.pt Supplementary data are available at Bioinformatics online.

Gamification of learning deactivates the Default Mode Network

Directory of Open Access Journals (Sweden)

Paul Alexander Howard-Jones

2016-01-01

Full Text Available We hypothesised that embedding educational learning in a game would improve learning outcomes, with increased engagement and recruitment of cognitive resources evidenced by increased activation of working memory network (WMN and deactivation of Default Mode Network (DMN regions. In an fMRI study, we compared activity during periods of learning in three conditions that were increasingly game-like: Study-only (when periods of learning were followed by an exemplar question together with its correct answer, Self-quizzing (when periods of learning were followed by a multiple choice question in return for a fixed number of points and Game-based (when, following each period of learning, participants competed with a peer to answer the question for escalating, uncertain rewards. DMN hubs deactivated as conditions became more game-like, alongside greater self-reported engagement and, in the Game-based condition, higher learning scores. These changes did not occur with any detectable increase in WMN activity. Additionally, ventral striatal activation was associated with responding to questions and receiving positive question feedback. Results support the significance of DMN deactivation for educational learning, and are aligned with recent evidence suggesting DMN and WMN activity may not always be anti-correlated.

Gamification of Learning Deactivates the Default Mode Network.

Science.gov (United States)

Howard-Jones, Paul A; Jay, Tim; Mason, Alice; Jones, Harvey

2015-01-01

We hypothesized that embedding educational learning in a game would improve learning outcomes, with increased engagement and recruitment of cognitive resources evidenced by increased activation of working memory network (WMN) and deactivation of default mode network (DMN) regions. In an fMRI study, we compared activity during periods of learning in three conditions that were increasingly game-like: Study-only (when periods of learning were followed by an exemplar question together with its correct answer), Self-quizzing (when periods of learning were followed by a multiple choice question in return for a fixed number of points) and Game-based (when, following each period of learning, participants competed with a peer to answer the question for escalating, uncertain rewards). DMN hubs deactivated as conditions became more game-like, alongside greater self-reported engagement and, in the Game-based condition, higher learning scores. These changes did not occur with any detectable increase in WMN activity. Additionally, ventral striatal activation was associated with responding to questions and receiving positive question feedback. Results support the significance of DMN deactivation for educational learning, and are aligned with recent evidence suggesting DMN and WMN activity may not always be anti-correlated.

Modifications in resting state functional anticorrelation between default mode network and dorsal attention network: comparison among young adults, healthy elders and mild cognitive impairment patients.

Science.gov (United States)

Esposito, Roberto; Cieri, Filippo; Chiacchiaretta, Piero; Cera, Nicoletta; Lauriola, Mariella; Di Giannantonio, Massimo; Tartaro, Armando; Ferretti, Antonio

2018-02-01

Resting state brain activity incorporates different components, including the Default Mode Network and the Dorsal Attention Network, also known as task-negative network and task-positive network respectively. These two networks typically show an anticorrelated activity during both spontaneous oscillations and task execution. However modifications of this anticorrelated activity pattern with age and pathology are still unclear. The present study aimed to investigate differences in resting state Default Mode Network-Dorsal Attention Network functional anticorrelation among young adults, healthy elders and Mild Cognitive Impairment patients. We retrospectively enrolled in this study 27 healthy young adults (age range: 25-35 y.o.; mean age: 28,5), 26 healthy elders (age range: 61-72 y.o.; mean age: 65,1) and 17 MCI patients (age range 64-87 y.o.; mean age: 73,6). Mild Cognitive Impairment patients were selected following Petersen criteria. All participants underwent neuropsychological evaluation and resting state functional Magnetic Resonance Imaging. Spontaneous anticorrelated activity between Default Mode Network and Dorsal Attention Network was observed in each group. This anticorrelation was significantly decreased with age in most Default Mode Network-Dorsal Attention Network connections (p Default Mode Network and the right inferior parietal sulcus node of the Dorsal Attention Network was significantly decreased when comparing Mild Cognitive Impairment with normal elders (p Default Mode Network and Dorsal Attention Network is part of the normal aging process and that Mild Cognitive Impairment status is associated with more evident inter-networks functional connectivity changes.

Reduced salience and default mode network activity in women with anorexia nervosa

Science.gov (United States)

McFadden, Kristina L.; Tregellas, Jason R.; Shott, Megan E.; Frank, Guido K.W.

2014-01-01

Background The neurobiology of anorexia nervosa is poorly understood. Neuronal networks contributing to action selection, self-regulation and interoception could contribute to pathologic eating and body perception in people with anorexia nervosa. We tested the hypothesis that the salience network (SN) and default mode network (DMN) would show decreased intrinsic activity in women with anorexia nervosa and those who had recovered from the disease compared to controls. The basal ganglia (BGN) and sensorimotor networks (SMN) were also investigated. Methods Between January 2008 and January 2012, women with restricting-type anorexia nervosa, women who recovered from the disease and healthy control women completed functional magnetic resonance imaging during a conditioned stimulus task. Network activity was studied using independent component analysis. Results We studied 20 women with anorexia nervosa, 24 recovered women and 24 controls. Salience network activity in the anterior cingulate cortex was reduced in women with anorexia nervosa (p = 0.030; all results false-discovery rate–corrected) and recovered women (p = 0.039) compared to controls. Default mode network activity in the precuneus was reduced in women with anorexia compared to controls (p = 0.023). Sensorimotor network activity in the supplementary motor area (SMA; p = 0.008), and the left (p = 0.028) and right (p = 0.002) postcentral gyrus was reduced in women with anorexia compared to controls; SMN activity in the SMA (p = 0.019) and the right postcentral gyrus (p = 0.008) was reduced in women with anorexia compared to recovered women. There were no group differences in the BGN. Limitations Differences between patient and control populations (e.g., depression, anxiety, medication) are potential confounds, but were included as covariates. Conclusion Reduced SN activity in women with anorexia nervosa and recovered women could be a trait-related biomarker or illness remnant, altering the drive to approach

NETWORK-CENTRIC TECHNOLOGIES FOR CONTROL OF THREE-PHASE NETWORK OPERATION MODES

Directory of Open Access Journals (Sweden)

Ye. I. Sokol

2017-06-01

Full Text Available Purpose. The development of the control system for three-phase network is based on intelligent technologies of network-centric control of heterogeneous objects. The introduction of unmanned aerial vehicles for monitoring of three-phase network increases the efficiency of management. Methodology. The case of decomposition of the instantaneous capacities of the fixed and variable components for 3-wire system. The features of power balance for the different modes of its functioning. It should be noted that symmetric sinusoidal mode is balanced and good, but really unbalanced, if the standard reactive power is not zero. To solve the problem of compensation is sufficient knowledge of the total value of the inactive components of full power (value of the inactive power without detail. The creation of a methodology of measurement and assessment will require knowledge of the magnitudes of each inactive component separately, which leads to the development of a unified approach to the measurement and compensation of inactive components of full power and the development of a generalized theory of power. Results. Procedure for the compensation of the current of zero sequence excludes from circuit the source, as the active component of instantaneous power of zero sequence, and a vector due to a current of zero sequence. This procedure is performed without time delay as it does not require integration. Only a 3–wire system with symmetrical voltage eliminates pulsations and symmetrization of the equivalent conductances of the phases of the task. Under asymmetric voltage, the power is different, its analysis requires the creation of a vector mathematical model of the energy processes of asymmetrical modes of 3–phase systems. Originality. The proposed method extends the basis of the vector method for any zero sequence voltages and shows that the various theories of instantaneous power three wired scheme due to the choice of a basis in a two

Cortical morphometry in frontoparietal and default mode networks in math-gifted adolescents.

Science.gov (United States)

Navas-Sánchez, Francisco J; Carmona, Susana; Alemán-Gómez, Yasser; Sánchez-González, Javier; Guzmán-de-Villoria, Juan; Franco, Carolina; Robles, Olalla; Arango, Celso; Desco, Manuel

2016-05-01

Math-gifted subjects are characterized by above-age performance in intelligence tests, exceptional creativity, and high task commitment. Neuroimaging studies reveal enhanced functional brain organization and white matter microstructure in the frontoparietal executive network of math-gifted individuals. However, the cortical morphometry of these subjects remains largely unknown. The main goal of this study was to compare the cortical morphometry of math-gifted adolescents with that of an age- and IQ-matched control group. We used surface-based methods to perform a vertex-wise analysis of cortical thickness and surface area. Our results show that math-gifted adolescents present a thinner cortex and a larger surface area in key regions of the frontoparietal and default mode networks, which are involved in executive processing and creative thinking, respectively. The combination of reduced cortical thickness and larger surface area suggests above-age neural maturation of these networks in math-gifted individuals. Hum Brain Mapp 37:1893-1902, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Logistics Mode and Network Planning for Recycle of Crop Straw Resources

OpenAIRE

Zhou, Lingyun; Gu, Weidong; Zhang, Qing

2013-01-01

To realize the straw biomass industrialized development, it should speed up building crop straw resource recycle logistics network, increasing straw recycle efficiency, and reducing straw utilization cost. On the basis of studying straw recycle process, this paper presents innovative concept and property of straw recycle logistics network, analyses design thinking of straw recycle logistics network, and works out straw recycle logistics mode and network topological structure. Finally, it come...

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

Science.gov (United States)

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

2013-07-30

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

On mode selection and power control for uplink D2D communication in cellular networks

KAUST Repository

Ali, Konpal S.

2015-06-08

Device-to-device (D2D) communication enables users lying in close proximity to bypass the cellular base station (BS) and transmit to one another directly. This offloads traffic from the cellular network, improves spatial frequency reuse and energy efficiency in the network. We present a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with two different flexible mode-selection schemes. The power-control cutoff thresholds of the two communication modes have been decoupled unlike past work on the subject. We find that for a given network, an optimal value exists not only for the biased mode selection criterion, but also for r, the ratio of the power-control cutoff thresholds of the two communication modes, which maximizes spatial spectral efficiency. Also, r turns out to be a more robust parameter for optimizing network performance. Further, it is shown that the second scheme, which prioritizes spatial frequency reuse over the per-user achievable performance compared to the first scheme, achieves almost the same overall network performance; thereby trading per user performance to serve a larger number of users.

On mode selection and power control for uplink D2D communication in cellular networks

KAUST Repository

Ali, Konpal S.; Elsawy, Hesham; Alouini, Mohamed-Slim

2015-01-01

Device-to-device (D2D) communication enables users lying in close proximity to bypass the cellular base station (BS) and transmit to one another directly. This offloads traffic from the cellular network, improves spatial frequency reuse and energy efficiency in the network. We present a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with two different flexible mode-selection schemes. The power-control cutoff thresholds of the two communication modes have been decoupled unlike past work on the subject. We find that for a given network, an optimal value exists not only for the biased mode selection criterion, but also for r, the ratio of the power-control cutoff thresholds of the two communication modes, which maximizes spatial spectral efficiency. Also, r turns out to be a more robust parameter for optimizing network performance. Further, it is shown that the second scheme, which prioritizes spatial frequency reuse over the per-user achievable performance compared to the first scheme, achieves almost the same overall network performance; thereby trading per user performance to serve a larger number of users.

Analysis of Few-Mode Multi-Core Fiber Splice Behavior Using an Optical Vector Network Analyzer

DEFF Research Database (Denmark)

Rommel, Simon; Mendinueta, Jose Manuel Delgado; Klaus, Werner

2017-01-01

The behavior of splices in a 3-mode 36-core fiber is analyzed using optical vector network analysis. Time-domain response analysis confirms splices may cause significant mode-mixing, while frequency-domain analysis shows splices may affect system level mode-dependent loss both positively and negativ......The behavior of splices in a 3-mode 36-core fiber is analyzed using optical vector network analysis. Time-domain response analysis confirms splices may cause significant mode-mixing, while frequency-domain analysis shows splices may affect system level mode-dependent loss both positively...

Affective network and default mode network in depressive adolescents with disruptive behaviors

Directory of Open Access Journals (Sweden)

Kim SM

2015-12-01

Full Text Available Sun Mi Kim,1 Sung Yong Park,1 Young In Kim,1 Young Don Son,2 Un-Sun Chung,3,4 Kyung Joon Min,1 Doug Hyun Han1 1Department of Psychiatry, School of Medicine, Chung-Ang University, Seoul, 2Department of Biomedical Engineering, Gachon University of Medicine and Science, Incheon, 3Department of Psychiatry, School of Medicine, Kyungpook National University, 4School Mental Health Resources and Research Center, Kyungpook National University Children’s Hospital, Daegu, South Korea Aim: Disruptive behaviors are thought to affect the progress of major depressive disorder (MDD in adolescents. In resting-state functional connectivity (RSFC studies of MDD, the affective network (limbic network and the default mode network (DMN have garnered a great deal of interest. We aimed to investigate RSFC in a sample of treatment-naïve adolescents with MDD and disruptive behaviors.Methods: Twenty-two adolescents with MDD and disruptive behaviors (disrup-MDD and 20 age- and sex-matched healthy control (HC participants underwent resting-state functional magnetic resonance imaging (fMRI. We used a seed-based correlation approach concerning two brain circuits including the affective network and the DMN, with two seed regions ­including the bilateral amygdala for the limbic network and the bilateral posterior cingulate cortex (PCC for the DMN. We also observed a correlation between RSFC and severity of depressive symptoms and disruptive behaviors.Results: The disrup-MDD participants showed lower RSFC from the amygdala to the orbitofrontal cortex and parahippocampal gyrus compared to HC participants. Depression scores in disrup-MDD participants were negatively correlated with RSFC from the amygdala to the right orbitofrontal cortex. The disrup-MDD participants had higher PCC RSFC compared to HC participants in a cluster that included the left precentral gyrus, left insula, and left parietal lobe. Disruptive behavior scores in disrup-MDD patients were positively

Real-time identification of vehicle motion-modes using neural networks

Science.gov (United States)

Wang, Lifu; Zhang, Nong; Du, Haiping

2015-01-01

A four-wheel ground vehicle has three body-dominated motion-modes, that is, bounce, roll, and pitch motion-modes. Real-time identification of these motion-modes can make vehicle suspensions, in particular, active suspensions, target on the dominant motion-mode and apply appropriate control strategies to improve its performance with less power consumption. Recently, a motion-mode energy method (MEM) was developed to identify the vehicle body motion-modes. However, this method requires the measurement of full vehicle states and road inputs, which are not always available in practice. This paper proposes an alternative approach to identify vehicle primary motion-modes with acceptable accuracy by employing neural networks (NNs). The effectiveness of the trained NNs is verified on a 10-DOF full-car model under various types of excitation inputs. The results confirm that the proposed method is effective in determining vehicle primary motion-modes with comparable accuracy to the MEM method. Experimental data is further used to validate the proposed method.

Default mode network interference in mild traumatic brain injury - a pilot resting state study.

Science.gov (United States)

Sours, Chandler; Zhuo, Jiachen; Janowich, Jacqueline; Aarabi, Bizhan; Shanmuganathan, Kathirkamanthan; Gullapalli, Rao P

2013-11-06

In this study we investigated the functional connectivity in 23 Mild TBI (mTBI) patients with and without memory complaints using resting state fMRI in the sub-acute stage of injury as well as a group of control participants. Results indicate that mTBI patients with memory complaints performed significantly worse than patients without memory complaints on tests assessing memory from the Automated Neuropsychological Assessment Metrics (ANAM). Altered functional connectivity was observed between the three groups between the default mode network (DMN) and the nodes of the task positive network (TPN). Altered functional connectivity was also observed between both the TPN and DMN and nodes associated with the Salience Network (SN). Following mTBI there is a reduction in anti-correlated networks for both those with and without memory complaints for the DMN, but only a reduction in the anti-correlated network in mTBI patients with memory complaints for the TPN. Furthermore, an increased functional connectivity between the TPN and SN appears to be associated with reduced performance on memory assessments. Overall the results suggest that a disruption in the segregation of the DMN and the TPN at rest may be mediated through both a direct pathway of increased FC between various nodes of the TPN and DMN, and through an indirect pathway that links the TPN and DMN through nodes of the SN. This disruption between networks may cause a detrimental impact on memory functioning following mTBI, supporting the Default Mode Interference Hypothesis in the context of mTBI related memory deficits. © 2013 Elsevier B.V. All rights reserved.

Default-mode-like network activation in awake rodents.

Directory of Open Access Journals (Sweden)

Jaymin Upadhyay

Full Text Available During wakefulness and in absence of performing tasks or sensory processing, the default-mode network (DMN, an intrinsic central nervous system (CNS network, is in an active state. Non-human primate and human CNS imaging studies have identified the DMN in these two species. Clinical imaging studies have shown that the pattern of activity within the DMN is often modulated in various disease states (e.g., Alzheimer's, schizophrenia or chronic pain. However, whether the DMN exists in awake rodents has not been characterized. The current data provides evidence that awake rodents also possess 'DMN-like' functional connectivity, but only subsequent to habituation to what is initially a novel magnetic resonance imaging (MRI environment as well as physical restraint. Specifically, the habituation process spanned across four separate scanning sessions (Day 2, 4, 6 and 8. At Day 8, significant (p<0.05 functional connectivity was observed amongst structures such as the anterior cingulate (seed region, retrosplenial, parietal, and hippocampal cortices. Prior to habituation (Day 2, functional connectivity was only detected (p<0.05 amongst CNS structures known to mediate anxiety (i.e., anterior cingulate (seed region, posterior hypothalamic area, amygdala and parabracial nucleus. In relating functional connectivity between cingulate-default-mode and cingulate-anxiety structures across Days 2-8, a significant inverse relationship (r = -0.65, p = 0.0004 was observed between these two functional interactions such that increased cingulate-DMN connectivity corresponded to decreased cingulate anxiety network connectivity. This investigation demonstrates that the cingulate is an important component of both the rodent DMN-like and anxiety networks.

Knowledge Management in the Network Mode: The Case of Private Equity

Directory of Open Access Journals (Sweden)

Britta Klagge

2012-01-01

Full Text Available There has been an ongoing debate on the changing geographical organization of the financial sector and the decreasing importance of regional financial centres. Our contribution explores a fresh perspective on this issue by looking at knowledge and risk management in different parts of the financial sector with an empirical focus on private equity in Germany. The argument we put forward is that the ways in which providers of finance manage knowledge and risk shape their organizational and geographical structure. In our analytical framework we distinguish between three ideal-type modes of knowledge management: the relationship, the data and the network mode. These modes differ in the types of knowledge exchanged, the actors involved and in the role and nature of relevant contacts and relationships. The shift from relationship to data mode in credit provision in Germany serves an example of how a new mode of knowledge management is associated with changes in the geographical organization of financial actors and activities. To illustrate the network mode we then focus on knowledge management in private equity in Germany, which involves a variety of different actors and links both regional and interregional networks. Our empirical research shows that the resulting organizational and geographical struc¬tures are rather complex and have nodes in regional financial centres. While these centres benefit from private equity activities, their chances for re-vitalization and a re-regionalization of financial expertise on the basis of private equity are nonetheless limited. So far, Munich seems to be the (only one location where private equity – cross-fertilized by other local financial actors – has initiated a self-supported development which strengthens Munich as a financial centre.

Default Mode Network Interference in Mild Traumatic Brain Injury – A Pilot Resting State Study

Science.gov (United States)

Sours, Chandler; Zhuo, Jiachen; Janowich, Jacqueline; Aarabi, Bizhan; Shanmuganathan, Kathirkamanthan; Gullapalli, Rao P

2013-01-01

In this study we investigated the functional connectivity in 23 Mild TBI (mTBI) patients with and without memory complaints using resting state fMRI in the sub-acute stage of injury as well as a group of control participants. Results indicate that mTBI patients with memory complaints performed significantly worse than patients without memory complaints on tests assessing memory from the Automated Neuropsychological Assessment Metrics (ANAM). Altered functional connectivity was observed between the three groups between the default mode network (DMN) and the nodes of the task positive network (TPN). Altered functional connectivity was also observed between both the TPN and DMN and nodes associated with the Salience Network (SN). Following mTBI there is a reduction in anti-correlated networks for both those with and without memory complaints for the DMN, but only a reduction in the anti-correlated network in mTBI patients with memory complaints for the TPN. Furthermore, an increased functional connectivity between the TPN and SN appears to be associated with reduced performance on memory assessments. Overall the results suggest that a disruption in the segregation of the DMN and the TPN at rest may be mediated through both a direct pathway of increased FC between various nodes of the TPN and DMN, and through an indirect pathway that links the TPN and DMN through nodes of the SN. This disruption between networks may cause a detrimental impact on memory functioning following mTBI, supporting the Default Mode Interference Hypothesis in the context of mTBI related memory deficits. PMID:23994210

Friend suggestion in social network based on user log

Science.gov (United States)

Kaviya, R.; Vanitha, M.; Sumaiya Thaseen, I.; Mangaiyarkarasi, R.

2017-11-01

Simple friend recommendation algorithms such as similarity, popularity and social aspects is the basic requirement to be explored to methodically form high-performance social friend recommendation. Suggestion of friends is followed. No tags of character were followed. In the proposed system, we use an algorithm for network correlation-based social friend recommendation (NC-based SFR).It includes user activities like where one lives and works. A new friend recommendation method, based on network correlation, by considering the effect of different social roles. To model the correlation between different networks, we develop a method that aligns these networks through important feature selection. We consider by preserving the network structure for a more better recommendations so that it significantly improves the accuracy for better friend-recommendation.

Holding-based network of nations based on listed energy companies: An empirical study on two-mode affiliation network of two sets of actors

Science.gov (United States)

Li, Huajiao; Fang, Wei; An, Haizhong; Gao, Xiangyun; Yan, Lili

2016-05-01

Economic networks in the real world are not homogeneous; therefore, it is important to study economic networks with heterogeneous nodes and edges to simulate a real network more precisely. In this paper, we present an empirical study of the one-mode derivative holding-based network constructed by the two-mode affiliation network of two sets of actors using the data of worldwide listed energy companies and their shareholders. First, we identify the primitive relationship in the two-mode affiliation network of the two sets of actors. Then, we present the method used to construct the derivative network based on the shareholding relationship between two sets of actors and the affiliation relationship between actors and events. After constructing the derivative network, we analyze different topological features on the node level, edge level and entire network level and explain the meanings of the different values of the topological features combining the empirical data. This study is helpful for expanding the usage of complex networks to heterogeneous economic networks. For empirical research on the worldwide listed energy stock market, this study is useful for discovering the inner relationships between the nations and regions from a new perspective.

Neural Network Substorm Identification: Enabling TREx Sensor Web Modes

Science.gov (United States)

Chaddock, D.; Spanswick, E.; Arnason, K. M.; Donovan, E.; Liang, J.; Ahmad, S.; Jackel, B. J.

2017-12-01

Transition Region Explorer (TREx) is a ground-based sensor web of optical and radio instruments that is presently being deployed across central Canada. The project consists of an array of co-located blue-line, full-colour, and near-infrared all-sky imagers, imaging riometers, proton aurora spectrographs, and GNSS systems. A key goal of the TREx project is to create the world's first (artificial) intelligent sensor web for remote sensing space weather. The sensor web will autonomously control and coordinate instrument operations in real-time. To accomplish this, we will use real-time in-line analytics of TREx and other data to dynamically switch between operational modes. An operating mode could be, for example, to have a blue-line imager gather data at a one or two orders of magnitude higher cadence than it operates for its `baseline' mode. The software decision to increase the imaging cadence would be in response to an anticipated increase in auroral activity or other programmatic requirements. Our first test for TREx's sensor web technologies is to develop the capacity to autonomously alter the TREx operating mode prior to a substorm expansion phase onset. In this paper, we present our neural network analysis of historical optical and riometer data and our ability to predict an optical onset. We explore the preliminary insights into using a neural network to pick out trends and features which it deems are similar among substorms.

Interaction of acupuncture treatment and manipulation laterality modulated by the default mode network.

Science.gov (United States)

Niu, Xuan; Zhang, Ming; Liu, Zhenyu; Bai, Lijun; Sun, Chuanzhu; Wang, Shan; Wang, Xiaocui; Chen, Zhen; Chen, Hongyan; Tian, Jie

2017-01-01

Appropriate selection of ipsilateral or contralateral electroacupuncture (corresponding to the pain site) plays an important role in reaching its better curative effect; however, the involving brain mechanism still remains unclear. Compared with the heat pain model generally established in previous study, capsaicin pain model induces reversible cutaneous allodynia and is proved to be better simulating aspects of clinical nociceptive and neuropathic pain. In the current study, 24 subjects were randomly divided into two groups with a 2 × 2 factorial design: laterality (ipsi- or contralateral side, inter-subject) × treatment with counter-balanced at an interval of one week (verum and placebo electroacupuncture, within-subject). We observed subjective pain intensity and brain activations changes induced by capsaicin allodynia pain stimuli before and after electroacupuncture treatment at acupoint LI4 for 30 min. Analysis of variance results indicated that ipsilateral electroacupuncture treatment produced significant pain relief and wide brain signal suppressions in pain-related brain areas compared with contralateral electroacupuncture. We also found that verum electroacupuncture at either ipsi- or contralateral side to the pain site exhibited comparable significant magnitudes of analgesic effect. By contrast, placebo electroacupuncture elicited significant pain reductions only on the ipsilateral rather than contralateral side. It was inferred that placebo analgesia maybe attenuated on the region of the body (opposite to pain site) where attention was less focused, suggesting that analgesic effect of placebo electroacupuncture mainly rely on the motivation of its spatial-specific placebo responses via attention mechanism. This inference can be further supported by the evidence that the significant interaction effect of manipulation laterality and treatment was exclusively located within the default mode network, including the bilateral superior parietal

Activation of the occipital cortex and deactivation of the default mode network during working memory in the early blind.

Science.gov (United States)

Park, Hae-Jeong; Chun, Ji-Won; Park, Bumhee; Park, Haeil; Kim, Joong Il; Lee, Jong Doo; Kim, Jae-Jin

2011-05-01

Although blind people heavily depend on working memory to manage daily life without visual information, it is not clear yet whether their working memory processing involves functional reorganization of the memory-related cortical network. To explore functional reorganization of the cortical network that supports various types of working memory processes in the early blind, we investigated activation differences between 2-back tasks and 0-back tasks using fMRI in 10 congenitally blind subjects and 10 sighted subjects. We used three types of stimulus sequences: words for a verbal task, pitches for a non-verbal task, and sound locations for a spatial task. When compared to the sighted, the blind showed additional activations in the occipital lobe for all types of stimulus sequences for working memory and more significant deactivation in the posterior cingulate cortex of the default mode network. The blind had increased effective connectivity from the default mode network to the left parieto-frontal network and from the occipital cortex to the right parieto-frontal network during the 2-back tasks than the 0-back tasks. These findings suggest not only cortical plasticity of the occipital cortex but also reorganization of the cortical network for the executive control of working memory.

Energy-saving framework for passive optical networks with ONU sleep/doze mode.

Science.gov (United States)

Van, Dung Pham; Valcarenghi, Luca; Dias, Maluge Pubuduni Imali; Kondepu, Koteswararao; Castoldi, Piero; Wong, Elaine

2015-02-09

This paper proposes an energy-saving passive optical network framework (ESPON) that aims to incorporate optical network unit (ONU) sleep/doze mode into dynamic bandwidth allocation (DBA) algorithms to reduce ONU energy consumption. In the ESPON, the optical line terminal (OLT) schedules both downstream (DS) and upstream (US) transmissions in the same slot in an online and dynamic fashion whereas the ONU enters sleep mode outside the slot. The ONU sleep time is maximized based on both DS and US traffic. Moreover, during the slot, the ONU might enter doze mode when only its transmitter is idle to further improve energy efficiency. The scheduling order of data transmission, control message exchange, sleep period, and doze period defines an energy-efficient scheme under the ESPON. Three schemes are designed and evaluated in an extensive FPGA-based evaluation. Results show that whilst all the schemes significantly save ONU energy for different evaluation scenarios, the scheduling order has great impact on their performance. In addition, the ESPON allows for a scheduling order that saves ONU energy independently of the network reach.

The CB1 Neutral Antagonist Tetrahydrocannabivarin Reduces Default Mode Network and Increases Executive Control Network Resting State Functional Connectivity in Healthy Volunteers.

Science.gov (United States)

Rzepa, Ewelina; Tudge, Luke; McCabe, Ciara

2015-09-10

The cannabinoid cannabinoid type 1 (CB1) neutral antagonist tetrahydrocannabivarin (THCv) has been suggested as a possible treatment for obesity, but without the depressogenic side-effects of inverse antagonists such as Rimonabant. However, how THCv might affect the resting state functional connectivity of the human brain is as yet unknown. We examined the effects of a single 10mg oral dose of THCv and placebo in 20 healthy volunteers in a randomized, within-subject, double-blind design. Using resting state functional magnetic resonance imaging and seed-based connectivity analyses, we selected the amygdala, insula, orbitofrontal cortex, and dorsal medial prefrontal cortex (dmPFC) as regions of interest. Mood and subjective experience were also measured before and after drug administration using self-report scales. Our results revealed, as expected, no significant differences in the subjective experience with a single dose of THCv. However, we found reduced resting state functional connectivity between the amygdala seed region and the default mode network and increased resting state functional connectivity between the amygdala seed region and the dorsal anterior cingulate cortex and between the dmPFC seed region and the inferior frontal gyrus/medial frontal gyrus. We also found a positive correlation under placebo for the amygdala-precuneus connectivity with the body mass index, although this correlation was not apparent under THCv. Our findings are the first to show that treatment with the CB1 neutral antagonist THCv decreases resting state functional connectivity in the default mode network and increases connectivity in the cognitive control network and dorsal visual stream network. This effect profile suggests possible therapeutic activity of THCv for obesity, where functional connectivity has been found to be altered in these regions. © The Author 2015. Published by Oxford University Press on behalf of CINP.

The Default Mode Network as a Biomarker of Persistent Complaints after Mild Traumatic Brain Injury: A Longitudinal Functional Magnetic Resonance Imaging Study.

Science.gov (United States)

van der Horn, Harm J; Scheenen, Myrthe E; de Koning, Myrthe E; Liemburg, Edith J; Spikman, Jacoba M; van der Naalt, Joukje

2017-12-01

The objective of this study was to examine longitudinal functional connectivity of resting-state networks in patients with and without complaints after uncomplicated mild traumatic brain injury (mTBI). Second, we aimed to determine the value of network connectivity in predicting persistent complaints, anxiety, depression and long-term outcome. Thirty mTBI patients with three or more post-traumatic complaints at 2 weeks post-injury, 19 without complaints, and 20 matched healthy controls were selected for this study. Resting-state functional MRI (fMRI) was performed in patients at 1 month and 3 months post-injury, and once in healthy controls. Independent component analysis (ICA) was used to investigate the default mode, executive and salience networks. Persistent post-traumatic complaints, anxiety, and depression were measured at 3 months post-injury, and outcome was determined at 1 year post-injury. Within the group with complaints, higher functional connectivity between the anterior and posterior components of the default mode network at 1 month post-injury was associated with a greater number of complaints at 3 months post-injury (ρ = 0.59, p = 0.001). Minor longitudinal changes in functional connectivity were found for patients with and without complaints after mTBI, which were limited to connectivity within the precuneus component of the default mode network. No significant results were found for the executive and salience networks. Current results suggest that the default mode network may serve as a biomarker of persistent complaints in patients with uncomplicated mTBI.

Bayesian network analysis revealed the connectivity difference of the default mode network from the resting-state to task-state

Science.gov (United States)

Wu, Xia; Yu, Xinyu; Yao, Li; Li, Rui

2014-01-01

Functional magnetic resonance imaging (fMRI) studies have converged to reveal the default mode network (DMN), a constellation of regions that display co-activation during resting-state but co-deactivation during attention-demanding tasks in the brain. Here, we employed a Bayesian network (BN) analysis method to construct a directed effective connectivity model of the DMN and compared the organizational architecture and interregional directed connections under both resting-state and task-state. The analysis results indicated that the DMN was consistently organized into two closely interacting subsystems in both resting-state and task-state. The directed connections between DMN regions, however, changed significantly from the resting-state to task-state condition. The results suggest that the DMN intrinsically maintains a relatively stable structure whether at rest or performing tasks but has different information processing mechanisms under varied states. PMID:25309414

A Sliding Mode Control-based on a RBF Neural Network for Deburring Industry Robotic Systems

OpenAIRE

Tao, Yong; Zheng, Jiaqi; Lin, Yuanchang

2016-01-01

A sliding mode control method based on radial basis function (RBF) neural network is proposed for the deburring of industry robotic systems. First, a dynamic model for deburring the robot system is established. Then, a conventional SMC scheme is introduced for the joint position tracking of robot manipulators. The RBF neural network based sliding mode control (RBFNN-SMC) has the ability to learn uncertain control actions. In the RBFNN-SMC scheme, the adaptive tuning algorithms for network par...

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

Science.gov (United States)

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

2017-12-01

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

Meditation experience is associated with differences in default mode network activity and connectivity

Science.gov (United States)

Brewer, Judson A.; Worhunsky, Patrick D.; Gray, Jeremy R.; Tang, Yi-Yuan; Weber, Jochen; Kober, Hedy

2011-01-01

Many philosophical and contemplative traditions teach that “living in the moment” increases happiness. However, the default mode of humans appears to be that of mind-wandering, which correlates with unhappiness, and with activation in a network of brain areas associated with self-referential processing. We investigated brain activity in experienced meditators and matched meditation-naive controls as they performed several different meditations (Concentration, Loving-Kindness, Choiceless Awareness). We found that the main nodes of the default-mode network (medial prefrontal and posterior cingulate cortices) were relatively deactivated in experienced meditators across all meditation types. Furthermore, functional connectivity analysis revealed stronger coupling in experienced meditators between the posterior cingulate, dorsal anterior cingulate, and dorsolateral prefrontal cortices (regions previously implicated in self-monitoring and cognitive control), both at baseline and during meditation. Our findings demonstrate differences in the default-mode network that are consistent with decreased mind-wandering. As such, these provide a unique understanding of possible neural mechanisms of meditation. PMID:22114193

Performance evaluation of a burst-mode EDFA in an optical packet and circuit integrated network.

Science.gov (United States)

Shiraiwa, Masaki; Awaji, Yoshinari; Furukawa, Hideaki; Shinada, Satoshi; Puttnam, Benjamin J; Wada, Naoya

2013-12-30

We experimentally investigate the performance of burst-mode EDFA in an optical packet and circuit integrated system. In such networks, packets and light paths can be dynamically assigned to the same fibers, resulting in gain transients in EDFAs throughout the network that can limit network performance. Here, we compare the performance of a 'burst-mode' EDFA (BM-EDFA), employing transient suppression techniques and optical feedback, with conventional EDFAs, and those using automatic gain control and previous BM-EDFA implementations. We first measure gain transients and other impairments in a simplified set-up before making frame error-rate measurements in a network demonstration.

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

Science.gov (United States)

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

2014-08-01

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

The Brain on Art: Intense Aesthetic Experience Activates the Default Mode Network

Directory of Open Access Journals (Sweden)

Edward A Vessel

2012-04-01

Full Text Available Aesthetic responses to visual art comprise multiple types of experiences, from sensation and perception to emotion and self-reflection. Moreover, aesthetic experience is highly individual, with observers varying significantly in their responses to the same artwork. Combining fMRI and behavioral analysis of individual differences in aesthetic response, we identify two distinct patterns of neural activity exhibited by different subnetworks. Activity increased linearly with observers’ ratings (4-level scale in sensory (occipito-temporal regions. Activity in the striatum also varied linearly with ratings, with below-baseline activations for low-rated artworks. In contrast, a network of frontal regions showed a step-like increase only for the most moving artworks (4 ratings and non-differential activity for all others. This included several regions belonging to the default mode network previously associated with self-referential mentation. Our results suggest that aesthetic experience involves the integration of sensory and emotional reactions in a manner linked with their personal relevance.

Cognitive and default-mode resting state networks: do male and female brains "rest" differently?

Science.gov (United States)

Weissman-Fogel, Irit; Moayedi, Massieh; Taylor, Keri S; Pope, Geoff; Davis, Karen D

2010-11-01

Variability in human behavior related to sex is supported by neuroimaging studies showing differences in brain activation patterns during cognitive task performance. An emerging field is examining the human connectome, including networks of brain regions that are not only temporally-correlated during different task conditions, but also networks that show highly correlated spontaneous activity during a task-free state. Both task-related and task-free network activity has been associated with individual task performance and behavior under certain conditions. Therefore, our aim was to determine whether sex differences exist during a task-free resting state for two networks associated with cognitive task performance (executive control network (ECN), salience network (SN)) and the default mode network (DMN). Forty-nine healthy subjects (26 females, 23 males) underwent a 5-min task-free fMRI scan in a 3T MRI. An independent components analysis (ICA) was performed to identify the best-fit IC for each network based on specific spatial nodes defined in previous studies. To determine the consistency of these networks across subjects we performed self-organizing group-level ICA analyses. There were no significant differences between sexes in the functional connectivity of the brain areas within the ECN, SN, or the DMN. These important findings highlight the robustness of intrinsic connectivity of these resting state networks and their similarity between sexes. Furthermore, our findings suggest that resting state fMRI studies do not need to be controlled for sex. © 2010 Wiley-Liss, Inc.

EEG PHASE RESET OF THE DEFAULT MODE NETWORK

Directory of Open Access Journals (Sweden)

Robert W. Thatcher

2014-07-01

Full Text Available Objectives: The purpose of this study was to explore phase reset of 3-dimensional current sources located in Brodmann areas located in the human default mode network (DMN using Low Resolution Electromagnetic Tomography (LORETA of the human electroencephalogram (EEG. Methods: The EEG was recorded from 19 scalp locations from 70 healthy normal subjects ranging in age from 13 to 20 years. A time point by time point computation of LORETA current sources were computed for 14 Brodman areas comprising the DMN in the delta frequency band. The Hilbert transform of the LORETA time series was used to compute the instantaneous phase differences between all pairs of Brodmann areas. Phase shift and lock durations were calculated based on the 1st & 2nd derivatives of the time series of phase differences. Results: Phase shift duration exhibited three discrete modes at approximately: 1- 30 msec,, 2- 55 msec and, 3- 65 msec. Phase lock duration present primarily at: 1- 300 to 350 msec and, 2- 350 msec to 450 msec. Phase shift and lock durations were inversely related and exhibited an exponential change with distance between Brodmann areas. Conclusions: The results are explained by local neural packing density of network hubs and an exponential decrease in connections with distance from a hub. The results are consistent with a discrete temporal model of brain function where anatomical hubs behave like a ‘shutter’ that opens and closes at specific durations as nodes of a network giving rise to temporarily phase locked clusters of neurons for specific durations.

The study of RMB exchange rate complex networks based on fluctuation mode

Science.gov (United States)

Yao, Can-Zhong; Lin, Ji-Nan; Zheng, Xu-Zhou; Liu, Xiao-Feng

2015-10-01

In the paper, we research on the characteristics of RMB exchange rate time series fluctuation with methods of symbolization and coarse gaining. First, based on fluctuation features of RMB exchange rate, we define the first type of fluctuation mode as one specific foreign currency against RMB in four days' fluctuating situations, and the second type as four different foreign currencies against RMB in one day's fluctuating situation. With the transforming method, we construct the unique-currency and multi-currency complex networks. Further, through analyzing the topological features including out-degree, betweenness centrality and clustering coefficient of fluctuation-mode complex networks, we find that the out-degree distribution of both types of fluctuation mode basically follows power-law distributions with exponents between 1 and 2. The further analysis reveals that the out-degree and the clustering coefficient generally obey the approximated negative correlation. With this result, we confirm previous observations showing that the RMB exchange rate exhibits a characteristic of long-range memory. Finally, we analyze the most probable transmission route of fluctuation modes, and provide probability prediction matrix. The transmission route for RMB exchange rate fluctuation modes exhibits the characteristics of partially closed loop, repeat and reversibility, which lays a solid foundation for predicting RMB exchange rate fluctuation patterns with large volume of data.

Implementing the sine transform of fermionic modes as a tensor network

Science.gov (United States)

Epple, Hannes; Fries, Pascal; Hinrichsen, Haye

2017-09-01

Based on the algebraic theory of signal processing, we recursively decompose the discrete sine transform of the first kind (DST-I) into small orthogonal block operations. Using a diagrammatic language, we then second-quantize this decomposition to construct a tensor network implementing the DST-I for fermionic modes on a lattice. The complexity of the resulting network is shown to scale as 5/4 n logn (not considering swap gates), where n is the number of lattice sites. Our method provides a systematic approach of generalizing Ferris' spectral tensor network for nontrivial boundary conditions.

Asynchronous transfer mode and Local Area Network emulation standards, protocols, and security implications

OpenAIRE

Kirwin, John P.

1999-01-01

A complex networking technology called Asynchronous Transfer Mode (ATM) and a networking protocol called Local Area Network Emulation (LANE) are being integrated into many naval networks without any security-driven naval configuration guidelines. No single publication is available that describes security issues of data delivery and signaling relating to the transition of Ethernet to LANE and ATM. The thesis' focus is to provide: (1) an overview and security analysis of standardized protocols ...

The evolution analysis of listed companies co-holding non-listed financial companies based on two-mode heterogeneous networks

Science.gov (United States)

An, Pengli; Li, Huajiao; Zhou, Jinsheng; Chen, Fan

2017-10-01

Complex network theory is a widely used tool in the empirical research of financial markets. Two-mode and multi-mode networks are new trends and represent new directions in that they can more accurately simulate relationships between entities. In this paper, we use data for Chinese listed companies holding non-listed financial companies over a ten-year period to construct two networks: a two-mode primitive network in which listed companies and non-listed financial companies are considered actors and events, respectively, and a one-mode network that is constructed based on the decreasing-mode method in which listed companies are considered nodes. We analyze the evolution of the listed company co-holding network from several perspectives, including that of the whole network, of information control ability, of implicit relationships, of community division and of small-world characteristics. The results of the analysis indicate that (1) China's developing stock market affects the share-holding condition of listed companies holding non-listed financial companies; (2) the information control ability of co-holding networks is focused on a few listed companies and the implicit relationship of investment preference between listed companies is determined by the co-holding behavior; (3) the community division of the co-holding network is increasingly obvious, as determined by the investment preferences among listed companies; and (4) the small-world characteristics of the co-holding network are increasingly obvious, resulting in reduced communication costs. In this paper, we conduct an evolution analysis and develop an understanding of the factors that influence the listed companies co-holding network. This study will help illuminate research on evolution analysis.

Revisiting the variation of clustering coefficient of biological networks suggests new modular structure.

Science.gov (United States)

Hao, Dapeng; Ren, Cong; Li, Chuanxing

2012-05-01

A central idea in biology is the hierarchical organization of cellular processes. A commonly used method to identify the hierarchical modular organization of network relies on detecting a global signature known as variation of clustering coefficient (so-called modularity scaling). Although several studies have suggested other possible origins of this signature, it is still widely used nowadays to identify hierarchical modularity, especially in the analysis of biological networks. Therefore, a further and systematical investigation of this signature for different types of biological networks is necessary. We analyzed a variety of biological networks and found that the commonly used signature of hierarchical modularity is actually the reflection of spoke-like topology, suggesting a different view of network architecture. We proved that the existence of super-hubs is the origin that the clustering coefficient of a node follows a particular scaling law with degree k in metabolic networks. To study the modularity of biological networks, we systematically investigated the relationship between repulsion of hubs and variation of clustering coefficient. We provided direct evidences for repulsion between hubs being the underlying origin of the variation of clustering coefficient, and found that for biological networks having no anti-correlation between hubs, such as gene co-expression network, the clustering coefficient doesn't show dependence of degree. Here we have shown that the variation of clustering coefficient is neither sufficient nor exclusive for a network to be hierarchical. Our results suggest the existence of spoke-like modules as opposed to "deterministic model" of hierarchical modularity, and suggest the need to reconsider the organizational principle of biological hierarchy.

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

Science.gov (United States)

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

2013-01-01

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

Anatomy of the dorsal default-mode network in conduct disorder: Association with callous-unemotional traits.

Science.gov (United States)

Sethi, Arjun; Sarkar, Sagari; Dell'Acqua, Flavio; Viding, Essi; Catani, Marco; Murphy, Declan G M; Craig, Michael C

2018-04-01

We recently reported that emotional detachment in adult psychopathy was associated with structural abnormalities in the dorsal 'default-mode' network (DMN). However, it is unclear whether these differences are present in young people at risk of psychopathy. The most widely recognised group at risk for psychopathy are children/adolescents with conduct disorder (CD) and callous-unemotional (CU) traits. We therefore examined the microstructure of the dorsal DMN in 27 CD youths (14-with/13-without CU traits) compared to 16 typically developing controls using DTI tractography. Both CD groups had significantly (p < 0.025) reduced dorsal DMN radial diffusivity compared to controls. In those with diagnostically significant CU traits, exploratory analyses (uncorrected for multiple comparisons) suggested that radial diffusivity was negatively correlated with CU severity (Left: rho = -0.68, p = 0.015). These results suggest that CD youths have microstructural abnormalities in the same network as adults with psychopathy. Further, the association with childhood/adolescent measures of emotional detachment (CU traits) resembles the relationship between emotional detachment and network microstructure in adult psychopaths. However, these changes appear to occur in opposite directions - with increased myelination in adolescent CD but reduced integrity in adult psychopathy. Collectively, these findings suggest that developmental abnormalities in dorsal DMN may play a role in the emergence of psychopathy. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

LORETA EEG phase reset of the default mode network.

Science.gov (United States)

Thatcher, Robert W; North, Duane M; Biver, Carl J

2014-01-01

The purpose of this study was to explore phase reset of 3-dimensional current sources in Brodmann areas located in the human default mode network (DMN) using Low Resolution Electromagnetic Tomography (LORETA) of the human electroencephalogram (EEG). The EEG was recorded from 19 scalp locations from 70 healthy normal subjects ranging in age from 13 to 20 years. A time point by time point computation of LORETA current sources were computed for 14 Brodmann areas comprising the DMN in the delta frequency band. The Hilbert transform of the LORETA time series was used to compute the instantaneous phase differences between all pairs of Brodmann areas. Phase shift and lock durations were calculated based on the 1st and 2nd derivatives of the time series of phase differences. Phase shift duration exhibited three discrete modes at approximately: (1) 25 ms, (2) 50 ms, and (3) 65 ms. Phase lock duration present primarily at: (1) 300-350 ms and (2) 350-450 ms. Phase shift and lock durations were inversely related and exhibited an exponential change with distance between Brodmann areas. The results are explained by local neural packing density of network hubs and an exponential decrease in connections with distance from a hub. The results are consistent with a discrete temporal model of brain function where anatomical hubs behave like a "shutter" that opens and closes at specific durations as nodes of a network giving rise to temporarily phase locked clusters of neurons for specific durations.

Revisiting the variation of clustering coefficient of biological networks suggests new modular structure

Directory of Open Access Journals (Sweden)

Hao Dapeng

2012-05-01

Full Text Available Abstract Background A central idea in biology is the hierarchical organization of cellular processes. A commonly used method to identify the hierarchical modular organization of network relies on detecting a global signature known as variation of clustering coefficient (so-called modularity scaling. Although several studies have suggested other possible origins of this signature, it is still widely used nowadays to identify hierarchical modularity, especially in the analysis of biological networks. Therefore, a further and systematical investigation of this signature for different types of biological networks is necessary. Results We analyzed a variety of biological networks and found that the commonly used signature of hierarchical modularity is actually the reflection of spoke-like topology, suggesting a different view of network architecture. We proved that the existence of super-hubs is the origin that the clustering coefficient of a node follows a particular scaling law with degree k in metabolic networks. To study the modularity of biological networks, we systematically investigated the relationship between repulsion of hubs and variation of clustering coefficient. We provided direct evidences for repulsion between hubs being the underlying origin of the variation of clustering coefficient, and found that for biological networks having no anti-correlation between hubs, such as gene co-expression network, the clustering coefficient doesn’t show dependence of degree. Conclusions Here we have shown that the variation of clustering coefficient is neither sufficient nor exclusive for a network to be hierarchical. Our results suggest the existence of spoke-like modules as opposed to “deterministic model” of hierarchical modularity, and suggest the need to reconsider the organizational principle of biological hierarchy.

