mode network activity: Topics by Science.gov

Sample records for mode network activity

Meditation leads to reduced default mode network activity beyond an active task.

PubMed

Garrison, Kathleen A; Zeffiro, Thomas A; Scheinost, Dustin; Constable, R Todd; Brewer, Judson A

2015-09-01

Meditation has been associated with relatively reduced activity in the default mode network, a brain network implicated in self-related thinking and mind wandering. However, previous imaging studies have typically compared meditation to rest, despite other studies having reported differences in brain activation patterns between meditators and controls at rest. Moreover, rest is associated with a range of brain activation patterns across individuals that has only recently begun to be better characterized. Therefore, in this study we compared meditation to another active cognitive task, both to replicate the findings that meditation is associated with relatively reduced default mode network activity and to extend these findings by testing whether default mode activity was reduced during meditation, beyond the typical reductions observed during effortful tasks. In addition, prior studies had used small groups, whereas in the present study we tested these hypotheses in a larger group. The results indicated that meditation is associated with reduced activations in the default mode network, relative to an active task, for meditators as compared to controls. Regions of the default mode network showing a Group × Task interaction included the posterior cingulate/precuneus and anterior cingulate cortex. These findings replicate and extend prior work indicating that the suppression of default mode processing may represent a central neural process in long-term meditation, and they suggest that meditation leads to relatively reduced default mode processing beyond that observed during another active cognitive task.
Meditation leads to reduced default mode network activity beyond an active task

PubMed Central

Garrison, Kathleen A.; Zeffiro, Thomas A.; Scheinost, Dustin; Constable, R. Todd; Brewer, Judson A.

2015-01-01

Meditation has been associated with relatively reduced activity in the default mode network, a brain network implicated in self-related thinking and mind wandering. However, previous imaging studies have typically compared meditation to rest despite other studies reporting differences in brain activation patterns between meditators and controls at rest. Moreover, rest is associated with a range of brain activation patterns across individuals that has only recently begun to be better characterized. Therefore, this study compared meditation to another active cognitive task, both to replicate findings that meditation is associated with relatively reduced default mode network activity, and to extend these findings by testing whether default mode activity was reduced during meditation beyond the typical reductions observed during effortful tasks. In addition, prior studies have used small groups, whereas the current study tested these hypotheses in a larger group. Results indicate that meditation is associated with reduced activations in the default mode network relative to an active task in meditators compared to controls. Regions of the default mode showing a group by task interaction include the posterior cingulate/precuneus and anterior cingulate cortex. These findings replicate and extend prior work indicating that suppression of default mode processing may represent a central neural process in long-term meditation, and suggest that meditation leads to relatively reduced default mode processing beyond that observed during another active cognitive task. PMID:25904238
Coupling effect of nodes popularity and similarity on social network persistence

PubMed Central

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

2017-01-01

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. PMID:28220840
Coupling effect of nodes popularity and similarity on social network persistence

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

PubMed

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.
Functional connectivity of default mode network components: correlation, anticorrelation, and causality

PubMed Central

Uddin, Lucina Q.; Clare Kelly, A. M.; Biswal, Bharat B.; Castellanos, F. Xavier; Milham, Michael P.

2013-01-01

The default mode network (DMN), based in ventromedial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC), exhibits higher metabolic activity at rest than during performance of externally-oriented cognitive tasks. Recent studies have suggested that competitive relationships between the DMN and various task-positive networks involved in task performance are intrinsically represented in the brain in the form of strong negative correlations (anticorrelations) between spontaneous fluctuations in these networks. Most neuroimaging studies characterize the DMN as a homogenous network, thus few have examined the differential contributions of DMN components to such competitive relationships. Here we examined functional differentiation within the default mode network, with an emphasis on understanding competitive relationships between this and other networks. We used a seed correlation approach on resting-state data to assess differences in functional connectivity between these two regions and their anticorrelated networks. While the positively correlated networks for the vmPFC and PCC seeds largely overlapped, the anticorrelated networks for each showed striking differences. Activity in vmPFC negatively predicted activity in parietal visual spatial and temporal attention networks, whereas activity in PCC negatively predicted activity in prefrontal-based motor control circuits. Granger causality analyses suggest that vmPFC and PCC exert greater influence on their anticorrelated networks than the other way around, suggesting that these two default mode nodes may directly modulate activity in task-positive networks. Thus, the two major nodes comprising the default mode network are differentiated with respect to the specific brain systems with which they interact, suggesting greater heterogeneity within this network than is commonly appreciated. PMID:18219617
A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice

PubMed Central

Snijders, Tom A.B.; Lomi, Alessandro; Torló, Vanina Jasmine

2012-01-01

We propose a new stochastic actor-oriented model for the co-evolution of two-mode and one-mode networks. The model posits that activities of a set of actors, represented in the two-mode network, co-evolve with exchanges and interactions between the actors, as represented in the one-mode network. The model assumes that the actors, not the activities, have agency. The empirical value of the model is demonstrated by examining how employment preferences co-evolve with friendship and advice relations in a group of seventy-five MBA students. The analysis shows that activity in the two-mode network, as expressed by number of employment preferences, is related to activity in the friendship network, as expressed by outdegrees. Further, advice ties between students lead to agreement with respect to employment preferences. In addition, considering the multiplexity of advice and friendship ties yields a better understanding of the dynamics of the advice relation: tendencies to reciprocation and homophily in advice relations are mediated to an important extent by friendship relations. The discussion pays attention to the implications of this study in the broader context of current efforts to model the co-evolutionary dynamics of social networks and individual behavior. PMID:23690653
The salience network causally influences default mode network activity during moral reasoning

PubMed Central

Wilson, Stephen M.; D’Esposito, Mark; Kayser, Andrew S.; Grossman, Scott N.; Poorzand, Pardis; Seeley, William W.; Miller, Bruce L.; Rankin, Katherine P.

2013-01-01

Large-scale brain networks are integral to the coordination of human behaviour, and their anatomy provides insights into the clinical presentation and progression of neurodegenerative illnesses such as Alzheimer’s disease, which targets the default mode network, and behavioural variant frontotemporal dementia, which targets a more anterior salience network. Although the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, patients with Alzheimer’s disease give normal responses to these dilemmas whereas patients with behavioural variant frontotemporal dementia give abnormal responses to these dilemmas. We hypothesized that this apparent discrepancy between activation- and patient-based studies of moral reasoning might reflect a modulatory role for the salience network in regulating default mode network activation. Using functional magnetic resonance imaging to characterize network activity of patients with behavioural variant frontotemporal dementia and healthy control subjects, we present four converging lines of evidence supporting a causal influence from the salience network to the default mode network during moral reasoning. First, as previously reported, the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, but patients with behavioural variant frontotemporal dementia producing atrophy in the salience network give abnormally utilitarian responses to these dilemmas. Second, patients with behavioural variant frontotemporal dementia have reduced recruitment of the default mode network compared with healthy control subjects when deliberating about these dilemmas. Third, a Granger causality analysis of functional neuroimaging data from healthy control subjects demonstrates directed functional connectivity from nodes of the salience network to nodes of the default mode network during moral reasoning. Fourth, this Granger causal influence is diminished in patients with behavioural variant frontotemporal dementia. These findings are consistent with a broader model in which the salience network modulates the activity of other large-scale networks, and suggest a revision to a previously proposed ‘dual-process’ account of moral reasoning. These findings also characterize network interactions underlying abnormal moral reasoning in frontotemporal dementia, which may serve as a model for the aberrant judgement and interpersonal behaviour observed in this disease and in other disorders of social function. More broadly, these findings link recent work on the dynamic interrelationships between large-scale brain networks to observable impairments in dementia syndromes, which may shed light on how diseases that target one network also alter the function of interrelated networks. PMID:23576128
Topological Edge Modes in Active Mikado Networks

NASA Astrophysics Data System (ADS)

Zhou, Di; Zhang, Leyou; Mao, Xiaoming

Mechanical properties of disordered fiber networks are not only important in understanding a broad range of natural (such as the cytoskeleton and the extracellular matrix) and manmade materials (such as aerogels and porous media) but also exhibit interesting and rich physics. In this talk, we discuss how topological floppy edge modes can emerge from these fiber networks as a result of active driving. It is known that straight fibers in a network carries a state of self-stress and bears a bulk floppy mode. We find that, interestingly, by driving the network with a tiny perturbation, the bulk modes evolve into edge modes. We introduce a new transfer matrix formulation that can be applied to this strongly disordered system, to characterize the topological edge modes. We also discuss possible implications of these edge modes in biological processes. NSF-DMR-1609051.
Combination of DTI and fMRI reveals the white matter changes correlating with the decline of default-mode network activity in Alzheimer's disease

NASA Astrophysics Data System (ADS)

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

PubMed Central

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

2016-01-01

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

PubMed Central

Mirzakhalili, Ehsan; Gourgou, Eleni; Booth, Victoria; Epureanu, Bogdan

2017-01-01

Synaptic deficiencies are a known hallmark of neurodegenerative diseases, but the diagnosis of impaired synapses on the cellular level is not an easy task. Nonetheless, changes in the system-level dynamics of neuronal networks with damaged synapses can be detected using techniques that do not require high spatial resolution. This paper investigates how the structure/topology of neuronal networks influences their dynamics when they suffer from synaptic loss. We study different neuronal network structures/topologies by specifying their degree distributions. The modes of the degree distribution can be used to construct networks that consist of rich clubs and resemble small world networks, as well. We define two dynamical metrics to compare the activity of networks with different structures: persistent activity (namely, the self-sustained activity of the network upon removal of the initial stimulus) and quality of activity (namely, percentage of neurons that participate in the persistent activity of the network). Our results show that synaptic loss affects the persistent activity of networks with bimodal degree distributions less than it affects random networks. The robustness of neuronal networks enhances when the distance between the modes of the degree distribution increases, suggesting that the rich clubs of networks with distinct modes keep the whole network active. In addition, a tradeoff is observed between the quality of activity and the persistent activity. For a range of distributions, both of these dynamical metrics are considerably high for networks with bimodal degree distribution compared to random networks. We also propose three different scenarios of synaptic impairment, which may correspond to different pathological or biological conditions. Regardless of the network structure/topology, results demonstrate that synaptic loss has more severe effects on the activity of the network when impairments are correlated with the activity of the neurons. PMID:28659765
Topological Edge Floppy Modes in Disordered Fiber Networks

NASA Astrophysics Data System (ADS)

Zhou, Di; Zhang, Leyou; Mao, Xiaoming

2018-02-01

Disordered fiber networks are ubiquitous in a broad range of natural (e.g., cytoskeleton) and manmade (e.g., aerogels) materials. In this Letter, we discuss the emergence of topological floppy edge modes in two-dimensional fiber networks as a result of deformation or active driving. It is known that a network of straight fibers exhibits bulk floppy modes which only bend the fibers without stretching them. We find that, interestingly, with a perturbation in geometry, these bulk modes evolve into edge modes. We introduce a topological index for these edge modes and discuss their implications in biology.
Altering the threshold of an excitable signal transduction network changes cell migratory modes.

PubMed

Miao, Yuchuan; Bhattacharya, Sayak; Edwards, Marc; Cai, Huaqing; Inoue, Takanari; Iglesias, Pablo A; Devreotes, Peter N

2017-04-01

The diverse migratory modes displayed by different cell types are generally believed to be idiosyncratic. Here we show that the migratory behaviour of Dictyostelium was switched from amoeboid to keratocyte-like and oscillatory modes by synthetically decreasing phosphatidylinositol-4,5-bisphosphate levels or increasing Ras/Rap-related activities. The perturbations at these key nodes of an excitable signal transduction network initiated a causal chain of events: the threshold for network activation was lowered, the speed and range of propagating waves of signal transduction activity increased, actin-driven cellular protrusions expanded and, consequently, the cell migratory mode transitions ensued. Conversely, innately keratocyte-like and oscillatory cells were promptly converted to amoeboid by inhibition of Ras effectors with restoration of directed migration. We use computational analysis to explain how thresholds control cell migration and discuss the architecture of the signal transduction network that gives rise to excitability.
An fMRI investigation of the relationship between future imagination and cognitive flexibility

PubMed Central

Roberts, R.P.; Wiebels, K.; Sumner, R.L.; van Mulukom, V.; Grady, C.L.; Schacter, D.L.; Addis, D.R.

2016-01-01

While future imagination is largely considered to be a cognitive process grounded in default mode network activity, studies have shown that future imagination recruits regions in both default mode and frontoparietal control networks. In addition, it has recently been shown that the ability to imagine the future is associated with cognitive flexibility, and that tasks requiring cognitive flexibility result in increased coupling of the default mode network with frontoparietal control and salience networks. In the current study, we investigated the neural correlates underlying the association between cognitive flexibility and future imagination in two ways. First, we experimentally varied the degree of cognitive flexibility required during future imagination by manipulating the disparateness of episodic details contributing to imagined events. To this end, participants generated episodic details (persons, locations, objects) within three social spheres; during fMRI scanning they were presented with sets of three episodic details all taken from the same social sphere (Congruent condition) or different social spheres (Incongruent condition) and required to imagine a future event involving the three details. We predicted that, relative to the Congruent condition, future simulation in the Incongruent condition would be associated with increased activity in regions of the default mode, frontoparietal and salience networks. Second, we hypothesized that individual differences in cognitive flexibility, as measured by performance on the Alternate Uses Task, would correspond to individual differences in the brain regions recruited during future imagination. A task partial least squares (PLS) analysis showed that the Incongruent condition resulted in an increase in activity in regions in salience networks (e.g. the insula) but, contrary to our prediction, reduced activity in many regions of the default mode network (including the hippocampus). A subsequent functional connectivity (within-subject seed PLS) analysis showed that the insula exhibited increased coupling with default mode regions during the Incongruent condition. Finally, a behavioral PLS analysis showed that individual differences in cognitive flexibility were associated with differences in activity in a number of regions from frontoparietal, salience and default-mode networks during both future imagination conditions, further highlighting that the cognitive flexibility underlying future imagination is grounded in the complex interaction of regions in these networks. PMID:27908591
Scalable Active Optical Access Network Using Variable High-Speed PLZT Optical Switch/Splitter