Adaptive Sliding Mode Control of Chaos in Permanent Magnet Synchronous Motor via Fuzzy Neural Networks

Directory of Open Access Journals (Sweden)

Tat-Bao-Thien Nguyen

2014-01-01

Full Text Available In this paper, based on fuzzy neural networks, we develop an adaptive sliding mode controller for chaos suppression and tracking control in a chaotic permanent magnet synchronous motor (PMSM drive system. The proposed controller consists of two parts. The first is an adaptive sliding mode controller which employs a fuzzy neural network to estimate the unknown nonlinear models for constructing the sliding mode controller. The second is a compensational controller which adaptively compensates estimation errors. For stability analysis, the Lyapunov synthesis approach is used to ensure the stability of controlled systems. Finally, simulation results are provided to verify the validity and superiority of the proposed method.

Intra-Organizational Two-Mode Networks Analysis of a Public Organization

Directory of Open Access Journals (Sweden)

Anna Ujwary-Gil

2017-10-01

Full Text Available The article focuses on the analysis of intra-organizational and two-mode networks of knowledge, resources and tasks. Each of these networks consists of a human and non-human actor in the terminology of the actor-network theory (ANT, or of only non-human actors. This type of research is rare in the theory of organization and management, even though the first article on meta-networks dates back to nearly two decades ago (Krackhardt & Carley, 1998. The article analyses the prominences and ties between particular network nodes (actors, knowledge, resources and tasks, assessing their effective use in an organization. The author selected a public organization operating in the university education sector, where saturation with communication, resource and knowledge-sharing are relatively high. The application of the network analysis provides a totally different perspective on an organization, taking into account the inter-relationship, which allows a holistic (complex outlook on the analyzed object. Especially, as it measures particular nodes as related to one another, not as isolated variables, as in classical research, where observations are independent.

Default mode network as a potential biomarker of chemotherapy-related brain injury

Science.gov (United States)

Kesler, Shelli R.

2014-01-01

Chronic medical conditions and/or their treatments may interact with aging to alter or even accelerate brain senescence. Adult onset cancer, for example, is a disease associated with advanced aging and emerging evidence suggests a profile of subtle but diffuse brain injury following cancer chemotherapy. Breast cancer is currently the primary model for studying these “chemobrain” effects. Given the widespread changes to brain structure and function as well as the common impairment of integrated cognitive skills observed following breast cancer chemotherapy, it is likely that large-scale brain networks are involved. Default mode network (DMN) is a strong candidate considering its preferential vulnerability to aging and sensitivity to toxicity and disease states. Additionally, chemotherapy is associated with several physiologic effects including increased inflammation and oxidative stress that are believed to elevate toxicity in the DMN. Biomarkers of DMN connectivity could aid in the development of treatments for chemotherapy-related cognitive decline. For example, certain nutritional interventions could potentially reduce the metabolic changes (e.g. amyloid beta toxicity) associated with DMN disruption. PMID:24913897

Trapped modes in linear quantum stochastic networks with delays

Energy Technology Data Exchange (ETDEWEB)

Tabak, Gil [Stanford University, Department of Applied Physics, Stanford, CA (United States); Mabuchi, Hideo

2016-12-15

Networks of open quantum systems with feedback have become an active area of research for applications such as quantum control, quantum communication and coherent information processing. A canonical formalism for the interconnection of open quantum systems using quantum stochastic differential equations (QSDEs) has been developed by Gough, James and co-workers and has been used to develop practical modeling approaches for complex quantum optical, microwave and optomechanical circuits/networks. In this paper we fill a significant gap in existing methodology by showing how trapped modes resulting from feedback via coupled channels with finite propagation delays can be identified systematically in a given passive linear network. Our method is based on the Blaschke-Potapov multiplicative factorization theorem for inner matrix-valued functions, which has been applied in the past to analog electronic networks. Our results provide a basis for extending the Quantum Hardware Description Language (QHDL) framework for automated quantum network model construction (Tezak et al. in Philos. Trans. R. Soc. A, Math. Phys. Eng. Sci. 370(1979):5270-5290, 2012) to efficiently treat scenarios in which each interconnection of components has an associated signal propagation time delay. (orig.)

Real-Time Transportation Mode Identification Using Artificial Neural Networks Enhanced with Mode Availability Layers: A Case Study in Dubai

Directory of Open Access Journals (Sweden)

Young-Ji Byon

2017-09-01

Full Text Available Traditionally, departments of transportation (DOTs have dispatched probe vehicles with dedicated vehicles and drivers for monitoring traffic conditions. Emerging assisted GPS (AGPS and accelerometer-equipped smartphones offer new sources of raw data that arise from voluntarily-traveling smartphone users provided that their modes of transportation can correctly be identified. By introducing additional raster map layers that indicate the availability of each mode, it is possible to enhance the accuracy of mode detection results. Even in its simplest form, an artificial neural network (ANN excels at pattern recognition with a relatively short processing timeframe once it is properly trained, which is suitable for real-time mode identification purposes. Dubai is one of the major cities in the Middle East and offers unique environments, such as a high density of extremely high-rise buildings that may introduce multi-path errors with GPS signals. This paper develops real-time mode identification ANNs enhanced with proposed mode availability geographic information system (GIS layers, firstly for a universal mode detection and, secondly for an auto mode detection for the particular intelligent transportation system (ITS application of traffic monitoring, and compares the results with existing approaches. It is found that ANN-based real-time mode identification, enhanced by mode availability GIS layers, significantly outperforms the existing methods.

Allocation of spectral and spatial modes in multidimensional metro-access optical networks

Science.gov (United States)

Gao, Wenbo; Cvijetic, Milorad

2018-04-01

Introduction of spatial division multiplexing (SDM) has added a new dimension in an effort to increase optical fiber channel capacity. At the same time, it can also be explored as an advanced optical networking tool. In this paper, we have investigated the resource allocation to end-users in multidimensional networking structure with plurality of spectral and spatial modes actively deployed in different networking segments. This presents a more comprehensive method as compared to the common practice where the segments of optical network are analyzed independently since the interaction between network hierarchies is included into consideration. We explored the possible transparency from the metro/core network to the optical access network, analyzed the potential bottlenecks from the network architecture perspective, and identified an optimized network structure. In our considerations, the viability of optical grooming through the entire hierarchical all-optical network is investigated by evaluating the effective utilization and spectral efficiency of the network architecture.

Teleoperation system using Asynchronous transfer mode, ATM network

International Nuclear Information System (INIS)

Mohd Dani Baba; A Nasoruddin Mohamad

1999-01-01

This paper examines the application of Asynchronous Transfer Mode (ATM) in a distributed industrial environment such as in teleoperation, which performs real time control manipulation from a remote location. In our study, two models of teleoperation are proposed; the first model is a point to point connection and the second model is through an ATM network. The performance results are analysed as to determine whether the two models can support the teleoperation traffics via simulation using commercial software design tool. (Author)

Few-mode fiber, splice and SDM component characterization by spatially-diverse optical vector network analysis

DEFF Research Database (Denmark)

Rommel, Simon; Mendinueta, José Manuel Delgado; Klaus, Werner

2017-01-01

This paper discusses spatially diverse optical vector network analysis for space division multiplexing (SDM) component and system characterization, which is becoming essential as SDM is widely considered to increase the capacity of optical communication systems. Characterization of a 108-channel ...... in the few-mode multi-core fiber and their impact on system IL and MDL are analyzed, finding splices to cause significant mode-mixing and to be non-negligible in system capacity analysis.......This paper discusses spatially diverse optical vector network analysis for space division multiplexing (SDM) component and system characterization, which is becoming essential as SDM is widely considered to increase the capacity of optical communication systems. Characterization of a 108-channel...... photonic lantern spatial multiplexer, coupled to a 36-core 3-mode fiber, is experimentally demonstrated, extracting the full impulse response and complex transfer function matrices as well as insertion loss (IL) and mode-dependent loss (MDL) data. Moreover, the mode-mixing behavior of fiber splices...

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Performance Evaluation of Beacon-Enabled Mode for IEEE 802.15.4 Wireless Sensor Network

Directory of Open Access Journals (Sweden)

M. Udin Harun Al Rasyid

2013-12-01

Full Text Available IEEE 802.15.5 standard support structure of star and peer-to-peer network formation. Strating from these, the cluster tree network can be built as a special case of peer-to-peer network to increse coverage area. In this paper, we provide an performance evaluation of beacon- enabled mode for IEEE 802.15.4 wireless sensor network on star and cluster topology in order to get the maximum result to apply the appropriate topology model as needed. We conduct analysis on each topology model by using the numbers of nodes from 10 nodes to 100 nodes to analyze throughput, delay, energy consumption, and probability success packet by using NS2 simulator. The simulation results show that the throughput and the probability of success packet of cluster topology are higher than that of star topology, and the energy consumption of cluster topology is lesser than that of star topology. However, cluster topology increases the delay more than star topology. Keywords: IEEE 802.15.4, wireless sensor network, beacon-enabled mode, topology, csma/ca

Identifying the default mode network structure using dynamic causal modeling on resting-state functional magnetic resonance imaging.

Science.gov (United States)

Di, Xin; Biswal, Bharat B

2014-02-01

The default mode network is part of the brain structure that shows higher neural activity and energy consumption when one is at rest. The key regions in the default mode network are highly interconnected as conveyed by both the white matter fiber tracing and the synchrony of resting-state functional magnetic resonance imaging signals. However, the causal information flow within the default mode network is still poorly understood. The current study used the dynamic causal modeling on a resting-state fMRI data set to identify the network structure underlying the default mode network. The endogenous brain fluctuations were explicitly modeled by Fourier series at the low frequency band of 0.01-0.08Hz, and those Fourier series were set as driving inputs of the DCM models. Model comparison procedures favored a model wherein the MPFC sends information to the PCC and the bilateral inferior parietal lobule sends information to both the PCC and MPFC. Further analyses provide evidence that the endogenous connectivity might be higher in the right hemisphere than in the left hemisphere. These data provided insight into the functions of each node in the DMN, and also validate the usage of DCM on resting-state fMRI data. © 2013.

A Sliding Mode Control-Based on a RBF Neural Network for Deburring Industry Robotic Systems

Directory of Open Access Journals (Sweden)

Yong Tao

2016-01-01

Full Text Available A sliding mode control method based on radial basis function (RBF neural network is proposed for the deburring of industry robotic systems. First, a dynamic model for deburring the robot system is established. Then, a conventional SMC scheme is introduced for the joint position tracking of robot manipulators. The RBF neural network based sliding mode control (RBFNN-SMC has the ability to learn uncertain control actions. In the RBFNN-SMC scheme, the adaptive tuning algorithms for network parameters are derived by a Koski function algorithm to ensure the network convergences and enacts stable control. The simulations and experimental results of the deburring robot system are provided to illustrate the effectiveness of the proposed RBFNN-SMC control method. The advantages of the proposed RBFNN-SMC method are also evaluated by comparing it to existing control schemes.

Effects of Cognitive Training on Resting-State Functional Connectivity of Default Mode, Salience, and Central Executive Networks.

Science.gov (United States)

Cao, Weifang; Cao, Xinyi; Hou, Changyue; Li, Ting; Cheng, Yan; Jiang, Lijuan; Luo, Cheng; Li, Chunbo; Yao, Dezhong

2016-01-01

Neuroimaging studies have documented that aging can disrupt certain higher cognitive systems such as the default mode network (DMN), the salience network and the central executive network (CEN). The effect of cognitive training on higher cognitive systems remains unclear. This study used a 1-year longitudinal design to explore the cognitive training effect on three higher cognitive networks in healthy older adults. The community-living healthy older adults were divided into two groups: the multi-domain cognitive training group (24 sessions of cognitive training over a 3-months period) and the wait-list control group. All subjects underwent cognitive measurements and resting-state functional magnetic resonance imaging scanning at baseline and at 1 year after the training ended. We examined training-related changes in functional connectivity (FC) within and between three networks. Compared with the baseline, we observed maintained or increased FC within all three networks after training. The scans after training also showed maintained anti-correlation of FC between the DMN and CEN compared to the baseline. These findings demonstrated that cognitive training maintained or improved the functional integration within networks and the coupling between the DMN and CEN in older adults. Our findings suggested that multi-domain cognitive training can mitigate the aging-related dysfunction of higher cognitive networks.

Imbalance of default mode and regulatory networks during externally focused processing in depression

Science.gov (United States)

Belleau, Emily L.; Taubitz, Lauren E.

2015-01-01

Attentional control difficulties likely underlie rumination, a core cognitive vulnerability in major depressive disorder (MDD). Abnormalities in the default mode, executive and salience networks are implicated in both rumination and attentional control difficulties in MDD. In the current study, individuals with MDD (n = 16) and healthy controls (n = 16) completed tasks designed to elicit self-focused (ruminative) and externally-focused thinking during fMRI scanning. The MDD group showed greater default mode network connectivity and less executive and salience network connectivity during the external-focus condition. Contrary to our predictions, there were no differences in connectivity between the groups during the self-focus condition. Thus, it appears that when directed to engage in self-referential thinking, both depressed and non-depressed individuals similarly recruit networks supporting this process. In contrast, when instructed to engage in non-self-focused thought, non-depressed individuals show a pattern of network connectivity indicative of minimized self-referential processing, whereas depressed individuals fail to reallocate neural resources in a manner consistent with effective down regulation of self-focused thought. This is consistent with difficulties in regulating self-focused thinking in order to engage in more goal-directed behavior that is seen in individuals with MDD. PMID:25274576

Current-mode subthreshold MOS implementation of the Herault-Jutten autoadaptive network

Science.gov (United States)

Cohen, Marc H.; Andreou, Andreas G.

1992-05-01

The translinear circuits in subthreshold MOS technology and current-mode design techniques for the implementation of neuromorphic analog network processing are investigated. The architecture, also known as the Herault-Jutten network, performs an independent component analysis and is essentially a continuous-time recursive linear adaptive filter. Analog I/O interface, weight coefficients, and adaptation blocks are all integrated on the chip. A small network with six neurons and 30 synapses was fabricated in a 2-microns n-well double-polysilicon, double-metal CMOS process. Circuit designs at the transistor level yield area-efficient implementations for neurons, synapses, and the adaptation blocks. The design methodology and constraints as well as test results from the fabricated chips are discussed.

Altered intrinsic organisation of brain networks implicated in attentional processes in adult attention-deficit/hyperactivity disorder: a resting-state study of attention, default mode and salience network connectivity.

Science.gov (United States)

Sidlauskaite, Justina; Sonuga-Barke, Edmund; Roeyers, Herbert; Wiersema, Jan R

2016-06-01

Deficits in task-related attentional engagement in attention-deficit/hyperactivity disorder (ADHD) have been hypothesised to be due to altered interrelationships between attention, default mode and salience networks. We examined the intrinsic connectivity during rest within and between these networks. Six-minute resting-state scans were obtained. Using a network-based approach, connectivity within and between the dorsal and ventral attention, the default mode and the salience networks was compared between the ADHD and control group. The ADHD group displayed hyperconnectivity between the two attention networks and within the default mode and ventral attention network. The salience network was hypoconnected to the dorsal attention network. There were trends towards hyperconnectivity within the dorsal attention network and between the salience and ventral attention network in ADHD. Connectivity within and between other networks was unrelated to ADHD. Our findings highlight the altered connectivity within and between attention networks, and between them and the salience network in ADHD. One hypothesis to be tested in future studies is that individuals with ADHD are affected by an imbalance between ventral and dorsal attention systems with the former playing a dominant role during task engagement, making individuals with ADHD highly susceptible to distraction by salient task-irrelevant stimuli.

State estimation for discrete-time Markovian jumping neural networks with mixed mode-dependent delays

International Nuclear Information System (INIS)

Liu Yurong; Wang Zidong; Liu Xiaohui

2008-01-01

In this Letter, we investigate the state estimation problem for a new class of discrete-time neural networks with Markovian jumping parameters as well as mode-dependent mixed time-delays. The parameters of the discrete-time neural networks are subject to the switching from one mode to another at different times according to a Markov chain, and the mixed time-delays consist of both discrete and distributed delays that are dependent on the Markovian jumping mode. New techniques are developed to deal with the mixed time-delays in the discrete-time setting, and a novel Lyapunov-Krasovskii functional is put forward to reflect the mode-dependent time-delays. Sufficient conditions are established in terms of linear matrix inequalities (LMIs) that guarantee the existence of the state estimators. We show that both the existence conditions and the explicit expression of the desired estimator can be characterized in terms of the solution to an LMI. A numerical example is exploited to show the usefulness of the derived LMI-based conditions

Emotion Regulation and Complex Brain Networks: Association Between Expressive Suppression and Efficiency in the Fronto-Parietal Network and Default-Mode Network

Directory of Open Access Journals (Sweden)

Junhao Pan

2018-03-01

Full Text Available Emotion regulation (ER refers to the “implementation of a conscious or non-conscious goal to start, stop or otherwise modulate the trajectory of an emotion” (Etkin et al., 2015. Whereas multiple brain areas have been found to be involved in ER, relatively little is known about whether and how ER is associated with the global functioning of brain networks. Recent advances in brain connectivity research using graph-theory based analysis have shown that the brain can be organized into complex networks composed of functionally or structurally connected brain areas. Global efficiency is one graphic metric indicating the efficiency of information exchange among brain areas and is utilized to measure global functioning of brain networks. The present study examined the relationship between trait measures of ER (expressive suppression (ES and cognitive reappraisal (CR and global efficiency in resting-state functional brain networks (the whole brain network and ten predefined networks using structural equation modeling (SEM. The results showed that ES was reliably associated with efficiency in the fronto-parietal network and default-mode network. The finding advances the understanding of neural substrates of ER, revealing the relationship between ES and efficient organization of brain networks.

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

Directory of Open Access Journals (Sweden)

Josu Etxaniz

2017-04-01

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

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

Science.gov (United States)

Etxaniz, Josu; Aranguren, Gerardo

2017-01-01

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

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

Science.gov (United States)

Etxaniz, Josu; Aranguren, Gerardo

2017-04-30

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

The hydrogen-bond network of water supports propagating optical phonon-like modes.

Science.gov (United States)

Elton, Daniel C; Fernández-Serra, Marivi

2016-01-04

The local structure of liquid water as a function of temperature is a source of intense research. This structure is intimately linked to the dynamics of water molecules, which can be measured using Raman and infrared spectroscopies. The assignment of spectral peaks depends on whether they are collective modes or single-molecule motions. Vibrational modes in liquids are usually considered to be associated to the motions of single molecules or small clusters. Using molecular dynamics simulations, here we find dispersive optical phonon-like modes in the librational and OH-stretching bands. We argue that on subpicosecond time scales these modes propagate through water's hydrogen-bond network over distances of up to 2 nm. In the long wavelength limit these optical modes exhibit longitudinal-transverse splitting, indicating the presence of coherent long-range dipole-dipole interactions, as in ice. Our results indicate the dynamics of liquid water have more similarities to ice than previously thought.

Forecasting outpatient visits using empirical mode decomposition coupled with back-propagation artificial neural networks optimized by particle swarm optimization.

Science.gov (United States)

Huang, Daizheng; Wu, Zhihui

2017-01-01

Accurately predicting the trend of outpatient visits by mathematical modeling can help policy makers manage hospitals effectively, reasonably organize schedules for human resources and finances, and appropriately distribute hospital material resources. In this study, a hybrid method based on empirical mode decomposition and back-propagation artificial neural networks optimized by particle swarm optimization is developed to forecast outpatient visits on the basis of monthly numbers. The data outpatient visits are retrieved from January 2005 to December 2013 and first obtained as the original time series. Second, the original time series is decomposed into a finite and often small number of intrinsic mode functions by the empirical mode decomposition technique. Third, a three-layer back-propagation artificial neural network is constructed to forecast each intrinsic mode functions. To improve network performance and avoid falling into a local minimum, particle swarm optimization is employed to optimize the weights and thresholds of back-propagation artificial neural networks. Finally, the superposition of forecasting results of the intrinsic mode functions is regarded as the ultimate forecasting value. Simulation indicates that the proposed method attains a better performance index than the other four methods.

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

Science.gov (United States)

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

Aging-related changes in the default mode network and its anti-correlated networks: a resting-state fMRI study.

Science.gov (United States)

Wu, Jing-Tao; Wu, Hui-Zhen; Yan, Chao-Gan; Chen, Wen-Xin; Zhang, Hong-Ying; He, Yong; Yang, Hai-Shan

2011-10-17

Intrinsic brain activity in a resting state incorporates components of the task negative network called default mode network (DMN) and task-positive networks called attentional networks. In the present study, the reciprocal neuronal networks in the elder group were compared with the young group to investigate the differences of the intrinsic brain activity using a method of temporal correlation analysis based on seed regions of posterior cingulate cortex (PCC) and ventromedial prefrontal cortex (vmPFC). We found significant decreased positive correlations and negative correlations with the seeds of PCC and vmPFC in the old group. The decreased coactivations in the DMN network components and their negative networks in the old group may reflect age-related alterations in various brain functions such as attention, motor control and inhibition modulation in cognitive processing. These alterations in the resting state anti-correlative networks could provide neuronal substrates for the aging brain. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network

Science.gov (United States)

Li, Huajiao; An, Haizhong; Wang, Yue; Huang, Jiachen; Gao, Xiangyun

2016-05-01

Keeping abreast of trends in the articles and rapidly grasping a body of article's key points and relationship from a holistic perspective is a new challenge in both literature research and text mining. As the important component, keywords can present the core idea of the academic article. Usually, articles on a single theme or area could share one or some same keywords, and we can analyze topological features and evolution of the articles co-keyword networks and keywords co-occurrence networks to realize the in-depth analysis of the articles. This paper seeks to integrate statistics, text mining, complex networks and visualization to analyze all of the academic articles on one given theme, complex network(s). All 5944 ;complex networks; articles that were published between 1990 and 2013 and are available on the Web of Science are extracted. Based on the two-mode affiliation network theory, a new frontier of complex networks, we constructed two different networks, one taking the articles as nodes, the co-keyword relationships as edges and the quantity of co-keywords as the weight to construct articles co-keyword network, and another taking the articles' keywords as nodes, the co-occurrence relationships as edges and the quantity of simultaneous co-occurrences as the weight to construct keyword co-occurrence network. An integrated method for analyzing the topological features and evolution of the articles co-keyword network and keywords co-occurrence networks is proposed, and we also defined a new function to measure the innovation coefficient of the articles in annual level. This paper provides a useful tool and process for successfully achieving in-depth analysis and rapid understanding of the trends and relationships of articles in a holistic perspective.

The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code

Directory of Open Access Journals (Sweden)

Susanne Kunkel

2017-06-01

Full Text Available NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling.

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

Science.gov (United States)

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

2017-03-01

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

Episodic memory and the role of the brain’s default-mode network

NARCIS (Netherlands)

Huijbers, W.

2010-01-01

This thesis provides a number of new insights into episodic memory and the role of the default-mode network. First, it provides the first direct evidence for the contrasting role of DMN during encoding and retrieval. Secondly, the experimental findings eliminate several possible explanations for the

Adjustment of issue positions based on network strategies in a nelection campaign: A two-mode network autoregression model with cross-nested random effects

NARCIS (Netherlands)

Kleinnijenhuis, J.; de Nooy, W.

2013-01-01

During election campaigns, political parties deliver statements on salient issues in the news media, which are called issue positions. This article conceptualizes issue positions as a valued and longitudinal two-mode network of parties by issues. The network is valued because parties pronounce pro

Adjustment of issue positions based on network strategies in an election campaign: a two-mode network autoregression model with cross-nested random effects

NARCIS (Netherlands)

Kleinnijenhuis, J.; de Nooy, W.

2013-01-01

During election campaigns, political parties deliver statements on salient issues in the news media, which are called issue positions. This article conceptualizes issue positions as a valued and longitudinal two-mode network of parties by issues. The network is valued because parties pronounce pro

An examination of the default mode network in individuals with autonomous sensory meridian response (ASMR).

Science.gov (United States)

Smith, Stephen D; Katherine Fredborg, Beverley; Kornelsen, Jennifer

2017-08-01

Autonomous Sensory Meridian Response (ASMR) is a perceptual condition in which specific visual and auditory stimuli consistently trigger tingling sensations on the scalp and neck, sometimes spreading to the back and limbs. These triggering stimuli are often social, almost intimate, in nature (e.g., hearing whispering, or watching someone brush her hair), and often elicit a calm and positive emotional state. Surprisingly, despite its prevalence in the general population, no published study has examined the neural underpinnings of ASMR. In the current study, the default mode network (DMN) of 11 individuals with ASMR was contrasted to that of 11 matched controls. The results indicated that the DMN of individuals with ASMR showed significantly less functional connectivity than that of controls. The DMN of individuals with ASMR also demonstrated increased connectivity between regions in the occipital, frontal, and temporal cortices, suggesting that ASMR was associated with a blending of multiple resting-state networks. This atypical functional connectivity likely influences the unique sensory-emotional experiences associated with ASMR.

Random noise effects in pulse-mode digital multilayer neural networks.

Science.gov (United States)

Kim, Y C; Shanblatt, M A

1995-01-01

A pulse-mode digital multilayer neural network (DMNN) based on stochastic computing techniques is implemented with simple logic gates as basic computing elements. The pulse-mode signal representation and the use of simple logic gates for neural operations lead to a massively parallel yet compact and flexible network architecture, well suited for VLSI implementation. Algebraic neural operations are replaced by stochastic processes using pseudorandom pulse sequences. The distributions of the results from the stochastic processes are approximated using the hypergeometric distribution. Synaptic weights and neuron states are represented as probabilities and estimated as average pulse occurrence rates in corresponding pulse sequences. A statistical model of the noise (error) is developed to estimate the relative accuracy associated with stochastic computing in terms of mean and variance. Computational differences are then explained by comparison to deterministic neural computations. DMNN feedforward architectures are modeled in VHDL using character recognition problems as testbeds. Computational accuracy is analyzed, and the results of the statistical model are compared with the actual simulation results. Experiments show that the calculations performed in the DMNN are more accurate than those anticipated when Bernoulli sequences are assumed, as is common in the literature. Furthermore, the statistical model successfully predicts the accuracy of the operations performed in the DMNN.

Visual Network Asymmetry and Default Mode Network Function in ADHD: An fMRI Study

Directory of Open Access Journals (Sweden)

T. Sigi eHale

2014-07-01

Full Text Available Background: A growing body of research has identified abnormal visual information processing in ADHD. In particular, slow processing speed and increased reliance on visuo-perceptual strategies have become evident. Objective: The current study used recently developed fMRI methods to replicate and further examine abnormal rightward biased visual information processing in ADHD and to further characterize the nature of this effect; we tested its association to several large-scale distributed network systems. Method: We examined fMRI BOLD response during letter and location judgment tasks, and directly assessed visual network asymmetry and its association to large-scale networks using both a voxelwise and an averaged signal approach. Results: Initial within-group analyses revealed a pattern of left lateralized visual cortical activity in controls but right lateralized visual cortical activity in ADHD children. Direct analyses of visual network asymmetry confirmed atypical rightward bias in ADHD children compared to controls. This ADHD characteristic was atypically associated with reduced activation across several extra-visual networks, including the default mode network (DMN. We also found atypical associations between DMN activation and ADHD subjects’ inattentive symptoms and task performance. Conclusion: The current study demonstrated rightward VNA in ADHD during a simple letter discrimination task. This result adds an important novel consideration to the growing literature identifying abnormal visual processing in ADHD. We postulate that this characteristic reflects greater perceptual engagement of task-extraneous content, and that it may be a basic feature of less efficient top-down task-directed control over visual processing. We additionally argue that abnormal DMN function may contribute to this characteristic.

Few-mode fiber, splice and SDM component characterization by spatially-diverse optical vector network analysis.

Science.gov (United States)

Rommel, Simon; Mendinueta, José Manuel Delgado; Klaus, Werner; Sakaguchi, Jun; Olmos, Juan José Vegas; Awaji, Yoshinari; Monroy, Idelfonso Tafur; Wada, Naoya

2017-09-18

This paper discusses spatially diverse optical vector network analysis for space division multiplexing (SDM) component and system characterization, which is becoming essential as SDM is widely considered to increase the capacity of optical communication systems. Characterization of a 108-channel photonic lantern spatial multiplexer, coupled to a 36-core 3-mode fiber, is experimentally demonstrated, extracting the full impulse response and complex transfer function matrices as well as insertion loss (IL) and mode-dependent loss (MDL) data. Moreover, the mode-mixing behavior of fiber splices in the few-mode multi-core fiber and their impact on system IL and MDL are analyzed, finding splices to cause significant mode-mixing and to be non-negligible in system capacity analysis.

Action Potential Modulation of Neural Spin Networks Suggests Possible Role of Spin

CERN Document Server

Hu, H P

2004-01-01

In this paper we show that nuclear spin networks in neural membranes are modulated by action potentials through J-coupling, dipolar coupling and chemical shielding tensors and perturbed by microscopically strong and fluctuating internal magnetic fields produced largely by paramagnetic oxygen. We suggest that these spin networks could be involved in brain functions since said modulation inputs information carried by the neural spike trains into them, said perturbation activates various dynamics within them and the combination of the two likely produce stochastic resonance thus synchronizing said dynamics to the neural firings. Although quantum coherence is desirable and may indeed exist, it is not required for these spin networks to serve as the subatomic components for the conventional neural networks.

Unilateral deafness in children affects development of multi-modal modulation and default mode networks

Directory of Open Access Journals (Sweden)

Vincent eSchmithorst

2014-03-01

Full Text Available Monaural auditory input due to congenital or acquired unilateral hearing loss (UHL may have neurobiological effects on the developing brain. Using fMRI, we investigated the effect of UHL on the development of functional brain networks used for cross-modal processing. Children ages 7-12 with moderate or greater unilateral hearing loss of sensorineural origin (UHL-SN; N = 21 and normal-hearing controls (N = 23 performed an fMRI-compatible adaptation of the Token Test involving listening to a sentence such as touched the small green circle and the large blue square and simultaneously viewing an arrow touching colored shapes on a video. Children with right or severe-to-profound UHL-SN displayed smaller activation in a region encompassing the right inferior temporal, middle temporal, and middle occipital gyrus (BA 19/37/39, evidencing differences due to monaural hearing in cross-modal modulation of the visual processing pathway. Children with UHL-SN displayed increased activation in the left posterior superior temporal gyrus, likely the result either of more effortful low-level processing of auditory stimuli or differences in cross-modal modulation of the auditory processing pathway. Additionally, children with UHL-SN displayed reduced deactivation of anterior and posterior regions of the default mode network. Results suggest that monaural hearing affects the development of brain networks related to cross-modal sensory processing and the regulation of the default network during processing of spoken language.

Aberrant default-mode network-hippocampus connectivity after sad memory-recall in remitted-depression

NARCIS (Netherlands)

Figueroa, Caroline A.; Mocking, Roel J. T.; van Wingen, Guido; Martens, Suzanne; Ruhé, Henricus G.; Schene, Aart H.

2017-01-01

Rumination and cognitive reactivity (dysfunctional cognitions after sad mood-induction) remain high in remitted Major Depressive Disorder (MDD) and can contribute to new episodes. These factors have been linked to increased fMRI resting-state functional-connectivity within the Default-Mode Network

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

Science.gov (United States)

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

2016-06-01

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

ONU power saving modes in next generation optical access networks: progress, efficiency and challenges.

Science.gov (United States)

Dixit, Abhishek; Lannoo, Bart; Colle, Didier; Pickavet, Mario; Demeester, Piet

2012-12-10

The optical network unit (ONU), installed at a customer's premises, accounts for about 60% of power in current fiber-to-the-home (FTTH) networks. We propose a power consumption model for the ONU and evaluate the ONU power consumption in various next generation optical access (NGOA) architectures. Further, we study the impact of the power savings of the ONU in various low power modes such as power shedding, doze and sleep.

A Dynamic Microblog Network and Information Dissemination in “@” Mode

Directory of Open Access Journals (Sweden)

Mingsheng Tang

2014-01-01

Full Text Available Social media, especially the microblogs, emerge as a part of our daily life and become a key way to information spread. Thus, information dissemination in the microblog became a research hotspot. Based on some principles that are summarized from the microblog users’ behaviors, this paper proposes a dynamic microblog network model. Through simulations this network has the features of periodicity of average degree, high clustering coefficient, high degree of modularity, and community. Besides, an information dissemination model through “@” in the microblog has been presented. With the microblog network model and the zombie-city model, this paper has modelled an artificial microblog and has simulated the information dissemination in the artificial microblog with different scenes. Therefore, some interesting findings have been presented. (1 Due to a better connectivity, information could spread widely in a random network; (2 information spreads more quickly in a stable microblog network; (3 the decay rate of the relationships will have an effect on information dissemination; that is, with a lower decay rate, information spreads more quickly and widely; (4 the higher active level of users in microblog could promote information spread widely and quickly; (5 the “@” mode of information dissemination makes a high modularity of the information diffusion network.

Resting-state functional connectivity of the default mode network associated with happiness.

Science.gov (United States)

Luo, Yangmei; Kong, Feng; Qi, Senqing; You, Xuqun; Huang, Xiting

2016-03-01

Happiness refers to people's cognitive and affective evaluation of their life. Why are some people happier than others? One reason might be that unhappy people are prone to ruminate more than happy people. The default mode network (DMN) is normally active during rest and is implicated in rumination. We hypothesized that unhappiness may be associated with increased default-mode functional connectivity during rest, including the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC) and inferior parietal lobule (IPL). The hyperconnectivity of these areas may be associated with higher levels of rumination. One hundred forty-eight healthy participants underwent a resting-state fMRI scan. A group-independent component analysis identified the DMNs. Results indicated increased functional connectivity in the DMN was associated with lower levels of happiness. Specifically, relative to happy people, unhappy people exhibited greater functional connectivity in the anterior medial cortex (bilateral MPFC), posterior medial cortex regions (bilateral PCC) and posterior parietal cortex (left IPL). Moreover, the increased functional connectivity of the MPFC, PCC and IPL, correlated positively with the inclination to ruminate. These results highlight the important role of the DMN in the neural correlates of happiness, and suggest that rumination may play an important role in people's perceived happiness. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Dysfunctional default mode network and executive control network in people with Internet gaming disorder: Independent component analysis under a probability discounting task.

Science.gov (United States)

Wang, L; Wu, L; Lin, X; Zhang, Y; Zhou, H; Du, X; Dong, G

2016-04-01

The present study identified the neural mechanism of risky decision-making in Internet gaming disorder (IGD) under a probability discounting task. Independent component analysis was used on the functional magnetic resonance imaging data from 19 IGD subjects (22.2 ± 3.08 years) and 21 healthy controls (HC, 22.8 ± 3.5 years). For the behavioral results, IGD subjects prefer the risky to the fixed options and showed shorter reaction time compared to HC. For the imaging results, the IGD subjects showed higher task-related activity in default mode network (DMN) and less engagement in the executive control network (ECN) than HC when making the risky decisions. Also, we found the activities of DMN correlate negatively with the reaction time and the ECN correlate positively with the probability discounting rates. The results suggest that people with IGD show altered modulation in DMN and deficit in executive control function, which might be the reason for why the IGD subjects continue to play online games despite the potential negative consequences. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

An Investigation of a New Social Networks Contact Suggestion Based on Face Recognition Algorithm

Directory of Open Access Journals (Sweden)

Ivan Zelinka

2016-01-01

Full Text Available Automated comparison of faces in the photographs is a well established discipline. The main aim of this paper is to describe an approach whereby face recognition can be used in suggestion of a new contacts. The new contact suggestion is a common technique used across all main social networks. Our approach uses a freely available face comparison called "Betaface" together with our automated processig of the user´s Facebook profile. The research´s main point of interest is the comparison of friend´s facial images in a social network itself, how to process such a great amount of photos and what additional sources of data should be used. In this approach we used our automated processing algorithm Betaface in the social network Facebook and for the additional data, the Flickr social network was used. The results and their quality are discussed at the end.

Combination of DTI and fMRI reveals the white matter changes correlating with the decline of default-mode network activity in Alzheimer's disease

Science.gov (United States)

Wu, Xianjun; Di, Qian; Li, Yao; Zhao, Xiaojie

2009-02-01

Recently, evidences from fMRI studies have shown that there was decreased activity among the default-mode network in Alzheimer's disease (AD), and DTI researches also demonstrated that demyelinations exist in white matter of AD patients. Therefore, combining these two MRI methods may help to reveal the relationship between white matter damages and alterations of the resting state functional connectivity network. In the present study, we tried to address this issue by means of correlation analysis between DTI and resting state fMRI images. The default-mode networks of AD and normal control groups were compared to find the areas with significantly declined activity firstly. Then, the white matter regions whose fractional anisotropy (FA) value correlated with this decline were located through multiple regressions between the FA values and the BOLD response of the default networks. Among these correlating white matter regions, those whose FA values also declined were found by a group comparison between AD patients and healthy elderly control subjects. Our results showed that the areas with decreased activity among default-mode network included left posterior cingulated cortex (PCC), left medial temporal gyrus et al. And the damaged white matter areas correlated with the default-mode network alterations were located around left sub-gyral temporal lobe. These changes may relate to the decreased connectivity between PCC and medial temporal lobe (MTL), and thus correlate with the deficiency of default-mode network activity.

On the effectiveness of single and multiple base station sleep modes in cellular networks

OpenAIRE

Marsan, Marco Ajmone; Chiaraviglio, Luca; Ciullo, Delia; Meo, Michela

2013-01-01

In this paper we study base station sleep modes that, by reducing power consumption in periods of low traffic, improve the energy efficiency of cellular access networks. We assume that when some base stations enter sleep mode, radio coverage and service provisioning are provided by the base stations that remain active, so as to guarantee that service is available over the whole area at all times. This may be an optimistic assumption in the case of the sparse base station layouts typical of ru...

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

Science.gov (United States)

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

2017-08-01

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

Influence of Load Modes on Voltage Stability of Receiving Network at DC/AC System

Directory of Open Access Journals (Sweden)

Mao Chizu

2016-01-01

Full Text Available This paper analyses influence of load modes on DC/AC system. Because of widespread use of HVDC, DC/AC system become more complex than before and the present modes used in dispatch and planning departments are not fit in simulation anymore. So it is necessary to find load modes accurately reflecting characteristics of the system. For the sake of the voltage stability, commutation failure, etc. the practical example of the receiving network in a large DC/AC system in China is simulated with BPA, and the influence of Classical Load Mode (CLM and Synthesis load model (SLM on simulation results is studies. Furthermore, some important parameters of SLM are varied respectively among an interval to analyse how they affect the system. According to this practical examples, the result is closely related to load modes and their parameters, and SLM is more conservative but more reasonable than the present modes. The consequences indicate that at critical states, micro variation in parameters may give rise to change in simulation results radically. Thus, correct mode and parameters are important to enhance simulation accuracy of DC/AC system and researches on how they affect the system make senses.

Joint Mode Selection and Resource Allocation for Downlink Fog Radio Access Networks Supported D2D

Directory of Open Access Journals (Sweden)

Xiang Hongyu

2015-09-01

Full Text Available Presented as an innovative paradigm incorporating the cloud computing into radio access network, Cloud radio access networks (C-RANs have been shown advantageous in curtailing the capital and operating expenditures as well as providing better services to the customers. However, heavy burden on the non-ideal fronthaul limits performances of CRANs. Here we focus on the alleviation of burden on the fronthaul via the edge devices’ caches and propose a fog computing based RAN (F-RAN architecture with three candidate transmission modes: device to device, local distributed coordination, and global C-RAN. Followed by the proposed simple mode selection scheme, the average energy efficiency (EE of systems optimization problem considering congestion control is presented. Under the Lyapunov framework, the problem is reformulated as a joint mode selection and resource allocation problem, which can be solved by block coordinate descent method. The mathematical analysis and simulation results validate the benefits of F-RAN and an EE-delay tradeoff can be achieved by the proposed algorithm.

Prefrontal Function Engaging in External-Focused Attention in 5- to 6-Month-Old Infants: A Suggestion for Default Mode Network.

Science.gov (United States)

Xu, Mingdi; Hoshino, Eiichi; Yatabe, Kiyomi; Matsuda, Soichiro; Sato, Hiroki; Maki, Atsushi; Yoshimura, Mina; Minagawa, Yasuyo

2016-01-01

The present study used functional near-infrared spectroscopy (fNIRS) to measure 5- to 6-month-old infants' hemodynamic response in the prefrontal cortex (PFC) to visual stimuli differing in saliency and social value. Nineteen Japanese 5- to 6-month-old infants watched video clips of Peek-a-Boo (social signal) performed by an anime character (AC) or a human, and hand movements without social signal performed by an AC. The PFC activity of infants was measured by 22-channel fNIRS, while behaviors including looking time were recorded simultaneously. NIRS data showed that infants' hemodynamic responses in the PFC generally decreased due to these stimuli, and the decrease was most prominent in the frontopolar (FP), covering medial PFC (MPFC), when infants were viewing Peek-a-Boo performed by an AC. Moreover, the decrease was more pronounced in the dorsolateral PFC (DLPFC) when infants were viewing Peek-a-Boo performed by an AC than by a human. Accordingly, behavioral data revealed significantly longer looking times when Peek-a-Boo was performed by an AC than by a human. No significant difference between Peek-a-Boo and non-Peek-a-Boo conditions was observed in either measure. These findings indicate that infants at this age may prefer stimuli with more salient features, which may be more effective in attracting their attentions. In conjunction with our previous findings on responses to self-name calling in infants of similar age, we hypothesize that the dynamic function of the MPFC and its vicinity (as part of default mode network (DMN): enhanced by self-focused stimuli, attenuated by externally focused stimuli), which is consistently observed in adults, may have already emerged in 5- to 6-month-old infants.

Mode 3 knowledge production: Systems and systems theory, clusters and networks

OpenAIRE

Carayannis, Elias G.; Campbell, David F. J.; Rehman, Scheherazade S.

2016-01-01

With the comprehensive term of "Mode 3," we want to draw a conceptual link between systems and systems theory and want to demonstrate further how this can be applied to knowledge in the next steps. Systems can be understood as being composed of "elements", which are tied together by a "self-rationale". For innovation, often innovation clusters and innovation networks are being regarded as important. By leveraging systems theory for innovation concepts, one can implement references between the...

Network-based analysis of genotype-phenotype correlations between different inheritance modes.

Science.gov (United States)

Hao, Dapeng; Li, Chuanxing; Zhang, Shaojun; Lu, Jianping; Jiang, Yongshuai; Wang, Shiyuan; Zhou, Meng

2014-11-15

Recent studies on human disease have revealed that aberrant interaction between proteins probably underlies a substantial number of human genetic diseases. This suggests a need to investigate disease inheritance mode using interaction, and based on which to refresh our conceptual understanding of a series of properties regarding inheritance mode of human disease. We observed a strong correlation between the number of protein interactions and the likelihood of a gene causing any dominant diseases or multiple dominant diseases, whereas no correlation was observed between protein interaction and the likelihood of a gene causing recessive diseases. We found that dominant diseases are more likely to be associated with disruption of important interactions. These suggest inheritance mode should be understood using protein interaction. We therefore reviewed the previous studies and refined an interaction model of inheritance mode, and then confirmed that this model is largely reasonable using new evidences. With these findings, we found that the inheritance mode of human genetic diseases can be predicted using protein interaction. By integrating the systems biology perspectives with the classical disease genetics paradigm, our study provides some new insights into genotype-phenotype correlations. haodapeng@ems.hrbmu.edu.cn or biofomeng@hotmail.com Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Social by default : the default-mode network and social cognition in healthy volunteers and siblings of schizophrenia patients

NARCIS (Netherlands)

van Buuren, M.

2012-01-01

During rest, a set of brain areas shows increased activity compared to when people are performing complex tasks. This network is commonly referred to as the default-mode network (DMN) and includes the ventral and dorsal medial prefrontal cortex, posterior cingulate cortex and lateral posterior

Sliding mode synchronization controller design with neural network for uncertain chaotic systems

Energy Technology Data Exchange (ETDEWEB)

Mou Chen [College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China)], E-mail: chenmou@nuaa.edu.cn; Jiang Changsheng; Bin Jiang; Wu Qingxian [College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China)

2009-02-28

A sliding mode synchronization controller is presented with RBF neural network for two chaotic systems in this paper. The compound disturbance of the synchronization error system consists of nonlinear uncertainties and exterior disturbances of chaotic systems. Based on RBF neural networks, a compound disturbance observer is proposed and the update law of parameters is given to monitor the compound disturbance. The synchronization controller is given based on the output of the compound disturbance observer. The designed controller can make the synchronization error convergent to zero and overcome the disruption of the uncertainty and the exterior disturbance of the system. Finally, an example is given to demonstrate the availability of the proposed synchronization control method.

Can the default-mode network be described with one spatial-covariance network?

Science.gov (United States)

Habeck, Christian; Steffener, Jason; Rakitin, Brian; Stern, Yaakov

2012-01-01

The default-mode network (DMN) has become a well accepted concept in cognitive and clinical neuroscience over the last decade, and perusal of the recent literature attests to a stimulating research field of cognitive and diagnostic applications (for example, (Andrews-Hanna, Reidler, Huang, & Buckner, 2010; Koch et al., 2010; Sheline, Barch et al., 2009; Sheline, Raichle et al., 2009; Uddin et al., 2008; Uddin, Kelly, Biswal, Castellanos, & Milham, 2009; Weng et al., 2009; Yan et al., 2009)). However, a formal definition of what exactly constitutes a functional brain network is difficult to come by. In recent contributions, some researchers argue that the DMN is best understood as multiple interacting subsystems (Buckner, Andrews-Hanna, & Schacter, 2008) and have explored modular components of the DMN that have different functional specialization and could to some extent be identified separately (Fox et al., 2005; Harrison et al., 2008; Uddin et al., 2009). Such conception of modularity seems to imply an opposite construct of a ‘unified whole’, but it is difficult to locate proponents of the idea of a DMN who are supplying constraints that can be brought to bear on data in rigorous tests. Our aim in this paper is to present a principled way of deriving a single covariance pattern as the neural substrate of the DMN, test to what extent its behavior tracks the coupling strength between critical seed regions, and investigate to what extent our stricter concept of a network is consistent with the already established findings about the DMN in the literature. We show that our approach leads to a functional covariance pattern whose pattern scores are a good proxy for the integrity of the connections between a medioprefrontal, posterior cingulate and parietal seed regions. Our derived DMN network thus has potential for diagnostic applications that are simpler to perform than computation of pairwise correlational strengths or seed maps. PMID:22668988

Task-Related Modulations of BOLD Low-Frequency Fluctuations within the Default Mode Network

Science.gov (United States)

Tommasin, Silvia; Mascali, Daniele; Gili, Tommaso; Assan, Ibrahim Eid; Moraschi, Marta; Fratini, Michela; Wise, Richard G.; Macaluso, Emiliano; Mangia, Silvia; Giove, Federico

2017-01-01

Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD) signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN), are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33 ± 6 years, 8 F/12 M) the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the continuous execution of a working memory n-back task. We found that task execution impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to continuous task execution, can contribute to a better understanding of how brain networks rearrange themselves in response to a task. PMID:28845420

Task-Related Modulations of BOLD Low-Frequency Fluctuations within the Default Mode Network

Directory of Open Access Journals (Sweden)

Silvia Tommasin

2017-07-01

Full Text Available Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN, are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33 ± 6 years, 8 F/12 M the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the continuous execution of a working memory n-back task. We found that task execution impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to continuous task execution, can contribute to a better understanding of how brain networks rearrange themselves in response to a task.

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

Directory of Open Access Journals (Sweden)

Ileana Pacheco-Colón

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

Treatment with olanzapine is associated with modulation of the default mode network in patients with Schizophrenia.

Science.gov (United States)

Sambataro, Fabio; Blasi, Giuseppe; Fazio, Leonardo; Caforio, Grazia; Taurisano, Paolo; Romano, Raffaella; Di Giorgio, Annabella; Gelao, Barbara; Lo Bianco, Luciana; Papazacharias, Apostolos; Popolizio, Teresa; Nardini, Marcello; Bertolino, Alessandro

2010-03-01

Earlier studies have shown widespread alterations of functional connectivity of various brain networks in schizophrenia, including the default mode network (DMN). The DMN has also an important role in the performance of cognitive tasks. Furthermore, treatment with second-generation antipsychotic drugs may ameliorate to some degree working memory (WM) deficits and related brain activity. The aim of this study was to evaluate the effects of treatment with olanzapine monotherapy on functional connectivity among brain regions of the DMN during WM. Seventeen patients underwent an 8-week prospective study and completed two functional magnetic resonance imaging (fMRI) scans at 4 and 8 weeks of treatment during the performance of the N-back WM task. To control for potential repetition effects, 19 healthy controls also underwent two fMRI scans at a similar time interval. We used spatial group-independent component analysis (ICA) to analyze fMRI data. Relative to controls, patients with schizophrenia had reduced connectivity strength within the DMN in posterior cingulate, whereas it was greater in precuneus and inferior parietal lobule. Treatment with olanzapine was associated with increases in DMN connectivity with ventromedial prefrontal cortex, but not in posterior regions of DMN. These results suggest that treatment with olanzapine is associated with the modulation of DMN connectivity in schizophrenia. In addition, our findings suggest critical functional differences in the regions of DMN.

Mind wandering away from pain dynamically engages antinociceptive and default mode brain networks.

Science.gov (United States)

Kucyi, Aaron; Salomons, Tim V; Davis, Karen D

2013-11-12

Human minds often wander away from their immediate sensory environment. It remains unknown whether such mind wandering is unsystematic or whether it lawfully relates to an individual's tendency to attend to salient stimuli such as pain and their associated brain structure/function. Studies of pain-cognition interactions typically examine explicit manipulation of attention rather than spontaneous mind wandering. Here we sought to better represent natural fluctuations in pain in daily life, so we assessed behavioral and neural aspects of spontaneous disengagement of attention from pain. We found that an individual's tendency to attend to pain related to the disruptive effect of pain on his or her cognitive task performance. Next, we linked behavioral findings to neural networks with strikingly convergent evidence from functional magnetic resonance imaging during pain coupled with thought probes of mind wandering, dynamic resting state activity fluctuations, and diffusion MRI. We found that (i) pain-induced default mode network (DMN) deactivations were attenuated during mind wandering away from pain; (ii) functional connectivity fluctuations between the DMN and periaqueductal gray (PAG) dynamically tracked spontaneous attention away from pain; and (iii) across individuals, stronger PAG-DMN structural connectivity and more dynamic resting state PAG-DMN functional connectivity were associated with the tendency to mind wander away from pain. These data demonstrate that individual tendencies to mind wander away from pain, in the absence of explicit manipulation, are subserved by functional and structural connectivity within and between default mode and antinociceptive descending modulation networks.

Automatic Railway Traffic Object Detection System Using Feature Fusion Refine Neural Network under Shunting Mode

Directory of Open Access Journals (Sweden)

Tao Ye

2018-06-01

Full Text Available Many accidents happen under shunting mode when the speed of a train is below 45 km/h. In this mode, train attendants observe the railway condition ahead using the traditional manual method and tell the observation results to the driver in order to avoid danger. To address this problem, an automatic object detection system based on convolutional neural network (CNN is proposed to detect objects ahead in shunting mode, which is called Feature Fusion Refine neural network (FR-Net. It consists of three connected modules, i.e., the depthwise-pointwise convolution, the coarse detection module, and the object detection module. Depth-wise-pointwise convolutions are used to improve the detection in real time. The coarse detection module coarsely refine the locations and sizes of prior anchors to provide better initialization for the subsequent module and also reduces search space for the classification, whereas the object detection module aims to regress accurate object locations and predict the class labels for the prior anchors. The experimental results on the railway traffic dataset show that FR-Net achieves 0.8953 mAP with 72.3 FPS performance on a machine with a GeForce GTX1080Ti with the input size of 320 × 320 pixels. The results imply that FR-Net takes a good tradeoff both on effectiveness and real time performance. The proposed method can meet the needs of practical application in shunting mode.

Motorized CPM/CAM physiotherapy device with sliding-mode Fuzzy Neural Network control loop.

Science.gov (United States)

Ho, Hung-Jung; Chen, Tien-Chi

2009-11-01

Continuous passive motion (CPM) and controllable active motion (CAM) physiotherapy devices promote rehabilitation of damaged joints. This paper presents a computerized CPM/CAM system that obviates the need for mechanical resistance devices such as springs. The system is controlled by a computer which performs sliding-mode Fuzzy Neural Network (FNN) calculations online. CAM-type resistance force is generated by the active performance of an electric motor which is controlled so as to oppose the motion of the patient's leg. A force sensor under the patient's foot on the device pedal provides data for feedback in a sliding-mode FNN control loop built around the motor. Via an active impedance control feedback system, the controller drives the motor to behave similarly to a damped spring by generating and controlling the amplitude and direction of the pedal force in relation to the patient's leg. Experiments demonstrate the high sensitivity and speed of the device. The PC-based feedback nature of the control loop means that sophisticated auto-adaptable CPM/CAM custom-designed physiotherapy becomes possible. The computer base also allows extensive data recording, data analysis and network-connected remote patient monitoring.

Breakdown of long-range temporal dependence in default mode and attention networks during deep sleep.

Science.gov (United States)

Tagliazucchi, Enzo; von Wegner, Frederic; Morzelewski, Astrid; Brodbeck, Verena; Jahnke, Kolja; Laufs, Helmut

2013-09-17

The integration of segregated brain functional modules is a prerequisite for conscious awareness during wakeful rest. Here, we test the hypothesis that temporal integration, measured as long-term memory in the history of neural activity, is another important quality underlying conscious awareness. For this aim, we study the temporal memory of blood oxygen level-dependent signals across the human nonrapid eye movement sleep cycle. Results reveal that this property gradually decreases from wakefulness to deep nonrapid eye movement sleep and that such decreases affect areas identified with default mode and attention networks. Although blood oxygen level-dependent spontaneous fluctuations exhibit nontrivial spatial organization, even during deep sleep, they also display a decreased temporal complexity in specific brain regions. Conversely, this result suggests that long-range temporal dependence might be an attribute of the spontaneous conscious mentation performed during wakeful rest.

Task-related modulations of BOLD low-frequency fluctuations within the default mode network

Science.gov (United States)

Tommasin, Silvia; Mascali, Daniele; Gili, Tommaso; Eid Assan, Ibrahim; Moraschi, Marta; Fratini, Michela; Wise, Richard G.; Macaluso, Emiliano; Mangia, Silvia; Giove, Federico

2017-07-01

Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD) signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN), are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33±6 years, 8F/12M) the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the steady-state execution of a sustained working memory n-back task. We found that the steady state execution of such a task impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to steady-state task execution, can contribute to a better understanding of how brain networks rearrange themselves in response of a task.

Classifying chemical mode of action using gene networks and machine learning: a case study with the herbicide linuron.

Science.gov (United States)

Ornostay, Anna; Cowie, Andrew M; Hindle, Matthew; Baker, Christopher J O; Martyniuk, Christopher J

2013-12-01

The herbicide linuron (LIN) is an endocrine disruptor with an anti-androgenic mode of action. The objectives of this study were to (1) improve knowledge of androgen and anti-androgen signaling in the teleostean ovary and to (2) assess the ability of gene networks and machine learning to classify LIN as an anti-androgen using transcriptomic data. Ovarian explants from vitellogenic fathead minnows (FHMs) were exposed to three concentrations of either 5α-dihydrotestosterone (DHT), flutamide (FLUT), or LIN for 12h. Ovaries exposed to DHT showed a significant increase in 17β-estradiol (E2) production while FLUT and LIN had no effect on E2. To improve understanding of androgen receptor signaling in the ovary, a reciprocal gene expression network was constructed for DHT and FLUT using pathway analysis and these data suggested that steroid metabolism, translation, and DNA replication are processes regulated through AR signaling in the ovary. Sub-network enrichment analysis revealed that FLUT and LIN shared more regulated gene networks in common compared to DHT. Using transcriptomic datasets from different fish species, machine learning algorithms classified LIN successfully with other anti-androgens. This study advances knowledge regarding molecular signaling cascades in the ovary that are responsive to androgens and anti-androgens and provides proof of concept that gene network analysis and machine learning can classify priority chemicals using experimental transcriptomic data collected from different fish species. © 2013.

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

Science.gov (United States)

Peeters, Sanne C T; van de Ven, Vincent; Gronenschild, Ed H B M; Patel, Ameera X; Habets, Petra; Goebel, Rainer; van Os, Jim; Marcelis, Machteld

2015-01-01

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

Default mode network abnormalities during state switching in attention deficit hyperactivity disorder.

Science.gov (United States)

Sidlauskaite, J; Sonuga-Barke, E; Roeyers, H; Wiersema, J R

2016-02-01

Individuals with attention deficit hyperactivity disorder (ADHD) display excess levels of default mode network (DMN) activity during goal-directed tasks, which are associated with attentional disturbances and performance decrements. One hypothesis is that this is due to attenuated down-regulation of this network during rest-to-task switching. A second related hypothesis is that it may be associated with right anterior insula (rAI) dysfunction - a region thought to control the actual state-switching process. These hypotheses were tested in the current fMRI study in which 19 adults with ADHD and 21 typically developing controls undertook a novel state-to-state switching paradigm. Advance cues signalled upcoming switches between rest and task periods and switch-related anticipatory modulation of DMN and rAI was measured. To examine whether rest-to-task switching impairments may be a specific example of a more general state regulation deficit, activity upon task-to-rest cues was also analysed. Against our hypotheses, we found that the process of down-regulating the DMN when preparing to switch from rest to task was unimpaired in ADHD and that there was no switch-specific deficit in rAI modulation. However, individuals with ADHD showed difficulties up-regulating the DMN when switching from task to rest. Rest-to-task DMN attenuation seems to be intact in adults with ADHD and thus appears unrelated to excess DMN activity observed during tasks. Instead, individuals with ADHD exhibit attenuated up-regulation of the DMN, hence suggesting disturbed re-initiation of a rest state.

Do Policy Networks lead to Network Governing?

DEFF Research Database (Denmark)

Damgaard, Bodil

This paper challenges the notion that creation of local policy networks necessarily leads to network governing. Through actor-centred case studies in the area of municipally implemented employment policy in Denmark it was found that the local governing mode is determined mainly by the municipality......’s approach to local co-governing as well as by the capacity and interest of key private actors. It is argued that national legislation requesting the creation of local policy networks was not enough to assure network governing and the case studies show that local policy networks may subsist also under...... hierarchical governing modes. Reasons why hierarchical governing modes prevail over network governing in some settings are identified pointing to both actor borne and structural factors. Output indicators of the four cases do not show that a particular governing mode is more efficient in its employment policy...

[Brain activitivation of euthymic patients with Type I bipolar disorder in resting state Default Mode Network].

Science.gov (United States)

Vargas, Cristian; Pineda, Julián; Calvo, Víctor; López-Jaramillo, Carlos

2014-01-01

As there are still doubts about brain connectivity in type I bipolar disorder (BID), resting-state functional magnetic resonance imaging (RS-fMRI) studies are necessary during euthymia for a better control of confounding factors. To evaluate the differences in brain activation between euthymic BID patients and control subjects using resting state- functional-magnetic resonance imaging (RS-fMRI), and to identify the lithium effect in these activations. A cross-sectional study was conducted on 21 BID patients (10 receiving lithium only, and 11 non-medicated) and 12 healthy control subjects, using RS fMRI and independent component analysis (ICA). Increased activation was found in the right hippocampus (P=.049) and posterior cingulate (P=.040) within the Default Mode Network (DMN) when BID and control group were compared. No statistically significant differences were identified between BID on lithium only therapy and non-medicated BID patients. The results suggest that there are changes in brain activation and connectivity in BID even during euthymic phase and mainly within the DMN network, which could be relevant in affect regulation. Copyright © 2013 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Aberrant default-mode network-hippocampus connectivity after sad memory-recall in remitted-depression

OpenAIRE

Figueroa, C.A.; Mocking, R.J.T.; Wingen, G.A. van; Martens, S.J.; Ruhe, H.G.; Schene, A.H.

2017-01-01

Abstract Rumination and cognitive reactivity (dysfunctional cognitions after sad mood-induction) remain high in remitted Major Depressive Disorder (MDD) and can contribute to new episodes. These factors have been linked to increased fMRI resting-state functional-connectivity within the Default-Mode Network (DMN). It remains unclear whether (I) increased DMN-connectivity persists during MDD-remission, and (II) whether sad mood-induction differentially affects DMN-connectivity in remitted-MDD v...

Structural and functional correlates of hypnotic depth and suggestibility.

Science.gov (United States)

McGeown, William Jonathan; Mazzoni, Giuliana; Vannucci, Manila; Venneri, Annalena

2015-02-28

This study explores whether self-reported depth of hypnosis and hypnotic suggestibility are associated with individual differences in neuroanatomy and/or levels of functional connectivity. Twenty-nine people varying in suggestibility were recruited and underwent structural, and after a hypnotic induction, functional magnetic resonance imaging at rest. We used voxel-based morphometry to assess the correlation of grey matter (GM) and white matter (WM) against the independent variables: depth of hypnosis, level of relaxation and hypnotic suggestibility. Functional networks identified with independent components analysis were regressed with the independent variables. Hypnotic depth ratings were positively correlated with GM volume in the frontal cortex and the anterior cingulate cortex (ACC). Hypnotic suggestibility was positively correlated with GM volume in the left temporal-occipital cortex. Relaxation ratings did not correlate significantly with GM volume and none of the independent variables correlated with regional WM volume measures. Self-reported deeper levels of hypnosis were associated with less connectivity within the anterior default mode network. Taken together, the results suggest that the greater GM volume in the medial frontal cortex and ACC, and lower connectivity in the DMN during hypnosis facilitate experiences of greater hypnotic depth. The patterns of results suggest that hypnotic depth and hypnotic suggestibility should not be considered synonyms. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Alterations of the default mode network connectivity in obsessive-compulsive personality disorder: A pilot study.

Science.gov (United States)

Coutinho, Joana; Goncalves, Oscar Filipe; Soares, José Miguel; Marques, Paulo; Sampaio, Adriana

2016-10-30

Obsessive-compulsive personality (OCPD) disorder is characterized by a pattern of excessive self-control, perfectionism and behavioral and cognitive rigidity. Despite the fact that OCPD is the most common personality disorder in the general population, published studies looking at the brain correlates of this disorder are practically nonexistent. The main goal of this study was to analyze the presence of brain alterations in OCPD when compared to healthy controls, specifically at the level of the Default Mode Network (DMN). The DMN is a well-established resting state network which was found to be associated with psychological processes that may play a key role in OCPD (e.g., self-awareness, episodic future thinking and mental simulation). Ten individuals diagnosed with OCPD and ten healthy controls underwent a clinical assessment interview and a resting-state functional magnetic resonance imaging (fMRI) acquisition. The results show that OCPD patients presented an increased functional connectivity in the precuneus (i.e., a posterior node of the DMN), known to be involved in the retrieval manipulation of past events in order to solve current problems and develop plans for the future. These results suggest that this key node of the DMN may play an important role in the pathophysiology of OCPD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Functional reorganization of the default mode network across chronic pain conditions.

Directory of Open Access Journals (Sweden)

Marwan N Baliki

Full Text Available Chronic pain is associated with neuronal plasticity. Here we use resting-state functional magnetic resonance imaging to investigate functional changes in patients suffering from chronic back pain (CBP, complex regional pain syndrome (CRPS and knee osteoarthritis (OA. We isolated five meaningful resting-state networks across the groups, of which only the default mode network (DMN exhibited deviations from healthy controls. All patient groups showed decreased connectivity of medial prefrontal cortex (MPFC to the posterior constituents of the DMN, and increased connectivity to the insular cortex in proportion to the intensity of pain. Multiple DMN regions, especially the MPFC, exhibited increased high frequency oscillations, conjoined with decreased phase locking with parietal regions involved in processing attention. Both phase and frequency changes correlated to pain duration in OA and CBP patients. Thus chronic pain seems to reorganize the dynamics of the DMN and as such reflect the maladaptive physiology of different types of chronic pain.

Mind wandering away from pain dynamically engages antinociceptive and default mode brain networks

OpenAIRE

Kucyi, Aaron; Salomons, Tim V.; Davis, Karen D.

2013-01-01

The mind easily wanders away from mundane tasks, but pain is presumed to automatically capture attention. We demonstrate that individuals differ in how often their minds spontaneously wander away from pain and that these differences are associated with the disruptive effect of pain on cognitive performance. Brain–behavior relationships underscore these individual differences. When people’s minds wander away from pain, there are increased activations of the default mode network (DMN) and stron...

Real-time networked control of an industrial robot manipulator via discrete-time second-order sliding modes

Science.gov (United States)

Massimiliano Capisani, Luca; Facchinetti, Tullio; Ferrara, Antonella

2010-08-01

This article presents the networked control of a robotic anthropomorphic manipulator based on a second-order sliding mode technique, where the control objective is to track a desired trajectory for the manipulator. The adopted control scheme allows an easy and effective distribution of the control algorithm over two networked machines. While the predictability of real-time tasks execution is achieved by the Soft Hard Real-Time Kernel (S.Ha.R.K.) real-time operating system, the communication is established via a standard Ethernet network. The performances of the control system are evaluated under different experimental system configurations using, to perform the experiments, a COMAU SMART3-S2 industrial robot, and the results are analysed to put into evidence the robustness of the proposed approach against possible network delays, packet losses and unmodelled effects.

Impaired consciousness is linked to changes in effective connectivity of the posterior cingulate cortex within the default mode network.

Science.gov (United States)

Crone, Julia Sophia; Schurz, Matthias; Höller, Yvonne; Bergmann, Jürgen; Monti, Martin; Schmid, Elisabeth; Trinka, Eugen; Kronbichler, Martin

2015-04-15

The intrinsic connectivity of the default mode network has been associated with the level of consciousness in patients with severe brain injury. Especially medial parietal regions are considered to be highly involved in impaired consciousness. To better understand what aspect of this intrinsic architecture is linked to consciousness, we applied spectral dynamic causal modeling to assess effective connectivity within the default mode network in patients with disorders of consciousness. We included 12 controls, 12 patients in minimally conscious state and 13 in vegetative state in this study. For each subject, we first defined the four key regions of the default mode network employing a subject-specific independent component analysis approach. The resulting regions were then included as nodes in a spectral dynamic causal modeling analysis in order to assess how the causal interactions across these regions as well as the characteristics of neuronal fluctuations change with the level of consciousness. The resulting pattern of interaction in controls identified the posterior cingulate cortex as the main driven hub with positive afferent but negative efferent connections. In patients, this pattern appears to be disrupted. Moreover, the vegetative state patients exhibit significantly reduced self-inhibition and increased oscillations in the posterior cingulate cortex compared to minimally conscious state and controls. Finally, the degree of self-inhibition and strength of oscillation in this region is correlated with the level of consciousness. These findings indicate that the equilibrium between excitatory connectivity towards posterior cingulate cortex and its feedback projections is a key aspect of the relationship between alterations in consciousness after severe brain injury and the intrinsic functional architecture of the default mode network. This impairment might be principally due to the disruption of the mechanisms underlying self-inhibition and neuronal

Shared and disorder-specific task-positive and default mode network dysfunctions during sustained attention in paediatric Attention-Deficit/Hyperactivity Disorder and obsessive/compulsive disorder

Directory of Open Access Journals (Sweden)

Luke J. Norman

2017-01-01

Full Text Available Patients with Attention-Deficit/Hyperactivity Disorder (ADHD and obsessive/compulsive disorder (OCD share problems with sustained attention, and are proposed to share deficits in switching between default mode and task positive networks. The aim of this study was to investigate shared and disorder-specific brain activation abnormalities during sustained attention in the two disorders. Twenty boys with ADHD, 20 boys with OCD and 20 age-matched healthy controls aged between 12 and 18 years completed a functional magnetic resonance imaging (fMRI version of a parametrically modulated sustained attention task with a progressively increasing sustained attention load. Performance and brain activation were compared between groups. Only ADHD patients were impaired in performance. Group by sustained attention load interaction effects showed that OCD patients had disorder-specific middle anterior cingulate underactivation relative to controls and ADHD patients, while ADHD patients showed disorder-specific underactivation in left dorsolateral prefrontal cortex/dorsal inferior frontal gyrus (IFG. ADHD and OCD patients shared left insula/ventral IFG underactivation and increased activation in posterior default mode network relative to controls, but had disorder-specific overactivation in anterior default mode regions, in dorsal anterior cingulate for ADHD and in anterior ventromedial prefrontal cortex for OCD. In sum, ADHD and OCD patients showed mostly disorder-specific patterns of brain abnormalities in both task positive salience/ventral attention networks with lateral frontal deficits in ADHD and middle ACC deficits in OCD, as well as in their deactivation patterns in medial frontal DMN regions. The findings suggest that attention performance in the two disorders is underpinned by disorder-specific activation patterns.

Preserved functional connectivity in the default mode and salience networks is associated with youthful memory in superaging

OpenAIRE

Barrett, Lisa; Zhang, Jiahe; Andreano, Joseph; Dickerson, Bradford; Touroutoglou, Alexandra

2018-01-01

'Superagers' are older adults who, despite their advanced age, maintain youthful memory. Previous morphometry studies revealed multiple default mode network (DMN) and salience network (SN) regions whose cortical thickness is preserved in superagers and correlates with memory performance. In this study, we examined the intrinsic functional connectivity within DMN and SN in 41 young (24.5 ± 3.6 years old) and 40 elderly adults (66.9 ± 5.5 years old). As in prior studies, superaging was defined ...

Prefrontal Cortex Networks Shift from External to Internal Modes during Learning

Science.gov (United States)

Brincat, Scott L.

2016-01-01

As we learn about items in our environment, their neural representations become increasingly enriched with our acquired knowledge. But there is little understanding of how network dynamics and neural processing related to external information changes as it becomes laden with “internal” memories. We sampled spiking and local field potential activity simultaneously from multiple sites in the lateral prefrontal cortex (PFC) and the hippocampus (HPC)—regions critical for sensory associations—of monkeys performing an object paired-associate learning task. We found that in the PFC, evoked potentials to, and neural information about, external sensory stimulation decreased while induced beta-band (∼11–27 Hz) oscillatory power and synchrony associated with “top-down” or internal processing increased. By contrast, the HPC showed little evidence of learning-related changes in either spiking activity or network dynamics. The results suggest that during associative learning, PFC networks shift their resources from external to internal processing. SIGNIFICANCE STATEMENT As we learn about items in our environment, their representations in our brain become increasingly enriched with our acquired “top-down” knowledge. We found that in the prefrontal cortex, but not the hippocampus, processing of external sensory inputs decreased while internal network dynamics related to top-down processing increased. The results suggest that during learning, prefrontal cortex networks shift their resources from external (sensory) to internal (memory) processing. PMID:27629722

Aberrant cerebellar connectivity in motor and association networks in schizophrenia

Directory of Open Access Journals (Sweden)

Ann K. Shinn

2015-03-01

Full Text Available Schizophrenia is a devastating illness characterized by disturbances in multiple domains. The cerebellum is involved in both motor and non-motor functions, and the cognitive dysmetria and dysmetria of thought models propose that abnormalities of the cerebellum may contribute to schizophrenia signs and symptoms. The cerebellum and cerebral cortex are reciprocally connected via a modular, closed-loop network architecture, but few schizophrenia neuroimaging studies have taken into account the topographical and functional heterogeneity of the cerebellum. In this study, using a previously defined 17-network cerebral cortical parcellation system as the basis for our functional connectivity seeds, we systematically investigated connectivity abnormalities within the cerebellum of 44 schizophrenia patients and 28 healthy control participants. We found selective alterations in cerebro-cerebellar functional connectivity. Specifically, schizophrenia patients showed decreased cerebro-cerebellar functional connectivity in higher level association networks (ventral attention, salience, control, and default mode networks relative to healthy control participants. Schizophrenia patients also showed increased cerebro-cerebellar connectivity in somatomotor and default mode networks, with the latter showing no overlap with the regions found to be hypoconnected within the same default mode network. Finally, we found evidence to suggest that somatomotor and default mode networks may be inappropriately linked in schizophrenia. The relationship of these dysconnectivities to schizophrenia symptoms, such as neurological soft signs and altered sense of agency, is discussed. We conclude that the cerebellum ought to be considered for analysis in all future studies of network abnormalities in SZ, and further suggest the cerebellum as a potential target for further elucidation, and possibly treatment, of the underlying mechanisms and network abnormalities producing symptoms of

Inhibition of Information Flow to the Default Mode Network During Self-Reference Versus Reference to Others.

Science.gov (United States)

Soch, Joram; Deserno, Lorenz; Assmann, Anne; Barman, Adriana; Walter, Henrik; Richardson-Klavehn, Alan; Schott, Björn H

2017-08-01

The default mode network (DMN), a network centered around the cortical midline, shows deactivation during most cognitive tasks and pronounced resting-state connectivity, but is actively engaged in self-reference and social cognition. It is, however, yet unclear how information reaches the DMN during social cognitive processing. Here, we addressed this question using dynamic causal modeling (DCM) of functional magnetic resonance imaging (fMRI) data acquired during self-reference (SR) and reference to others (OR). Both conditions engaged the left inferior frontal gyrus (LIFG), most likely reflecting semantic processing. Within the DMN, self-reference preferentially elicited rostral anterior cingulate and ventromedial prefrontal cortex (rACC/vmPFC) activity, whereas OR engaged posterior cingulate and precuneus (PCC/PreCun). DCM revealed that the regulation of information flow to the DMN was primarily inhibitory. Most prominently, SR elicited inhibited information flow from the LIFG to the PCC/PreCun, while OR was associated with suppression of the connectivity from the LIFG to the rACC/vmPFC. These results suggest that task-related DMN activation is enabled by inhibitory down-regulation of task-irrelevant information flow when switching from rest to stimulus-specific processing. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Analytical modeling of mode selection and power control for underlay D2D communication in cellular networks

KAUST Repository

Elsawy, Hesham

2014-11-01

Device-to-device (D2D) communication enables the user equipments (UEs) located in close proximity to bypass the cellular base stations (BSs) and directly connect to each other, and thereby, offload traffic from the cellular infrastructure. D2D communication can improve spatial frequency reuse and energy efficiency in cellular networks. This paper presents a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with a flexible mode selection scheme along with truncated channel inversion power control. The developed framework is used to analyze and understand how the underlaying D2D communication affects the cellular network performance. Through comprehensive numerical analysis, we investigate the expected performance gains and provide guidelines for selecting the network parameters.

The Effects of Suggestibility on Relaxation.

Science.gov (United States)

Rickard, Henry C.; And Others

1985-01-01

Selected undergraduates (N=32) on the basis of Creative Imagination Scale scores and randomly assigned high and low suggestibility subjects to progressive relaxation (PR) and suggestions of relaxation (SR) training modes. Results revealed a significant pre-post relaxation effect, and main efffects for both suggestibility and training mode. (NRB)

Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism

Directory of Open Access Journals (Sweden)

Tae-Hyoung Kim

2017-01-01

Full Text Available This paper studies the metaheuristic optimizer-based direct identification of a multiple-mode system consisting of a finite set of linear regression representations of subsystems. To this end, the concept of a multiple-mode linear regression model is first introduced, and its identification issues are established. A method for reducing the identification problem for multiple-mode models to an optimization problem is also described in detail. Then, to overcome the difficulties that arise because the formulated optimization problem is inherently ill-conditioned and nonconvex, the cyclic-network-topology-based constrained particle swarm optimizer (CNT-CPSO is introduced, and a concrete procedure for the CNT-CPSO-based identification methodology is developed. This scheme requires no prior knowledge of the mode transitions between subsystems and, unlike some conventional methods, can handle a large amount of data without difficulty during the identification process. This is one of the distinguishing features of the proposed method. The paper also considers an extension of the CNT-CPSO-based identification scheme that makes it possible to simultaneously obtain both the optimal parameters of the multiple submodels and a certain decision parameter involved in the mode transition criteria. Finally, an experimental setup using a DC motor system is established to demonstrate the practical usability of the proposed metaheuristic optimizer-based identification scheme for developing a multiple-mode linear regression model.

Default Mode Dynamics for Global Functional Integration.

Science.gov (United States)

Vatansever, Deniz; Menon, David K; Manktelow, Anne E; Sahakian, Barbara J; Stamatakis, Emmanuel A

2015-11-18

The default mode network (DMN) has been traditionally assumed to hinder behavioral performance in externally focused, goal-directed paradigms and to provide no active contribution to human cognition. However, recent evidence suggests greater DMN activity in an array of tasks, especially those that involve self-referential and memory-based processing. Although data that robustly demonstrate a comprehensive functional role for DMN remains relatively scarce, the global workspace framework, which implicates the DMN in global information integration for conscious processing, can potentially provide an explanation for the broad range of higher-order paradigms that report DMN involvement. We used graph theoretical measures to assess the contribution of the DMN to global functional connectivity dynamics in 22 healthy volunteers during an fMRI-based n-back working-memory paradigm with parametric increases in difficulty. Our predominant finding is that brain modularity decreases with greater task demands, thus adapting a more global workspace configuration, in direct relation to increases in reaction times to correct responses. Flexible default mode regions dynamically switch community memberships and display significant changes in their nodal participation coefficient and strength, which may reflect the observed whole-brain changes in functional connectivity architecture. These findings have important implications for our understanding of healthy brain function, as they suggest a central role for the DMN in higher cognitive processing. The default mode network (DMN) has been shown to increase its activity during the absence of external stimulation, and hence was historically assumed to disengage during goal-directed tasks. Recent evidence, however, implicates the DMN in self-referential and memory-based processing. We provide robust evidence for this network's active contribution to working memory by revealing dynamic reconfiguration in its interactions with other networks

Temporal lobe epilepsy and surgery selectively alter the dorsal, not the ventral, default-mode network

Directory of Open Access Journals (Sweden)

Gaelle Eve Doucet

2014-03-01

Full Text Available The default-mode network (DMN is a major resting-state network. It can be divided in 2 distinct networks: one is composed of dorsal and anterior regions (referred to as the dorsal DMN, dDMN, while the other involves the more posterior regions (referred to as the ventral DMN, vDMN. To date, no studies have investigated the potentially distinct impact of temporal lobe epilepsy (TLE on these networks. In this context, we explored the effect of TLE and anterior temporal lobectomy (ATL on the dDMN and vDMN. We utilized 2 resting-state fMRI sessions from left, right TLE patients (pre-/post-surgery and normal controls (NCs, sessions 1/2. Using independent component analysis, we identified the 2 networks. We then evaluated for differences in spatial extent for each network between the groups, and across the scanning sessions. The results revealed that, pre-surgery, the dDMN showed larger differences between the three groups than the vDMN, and more particularly between right and left TLE than between the TLE patients and controls. In terms of change post-surgery, in both TLE groups, the dDMN also demonstrated larger changes than the vDMN. For the vDMN, the only changes involved the resected temporal lobe for each ATL group. For the dDMN, the left ATL group showed post-surgical increases in several regions outside the ictal temporal lobe. In contrast, the right ATL group displayed a large reduction in the frontal cortex. The results highlight that the 2 DMNs are not impacted by TLE and ATL in an equivalent fashion. Importantly, the dDMN was the more affected, with right ATL having a more deleterious effects on the dDMN than left ATL. We are the first to highlight that the dDMN more strongly bears the negative impact of TLE than the vDMN, suggesting there is an interaction between the side of pathology and DM subnetwork activity. Our findings have implications for understanding the impact TLE and subsequent ATL on the functions implemented by the distinct

Age-Related Differences in Dynamic Interactions Among Default Mode, Frontoparietal Control, and Dorsal Attention Networks during Resting-State and Interference Resolution

Science.gov (United States)

Avelar-Pereira, Bárbara; Bäckman, Lars; Wåhlin, Anders; Nyberg, Lars; Salami, Alireza

2017-01-01

Resting-state fMRI (rs-fMRI) can identify large-scale brain networks, including the default mode (DMN), frontoparietal control (FPN) and dorsal attention (DAN) networks. Interactions among these networks are critical for supporting complex cognitive functions, yet the way in which they are modulated across states is not well understood. Moreover, it remains unclear whether these interactions are similarly affected in aging regardless of cognitive state. In this study, we investigated age-related differences in functional interactions among the DMN, FPN and DAN during rest and the Multi-Source Interference task (MSIT). Networks were identified using independent component analysis (ICA), and functional connectivity was measured during rest and task. We found that the FPN was more coupled with the DMN during rest and with the DAN during the MSIT. The degree of FPN-DMN connectivity was lower in older compared to younger adults, whereas no age-related differences were observed in FPN-DAN connectivity in either state. This suggests that dynamic interactions of the FPN are stable across cognitive states. The DMN and DAN were anti correlated and age-sensitive during the MSIT only, indicating variation in a task-dependent manner. Increased levels of anticorrelation from rest to task also predicted successful interference resolution. Additional analyses revealed that the degree of DMN-DAN anticorrelation during the MSIT was associated to resting cerebral blood flow (CBF) within the DMN. This suggests that reduced DMN neural activity during rest underlies an impaired ability to achieve higher levels of anticorrelation during a task. Taken together, our results suggest that only parts of age-related differences in connectivity are uncovered at rest and thus, should be studied in the functional connectome across multiple states for a more comprehensive picture. PMID:28588476

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

Science.gov (United States)

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

2017-07-10

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

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

Science.gov (United States)

Vemuri, Kavita; Surampudi, Bapi Raju

2015-08-01

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

The relationship between default mode network connectivity and social functioning in individuals at familial high-risk for schizophrenia

OpenAIRE

Dodell-Feder, David; DeLisi, Lynn E.; Hooker, Christine I.

2014-01-01

Unaffected first-degree relatives of individuals with schizophrenia (i.e., those at familial high-risk [FHR]), demonstrate social dysfunction qualitatively similar though less severe than that of their affected relatives. These social difficulties may be the consequence of genetically conferred disruption to aspects of the default mode network (DMN), such as the dMPFC subsystem, which overlaps with the network of brain regions recruited during social cognitive processes. In the present study,...

Specific default mode subnetworks support mentalizing as revealed through opposing network recruitment by social and semantic FMRI tasks.

Science.gov (United States)

Hyatt, Christopher J; Calhoun, Vince D; Pearlson, Godfrey D; Assaf, Michal

2015-08-01

The ability to attribute mental states to others, or "mentalizing," is posited to involve specific subnetworks within the overall default mode network (DMN), but this question needs clarification. To determine which default mode (DM) subnetworks are engaged by mentalizing processes, we assessed task-related recruitment of DM subnetworks. Spatial independent component analysis (sICA) applied to fMRI data using relatively high-order model (75 components). Healthy participants (n = 53, ages 17-60) performed two fMRI tasks: an interactive game involving mentalizing (Domino), a semantic memory task (SORT), and a resting state fMRI scan. sICA of the two tasks split the DMN into 10 subnetworks located in three core regions: medial prefrontal cortex (mPFC; five subnetworks), posterior cingulate/precuneus (PCC/PrC; three subnetworks), and bilateral temporoparietal junction (TPJ). Mentalizing events increased recruitment in five of 10 DM subnetworks, located in all three core DMN regions. In addition, three of these five DM subnetworks, one dmPFC subnetwork, one PCC/PrC subnetwork, and the right TPJ subnetwork, showed reduced recruitment by semantic memory task events. The opposing modulation by the two tasks suggests that these three DM subnetworks are specifically engaged in mentalizing. Our findings, therefore, suggest the unique involvement of mentalizing processes in only three of 10 DM subnetworks, and support the importance of the dmPFC, PCC/PrC, and right TPJ in mentalizing as described in prior studies. © 2015 Wiley Periodicals, Inc.

Effect of cobratoxin binding on the normal mode vibration within acetylcholine binding protein.

Science.gov (United States)

Bertaccini, Edward J; Lindahl, Erik; Sixma, Titia; Trudell, James R

2008-04-01

Recent crystal structures of the acetylcholine binding protein (AChBP) have revealed surprisingly small structural alterations upon ligand binding. Here we investigate the extent to which ligand binding may affect receptor dynamics. AChBP is a homologue of the extracellular component of ligand-gated ion channels (LGICs). We have previously used an elastic network normal-mode analysis to propose a gating mechanism for the LGICs and to suggest the effects of various ligands on such motions. However, the difficulties with elastic network methods lie in their inability to account for the modest effects of a small ligand or mutation on ion channel motion. Here, we report the successful application of an elastic network normal mode technique to measure the effects of large ligand binding on receptor dynamics. The present calculations demonstrate a clear alteration in the native symmetric motions of a protein due to the presence of large protein cobratoxin ligands. In particular, normal-mode analysis revealed that cobratoxin binding to this protein significantly dampened the axially symmetric motion of the AChBP that may be associated with channel gating in the full nAChR. The results suggest that alterations in receptor dynamics could be a general feature of ligand binding.

Hybrid UWB and WiMAX radio-over-multi-mode fibre for in-building optical networks

International Nuclear Information System (INIS)

Perez, J; Llorente, R

2014-01-01

In this paper the use of hybrid WiMedia-defined ultra-wideband (UWB) and IEEE 802.16d WiMAX radio-over-fibre is proposed and experimentally demonstrated for multi-mode based in-building optical networks with the advantage of great immunity to optical transmission impairments. In the proposed approach, spectral coexistence of both signals must be achieved with negligible mutual interference. The experimental study performed addressed an indoor configuration with 50 μm multi-mode fibres (MMF) and 850 nm vertical-cavity surface-emitting laser (VCSEL) transmitters. The results indicate that the impact of the wireless convergence in radio-over-multi-mode fibre (RoMMF) is significant for UWB transmissions, mainly due to MMF dispersion and electrooptical (EO) devices with limited bandwidth. On the other hand, WiMAX transmission is feasible for a 300 m MMF and 30 m wireless link in the presence of UWB, with −31 dBm WiMAX EVM. (paper)

Shared atypical default mode and salience network functional connectivity between autism and schizophrenia.

Science.gov (United States)

Chen, Heng; Uddin, Lucina Q; Duan, Xujun; Zheng, Junjie; Long, Zhiliang; Zhang, Youxue; Guo, Xiaonan; Zhang, Yan; Zhao, Jingping; Chen, Huafu

2017-11-01

Schizophrenia and autism spectrum disorder (ASD) are two prevalent neurodevelopmental disorders sharing some similar genetic basis and clinical features. The extent to which they share common neural substrates remains unclear. Resting-state fMRI data were collected from 35 drug-naïve adolescent participants with first-episode schizophrenia (15.6 ± 1.8 years old) and 31 healthy controls (15.4 ± 1.6 years old). Data from 22 participants with ASD (13.1 ± 3.1 years old) and 21 healthy controls (12.9 ± 2.9 years old) were downloaded from the Autism Brain Imaging Data Exchange. Resting-state functional networks were constructed using predefined regions of interest. Multivariate pattern analysis combined with multi-task regression feature selection methods were conducted in two datasets separately. Classification between individuals with disorders and controls was achieved with high accuracy (schizophrenia dataset: accuracy = 83%; ASD dataset: accuracy = 80%). Shared atypical brain connections contributing to classification were mostly present in the default mode network (DMN) and salience network (SN). These functional connections were further related to severity of social deficits in ASD (p = 0.002). Distinct atypical connections were also more related to the DMN and SN, but showed different atypical connectivity patterns between the two disorders. These results suggest some common neural mechanisms contributing to schizophrenia and ASD, and may aid in understanding the pathology of these two neurodevelopmental disorders. Autism Res 2017, 10: 1776-1786. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Autism spectrum disorder (ASD) and schizophrenia are two common neurodevelopmental disorders which share several genetic and behavioral features. The present study identified common neural mechanisms contributing to ASD and schizophrenia using resting-state functional MRI data. The results may help to understand

Default Mode of Brain Function in Monkeys

Science.gov (United States)

Mantini, Dante; Gerits, Annelis; Nelissen, Koen; Durand, Jean-Baptiste; Joly, Olivier; Simone, Luciano; Sawamura, Hiromasa; Wardak, Claire; Orban, Guy A.; Buckner, Randy L.; Vanduffel, Wim

2013-01-01

Human neuroimaging has revealed a specific network of brain regions—the default-mode network (DMN)—that reduces its activity during goal-directed behavior. So far, evidence for a similar network in monkeys is mainly indirect, since, except for one positron emission tomography study, it is all based on functional connectivity analysis rather than activity increases during passive task states. Here, we tested whether a consistent DMN exists in monkeys using its defining property. We performed a meta-analysis of functional magnetic resonance imaging data collected in 10 awake monkeys to reveal areas in which activity consistently decreases when task demands shift from passive tasks to externally oriented processing. We observed task-related spatially specific deactivations across 15 experiments, implying in the monkey a functional equivalent of the human DMN. We revealed by resting-state connectivity that prefrontal and medial parietal regions, including areas 9/46d and 31, respectively, constitute the DMN core, being functionally connected to all other DMN areas. We also detected two distinct subsystems composed of DMN areas with stronger functional connections between each other. These clusters included areas 24/32, 8b, and TPOC and areas 23, v23, and PGm, respectively. Such a pattern of functional connectivity largely fits, but is not completely consistent with anatomical tract tracing data in monkeys. Also, analysis of afferent and efferent connections between DMN areas suggests a multisynaptic network structure. Like humans, monkeys increase activity during passive epochs in heteromodal and limbic association regions, suggesting that they also default to internal modes of processing when not actively interacting with the environment. PMID:21900574

Psychopathic traits associated with abnormal hemodynamic activity in salience and default mode networks during auditory oddball task.

Science.gov (United States)

Anderson, Nathaniel E; Maurer, J Michael; Steele, Vaughn R; Kiehl, Kent A

2018-06-01

Psychopathy is a personality disorder accompanied by abnormalities in emotional processing and attention. Recent theoretical applications of network-based models of cognition have been used to explain the diverse range of abnormalities apparent in psychopathy. Still, the physiological basis for these abnormalities is not well understood. A significant body of work has examined psychopathy-related abnormalities in simple attention-based tasks, but these studies have largely been performed using electrocortical measures, such as event-related potentials (ERPs), and they often have been carried out among individuals with low levels of psychopathic traits. In this study, we examined neural activity during an auditory oddball task using functional magnetic resonance imaging (fMRI) during a simple auditory target detection (oddball) task among 168 incarcerated adult males, with psychopathic traits assessed via the Hare Psychopathy Checklist-Revised (PCL-R). Event-related contrasts demonstrated that the largest psychopathy-related effects were apparent between the frequent standard stimulus condition and a task-off, implicit baseline. Negative correlations with interpersonal-affective dimensions (Factor 1) of the PCL-R were apparent in regions comprising default mode and salience networks. These findings support models of psychopathy describing impaired integration across functional networks. They additionally corroborate reports which have implicated failures of efficient transition between default mode and task-positive networks. Finally, they demonstrate a neurophysiological basis for abnormal mobilization of attention and reduced engagement with stimuli that have little motivational significance among those with high psychopathic traits.

Brains striving for coherence: Long-term cumulative plot formation in the default mode network.

Science.gov (United States)

Tylén, K; Christensen, P; Roepstorff, A; Lund, T; Østergaard, S; Donald, M

2015-11-01

Many everyday activities, such as engaging in conversation or listening to a story, require us to sustain attention over a prolonged period of time while integrating and synthesizing complex episodic content into a coherent mental model. Humans are remarkably capable of navigating and keeping track of all the parallel social activities of everyday life even when confronted with interruptions or changes in the environment. However, the underlying cognitive and neurocognitive mechanisms of such long-term integration and profiling of information remain a challenge to neuroscience. While brain activity is generally traceable within the short time frame of working memory (milliseconds to seconds), these integrative processes last for minutes, hours or even days. Here we report two experiments on story comprehension. Experiment I establishes a cognitive dissociation between our comprehension of plot and incidental facts in narratives: when episodic material allows for long-term integration in a coherent plot, we recall fewer factual details. However, when plot formation is challenged, we pay more attention to incidental facts. Experiment II investigates the neural underpinnings of plot formation. Results suggest a central role for the brain's default mode network related to comprehension of coherent narratives while incoherent episodes rather activate the frontoparietal control network. Moreover, an analysis of cortical activity as a function of the cumulative integration of narrative material into a coherent story reveals to linear modulations of right hemisphere posterior temporal and parietal regions. Together these findings point to key neural mechanisms involved in the fundamental human capacity for cumulative plot formation. Copyright © 2015 Elsevier Inc. All rights reserved.

Altered effective connectivity within default mode network in major depression disorder

Science.gov (United States)

Li, Liang; Li, Baojuan; Bai, Yuanhan; Wang, Huaning; Zhang, Linchuan; Cui, Longbiao; Lu, Hongbing

2016-03-01

Understanding the neural basis of Major Depressive Disorder (MDD) is important for the diagnosis and treatment of this mental disorder. The default mode network (DMN) is considered to be highly involved in the MDD. To find directed interaction between DMN regions associated with the development of MDD, the effective connectivity within the DMN of the MDD patients and matched healthy controls was estimated by using a recently developed spectral dynamic causal modeling. Sixteen patients with MDD and sixteen matched healthy control subjects were included in this study. While the control group underwent the resting state fMRI scan just once, all patients underwent resting state fMRI scans before and after two months' treatment. The spectral dynamic causal modeling was used to estimate directed connections between four DMN nodes. Statistical analysis on connection strengths indicated that efferent connections from the medial frontal cortex (MFC) to posterior cingulate cortex (PCC) and to right parietal cortex (RPC) were significant higher in pretreatment MDD patients than those of the control group. After two-month treatment, the efferent connections from the MFC decreased significantly, while those from the left parietal cortex (LPC) to MFC, PCC and RPC showed a significant increase. These findings suggest that the MFC may play an important role for inhibitory conditioning of the DMN, which was disrupted in MDD patients. It also indicates that disrupted suppressive function of the MFC could be effectively restored after two-month treatment.

Acupuncture induce the different modulation patterns of the default mode network: an fMRI study

Science.gov (United States)

Liu, Peng; Qin, Wei; Tian, Jie; Zhang, Yi

2009-02-01

According to Traditional Chinese Medicine (TCM) theory and certain clinical treatment reports, the sustained effects of acupuncture indeed exist, which may last several minutes or hours. Furthermore, increased attention has fallen on the sustained effects of acupuncture. Recently, it is reported that the sustained acupuncture effects may alter the default mode network (DMN). It raises interesting questions: whether the modulations of acupuncture effects to the DMN are still detected at other acupoints and whether the modulation patterns are different induced by different acupoints. In the present study, we wanted to investigate the questions. An experiment fMRI design was carried out on 36 subjects with the electroacupuncture stimulation (EAS) at the three acupoints: Guangming (GB37), Kunlun (BL60) and Jiaoxin (KI8) on the left leg. The data sets were analyzed by a data driven method named independent component analysis (ICA). The results indicated that the three acupoints stimulations may modulate the DMN. Moreover, the modulation patterns were distinct. We suggest the different modulation patterns on the DMN may attribute to the distinct functional effects of acupoints.

Stronger default mode network connectivity is associated with poorer clinical insight in youth at ultra high-risk for psychotic disorders.