NASA Astrophysics Data System (ADS)

Ashizawa, Kunitaka; Sato, Takehiro; Tokuhashi, Kazumasa; Ishii, Daisuke; Okamoto, Satoru; Yamanaka, Naoaki; Oki, Eiji

This paper proposes a scalable active optical access network using high-speed Plumbum Lanthanum Zirconate Titanate (PLZT) optical switch/splitter. The Active Optical Network, called ActiON, using PLZT switching technology has been presented to increase the number of subscribers and the maximum transmission distance, compared to the Passive Optical Network (PON). ActiON supports the multicast slot allocation realized by running the PLZT switch elements in the splitter mode, which forces the switch to behave as an optical splitter. However, the previous ActiON creates a tradeoff between the network scalability and the power loss experienced by the optical signal to each user. It does not use the optical power efficiently because the optical power is simply divided into 0.5 to 0.5 without considering transmission distance from OLT to each ONU. The proposed network adopts PLZT switch elements in the variable splitter mode, which controls the split ratio of the optical power considering the transmission distance from OLT to each ONU, in addition to PLZT switch elements in existing two modes, the switching mode and the splitter mode. The proposed network introduces the flexible multicast slot allocation according to the transmission distance from OLT to each user and the number of required users using three modes, while keeping the advantages of ActiON, which are to support scalable and secure access services. Numerical results show that the proposed network dramatically reduces the required number of slots and supports high bandwidth efficiency services and extends the coverage of access network, compared to the previous ActiON, and the required computation time for selecting multicast users is less than 30msec, which is acceptable for on-demand broadcast services.
Broken Detailed Balance of Filament Dynamics in Active Networks

NASA Astrophysics Data System (ADS)

Schmidt, Christoph F.; Gladrow, Jannes; Fakhri, Nikta; Mackintosh, Fred C.; Broedersz, Chase

Endogenous embedded semiflexible filaments such as microtubules, or added filaments such as single- walled carbon nanotubes can be used as novel tools to noninvasively track equilibrium and nonequilibrium fluctuations in biopolymer networks. We analytically calculated shape fluctuations of semi- flexible probe filaments in a viscoelastic environment, driven out of equilibrium by motor activity. Transverse bending fluctuations of the probe filaments can be decomposed into dynamic normal modes. We find that these modes no longer evolve independently under non-equilibrium driving. This effective mode coupling results in nonzero circulatory currents in a conformational phase space, reflecting a violation of detailed balance. We present predictions for the characteristic frequencies associated with these currents and investigate how the temporal signatures of motor activity determine mode correlations, which we find to be consistent with recent experiments on microtubules embedded in cytoskeletal networks.
Meditation experience is associated with differences in default mode network activity and connectivity

PubMed Central

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
Broken Detailed Balance of Filament Dynamics in Active Networks

NASA Astrophysics Data System (ADS)

Gladrow, J.; Fakhri, N.; MacKintosh, F. C.; Schmidt, C. F.; Broedersz, C. P.

2016-06-01

Myosin motor proteins drive vigorous steady-state fluctuations in the actin cytoskeleton of cells. Endogenous embedded semiflexible filaments such as microtubules, or added filaments such as single-walled carbon nanotubes are used as novel tools to noninvasively track equilibrium and nonequilibrium fluctuations in such biopolymer networks. Here, we analytically calculate shape fluctuations of semiflexible probe filaments in a viscoelastic environment, driven out of equilibrium by motor activity. Transverse bending fluctuations of the probe filaments can be decomposed into dynamic normal modes. We find that these modes no longer evolve independently under nonequilibrium driving. This effective mode coupling results in nonzero circulatory currents in a conformational phase space, reflecting a violation of detailed balance. We present predictions for the characteristic frequencies associated with these currents and investigate how the temporal signatures of motor activity determine mode correlations, which we find to be consistent with recent experiments on microtubules embedded in cytoskeletal networks.
Default Mode and Executive Networks Areas: Association with the Serial Order in Divergent Thinking