Science.gov (United States)

Clark, Sarah V; Mittal, Vijay A; Bernard, Jessica A; Ahmadi, Aral; King, Tricia Z; Turner, Jessica A

2018-03-01

Impaired clinical insight (CI) is a common symptom of psychotic disorders and a promising treatment target. However, to date, our understanding of how variability in CI is tied to underlying brain dysfunction in the clinical high-risk period is limited. Developing a stronger conception of this link will be a vital first step for efforts to determine if CI can serve as a useful prognostic indicator. The current study investigated whether variability in CI is related to major brain networks in adolescents and young adults at ultra high-risk (UHR) of developing psychosis. Thirty-five UHR youth were administered structured clinical interviews as well as an assessment for CI and underwent resting-state magnetic resonance imaging scans. Functional connectivity was calculated in the default mode network (DMN) and fronto-parietal network (FPN), two major networks that are dysfunctional in psychosis and are hypothesized to affect insight. Greater DMN connectivity between the posterior cingulate/precuneus and ventromedial prefrontal cortex (DMN) was related to poorer CI (R 2 =0.399). There were no significant relationships between insight and the FPN. This is the first study to relate a major brain network to clinical insight before the onset of psychosis. Findings are consistent with evidence if a hyperconnected DMN in schizophrenia and UHR, and similar to a previous study of insight and connectivity in schizophrenia. Results suggest that a strongly connected DMN may be related to poor self-awareness of subthreshold psychotic symptoms in UHR adolescents and young adults. Copyright © 2017 Elsevier B.V. All rights reserved.

Default mode contributions to automated information processing.

Science.gov (United States)

Vatansever, Deniz; Menon, David K; Stamatakis, Emmanuel A

2017-11-28

Concurrent with mental processes that require rigorous computation and control, a series of automated decisions and actions govern our daily lives, providing efficient and adaptive responses to environmental demands. Using a cognitive flexibility task, we show that a set of brain regions collectively known as the default mode network plays a crucial role in such "autopilot" behavior, i.e., when rapidly selecting appropriate responses under predictable behavioral contexts. While applying learned rules, the default mode network shows both greater activity and connectivity. Furthermore, functional interactions between this network and hippocampal and parahippocampal areas as well as primary visual cortex correlate with the speed of accurate responses. These findings indicate a memory-based "autopilot role" for the default mode network, which may have important implications for our current understanding of healthy and adaptive brain processing.

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

Science.gov (United States)

Horne, Charlotte Mary; Norbury, Ray

2018-04-20

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

Restoring large-scale brain networks in PTSD and related disorders: a proposal for neuroscientifically-informed treatment interventions

Directory of Open Access Journals (Sweden)

Ruth A. Lanius

2015-03-01

Full Text Available Background: Three intrinsic connectivity networks in the brain, namely the central executive, salience, and default mode networks, have been identified as crucial to the understanding of higher cognitive functioning, and the functioning of these networks has been suggested to be impaired in psychopathology, including posttraumatic stress disorder (PTSD. Objective: 1 To describe three main large-scale networks of the human brain; 2 to discuss the functioning of these neural networks in PTSD and related symptoms; and 3 to offer hypotheses for neuroscientifically-informed interventions based on treating the abnormalities observed in these neural networks in PTSD and related disorders. Method: Literature relevant to this commentary was reviewed. Results: Increasing evidence for altered functioning of the central executive, salience, and default mode networks in PTSD has been demonstrated. We suggest that each network is associated with specific clinical symptoms observed in PTSD, including cognitive dysfunction (central executive network, increased and decreased arousal/interoception (salience network, and an altered sense of self (default mode network. Specific testable neuroscientifically-informed treatments aimed to restore each of these neural networks and related clinical dysfunction are proposed. Conclusions: Neuroscientifically-informed treatment interventions will be essential to future research agendas aimed at targeting specific PTSD and related symptoms.

An estimation of global solar p-mode frequencies from IRIS network data: 1989-1996

Science.gov (United States)

Serebryanskiy, A.; Ehgamberdiev, Sh.; Kholikov, Sh.; Fossat, E.; Gelly, B.; Schmider, F. X.; Grec, G.; Cacciani, A.; Palle, P. L.; Lazrek, M.; Hoeksema, J. T.

2001-06-01

The IRIS network has accumulated full disk helioseismological data since July 1989, i.e. a complete 11-year solar cycle. Since the last paper publishing a frequency list [A&A 317 (1997) L71], not only has the network acquired new data, but has also developed new co-operative programs with compatible instruments [Abstr. SOHO 6/GONG 98 Workshop (1998) 51], so that merging IRIS files with these co-operative program data sets has made possible the improvement of the overall duty cycle. This paper presents new estimations of low degree p-mode frequencies obtained from this IRIS++ data bank covering the period 1989-1996, as well as the variation of their main parameters along the total range of magnetic activity, from before the last maximum to the very minimum. A preliminary estimation of the peak profile asymmetries is also included.

Local structural properties and attribute characteristisc in 2-mode networks: p* models to map choices of theater events

NARCIS (Netherlands)

Agneessens, F.; Roose, H.

2008-01-01

Choices of plays made by theatergoers can be considered as a 2-mode or affiliation network. In this article we illustrate how p* models (an exponential family of distributions for random graphs) can be used to uncover patterns of choices. Based on audience research in three theater institutions in

Mind-wandering and alterations to default mode network connectivity when listening to naturalistic versus artificial sounds

OpenAIRE

Gould van Praag, CD; Garfinkel, SN; Sparasci, O; Mees, A; Philippides, AO; Ware, M; Ottaviani, C; Critchley, HD

2017-01-01

Naturalistic environments have been demonstrated to promote relaxation and wellbeing. We assess opposing theoretical accounts for these effects through investigation of autonomic arousal and alterations of activation and functional connectivity within the default mode network (DMN) of the brain while participants listened to sounds from artificial and natural environments. We found no evidence for increased DMN activity in the naturalistic compared to artificial or control condition, however,...

Reliability, Convergent Validity and Time Invariance of Default Mode Network Deviations in Early Adult Major Depressive Disorder

Directory of Open Access Journals (Sweden)

Katie L. Bessette

2018-06-01

Full Text Available There is substantial variability across studies of default mode network (DMN connectivity in major depressive disorder, and reliability and time-invariance are not reported. This study evaluates whether DMN dysconnectivity in remitted depression (rMDD is reliable over time and symptom-independent, and explores convergent relationships with cognitive features of depression. A longitudinal study was conducted with 82 young adults free of psychotropic medications (47 rMDD, 35 healthy controls who completed clinical structured interviews, neuropsychological assessments, and 2 resting-state fMRI scans across 2 study sites. Functional connectivity analyses from bilateral posterior cingulate and anterior hippocampal formation seeds in DMN were conducted at both time points within a repeated-measures analysis of variance to compare groups and evaluate reliability of group-level connectivity findings. Eleven hyper- (from posterior cingulate and 6 hypo- (from hippocampal formation connectivity clusters in rMDD were obtained with moderate to adequate reliability in all but one cluster (ICC's range = 0.50 to 0.76 for 16 of 17. The significant clusters were reduced with a principle component analysis (5 components obtained to explore these connectivity components, and were then correlated with cognitive features (rumination, cognitive control, learning and memory, and explicit emotion identification. At the exploratory level, for convergent validity, components consisting of posterior cingulate with cognitive control network hyperconnectivity in rMDD were related to cognitive control (inverse and rumination (positive. Components consisting of anterior hippocampal formation with social emotional network and DMN hypoconnectivity were related to memory (inverse and happy emotion identification (positive. Thus, time-invariant DMN connectivity differences exist early in the lifespan course of depression and are reliable. The nuanced results suggest a ventral

Robust sliding mode control for uncertain servo system using friction observer and recurrent fuzzy neural networks

International Nuclear Information System (INIS)

Han, Seong Ik; Jeong, Chan Se; Yang, Soon Yong

2012-01-01

A robust positioning control scheme has been developed using friction parameter observer and recurrent fuzzy neural networks based on the sliding mode control. As a dynamic friction model, the LuGre model is adopted for handling friction compensation because it has been known to capture sufficiently the properties of a nonlinear dynamic friction. A developed friction parameter observer has a simple structure and also well estimates friction parameters of the LuGre friction model. In addition, an approximation method for the system uncertainty is developed using recurrent fuzzy neural networks technology to improve the precision positioning degree. Some simulation and experiment provide the verification on the performance of a proposed robust control scheme

Robust sliding mode control for uncertain servo system using friction observer and recurrent fuzzy neural networks

Energy Technology Data Exchange (ETDEWEB)

Han, Seong Ik [Pusan National University, Busan (Korea, Republic of); Jeong, Chan Se; Yang, Soon Yong [University of Ulsan, Ulsan (Korea, Republic of)

2012-04-15

A robust positioning control scheme has been developed using friction parameter observer and recurrent fuzzy neural networks based on the sliding mode control. As a dynamic friction model, the LuGre model is adopted for handling friction compensation because it has been known to capture sufficiently the properties of a nonlinear dynamic friction. A developed friction parameter observer has a simple structure and also well estimates friction parameters of the LuGre friction model. In addition, an approximation method for the system uncertainty is developed using recurrent fuzzy neural networks technology to improve the precision positioning degree. Some simulation and experiment provide the verification on the performance of a proposed robust control scheme.

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

Directory of Open Access Journals (Sweden)

Donna L Murdaugh

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

Active tension network model suggests an exotic mechanical state realized in epithelial tissues

Science.gov (United States)

Noll, Nicholas; Mani, Madhav; Heemskerk, Idse; Streichan, Sebastian J.; Shraiman, Boris I.

2017-12-01

Mechanical interactions play a crucial role in epithelial morphogenesis, yet understanding the complex mechanisms through which stress and deformation affect cell behaviour remains an open problem. Here we formulate and analyse the active tension network (ATN) model, which assumes that the mechanical balance of cells within a tissue is dominated by cortical tension and introduces tension-dependent active remodelling of the cortex. We find that ATNs exhibit unusual mechanical properties. Specifically, an ATN behaves as a fluid at short times, but at long times supports external tension like a solid. Furthermore, an ATN has an extensively degenerate equilibrium mechanical state associated with a discrete conformal--`isogonal'--deformation of cells. The ATN model predicts a constraint on equilibrium cell geometries, which we demonstrate to approximately hold in certain epithelial tissues. We further show that isogonal modes are observed in the fruit fly embryo, accounting for the striking variability of apical areas of ventral cells and helping understand the early phase of gastrulation. Living matter realizes new and exotic mechanical states, the study of which helps to understand biological phenomena.

Energy-efficient orthogonal frequency division multiplexing-based passive optical network based on adaptive sleep-mode control and dynamic bandwidth allocation

Science.gov (United States)

Zhang, Chongfu; Xiao, Nengwu; Chen, Chen; Yuan, Weicheng; Qiu, Kun

2016-02-01

We propose an energy-efficient orthogonal frequency division multiplexing-based passive optical network (OFDM-PON) using adaptive sleep-mode control and dynamic bandwidth allocation. In this scheme, a bidirectional-centralized algorithm named the receiver and transmitter accurate sleep control and dynamic bandwidth allocation (RTASC-DBA), which has an overall bandwidth scheduling policy, is employed to enhance the energy efficiency of the OFDM-PON. The RTASC-DBA algorithm is used in an optical line terminal (OLT) to control the sleep mode of an optical network unit (ONU) sleep and guarantee the quality of service of different services of the OFDM-PON. The obtained results show that, by using the proposed scheme, the average power consumption of the ONU is reduced by ˜40% when the normalized ONU load is less than 80%, compared with the average power consumption without using the proposed scheme.

What we talk about when we talk about the default mode network

Directory of Open Access Journals (Sweden)

Felicity eCallard

2014-08-01

Full Text Available The default mode network (DMN has been widely defined as a set of brain regions that are engaged when people are in a ‘resting state’ (left to themselves in a scanner, with no explicit task instruction. The network emerged as a scientific object in the early twenty-first century, and in just over a decade has become the focus of intense empirical and conceptual neuroscientific inquiry. In this Perspective, we contribute to the work of critical neuroscience by providing brief reflections on the birth, working life, and future of the DMN. We consider: how the DMN emerged through the convergence of distinct lines of scientific investigation; controversies surrounding the definition, function and localization of the DMN; and the lines of interdisciplinary investigation that the DMN has helped to enable. We conclude by arguing that one of the most pressing issues in the field in 2014 is to understand how the mechanisms of thought are related to the function of brain dynamics. While the DMN has been central in allowing the field to reach this point, it is not inevitable that the DMN itself will remain at the heart of future investigations of this complex problem.

Dysfunctional Default Mode Network in Methadone Treated Patients Who Have a Higher Heroin Relapse Risk.

Science.gov (United States)

Li, Wei; Li, Qiang; Wang, Defeng; Xiao, Wei; Liu, Kai; Shi, Lin; Zhu, Jia; Li, Yongbin; Yan, Xuejiao; Chen, Jiajie; Ye, Jianjun; Li, Zhe; Wang, Yarong; Wang, Wei

2015-10-15

The purpose of this study was to identify whether heroin relapse is associated with changes in the functional connectivity of the default mode network (DMN) during methadone maintenance treatment (MMT). Resting-state functional magnetic resonance imaging (fMRI) data of chronic heroin relapsers (HR) (12 males, 1 female, age: 36.1 ± 6.9 years) and abstainers (HA) (11males, 2 female; age: 42.1 ± 8.1 years) were investigated with an independent component analysis to address the functional connectivity of their DMN. Group comparison was then performed between the relapsers and abstainers. Our study found that the left inferior temporal gyrus and the right superior occipital gyrus associated with DMN showed decreased functional connectivity in HR when compared with HA, while the left precuneus and the right middle cingulum had increased functional connectivity. Mean intensity signal, extracted from left inferior temporal gyrus of HR patients, showed a significant negative correlation corresponding to the degree of heroin relapse. These findings suggest that altered functional connectivity of DMN may contribute to the potential neurobiological mechanism(s) of heroin relapse and have a predictive value concerning heroin relapse under MMT.

Antidepressants normalize the default mode network in patients with dysthymia.

Science.gov (United States)

Posner, Jonathan; Hellerstein, David J; Gat, Inbal; Mechling, Anna; Klahr, Kristin; Wang, Zhishun; McGrath, Patrick J; Stewart, Jonathan W; Peterson, Bradley S

2013-04-01

The default mode network (DMN) is a collection of brain regions that reliably deactivate during goal-directed behaviors and is more active during a baseline, or so-called resting, condition. Coherence of neural activity, or functional connectivity, within the brain's DMN is increased in major depressive disorder relative to healthy control (HC) subjects; however, whether similar abnormalities are present in persons with dysthymic disorder (DD) is unknown. Moreover, the effect of antidepressant medications on DMN connectivity in patients with DD is also unknown. To use resting-state functional-connectivity magnetic resonance imaging (MRI) to study (1) the functional connectivity of the DMN in subjects with DD vs HC participants and (2) the effects of antidepressant therapy on DMN connectivity. After collecting baseline MRI scans from subjects with DD and HC participants, we enrolled the participants with DD into a 10-week prospective, double-blind, placebo-controlled trial of duloxetine and collected MRI scans again at the conclusion of the study. Enrollment occurred between 2007 and 2011. University research institute. Volunteer sample of 41 subjects with DD and 25 HC participants aged 18 to 53 years. Control subjects were group matched to patients with DD by age and sex. We used resting-state functional-connectivity MRI to measure the functional connectivity of the brain's DMN in persons with DD compared with HC subjects, and we examined the effects of treatment with duloxetine vs placebo on DMN connectivity. Of the 41 subjects with DD, 32 completed the clinical trial and MRI scans, along with the 25 HC participants. At baseline, we found that the coherence of neural activity within the brain's DMN was greater in persons with DD compared with HC subjects. Following a 10-week clinical trial, we found that treatment with duloxetine, but not placebo, normalized DMN connectivity. The baseline imaging findings are consistent with those found in patients with major

Individual variation in intentionality in the mind-wandering state is reflected in the integration of the default-mode, fronto-parietal, and limbic networks.

Science.gov (United States)

Golchert, Johannes; Smallwood, Jonathan; Jefferies, Elizabeth; Seli, Paul; Huntenburg, Julia M; Liem, Franziskus; Lauckner, Mark E; Oligschläger, Sabine; Bernhardt, Boris C; Villringer, Arno; Margulies, Daniel S

2017-02-01

Mind-wandering has a controversial relationship with cognitive control. Existing psychological evidence supports the hypothesis that episodes of mind-wandering reflect a failure to constrain thinking to task-relevant material, as well the apparently alternative view that control can facilitate the expression of self-generated mental content. We assessed whether this apparent contradiction arises because of a failure to consider differences in the types of thoughts that occur during mind-wandering, and in particular, the associated level of intentionality. Using multi-modal magnetic resonance imaging (MRI) analysis, we examined the cortical organisation that underlies inter-individual differences in descriptions of the spontaneous or deliberate nature of mind-wandering. Cortical thickness, as well as functional connectivity analyses, implicated regions relevant to cognitive control and regions of the default-mode network for individuals who reported high rates of deliberate mind-wandering. In contrast, higher reports of spontaneous mind-wandering were associated with cortical thinning in parietal and posterior temporal regions in the left hemisphere (which are important in the control of cognition and attention) as well as heightened connectivity between the intraparietal sulcus and a region that spanned limbic and default-mode regions in the ventral inferior frontal gyrus. Finally, we observed a dissociation in the thickness of the retrosplenial cortex/lingual gyrus, with higher reports of spontaneous mind-wandering being associated with thickening in the left hemisphere, and higher repots of deliberate mind-wandering with thinning in the right hemisphere. These results suggest that the intentionality of the mind-wandering state depends on integration between the control and default-mode networks, with more deliberation being associated with greater integration between these systems. We conclude that one reason why mind-wandering has a controversial relationship

Default mode network in young male adults with autism spectrum disorder: Relationship with autism spectrum traits

OpenAIRE

Jung, Minyoung; Kosaka, Hirotaka; Saito, Daisuke N; Ishitobi, Makoto; Morita, Tomoyo; Inohara, Keisuke; Asano, Mizuki; Arai, Sumiyoshi; Munesue, Toshio; Tomoda, Akemi; Wada, Yuji; Sadato, Norihiro; Okazawa, Hidehiko; Iidaka, Tetsuya

2014-01-01

Background: Autism spectrum traits are postulated to lie on a continuum that extends between individuals with autism and individuals with typical development (TD). Social cognition properties that are deeply associated with autism spectrum traits have been linked to functional connectivity between regions within the brain's default mode network (DMN). Previous studies have shown that the resting-state functional connectivities (rs-FCs) of DMN are low and show negative correlation with the lev...

Cognitive and behavioral comorbidities in Rolandic epilepsy and their relation with default mode network's functional connectivity and organization.

Science.gov (United States)

Ofer, Isabell; Jacobs, Julia; Jaiser, Nathalie; Akin, Burak; Hennig, Jürgen; Schulze-Bonhage, Andreas; LeVan, Pierre

2018-01-01

Rolandic epilepsy (RE) is characterized by typical interictal-electroencephalogram (EEG) patterns mainly localized in centrotemporal and parietooccipital areas. An aberrant intrinsic organization of the default mode network (DMN) due to repeated disturbances from spike-generating areas may be able to account for specific cognitive deficits and behavioral problems in RE. The aim of the present study was to investigate cognitive development (CD) and socioemotional development (SED) in patients with RE during active disease in relation to DMN connectivity and network topology. In 10 children with RE and active EEG, CD was assessed using the Wechsler Intelligence Scale for Children-IV (WISC-IV); SED was assessed using the Fünf-Faktoren-Fragebogen für Kinder (FFFK), a Big-Five inventory for the assessment of personality traits in children. Functional connectivity (FC) in the DMN was determined from a 15-minute resting state functional magnetic resonance imaging (fMRI), and network properties were calculated using standard graph-theoretical measures. More severe deficits of verbal abilities tended to be associated with an earlier age at epilepsy onset, but were not directly related to the number of seizures and disease duration. Nonetheless, at the network level, disease duration was associated with alterations of the efficiency and centrality of parietal network nodes and midline structures. Particularly, centrality of the left inferior parietal lobe (IPL) was found to be linked with CD. Reduced centrality of the left IPL and alterations supporting a rather segregated processing within DMN's subsystems was associated with a more favorable CD. A more complicated SED was associated with high seizure frequency and long disease duration, and revealed links with a less favorable CD. An impaired CD and - because of their interrelation - SED might be mediated by a common pathomechanism reflected in an aberrant organization, and thus, a potential functional deficit of the DMN

The default mode network and recurrent depression: a neurobiological model of cognitive risk factors.

Science.gov (United States)

Marchetti, Igor; Koster, Ernst H W; Sonuga-Barke, Edmund J; De Raedt, Rudi

2012-09-01

A neurobiological account of cognitive vulnerability for recurrent depression is presented based on recent developments of resting state neural networks. We propose that alterations in the interplay between task positive (TP) and task negative (TN) elements of the Default Mode Network (DMN) act as a neurobiological risk factor for recurrent depression mediated by cognitive mechanisms. In the framework, depression is characterized by an imbalance between TN-TP components leading to an overpowering of TP by TN activity. The TN-TP imbalance is associated with a dysfunctional internally-focused cognitive style as well as a failure to attenuate TN activity in the transition from rest to task. Thus we propose the TN-TP imbalance as overarching neural mechanism involved in crucial cognitive risk factors for recurrent depression, namely rumination, impaired attentional control, and cognitive reactivity. During remission the TN-TP imbalance persists predisposing to vulnerability of recurrent depression. Empirical data to support this model is reviewed. Finally, we specify how this framework can guide future research efforts.

Income change alters default mode network connectivity for adolescents in poverty

Directory of Open Access Journals (Sweden)

David G. Weissman

2018-04-01

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

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

Science.gov (United States)

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

2018-04-01

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

Functional MRI Assessment of Task-Induced Deactivation of the Default Mode Network in Alzheimer?s Disease and At-Risk Older Individuals

OpenAIRE

Pihlajam?ki, Maija; Sperling, Reisa A.

2009-01-01

Alzheimer’s disease (AD) is the most common form of dementia in old age, and is characterized by prominent impairment of episodic memory. Recent functional imaging studies in AD have demonstrated alterations in a distributed network of brain regions supporting memory function, including regions of the default mode network. Previous positron emission tomography studies of older individuals at risk for AD have revealed hypometabolism of association cortical regions similar to the metabolic abno...

Sliding Mode Control for NSVs with Input Constraint Using Neural Network and Disturbance Observer

Directory of Open Access Journals (Sweden)

Yan-long Zhou

2013-01-01

Full Text Available The sliding mode control (SMC scheme is proposed for near space vehicles (NSVs with strong nonlinearity, high coupling, parameter uncertainty, and unknown time-varying disturbance based on radial basis function neural networks (RBFNNs and the nonlinear disturbance observer (NDO. Considering saturation characteristic of rudders, RBFNNs are constructed as a compensator to overcome the saturation nonlinearity. The stability of the closed-loop system is proved, and the tracking error as well as the disturbance observer error can converge to the origin through the Lyapunov analysis. Simulation results are presented to demonstrate the effectiveness of the proposed flight control scheme.

Normal modes of weak colloidal gels

Science.gov (United States)

Varga, Zsigmond; Swan, James W.

2018-01-01

The normal modes and relaxation rates of weak colloidal gels are investigated in calculations using different models of the hydrodynamic interactions between suspended particles. The relaxation spectrum is computed for freely draining, Rotne-Prager-Yamakawa, and accelerated Stokesian dynamics approximations of the hydrodynamic mobility in a normal mode analysis of a harmonic network representing several colloidal gels. We find that the density of states and spatial structure of the normal modes are fundamentally altered by long-ranged hydrodynamic coupling among the particles. Short-ranged coupling due to hydrodynamic lubrication affects only the relaxation rates of short-wavelength modes. Hydrodynamic models accounting for long-ranged coupling exhibit a microscopic relaxation rate for each normal mode, λ that scales as l-2, where l is the spatial correlation length of the normal mode. For the freely draining approximation, which neglects long-ranged coupling, the microscopic relaxation rate scales as l-γ, where γ varies between three and two with increasing particle volume fraction. A simple phenomenological model of the internal elastic response to normal mode fluctuations is developed, which shows that long-ranged hydrodynamic interactions play a central role in the viscoelasticity of the gel network. Dynamic simulations of hard spheres that gel in response to short-ranged depletion attractions are used to test the applicability of the density of states predictions. For particle concentrations up to 30% by volume, the power law decay of the relaxation modulus in simulations accounting for long-ranged hydrodynamic interactions agrees with predictions generated by the density of states of the corresponding harmonic networks as well as experimental measurements. For higher volume fractions, excluded volume interactions dominate the stress response, and the prediction from the harmonic network density of states fails. Analogous to the Zimm model in polymer

Investigating the relationship between subjective drug craving and temporal dynamics of the default mode network, executive control network, and salience network in methamphetamine dependents using rsfMRI

Science.gov (United States)

Soltanian-Zadeh, Somayyeh; Hossein-Zadeh, Gholam-Ali; Shahbabaie, Alireza; Ekhtiari, Hamed

2016-03-01

Resting state functional connectivity (rsFC) studies using fMRI provides a great deal of knowledge on the spatiotemporal organization of the brain. The relationships between and within a number of resting state functional networks, namely the default mode network (DMN), salience network (SN) and executive control network (ECN) have been intensely studied in basic and clinical cognitive neuroscience [1]. However, the presumption of spatial and temporal stationarity has mostly restricted the assessment of rsFC [1]. In this study, sliding window correlation analysis and k-means clustering were exploited to examine the temporal dynamics of rsFC of these three networks in 24 abstinent methamphetamine dependents. Afterwards, using canonical correlation analysis (CCA) the possible relationship between the level of self-reported craving and the temporal dynamics was examined. Results indicate that the rsFC transits between 6 discrete "FC states" in the meth dependents. CCA results show that higher levels of craving are associated with higher probability of transiting from state 4 to 6 (positive FC of DMN-ECN getting weak and negative FC of DMN-SN appearing) and staying in state 4 (positive FC of DMN-ECN), lower probability of staying in state 2 (negative FC of DMN-ECN), transiting from state 4 to 2 (change of positive FC of DMN-ECN to negative FC), and transiting from state 3 to 5 (appearance of negative FC of DMN-SN and positive FC of DMN-ECN with the presence of negative FC of SN-ECN). Quantitative measures of temporal dynamics in large-scale brain networks could bring new added values to increase potentials for applications of rsfMRI in addiction medicine.

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

Directory of Open Access Journals (Sweden)

Nicolai Franzmeier

2017-08-01

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

Detection of Gait Modes Using an Artificial Neural Network during Walking with a Powered Ankle-Foot Orthosis

Science.gov (United States)

2016-01-01

This paper presents an algorithm, for use with a Portable Powered Ankle-Foot Orthosis (i.e., PPAFO) that can automatically detect changes in gait modes (level ground, ascent and descent of stairs or ramps), thus allowing for appropriate ankle actuation control during swing phase. An artificial neural network (ANN) algorithm used input signals from an inertial measurement unit and foot switches, that is, vertical velocity and segment angle of the foot. Output from the ANN was filtered and adjusted to generate a final data set used to classify different gait modes. Five healthy male subjects walked with the PPAFO on the right leg for two test scenarios (walking over level ground and up and down stairs or a ramp; three trials per scenario). Success rate was quantified by the number of correctly classified steps with respect to the total number of steps. The results indicated that the proposed algorithm's success rate was high (99.3%, 100%, and 98.3% for level, ascent, and descent modes in the stairs scenario, respectively; 98.9%, 97.8%, and 100% in the ramp scenario). The proposed algorithm continuously detected each step's gait mode with faster timing and higher accuracy compared to a previous algorithm that used a decision tree based on maximizing the reliability of the mode recognition. PMID:28070188

Distant from input: Evidence of regions within the default mode network supporting perceptually-decoupled and conceptually-guided cognition.

Science.gov (United States)

Murphy, Charlotte; Jefferies, Elizabeth; Rueschemeyer, Shirley-Ann; Sormaz, Mladen; Wang, Hao-Ting; Margulies, Daniel S; Smallwood, Jonathan

2018-05-01

The default mode network supports a variety of mental operations such as semantic processing, episodic memory retrieval, mental time travel and mind-wandering, yet the commonalities between these functions remains unclear. One possibility is that this system supports cognition that is independent of the immediate environment; alternatively or additionally, it might support higher-order conceptual representations that draw together multiple features. We tested these accounts using a novel paradigm that separately manipulated the availability of perceptual information to guide decision-making and the representational complexity of this information. Using task based imaging we established regions that respond when cognition combines both stimulus independence with multi-modal information. These included left and right angular gyri and the left middle temporal gyrus. Although these sites were within the default mode network, they showed a stronger response to demanding memory judgements than to an easier perceptual task, contrary to the view that they support automatic aspects of cognition. In a subsequent analysis, we showed that these regions were located at the extreme end of a macroscale gradient, which describes gradual transitions from sensorimotor to transmodal cortex. This shift in the focus of neural activity towards transmodal, default mode, regions might reflect a process of where the functional distance from specific sensory enables conceptually rich and detailed cognitive states to be generated in the absence of input. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

The structural connectivity pattern of the default mode network and its association with memory and anxiety

Directory of Open Access Journals (Sweden)

Yan eTao

2015-11-01

Full Text Available The default mode network (DMN is one of the most widely studied resting state functional networks. The structural basis for the DMN is of particular interest and has been studied by several researchers using diffusion tensor imaging (DTI. Most of these previous studies focused on a few regions or white matter tracts of the DMN so that the global structural connectivity pattern and network properties of the DMN remain unclear. Moreover, evidences indicate that the DMN is involved in both memory and emotion, but how the DMN regulates memory and anxiety from the perspective of the whole DMN structural network remains unknown. We used multimodal neuroimaging methods to investigate the structural connectivity pattern of the DMN and the association of its network properties with memory and anxiety in 205 young healthy subjects. Using a probabilistic fiber tractography technique based on DTI data and graph theory methods, we constructed the global structural connectivity pattern of the DMN and found that memory quotient (MQ score was significantly positively correlated with the global and local efficiency of the DMN whereas anxiety was found to be negatively correlated with the efficiency. The strong structural connectivity between multiple brain regions within DMN may reflect that the DMN has certain structural basis. Meanwhile, we found the network efficiency of the DMN were related to memory and anxiety measures, which indicated that the DMN may play a role in the memory and anxiety.

Competing Transport Networks

NARCIS (Netherlands)

M.J. van der Leij (Marco)

2003-01-01

textabstractIn a circular city model, I consider network design and pricing decisions for a single fast transport connection that faces competition from a slower but better accessible transport mode. To access the fast transport network individuals have to make complementary trips by slow mode. This

Enhanced Sleep Mode MAC Control for EPON

DEFF Research Database (Denmark)

Yan, Ying; Dittmann, Lars

2011-01-01

This paper introduces sleep mode operations for EPON. New MAC control functions are proposed to schedule sleep periods. Traffic profiles are considered to optimize energy efficiency and network performances. Simulation results are analyzed in OPNET modeler.......This paper introduces sleep mode operations for EPON. New MAC control functions are proposed to schedule sleep periods. Traffic profiles are considered to optimize energy efficiency and network performances. Simulation results are analyzed in OPNET modeler....

A failure of suppression within the default mode network in depressed adolescents with compulsive internet game play.

Science.gov (United States)

Han, Doug Hyun; Kim, Sun Mi; Bae, Sujin; Renshaw, Perry F; Anderson, Jeffrey S

2016-04-01

Individuals who are chronic, compulsive video game players experience an elevated incidence of major depression. Excessive or problematic game play can interact with depression clinically, and may magnify impulsive behavior associated with video gaming. Functional brain imaging was performed during a Wisconsin Card Sorting Test (WCST) task in 42 healthy control and 95 volunteers seeking treatment for compulsive video game playing, including 60 participants without major depression (pure internet gaming disorder, pure IGD) and 35 participants comorbid with major depression (IGD+MDD). In response to the WCST in contrast to fixation, activation was observed in canonical brain attentional networks including bilateral intraparietal sulcus, frontal eye fields, and middle temporal cortical regions as well as dorsolateral prefrontal, inferior parietal and anterior insula, anterior cingulate cortex in all participants. For WCST>Fixation contrasts, the IGD+MDD group exhibited greater relative activation within the left hippocampus, compared to healthy control participants. For WCST>Fixation contrasts, the IGD+MDD group exhibited greater relative activation within the left hippocampus and the right parahippocampal gyrus immediately posterior to the hippocampus, compared to the pure IGD group. In cohorts of individuals with a history of compulsive internet game play, individuals with depression showed failure to suppress default mode network activity during an attentionally demanding task, compared to individuals without depression, including comparison groups with and without a history of compulsive video gaming. This reduced suppression of the brain regions within the default mode network may be a consequence of depressive neurophysiology or represent a predisposition for depression within compulsive game players. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

2013-01-01

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

Cell Size Breathing and Possibilities to Introduce Cell Sleep Mode

DEFF Research Database (Denmark)

Micallef, Gilbert; Mogensen, Preben; Scheck, Hans-Otto

2010-01-01

regular upgrades in the infrastructure. While network equipment is in itself becoming more efficient, these upgrades still increase the overall energy consumption of the networks. This paper investigates the energy saving potential of exploiting cell size breathing by putting low loaded cells into sleep...... mode. The energy consumption and network performance of the resulting network are used to quantify the potential of this feature. The investigation is carried out on a tilt optimized network. Since putting cells into sleep mode results in a non-optimum antenna tilt configuration, this paper also...

Towards a networked governance approach in Danish hospitals?

DEFF Research Database (Denmark)

Brambini-Pedersen, Jan Vang; Brambini, Annalisa

2018-01-01

Hospitals across the globe are prone to numerous wicked problems. Wicked problems are difficult to solve and continue to negatively influence hospital systems. The proponents of the networked governance approach suggest that a new governance mode embracing a collaborative innovation approach to s...

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

Directory of Open Access Journals (Sweden)

Kathrin Koch

2018-06-01

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

Mode Choice Modeling Using Artificial Neural Networks

OpenAIRE

Edara, Praveen Kumar

2003-01-01

Artificial intelligence techniques have produced excellent results in many diverse fields of engineering. Techniques such as neural networks and fuzzy systems have found their way into transportation engineering. In recent years, neural networks are being used instead of regression techniques for travel demand forecasting purposes. The basic reason lies in the fact that neural networks are able to capture complex relationships and learn from examples and also able to adapt when new data becom...

Modelling life trajectories and mode choice using Bayesian belief networks

NARCIS (Netherlands)

Verhoeven, M.

2010-01-01

Traditionally, transport mode choice was primarily examined as a stand alone problem. Given a purpose and destination, the choice of transport mode was modelled as a function of the various attributes of the transport mode alternatives. Later, transport mode choice decisions were modelled as part of

Cyclotron operating mode determination based on intelligent methods

International Nuclear Information System (INIS)

Ouda, M.M.E.M.

2011-01-01

Particle accelerators are generators that produce beams of charged particles with energies depending on the accelerator type. The MGC-20 cyclotron is a cyclic particle accelerator used for accelerating protons, deuterons, alpha particles, and helium-3 to different energies. Main applications are isotopes production, nuclear reactions studies, and mass spectroscopy studies and other industrial applications. The cyclotron is a complicated machine depends on using a strong magnetic field and high frequency-high voltage electric field together to accelerate and bend charged particles inside the accelerating chamber. It consists of the following main parts, the radio frequency system, the main magnet with the auxiliary concentric and harmonic coils, the electrostatic deflector, and the ion source, the beam transport system, and high precision and high stability DC power supplies.To accelerate a particle to certain energy, one has to adjust the cyclotron operating parameters to be suitable to accelerate this particle to that energy. If the cyclotron operating parameters together are adjusted to accelerate a charged particle to certain energy, then these parameters together are named the operating mode to accelerate this particle to that energy. For example the operating mode to accelerate protons to 18 MeV is named the (18 MeV protons operating mode). The operating mode includes many parameters that must be adjusted together to be successful to accelerate, extract, focus, steer a particle from the ion source to the experiment. Due to the big number of parameters in the operating modes, 19 parameters have been selected in this thesis to be used in an intelligent system based on feed forward back propagation neural network to determine the parameters for new operating modes. The new intelligent system depends on the available information about the currently used operating modes.The classic way to determine a new operating mode was depending on trial and error method to

Cortical Thinning and Altered Cortico-Cortical Structural Covariance of the Default Mode Network in Patients with Persistent Insomnia Symptoms.

Science.gov (United States)

Suh, Sooyeon; Kim, Hosung; Dang-Vu, Thien Thanh; Joo, Eunyeon; Shin, Chol

2016-01-01

Recent studies have suggested that structural abnormalities in insomnia may be linked with alterations in the default-mode network (DMN). This study compared cortical thickness and structural connectivity linked to the DMN in patients with persistent insomnia (PI) and good sleepers (GS). The current study used a clinical subsample from the longitudinal community-based Korean Genome and Epidemiology Study (KoGES). Cortical thickness and structural connectivity linked to the DMN in patients with persistent insomnia symptoms (PIS; n = 57) were compared to good sleepers (GS; n = 40). All participants underwent MRI acquisition. Based on literature review, we selected cortical regions corresponding to the DMN. A seed-based structural covariance analysis measured cortical thickness correlation between each seed region of the DMN and other cortical areas. Association of cortical thickness and covariance with sleep quality and neuropsychological assessments were further assessed. Compared to GS, cortical thinning was found in PIS in the anterior cingulate cortex, precentral cortex, and lateral prefrontal cortex. Decreased structural connectivity between anterior and posterior regions of the DMN was observed in the PIS group. Decreased structural covariance within the DMN was associated with higher PSQI scores. Cortical thinning in the lateral frontal lobe was related to poor performance in executive function in PIS. Disrupted structural covariance network in PIS might reflect malfunctioning of antero-posterior disconnection of the DMN during the wake to sleep transition that is commonly found during normal sleep. The observed structural network alteration may further implicate commonly observed sustained sleep difficulties and cognitive impairment in insomnia. © 2016 Associated Professional Sleep Societies, LLC.

Fundamental Dynamical Modes Underlying Human Brain Synchronization

Directory of Open Access Journals (Sweden)

Catalina Alvarado-Rojas

2012-01-01

Full Text Available Little is known about the long-term dynamics of widely interacting cortical and subcortical networks during the wake-sleep cycle. Using large-scale intracranial recordings of epileptic patients during seizure-free periods, we investigated local- and long-range synchronization between multiple brain regions over several days. For such high-dimensional data, summary information is required for understanding and modelling the underlying dynamics. Here, we suggest that a compact yet useful representation is given by a state space based on the first principal components. Using this representation, we report, with a remarkable similarity across the patients with different locations of electrode placement, that the seemingly complex patterns of brain synchrony during the wake-sleep cycle can be represented by a small number of characteristic dynamic modes. In this space, transitions between behavioral states occur through specific trajectories from one mode to another. These findings suggest that, at a coarse level of temporal resolution, the different brain states are correlated with several dominant synchrony patterns which are successively activated across wake-sleep states.

Does the social capital in networks of “fish and fire” scientists and managers suggest learning?

Science.gov (United States)

A. Paige Fischer; Ken Vance-Borland; Kelly M. Burnett; Susan Hummel; Janean H. Creighton; Sherri L. Johnson; Lorien Jasny

2014-01-01

Patterns of social interaction influence how knowledge is generated, communicated, and applied. Theories of social capital and organizational learning suggest that interactions within disciplinary or functional groups foster communication of knowledge, whereas interactions across groups foster generation of new knowledge. We used social network analysis to examine...

Dendritic slow dynamics enables localized cortical activity to switch between mobile and immobile modes with noisy background input.

Directory of Open Access Journals (Sweden)

Hiroki Kurashige

Full Text Available Mounting lines of evidence suggest the significant computational ability of a single neuron empowered by active dendritic dynamics. This motivates us to study what functionality can be acquired by a network of such neurons. The present paper studies how such rich single-neuron dendritic dynamics affects the network dynamics, a question which has scarcely been specifically studied to date. We simulate neurons with active dendrites networked locally like cortical pyramidal neurons, and find that naturally arising localized activity--called a bump--can be in two distinct modes, mobile or immobile. The mode can be switched back and forth by transient input to the cortical network. Interestingly, this functionality arises only if each neuron is equipped with the observed slow dendritic dynamics and with in vivo-like noisy background input. If the bump activity is considered to indicate a point of attention in the sensory areas or to indicate a representation of memory in the storage areas of the cortex, this would imply that the flexible mode switching would be of great potential use for the brain as an information processing device. We derive these conclusions using a natural extension of the conventional field model, which is defined by combining two distinct fields, one representing the somatic population and the other representing the dendritic population. With this tool, we analyze the spatial distribution of the degree of after-spike adaptation and explain how we can understand the presence of the two distinct modes and switching between the modes. We also discuss the possible functional impact of this mode-switching ability.

Functional neuroimaging with default mode network regions distinguishes PTSD from TBI in a military veteran population

OpenAIRE

Raji, Cyrus A.; Willeumier, Kristen; Taylor, Derek; Tarzwell, Robert; Newberg, Andrew; Henderson, Theodore A.; Amen, Daniel G.

2015-01-01

PTSD and TBI are two common conditions in veteran populations that can be difficult to distinguish clinically. The default mode network (DMN) is abnormal in a multitude of neurological and psychiatric disorders. We hypothesize that brain perfusion SPECT can be applied to diagnostically separate PTSD from TBI reliably in a veteran cohort using DMN regions. A group of 196 veterans (36 with PTSD, 115 with TBI, 45 with PTSD/TBI) were selected from a large multi-site population cohort of individua...

Patterns of altered neural synchrony in the default mode network in autism spectrum disorder revealed with magnetoencephalography (MEG): Relationship to clinical symptomatology.

Science.gov (United States)

Lajiness-O'Neill, Renée; Brennan, Jonathan R; Moran, John E; Richard, Annette E; Flores, Ana-Mercedes; Swick, Casey; Goodcase, Ryan; Andersen, Tiffany; McFarlane, Kaitlyn; Rusiniak, Kenneth; Kovelman, Ioulia; Wagley, Neelima; Ugolini, Maggie; Albright, Jeremy; Bowyer, Susan M

2018-03-01

Disrupted neural synchrony may be a primary electrophysiological abnormality in autism spectrum disorders (ASD), altering communication between discrete brain regions and contributing to abnormalities in patterns of connectivity within identified neural networks. Studies exploring brain dynamics to comprehensively characterize and link connectivity to large-scale cortical networks and clinical symptoms are lagging considerably. Patterns of neural coherence within the Default Mode Network (DMN) and Salience Network (SN) during resting state were investigated in 12 children with ASD (M Age  = 9.2) and 13 age and gender-matched neurotypicals (NT) (M Age  = 9.3) with magnetoencephalography. Coherence between 231 brain region pairs within four frequency bands (theta (4-7 Hz), alpha, (8-12 Hz), beta (13-30 Hz), and gamma (30-80 Hz)) was calculated. Relationships between neural coherence and social functioning were examined. ASD was characterized by lower synchronization across all frequencies, reaching clinical significance in the gamma band. Lower gamma synchrony between fronto-temporo-parietal regions was observed, partially consistent with diminished default mode network (DMN) connectivity. Lower gamma coherence in ASD was evident in cross-hemispheric connections between: angular with inferior/middle frontal; middle temporal with middle/inferior frontal; and within right-hemispheric connections between angular, middle temporal, and inferior/middle frontal cortices. Lower gamma coherence between left angular and left superior frontal, right inferior/middle frontal, and right precuneus and between right angular and inferior/middle frontal cortices was related to lower social/social-communication functioning. Results suggest a pattern of lower gamma band coherence in a subset of regions within the DMN in ASD (angular and middle temporal cortical areas) related to lower social/social-communicative functioning. Autism Res 2018, 11: 434-449. © 2017 International

Self-processing and the default mode network: Interactions with the mirror neuron system

Directory of Open Access Journals (Sweden)

Istvan eMolnar-Szakacs

2013-09-01

Full Text Available Recent evidence for the fractionation of the default mode network (DMN into functionally distinguishable subdivisions with unique patterns of connectivity calls for a reconceptualization of the relationship between this network and self-referential processing. Advances in resting-state functional connectivity analyses are beginning to reveal increasingly complex patterns of organization within the key nodes of the DMN - medial prefrontal cortex (MPFC and posterior cingulate cortex (PCC – as well as between these nodes and other brain systems. Here we review recent examinations of the relationships between the DMN and various aspects of self-relevant and social-cognitive processing in light of emerging evidence for heterogeneity within this network. Drawing from a rapidly evolving social cognitive neuroscience literature, we propose that embodied simulation and mentalizing are processes which allow us to gain insight into another's physical and mental state by providing privileged access to our own physical and mental states. Embodiment implies that the same neural systems are engaged for self- and other-understanding through a simulation mechanism, while mentalizing refers to the use of high-level conceptual information to make inferences about the mental states of self and others. These mechanisms work together to provide a coherent representation of the self and by extension, of others. Nodes of the DMN selectively interact with brain systems for embodiment and mentalizing, including the mirror neuron system, to produce appropriate mappings in the service of social cognitive demands.

Mixed H∞ and passive projective synchronization for fractional-order memristor-based neural networks with time delays via adaptive sliding mode control

Science.gov (United States)

Song, Shuai; Song, Xiaona; Balsera, Ines Tejado

2017-05-01

This paper investigates the mixed H∞ and passive projective synchronization problem for fractional-order (FO) memristor-based neural networks with time delays. Our aim is to design a controller such that, though the unavoidable phenomena of time delay and external disturbances is fully considered, the resulting closed-loop system is stable with a mixed H∞ and passive performance level. By combining sliding mode control and adaptive control methods, a novel adaptive sliding mode control strategy is designed for the synchronization of time-delayed FO dynamic networks. Via the application of FO system stability theory, the projective synchronization conditions are addressed in terms of linear matrix inequalities. Based on the conditions, a desired controller which can guarantee the stability of the closed-loop system and also ensure a mixed H∞ and passive performance level is designed. Finally, two simulation examples are given to illustrate the effectiveness of the proposed method.

Functional MRI Assessment of Task-Induced Deactivation of the Default Mode Network in Alzheimer’s Disease and At-Risk Older Individuals

Directory of Open Access Journals (Sweden)

Maija Pihlajamäki

2009-01-01

Full Text Available Alzheimer’s disease (AD is the most common form of dementia in old age, and is characterized by prominent impairment of episodic memory. Recent functional imaging studies in AD have demonstrated alterations in a distributed network of brain regions supporting memory function, including regions of the default mode network. Previous positron emission tomography studies of older individuals at risk for AD have revealed hypometabolism of association cortical regions similar to the metabolic abnormalities seen in AD patients. In recent functional magnetic resonance imaging (fMRI studies of AD, corresponding brain default mode regions have also been found to demonstrate an abnormal fMRI task-induced deactivation response pattern. That is, the relative decreases in fMRI signal normally observed in the default mode regions in healthy subjects performing a cognitive task are not seen in AD patients, or may even be reversed to a paradoxical activation response. Our recent studies have revealed alterations in the pattern of deactivation also in elderly individuals at risk for AD by virtue of their APOE e4 genotype, or evidence of mild cognitive impairment (MCI. In agreement with recent reports from other groups, these studies demonstrate that the pattern of fMRI task-induced deactivation is progressively disrupted along the continuum from normal aging to MCI and to clinical AD and more impaired in e4 carriers compared to non-carriers. These findings will be discussed in the context of current literature regarding functional imaging of the default network in AD and at-risk populations.

The Modes of Data Development in the Internet Age

Directory of Open Access Journals (Sweden)

Yuxian Wu

2007-12-01

Full Text Available It is historical that data development has its own mode (collect, treatment, delivery, store, and use, from Manual mode, Mechanism mode, and Electronic mode, now to the Network mode. And search engine plus self-learning is the advanced mode of data development. Network mode has also been changing, the underlying motivation exits in the development & progress of Internet itself. There are two huge trends force the mode of data development to face new challenge & make decision. One is the revolution resulted by the change of the user market need & represented by Web2.0. Another is the revolution resulted by technological developing tendency & represented by Grid. Squeezed by the two huge trends from opposite directions, the lagging, crude and inefficient mode will change revolutionarily forced by wise decision-making or silent market. As for data-development mode, the change of technology & operation need the change of game rule simultaneously. So eliminating barriers, promoting resource-sharing, rationalize relations of market/non-market is to be a big inescapable work

Health in All Policies (HiAP) governance: lessons from network governance.