PubMed Central

Heinonen, Jarmo; Numminen, Jussi; Hlushchuk, Yevhen; Antell, Henrik; Taatila, Vesa; Suomala, Jyrki

2016-01-01

Scientific findings have suggested a two-fold structure of the cognitive process. By using the heuristic thinking mode, people automatically process information that tends to be invariant across days, whereas by using the explicit thinking mode people explicitly process information that tends to be variant compared to typical previously learned information patterns. Previous studies on creativity found an association between creativity and the brain regions in the prefrontal cortex, the anterior cingulate cortex, the default mode network and the executive network. However, which neural networks contribute to the explicit mode of thinking during idea generation remains an open question. We employed an fMRI paradigm to examine which brain regions were activated when participants (n = 16) mentally generated alternative uses for everyday objects. Most previous creativity studies required participants to verbalize responses during idea generation, whereas in this study participants produced mental alternatives without verbalizing. This study found activation in the left anterior insula when contrasting idea generation and object identification. This finding suggests that the insula (part of the brain’s salience network) plays a role in facilitating both the central executive and default mode networks to activate idea generation. We also investigated closely the effect of the serial order of idea being generated on brain responses: The amplitude of fMRI responses correlated positively with the serial order of idea being generated in the anterior cingulate cortex, which is part of the central executive network. Positive correlation with the serial order was also observed in the regions typically assigned to the default mode network: the precuneus/cuneus, inferior parietal lobule and posterior cingulate cortex. These networks support the explicit mode of thinking and help the individual to convert conventional mental models to new ones. The serial order correlated negatively with the BOLD responses in the posterior presupplementary motor area, left premotor cortex, right cerebellum and left inferior frontal gyrus. This finding might imply that idea generation without a verbal processing demand reflecting lack of need for new object identification in idea generation events. The results of the study are consistent with recent creativity studies, which emphasize that the creativity process involves working memory capacity to spontaneously shift between different kinds of thinking modes according to the context. PMID:27627760

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

ERIC Educational Resources Information Center

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.…
Dendritic Slow Dynamics Enables Localized Cortical Activity to Switch between Mobile and Immobile Modes with Noisy Background Input

PubMed Central

Kurashige, Hiroki; Câteau, Hideyuki

2011-01-01

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. PMID:21931635
Salience and Default Mode Network Coupling Predicts Cognition in Aging and Parkinson's Disease.

PubMed

Putcha, Deepti; Ross, Robert S; Cronin-Golomb, Alice; Janes, Amy C; Stern, Chantal E

2016-02-01

Cognitive impairment is common in Parkinson's disease (PD). Three neurocognitive networks support efficient cognition: the salience network, the default mode network, and the central executive network. The salience network is thought to switch between activating and deactivating the default mode and central executive networks. Anti-correlated interactions between the salience and default mode networks in particular are necessary for efficient cognition. Our previous work demonstrated altered functional coupling between the neurocognitive networks in non-demented individuals with PD compared to age-matched control participants. Here, we aim to identify associations between cognition and functional coupling between these neurocognitive networks in the same group of participants. We investigated the extent to which intrinsic functional coupling among these neurocognitive networks is related to cognitive performance across three neuropsychological domains: executive functioning, psychomotor speed, and verbal memory. Twenty-four non-demented individuals with mild to moderate PD and 20 control participants were scanned at rest and evaluated on three neuropsychological domains. PD participants were impaired on tests from all three domains compared to control participants. Our imaging results demonstrated that successful cognition across healthy aging and Parkinson's disease participants was related to anti-correlated coupling between the salience and default mode networks. Individuals with poorer performance scores across groups demonstrated more positive salience network/default-mode network coupling. Successful cognition relies on healthy coupling between the salience and default mode networks, which may become dysfunctional in PD. These results can help inform non-pharmacological interventions (repetitive transcranial magnetic stimulation) targeting these specific networks before they become vulnerable in early stages of Parkinson's disease.
REAL TIME CONTROL OF URBAN DRAINAGE NETWORKS

EPA Science Inventory

Real-time control (RTC) is a custom-designed, computer-assisted management technology for a specific sewerage network to meet the operational objectives of its collection/conveyance system. RTC can operate in several modes, including a mode that is activated during a wet weather ...
Temporal lobe and "default" hemodynamic brain modes discriminate between schizophrenia and bipolar disorder.