Science.gov (United States)

Khayatzadeh-Mahani, Akram; Ruckert, Arne; Labonté, Ronald; Kenis, Patrick; Akbari-Javar, Mohammad Reza

2018-05-25

The Health in All Policies (HiAP) approach requires formal and sustained governance structures and mechanisms to ensure that the policies of various non-health sectors maximize positive and minimize negative impacts on population health. In this paper, we demonstrate the usefulness of a network perspective in understanding and contributing to the effectiveness of HiAP. We undertook an exploratory, qualitative case study of a HiAP structure in Iran, the Kerman province Council of Health and Food Security (CHFS) with diverse members from health and non-health sectors. We analyzed relevant policy texts and interviewed 32 policy actors involved in the CHFS. Data were analyzed using within-case analysis and constant comparative methodology. Our findings suggest that CHFS governance from a network perspective drew in practice on elements of two competing network governance modes: the network administrative organization (NAO) and the lead organization mode. Our results also show that a shift from a hierarchical and market-based mode of interaction to a network logic within CHFS has not yet taken place. In addition, CHFS suffers from large membership and an inability to address complex 'wicked problems', as well as low trust, legitimacy and goal consensus among its members. Drawing on other HiAP studies and commentaries, insights from organization network theory, and in-depth findings from our case study, we conclude that a NAO may be the most effective mode of governance for tackling complex social problems in HiAP structures. Since similar studies are limited, and our single case study may not be transferable across all contexts, we suggest that further research be undertaken to explore HiAP structures from a network perspective in different institutional and cultural settings. With increasing emphasis given to HiAP approaches in national and international health policy discourse, it is important that comparative knowledge about the effectiveness of HiAP governance

Fasting plasma insulin and the default mode network in women at risk for Alzheimer's disease.

Science.gov (United States)

Kenna, Heather; Hoeft, Fumiko; Kelley, Ryan; Wroolie, Tonita; DeMuth, Bevin; Reiss, Allan; Rasgon, Natalie

2013-03-01

Brain imaging studies in Alzheimer's disease research have demonstrated structural and functional perturbations in the hippocampus and default mode network (DMN). Additional evidence suggests risk for pathological brain aging in association with insulin resistance (IR). This study piloted investigation of associations of IR with DMN-hippocampal functional connectivity among postmenopausal women at risk for Alzheimer's disease. Twenty middle-aged women underwent resting state functional magnetic resonance imaging. Subjects were dichotomized relative to fasting plasma insulin levels (i.e., > 8 μIU/mL [n = 10] and < 8 μIU/mL [n = 10]), and functional connectivity analysis contrasted their respective blood oxygen level-dependent signal correlation between DMN and hippocampal regions. Higher-insulin women had significantly reduced positive associations between the medial prefrontal cortex and bilateral parahippocampal regions extending to the right hippocampus, and conversely, between the left and right hippocampus and medial prefrontal cortex. Neuropsychological data (all within normal ranges) also showed significant differences with respect to executive functioning and global intelligence. The results provide further evidence of deleterious effects of IR on the hippocampus and cognition. Further imaging studies of the IR-related perturbations in DMN-hippocampal functional connectivity are needed. Copyright © 2013 Elsevier Inc. All rights reserved.

Art reaches within: aesthetic experience, the self and the default mode network

Directory of Open Access Journals (Sweden)

Edward A Vessel

2013-12-01

Full Text Available In a task of rating images of artworks in an fMRI scanner, regions in the medial prefrontal cortex that are known to be part of the default mode network (DMN were positively activated on the highest-rated trials. This is surprising given the DMN's original characterization as the set of brain regions that show greater fMRI activity during rest periods than during performance of tasks requiring focus on external stimuli. But further research showed that DMN regions could be positively activated also in structured tasks, if those tasks involved self-referential thought or self-relevant information. How may our findings be understood in this context? Although our task had no explicit self-referential aspect and the stimuli had no a priori self-relevance to the observers, the experimental design we employed emphasized the personal aspects of aesthetic experience. Observers were told that we were interested in their individual tastes, and asked to base their ratings on how much each artwork "moved" them. Moreover, we used little-known artworks that covered a wide range of styles, which led to high individual variability: each artwork was rated highly by some observers and poorly by others. This means that rating-specific neural responses cannot be attributed to the features of any particular artworks, but rather to the aesthetic experience itself. The DMN activity therefore suggests that certain artworks, albeit unfamiliar, may be so well-matched to an individual’s unique makeup that they obtain access to the neural substrates concerned with the self – access which other external stimuli normally do not get. This mediates a sense of being moved, or touched from within. This account is consistent with the modern notion that individuals’ taste in art is linked with their sense of identity, and suggests that DMN activity may serve to signal self-relevance in a broader sense than has been thought so far.

State estimation for Markov-type genetic regulatory networks with delays and uncertain mode transition rates

International Nuclear Information System (INIS)

Liang Jinling; Lam, James; Wang Zidong

2009-01-01

This Letter is concerned with the robust state estimation problem for uncertain time-delay Markovian jumping genetic regulatory networks (GRNs) with SUM logic, where the uncertainties enter into both the network parameters and the mode transition rate. The nonlinear functions describing the feedback regulation are assumed to satisfy the sector-like conditions. The main purpose of the problem addressed is to design a linear estimator to approximate the true concentrations of the mRNA and protein through available measurement outputs. By resorting to the Lyapunov functional method and some stochastic analysis tools, it is shown that if a set of linear matrix inequalities (LMIs) is feasible, the desired state estimator, that can ensure the estimation error dynamics to be globally robustly asymptotically stable in the mean square, exists. The obtained LMI conditions are dependent on both the lower and the upper bounds of the delays. An illustrative example is presented to demonstrate the feasibility of the proposed estimation schemes.

Network externality perspective of feed-in-tariffs (FIT) instruments-Some observations and suggestions

International Nuclear Information System (INIS)

Shum, Kwok L.; Watanabe, Chihiro

2010-01-01

Existing energy policy frameworks revolving around the acceleration of deployment of renewable energy technology can be broadly classified as the quantity vs. price approach. With this brief viewpoint, this paper suggests another perspective of viewing these instruments in terms of a more fundamental basis: whether the deployment in capacity is in terms of a cost minimization approach or a network externality approach. We suggest that the generic price or feed in tariff (FIT) approach in subsidizing renewable electricity generation and associated income would create a bandwagon or self-propagation effect among users rendering the renewable energy technology spreads like a software or information technology. Our objective is to raise awareness of this technology dynamics oriented perspective in renewable deployment supplementing the conventional installation subsidies perspective. We hope that it would inspire more empirical works and studies relating to the policy implications of this viewpoint.

Shared protection based virtual network mapping in space division multiplexing optical networks

Science.gov (United States)

Zhang, Huibin; Wang, Wei; Zhao, Yongli; Zhang, Jie

2018-05-01

Space Division Multiplexing (SDM) has been introduced to improve the capacity of optical networks. In SDM optical networks, there are multiple cores/modes in each fiber link, and spectrum resources are multiplexed in both frequency and core/modes dimensions. Enabled by network virtualization technology, one SDM optical network substrate can be shared by several virtual networks operators. Similar with point-to-point connection services, virtual networks (VN) also need certain survivability to guard against network failures. Based on customers' heterogeneous requirements on the survivability of their virtual networks, this paper studies the shared protection based VN mapping problem and proposes a Minimum Free Frequency Slots (MFFS) mapping algorithm to improve spectrum efficiency. Simulation results show that the proposed algorithm can optimize SDM optical networks significantly in terms of blocking probability and spectrum utilization.

Fluctuations of Attentional Networks and Default Mode Network during the Resting State Reflect Variations in Cognitive States: Evidence from a Novel Resting-state Experience Sampling Method.

Science.gov (United States)

Van Calster, Laurens; D'Argembeau, Arnaud; Salmon, Eric; Peters, Frédéric; Majerus, Steve

2017-01-01

Neuroimaging studies have revealed the recruitment of a range of neural networks during the resting state, which might reflect a variety of cognitive experiences and processes occurring in an individual's mind. In this study, we focused on the default mode network (DMN) and attentional networks and investigated their association with distinct mental states when participants are not performing an explicit task. To investigate the range of possible cognitive experiences more directly, this study proposes a novel method of resting-state fMRI experience sampling, informed by a phenomenological investigation of the fluctuation of mental states during the resting state. We hypothesized that DMN activity would increase as a function of internal mentation and that the activity of dorsal and ventral networks would indicate states of top-down versus bottom-up attention at rest. Results showed that dorsal attention network activity fluctuated as a function of subjective reports of attentional control, providing evidence that activity of this network reflects the perceived recruitment of controlled attentional processes during spontaneous cognition. Activity of the DMN increased when participants reported to be in a subjective state of internal mentation, but not when they reported to be in a state of perception. This study provides direct evidence for a link between fluctuations of resting-state neural activity and fluctuations in specific cognitive processes.

Risk factors associated with cognitions for late-onset depression based on anterior and posterior default mode sub-networks.

Science.gov (United States)

Liu, Rui; Yue, Yingying; Hou, Zhenghua; Yuan, Yonggui; Wang, Qiao

2018-08-01

Abnormal functional connectivity (FC) in the default mode network (DMN) plays an important role in late-onset depression (LOD) patients. In this study, the risk predictors of LOD based on anterior and posterior DMN are explored. A total of 27 LOD patients and 40 healthy controls (HC) underwent resting-state functional magnetic resonance imaging and cognitive assessments. Firstly, FCs within DMN sub-networks were determined by placing seeds in the ventral medial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC). Secondly, multivariable logistic regression was used to identify risk factors for LOD patients. Finally, correlation analysis was performed to investigate the relationship between risk factors and the cognitive value. Multivariable logistic regression showed that the FCs between the vmPFC and right middle temporal gyrus (MTG) (vmPFC-MTG_R), FCs between the vmPFC and left precuneus (PCu), and FCs between the PCC and left PCu (PCC-PCu_L) were the risk factors for LOD. Furthermore, FCs of the vmPFC-MTG_R and PCC-PCu_L correlated with processing speed (R = 0.35, P = 0.002; R = 0.32, P = 0.009), and FCs of the vmPFC-MTG_R correlated with semantic memory (R = 0.41, P = 0.001). The study was a cross-sectional study. The results may be potentially biased because of a small sample. In this study, we confirmed that LOD patients mainly present cognitive deficits in processing speed and semantic memory. Moreover, our findings further suggested that FCs within DMN sub-networks associated with cognitions were risk factors, which may be used for the prediction of LOD. Copyright © 2018 Elsevier B.V. All rights reserved.

Development of neural network models for the prediction of solidification mode, weld bead geometry and sensitisation in austenitic stainless steels

International Nuclear Information System (INIS)

Vasudevan, M.; Raj, B.; Prasad Rao, K.

2005-01-01

Quantitative models describing the effect of weld composition on the solidification mode, ferrite content and process parameters on the weld bead geometry are necessary in order to design composition of the welding consumable to ensure primary ferritic solidification mode, proper ferrite content and to ensure right choice of process parameters to achieve good bead geometry. A quantitative model on sensitisation behaviour of austenitic stainless steels is also necessary to optimise the composition of the austenitic stainless steel and to limit the strain on the material in order to enhance the resistance to sensitisation. The present paper discuss the development of quantitative models using artificial neural networks to correlate weld metal composition with solidification mode, process parameter with weld bead geometry and time for sensitisation with composition, strain in the material before welding and the temperature of exposure in austenitic stainless steels. (author)

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

Science.gov (United States)

Ji, Xuewu; He, Xiangkun; Lv, Chen; Liu, Yahui; Wu, Jian

2018-06-01

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.

The self-pleasantness judgment modulates the encoding performance and the Default Mode Network activity

Directory of Open Access Journals (Sweden)

Perrone-Bertolotti eMarcela

2016-03-01

Full Text Available In this functional magnetic resonance imaging (fMRI study, we evaluated the effect of self-relevance on cerebral activity and behavioral performance during an incidental encoding task. Recent findings suggest that pleasantness judgments reliably induce self-oriented (internal thoughts and increase default mode network (DMN activity. We hypothesized that this increase in DMN activity would relate to increased memory recognition for pleasantly-judged stimuli (which depend on internally-oriented attention but decreased recognition for unpleasantly-judged items (which depend on externally-oriented attention. To test this hypothesis, brain activity was recorded from 21 healthy participants while they performed a pleasantness judgment requiring them to rate visual stimuli as pleasant or unpleasant. One hour later, participants performed a surprise memory recognition test outside of the scanner. Thus, we were able to evaluate the effects of pleasant and unpleasant judgments on cerebral activity and incidental encoding. The behavioral results showed that memory recognition was better for items rated as pleasant than items rated as unpleasant. The whole brain analysis indicated that successful encoding activates the inferior frontal and lateral temporal cortices, whereas unsuccessful encoding recruits two key medial posterior DMN regions, the posterior cingulate cortex and precuneus. A region of interest analysis including classic DMN areas, revealed significantly greater involvement of the medial Prefrontal Cortex in pleasant compared to unpleasant judgments, suggesting this region’s involvement in self-referential (i.e., internal processing. This area may be responsible for the greater recognition performance seen for pleasant stimuli. Furthermore, a significant interaction between the encoding performance (successful vs. unsuccessful and pleasantness was observed for the posterior cingulate cortex, precuneus and inferior frontal gyrus. Overall, our

Synchrony-induced modes of oscillation of a neural field model

Science.gov (United States)

Esnaola-Acebes, Jose M.; Roxin, Alex; Avitabile, Daniele; Montbrió, Ernest

2017-11-01

We investigate the modes of oscillation of heterogeneous ring networks of quadratic integrate-and-fire (QIF) neurons with nonlocal, space-dependent coupling. Perturbations of the equilibrium state with a particular wave number produce transient standing waves with a specific temporal frequency, analogously to those in a tense string. In the neuronal network, the equilibrium corresponds to a spatially homogeneous, asynchronous state. Perturbations of this state excite the network's oscillatory modes, which reflect the interplay of episodes of synchronous spiking with the excitatory-inhibitory spatial interactions. In the thermodynamic limit, an exact low-dimensional neural field model describing the macroscopic dynamics of the network is derived. This allows us to obtain formulas for the Turing eigenvalues of the spatially homogeneous state and hence to obtain its stability boundary. We find that the frequency of each Turing mode depends on the corresponding Fourier coefficient of the synaptic pattern of connectivity. The decay rate instead is identical for all oscillation modes as a consequence of the heterogeneity-induced desynchronization of the neurons. Finally, we numerically compute the spectrum of spatially inhomogeneous solutions branching from the Turing bifurcation, showing that similar oscillatory modes operate in neural bump states and are maintained away from onset.

THE RESONANT OVERVOLTAGE IN NON-SINUSOIDAL MODE OF MAIN ELECTRIC NETWORK

Directory of Open Access Journals (Sweden)

V. G. Kuznetsov

2018-04-01

Full Text Available Purpose. The resonant overvoltage arises in main electrical networks as a result of random coincidence of some parameters of circuit and its mode and it may exist for a relatively long time. Therefore, the traditional means of limitation of short duration commutation surges are not effective in this case. The study determines conditions of appearance and development of non-sinusoidal mode after switching idle autotransformer to the overhead line of extra high voltage. The purpose of the paper is to choice measures for prevention overvoltage, too. Methodology. The study has used the result of extra high voltage line testing, the methods of electric circuit theory and the simulation in the MATLAB & Simulink package. Results. The simulation model of the extra high voltage transmission line for the study of resonant non-sinusoidal overvoltage is developed. The conditions for the appearance of resonant circuits in the real power line are found and harmonic frequency in which overvoltage arises are obtained. The study proposes using the controlled switching device as a measure to prevent resonance surges and determines the appropriate settings. Originality. The expression for calculation of resonant length of extra high voltage line was derived. The special investigation of processes in the resonant circuit of the extra high voltage transmission line for higher harmonic components of voltage is carried out. The program of switching for control apparatus that prevents non-sinusoidal overvoltage has been developed at the first time. Practical value. The using of the proposed settings of controlled switchgear will prevent the occurrence of hazardous resonant surge on higher harmonic components of voltage.

Innovation in Virtual Networks

DEFF Research Database (Denmark)

Hu, Yimei; Sørensen, Olav Jull

2011-01-01

The purpose of this article is to explore and highlight the particular innovation characteristics and modes of the chinese game industry from a networking perspective......The purpose of this article is to explore and highlight the particular innovation characteristics and modes of the chinese game industry from a networking perspective...

An evaluation of neural networks for identification of system parameters in reactor noise signals

International Nuclear Information System (INIS)

Miller, L.F.

1991-01-01

Several backpropagation neural networks for identifying fundamental mode eigenvalues were evaluated. The networks were trained and tested on analytical data and on results from other numerical methods. They were then used to predict first mode break frequencies for noise data from several sources. These predictions were, in turn, compared with analytical values and with results from alternative methods. Comparisons of results for some data sets suggest that the accuracy of predictions from neural networks are essentially equivalent to results from conventional methods while other evaluations indicate that either method may be superior. Experience gained from these numerical experiments provide insight for improving the performance of neural networks relative to other methods for identifying parameters associated with experimental data. Neural networks may also be used in support of conventional algorithms by providing starting points for nonlinear minimization algorithms

Polymeric electrochemical element for adaptive networks: Pulse mode

International Nuclear Information System (INIS)

Smerieri, Anteo; Berzina, Tatiana; Erokhin, Victor; Fontana, M. P.

2008-01-01

An electrochemically controlled polymeric heterojunction working as a memristor, i.e., having memory properties, was investigated in pulse mode, mimicking synaptic behavior of signal transmission in biological systems. Influence of parameters such as pulse duration, interval between pulses, and value of potential base level was analyzed. Learning capabilities were shown to be reversible and repeatable for both potentiation and inhibition of signal transmission. The adaptive behavior of the element was investigated and was shown to be more efficient than the dc mode

Characterization of a Fiber-Coupled 36-Core 3-Mode Photonic Lantern Spatial Multiplexer

DEFF Research Database (Denmark)

Rommel, Simon; Mendinueta, José Manuel Delgado; Klaus, Werner

2017-01-01

A fiber-coupled 108-port photonic lantern spatial-MUX is characterized with a spatially-diverse optical vector network analyzer. Insertion loss, mode-dependent losses, and time response are measured, showing significant mode mixing at a fiber splice.......A fiber-coupled 108-port photonic lantern spatial-MUX is characterized with a spatially-diverse optical vector network analyzer. Insertion loss, mode-dependent losses, and time response are measured, showing significant mode mixing at a fiber splice....

Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer's disease.

Science.gov (United States)

Chong, Joanna Su Xian; Liu, Siwei; Loke, Yng Miin; Hilal, Saima; Ikram, Mohammad Kamran; Xu, Xin; Tan, Boon Yeow; Venketasubramanian, Narayanaswamy; Chen, Christopher Li-Hsian; Zhou, Juan

2017-11-01

Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer's disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer's disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer's disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks-the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer's disease patients with and without cerebrovascular disease. Alzheimer's disease patients without cerebrovascular disease, but not Alzheimer's disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer's disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer's disease patients with and without cerebrovascular disease. Across Alzheimer's disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer's disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer's disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our

Empirical Mode Decomposition and Neural Networks on FPGA for Fault Diagnosis in Induction Motors

Directory of Open Access Journals (Sweden)

David Camarena-Martinez

2014-01-01

Full Text Available Nowadays, many industrial applications require online systems that combine several processing techniques in order to offer solutions to complex problems as the case of detection and classification of multiple faults in induction motors. In this work, a novel digital structure to implement the empirical mode decomposition (EMD for processing nonstationary and nonlinear signals using the full spline-cubic function is presented; besides, it is combined with an adaptive linear network (ADALINE-based frequency estimator and a feed forward neural network (FFNN-based classifier to provide an intelligent methodology for the automatic diagnosis during the startup transient of motor faults such as: one and two broken rotor bars, bearing defects, and unbalance. Moreover, the overall methodology implementation into a field-programmable gate array (FPGA allows an online and real-time operation, thanks to its parallelism and high-performance capabilities as a system-on-a-chip (SoC solution. The detection and classification results show the effectiveness of the proposed fused techniques; besides, the high precision and minimum resource usage of the developed digital structures make them a suitable and low-cost solution for this and many other industrial applications.

Empirical Mode Decomposition and Neural Networks on FPGA for Fault Diagnosis in Induction Motors

Science.gov (United States)

Garcia-Perez, Arturo; Osornio-Rios, Roque Alfredo; Romero-Troncoso, Rene de Jesus

2014-01-01

Nowadays, many industrial applications require online systems that combine several processing techniques in order to offer solutions to complex problems as the case of detection and classification of multiple faults in induction motors. In this work, a novel digital structure to implement the empirical mode decomposition (EMD) for processing nonstationary and nonlinear signals using the full spline-cubic function is presented; besides, it is combined with an adaptive linear network (ADALINE)-based frequency estimator and a feed forward neural network (FFNN)-based classifier to provide an intelligent methodology for the automatic diagnosis during the startup transient of motor faults such as: one and two broken rotor bars, bearing defects, and unbalance. Moreover, the overall methodology implementation into a field-programmable gate array (FPGA) allows an online and real-time operation, thanks to its parallelism and high-performance capabilities as a system-on-a-chip (SoC) solution. The detection and classification results show the effectiveness of the proposed fused techniques; besides, the high precision and minimum resource usage of the developed digital structures make them a suitable and low-cost solution for this and many other industrial applications. PMID:24678281

Dopamine Transporters in Striatum Correlate with Deactivation in the Default Mode Network during Visuospatial Attention

International Nuclear Information System (INIS)

Tomasi, D.; Fowler, J.; Tomasi, D.; Volkow, N.D.; Wang, R.L.; Telang, F.; Wang, Chang L.; Ernst, T.; Fowler, J.S.

2009-01-01

Dopamine and dopamine transporters (DAT, which regulate extracellular dopamine in the brain) are implicated in the modulation of attention but their specific roles are not well understood. Here we hypothesized that dopamine modulates attention by facilitation of brain deactivation in the default mode network (DMN). Thus, higher striatal DAT levels, which would result in an enhanced clearance of dopamine and hence weaker dopamine signals, would be associated to lower deactivation in the DMN during an attention task. For this purpose we assessed the relationship between DAT in striatum (measured with positron emission tomography and [ 11 C]cocaine used as DAT radiotracer) and brain activation and deactivation during a parametric visual attention task (measured with blood oxygenation level dependent functional magnetic resonance imaging) in healthy controls. We show that DAT availability in caudate and putamen had a negative correlation with deactivation in ventral parietal regions of the DMN (precuneus, BA 7) and a positive correlation with deactivation in a small region in the ventral anterior cingulate gyrus (BA 24/32). With increasing attentional load, DAT in caudate showed a negative correlation with load-related deactivation increases in precuneus. These findings provide evidence that dopamine transporters modulate neural activity in the DMN and anterior cingulate gyrus during visuospatial attention. Our findings suggest that dopamine modulates attention in part by regulating neuronal activity in posterior parietal cortex including precuneus (region involved in alertness) and cingulate gyrus (region deactivated in proportion to emotional interference). These findings suggest that the beneficial effects of stimulant medications (increase dopamine by blocking DAT) in inattention reflect in part their ability to facilitate the deactivation of the DMN.

Inheritance-mode specific pathogenicity prioritization (ISPP) for human protein coding genes.

Science.gov (United States)

Hsu, Jacob Shujui; Kwan, Johnny S H; Pan, Zhicheng; Garcia-Barcelo, Maria-Mercè; Sham, Pak Chung; Li, Miaoxin

2016-10-15

Exome sequencing studies have facilitated the detection of causal genetic variants in yet-unsolved Mendelian diseases. However, the identification of disease causal genes among a list of candidates in an exome sequencing study is still not fully settled, and it is often difficult to prioritize candidate genes for follow-up studies. The inheritance mode provides crucial information for understanding Mendelian diseases, but none of the existing gene prioritization tools fully utilize this information. We examined the characteristics of Mendelian disease genes under different inheritance modes. The results suggest that Mendelian disease genes with autosomal dominant (AD) inheritance mode are more haploinsufficiency and de novo mutation sensitive, whereas those autosomal recessive (AR) genes have significantly more non-synonymous variants and regulatory transcript isoforms. In addition, the X-linked (XL) Mendelian disease genes have fewer non-synonymous and synonymous variants. As a result, we derived a new scoring system for prioritizing candidate genes for Mendelian diseases according to the inheritance mode. Our scoring system assigned to each annotated protein-coding gene (N = 18 859) three pathogenic scores according to the inheritance mode (AD, AR and XL). This inheritance mode-specific framework achieved higher accuracy (area under curve  = 0.84) in XL mode. The inheritance-mode specific pathogenicity prioritization (ISPP) outperformed other well-known methods including Haploinsufficiency, Recessive, Network centrality, Genic Intolerance, Gene Damage Index and Gene Constraint scores. This systematic study suggests that genes manifesting disease inheritance modes tend to have unique characteristics. ISPP is included in KGGSeq v1.0 (http://grass.cgs.hku.hk/limx/kggseq/), and source code is available from (https://github.com/jacobhsu35/ISPP.git). mxli@hku.hkSupplementary information: Supplementary data are available at Bioinformatics online. © The Author

Connectivity of default-mode network is associated with cerebral edema in hepatic encephalopathy.

Directory of Open Access Journals (Sweden)

Wei-Che Lin

Full Text Available Cerebral edema, a well-known feature of acute liver disease, can occur in cirrhotic patients regardless of hepatic encephalopathy (HE and adversely affect prognosis. This study characterized and correlated functional HE abnormalities in the brain to cerebral edema using resting-state functional magnetic resonance imaging (rs-fMRI and diffusion tensor imaging (DTI. Forty-one cirrhotic patients (16 without HE, 14 minimal HE, 11 overt HE and 32 healthy controls were assessed. The HE grade in cirrhotic patients was evaluated by the West Haven criteria and neuro-psychological examinations. Functional connectivity correlation coefficient (fc-CC of the default mode network (DMN was determined by rs-fMRI, while the corresponding mean diffusivity (MD was obtained from DTI. Correlations among inter-cortical fc-CC, DTI indices, Cognitive Ability Screening Instrument scores, and laboratory tests were also analyzed. Results showed that gradual reductions of HE-related consciousness levels, from "without HE" or "minimal HE" to "overt HE", correlated with decreased anterior-posterior fc-CC in DMN [F(4.415, p = 0.000]. The MD values from regions with anterior-posterior fc-CC differences in DMN revealed significant differences between the overt HE group and other groups. Increased MD in this network was inversely associated with decreased fc-CC in DMN and linearly correlated with poor cognitive performance. In conclusion, cerebral edema can be linked to altered cerebral temporal architecture that modifies both within- and between-network connectivity in HE. Reduced fc-CC in DMN is associated with behavior and consciousness deterioration. Through appropriate targets, rs-fMRI technology may provide relevant supplemental information for monitoring HE and serve as a new biomarker for clinical diagnosis.

Network user's guide

International Nuclear Information System (INIS)

McGrady, P.W.

1994-12-01

NETWORK is a FORTRAN code used to model process flow systems in the gaseous diffusion plants at Portsmouth, Ohio and Paducah, Kentucky, operated by the United States Enrichment Corporation. It can handle a wide range of components and several different types of controllers. NETWORK can be run in either a steady-state mode or a transient mode. In the transient mode many different types of perturbations may be modeled. It is currently being used to model taking a cell off-stream in a gaseous diffusion plant. A brief description of the code is given, and process equipment models and input data are discussed

Systemic inflammation and resting state connectivity of the default mode network.

Science.gov (United States)

Marsland, Anna L; Kuan, Dora C-H; Sheu, Lei K; Krajina, Katarina; Kraynak, Thomas E; Manuck, Stephen B; Gianaros, Peter J

2017-05-01

The default mode network (DMN) encompasses brain systems that exhibit coherent neural activity at rest. DMN brain systems have been implicated in diverse social, cognitive, and affective processes, as well as risk for forms of dementia and psychiatric disorders that associate with systemic inflammation. Areas of the anterior cingulate cortex (ACC) and surrounding medial prefrontal cortex (mPFC) within the DMN have been implicated specifically in regulating autonomic and neuroendocrine processes that relate to systemic inflammation via bidirectional signaling mechanisms. However, it is still unclear whether indicators of inflammation relate directly to coherent resting state activity of the ACC, mPFC, or other areas within the DMN. Accordingly, we tested whether plasma interleukin (IL)-6, an indicator of systemic inflammation, covaried with resting-state functional connectivity of the DMN among 98 adults aged 30-54 (39% male; 81% Caucasian). Independent component analyses were applied to resting state fMRI data to generate DMN connectivity maps. Voxel-wise regression analyses were then used to test for associations between IL-6 and DMN connectivity across individuals, controlling for age, sex, body mass index, and fMRI signal motion. Within the DMN, IL-6 covaried positively with connectivity of the sub-genual ACC and negatively with a region of the dorsal medial PFC at corrected statistical thresholds. These novel findings offer evidence for a unique association between a marker of systemic inflammation (IL-6) and ACC and mPFC functional connectivity within the DMN, a network that may be important for linking aspects of immune function to psychological and behavioral states in health and disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Reconstruction of a metabolic regulatory network in Escherichia coli for purposeful switching from cell growth mode to production mode in direct GABA fermentation from glucose.

Science.gov (United States)

Soma, Yuki; Fujiwara, Yuri; Nakagawa, Takuya; Tsuruno, Keigo; Hanai, Taizo

2017-09-01

γ-aminobutyric acid (GABA) is a drug and functional food additive and is used as a monomer for producing the biodegradable plastic, polyamide 4. Recently, direct GABA fermentation from glucose has been developed as an alternative to glutamate-based whole cell bioconversion. Although total productivity in fermentation is determined by the specific productivity and cell amount responsible for GABA production, the optimal metabolic state for GABA production conflicts with that for bacterial cell growth. Herein, we demonstrated metabolic state switching from the cell growth mode based on the metabolic pathways of the wild type strain to a GABA production mode based on a synthetic metabolic pathway in Escherichia coli through rewriting of the metabolic regulatory network and pathway engineering. The GABA production mode was achieved by multiple strategies such as conditional interruption of the TCA and glyoxylate cycles, engineering of GABA production pathway including a bypass for precursor metabolite supply, and upregulation of GABA transporter. As a result, we achieved 3-fold improvement in total GABA production titer and yield (4.8g/L, 49.2% (mol/mol glucose)) in batch fermentation compared to the case without metabolic state switching (1.6g/L, 16.4% (mol/mol glucose)). This study reports the highest GABA production performance among previous reports on GABA fermentation from glucose using engineered E. coli. Copyright © 2017 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Synchronized brain activity during rehearsal and short-term memory disruption by irrelevant speech is affected by recall mode.

Science.gov (United States)

Kopp, Franziska; Schröger, Erich; Lipka, Sigrid

2006-08-01

EEG coherence as a measure of synchronization of brain activity was used to investigate effects of irrelevant speech. In a delayed serial recall paradigm 21 healthy participants retained verbal items over a 10-s delay with and without interfering irrelevant speech. Recall after the delay was varied in two modes (spoken vs. written). Behavioral data showed the classic irrelevant speech effect and a superiority of written over spoken recall mode. Coherence, however, was more sensitive to processing characteristics and showed interactions between the irrelevant speech effect and recall mode during the rehearsal delay in theta (4-7.5 Hz), alpha (8-12 Hz), beta (13-20 Hz), and gamma (35-47 Hz) frequency bands. For gamma, a rehearsal-related decrease of the duration of high coherence due to presentation of irrelevant speech was found in a left-lateralized fronto-central and centro-temporal network only in spoken but not in written recall. In theta, coherence at predominantly fronto-parietal electrode combinations was indicative for memory demands and varied with individual working memory capacity assessed by digit span. Alpha coherence revealed similar results and patterns as theta coherence. In beta, a left-hemispheric network showed longer high synchronizations due to irrelevant speech only in written recall mode. EEG results suggest that mode of recall is critical for processing already during the retention period of a delayed serial recall task. Moreover, the finding that different networks are engaged with different recall modes shows that the disrupting effect of irrelevant speech is not a unitary mechanism.

Multi-mode energy management strategy for fuel cell electric vehicles based on driving pattern identification using learning vector quantization neural network algorithm

Science.gov (United States)

Song, Ke; Li, Feiqiang; Hu, Xiao; He, Lin; Niu, Wenxu; Lu, Sihao; Zhang, Tong

2018-06-01

The development of fuel cell electric vehicles can to a certain extent alleviate worldwide energy and environmental issues. While a single energy management strategy cannot meet the complex road conditions of an actual vehicle, this article proposes a multi-mode energy management strategy for electric vehicles with a fuel cell range extender based on driving condition recognition technology, which contains a patterns recognizer and a multi-mode energy management controller. This paper introduces a learning vector quantization (LVQ) neural network to design the driving patterns recognizer according to a vehicle's driving information. This multi-mode strategy can automatically switch to the genetic algorithm optimized thermostat strategy under specific driving conditions in the light of the differences in condition recognition results. Simulation experiments were carried out based on the model's validity verification using a dynamometer test bench. Simulation results show that the proposed strategy can obtain better economic performance than the single-mode thermostat strategy under dynamic driving conditions.

A Bayesian network model for predicting aquatic toxicity mode of action using two dimensional theoretical molecular descriptors

Energy Technology Data Exchange (ETDEWEB)

Carriger, John F. [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States); Martin, Todd M. [U.S. Environmental Protection Agency, Office of Research and Development, Sustainable Technology Division, Cincinnati, OH, 45220 (United States); Barron, Mace G., E-mail: barron.mace@epa.gov [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States)

2016-11-15

Highlights: • A Bayesian network was developed to classify chemical mode of action (MoA). • The network was based on the aquatic toxicity MoA for over 1000 chemicals. • A Markov blanket algorithm selected a subset of theoretical molecular descriptors. • Sensitivity analyses found influential descriptors for classifying the MoAs. • Overall precision of the Bayesian MoA classification model was 80%. - Abstract: The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity, but development of predictive MoA classification models in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity MoA using a recently published dataset containing over one thousand chemicals with MoA assignments for aquatic animal toxicity. Two dimensional theoretical chemical descriptors were generated for each chemical using the Toxicity Estimation Software Tool. The model was developed through augmented Markov blanket discovery from the dataset of 1098 chemicals with the MoA broad classifications as a target node. From cross validation, the overall precision for the model was 80.2%. The best precision was for the AChEI MoA (93.5%) where 257 chemicals out of 275 were correctly classified. Model precision was poorest for the reactivity MoA (48.5%) where 48 out of 99 reactive chemicals were correctly classified. Narcosis represented the largest class within the MoA dataset and had a precision and reliability of 80.0%, reflecting the global precision across all of the MoAs. False negatives for narcosis most often fell into electron transport inhibition, neurotoxicity or reactivity MoAs. False negatives for all other MoAs were most often narcosis. A probabilistic sensitivity analysis was undertaken for each MoA to examine the sensitivity to individual and multiple descriptor findings. The results show that the Markov blanket of a structurally complex dataset can simplify analysis and interpretation by

Modulation of dynamic modes by interplay between positive and negative feedback loops in gene regulatory networks

Science.gov (United States)

Wang, Liu-Suo; Li, Ning-Xi; Chen, Jing-Jia; Zhang, Xiao-Peng; Liu, Feng; Wang, Wei

2018-04-01

A positive and a negative feedback loop can induce bistability and oscillation, respectively, in biological networks. Nevertheless, they are frequently interlinked to perform more elaborate functions in many gene regulatory networks. Coupled positive and negative feedback loops may exhibit either oscillation or bistability depending on the intensity of the stimulus in some particular networks. It is less understood how the transition between the two dynamic modes is modulated by the positive and negative feedback loops. We developed an abstract model of such systems, largely based on the core p53 pathway, to explore the mechanism for the transformation of dynamic behaviors. Our results show that enhancing the positive feedback may promote or suppress oscillations depending on the strength of both feedback loops. We found that the system oscillates with low amplitudes in response to a moderate stimulus and switches to the on state upon a strong stimulus. When the positive feedback is activated much later than the negative one in response to a strong stimulus, the system exhibits long-term oscillations before switching to the on state. We explain this intriguing phenomenon using quasistatic approximation. Moreover, early switching to the on state may occur when the system starts from a steady state in the absence of stimuli. The interplay between the positive and negative feedback plays a key role in the transitions between oscillation and bistability. Of note, our conclusions should be applicable only to some specific gene regulatory networks, especially the p53 network, in which both oscillation and bistability exist in response to a certain type of stimulus. Our work also underscores the significance of transient dynamics in determining cellular outcome.

ANALYSIS OF ENERGY EFFICIENCY OF OPERATING MODES OF ELECTRICAL SYSTEMS WITH THE TRACTION LOADS

Directory of Open Access Journals (Sweden)

V. E. Bondarenko

2017-03-01

Full Text Available Innovative scenarios of reliable energy supply of transportation process aimed at reducing the specific energy consumption and increase energy efficiency of the systems of electric traction. The paper suggests innovative energy saving directions in traction networks of railways and new circuit solutions accessing traction substations in energy systems networks, ensure energy security of the transportation process. To ensure the energy security of rail transport special schemes were developed to propose the concept of external power traction substations, which would increase the number of connections to the networks of 220 – 330 kV, as well as the creation of transport and energy corridors, development of its own supply of electric networks of 110 kV substations and mobile RP-110 kV of next generation. Therefore, the investment program of the structures owned by the Ukrainian Railways (Ukrzaliznytsia need to be synchronized in their technological characteristics, as well as the criteria of reliability and quality of power supply with the same external energy investment programs. It is found that without any load on left or right supplying arm one of two less loaded phases of traction transformer begins generating specific modes in the supplying three-phase line. Thus, modes of mobile substation cause leakage in one of the phases of the supply line of traction transformers of active-capacitive current, and as a result generating energy in the main power line of 154 kV, which is fixed and calculated by electricity meters. For these three phase mode supply network is necessary to use 1st algorithm, i.e. taking into account the amount of electricity as the energy in all phases. For effective application of reactive power compensation devices in the AC traction power supply systems it is proposed to develop regulatory documentation on necessity of application and the order of choice of parameters and placement of compensation systems taking into

Metropolitian area network services comprised of virtual local area networks running over hybrid fiber-coax and asynchronous transfer mode technologies

Science.gov (United States)

Biedron, William S.

1995-11-01

Since 1990 there has been a rapid increase in the demand for communication services, especially local and wide area network (LAN/WAN) oriented services. With the introduction of the DFB laser transmitter, hybrid-fiber-coax (HFC) cable plant designs, ATM transport technologies and rf modems, new LAN/WAN services can now be defined and marketed to residential and business customers over existing cable TV systems. The term metropolitan area network (MAN) can be used to describe this overall network. This paper discusses the technical components needed to provision these services as well as provides some perspectives on integration issues. Architecture at the headend and in the backbone is discussed, as well as specific service definitions and the technology issues associated with each. The TCP/IP protocol is suggested as a primary protocol to be used throughout the MAN.

Scholastic performance and functional connectivity of brain networks in children.

Directory of Open Access Journals (Sweden)

Laura Chaddock-Heyman

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

Streaming tearing mode

Science.gov (United States)

Shigeta, M.; Sato, T.; Dasgupta, B.

1985-01-01

The magnetohydrodynamic stability of streaming tearing mode is investigated numerically. A bulk plasma flow parallel to the antiparallel magnetic field lines and localized in the neutral sheet excites a streaming tearing mode more strongly than the usual tearing mode, particularly for the wavelength of the order of the neutral sheet width (or smaller), which is stable for the usual tearing mode. Interestingly, examination of the eigenfunctions of the velocity perturbation and the magnetic field perturbation indicates that the streaming tearing mode carries more energy in terms of the kinetic energy rather than the magnetic energy. This suggests that the streaming tearing mode instability can be a more feasible mechanism of plasma acceleration than the usual tearing mode instability.

Mode of effective connectivity within a putative neural network differentiates moral cognitions related to care and justice ethics.

Science.gov (United States)

Cáceda, Ricardo; James, G Andrew; Ely, Timothy D; Snarey, John; Kilts, Clinton D

2011-02-25

Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC) and posterior (PCC) cingulate cortex, posterior superior temporal sulcus (pSTS), insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses.

Large-scale brain network coupling predicts acute nicotine abstinence effects on craving and cognitive function.

Science.gov (United States)

Lerman, Caryn; Gu, Hong; Loughead, James; Ruparel, Kosha; Yang, Yihong; Stein, Elliot A

2014-05-01

Interactions of large-scale brain networks may underlie cognitive dysfunctions in psychiatric and addictive disorders. To test the hypothesis that the strength of coupling among 3 large-scale brain networks--salience, executive control, and default mode--will reflect the state of nicotine withdrawal (vs smoking satiety) and will predict abstinence-induced craving and cognitive deficits and to develop a resource allocation index (RAI) that reflects the combined strength of interactions among the 3 large-scale networks. A within-subject functional magnetic resonance imaging study in an academic medical center compared resting-state functional connectivity coherence strength after 24 hours of abstinence and after smoking satiety. We examined the relationship of abstinence-induced changes in the RAI with alterations in subjective, behavioral, and neural functions. We included 37 healthy smoking volunteers, aged 19 to 61 years, for analyses. Twenty-four hours of abstinence vs smoking satiety. Inter-network connectivity strength (primary) and the relationship with subjective, behavioral, and neural measures of nicotine withdrawal during abstinence vs smoking satiety states (secondary). The RAI was significantly lower in the abstinent compared with the smoking satiety states (left RAI, P = .002; right RAI, P = .04), suggesting weaker inhibition between the default mode and salience networks. Weaker inter-network connectivity (reduced RAI) predicted abstinence-induced cravings to smoke (r = -0.59; P = .007) and less suppression of default mode activity during performance of a subsequent working memory task (ventromedial prefrontal cortex, r = -0.66, P = .003; posterior cingulate cortex, r = -0.65, P = .001). Alterations in coupling of the salience and default mode networks and the inability to disengage from the default mode network may be critical in cognitive/affective alterations that underlie nicotine dependence.

Structural and functional cerebral correlates of hypnotic suggestibility.

Directory of Open Access Journals (Sweden)

Alexa Huber

Full Text Available Little is known about the neural bases of hypnotic suggestibility, a cognitive trait referring to the tendency to respond to hypnotic suggestions. In the present magnetic resonance imaging study, we performed regression analyses to assess hypnotic suggestibility-related differences in local gray matter volume, using voxel-based morphometry, and in waking resting state functional connectivity of 10 resting state networks, in 37 healthy women. Hypnotic suggestibility was positively correlated with gray matter volume in portions of the left superior and medial frontal gyri, roughly overlapping with the supplementary and pre-supplementary motor area, and negatively correlated with gray matter volume in the left superior temporal gyrus and insula. In the functional connectivity analysis, hypnotic suggestibility was positively correlated with functional connectivity between medial posterior areas, including bilateral posterior cingulate cortex and precuneus, and both the lateral visual network and the left fronto-parietal network; a positive correlation was also found with functional connectivity between the executive-control network and a right postcentral/parietal area. In contrast, hypnotic suggestibility was negatively correlated with functional connectivity between the right fronto-parietal network and the right lateral thalamus. These findings demonstrate for the first time a correlation between hypnotic suggestibility, the structural features of specific cortical regions, and the functional connectivity during the normal resting state of brain structures involved in imagery and self-monitoring activity.

Structural and functional cerebral correlates of hypnotic suggestibility.

Science.gov (United States)

Huber, Alexa; Lui, Fausta; Duzzi, Davide; Pagnoni, Giuseppe; Porro, Carlo Adolfo

2014-01-01

Little is known about the neural bases of hypnotic suggestibility, a cognitive trait referring to the tendency to respond to hypnotic suggestions. In the present magnetic resonance imaging study, we performed regression analyses to assess hypnotic suggestibility-related differences in local gray matter volume, using voxel-based morphometry, and in waking resting state functional connectivity of 10 resting state networks, in 37 healthy women. Hypnotic suggestibility was positively correlated with gray matter volume in portions of the left superior and medial frontal gyri, roughly overlapping with the supplementary and pre-supplementary motor area, and negatively correlated with gray matter volume in the left superior temporal gyrus and insula. In the functional connectivity analysis, hypnotic suggestibility was positively correlated with functional connectivity between medial posterior areas, including bilateral posterior cingulate cortex and precuneus, and both the lateral visual network and the left fronto-parietal network; a positive correlation was also found with functional connectivity between the executive-control network and a right postcentral/parietal area. In contrast, hypnotic suggestibility was negatively correlated with functional connectivity between the right fronto-parietal network and the right lateral thalamus. These findings demonstrate for the first time a correlation between hypnotic suggestibility, the structural features of specific cortical regions, and the functional connectivity during the normal resting state of brain structures involved in imagery and self-monitoring activity.

Social network sites as a mode to collect health data: a systematic review.

Science.gov (United States)

Alshaikh, Fahdah; Ramzan, Farzan; Rawaf, Salman; Majeed, Azeem

2014-07-14

To date, health research literature has focused on social network sites (SNS) either as tools to deliver health care, to study the effect of these networks on behavior, or to analyze Web health content. Less is known about the effectiveness of these sites as a method for collecting data for health research and the means to use such powerful tools in health research. The objective of this study was to systematically review the available literature and explore the use of SNS as a mode of collecting data for health research. The review aims to answer four questions: Does health research employ SNS as method for collecting data? Is data quality affected by the mode of data collection? What types of participants were reached by SNS? What are the strengths and limitations of SNS? The literature was reviewed systematically in March 2013 by searching the databases MEDLINE, Embase, and PsycINFO, using the Ovid and PubMed interface from 1996 to the third week of March 2013. The search results were examined by 2 reviewers, and exclusion, inclusion, and quality assessment were carried out based on a pre-set protocol. The inclusion criteria were met by 10 studies and results were analyzed descriptively to answer the review questions. There were four main results. (1) SNS have been used as a data collection tool by health researchers; all but 1 of the included studies were cross-sectional and quantitative. (2) Data quality indicators that were reported include response rate, cost, timeliness, missing data/completion rate, and validity. However, comparison was carried out only for response rate and cost as it was unclear how other reported indicators were measured. (3) The most targeted population were females and younger people. (4) All studies stated that SNS is an effective recruitment method but that it may introduce a sampling bias. SNS has a role in health research, but we need to ascertain how to use it effectively without affecting the quality of research. The field of

Improved diagnostic accuracy of Alzheimer's disease by combining regional cortical thickness and default mode network functional connectivity: Validated in the Alzheimer's disease neuroimaging initiative set

International Nuclear Information System (INIS)

Park, Ji Eun; Park, Bum Woo; Kim, Sang Joon; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Jung; Oh, Joo Young; Shim, Woo Hyun; Lee, Jae Hong; Roh, Jee Hoon

2017-01-01

To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal (p < 0.001) and supramarginal gyrus (p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease

Aging and functional brain networks

International Nuclear Information System (INIS)

Tomasi D.; Volkow, N.D.

2012-01-01

Aging is associated with changes in human brain anatomy and function and cognitive decline. Recent studies suggest the aging decline of major functional connectivity hubs in the 'default-mode' network (DMN). Aging effects on other networks, however, are largely unknown. We hypothesized that aging would be associated with a decline of short- and long-range functional connectivity density (FCD) hubs in the DMN. To test this hypothesis, we evaluated resting-state data sets corresponding to 913 healthy subjects from a public magnetic resonance imaging database using functional connectivity density mapping (FCDM), a voxelwise and data-driven approach, together with parallel computing. Aging was associated with pronounced long-range FCD decreases in DMN and dorsal attention network (DAN) and with increases in somatosensory and subcortical networks. Aging effects in these networks were stronger for long-range than for short-range FCD and were also detected at the level of the main functional hubs. Females had higher short- and long-range FCD in DMN and lower FCD in the somatosensory network than males, but the gender by age interaction effects were not significant for any of the networks or hubs. These findings suggest that long-range connections may be more vulnerable to aging effects than short-range connections and that, in addition to the DMN, the DAN is also sensitive to aging effects, which could underlie the deterioration of attention processes that occurs with aging.