PubMed

Calhoun, Vince D; Maciejewski, Paul K; Pearlson, Godfrey D; Kiehl, Kent A

2008-11-01

Schizophrenia and bipolar disorder are currently diagnosed on the basis of psychiatric symptoms and longitudinal course. The determination of a reliable, biologically-based diagnostic indicator of these diseases (a biomarker) could provide the groundwork for developing more rigorous tools for differential diagnosis and treatment assignment. Recently, methods have been used to identify distinct sets of brain regions or "spatial modes" exhibiting temporally coherent brain activity. Using functional magnetic resonance imaging (fMRI) data and a multivariate analysis method, independent component analysis, we combined the temporal lobe and the default modes to discriminate subjects with bipolar disorder, chronic schizophrenia, and healthy controls. Temporal lobe and default mode networks were reliably identified in all participants. Classification results on an independent set of individuals revealed an average sensitivity and specificity of 90 and 95%, respectively. The use of coherent brain networks such as the temporal lobe and default mode networks may provide a more reliable measure of disease state than task-correlated fMRI activity. A combination of two such hemodynamic brain networks shows promise as a biomarker for schizophrenia and bipolar disorder.
YANA – a software tool for analyzing flux modes, gene-expression and enzyme activities

PubMed Central

Schwarz, Roland; Musch, Patrick; von Kamp, Axel; Engels, Bernd; Schirmer, Heiner; Schuster, Stefan; Dandekar, Thomas

2005-01-01

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 . 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-friendly software for such efforts. PMID:15929789
Neural network-based sliding mode control for atmospheric-actuated spacecraft formation using switching strategy

NASA Astrophysics Data System (ADS)

Sun, Ran; Wang, Jihe; Zhang, Dexin; Shao, Xiaowei

2018-02-01

This paper presents an adaptive neural networks-based control method for spacecraft formation with coupled translational and rotational dynamics using only aerodynamic forces. It is assumed that each spacecraft is equipped with several large flat plates. A coupled orbit-attitude dynamic model is considered based on the specific configuration of atmospheric-based actuators. For this model, a neural network-based adaptive sliding mode controller is implemented, accounting for system uncertainties and external perturbations. To avoid invalidation of the neural networks destroying stability of the system, a switching control strategy is proposed which combines an adaptive neural networks controller dominating in its active region and an adaptive sliding mode controller outside the neural active region. An optimal process is developed to determine the control commands for the plates system. The stability of the closed-loop system is proved by a Lyapunov-based method. Comparative results through numerical simulations illustrate the effectiveness of executing attitude control while maintaining the relative motion, and higher control accuracy can be achieved by using the proposed neural-based switching control scheme than using only adaptive sliding mode controller.
Tunable deformation modes shape contractility in active biopolymer networks

NASA Astrophysics Data System (ADS)

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

PubMed

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.
Modulation of steady state functional connectivity in the default mode and working memory networks by cognitive load.

PubMed

Newton, Allen T; Morgan, Victoria L; Rogers, Baxter P; Gore, John C

2011-10-01

Interregional correlations between blood oxygen level dependent (BOLD) magnetic resonance imaging (fMRI) signals in the resting state have been interpreted as measures of connectivity across the brain. Here we investigate whether such connectivity in the working memory and default mode networks is modulated by changes in cognitive load. Functional connectivity was measured in a steady-state verbal identity N-back task for three different conditions (N = 1, 2, and 3) as well as in the resting state. We found that as cognitive load increases, the functional connectivity within both the working memory the default mode network increases. To test whether functional connectivity between the working memory and the default mode networks changed, we constructed maps of functional connectivity to the working memory network as a whole and found that increasingly negative correlations emerged in a dorsal region of the posterior cingulate cortex. These results provide further evidence that low frequency fluctuations in BOLD signals reflect variations in neural activity and suggests interaction between the default mode network and other cognitive networks. Copyright © 2010 Wiley-Liss, Inc.
A multilevel path analysis of contact frequency between social network members

NASA Astrophysics Data System (ADS)

van den Berg, Pauline; Arentze, Theo; Timmermans, Harry

2012-04-01

Recently, there has been an increasing interest in the role of social networks in spatial-choice and travel behavior. It has been acknowledged that social activities and the travel for these activities can emerge from individuals' social networks and that social activities are responsible for an important portion of travel demand. The influence of information and communication technologies (ICT's) is also important in this respect. The purpose of the paper is to examine the effects of characteristics of egos and ego-alter relationships on the frequency of social interaction by different communication modes, using multilevel path analysis. The analyses are based on social network data collected in 2008 in the Eindhoven region in the Netherlands among 116 respondents. The results indicate a complementary relationship between contact frequencies by different modes. The contact frequencies of the different modes, especially face-to-face and telephone, can also be largely explained by the ego's personal characteristics and the type of relationship and the distance between ego and alter.
Nonequilibrium dynamics of probe filaments in actin-myosin networks

NASA Astrophysics Data System (ADS)

Gladrow, J.; Broedersz, C. P.; Schmidt, C. F.