Intrinsic default mode network connectivity predicts spontaneous verbal descriptions of autobiographical memories during social processing

Directory of Open Access Journals (Sweden)

Xiao-Fei eYang

2013-01-01

Full Text Available Neural systems activated in a coordinated way during rest, known as the default mode network (DMN, also support autobiographical memory (AM retrieval and social processing/mentalizing. However, little is known about how individual variability in reliance on personal memories during social processing relates to individual differences in DMN functioning during rest (intrinsic functional connectivity. Here we examined 18 participants’ spontaneous descriptions of autobiographical memories during a two-hour, private, open-ended interview in which they reacted to a series of true stories about real people’s social situations and responded to the prompt, how does this person’s story make you feel? We classified these descriptions as either containing factual information (semantic AMs or more elaborate descriptions of emotionally meaningful events (episodic AMs. We also collected resting state fMRI scans from the participants and related individual differences in frequency of described AMs to participants’ intrinsic functional connectivity within regions of the DMN. We found that producing more descriptions of either memory type correlated with stronger intrinsic connectivity in the parahippocampal and middle temporal gyri. Additionally, episodic AM descriptions correlated with connectivity in the bilateral hippocampi and medial prefrontal cortex, and semantic memory descriptions correlated with connectivity in right inferior lateral parietal cortex. These findings suggest that in individuals who naturally invoke more memories during social processing, brain regions involved in memory retrieval and self/social processing are more strongly coupled to the DMN during rest.

Exploring default mode and information flow on the web.

Science.gov (United States)

Oka, Mizuki; Ikegami, Takashi

2013-01-01

Social networking services (e.g., Twitter, Facebook) are now major sources of World Wide Web (called "Web") dynamics, together with Web search services (e.g., Google). These two types of Web services mutually influence each other but generate different dynamics. In this paper, we distinguish two modes of Web dynamics: the reactive mode and the default mode. It is assumed that Twitter messages (called "tweets") and Google search queries react to significant social movements and events, but they also demonstrate signs of becoming self-activated, thereby forming a baseline Web activity. We define the former as the reactive mode and the latter as the default mode of the Web. In this paper, we investigate these reactive and default modes of the Web's dynamics using transfer entropy (TE). The amount of information transferred between a time series of 1,000 frequent keywords in Twitter and the same keywords in Google queries is investigated across an 11-month time period. Study of the information flow on Google and Twitter revealed that information is generally transferred from Twitter to Google, indicating that Twitter time series have some preceding information about Google time series. We also studied the information flow among different Twitter keywords time series by taking keywords as nodes and flow directions as edges of a network. An analysis of this network revealed that frequent keywords tend to become an information source and infrequent keywords tend to become sink for other keywords. Based on these findings, we hypothesize that frequent keywords form the Web's default mode, which becomes an information source for infrequent keywords that generally form the Web's reactive mode. We also found that the Web consists of different time resolutions with respect to TE among Twitter keywords, which will be another focal point of this paper.

Measurement of correlations between low-frequency vibrational modes and particle rearrangements in quasi-two-dimensional colloidal glasses.

Science.gov (United States)

Chen, Ke; Manning, M L; Yunker, Peter J; Ellenbroek, Wouter G; Zhang, Zexin; Liu, Andrea J; Yodh, A G

2011-09-02

We investigate correlations between low-frequency vibrational modes and rearrangements in two-dimensional colloidal glasses composed of thermosensitive microgel particles, which readily permit variation of the sample packing fraction. At each packing fraction, the particle displacement covariance matrix is measured and used to extract the vibrational spectrum of the "shadow" colloidal glass (i.e., the particle network with the same geometry and interactions as the sample colloid but absent damping). Rearrangements are induced by successive, small reductions in the packing fraction. The experimental results suggest that low-frequency quasilocalized phonon modes in colloidal glasses, i.e., modes that present low energy barriers for system rearrangements, are spatially correlated with rearrangements in this thermal system.

Decreased Fronto-Parietal and Increased Default Mode Network Activation is Associated with Subtle Cognitive Deficits in Elderly Controls

Directory of Open Access Journals (Sweden)

Davide Zanchi

2017-12-01

Full Text Available Background: Cognitive functions progressively deteriorate during aging and neurodegenerative diseases. The present study aims at investigating differences in working memory performance as well as functional brain changes during the earliest stages of cognitive decline in health elderly individuals. Methods: 62 elderly individuals (41 females, including 41 controls (35 females and 21 middle cognitive impairment subjects (6 females, underwent neuropsychological assessment at baseline and an fMRI examination in a N-back paradigm contrasting 2-back vs. 0-back condition. Upon a 18 months follow-up, we identified stable controls (sCON with preserved cognition and deteriorating controls (dCON with -1SD decrease of performances in at least two neuropsychological tests. Data analyses included accuracy and reaction time (RT for the 2-back condition and general linear model (GLM for the fMRI sequence. Results: At the behavioral level, sCON and dCON performed better than MCI in terms of accuracy and reaction time. At the brain level, functional differences in regions of the fronto-parietal network (FPN and of the Default Mode Network (DFM were observed. Significantly lower neural activations in the bilateral inferior and middle frontal gyri were found in MCI versus both dCON / sCON and for dCON versus sCON. Significantly increased activations in the anterior cingulate cortex and posterior cingulate cortex and bilateral insula were found in MCI versus both dCON / sCON and in dCON versus sCON. Conclusion: The present study suggests that brain functional changes in FPN and DMN anticipate differences in cognitive performance in healthy elderly individuals with subsequent subtle cognitive decline.

A note on the complexity of finding and enumerating elementary modes.

NARCIS (Netherlands)

Acuna, V.; Marchetti-Spaccamela, A.; Sagot, M.-F.; Stougie, L.

2010-01-01

In the context of the study into elementary modes of metabolic networks, we prove two complexity results. Enumerating elementary modes containing a specific reaction is hard in an enumeration complexity sense. The decision problem if there exists an elementary mode containing two specific reactions

Mathematics anxiety reduces default mode network deactivation in response to numerical tasks

Directory of Open Access Journals (Sweden)

Belinda ePletzer

2015-04-01

Full Text Available Mathematics anxiety is negatively related to mathematics performance, thereby threatening the professional success. Preoccupation with the emotional content of the stimuli may consume working memory resources, which may be reflected in decreased deactivation of areas associated with the default mode network (DMN activated during self-referential and emotional processing. The common problem is that math anxiety is usually associated with poor math performance, so that any group differences are difficult to interpret.Here we compared the BOLD-response of 18 participants with high (HMAs and 18 participants with low mathematics anxiety (LMAs matched for their mathematical performance to two numerical tasks (number comparison, number bisection. During both tasks, we found stronger deactivation within the DMN in LMAs compared to HMAs, while BOLD-response in task-related activation areas did not differ between HMAs and LMAs. The difference in DMN deactivation between the HMA and LMA group was more pronounced in stimuli with additional requirement on inhibitory functions, but did not differ between number magnitude processing and arithmetic fact retrieval.

Mathematics anxiety reduces default mode network deactivation in response to numerical tasks.

Science.gov (United States)

Pletzer, Belinda; Kronbichler, Martin; Nuerk, Hans-Christoph; Kerschbaum, Hubert H

2015-01-01

Mathematics anxiety is negatively related to mathematics performance, thereby threatening the professional success. Preoccupation with the emotional content of the stimuli may consume working memory resources, which may be reflected in decreased deactivation of areas associated with the default mode network (DMN) activated during self-referential and emotional processing. The common problem is that math anxiety is usually associated with poor math performance, so that any group differences are difficult to interpret. Here we compared the BOLD-response of 18 participants with high (HMAs) and 18 participants with low mathematics anxiety (LMAs) matched for their mathematical performance to two numerical tasks (number comparison, number bisection). During both tasks, we found stronger deactivation within the DMN in LMAs compared to HMAs, while BOLD-response in task-related activation areas did not differ between HMAs and LMAs. The difference in DMN deactivation between the HMA and LMA group was more pronounced in stimuli with additional requirement on inhibitory functions, but did not differ between number magnitude processing and arithmetic fact retrieval.

Indirect intelligent sliding mode control of a shape memory alloy actuated flexible beam using hysteretic recurrent neural networks

International Nuclear Information System (INIS)

Hannen, Jennifer C; Buckner, Gregory D; Crews, John H

2012-01-01

This paper introduces an indirect intelligent sliding mode controller (IISMC) for shape memory alloy (SMA) actuators, specifically a flexible beam deflected by a single offset SMA tendon. The controller manipulates applied voltage, which alters SMA tendon temperature to track reference bending angles. A hysteretic recurrent neural network (HRNN) captures the nonlinear, hysteretic relationship between SMA temperature and bending angle. The variable structure control strategy provides robustness to model uncertainties and parameter variations, while effectively compensating for system nonlinearities, achieving superior tracking compared to an optimized PI controller. (paper)

Performance of asynchronous transfer mode (ATM) local area and wide area networks for medical imaging transmission in clinical environment.

Science.gov (United States)

Huang, H K; Wong, A W; Zhu, X

1997-01-01

Asynchronous transfer mode (ATM) technology emerges as a leading candidate for medical image transmission in both local area network (LAN) and wide area network (WAN) applications. This paper describes the performance of an ATM LAN and WAN network at the University of California, San Francisco. The measurements were obtained using an intensive care unit (ICU) server connecting to four image workstations (WS) at four different locations of a hospital-integrated picture archiving and communication system (HI-PACS) in a daily regular clinical environment. Four types of performance were evaluated: magnetic disk-to-disk, disk-to-redundant array of inexpensive disks (RAID), RAID-to-memory, and memory-to-memory. Results demonstrate that the transmission rate between two workstations can reach 5-6 Mbytes/s from RAID-to-memory, and 8-10 Mbytes/s from memory-to-memory. When the server has to send images to all four workstations simultaneously, the transmission rate to each WS is about 4 Mbytes/s. Both situations are adequate for radiologic image communications for picture archiving and communication systems (PACS) and teleradiology applications.

The effects of CPAP treatment on task positive and default mode networks in obstructive sleep apnea patients: an fMRI study.

Directory of Open Access Journals (Sweden)

Olga Prilipko

Full Text Available INTRODUCTION: Functional magnetic resonance imaging studies enable the investigation of neural correlates underlying behavioral performance. We investigate the effect of active and sham Continuous Positive Airway Pressure (CPAP treatment on working memory function of patients with Obstructive Sleep Apnea Syndrome (OSAS considering Task Positive and Default Mode networks (TPN and DMN. METHODS: An experiment with 4 levels of visuospatial n-back task was used to investigate the pattern of cortical activation in 17 men with moderate or severe OSAS before and after 2 months of therapeutic (active or sub-therapeutic (sham CPAP treatment. RESULTS: Patients with untreated OSAS had significantly less deactivation in the temporal regions of the DMN as compared to healthy controls, but activation within TPN regions was comparatively relatively preserved. After 2 months of treatment, active and sham CPAP groups exhibited opposite trends of cerebral activation and deactivation. After treatment, the active CPAP group demonstrated an increase of cerebral activation in the TPN at all task levels and of task-related cerebral deactivation in the anterior midline and medial temporal regions of the DMN at the 3-back level, associated with a significant improvement of behavioral performance, whereas the sham CPAP group exhibited less deactivation in the temporal regions of Default Mode Network and less Task Positive Network activation associated to longer response times at the 3-back. CONCLUSION: OSAS has a significant negative impact primarily on task-related DMN deactivation, particularly in the medial temporal regions, possibly due to nocturnal hypoxemia, as well as TPN activation, particularly in the right ventral fronto-parietal network. After 2 months of active nasal CPAP treatment a positive response was noted in both TPN and DMN but without compete recovery of existing behavioral and neuronal deficits. Initiation of CPAP treatment early in the course of the

Intrinsic brain networks normalize with treatment in pediatric complex regional pain syndrome

Science.gov (United States)

Becerra, Lino; Sava, Simona; Simons, Laura E.; Drosos, Athena M.; Sethna, Navil; Berde, Charles; Lebel, Alyssa A.; Borsook, David

2014-01-01

Pediatric complex regional pain syndrome (P-CRPS) offers a unique model of chronic neuropathic pain as it either resolves spontaneously or through therapeutic interventions in most patients. Here we evaluated brain changes in well-characterized children and adolescents with P-CRPS by measuring resting state networks before and following a brief (median = 3 weeks) but intensive physical and psychological treatment program, and compared them to matched healthy controls. Differences in intrinsic brain networks were observed in P-CRPS compared to controls before treatment (disease state) with the most prominent differences in the fronto-parietal, salience, default mode, central executive, and sensorimotor networks. Following treatment, behavioral measures demonstrated a reduction of symptoms and improvement of physical state (pain levels and motor functioning). Correlation of network connectivities with spontaneous pain measures pre- and post-treatment indicated concomitant reductions in connectivity in salience, central executive, default mode and sensorimotor networks (treatment effects). These results suggest a rapid alteration in global brain networks with treatment and provide a venue to assess brain changes in CRPS pre- and post-treatment, and to evaluate therapeutic effects. PMID:25379449

Intrinsic brain networks normalize with treatment in pediatric complex regional pain syndrome

Directory of Open Access Journals (Sweden)

Lino Becerra

2014-01-01

Full Text Available Pediatric complex regional pain syndrome (P-CRPS offers a unique model of chronic neuropathic pain as it either resolves spontaneously or through therapeutic interventions in most patients. Here we evaluated brain changes in well-characterized children and adolescents with P-CRPS by measuring resting state networks before and following a brief (median = 3 weeks but intensive physical and psychological treatment program, and compared them to matched healthy controls. Differences in intrinsic brain networks were observed in P-CRPS compared to controls before treatment (disease state with the most prominent differences in the fronto-parietal, salience, default mode, central executive, and sensorimotor networks. Following treatment, behavioral measures demonstrated a reduction of symptoms and improvement of physical state (pain levels and motor functioning. Correlation of network connectivities with spontaneous pain measures pre- and post-treatment indicated concomitant reductions in connectivity in salience, central executive, default mode and sensorimotor networks (treatment effects. These results suggest a rapid alteration in global brain networks with treatment and provide a venue to assess brain changes in CRPS pre- and post-treatment, and to evaluate therapeutic effects.

Reentrant Information Flow in Electrophysiological Rat Default Mode Network.

Science.gov (United States)

Jing, Wei; Guo, Daqing; Zhang, Yunxiang; Guo, Fengru; Valdés-Sosa, Pedro A; Xia, Yang; Yao, Dezhong

2017-01-01

Functional MRI (fMRI) studies have demonstrated that the rodent brain shows a default mode network (DMN) activity similar to that in humans, offering a potential preclinical model both for physiological and pathophysiological studies. However, the neuronal mechanism underlying rodent DMN remains poorly understood. Here, we used electrophysiological data to analyze the power spectrum and estimate the directed phase transfer entropy (dPTE) within rat DMN across three vigilance states: wakeful rest (WR), slow-wave sleep (SWS), and rapid-eye-movement sleep (REMS). We observed decreased gamma powers during SWS compared with WR in most of the DMN regions. Increased gamma powers were found in prelimbic cortex, cingulate cortex, and hippocampus during REMS compared with WR, whereas retrosplenial cortex showed a reverse trend. These changed gamma powers are in line with the local metabolic variation of homologous brain regions in humans. In the analysis of directional interactions, we observed well-organized anterior-to-posterior patterns of information flow in the delta band, while opposite patterns of posterior-to-anterior flow were found in the theta band. These frequency-specific opposite patterns were only observed in WR and REMS. Additionally, most of the information senders in the delta band were also the receivers in the theta band, and vice versa. Our results provide electrophysiological evidence that rat DMN is similar to its human counterpart, and there is a frequency-dependent reentry loop of anterior-posterior information flow within rat DMN, which may offer a mechanism for functional integration, supporting conscious awareness.

Default mode network connectivity in children with a history of preschool onset depression.

Science.gov (United States)

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

2012-09-01

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

Early warning network of the Czech Republic

International Nuclear Information System (INIS)

Drabova, D.; Kuca, P.; Prouza, Z.

1998-01-01

The Early Warning Network encompasses 48 measuring sites covering the whole territory of the Czech Republic; 38 of them are located at observatories of the Czech Hydro-Meteorological Institute (28 at round-the-clock manned observatories, 10 at unmanned, automated observatories) and 10 are located at air contamination measuring points operated by the National Radiation Protection Institute and Regional Centres of the State Office for Nuclear Safety. The network operates in one of 3 modes: the standard mode, alert mode, and emergency mode. (P.A.)

Towards Third-Generation Living Lab Networks in Cities

Directory of Open Access Journals (Sweden)

Seppo Leminen

2017-11-01

Full Text Available Many cities engage in diverse experimentation, innovation, and development activities with a broad variety of environments and stakeholders to the benefit of citizens, companies, municipalities, and other organizations. Hence, this article discusses such engagement in terms of next-generation living lab networks in the city context. In so doing, the study contributes to the discussion on living labs by introducing a framework of collaborative innovation networks in cities and suggesting a typology of third-generation living labs. Our framework is characterized by diverse platforms and participation approaches, resulting in four distinctive modes of collaborative innovation networks where the city is: i a provider, ii a neighbourhood participator, iii a catalyst, or iv a rapid experimenter. The typology is based on an analysis of 118 interviews with participants in six Finnish cities and reveals various ways to organize innovation activities in the city context. In particular, cities can benefit from innovation networks by simultaneously exploiting multiple platforms such as living labs for innovation. We conclude by discussing implications to theory and practice, and suggesting directions for future research.

APPLICATION OF A FULL-COHERENT ARTIFICIAL NEURAL NETWORK FOR FORECASTING OF THE MODES OF STORAGE OF DOMESTIC LOW-OLIVE RAW MATERIALS IN CONTROLLED ENVIRONMENTS

Directory of Open Access Journals (Sweden)

N. S. Rodionova

2015-01-01

Full Text Available Summary. Researches on increase in an expiration date of the wheat germs (WG with use of compositions of organic acids are conducted. With a research objective of influence of concentration of mixes of organic acids on change of indicators of quality at storage of the SALARY in various modes investigated quality indicators in the range of concentration of 1-7% to the mass of a product. As control the raw SALARIES served. Skilled products stored in refrigerator conditions (temperature 4-6 ºС, relative humidity of air of 75-80% and a warehouse (temperature 20-22 ºС, relative humidity of air of 70-80%. The software product on the basis of the program of training and the analysis of training of an artificial full-coherent neural network (INS in the Python 2.7 language with program libraries of mathematical processing of scientific data of "scipy" is developed. As input parameters of a neural network were considered: humidity of wheaten germs (х1, %, relative humidity of air (х2, %, ambient temperature (х3, ºС and concentration of mix of organic acids (х4, %. By means of the software, some neural networks were designed and trained. For modeling the network with two layers was used. Applying the developed and trained neural network it is possible constructed dependence у(х1, х2, х3, х4. For visualization in three-dimensional space limited amount of arguments of function by two. Results of work of neural networks y (x1, x4 with the recorded entrance parameters (x2 = 60, %, x3=20, ºC and a neural network y (x2, x3 with the recorded input parameters are presented (x1 = 15%, x4 = 5%. The received mathematical model which on the set set of certain parameters of storage, allows to receive concrete value of output parameter and to plan the storage modes in controlled environments.

Mode of effective connectivity within a putative neural network differentiates moral cognitions related to care and justice ethics.

Directory of Open Access Journals (Sweden)

Ricardo Cáceda

Full Text Available BACKGROUND: Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC and posterior (PCC cingulate cortex, posterior superior temporal sulcus (pSTS, insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. METHODOLOGY/PRINCIPAL FINDINGS: Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. CONCLUSIONS/SIGNIFICANCE: These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses.

Mode of Effective Connectivity within a Putative Neural Network Differentiates Moral Cognitions Related to Care and Justice Ethics

Science.gov (United States)

Cáceda, Ricardo; James, G. Andrew; Ely, Timothy D.; Snarey, John; Kilts, Clinton D.

2011-01-01

Background Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC) and posterior (PCC) cingulate cortex, posterior superior temporal sulcus (pSTS), insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. Methodology/Principal Findings Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. Conclusions/Significance These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses. PMID:21364916

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

Science.gov (United States)

Washington, Stuart D; VanMeter, John W

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

Operating principle of Soft Open Points for electrical distribution network operation

International Nuclear Information System (INIS)

Cao, Wanyu; Wu, Jianzhong; Jenkins, Nick; Wang, Chengshan; Green, Timothy

2016-01-01

Highlights: • Two control modes were developed for a B2B VSCs based SOP. • The SOP operating principle was investigated under various network conditions. • The performance of the SOP using two control modes was analyzed. - Abstract: Soft Open Points (SOPs) are power electronic devices installed in place of normally-open points in electrical power distribution networks. They are able to provide active power flow control, reactive power compensation and voltage regulation under normal network operating conditions, as well as fast fault isolation and supply restoration under abnormal conditions. Two control modes were developed for the operation of an SOP, using back-to-back voltage-source converters (VSCs). A power flow control mode with current control provides independent control of real and reactive power. A supply restoration mode with a voltage controller enables power supply to isolated loads due to network faults. The operating principle of the back-to-back VSCs based SOP was investigated under both normal and abnormal network operating conditions. Studies on a two-feeder medium-voltage distribution network showed the performance of the SOP under different network-operating conditions: normal, during a fault and post-fault supply restoration. During the change of network operating conditions, a mode switch method based on the phase locked loop controller was used to achieve the transitions between the two control modes. Hard transitions by a direct mode switching were noticed unfavourable, but seamless transitions were obtained by deploying a soft cold load pickup and voltage synchronization process.

Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

Science.gov (United States)

Fei, Juntao; Lu, Cheng

2018-04-01

In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.

Risk seeking for losses modulates the functional connectivity of the default mode and left frontoparietal networks in young males.

Science.gov (United States)

Deza Araujo, Yacila I; Nebe, Stephan; Neukam, Philipp T; Pooseh, Shakoor; Sebold, Miriam; Garbusow, Maria; Heinz, Andreas; Smolka, Michael N

2018-06-01

Value-based decision making (VBDM) is a principle that states that humans and other species adapt their behavior according to the dynamic subjective values of the chosen or unchosen options. The neural bases of this process have been extensively investigated using task-based fMRI and lesion studies. However, the growing field of resting-state functional connectivity (RSFC) may shed light on the organization and function of brain connections across different decision-making domains. With this aim, we used independent component analysis to study the brain network dynamics in a large cohort of young males (N = 145) and the relationship of these dynamics with VBDM. Participants completed a battery of behavioral tests that evaluated delay aversion, risk seeking for losses, risk aversion for gains, and loss aversion, followed by an RSFC scan session. We identified a set of large-scale brain networks and conducted our analysis only on the default mode network (DMN) and networks comprising cognitive control, appetitive-driven, and reward-processing regions. Higher risk seeking for losses was associated with increased connectivity between medial temporal regions, frontal regions, and the DMN. Higher risk seeking for losses was also associated with increased coupling between the left frontoparietal network and occipital cortices. These associations illustrate the participation of brain regions involved in prospective thinking, affective decision making, and visual processing in participants who are greater risk-seekers, and they demonstrate the sensitivity of RSFC to detect brain connectivity differences associated with distinct VBDM parameters.

Multiscale virtual particle based elastic network model (MVP-ENM) for normal mode analysis of large-sized biomolecules.

Science.gov (United States)

Xia, Kelin

2017-12-20

In this paper, a multiscale virtual particle based elastic network model (MVP-ENM) is proposed for the normal mode analysis of large-sized biomolecules. The multiscale virtual particle (MVP) model is proposed for the discretization of biomolecular density data. With this model, large-sized biomolecular structures can be coarse-grained into virtual particles such that a balance between model accuracy and computational cost can be achieved. An elastic network is constructed by assuming "connections" between virtual particles. The connection is described by a special harmonic potential function, which considers the influence from both the mass distributions and distance relations of the virtual particles. Two independent models, i.e., the multiscale virtual particle based Gaussian network model (MVP-GNM) and the multiscale virtual particle based anisotropic network model (MVP-ANM), are proposed. It has been found that in the Debye-Waller factor (B-factor) prediction, the results from our MVP-GNM with a high resolution are as good as the ones from GNM. Even with low resolutions, our MVP-GNM can still capture the global behavior of the B-factor very well with mismatches predominantly from the regions with large B-factor values. Further, it has been demonstrated that the low-frequency eigenmodes from our MVP-ANM are highly consistent with the ones from ANM even with very low resolutions and a coarse grid. Finally, the great advantage of MVP-ANM model for large-sized biomolecules has been demonstrated by using two poliovirus virus structures. The paper ends with a conclusion.

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

Science.gov (United States)

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

2016-11-10

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

DRD2 genotype-based variation of default mode network activity and of its relationship with striatal DAT binding.

Science.gov (United States)

Sambataro, Fabio; Fazio, Leonardo; Taurisano, Paolo; Gelao, Barbara; Porcelli, Annamaria; Mancini, Marina; Sinibaldi, Lorenzo; Ursini, Gianluca; Masellis, Rita; Caforio, Grazia; Di Giorgio, Annabella; Niccoli-Asabella, Artor; Popolizio, Teresa; Blasi, Giuseppe; Bertolino, Alessandro

2013-01-01

The default mode network (DMN) comprises a set of brain regions with "increased" activity during rest relative to cognitive processing. Activity in the DMN is associated with functional connections with the striatum and dopamine (DA) levels in this brain region. A functional single-nucleotide polymorphism within the dopamine D2 receptor gene (DRD2, rs1076560 G > T) shifts splicing of the 2 D2 isoforms, D2 short and D2 long, and has been associated with striatal DA signaling as well as with cognitive processing. However, the effects of this polymorphism on DMN have not been explored. The aim of this study was to evaluate the effects of rs1076560 on DMN and striatal connectivity and on their relationship with striatal DA signaling. Twenty-eight subjects genotyped for rs1076560 underwent functional magnetic resonance imaging during a working memory task and 123 55 I-Fluoropropyl-2-beta-carbomethoxy-3-beta(4-iodophenyl) nortropan Single Photon Emission Computed Tomography ([(123)I]-FP-CIT SPECT) imaging (a measure of dopamine transporter [DAT] binding). Spatial group-independent component (IC) analysis was used to identify DMN and striatal ICs. Within the anterior DMN IC, GG subjects had relatively greater connectivity in medial prefrontal cortex (MPFC), which was directly correlated with striatal DAT binding. Within the posterior DMN IC, GG subjects had reduced connectivity in posterior cingulate relative to T carriers. Additionally, rs1076560 genotype predicted connectivity differences within a striatal network, and these changes were correlated with connectivity in MPFC and posterior cingulate within the DMN. These results suggest that genetically determined D2 receptor signaling is associated with DMN connectivity and that these changes are correlated with striatal function and presynaptic DA signaling.

The Longitudinal Trajectory of Default Mode Network Connectivity in Healthy Older Adults Varies As a Function of Age and Is Associated with Changes in Episodic Memory and Processing Speed.

Science.gov (United States)

Staffaroni, Adam M; Brown, Jesse A; Casaletto, Kaitlin B; Elahi, Fanny M; Deng, Jersey; Neuhaus, John; Cobigo, Yann; Mumford, Paige S; Walters, Samantha; Saloner, Rowan; Karydas, Anna; Coppola, Giovanni; Rosen, Howie J; Miller, Bruce L; Seeley, William W; Kramer, Joel H

2018-03-14

The default mode network (DMN) supports memory functioning and may be sensitive to preclinical Alzheimer's pathology. Little is known, however, about the longitudinal trajectory of this network's intrinsic functional connectivity (FC). In this study, we evaluated longitudinal FC in 111 cognitively normal older human adults (ages 49-87, 46 women/65 men), 92 of whom had at least three task-free fMRI scans ( n = 353 total scans). Whole-brain FC and three DMN subnetworks were assessed: (1) within-DMN, (2) between anterior and posterior DMN, and (3) between medial temporal lobe network and posterior DMN. Linear mixed-effects models demonstrated significant baseline age × time interactions, indicating a nonlinear trajectory. There was a trend toward increasing FC between ages 50-66 and significantly accelerating declines after age 74. A similar interaction was observed for whole-brain FC. APOE status did not predict baseline connectivity or change in connectivity. After adjusting for network volume, changes in within-DMN connectivity were specifically associated with changes in episodic memory and processing speed but not working memory or executive functions. The relationship with processing speed was attenuated after covarying for white matter hyperintensities (WMH) and whole-brain FC, whereas within-DMN connectivity remained associated with memory above and beyond WMH and whole-brain FC. Whole-brain and DMN FC exhibit a nonlinear trajectory, with more rapid declines in older age and possibly increases in connectivity early in the aging process. Within-DMN connectivity is a marker of episodic memory performance even among cognitively healthy older adults. SIGNIFICANCE STATEMENT Default mode network and whole-brain connectivity, measured using task-free fMRI, changed nonlinearly as a function of age, with some suggestion of early increases in connectivity. For the first time, longitudinal changes in DMN connectivity were shown to correlate with changes in episodic

Coupling effect of nodes popularity and similarity on social network persistence.

Science.gov (United States)

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-02-21

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes' popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.

Strength of Default Mode Resting-State Connectivity Relates to White Matter Integrity in Children

Science.gov (United States)

Gordon, Evan M.; Lee, Philip S.; Maisog, Jose M.; Foss-Feig, Jennifer; Billington, Michael E.; VanMeter, John; Vaidya, Chandan J.

2011-01-01

A default mode network of brain regions is known to demonstrate coordinated activity during the resting state. While the default mode network is well characterized in adults, few investigations have focused upon its development. We scanned 9-13-year-old children with diffusion tensor imaging and resting-state functional magnetic resonance imaging.…

Super-Gaussian, super-diffusive transport of multi-mode active matter

OpenAIRE

Hahn, Seungsoo; Song, Sanggeun; Kim, Dae Hyun; Yang, Gil-Suk; Lee, Kang Taek; Sung, Jaeyoung

2017-01-01

Living cells exhibit multi-mode transport that switches between an active, self-propelled motion and a seemingly passive, random motion. Cellular decision-making over transport mode switching is a stochastic process that depends on the dynamics of the intracellular chemical network regulating the cell migration process. Here, we propose a theory and an exactly solvable model of multi-mode active matter. Our exact model study shows that the reversible transition between a passive mode and an a...

Higher‐order mode absorption measurement of X-band choke-mode cavities in a radial line structure

International Nuclear Information System (INIS)

Zha, Hao; Shi, Jiaru; Wu, Xiaowei; Chen, Huaibi

2016-01-01

An experiment is presented to study the higher-order mode (HOM) suppression of X-band choke-mode structures with a vector network analyzer (VNA). Specific radial line disks were built to test the reflection from the corresponding damping load and different choke geometries. The mismatch between the radial lines and the VNA was calibrated through a special multi-short-load calibration method. The measured reflections of different choke geometries showed good agreement with the theoretical calculations and verified the HOM absorption feature of each geometric design.

Higher‐order mode absorption measurement of X-band choke-mode cavities in a radial line structure

Energy Technology Data Exchange (ETDEWEB)

Zha, Hao [Department of Engineering Physics, Tsinghua University, Beijing CN-100086 (China); Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing (China); The European Organization for Nuclear Research, Geneva CH-1211 (Switzerland); Shi, Jiaru, E-mail: shij@mail.tsinghua.edu.cn [Department of Engineering Physics, Tsinghua University, Beijing CN-100086 (China); Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing (China); The European Organization for Nuclear Research, Geneva CH-1211 (Switzerland); Wu, Xiaowei; Chen, Huaibi [Department of Engineering Physics, Tsinghua University, Beijing CN-100086 (China); Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing (China)

2016-04-01

An experiment is presented to study the higher-order mode (HOM) suppression of X-band choke-mode structures with a vector network analyzer (VNA). Specific radial line disks were built to test the reflection from the corresponding damping load and different choke geometries. The mismatch between the radial lines and the VNA was calibrated through a special multi-short-load calibration method. The measured reflections of different choke geometries showed good agreement with the theoretical calculations and verified the HOM absorption feature of each geometric design.

Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network.

Science.gov (United States)

Batllori, Enric; Parisien, Marc-André; Parks, Sean A; Moritz, Max A; Miller, Carol

2017-08-01

Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform a continent-wide climate change vulnerability assessment whereby we compare the baseline climate of the protected area network in North America (Canada, United States, México-NAM) to the projected end-of-century climate (2071-2100). We estimated the projected pace at which climatic conditions may redistribute across NAM (i.e., climate velocity), and identified future nearest climate analogs to quantify patterns of climate relocation within, among, and outside protected areas. Also, we interpret climatic relocation patterns in terms of associated land-cover types. Our analysis suggests that the conservation capacity of the NAM protection network is likely to be severely compromised by a changing climate. The majority of protected areas (~80%) might be exposed to high rates of climate displacement that could promote important shifts in species abundance or distribution. A small fraction of protected areas (climates that represent analogs of conditions currently characterizing almost a fifth of the protected areas across NAM. However, the majority of nearest climatic analogs for protected areas are in nonprotected locations. Therefore, unprotected landscapes could pose additional threats, beyond climate forcing itself, as sensitive biota may have to migrate farther than what is prescribed by the climate velocity to reach a protected area destination. To mitigate future threats to the conservation capacity of the NAM protected area network, conservation plans will need to capitalize on opportunities provided by the existing availability of natural land-cover types outside the current network of NAM

Vascular risk factors, cerebrovascular reactivity, and the default-mode brain network.

Science.gov (United States)

Haight, Thaddeus J; Bryan, R Nick; Erus, Guray; Davatzikos, Christos; Jacobs, David R; D'Esposito, Mark; Lewis, Cora E; Launer, Lenore J

2015-07-15

Cumulating evidence from epidemiologic studies implicates cardiovascular health and cerebrovascular function in several brain diseases in late life. We examined vascular risk factors with respect to a cerebrovascular measure of brain functioning in subjects in mid-life, which could represent a marker of brain changes in later life. Breath-hold functional MRI (fMRI) was performed in 541 women and men (mean age 50.4 years) from the Coronary Artery Risk Development in Young Adults (CARDIA) Brain MRI sub-study. Cerebrovascular reactivity (CVR) was quantified as percentage change in blood-oxygen level dependent (BOLD) signal in activated voxels, which was mapped to a common brain template and log-transformed. Mean CVR was calculated for anatomic regions underlying the default-mode network (DMN) - a network implicated in AD and other brain disorders - in addition to areas considered to be relatively spared in the disease (e.g. occipital lobe), which were utilized as reference regions. Mean CVR was significantly reduced in the posterior cingulate/precuneus (β=-0.063, 95% CI: -0.106, -0.020), anterior cingulate (β=-0.055, 95% CI: -0.101, -0.010), and medial frontal lobe (β=-0.050, 95% CI: -0.092, -0.008) relative to mean CVR in the occipital lobe, after adjustment for age, sex, race, education, and smoking status, in subjects with pre-hypertension/hypertension compared to normotensive subjects. By contrast, mean CVR was lower, but not significantly, in the inferior parietal lobe (β=-0.024, 95% CI: -0.062, 0.014) and the hippocampus (β=-0.006, 95% CI: -0.062, 0.050) relative to mean CVR in the occipital lobe. Similar results were observed in subjects with diabetes and dyslipidemia compared to those without these conditions, though the differences were non-significant. Reduced CVR may represent diminished vascular functionality for the DMN for individuals with prehypertension/hypertension in mid-life, and may serve as a preclinical marker for brain dysfunction in later

Nonlinear PCA: characterizing interactions between modes of brain activity.

OpenAIRE

Friston, K; Phillips, J; Chawla, D; Büchel, C

2000-01-01

This paper presents a nonlinear principal component analysis (PCA) that identifies underlying sources causing the expression of spatial modes or patterns of activity in neuroimaging time-series. The critical aspect of this technique is that, in relation to conventional PCA, the sources can interact to produce (second-order) spatial modes that represent the modulation of one (first-order) spatial mode by another. This nonlinear PCA uses a simple neural network architecture that embodies a spec...

Spontaneous default mode network phase-locking moderates performance perceptions under stereotype threat.

Science.gov (United States)

Forbes, Chad E; Leitner, Jordan B; Duran-Jordan, Kelly; Magerman, Adam B; Schmader, Toni; Allen, John J B

2015-07-01

This study assessed whether individual differences in self-oriented neural processing were associated with performance perceptions of minority students under stereotype threat. Resting electroencephalographic activity recorded in white and minority participants was used to predict later estimates of task errors and self-doubt on a presumed measure of intelligence. We assessed spontaneous phase-locking between dipole sources in left lateral parietal cortex (LPC), precuneus/posterior cingulate cortex (P/PCC), and medial prefrontal cortex (MPFC); three regions of the default mode network (DMN) that are integral for self-oriented processing. Results revealed that minorities with greater LPC-P/PCC phase-locking in the theta band reported more accurate error estimations. All individuals experienced less self-doubt to the extent they exhibited greater LPC-MPFC phase-locking in the alpha band but this effect was driven by minorities. Minorities also reported more self-doubt to the extent they overestimated errors. Findings reveal novel neural moderators of stereotype threat effects on subjective experience. Spontaneous synchronization between DMN regions may play a role in anticipatory coping mechanisms that buffer individuals from stereotype threat. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Analysis of Sleep-Mode Downlink Scheduling Operations in EPON Systems

DEFF Research Database (Denmark)

Yan, Ying; Dittmann, Lars

2011-01-01

Energy management strategy has been considered as an important component in the future Ethernet Passive Optical Networks (EPONs). In this paper, a sleeping mode operation is studied, and a downlink packet scheduling scheme is analyzed to preserve energy consumption and maintain the required Qo......S. This paper proposes a novel sleep-mode downlink packet scheduling scheme in order to enhance the sleep control function. Simulation results confirm that the proposed approach offers effective power management on the basis of the traffic conditions. The trade-off between network performances and the power...

Ad hoc laser networks component technology for modular spacecraft

Science.gov (United States)

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.

Altered functional connectivity of the default mode network in Williams syndrome: a multimodal approach.

Science.gov (United States)

Sampaio, Adriana; Moreira, Pedro Silva; Osório, Ana; Magalhães, Ricardo; Vasconcelos, Cristiana; Férnandez, Montse; Carracedo, Angel; Alegria, Joana; Gonçalves, Óscar F; Soares, José Miguel

2016-07-01

Resting state brain networks are implicated in a variety of relevant brain functions. Importantly, abnormal patterns of functional connectivity (FC) have been reported in several neurodevelopmental disorders. In particular, the Default Mode Network (DMN) has been found to be associated with social cognition. We hypothesize that the DMN may be altered in Williams syndrome (WS), a neurodevelopmental genetic disorder characterized by an unique cognitive and behavioral phenotype. In this study, we assessed the architecture of the DMN using fMRI in WS patients and typically developing matched controls (sex and age) in terms of FC and volumetry of the DMN. Moreover, we complemented the analysis with a functional connectome approach. After excluding participants due to movement artifacts (n = 3), seven participants with WS and their respective matched controls were included in the analyses. A decreased FC between the DMN regions was observed in the WS group when compared with the typically developing group. Specifically, we found a decreased FC in a posterior hub of the DMN including the precuneus, calcarine and the posterior cingulate of the left hemisphere. The functional connectome approach showed a focalized and global increased FC connectome in the WS group. The reduced FC of the posterior hub of the DMN in the WS group is consistent with immaturity of the brain FC patterns and may be associated with the singularity of their visual spatial phenotype. © 2016 John Wiley & Sons Ltd.

Acupuncture, the limbic system, and the anticorrelated networks of the brain.

Science.gov (United States)

Hui, Kathleen K S; Marina, Ovidiu; Liu, Jing; Rosen, Bruce R; Kwong, Kenneth K

2010-10-28

The study of the mechanism of acupuncture action was revolutionized by the use of functional magnetic resonance imaging (fMRI). Over the past decade, our fMRI studies of healthy subjects have contributed substantially to elucidating the central effect of acupuncture on the human brain. These studies have shown that acupuncture stimulation, when associated with sensations comprising deqi, evokes deactivation of a limbic-paralimbic-neocortical network, which encompasses the limbic system, as well as activation of somatosensory brain regions. These networks closely match the default mode network and the anti-correlated task-positive network described in the literature. We have also shown that the effect of acupuncture on the brain is integrated at multiple levels, down to the brainstem and cerebellum. Our studies support the hypothesis that the effect of acupuncture on the brain goes beyond the effect of attention on the default mode network or the somatosensory stimulation of acupuncture needling. The amygdala and hypothalamus, in particular, show decreased activation during acupuncture stimulation that is not commonly associated with default mode network activity. At the same time, our research shows that acupuncture stimulation needs to be done carefully, limiting stimulation when the resulting sensations are very strong or when sharp pain is elicited. When acupuncture induced sharp pain, our studies show that the deactivation was attenuated or reversed in direction. Our results suggest that acupuncture mobilizes the functionally anti-correlated networks of the brain to mediate its actions, and that the effect is dependent on the psychophysical response. In this work we also discuss multiple avenues of future research, including the role of neurotransmitters, the effect of different acupuncture techniques, and the potential clinical application of our research findings to disease states including chronic pain, major depression, schizophrenia, autism, and Alzheimer

Robustness analysis of interdependent networks under multiple-attacking strategies

Science.gov (United States)

Gao, Yan-Li; Chen, Shi-Ming; Nie, Sen; Ma, Fei; Guan, Jun-Jie

2018-04-01

The robustness of complex networks under attacks largely depends on the structure of a network and the nature of the attacks. Previous research on interdependent networks has focused on two types of initial attack: random attack and degree-based targeted attack. In this paper, a deliberate attack function is proposed, where six kinds of deliberate attacking strategies can be derived by adjusting the tunable parameters. Moreover, the robustness of four types of interdependent networks (BA-BA, ER-ER, BA-ER and ER-BA) with different coupling modes (random, positive and negative correlation) is evaluated under different attacking strategies. Interesting conclusions could be obtained. It can be found that the positive coupling mode can make the vulnerability of the interdependent network to be absolutely dependent on the most vulnerable sub-network under deliberate attacks, whereas random and negative coupling modes make the vulnerability of interdependent network to be mainly dependent on the being attacked sub-network. The robustness of interdependent network will be enhanced with the degree-degree correlation coefficient varying from positive to negative. Therefore, The negative coupling mode is relatively more optimal than others, which can substantially improve the robustness of the ER-ER network and ER-BA network. In terms of the attacking strategies on interdependent networks, the degree information of node is more valuable than the betweenness. In addition, we found a more efficient attacking strategy for each coupled interdependent network and proposed the corresponding protection strategy for suppressing cascading failure. Our results can be very useful for safety design and protection of interdependent networks.

Connecting Social Networks with Ecosystem Services for Watershed Governance: a Social-Ecological Network Perspective Highlights the Critical Role of Bridging Organizations

Directory of Open Access Journals (Sweden)

Kaitlyn J. Rathwell

2012-06-01

Full Text Available In many densely settled agricultural watersheds, water quality is a point of conflict between amenity and agricultural activities because of the varied demands and impacts on shared water resources. Successful governance of these watersheds requires coordination among different activities. Recent research has highlighted the role that social networks between management entities can play to facilitate cross-scale interaction in watershed governance. For example, bridging organizations can be positioned in social networks to bridge local initiatives done by single municipalities across whole watersheds. To better understand the role of social networks in social-ecological system dynamics, we combine a social network analysis of the water quality management networks held by local governments with a social-ecological analysis of variation in water management and ecosystem services across the Montérégie, an agricultural landscape near Montréal, Québec, Canada. We analyze municipal water management networks by using one-mode networks to represent direct collaboration between municipalities, and two-mode networks to capture how bridging organizations indirectly connect municipalities. We find that municipalities do not collaborate directly with one another but instead are connected via bridging organizations that span the water quality management network. We also discovered that more connected municipalities engaged in more water management activities. However, bridging organizations preferentially connected with municipalities that used more tourism related ecosystem services rather than those that used more agricultural ecosystem services. Many agricultural municipalities were relatively isolated, despite being the main producers of water quality problems. In combination, these findings suggest that further strengthening the water management network in the Montérégie will contribute to improving water quality in the region. However, such

THE OPERATION MODES OPTIMIZATION OF THE NEUTRAL DISTRIBUTION NETWORKS

Directory of Open Access Journals (Sweden)

F. P. Shkarbets

2009-03-01

Full Text Available The variants of grounding the neutral wire of electric networks are considered and the recommendations are presented on increasing the level of operational reliability and electric safety of distribution networks with 6 kV voltage on the basis of limitation and suppression of transitional processes at asymmetrical damages.

Identification of Resting State Networks Involved in Executive Function.

Science.gov (United States)

Connolly, Joanna; McNulty, Jonathan P; Boran, Lorraine; Roche, Richard A P; Delany, David; Bokde, Arun L W

2016-06-01

The structural networks in the human brain are consistent across subjects, and this is reflected also in that functional networks across subjects are relatively consistent. These findings are not only present during performance of a goal oriented task but there are also consistent functional networks during resting state. It suggests that goal oriented activation patterns may be a function of component networks identified using resting state. The current study examines the relationship between resting state networks measured and patterns of neural activation elicited during a Stroop task. The association between the Stroop-activated networks and the resting state networks was quantified using spatial linear regression. In addition, we investigated if the degree of spatial association of resting state networks with the Stroop task may predict performance on the Stroop task. The results of this investigation demonstrated that the Stroop activated network can be decomposed into a number of resting state networks, which were primarily associated with attention, executive function, visual perception, and the default mode network. The close spatial correspondence between the functional organization of the resting brain and task-evoked patterns supports the relevance of resting state networks in cognitive function.

Implementation of quantum key distribution network simulation module in the network simulator NS-3

Science.gov (United States)

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.

Disrupted Thalamus White Matter Anatomy and Posterior Default Mode Network Effective Connectivity in Amnestic Mild Cognitive Impairment

Directory of Open Access Journals (Sweden)

Thomas Alderson

2017-11-01

Full Text Available Alzheimer’s disease (AD and its prodromal state amnestic mild cognitive impairment (aMCI are characterized by widespread abnormalities in inter-areal white matter fiber pathways and parallel disruption of default mode network (DMN resting state functional and effective connectivity. In healthy subjects, DMN and task positive network interaction are modulated by the thalamus suggesting that abnormal task-based DMN deactivation in aMCI may be a consequence of impaired thalamo-cortical white matter circuitry. Thus, this article uses a multimodal approach to assess white matter integrity between thalamus and DMN components and associated effective connectivity in healthy controls (HCs relative to aMCI patients. Twenty-six HC and 20 older adults with aMCI underwent structural, functional and diffusion MRI scanning using the high angular resolution diffusion-weighted acquisition protocol. The DMN of each subject was identified using independent component analysis (ICA and resting state effective connectivity was calculated between thalamus and DMN nodes. White matter integrity changes between thalamus and DMN were investigated with constrained spherical deconvolution (CSD tractography. Significant structural deficits in thalamic white matter projection fibers to posterior DMN components posterior cingulate cortex (PCC and lateral inferior parietal lobe (IPL were identified together with significantly reduced effective connectivity from left thalamus to left IPL. Crucially, impaired thalamo-cortical white matter circuitry correlated with memory performance. Disrupted thalamo-cortical structure was accompanied by significant reductions in IPL and PCC cortico-cortical effective connectivity. No structural deficits were found between DMN nodes. Abnormal posterior DMN activity may be driven by changes in thalamic white matter connectivity; a view supported by the close anatomical and functional association of thalamic nuclei effected by AD pathology and

Internal and external attention and the default mode network.