2017-08-01

Active dynamic processes of cells are largely driven by the cytoskeleton, a complex and adaptable semiflexible polymer network, motorized by mechanoenzymes. Small dimensions, confined geometries, and hierarchical structures make it challenging to probe dynamics and mechanical response of such networks. Embedded semiflexible probe polymers can serve as nonperturbing multiscale probes to detect force distributions in active polymer networks. We show here that motor-induced forces transmitted to the probe polymers are reflected in nonequilibrium bending dynamics, which we analyze in terms of spatial eigenmodes of an elastic beam under steady-state conditions. We demonstrate how these active forces induce correlations among the mode amplitudes, which furthermore break time-reversal symmetry. This leads to a breaking of detailed balance in this mode space. We derive analytical predictions for the magnitude of resulting probability currents in mode space in the white-noise limit of motor activity. We relate the structure of these currents to the spatial profile of motor-induced forces along the probe polymers and provide a general relation for observable currents on two-dimensional hyperplanes.
Developmental process emerges from extended brain-body-behavior networks

PubMed Central

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

ERIC Educational Resources Information Center

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…
The default mode network and the working memory network are not anti-correlated during all phases of a working memory task.

PubMed

Piccoli, Tommaso; Valente, Giancarlo; Linden, David E J; Re, Marta; Esposito, Fabrizio; Sack, Alexander T; Di Salle, Francesco

2015-01-01

The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time. To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks. We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between "task-positive" and "task-negative" brain networks. Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network.
The Default Mode Network and the Working Memory Network Are Not Anti-Correlated during All Phases of a Working Memory Task

PubMed Central

Piccoli, Tommaso; Valente, Giancarlo; Linden, David E. J.; Re, Marta; Esposito, Fabrizio; Sack, Alexander T.; Salle, Francesco Di

2015-01-01

Introduction The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time. Methods To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks. Results We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between “task-positive” and “task-negative” brain networks. Conclusions Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network. PMID:25848951
Long-range synchrony and emergence of neural reentry

NASA Astrophysics Data System (ADS)

Keren, Hanna; Marom, Shimon

2016-11-01

Neural synchronization across long distances is a functionally important phenomenon in health and disease. In order to access the basis of different modes of long-range synchrony, we monitor spiking activities over centimetre scale in cortical networks and show that the mode of synchrony depends upon a length scale, λ, which is the minimal path that activity should propagate through to find its point of origin ready for reactivation. When λ is larger than the physical dimension of the network, distant neuronal populations operate synchronously, giving rise to irregularly occurring network-wide events that last hundreds of milliseconds to several seconds. In contrast, when λ approaches the dimension of the network, a continuous self-sustained reentry propagation emerges, a regular seizure-like mode that is marked by precise spatiotemporal patterns (‘synfire chains’) and may last many minutes. Termination of a reentry phase is preceded by a decrease of propagation speed to a halt. Stimulation decreases both propagation speed and λ values, which modifies the synchrony mode respectively. The results contribute to the understanding of the origin and termination of different modes of neural synchrony as well as their long-range spatial patterns, while hopefully catering to manipulation of the phenomena in pathological conditions.
DELTAMETHRIN AND ESFENVALERATE INHIBIT SPONTANEOUS NETWORK ACTIVITY IN RAT CORTICAL NEURONS IN VITRO.

EPA Science Inventory

Understanding pyrethroid actions on neuronal networks will help to establish a mode of action for these compounds, which is needed for cumulative risk decisions under the Food Quality Protection Act of 1996. However, pyrethroid effects on spontaneous activity in networks of inter...
Acupuncture mobilizes the brain's default mode and its anti-correlated network in healthy subjects.

PubMed

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.
GABA-A receptor antagonists increase firing, bursting and synchrony of spontaneous activity in neuronal networks grown on microelectrode arrays: a step towards chemical "fingerprinting"

EPA Science Inventory

Assessment of effects on spontaneous network activity in neurons grown on MEAs is a proposed method to screen chemicals for potential neurotoxicity. In addition, differential effects on network activity (chemical "fingerprints") could be used to classify chemical modes of action....