Science.gov (United States)

Scheibner, Hannah J; Bogler, Carsten; Gleich, Tobias; Haynes, John-Dylan; Bermpohl, Felix

2017-03-01

Focused attention meditations have been shown to improve psychological health and wellbeing and are nowadays an integral part of many psychotherapies. While research on the neural correlates of focused attention meditation is increasing, findings vary on whether meditations are associated with high or low activity in the default mode network (DMN). To clarify the relationship between focused attention meditation and the activity in DMN regions, it may be helpful to distinguish internal and external attention as well as different phases within one meditation: During focused attention meditation, the practitioner switches between mindful attention, mind-wandering and refocusing. Here, we employed a thought-probe paradigm to study the neural correlates of these different phases. Twenty healthy, meditation naïve participants were introduced to external (mindfulness of sound) and internal (mindfulness of breathing) attention meditation and then practiced the meditation at home for four consecutive days. They then performed the same focused attention meditations during fMRI scanning, in four runs alternating between internal and external attention. At pseudorandom intervals, participants were asked whether they had just been focused on the task (mindful attention) or had been distracted (mind-wandering). During mindful attention, brain regions typically associated with the DMN, such as the medial prefrontal cortex, posterior cingulate cortex and left temporoparietal junction showed significantly less neural activation compared to mind-wandering phases. Reduced activity of the DMN was found during both external and internal attention, with stronger deactivation in the posterior cingulate cortex during internal attention compared to external attention. Moreover, refocusing after mind-wandering was associated with activity in the left inferior frontal gyrus. Our results support the theory that mindful attention is associated with reduced DMN activity compared to mind

Topological Reorganization of the Default Mode Network in Severe Male Obstructive Sleep Apnea

Directory of Open Access Journals (Sweden)

Liting Chen

2018-06-01

Full Text Available Impaired spontaneous regional activity and altered topology of the brain network have been observed in obstructive sleep apnea (OSA. However, the mechanisms of disrupted functional connectivity (FC and topological reorganization of the default mode network (DMN in patients with OSA remain largely unknown. We explored whether the FC is altered within the DMN and examined topological changes occur in the DMN in patients with OSA using a graph theory analysis of resting-state functional magnetic resonance imaging data and evaluated the relationship between neuroimaging measures and clinical variables. Resting-state data were obtained from 46 male patients with untreated severe OSA and 46 male good sleepers (GSs. We specifically selected 20 DMN subregions to construct the DMN architecture. The disrupted FC and topological properties of the DMN in patients with OSA were characterized using graph theory. The OSA group showed significantly decreased FC of the anterior–posterior DMN and within the posterior DMN, and also showed increased FC within the DMN. The DMN exhibited small-world topology in both OSA and GS groups. Compared to GSs, patients with OSA showed a decreased clustering coefficient (Cp and local efficiency, and decreased nodal centralities in the left posterior cingulate cortex and dorsal medial prefrontal cortex, and increased nodal centralities in the ventral medial prefrontal cortex and the right parahippocampal cortex. Finally, the abnormal DMN FC was significantly related to Cp, path length, global efficiency, and Montreal cognitive assessment score. OSA showed disrupted FC within the DMN, which may have contributed to the observed topological reorganization. These findings may provide further evidence of cognitive deficits in patients with OSA.

Episodic memory in aspects of large-scale brain networks

Science.gov (United States)

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

Episodic memory in aspects of large-scale brain networks

Directory of Open Access Journals (Sweden)

Woorim eJeong

2015-08-01

Full Text Available 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. Furthermore, researchers have begun to investigate memory networks throughout the entire brain not restricted to the specific resting-state network. Altered patterns of functional connectivity 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.

Investigation of mode partition noise in Fabry-Perot laser diode

Science.gov (United States)

Guo, Qingyi; Deng, Lanxin; Mu, Jianwei; Li, Xun; Huang, Wei-Ping

2014-09-01

Passive optical network (PON) is considered as the most appealing access network architecture in terms of cost-effectiveness, bandwidth management flexibility, scalability and durability. And to further reduce the cost per subscriber, a Fabry-Perot (FP) laser diode is preferred as the transmitter at the optical network units (ONUs) because of its lower cost compared to distributed feedback (DFB) laser diode. However, the mode partition noise (MPN) associated with the multi-longitudinal-mode FP laser diode becomes the limiting factor in the network. This paper studies the MPN characteristics of the FP laser diode using the time-domain simulation of noise-driven multi-mode laser rate equation. The probability density functions are calculated for each longitudinal mode. The paper focuses on the investigation of the k-factor, which is a simple yet important measure of the noise power, but is usually taken as a fitted or assumed value in the penalty calculations. In this paper, the sources of the k-factor are studied with simulation, including the intrinsic source of the laser Langevin noise, and the extrinsic source of the bit pattern. The photon waveforms are shown under four simulation conditions for regular or random bit pattern, and with or without Langevin noise. The k-factors contributed by those sources are studied with a variety of bias current and modulation current. Simulation results are illustrated in figures, and show that the contribution of Langevin noise to the k-factor is larger than that of the random bit pattern, and is more dominant at lower bias current or higher modulation current.

Establishing the resting state default mode network derived from functional magnetic resonance imaging tasks as an endophenotype: A twins study.

Science.gov (United States)

Korgaonkar, Mayuresh S; Ram, Kaushik; Williams, Leanne M; Gatt, Justine M; Grieve, Stuart M

2014-08-01

The resting state default mode network (DMN) has been shown to characterize a number of neurological and psychiatric disorders. Evidence suggests an underlying genetic basis for this network and hence could serve as potential endophenotype for these disorders. Heritability is a defining criterion for endophenotypes. The DMN is measured either using a resting-state functional magnetic resonance imaging (fMRI) scan or by extracting resting state activity from task-based fMRI. The current study is the first to evaluate heritability of this task-derived resting activity. 250 healthy adult twins (79 monozygotic and 46 dizygotic same sex twin pairs) completed five cognitive and emotion processing fMRI tasks. Resting state DMN functional connectivity was derived from these five fMRI tasks. We validated this approach by comparing connectivity estimates from task-derived resting activity for all five fMRI tasks, with those obtained using a dedicated task-free resting state scan in an independent cohort of 27 healthy individuals. Structural equation modeling using the classic twin design was used to estimate the genetic and environmental contributions to variance for the resting-state DMN functional connectivity. About 9-41% of the variance in functional connectivity between the DMN nodes was attributed to genetic contribution with the greatest heritability found for functional connectivity between the posterior cingulate and right inferior parietal nodes (P<0.001). Our data provide new evidence that functional connectivity measures from the intrinsic DMN derived from task-based fMRI datasets are under genetic control and have the potential to serve as endophenotypes for genetically predisposed psychiatric and neurological disorders. Copyright © 2014 Wiley Periodicals, Inc.

Design of a search and rescue terminal based on the dual-mode satellite and CDMA network

Science.gov (United States)

Zhao, Junping; Zhang, Xuan; Zheng, Bing; Zhou, Yubin; Song, Hao; Song, Wei; Zhang, Meikui; Liu, Tongze; Zhou, Li

2010-12-01

The current goal is to create a set of portable terminals with GPS/BD2 dual-mode satellite positioning, vital signs monitoring and wireless transmission functions. The terminal depends on an ARM processor to collect and combine data related to vital signs and GPS/BD2 location information, and sends the message to headquarters through the military CDMA network. It integrates multiple functions as a whole. The satellite positioning and wireless transmission capabilities are integrated into the motherboard, and the vital signs sensors used in the form of belts communicate with the board through Bluetooth. It can be adjusted according to the headquarters' instructions. This kind of device is of great practical significance for operations during disaster relief, search and rescue of the wounded in wartime, non-war military operations and other special circumstances.

[Association of the physical activity of community-dwelling older adults with transportation modes, depression and social networks].

Science.gov (United States)

Tsunoda, Kenji; Mitsuishi, Yasuhiro; Tsuji, Taishi; Yoon, Ji-Yeong; Muraki, Toshiaki; Hotta, Kazushi; Okura, Tomohiro

2011-01-01

The purpose of this study was to cross-sectionally examine the relationships among leisure, household and occupational physical activity with the frequency of going out by various transportation modes, depression and social networks in older adults. We randomly selected a total of 2,100 community-dwelling adults aged 65 to 85 years of age from the Basic Resident Register. Of these, 340 people were the subjects of this study. The scales of measurement used were the Physical Activity Scale for the Elderly, the Lubben Social Network Scale (LSNS) and the Geriatric Depression Scale (GDS). In a regression model, leisure-time physical activity significantly correlated with frequency of going out by bicycle (β=0.17) and LSNS score (β=0.17). Household physical activity and occupational physical activity were significantly correlated with LSNS score (β=0.21) and frequency of going out by motor vehicle (β=0.25), respectively. For total physical activity, in the 3 above-mentioned activities a significant correlation was observed among frequency of going out by bicycle (β=0.10), by motor vehicle (β=0.23), GDS score (β=-0.16) and LSNS score (β=0.23). These results indicate that the frequency of going out by bicycle and by motor vehicle were significant factors to predict leisure and occupational physical activity. Furthermore, social networks appear to be important determiners in leisure and household physical activity in community-dwelling older adults.

The role of the umbrella inversion mode in proton diffusion

Science.gov (United States)

Hassanali, Ali A.; Giberti, Federico; Sosso, Gabriele C.; Parrinello, Michele

2014-04-01

Here, using ab initio molecular dynamics (AIMD) simulations, we elucidate the role of the umbrella inversion mode of the hydronium in proton transfer (PT) in liquid water. The hydrophobic face of the hydronium oxygen experiences asymmetries in the solvent potential along the inversion coordinate and this has a rather drastic effect on the barrier for proton transfer. This behavior is coupled to the fluctuations of voids or cavities in the vicinity of the hydronium in the water network. The peculiar inversion mode can either trap or release the proton from different parts of the water network.

Age and Alzheimer's pathology disrupt default mode network functioning via alterations in white matter microstructure but not hyperintensities.

Science.gov (United States)

Brown, Christopher A; Jiang, Yang; Smith, Charles D; Gold, Brian T

2018-04-19

The default mode network (DMN) comprises defined brain regions contributing to internally-directed thought processes. Reductions in task-induced deactivation in the DMN have been associated with increasing age and poorer executive task performance, but factors underlying these functional changes remain unclear. We investigated contributions of white matter (WM) microstructure, WM hyperintensities (WMH) and Alzheimer's pathology to age-related alterations in DMN function. Thirty-five cognitively normal older adults and 29 younger adults underwent working memory task fMRI and diffusion tensor imaging. In the older adults, we measured cerebrospinal fluid tau and Aβ 42 (markers of AD pathology), and WMH on FLAIR imaging (marker of cerebrovascular disease). We identified a set of regions showing DMN deactivation and a set of inter-connecting WM tracts (DMN-WM) common to both age groups. There were negative associations between DMN deactivation and task performance in older adults, consistent with previous studies. Decreased DMN deactivation was associated with AD pathology and WM microstructure but not with WMH volume. Mediation analyses showed that WM microstructure mediated declines in DMN deactivation associated with both aging and AD pathology. Together these results suggest that AD pathology may exert a "second-hit" on WM microstructure, over-and-above the effects of age, both contributing to diminished DMN deactivation in older adults. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial Disassociation of Disrupted Functional Connectivity for the Default Mode Network in Patients with End-Stage Renal Disease.

Directory of Open Access Journals (Sweden)

Xiaofen Ma

Full Text Available To investigate the aberrant functional connectivity of the default mode network (DMN in patients with end-stage renal disease (ESRD and their clinical relevance.Resting-state functional MRI data were collected from 31 patients with ESRD (24 men, 24-61 years and 31 age- and gender-matched healthy controls (HCs, 21 men, 26-61years. A whole-brain seed-based functional connectivity analysis of these collected R-fMRI data was performed by locating the seeds in the posterior cingulate cortex (PCC and ventromedial prefrontal cortex (vmPFC to investigate the functional connectivity of the posterior and anterior DMN over the whole brain, respectively.Compared to the HCs, the patients exhibited significantly decreased functional connectivity with the PCC in the left middle temporal gyrus, the right anterior cingulate gyrus, and the bilateral medial superior frontal gyrus. For the vmPFC seed, only the right thalamus showed significantly decreased functional connectivity in the patients with ESRD compared to HCs. Interestingly, functional connectivity between the PCC and right medial superior frontal gyrus exhibited a significantly positive correlation with the hemoglobin level in the patients.Our findings suggest a spatially specific disruption of functional connectivity in the DMN in patients with ESRD, thereby providing novel insights into our understanding of the neurophysiology mechanism that underlies the disease.

Research and implementation of geographic information service mode in digital home

Science.gov (United States)

Lei, B.; Liu, K.; Gan, Y.; Zhong, M.

2014-04-01

Accompanying infrastructure improvements and networking technology innovation, the development of digital home service industry has gotten more and more attention. However, the digital home service levels have not sufficiently met rising demand from users. Therefore, it is urgent to propose and develop new service modes for the digital home. Geographic information services can provide various spatial information services such as map search, spatial information query. It has become an inevitable trend to implement geographic information services in the digital home. This paper proposes three new geographic information services modes for the digital home after sufficient requirement analysis: pushed information service mode, interactive information service mode, personalized information service mode. The key technologies to implement geographic information services on digital televisions are studied, involving digital television middleware technology, network transmission technology and visualization technology. According to the service modes' characteristics mentioned above, a service system in the digital home is established to implement geographic information services on the basis of digital television. The implementation of geographic information services in the digital home not only enriches the digital home services content, but also promotes geographic information from specialization to public popularity.

Research of application mode for FTTX technology

Science.gov (United States)

Wang, Zhong; Yun, Xiang; Huang, Wei

2009-08-01

With rapid development of Internet and broadband access network, the technologies of xDSL, FTTx+LAN, WLAN have more applications, new network service emerges in endless stream, especially the increase of network game, meeting TV, video on demand, etc. FTTH supports all present and future service with enormous bandwidth, including traditional telecommunication service, traditional data service and traditional TV service, and the future digital TV and VOD. With huge bandwidth of FTTH, it wins the final solution of broadband network, becomes the final goal of development of optical access network. In this paper, technique theory of EPON is introduced at first. At the same time, MAC frame structure, automatic detection and ranging of MPCP, DBA,and multi-LLID of EPON is analyzed. Then, service development ability, cost advantage and maintenance superiority based on EPON technology are carried out. At last,with Cost comparison between FTTH / FTTB building model and the traditional model, FTTB + LAN mode which is suitable for the newadding residential users in general areas and FTTN + DSL mode which is suitable for the old city and rural access network transformation are built up in detail. And FTTN + DSL project of rural information in rural areas and FTTH broadband HOUSE project on service solutions program are analyzed. comparing to the traditional access technologies, EPON technology has the obvious advantages, such as distance transmission, high or wide band, saving line resources, service abilities, etc. These are the qualities which not only be served for home users, but solve more access problems for us effectively.

Alteration in intrinsic and extrinsic functional connectivity of resting state networks associated with subclinical hypothyroid.

Science.gov (United States)

Kumar, Mukesh; Modi, Shilpi; Rana, Poonam; Kumar, Pawan; Kanwar, Ratnesh; Sekhri, Tarun; D'souza, Maria; Khushu, Subash

2018-03-05

Subclinical hypothyroidism (SCH) is characterized by mild elevation of thyroid stimulating hormone (TSH) (range 5-10 μIU/ml) and normal free triiodothyronine (FT3) and free thyroxine (FT4). The cognitive function impairment is well known in thyroid disorders such as hypothyroidism and hyperthyroidism, but little is known about deficits in brain functions in SCH subjects. Also, whether hormone-replacement treatment is necessary or not in SCH subjects is still debatable. In order to have an insight into the cognition of SCH subjects, intrinsic and extrinsic functional connectivity (FC) of the resting state networks (RSNs) was studied. For resting state data analysis we used an unbiased, data-driven approach based on Independent Component Analysis (ICA) and dual-regression that can emphasize widespread changes in FC without restricting to a set of predefined seeds. 28 SCH subjects and 28 matched healthy controls (HC) participated in the study. RSN analysis showed significantly decreased intrinsic FC in somato-motor network (SMN) and right fronto-parietal attention network (RAN) and increased intrinsic FC in default mode network (DMN) in SCH subjects as compared to control subjects. The reduced intrinsic FC in the SMN and RAN suggests neuro-cognitive alterations in SCH subjects in the corresponding functions which were also evident from the deficit in the neuropsychological performance of the SCH subjects on behavioural tests such as digit span, delayed recall, visual retention, recognition, Bender Gestalt and Mini-Mental State Examination (MMSE). We also found a significant reduction in extrinsic network FC between DMN and RAN; SMN and posterior default mode network (PDMN); and increased extrinsic FC between SMN and anterior default mode network (ADMN) in SCH subjects as compared to controls. An altered extrinsic FC in SCH suggests functional reorganization in response to neurological disruption. The partial correlation analysis between intrinsic and extrinsic RSNs

Developmental process emerges from extended brain-body-behavior networks

Science.gov (United States)

Byrge, Lisa; Sporns, Olaf; Smith, Linda B.

2014-01-01

Studies of brain connectivity have focused on two modes of networks: structural networks describing neuroanatomy and the intrinsic and evoked dependencies of functional networks at rest and during tasks. Each mode constrains and shapes the other across multiple time scales, and each also shows age-related changes. Here we argue that understanding how brains change across development requires understanding the interplay between behavior and brain networks: changing bodies and activities modify the statistics of inputs to the brain; these changing inputs mold brain networks; these networks, in turn, promote further change in behavior and input. PMID:24862251

Normal mode-guided transition pathway generation in proteins.

Directory of Open Access Journals (Sweden)

Byung Ho Lee

Full Text Available The biological function of proteins is closely related to its structural motion. For instance, structurally misfolded proteins do not function properly. Although we are able to experimentally obtain structural information on proteins, it is still challenging to capture their dynamics, such as transition processes. Therefore, we need a simulation method to predict the transition pathways of a protein in order to understand and study large functional deformations. Here, we present a new simulation method called normal mode-guided elastic network interpolation (NGENI that performs normal modes analysis iteratively to predict transition pathways of proteins. To be more specific, NGENI obtains displacement vectors that determine intermediate structures by interpolating the distance between two end-point conformations, similar to a morphing method called elastic network interpolation. However, the displacement vector is regarded as a linear combination of the normal mode vectors of each intermediate structure, in order to enhance the physical sense of the proposed pathways. As a result, we can generate more reasonable transition pathways geometrically and thermodynamically. By using not only all normal modes, but also in part using only the lowest normal modes, NGENI can still generate reasonable pathways for large deformations in proteins. This study shows that global protein transitions are dominated by collective motion, which means that a few lowest normal modes play an important role in this process. NGENI has considerable merit in terms of computational cost because it is possible to generate transition pathways by partial degrees of freedom, while conventional methods are not capable of this.

Generating broadband vortex modes in ring-core fiber by using a plasmonic q-plate.

Science.gov (United States)

Ye, Jingfu; Li, Yan; Han, Yanhua; Deng, Duo; Su, Xiaoya; Song, He; Gao, Jianmin; Qu, Shiliang

2017-08-15

A mode convertor was proposed and investigated for generating vortex modes in a ring-core fiber based on a plasmonic q-plate (PQP), which is composed of specially organized L-shaped resonator (LSR) arrays. A multicore fiber was used to transmit fundamental modes, and the LSR arrays were used to modulate phases of these fundamental modes. Behind the PQP, the transmitted fundamental modes with gradient phase distribution can be considered as the incident lights for generating broadband vortex modes in the ring-core fiber filter. The topological charges of generated vortex modes can be various by using an optical PQP with different q, and the chirality of the generated vortex mode can be controlled by the sign of q and handedness of the incident circularly polarized light. The operation bandwidth is 800 nm in the range of 1200-2000 nm, which covers six communication bands from the O band to the U band. The separation of vortex modes also was addressed by using a dual ring-core fiber. The mode convertor is of potential interest for connecting a traditional network and vortex communication network.

Conceptualising Lennox-Gastaut Syndrome as a secondary network epilepsy

Directory of Open Access Journals (Sweden)

John S ARCHER

2014-10-01

Full Text Available Lennox-Gastaut Syndrome (LGS is a category of severe, disabling epilepsy, characterised by frequent, treatment-resistant seizures and cognitive impairment. EEG (electroencephalography shows characteristic generalised epileptic activity that is similar in those with lesional, genetic or unknown causes, suggesting a common underlying mechanism. The condition typically begins in young children, leaving many severely disabled with recurring seizures throughout their adult life.Scalp EEG of the tonic seizures of LGS is characterised by a diffuse high voltage slow transient evolving into generalised low voltage fast activity, likely reflecting sustained fast neuronal firing over a wide cortical area. The typical interictal discharges (runs of slow spike-and-wave (SSW and bursts of generalised paroxysmal fast activity (GPFA also have a ‘generalised’ electrical field, suggesting widespread cortical involvement. Recent brain mapping studies have begun to reveal which cortical and subcortical regions are active during these ‘generalised’ discharges.In this critical review we examine findings from neuroimaging studies of LGS and place these in the context of the electrical and clinical features of the syndrome. We suggest that LGS can be conceptualised as a ‘secondary network epilepsy’, where the epileptic activity is expressed through large-scale brain networks, particularly the attention and default-mode networks. Cortical lesions, when present, appear to chronically interact with these networks to produce network instability rather than triggering each individual epileptic discharge. LGS can be considered a ‘secondary’ network epilepsy because the epileptic manifestations of the disorder reflect the networks being driven, rather than the specific initiating process.

Normal mode analysis and applications in biological physics.

Science.gov (United States)

Dykeman, Eric C; Sankey, Otto F

2010-10-27

Normal mode analysis has become a popular and often used theoretical tool in the study of functional motions in enzymes, viruses, and large protein assemblies. The use of normal modes in the study of these motions is often extremely fruitful since many of the functional motions of large proteins can be described using just a few normal modes which are intimately related to the overall structure of the protein. In this review, we present a broad overview of several popular methods used in the study of normal modes in biological physics including continuum elastic theory, the elastic network model, and a new all-atom method, recently developed, which is capable of computing a subset of the low frequency vibrational modes exactly. After a review of the various methods, we present several examples of applications of normal modes in the study of functional motions, with an emphasis on viral capsids.

Magnetoencephalographic alpha band connectivity reveals differential default mode network interactions during focused attention and open monitoring meditation

Science.gov (United States)

Marzetti, Laura; Di Lanzo, Claudia; Zappasodi, Filippo; Chella, Federico; Raffone, Antonino; Pizzella, Vittorio

2014-01-01

According to several conceptualizations of meditation, the interplay between brain systems associated to self-related processing, attention and executive control is crucial for meditative states and related traits. We used magnetoencephalography (MEG) to investigate such interplay in a highly selected group of “virtuoso” meditators (Theravada Buddhist monks), with long-term training in the two main meditation styles: focused attention (FA) and open monitoring (OM) meditation. Specifically, we investigated the differences between FA meditation, OM meditation and resting state in the coupling between the posterior cingulate cortex, core node of the Default Mode Network (DMN) implicated in mind wandering and self-related processing, and the whole brain, with a recently developed phase coherence approach. Our findings showed a state dependent coupling of posterior cingulate cortex (PCC) to nodes of the DMN and of the executive control brain network in the alpha frequency band (8–12 Hz), related to different attentional and cognitive control processes in FA and OM meditation, consistently with the putative role of alpha band synchronization in the functional mechanisms for attention and consciousness. The coupling of PCC with left medial prefrontal cortex (lmPFC) and superior frontal gyrus characterized the contrast between the two meditation styles in a way that correlated with meditation expertise. These correlations may be related to a higher mindful observing ability and a reduced identification with ongoing mental activity in more expert meditators. Notably, different styles of meditation and different meditation expertise appeared to modulate the dynamic balance between fronto-parietal (FP) and DMN networks. Our results support the idea that the interplay between the DMN and the FP network in the alpha band is crucial for the transition from resting state to different meditative states. PMID:25360102

A Minimal Model to Explore the Influence of Distant Modes on Mode-Coupling Instabilities

Science.gov (United States)

Kruse, Sebastian; Hoffmann, Norbert

2010-09-01

The phenomenon of mode-coupling instability is one of the most frequently explored mechanisms to explain self-excited oscillation in sliding systems with friction. A mode coupling instability is usually due to the coupling of two modes. However, further modes can have an important influence on the coupling of two modes. This work extends a well-known minimal model to describe mode-coupling instabilities in order to explore the influence of a distant mode on the classical mode-coupling pattern. This work suggests a new minimal model. The model is explored and it is shown that a third mode can have significant influence on the classical mode-coupling instabilities where two modes are coupling. Different phenomena are analysed and it is pointed out that distant modes can only be ignored in very special cases and that the onset friction-induced oscillations can even be very sensitive to minimal variation of a distant mode. Due to the chosen academic minimal-model and the abandonment of a complex Finite-Element model the insight stays rather phenomenological but a better understanding of the mode-coupling mechnanism can be gained.

Improved diagnostic accuracy of Alzheimer's disease by combining regional cortical thickness and default mode network functional connectivity: Validated in the Alzheimer's disease neuroimaging initiative set

Energy Technology Data Exchange (ETDEWEB)

Park, Ji Eun; Park, Bum Woo; Kim, Sang Joon; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Jung; Oh, Joo Young; Shim, Woo Hyun [Dept. of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul (Korea, Republic of); Lee, Jae Hong; Roh, Jee Hoon [University of Ulsan College of Medicine, Asan Medical Center, Seoul (Korea, Republic of)

2017-11-15

To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal (p < 0.001) and supramarginal gyrus (p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease.

Service offerings and interfaces for the ACTS network of earth stations

Science.gov (United States)

Coney, T. A.; Dobyns, T. R.; Chitre, D. M.; Lindstrom, R.

1988-01-01

The NASA Advanced Communications Technology Satellite (ACTS) will use a network of about 20 earth stations to operate as a Mode 1 network. This network will support two ACTS program objectives: to verify the technical performance of ACTS Mode 1 operation in GEO and to demonstrate the types and quality of services that can be provided by an ACTS Mode 1 communications system. The terrestrial interface design is a critical element in assuring that these network earth stations will meet the objectives. In this paper, the applicable terrestrial interface design requirements, the resulting interface specifications, and the associated terrestrial input/output hardware are discussed. A functional block diagram of a network earth station is shown.

On Kinetic Slow Modes, Fluid Slow Modes, and Pressure-balanced Structures in the Solar Wind

Energy Technology Data Exchange (ETDEWEB)

Verscharen, Daniel [Space Science Center and Department of Physics, University of New Hampshire, Durham, NH 03824 (United States); Chen, Christopher H. K. [Department of Physics, Imperial College London, London SW7 2AZ (United Kingdom); Wicks, Robert T., E-mail: daniel.verscharen@unh.edu, E-mail: christopher.chen@imperial.ac.uk, E-mail: r.wicks@ucl.ac.uk [Mullard Space Science Laboratory, University College London, London WC1E 6BT (United Kingdom)

2017-05-10

Observations in the solar wind suggest that the compressive component of inertial-range solar-wind turbulence is dominated by slow modes. The low collisionality of the solar wind allows for nonthermal features to survive, which suggests the requirement of a kinetic plasma description. The least-damped kinetic slow mode is associated with the ion-acoustic (IA) wave and a nonpropagating (NP) mode. We derive analytical expressions for the IA-wave dispersion relation in an anisotropic plasma in the framework of gyrokinetics and then compare them to fully kinetic numerical calculations, results from two-fluid theory, and magnetohydrodynamics (MHD). This comparison shows major discrepancies in the predicted wave phase speeds from MHD and kinetic theory at moderate to high β . MHD and kinetic theory also dictate that all plasma normal modes exhibit a unique signature in terms of their polarization. We quantify the relative amplitude of fluctuations in the three lowest particle velocity moments associated with IA and NP modes in the gyrokinetic limit and compare these predictions with MHD results and in situ observations of the solar-wind turbulence. The agreement between the observations of the wave polarization and our MHD predictions is better than the kinetic predictions, which suggests that the plasma behaves more like a fluid in the solar wind than expected.

On Kinetic Slow Modes, Fluid Slow Modes, and Pressure-balanced Structures in the Solar Wind

International Nuclear Information System (INIS)

Verscharen, Daniel; Chen, Christopher H. K.; Wicks, Robert T.

2017-01-01

Observations in the solar wind suggest that the compressive component of inertial-range solar-wind turbulence is dominated by slow modes. The low collisionality of the solar wind allows for nonthermal features to survive, which suggests the requirement of a kinetic plasma description. The least-damped kinetic slow mode is associated with the ion-acoustic (IA) wave and a nonpropagating (NP) mode. We derive analytical expressions for the IA-wave dispersion relation in an anisotropic plasma in the framework of gyrokinetics and then compare them to fully kinetic numerical calculations, results from two-fluid theory, and magnetohydrodynamics (MHD). This comparison shows major discrepancies in the predicted wave phase speeds from MHD and kinetic theory at moderate to high β . MHD and kinetic theory also dictate that all plasma normal modes exhibit a unique signature in terms of their polarization. We quantify the relative amplitude of fluctuations in the three lowest particle velocity moments associated with IA and NP modes in the gyrokinetic limit and compare these predictions with MHD results and in situ observations of the solar-wind turbulence. The agreement between the observations of the wave polarization and our MHD predictions is better than the kinetic predictions, which suggests that the plasma behaves more like a fluid in the solar wind than expected.

Stochastic model and method of zoning water networks

OpenAIRE

Тевяшев, Андрей Дмитриевич; Матвиенко, Ольга Ивановна

2014-01-01

Water consumption at different time of the day is uneven. The model of steady flow distribution in water-supply networks is calculated for maximum consumption and effectively used in the network design and reconstruction. Quasi-stationary modes, in which the parameters are random variables and vary relative to their mean values are more suitable for operational management and planning of rational network operation modes.Leaks, which sometimes exceed 50 % of the volume of water supplied, are o...

Multimodal Network Equilibrium with Stochastic Travel Times

Directory of Open Access Journals (Sweden)

M. Meng

2014-01-01

Full Text Available The private car, unlike public traffic modes (e.g., subway, trolley running along dedicated track-ways, is invariably subject to various uncertainties resulting in travel time variation. A multimodal network equilibrium model is formulated that explicitly considers stochastic link capacity variability in the road network. The travel time of combined-mode trips is accumulated based on the concept of the mean excess travel time (METT which is a summation of estimated buffer time and tardy time. The problem is characterized by an equivalent VI (variational inequality formulation where the mode choice is expressed in a hierarchical logit structure. Specifically, the supernetwork theory and expansion technique are used herein to represent the multimodal transportation network, which completely represents the combined-mode trips as constituting multiple modes within a trip. The method of successive weighted average is adopted for problem solutions. The model and solution method are further applied to study the trip distribution and METT variations caused by the different levels of the road conditions. Results of numerical examples show that travelers prefer to choose the combined travel mode as road capacity decreases. Travelers with different attitudes towards risk are shown to exhibit significant differences when making travel choice decisions.

The LHC Beam Pipe Waveguide Mode Reflectometer

CERN Document Server

Kroyer, T; Caspers, Friedhelm; Sulek, Z; Williams, L R

2007-01-01

The waveguide-mode reflectometer for obstacle detection in the LHC beam pipe has been intensively used for more than 18 months. The â€ﾜAssembly” version is based on the synthetic pulse method using a modern vector network analyzer. It has mode selective excitation couplers for the first TE and TM mode and uses a specially developed waveguide mode dispersion compensation algorithm with external software. In addition there is a similar â€ﾜIn Situ” version of the reflectometer which uses permanently installed microwave couplers at the end of each of the nearly 3 km long LHC arcs. During installation a considerable number of unexpected objects have been found in the beam pipes and subsequently removed. Operational statistics and lessons learned are presented and the overall performance is discussed.

Network-dependent modulation of brain activity during sleep.

Science.gov (United States)

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.

Effects of Sad and Happy Music on Mind-Wandering and the Default Mode Network.

Science.gov (United States)

Taruffi, Liila; Pehrs, Corinna; Skouras, Stavros; Koelsch, Stefan

2017-10-31

Music is a ubiquitous phenomenon in human cultures, mostly due to its power to evoke and regulate emotions. However, effects of music evoking different emotional experiences such as sadness and happiness on cognition, and in particular on self-generated thought, are unknown. Here we use probe-caught thought sampling and functional magnetic resonance imaging (fMRI) to investigate the influence of sad and happy music on mind-wandering and its underlying neuronal mechanisms. In three experiments we found that sad music, compared with happy music, is associated with stronger mind-wandering (Experiments 1A and 1B) and greater centrality of the nodes of the Default Mode Network (DMN) (Experiment 2). Thus, our results demonstrate that, when listening to sad vs. happy music, people withdraw their attention inwards and engage in spontaneous, self-referential cognitive processes. Importantly, our results also underscore that DMN activity can be modulated as a function of sad and happy music. These findings call for a systematic investigation of the relation between music and thought, having broad implications for the use of music in education and clinical settings.

Joint duplex mode selection, channel allocation, and power control for full-duplex cognitive femtocell networks

Directory of Open Access Journals (Sweden)

Mingjie Feng

2015-02-01

Full Text Available In this paper, we aim to maximize the sum rate of a full-duplex cognitive femtocell network (FDCFN as well as guaranteeing the quality of service (QoS of users in the form of a required signal to interference plus noise ratios (SINR. We first consider the case of a pair of channels, and develop optimum-achieving power control solutions. Then, for the case of multiple channels, we formulate joint duplex model selection, power control, and channel allocation as a mixed integer nonlinear problem (MINLP, and propose an iterative framework to solve it. The proposed iterative framework consists of a duplex mode selection scheme, a near-optimal distributed power control algorithm, and a greedy channel allocation algorithm. We prove the convergence of the proposed iterative framework as well as a lower bound for the greedy channel allocation algorithm. Numerical results show that the proposed schemes effectively improve the sum rate of FDCFNs.

The Causal Inference of Cortical Neural Networks during Music Improvisations

Science.gov (United States)

Wan, Xiaogeng; Crüts, Björn; Jensen, Henrik Jeldtoft

2014-01-01

We present an EEG study of two music improvisation experiments. Professional musicians with high level of improvisation skills were asked to perform music either according to notes (composed music) or in improvisation. Each piece of music was performed in two different modes: strict mode and “let-go” mode. Synchronized EEG data was measured from both musicians and listeners. We used one of the most reliable causality measures: conditional Mutual Information from Mixed Embedding (MIME), to analyze directed correlations between different EEG channels, which was combined with network theory to construct both intra-brain and cross-brain networks. Differences were identified in intra-brain neural networks between composed music and improvisation and between strict mode and “let-go” mode. Particular brain regions such as frontal, parietal and temporal regions were found to play a key role in differentiating the brain activities between different playing conditions. By comparing the level of degree centralities in intra-brain neural networks, we found a difference between the response of musicians and the listeners when comparing the different playing conditions. PMID:25489852

The causal inference of cortical neural networks during music improvisations.

Science.gov (United States)

Wan, Xiaogeng; Crüts, Björn; Jensen, Henrik Jeldtoft

2014-01-01

We present an EEG study of two music improvisation experiments. Professional musicians with high level of improvisation skills were asked to perform music either according to notes (composed music) or in improvisation. Each piece of music was performed in two different modes: strict mode and "let-go" mode. Synchronized EEG data was measured from both musicians and listeners. We used one of the most reliable causality measures: conditional Mutual Information from Mixed Embedding (MIME), to analyze directed correlations between different EEG channels, which was combined with network theory to construct both intra-brain and cross-brain networks. Differences were identified in intra-brain neural networks between composed music and improvisation and between strict mode and "let-go" mode. Particular brain regions such as frontal, parietal and temporal regions were found to play a key role in differentiating the brain activities between different playing conditions. By comparing the level of degree centralities in intra-brain neural networks, we found a difference between the response of musicians and the listeners when comparing the different playing conditions.

The causal inference of cortical neural networks during music improvisations.

Directory of Open Access Journals (Sweden)

Xiaogeng Wan

Full Text Available We present an EEG study of two music improvisation experiments. Professional musicians with high level of improvisation skills were asked to perform music either according to notes (composed music or in improvisation. Each piece of music was performed in two different modes: strict mode and "let-go" mode. Synchronized EEG data was measured from both musicians and listeners. We used one of the most reliable causality measures: conditional Mutual Information from Mixed Embedding (MIME, to analyze directed correlations between different EEG channels, which was combined with network theory to construct both intra-brain and cross-brain networks. Differences were identified in intra-brain neural networks between composed music and improvisation and between strict mode and "let-go" mode. Particular brain regions such as frontal, parietal and temporal regions were found to play a key role in differentiating the brain activities between different playing conditions. By comparing the level of degree centralities in intra-brain neural networks, we found a difference between the response of musicians and the listeners when comparing the different playing conditions.

A novel mode-locking technique

International Nuclear Information System (INIS)

Chen Shaoh; Chen Youming; Chen Taolue; Si Xiangdong; Yang Yi; Deng Ximing

1993-01-01

A novel mode-locked Nd:YAG oscillator has been developed by using an ultrafast photoconductive feedback controlled loop, and mode-locked pulses with a duration of 100ps have been obtained. The energy instability of the pulse trains is ±5%. In this type of mode-locking technology, a type of deep-level doped GaAs (Cr-doped) photoconductive switch, which has a fast response in time and is free of avalance process, is used to drive a Pockels' cell to realize mode-locking. The dark resistance of this type of photoconductive switch is 6 orders of magnitude higher than that of the intrinsic single-crystal silicon, and it can reach a level as high as 10 9 ohms. Consequently, it is able to withstand longterm operation at several thousand DC volts. By means of the photoconductive ohmic switch characteristics, the authors have designed a positive feedback control network which has a very fast response time, and can couple a voltage of up to a thousand volts. Using this unit in a Nd:YAG laser, they have successfully realized a very stable mode-locked pulse train with pulse width shorter than 100 ps. The operation principle, and the results of the preliminary experiments are presented here. 1 ref., 3 figs

Role models for complex networks

Science.gov (United States)

Reichardt, J.; White, D. R.

2007-11-01

We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.

Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

Science.gov (United States)

Decker, Arthur J.

2004-01-01

A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation

Integration and segregation of large-scale brain networks during short-term task automatization.

Science.gov (United States)

Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

2016-11-03

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes.

Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

Energy Technology Data Exchange (ETDEWEB)

Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

2017-03-27

Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

Strategic Knowledge Networks for Global Education

Science.gov (United States)

Peterson, J. Fiona

2009-01-01

The inherent opportunities for communication, collaboration and experiential learning in an online and global network create the impetus for the new network paradigm in higher education. A strategic knowledge network in education was designed and developed to build "Mode 2" knowledge capabilities; create new knowledge for innovative…

The psychedelic state induced by ayahuasca modulates the activity and connectivity of the default mode network.

Science.gov (United States)

Palhano-Fontes, Fernanda; Andrade, Katia C; Tofoli, Luis F; Santos, Antonio C; Crippa, Jose Alexandre S; Hallak, Jaime E C; Ribeiro, Sidarta; de Araujo, Draulio B

2015-01-01

The experiences induced by psychedelics share a wide variety of subjective features, related to the complex changes in perception and cognition induced by this class of drugs. A remarkable increase in introspection is at the core of these altered states of consciousness. Self-oriented mental activity has been consistently linked to the Default Mode Network (DMN), a set of brain regions more active during rest than during the execution of a goal-directed task. Here we used fMRI technique to inspect the DMN during the psychedelic state induced by Ayahuasca in ten experienced subjects. Ayahuasca is a potion traditionally used by Amazonian Amerindians composed by a mixture of compounds that increase monoaminergic transmission. In particular, we examined whether Ayahuasca changes the activity and connectivity of the DMN and the connection between the DMN and the task-positive network (TPN). Ayahuasca caused a significant decrease in activity through most parts of the DMN, including its most consistent hubs: the Posterior Cingulate Cortex (PCC)/Precuneus and the medial Prefrontal Cortex (mPFC). Functional connectivity within the PCC/Precuneus decreased after Ayahuasca intake. No significant change was observed in the DMN-TPN orthogonality. Altogether, our results support the notion that the altered state of consciousness induced by Ayahuasca, like those induced by psilocybin (another serotonergic psychedelic), meditation and sleep, is linked to the modulation of the activity and the connectivity of the DMN.

Modifications of resting state networks in spinocerebellar ataxia type 2.

Science.gov (United States)

Cocozza, Sirio; Saccà, Francesco; Cervo, Amedeo; Marsili, Angela; Russo, Cinzia Valeria; Giorgio, Sara Maria Delle Acque; De Michele, Giuseppe; Filla, Alessandro; Brunetti, Arturo; Quarantelli, Mario

2015-09-01

We aimed to investigate the integrity of the Resting State Networks in spinocerebellar ataxia type 2 (SCA2) and the correlations between the modification of these networks and clinical variables. Resting-state functional magnetic resonance imaging (RS-fMRI) data from 19 SCA2 patients and 29 healthy controls were analyzed using an independent component analysis and dual regression, controlling at voxel level for the effect of atrophy by co-varying for gray matter volume. Correlations between the resting state networks alterations and disease duration, age at onset, number of triplets, and clinical score were assessed by Spearman's coefficient, for each cluster which was significantly different in SCA2 patients compared with healthy controls. In SCA2 patients, disruption of the cerebellar components of all major resting state networks was present, with supratentorial involvement only for the default mode network. When controlling at voxel level for gray matter volume, the reduction in functional connectivity in supratentorial regions of the default mode network, and in cerebellar regions within the default mode, executive and right fronto-parietal networks, was still significant. No correlations with clinical variables were found for any of the investigated resting state networks. The SCA2 patients show significant alterations of the resting state networks, only partly explained by the atrophy. The default mode network is the only resting state network that shows also supratentorial changes, which appear unrelated to the cortical gray matter volume. Further studies are needed to assess the clinical significance of these changes. © 2015 International Parkinson and Movement Disorder Society.

Emotional detachment in psychopathy: Involvement of dorsal default-mode connections.

Science.gov (United States)

Sethi, Arjun; Gregory, Sarah; Dell'Acqua, Flavio; Periche Thomas, Eva; Simmons, Andy; Murphy, Declan G M; Hodgins, Sheilagh; Blackwood, Nigel J; Craig, Michael C

2015-01-01

Criminal psychopathy is defined by emotional detachment [Psychopathy Checklist - Revised (PCL-R) factor 1], and antisocial behaviour (PCL-R factor 2). Previous work has associated antisocial behaviour in psychopathy with abnormalities in a ventral temporo-amygdala-orbitofrontal network. However, little is known of the neural correlates of emotional detachment. Imaging studies have indicated that the 'default-mode network' (DMN), and in particular its dorsomedial (medial prefrontal - posterior cingulate) component, contributes to affective and social processing in healthy individuals. Furthermore, recent work suggests that this network may be implicated in psychopathy. However, no research has examined the relationship between psychopathy, emotional detachment, and the white matter underpinning the DMN. We therefore used diffusion tensor imaging (DTI) tractography in 13 offenders with psychopathy and 13 non-offenders to investigate the relationship between emotional detachment and the microstructure of white matter connections within the DMN. These included the dorsal cingulum (containing the medial prefrontal - posterior cingulate connections of the DMN), and the ventral cingulum (containing the posterior cingulate - medial temporal connections of the DMN). We found that fractional anisotropy (FA) was reduced in the left dorsal cingulum in the psychopathy group (p = .024). Moreover, within this group, emotional detachment was negatively correlated with FA in this tract portion bilaterally (left: r = -.61, p = .026; right: r = -.62, p = .023). These results suggest the importance of the dorsal DMN in the emotional detachment observed in individuals with psychopathy. We propose a 'dual-network' model of white matter abnormalities in the disorder, which incorporates these with previous findings. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mixed-mode fracture of ceramics

Energy Technology Data Exchange (ETDEWEB)

Petrovic, J.J.

1985-01-01

The mixed-mode fracture behavior of ceramic materials is of importance for monolithic ceramics in order to predict the onset of fracture under generalized loading conditions and for ceramic composites to describe crack deflection toughening mechanisms. Experimental data on surface flaw mixed-mode fracture in various ceramics indicate that the flaw-plane normal stress at fracture decreases with increasing in-flaw-plane shear stress, although present data exhibit a fairly wide range in details of this sigma - tau relationship. Fracture from large cracks suggests that Mode II has a greater effect on Mode I fracture than Mode III. A comparison of surface flaw and large crack mixed-mode I-II fracture responses indicated that surface flaw behavior is influenced by shear resistance effects.

Classification of hadith into positive suggestion, negative suggestion, and information

Science.gov (United States)

Faraby, Said Al; Riviera Rachmawati Jasin, Eliza; Kusumaningrum, Andina; Adiwijaya

2018-03-01

As one of the Muslim life guidelines, based on the meaning of its sentence(s), a hadith can be viewed as a suggestion for doing something, or a suggestion for not doing something, or just information without any suggestion. In this paper, we tried to classify the Bahasa translation of hadith into the three categories using machine learning approach. We tried stemming and stopword removal in preprocessing, and TF-IDF of unigram, bigram, and trigram as the extracted features. As the classifier, we compared between SVM and Neural Network. Since the categories are new, so in order to compare the results of the previous pipelines, we created a baseline classifier using simple rule-based string matching technique. The rule-based algorithm conditions on the occurrence of words such as “janganlah, sholatlah, and so on” to determine the category. The baseline method achieved F1-Score of 0.69, while the best F1-Score from the machine learning approach was 0.88, and it was produced by SVM model with the linear kernel.

Inventory theory, mode choice and network structure in freight transport

NARCIS (Netherlands)

Combes, F.; Tavasszy, L.A.

2016-01-01

In passenger transport, hub-and-spoke networks allow the transportation of small passenger flows with competitive frequencies, in a way that direct line networks cannot. Equivalently, in freight transport, it can be expected that small shipper-receiver flows of high added value commodities transit

What makes your brain suggestible? Hypnotizability is associated with differential brain activity during attention outside hypnosis.

Science.gov (United States)

Cojan, Yann; Piguet, Camille; Vuilleumier, Patrik

2015-08-15

Theoretical models of hypnosis have emphasized the importance of attentional processes in accounting for hypnotic phenomena but their exact nature and brain substrates remain unresolved. Individuals vary in their susceptibility to hypnosis, a variability often attributed to differences in attentional functioning such as greater ability to filter irrelevant information and inhibit prepotent responses. However, behavioral studies of attentional performance outside the hypnotic state have provided conflicting results. We used fMRI to investigate the recruitment of attentional networks during a modified flanker task in High and Low hypnotizable participants. The task was performed in a normal (no hypnotized) state. While behavioral performance did not reliably differ between groups, components of the fronto-parietal executive network implicated in monitoring (anterior cingulate cortex; ACC), adjustment (lateral prefrontal cortex; latPFC), and implementation of attentional control (intraparietal sulcus; IPS) were differently activated depending on the hypnotizability of the subjects: the right inferior frontal gyrus (rIFG) was more recruited, whereas IPS and ACC were less recruited by High susceptible individuals compared to Low. Our results demonstrate that susceptibility to hypnosis is associated with particular executive control capabilities allowing efficient attentional focusing, and point to specific neural substrates in right prefrontal cortex. We demonstrated that outside hypnosis, low hypnotizable subjects recruited more parietal cortex and anterior cingulate regions during selective attention conditions suggesting a better detection and implementation of conflict. However, outside hypnosis the right inferior frontal gyrus (rIFG) was more recruited by highly hypnotizable subjects during selective attention conditions suggesting a better control of conflict. Furthermore, in highly hypnotizable subjects this region was more connected to the default mode network

Effects of behavioral patterns and network topology structures on Parrondo’s paradox

Science.gov (United States)

Ye, Ye; Cheong, Kang Hao; Cen, Yu-Wan; Xie, Neng-Gang

2016-11-01

A multi-agent Parrondo’s model based on complex networks is used in the current study. For Parrondo’s game A, the individual interaction can be categorized into five types of behavioral patterns: the Matthew effect, harmony, cooperation, poor-competition-rich-cooperation and a random mode. The parameter space of Parrondo’s paradox pertaining to each behavioral pattern, and the gradual change of the parameter space from a two-dimensional lattice to a random network and from a random network to a scale-free network was analyzed. The simulation results suggest that the size of the region of the parameter space that elicits Parrondo’s paradox is positively correlated with the heterogeneity of the degree distribution of the network. For two distinct sets of probability parameters, the microcosmic reasons underlying the occurrence of the paradox under the scale-free network are elaborated. Common interaction mechanisms of the asymmetric structure of game B, behavioral patterns and network topology are also revealed.

Exploring the psychosis functional connectome: aberrant intrinsic networks in schizophrenia and bipolar disorder

Directory of Open Access Journals (Sweden)

Vince D Calhoun

2012-01-01

Full Text Available Intrinsic functional brain networks (INs are regions showing temporal coherence with one another. These INs are present in the context of a task (as opposed to an undirected task such as rest, albeit modulated to a degree both spatially and temporally. Prominent networks include the default mode, attentional fronto-parietal, executive control, bilateral temporal lobe and motor networks. The characterization of INs has recently gained considerable momentum, however; most previous studies evaluate only a small subset of the intrinsic networks (e.g. default mode. In this paper we use independent component analysis to study INs decomposed from fMRI data collected in a large group of schizophrenia patients, healthy controls, and individuals with bipolar disorder, while performing an auditory oddball task. Schizophrenia and bipolar disorder share significant overlap in clinical symptoms, brain characteristics, and risk genes which motivates our goal of identifying whether functional imaging data can differentiate the two disorders. We tested for group differences in properties of all identified intrinsic networks including spatial maps, spectra, and functional network connectivity. A small set of default mode, temporal lobe, and frontal networks with default mode regions appearing to play a key role in all comparisons. Bipolar subjects showed more prominent changes in ventromedial and prefrontal default mode regions whereas schizophrenia patients showed changes in posterior default mode regions. Anti-correlations between left parietal areas and dorsolateral prefrontal cortical areas were different in bipolar and schizophrenia patients and amplitude was significantly different from healthy controls in both patient groups. Patients exhibited similar frequency behavior across multiple networks with decreased low frequency power. In summary, a comprehensive analysis of intrinsic networks reveals a key role for the default mode in both schizophrenia and

Switched-mode converters (one quadrant)

CERN Document Server

Barrade, P

2006-01-01

Switched-mode converters are DC/DC converters that supply DC loads with a regulated output voltage, and protection against overcurrents and short circuits. These converters are generally fed from an AC network via a transformer and a conventional diode rectifier. Switched-mode converters (one quadrant) are non-reversible converters that allow the feeding of a DC load with unipolar voltage and current. The switched-mode converters presented in this contribution are classified into two families. The first is dedicated to the basic topologies of DC/DC converters, generally used for low- to mid-power applications. As such structures enable only hard commutation processes, the main drawback of such topologies is high commutation losses. A typical multichannel evolution is presented that allows an interesting decrease in these losses. Deduced from this direct DC/DC converter, an evolution is also presented that allows the integration of a transformer into the buck and the buck–boost structure. This enables an int...

Integration of Multilocus Genetic Risk into the Default Mode Network Longitudinal Trajectory during the Alzheimer's Disease Process.

Science.gov (United States)

Su, Fan; Shu, Hao; Ye, Qing; Xie, Chunming; Yuan, Baoyu; Zhang, Zhijun; Bai, Feng

2017-01-01

The aim of the study was to investigate the cognitive significance of the changes in default mode network (DMN) during the process of Alzheimer's disease (AD) and the genetic basis that drives the alteration. Eighty-seven subjects with mild cognitive impairment (MCI) and 131 healthy controls (HC) were employed at baseline, and they had the genetic risk scores (GRS) based on the GWAS-validated AD-related top loci. Eleven MCIs who converted to AD (c-MCIs), 32 subjects who remained stable (nc-MCIs), and 56 HCs participated in the follow-up analyses after an average of 35 months. Decreased functional connectivity (FC) within temporal cortex was identified for MCIs at baseline, which was partially determined by the GRS; moreover, compensations may occur within the frontal-parietal brain to maintain relatively intact cognition. During the follow-ups, c-MCIs exhibited more FC declines within the prefrontal-parietal lobes and parahippocampal gyrus/hippocampus than the HCs and nc-MCIs. The GRS did not significantly vary among the three groups, whereas associations were identified at risky alleles and FC declines in all AD spectra. Interestingly, the influence of APOEɛ4 varied as the disease progressed; APOEɛ4 was associated with longitudinal FC decreases only for HCs in the single variance-based analyses and deteriorated DMN integration in nc-MCIs by combining the effects of other loci. However, the GRS without APOEɛ4 predicted FC decline for converters. It is suggested that the integration of multilocus genetic risk predicted the longitudinal trajectory of DMN and may be used as a clinical strategy to track AD progression.

Interviewer Effects on a Network-Size Filter Question

Directory of Open Access Journals (Sweden)

Josten Michael

2016-06-01

Full Text Available There is evidence that survey interviewers may be tempted to manipulate answers to filter questions in a way that minimizes the number of follow-up questions. This becomes relevant when ego-centered network data are collected. The reported network size has a huge impact on interview duration if multiple questions on each alter are triggered. We analyze interviewer effects on a network-size question in the mixed-mode survey “Panel Study ‘Labour Market and Social Security’” (PASS, where interviewers could skip up to 15 follow-up questions by generating small networks. Applying multilevel models, we find almost no interviewer effects in CATI mode, where interviewers are paid by the hour and frequently supervised. In CAPI, however, where interviewers are paid by case and no close supervision is possible, we find strong interviewer effects on network size. As the area-specific network size is known from telephone mode, where allocation to interviewers is random, interviewer and area effects can be separated. Furthermore, a difference-in-difference analysis reveals the negative effect of introducing the follow-up questions in Wave 3 on CAPI network size. Attempting to explain interviewer effects we neither find significant main effects of experience within a wave, nor significantly different slopes between interviewers.

Using minimal spanning trees to compare the reliability of network topologies

Science.gov (United States)

Leister, Karen J.; White, Allan L.; Hayhurst, Kelly J.

1990-01-01

Graph theoretic methods are applied to compute the reliability for several types of networks of moderate size. The graph theory methods used are minimal spanning trees for networks with bi-directional links and the related concept of strongly connected directed graphs for networks with uni-directional links. A comparison is conducted of ring networks and braided networks. The case is covered where just the links fail and the case where both links and nodes fail. Two different failure modes for the links are considered. For one failure mode, the link no longer carries messages. For the other failure mode, the link delivers incorrect messages. There is a description and comparison of link-redundancy versus path-redundancy as methods to achieve reliability. All the computations are carried out by means of a fault tree program.

Taiwan Automated Telescope Network

Directory of Open Access Journals (Sweden)

Dean-Yi Chou

2010-01-01

can be operated either interactively or fully automatically. In the interactive mode, it can be controlled through the Internet. In the fully automatic mode, the telescope operates with preset parameters without any human care, including taking dark frames and flat frames. The network can also be used for studies that require continuous observations for selected objects.

A Cutting Pattern Recognition Method for Shearers Based on Improved Ensemble Empirical Mode Decomposition and a Probabilistic Neural Network

Directory of Open Access Journals (Sweden)

Jing Xu

2015-10-01

Full Text Available In order to guarantee the stable operation of shearers and promote construction of an automatic coal mining working face, an online cutting pattern recognition method with high accuracy and speed based on Improved Ensemble Empirical Mode Decomposition (IEEMD and Probabilistic Neural Network (PNN is proposed. An industrial microphone is installed on the shearer and the cutting sound is collected as the recognition criterion to overcome the disadvantages of giant size, contact measurement and low identification rate of traditional detectors. To avoid end-point effects and get rid of undesirable intrinsic mode function (IMF components in the initial signal, IEEMD is conducted on the sound. The end-point continuation based on the practical storage data is performed first to overcome the end-point effect. Next the average correlation coefficient, which is calculated by the correlation of the first IMF with others, is introduced to select essential IMFs. Then the energy and standard deviation of the reminder IMFs are extracted as features and PNN is applied to classify the cutting patterns. Finally, a simulation example, with an accuracy of 92.67%, and an industrial application prove the efficiency and correctness of the proposed method.

A Novel Multiscale Ensemble Carbon Price Prediction Model Integrating Empirical Mode Decomposition, Genetic Algorithm and Artificial Neural Network

Directory of Open Access Journals (Sweden)

Bangzhu Zhu

2012-02-01

Full Text Available Due to the movement and complexity of the carbon market, traditional monoscale forecasting approaches often fail to capture its nonstationary and nonlinear properties and accurately describe its moving tendencies. In this study, a multiscale ensemble forecasting model integrating empirical mode decomposition (EMD, genetic algorithm (GA and artificial neural network (ANN is proposed to forecast carbon price. Firstly, the proposed model uses EMD to decompose carbon price data into several intrinsic mode functions (IMFs and one residue. Then, the IMFs and residue are composed into a high frequency component, a low frequency component and a trend component which have similar frequency characteristics, simple components and strong regularity using the fine-to-coarse reconstruction algorithm. Finally, those three components are predicted using an ANN trained by GA, i.e., a GAANN model, and the final forecasting results can be obtained by the sum of these three forecasting results. For verification and testing, two main carbon future prices with different maturity in the European Climate Exchange (ECX are used to test the effectiveness of the proposed multiscale ensemble forecasting model. Empirical results obtained demonstrate that the proposed multiscale ensemble forecasting model can outperform the single random walk (RW, ARIMA, ANN and GAANN models without EMD preprocessing and the ensemble ARIMA model with EMD preprocessing.

The influence of suggestibility on memory.

Science.gov (United States)

Nicolas, Serge; Collins, Thérèse; Gounden, Yannick; Roediger, Henry L

2011-06-01

We provide a translation of Binet and Henri's pioneering 1894 paper on the influence of suggestibility on memory. Alfred Binet (1857-1911) is famous as the author who created the IQ test that bears his name, but he is almost unknown as the psychological investigator who generated numerous original experiments and fascinating results in the study of memory. His experiments published in 1894 manipulated suggestibility in several ways to determine effects on remembering. Three particular modes of suggestion were employed to induce false recognitions: (1) indirect suggestion by a preconceived idea; (2) direct suggestion; and (3) collective suggestion. In the commentary we suggest that Binet and Henri's (1894) paper written over 115 years ago is still highly relevant even today. In particular, Binet's legacy lives on in modern research on misinformation effects in memory, in studies of conformity, and in experiments on the social contagion of memory. Copyright © 2010 Elsevier Inc. All rights reserved.

Analyzing Multimode Wireless Sensor Networks Using the Network Calculus

Directory of Open Access Journals (Sweden)

Xi Jin

2015-01-01

Full Text Available The network calculus is a powerful tool to analyze the performance of wireless sensor networks. But the original network calculus can only model the single-mode wireless sensor network. In this paper, we combine the original network calculus with the multimode model to analyze the maximum delay bound of the flow of interest in the multimode wireless sensor network. There are two combined methods A-MM and N-MM. The method A-MM models the whole network as a multimode component, and the method N-MM models each node as a multimode component. We prove that the maximum delay bound computed by the method A-MM is tighter than or equal to that computed by the method N-MM. Experiments show that our proposed methods can significantly decrease the analytical delay bound comparing with the separate flow analysis method. For the large-scale wireless sensor network with 32 thousands of sensor nodes, our proposed methods can decrease about 70% of the analytical delay bound.

Characteristics of edge localized mode in JFT-2M H-mode

International Nuclear Information System (INIS)

Matsumoto, Hiroshi; Funahashi, Akimasa; Goldston, R.J.

1989-03-01

Characteristics of edge localized mode (ELM/ERP) during H-mode plasma of JFT-2M were investigated. It was found that ELM/ERP is mainly a density fluctuation phenomena in the edge, and electron temperature in the edge except just near the separatrix is not very much perturbed. Several experimental conditions to controll ELM/ERP are, plasma density, plasma ion species, heating power, and plasma current ramping. ELM/ERPs found in low density deuterium discharge are suppressed by raising the density. ELM/ERPs are pronounced in hydrogen plasma compared with deuterium plasma. ELM/ERPs seen in hydrogen plasma or in near marginal H-mode conditions are suppressed by increasing the heating power. ELM/ERPs are found to be suppressed by plasma current ramp down, whereas they are enhanced by current ramp up. MHD aspect of ELM/ERP was investigated. No clear MHD features of ELM/ERP were found. However, reversal of mode rotation seen imediately after ELM/ERP suggests the temporal return to L-mode during the ELM/ERP event. (author)

Working memory activation of neural networks in the elderly as a function of information processing phase and task complexity.

Science.gov (United States)

Charroud, Céline; Steffener, Jason; Le Bars, Emmanuelle; Deverdun, Jérémy; Bonafe, Alain; Abdennour, Meriem; Portet, Florence; Molino, François; Stern, Yaakov; Ritchie, Karen; Menjot de Champfleur, Nicolas; Akbaraly, Tasnime N

2015-11-01

Changes in working memory are sensitive indicators of both normal and pathological brain aging and associated disability. The present study aims to further understanding of working memory in normal aging using a large cohort of healthy elderly in order to examine three separate phases of information processing in relation to changes in task load activation. Using covariance analysis, increasing and decreasing neural activation was observed on fMRI in response to a delayed item recognition task in 337 cognitively healthy elderly persons as part of the CRESCENDO (Cognitive REServe and Clinical ENDOphenotypes) study. During three phases of the task (stimulation, retention, probe), increased activation was observed with increasing task load in bilateral regions of the prefrontal cortex, parietal lobule, cingulate gyrus, insula and in deep gray matter nuclei, suggesting an involvement of central executive and salience networks. Decreased activation associated with increasing task load was observed during the stimulation phase, in bilateral temporal cortex, parietal lobule, cingulate gyrus and prefrontal cortex. This spatial distribution of decreased activation is suggestive of the default mode network. These findings support the hypothesis of an increased activation in salience and central executive networks and a decreased activation in default mode network concomitant to increasing task load. Copyright © 2015 Elsevier Inc. All rights reserved.

Abnormal functional integration across core brain networks in migraine without aura.

Science.gov (United States)

Yu, Dahua; Yuan, Kai; Luo, Lin; Zhai, Jinquan; Bi, Yanzhi; Xue, Ting; Ren, Xiaoying; Zhang, Ming; Ren, Guoyin; Lu, Xiaoqi

2017-01-01

As a complex subjective experience, pain processing may be related to functional integration among intrinsic connectivity networks of migraine patients without aura. However, few study focused on the pattern alterations in the intrinsic connectivity networks of migraine patients without aura. Thirty-one migraine patients without aura and 31 age- and education-matched healthy controls participated in this study. After identifying the default mode network, central executive network and salience network as core intrinsic connectivity networks by using independent component analysis, functional connectivity, and effective connectivity during the resting state were used to investigate the abnormalities in intrinsic connectivity network interactions. Migraine patients without aura showed decreased functional connectivity among intrinsic connectivity networks compared with healthy controls. The strength of causal influences from the right frontoinsular cortex to the right anterior cingulate cortex became weaker, and the right frontoinsular cortex to the right medial prefrontal cortex became stronger in migraine patients without aura. These changes suggested that the salience network may play a major role in the pathophysiological features of migraine patients without aura and helped us to synthesize previous findings into an aberrant network dynamical framework.

Partnership Mode of Organising Government-Business Relationships

DEFF Research Database (Denmark)

Lehmann, Martin; Sørensen, Olav Jull

2004-01-01

At the 2002 Earth Summit in Johannesburg, it was concluded that public-private partnerships should be one of the pivotal mechanisms of greening. This conclusion underlined the shift in regulatory regimes that has been going on for more than a decade. Moving from largely command and control measures...... and means employed - outside as well as inside the network - have developed accordingly. In this paper, the authors discuss a distinct partnership mode of government business relationships ? a strategic alliance with respect, trust, and mutual legitimacy ? and relate this to the Green Network way of doing...

Health impact assessment of cycling network expansions in European cities.

Science.gov (United States)

Mueller, Natalie; Rojas-Rueda, David; Salmon, Maëlle; Martinez, David; Ambros, Albert; Brand, Christian; de Nazelle, Audrey; Dons, Evi; Gaupp-Berghausen, Mailin; Gerike, Regine; Götschi, Thomas; Iacorossi, Francesco; Int Panis, Luc; Kahlmeier, Sonja; Raser, Elisabeth; Nieuwenhuijsen, Mark

2018-04-01

We conducted a health impact assessment (HIA) of cycling network expansions in seven European cities. We modeled the association between cycling network length and cycling mode share and estimated health impacts of the expansion of cycling networks. First, we performed a non-linear least square regression to assess the relationship between cycling network length and cycling mode share for 167 European cities. Second, we conducted a quantitative HIA for the seven cities of different scenarios (S) assessing how an expansion of the cycling network [i.e. 10% (S1); 50% (S2); 100% (S3), and all-streets (S4)] would lead to an increase in cycling mode share and estimated mortality impacts thereof. We quantified mortality impacts for changes in physical activity, air pollution and traffic incidents. Third, we conducted a cost-benefit analysis. The cycling network length was associated with a cycling mode share of up to 24.7% in European cities. The all-streets scenario (S4) produced greatest benefits through increases in cycling for London with 1,210 premature deaths (95% CI: 447-1,972) avoidable annually, followed by Rome (433; 95% CI: 170-695), Barcelona (248; 95% CI: 86-410), Vienna (146; 95% CI: 40-252), Zurich (58; 95% CI: 16-100) and Antwerp (7; 95% CI: 3-11). The largest cost-benefit ratios were found for the 10% increase in cycling networks (S1). If all 167 European cities achieved a cycling mode share of 24.7% over 10,000 premature deaths could be avoided annually. In European cities, expansions of cycling networks were associated with increases in cycling and estimated to provide health and economic benefits. Copyright © 2018 Elsevier Inc. All rights reserved.

Impact of delivery mode on the colostrum microbiota composition.

Science.gov (United States)

Toscano, Marco; De Grandi, Roberta; Peroni, Diego Giampietro; Grossi, Enzo; Facchin, Valentina; Comberiati, Pasquale; Drago, Lorenzo

2017-09-25

Breast milk is a rich nutrient with a temporally dynamic nature. In particular, numerous alterations in the nutritional, immunological and microbiological content occur during the transition from colostrum to mature milk. The objective of our study was to evaluate the potential impact of delivery mode on the microbiota of colostrum, at both the quantitative and qualitative levels (bacterial abundance and microbiota network). Twenty-nine Italian mothers (15 vaginal deliveries vs 14 Cesarean sections) were enrolled in the study. The microbiota of colostrum samples was analyzed by next generation sequencing (Ion Torrent Personal Genome Machine). The colostrum microbiota network associated with Cesarean section and vaginal delivery was evaluated by means of the Auto Contractive Map (AutoCM), a mathematical methodology based on Artificial Neural Network (ANN) architecture. Numerous differences between Cesarean section and vaginal delivery colostrum were observed. Vaginal delivery colostrum had a significant lower abundance of Pseudomonas spp., Staphylococcus spp. and Prevotella spp. when compared to Cesarean section colostrum samples. Furthermore, the mode of delivery had a strong influence on the microbiota network, as Cesarean section colostrum showed a higher number of bacterial hubs if compared to vaginal delivery, sharing only 5 hubs. Interestingly, the colostrum of mothers who had a Cesarean section was richer in environmental bacteria than mothers who underwent vaginal delivery. Finally, both Cesarean section and vaginal delivery colostrum contained a greater number of anaerobic bacteria genera. The mode of delivery had a large impact on the microbiota composition of colostrum. Further studies are needed to better define the meaning of the differences we observed between Cesarean section and vaginal delivery colostrum microbiota.

A general evolving model for growing bipartite networks

International Nuclear Information System (INIS)

Tian, Lixin; He, Yinghuan; Liu, Haijun; Du, Ruijin

2012-01-01

In this Letter, we propose and study an inner evolving bipartite network model. Significantly, we prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. Furthermore, the joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks. Numerical simulations and empirical results are given to verify the theoretical results. -- Highlights: ► We proposed a general evolving bipartite network model which was based on priority connection, reconnection and breaking edges. ► We prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. ► The joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. ► The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks.

Single-mode glass waveguide technology for optical interchip communication on board level

Science.gov (United States)

Brusberg, Lars; Neitz, Marcel; Schröder, Henning

2012-01-01

The large bandwidth demand in long-distance telecom networks lead to single-mode fiber interconnects as result of low dispersion, low loss and dense wavelength multiplexing possibilities. In contrast, multi-mode interconnects are suitable for much shorter lengths up to 300 meters and are promising for optical links between racks and on board level. Active optical cables based on multi-mode fiber links are at the market and research in multi-mode waveguide integration on board level is still going on. Compared to multi-mode, a single-mode waveguide has much more integration potential because of core diameters of around 20% of a multi-mode waveguide by a much larger bandwidth. But light coupling in single-mode waveguides is much more challenging because of lower coupling tolerances. Together with the silicon photonics technology, a single-mode waveguide technology on board-level will be the straight forward development goal for chip-to-chip optical interconnects integration. Such a hybrid packaging platform providing 3D optical single-mode links bridges the gap between novel photonic integrated circuits and the glass fiber based long-distance telecom networks. Following we introduce our 3D photonic packaging approach based on thin glass substrates with planar integrated optical single-mode waveguides for fiber-to-chip and chip-to-chip interconnects. This novel packaging approach merges micro-system packaging and glass integrated optics. It consists of a thin glass substrate with planar integrated singlemode waveguide circuits, optical mirrors and lenses providing an integration platform for photonic IC assembly and optical fiber interconnect. Thin glass is commercially available in panel and wafer formats and characterizes excellent optical and high-frequency properties. That makes it perfect for microsystem packaging. The paper presents recent results in single-mode waveguide technology on wafer level and waveguide characterization. Furthermore the integration in a

The psychedelic state induced by ayahuasca modulates the activity and connectivity of the default mode network.

Directory of Open Access Journals (Sweden)

Fernanda Palhano-Fontes

Full Text Available The experiences induced by psychedelics share a wide variety of subjective features, related to the complex changes in perception and cognition induced by this class of drugs. A remarkable increase in introspection is at the core of these altered states of consciousness. Self-oriented mental activity has been consistently linked to the Default Mode Network (DMN, a set of brain regions more active during rest than during the execution of a goal-directed task. Here we used fMRI technique to inspect the DMN during the psychedelic state induced by Ayahuasca in ten experienced subjects. Ayahuasca is a potion traditionally used by Amazonian Amerindians composed by a mixture of compounds that increase monoaminergic transmission. In particular, we examined whether Ayahuasca changes the activity and connectivity of the DMN and the connection between the DMN and the task-positive network (TPN. Ayahuasca caused a significant decrease in activity through most parts of the DMN, including its most consistent hubs: the Posterior Cingulate Cortex (PCC/Precuneus and the medial Prefrontal Cortex (mPFC. Functional connectivity within the PCC/Precuneus decreased after Ayahuasca intake. No significant change was observed in the DMN-TPN orthogonality. Altogether, our results support the notion that the altered state of consciousness induced by Ayahuasca, like those induced by psilocybin (another serotonergic psychedelic, meditation and sleep, is linked to the modulation of the activity and the connectivity of the DMN.

Design and characterization of 16-mode PANDA polarization-maintaining few-mode ring-core fiber for spatial division multiplexing

Science.gov (United States)

Cao, Yuan; Zhao, Yongli; Yu, Xiaosong; Han, Jiawei; Zhang, Jie

2017-11-01

A PANDA polarization-maintaining few-mode ring-core fiber (PM-FM-RCF) structure with two air holes around the ring core is proposed. The relative mode multiplicity factor (RMMF) is defined to evaluate the spatial efficiency of the designed PM-FM-RCF. The performance analysis and comparison of the proposed PANDA PM-FM-RCFs considering three different types of step-index profiles are detailed. Through modal characteristic analysis and numerical simulation, the PM-FM-RCF with a lower refractive index difference (Δnoi=1.5%) between the ring core and the inner central circle can support up to 16 polarization modes with large RMMF at C-band, which shows the optimum modal properties compared with the PM-FM-RCF with higher Δnoi. All the supported polarization modes are effectively separated from their adjacent polarization modes with effective refractive index differences (Δn) larger than 10-4, which also show relatively small chromatic dispersion (-20 to 25 ps/nm/km), low attenuation (<1.4 dB/km), and small bending radius (˜8 mm) over the C-band. The designed PM-FM-RCF can be compatible with standard single-mode fibers and applied in multiple-input multiple-output-free spatial division multiplexing optical networks for short-reach optical interconnection.

Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis

Directory of Open Access Journals (Sweden)

Bach Phi Duong

2018-04-01

Full Text Available The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE signals. To address this issue, a new approach is proposed in this paper for the detection of multiple combined faults in bearings. The proposed methodology uses a deep neural network (DNN architecture to effectively diagnose the combined defects. The DNN structure is based on the stacked denoising autoencoder non-mutually exclusive classifier (NMEC method for combined modes. The NMEC-DNN is trained using data for a single fault and it classifies both single faults and multiple combined faults. The results of experiments conducted on AE data collected through an experimental test-bed demonstrate that the DNN achieves good classification performance with a maximum accuracy of 95%. The proposed method is compared with a multi-class classifier based on support vector machines (SVMs. The NMEC-DNN yields better diagnostic performance in comparison to the multi-class classifier based on SVM. The NMEC-DNN reduces the number of necessary data collections and improves the bearing fault diagnosis performance.

Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis.

Science.gov (United States)

Duong, Bach Phi; Kim, Jong-Myon

2018-04-07

The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE) signals. To address this issue, a new approach is proposed in this paper for the detection of multiple combined faults in bearings. The proposed methodology uses a deep neural network (DNN) architecture to effectively diagnose the combined defects. The DNN structure is based on the stacked denoising autoencoder non-mutually exclusive classifier (NMEC) method for combined modes. The NMEC-DNN is trained using data for a single fault and it classifies both single faults and multiple combined faults. The results of experiments conducted on AE data collected through an experimental test-bed demonstrate that the DNN achieves good classification performance with a maximum accuracy of 95%. The proposed method is compared with a multi-class classifier based on support vector machines (SVMs). The NMEC-DNN yields better diagnostic performance in comparison to the multi-class classifier based on SVM. The NMEC-DNN reduces the number of necessary data collections and improves the bearing fault diagnosis performance.

Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis

Science.gov (United States)

Kim, Jong-Myon

2018-01-01

The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE) signals. To address this issue, a new approach is proposed in this paper for the detection of multiple combined faults in bearings. The proposed methodology uses a deep neural network (DNN) architecture to effectively diagnose the combined defects. The DNN structure is based on the stacked denoising autoencoder non-mutually exclusive classifier (NMEC) method for combined modes. The NMEC-DNN is trained using data for a single fault and it classifies both single faults and multiple combined faults. The results of experiments conducted on AE data collected through an experimental test-bed demonstrate that the DNN achieves good classification performance with a maximum accuracy of 95%. The proposed method is compared with a multi-class classifier based on support vector machines (SVMs). The NMEC-DNN yields better diagnostic performance in comparison to the multi-class classifier based on SVM. The NMEC-DNN reduces the number of necessary data collections and improves the bearing fault diagnosis performance. PMID:29642466

Magnetohydrodynamic waves driven by p-modes

International Nuclear Information System (INIS)

Khomenko, Elena; Santamaria, Irantzu Calvo

2013-01-01

Waves are observed at all layers of the solar atmosphere and the magnetic field plays a key role in their propagation. While deep down in the atmosphere the p-modes are almost entirely of acoustic nature, in the upper layers magnetic forces are dominating, leading to a large variety of new wave modes. Significant advances have been made recently in our understanding of the physics of waves interaction with magnetic structures, with the help of analytical theories, numerical simulations, as well as high-resolution observations. In this contribution, we review recent observational findings and current theoretical ideas in the field, with an emphasis on the following questions: (i) Peculiarities of the observed wave propagation in network, plage and facular regions; (ii) Role of the mode transformation and observational evidences of this process: (iii) Coupling of the photosphere, chromosphere, and above by means of waves propagating in magnetic structures.

Chaotic Modes in Scale Free Opinion Networks

Science.gov (United States)

Kusmartsev, Feo V.; Kürten, Karl E.

2010-12-01

In this paper, we investigate processes associated with formation of public opinion in varies directed random, scale free and small-world social networks. The important factor of the opinion formation is the existence of contrarians which were discovered by Granovetter in various social psychology experiments1,2,3 long ago and later introduced in sociophysics by Galam.4 When the density of contrarians increases the system behavior drastically changes at some critical value. At high density of contrarians the system can never arrive to a consensus state and periodically oscillates with different periods depending on specific structure of the network. At small density of the contrarians the behavior is manifold. It depends primary on the initial state of the system. If initially the majority of the population agrees with each other a state of stable majority may be easily reached. However when originally the population is divided in nearly equal parts consensus can never be reached. We model the emergence of collective decision making by considering N interacting agents, whose opinions are described by two state Ising spin variable associated with YES and NO. We show that the dynamical behaviors are very sensitive not only to the density of the contrarians but also to the network topology. We find that a phase of social chaos may arise in various dynamical processes of opinion formation in many realistic models. We compare the prediction of the theory with data describing the dynamics of the average opinion of the USA population collected on a day-by-day basis by varies media sources during the last six month before the final Obama-McCain election. The qualitative ouctome is in reasonable agreement with the prediction of our theory. In fact, the analyses of these data made within the paradigm of our theory indicates that even in this campaign there were chaotic elements where the public opinion migrated in an unpredictable chaotic way. The existence of such a phase

Suggestive Objects at Work

DEFF Research Database (Denmark)

Ratner, Helene Gad

2009-01-01

In Western secular societies, spiritual life is no longer limited to classical religious institutions but can also be found at workplace organizations. While spirituality is conventionally understood as a subjective and internal process, this paper proposes the concept of ‘suggestive objects......’, constructed by combining insights from Gabriel Tarde's sociology with Bruno Latour's actor-network theory, to theorize the material dimension of organizational spirituality. The sacred in organizations arises not from the internalization of collective values but through the establishment of material...... scaffolding. This has deep implications for our understanding of the sacred, including a better appreciation of the way that suggestive objects make the sacred durable, the way they organize it....

Abnormal resting state effective connectivity within the default mode network in major depressive disorder: A spectral dynamic causal modeling study.

Science.gov (United States)

Li, Liang; Li, Baojuan; Bai, Yuanhan; Liu, Wenlei; Wang, Huaning; Leung, Hoi-Chung; Tian, Ping; Zhang, Linchuan; Guo, Fan; Cui, Long-Biao; Yin, Hong; Lu, Hongbing; Tan, Qingrong

2017-07-01

Understanding the neural basis underlying major depressive disorder (MDD) is essential for the diagnosis and treatment of this mental disorder. Aberrant activation and functional connectivity of the default mode network (DMN) have been consistently found in patients with MDD. It is not known whether effective connectivity within the DMN is altered in MDD. The primary object of this study is to investigate the effective connectivity within the DMN during resting state in MDD patients before and after eight weeks of antidepressant treatment. We defined four regions of the DMN (medial frontal cortex, posterior cingulate cortex, left parietal cortex, and right parietal cortex) for each participant using a group independent component analysis. The coupling parameters reflecting the causal interactions among the DMN regions were estimated using spectral dynamic causal modeling (DCM). Twenty-seven MDD patients and 27 healthy controls were included in the statistical analysis. Our results showed declined influences from the left parietal cortex to other DMN regions in the pre-treatment patients as compared with healthy controls. After eight weeks of treatment, the influence from the right parietal cortex to the posterior cingulate cortex significantly decreased. These findings suggest that the reduced excitatory causal influence of the left parietal cortex is the key alteration of the DMN in patients with MDD, and the disrupted causal influences that parietal cortex exerts on the posterior cingulate cortex is responsive to antidepressant treatment.

Network evolution of body plans.

Directory of Open Access Journals (Sweden)

Koichi Fujimoto

Full Text Available One of the major goals in evolutionary developmental biology is to understand the relationship between gene regulatory networks and the diverse morphologies and their functionalities. Are the diversities solely triggered by random events, or are they inevitable outcomes of an interplay between evolving gene networks and natural selection? Segmentation in arthropod embryogenesis represents a well-known example of body plan diversity. Striped patterns of gene expression that lead to the future body segments appear simultaneously or sequentially in long and short germ-band development, respectively. Moreover, a combination of both is found in intermediate germ-band development. Regulatory genes relevant for stripe formation are evolutionarily conserved among arthropods, therefore the differences in the observed traits are thought to have originated from how the genes are wired. To reveal the basic differences in the network structure, we have numerically evolved hundreds of gene regulatory networks that produce striped patterns of gene expression. By analyzing the topologies of the generated networks, we show that the characteristics of stripe formation in long and short germ-band development are determined by Feed-Forward Loops (FFLs and negative Feed-Back Loops (FBLs respectively, and those of intermediate germ-band development are determined by the interconnections between FFL and negative FBL. Network architectures, gene expression patterns and knockout responses exhibited by the artificially evolved networks agree with those reported in the fly Drosophila melanogaster and the beetle Tribolium castaneum. For other arthropod species, principal network architectures that remain largely unknown are predicted. Our results suggest that the emergence of the three modes of body segmentation in arthropods is an inherent property of the evolving networks.

Space evolution model and empirical analysis of an urban public transport network

Science.gov (United States)

Sui, Yi; Shao, Feng-jing; Sun, Ren-cheng; Li, Shu-jing

2012-07-01

This study explores the space evolution of an urban public transport network, using empirical evidence and a simulation model validated on that data. Public transport patterns primarily depend on traffic spatial-distribution, demands of passengers and expected utility of investors. Evolution is an iterative process of satisfying the needs of passengers and investors based on a given traffic spatial-distribution. The temporal change of urban public transport network is evaluated both using topological measures and spatial ones. The simulation model is validated using empirical data from nine big cities in China. Statistical analyses on topological and spatial attributes suggest that an evolution network with traffic demands characterized by power-law numerical values which distribute in a mode of concentric circles tallies well with these nine cities.

YANA – a software tool for analyzing flux modes, gene-expression and enzyme activities

Directory of Open Access Journals (Sweden)

Engels Bernd

2005-06-01

Full Text Available Abstract Background A number of algorithms for steady state analysis of metabolic networks have been developed over the years. Of these, Elementary Mode Analysis (EMA has proven especially useful. Despite its low user-friendliness, METATOOL as a reliable high-performance implementation of the algorithm has been the instrument of choice up to now. As reported here, the analysis of metabolic networks has been improved by an editor and analyzer of metabolic flux modes. Analysis routines for expression levels and the most central, well connected metabolites and their metabolic connections are of particular interest. Results YANA features a platform-independent, dedicated toolbox for metabolic networks with a graphical user interface to calculate (integrating METATOOL, edit (including support for the SBML format, visualize, centralize, and compare elementary flux modes. Further, YANA calculates expected flux distributions for a given Elementary Mode (EM activity pattern and vice versa. Moreover, a dissection algorithm, a centralization algorithm, and an average diameter routine can be used to simplify and analyze complex networks. Proteomics or gene expression data give a rough indication of some individual enzyme activities, whereas the complete flux distribution in the network is often not known. As such data are noisy, YANA features a fast evolutionary algorithm (EA for the prediction of EM activities with minimum error, including alerts for inconsistent experimental data. We offer the possibility to include further known constraints (e.g. growth constraints in the EA calculation process. The redox metabolism around glutathione reductase serves as an illustration example. All software and documentation are available for download at http://yana.bioapps.biozentrum.uni-wuerzburg.de. Conclusion A graphical toolbox and an editor for METATOOL as well as a series of additional routines for metabolic network analyses constitute a new user

Evaluation of connected vehicle impact on mobility and mode choice

Directory of Open Access Journals (Sweden)

Simon Minelli

2015-10-01

Full Text Available Connected vehicle is emerging as a solution to exacerbating congestion problems in urban areas. It is important to understand the impacts of connected vehicle on network and travel behavior of road users. The main objective of this paper is to evaluate the impact of connected vehicle on the mode choice and mobility of transportation networks. An iterative methodology was used in this paper where demands for various modes were modified based on the changes in travel time between each origin-destination (OD pair caused by introduction of connected vehicle. Then a traffic assignment was performed in a micro-simulation model, which was able to accurately simulate vehicle-to-vehicle communication. It is assumed that vehicles are equipped with a dynamic route guidance technology to choose their own route using real-time traffic information obtained through communication. The travel times obtained from the micro-simulation model were compared with a base scenario with no connected vehicle. The methodology was tested for a portion of Downtown Toronto, Ontario, Canada. In order to quantify changes in mode share with changes in travel time associated with each OD pair, mode choice models were developed for auto, transit, cycling and pedestrians using data mainly from the Transportation Tomorrow Survey. The impact of connected vehicle on mode choice was evaluated for different market penetrations of connected vehicle. The results of this study show that average travel times for the whole auto mode will generally increase, with the largest increase from connected vehicles. This causes an overall move away from the auto mode for high market penetrations if a dynamic route guidance algorithm is implemented.

PV-Plants in autarky or network coupled operation: technical and economic comparison accordingly to practical investigations

International Nuclear Information System (INIS)

Ajib, Salman; Seitz, Thomas; Petzold, Reinhardt

2006-01-01

PV-Plants can be operated, as known, using autarky or network coupled operation modes, The first operation mode is recommended in the places which locate away from the electrical supply network. However the PV-plants, when using network coupled mode, can be used in all of the places, where the sunlight is suitable and there is a sufficient place to establish these plants in the required size. The differences between the two operation modes are the additional components and the dimensioning of the PV-plants. The whole needed electrical energy must be obtained from the PV-plants, when the autarky operation mode is used. In contrast to this, this energy can be provided by the PV-plants or by the electrical supply network when the network coupled operation mode is used, therefore a network coupled PV-plants need a careful initial planning and installation. In this paper the function principles and the components of these PV-plants in the two operation modes will be presented. In addition to this, the results obtained from the investigation of PV-plants while working with nominal power of P= 1 kW p will be analyzed and discussed too. After that the dimensioning steps and the economic evaluation will be depicted.(Author)

Selective vulnerability related to aging in large-scale resting brain networks.

Science.gov (United States)

Zhang, Hong-Ying; Chen, Wen-Xin; Jiao, Yun; Xu, Yao; Zhang, Xiang-Rong; Wu, Jing-Tao

2014-01-01

Normal aging is associated with cognitive decline. Evidence indicates that large-scale brain networks are affected by aging; however, it has not been established whether aging has equivalent effects on specific large-scale networks. In the present study, 40 healthy subjects including 22 older (aged 60-80 years) and 18 younger (aged 22-33 years) adults underwent resting-state functional MRI scanning. Four canonical resting-state networks, including the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN) and salience network, were extracted, and the functional connectivities in these canonical networks were compared between the younger and older groups. We found distinct, disruptive alterations present in the large-scale aging-related resting brain networks: the ECN was affected the most, followed by the DAN. However, the DMN and salience networks showed limited functional connectivity disruption. The visual network served as a control and was similarly preserved in both groups. Our findings suggest that the aged brain is characterized by selective vulnerability in large-scale brain networks. These results could help improve our understanding of the mechanism of degeneration in the aging brain. Additional work is warranted to determine whether selective alterations in the intrinsic networks are related to impairments in behavioral performance.

Aging and Network Properties: Stability Over Time and Links with Learning during Working Memory Training

Directory of Open Access Journals (Sweden)

Alexandru D. Iordan

2018-01-01

Full Text Available Growing evidence suggests that healthy aging affects the configuration of large-scale functional brain networks. This includes reducing network modularity and local efficiency. However, the stability of these effects over time and their potential role in learning remain poorly understood. The goal of the present study was to further clarify previously reported age effects on “resting-state” networks, to test their reliability over time, and to assess their relation to subsequent learning during training. Resting-state fMRI data from 23 young (YA and 20 older adults (OA were acquired in 2 sessions 2 weeks apart. Graph-theoretic analyses identified both consistencies in network structure and differences in module composition between YA and OA, suggesting topological changes and less stability of functional network configuration with aging. Brain-wide, OA showed lower modularity and local efficiency compared to YA, consistent with the idea of age-related functional dedifferentiation, and these effects were replicable over time. At the level of individual networks, OA consistently showed greater participation and lower local efficiency and within-network connectivity in the cingulo-opercular network, as well as lower intra-network connectivity in the default-mode network and greater participation of the somato-sensorimotor network, suggesting age-related differential effects at the level of specialized brain modules. Finally, brain-wide network properties showed associations, albeit limited, with learning rates, as assessed with 10 days of computerized working memory training administered after the resting-state sessions, suggesting that baseline network configuration may influence subsequent learning outcomes. Identification of neural mechanisms associated with learning-induced plasticity is important for further clarifying whether and how such changes predict the magnitude and maintenance of training gains, as well as the extent and limits of

Changes in default mode network as automaticity develops in a categorization task.

Science.gov (United States)

Shamloo, Farzin; Helie, Sebastien

2016-10-15

The default mode network (DMN) is a set of brain regions in which blood oxygen level dependent signal is suppressed during attentional focus on the external environment. Because automatic task processing requires less attention, development of automaticity in a rule-based categorization task may result in less deactivation and altered functional connectivity of the DMN when compared to the initial learning stage. We tested this hypothesis by re-analyzing functional magnetic resonance imaging data of participants trained in rule-based categorization for over 10,000 trials (Helie et al., 2010) [12,13]. The results show that some DMN regions are deactivated in initial training but not after automaticity has developed. There is also a significant decrease in DMN deactivation after extensive practice. Seed-based functional connectivity analyses with the precuneus, medial prefrontal cortex (two important DMN regions) and Brodmann area 6 (an important region in automatic categorization) were also performed. The results show increased functional connectivity with both DMN and non-DMN regions after the development of automaticity, and a decrease in functional connectivity between the medial prefrontal cortex and ventromedial orbitofrontal cortex. Together, these results further support the hypothesis of a strategy shift in automatic categorization and bridge the cognitive and neuroscientific conceptions of automaticity in showing that the reduced need for cognitive resources in automatic processing is accompanied by a disinhibition of the DMN and stronger functional connectivity between DMN and task-related brain regions. Copyright © 2016 Elsevier B.V. All rights reserved.

A mixed-mode traffic assignment model with new time-flow impedance function

Science.gov (United States)

Lin, Gui-Hua; Hu, Yu; Zou, Yuan-Yang

2018-01-01

Recently, with the wide adoption of electric vehicles, transportation network has shown different characteristics and been further developed. In this paper, we present a new time-flow impedance function, which may be more realistic than the existing time-flow impedance functions. Based on this new impedance function, we present an optimization model for a mixed-mode traffic network in which battery electric vehicles (BEVs) and gasoline vehicles (GVs) are chosen. We suggest two approaches to handle the model: One is to use the interior point (IP) algorithm and the other is to employ the sequential quadratic programming (SQP) algorithm. Three numerical examples are presented to illustrate the efficiency of these approaches. In particular, our numerical results show that more travelers prefer to choosing BEVs when the distance limit of BEVs is long enough and the unit operating cost of GVs is higher than that of BEVs, and the SQP algorithm is faster than the IP algorithm.

Latent geometry of bipartite networks

Science.gov (United States)

Kitsak, Maksim; Papadopoulos, Fragkiskos; Krioukov, Dmitri

2017-03-01

Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs. Here we pursue a different approach for analyzing bipartite systems that is based on the observation that such systems have a latent metric structure: network nodes are points in a latent metric space, while connections are more likely to form between nodes separated by shorter distances. This approach has been developed for unipartite networks, and relatively little is known about its applicability to bipartite systems. Here, we fully analyze a simple latent-geometric model of bipartite networks and show that this model explains the peculiar structural properties of many real bipartite systems, including the distributions of common neighbors and bipartite clustering. We also analyze the geometric information loss in one-mode projections in this model and propose an efficient method to infer the latent pairwise distances between nodes. Uncovering the latent geometry underlying real bipartite networks can find applications in diverse domains, ranging from constructing efficient recommender systems to understanding cell metabolism.

RISIKO RANTAI PASOK KAKAO DI INDONESIA DENGAN METODE ANALYTIC NETWORK PROCESS DAN FAILURE MODE EFFECT ANALYSIS TERINTEGRASI

Directory of Open Access Journals (Sweden)

Harumi Aini

2015-03-01

Full Text Available Cocoa is one of the plantation commodities whose role is quite important for the national economy of Indonesia. However, the cocoa industry faces several problems including the various risks involved in the cocoa supply chain. The aim of this study were: 1 Identify the various risks involved in the cocoa supply chain, 2 analyze and evaluate the supply chain actors members with the highest risk in the cocoa supply chain management, and 3 understand how to evaluate and mitigate the highest risk in the cocoa supply chain effectively and efficiently. An Integrated Analytic Network Process (ANP and Weighted Failure Mode Effect Analysis (WFMEA method will be used to determine and analyze the highest risk in the cocoa supply chain. The results of the priority of the members of the value chain in the cocoa supply chain risk management are the farmer (0.408 with the risk of having the greatest priority is production risk (0.221. Risk control could be done by improving the productivity and competitiveness of cocoa.Keywords: ANP, FMEA, cocoa, risk management, supply chainABSTRAKKakao merupakan salah satu komoditas perkebunan yang peranannya cukup penting bagi perekonomian Indonesia. Industri kakao menghadapi beberapa masalah termasuk berbagai risiko yang timbul dalam rantai pasokan kakao. Tujuan penelitian ini adalah 1 mengidentifikasi macam-macam risiko pada rantai pasok kakao, 2 menganalisis dan mengevaluasi anggota pelaku rantai pasok dengan risiko tertinggi dalam manajemen rantai pasok kakao, dan 3 mengetahui cara mengevaluasi dan memitigasi risiko tertinggi pada rantai pasok kakao dengan efektif dan efisien. Metode Analytic Network Process (ANP dan Weighted Failure Mode Effect Analysis (WFMEA terintegrasi digunakan untuk mengetahui dan menganalisis risiko tertinggi dalam rantai pasokan kakao. Hasil prioritas anggota pelaku rantai pasok dalam manajemen risiko rantai pasokan kakao petani (0,408 dengan risiko yang memiliki prioritas terbesar adalah

The influence of rest period instructions on the default mode network

Directory of Open Access Journals (Sweden)

Christopher eBenjamin

2010-12-01

Full Text Available The default mode network (DMN refers to regional brain activity that is greater during rest periods than during attention-demanding tasks and many studies have reported DMN alterations in patient populations. It has also been shown that the DMN is suppressed by scanner background noise (SBN, which is the noise produced by functional magnetic resonance imaging (fMRI. However, it is unclear whether different approaches to rest in the noisy MR environment can alter the DMN and constitute a confound in studies investigating the DMN in particular patient populations (e.g., individuals with schizophrenia, Alzheimer’s disease. We examined twenty-seven healthy adult volunteers who completed an fMRI experiment with 3 different instructions for rest: (1 relax and be still, (2 attend to SBN, or (3 ignore SBN. Region of interest (ROI analyses were performed to determine the influence of rest period instructions on core regions of the DMN and DMN regions previously reported to be altered in patients with or at risk for Alzheimer’s disease or schizophrenia. The dorsal medial prefrontal cortex (dmPFC exhibited greater activity when specific resting instructions were given (i.e. attend to or ignore SBN compared to when non-specific resting instructions were given. Condition-related differences in connectivity were also observed between regions of the dmPFC and inferior parietal/posterior superior temporal cortex. We conclude that rest period instructions and SBN levels should be carefully considered for fMRI studies on the DMN, especially studies on clinical populations and groups that may have different approaches to rest, such as first-time research participants and children.

Designing optimal greenhouse gas monitoring networks for Australia

Science.gov (United States)

Ziehn, T.; Law, R. M.; Rayner, P. J.; Roff, G.

2016-01-01