Temporal Lobe and “Default” Hemodynamic Brain Modes Discriminate Between Schizophrenia and Bipolar Disorder

PubMed Central

Calhoun, Vince D.; Maciejewski, Paul K.; Pearlson, Godfrey D.; Kiehl, Kent A.

2009-01-01

Schizophrenia and bipolar disorder are currently diagnosed on the basis of psychiatric symptoms and longitudinal course. The determination of a reliable, biologically-based diagnostic indicator of these diseases (a biomarker) could provide the groundwork for developing more rigorous tools for differential diagnosis and treatment assignment. Recently, methods have been used to identify distinct sets of brain regions or “spatial modes” exhibiting temporally coherent brain activity. Using functional magnetic resonance imaging (fMRI) data and a multivariate analysis method, independent component analysis, we combined the temporal lobe and the default modes to discriminate subjects with bipolar disorder, chronic schizophrenia, and healthy controls. Temporal lobe and default mode networks were reliably identified in all participants. Classification results on an independent set of individuals revealed an average sensitivity and specificity of 90 and 95%, respectively. The use of coherent brain networks such as the temporal lobe and default mode networks may provide a more reliable measure of disease state than task-correlated fMRI activity. A combination of two such hemodynamic brain networks shows promise as a biomarker for schizophrenia and bipolar disorder. PMID:17894392
Aging-related changes in the default mode network and its anti-correlated networks: a resting-state fMRI study.

PubMed

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.
Best facilitated cortical activation during different stepping, treadmill, and robot-assisted walking training paradigms and speeds: A functional near-infrared spectroscopy neuroimaging study.

PubMed

Kim, Ha Yeon; Yang, Sung Phil; Park, Gyu Lee; Kim, Eun Joo; You, Joshua Sung Hyun

2016-01-01

Robot-assisted and treadmill-gait training are promising neurorehabilitation techniques, with advantages over conventional gait training, but the neural substrates underpinning locomotor control remain unknown particularly during different gait training modes and speeds. The present optical imaging study compared cortical activities during conventional stepping walking (SW), treadmill walking (TW), and robot-assisted walking (RW) at different speeds. Fourteen healthy subjects (6 women, mean age 30.06, years ± 4.53) completed three walking training modes (SW, TW, and RW) at various speeds (self-selected, 1.5, 2.0, 2.5, and 3.0 km/h). A functional near-infrared spectroscopy (fNIRS) system determined cerebral hemodynamic changes associated with cortical locomotor network areas in the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), prefrontal cortex (PFC), and sensory association cortex (SAC). There was increased cortical activation in the SMC, PMC, and SMA during different walking training modes. More global locomotor network activation was observed during RW than TW or SW. As walking speed increased, multiple locomotor network activations were observed, and increased activation power spectrum. This is the first empirical evidence highlighting the neural substrates mediating dynamic locomotion for different gait training modes and speeds. Fast, robot-assisted gait training best facilitated cortical activation associated with locomotor control.
On the relationship between the “default mode network” and the “social brain”

PubMed Central

Mars, Rogier B.; Neubert, Franz-Xaver; Noonan, MaryAnn P.; Sallet, Jerome; Toni, Ivan; Rushworth, Matthew F. S.

2012-01-01

The default mode network (DMN) of the brain consists of areas that are typically more active during rest than during active task performance. Recently however, this network has been shown to be activated by certain types of tasks. Social cognition, particularly higher-order tasks such as attributing mental states to others, has been suggested to activate a network of areas at least partly overlapping with the DMN. Here, we explore this claim, drawing on evidence from meta-analyses of functional MRI data and recent studies investigating the structural and functional connectivity of the social brain. In addition, we discuss recent evidence for the existence of a DMN in non-human primates. We conclude by discussing some of the implications of these observations. PMID:22737119
CE dual-homing protection in layer 1 VPN

NASA Astrophysics Data System (ADS)

Du, Shu; Peng, Yunfeng; Long, Keping

2008-11-01

Layer 1 VPN (L1VPN) extends the notion of VPN to the optical domain to provide virtually dedicated circuit like leased lines, so that the security is more enhanced. Despite their secure gains from channel isolation, VPNs still suffer fragilities resulting from link-failures or node-failures. Extensive activities on survivability designs for wavelength-routed optical networks are proposed, including various protection and restoration schemes, but concerns on network edge are rare. Dual-homing is an effective skill to achieve survivability gains for L1VPNs. There are two dual-homing mode: Active/Standby mode and Load-Sharing mode In this paper, we investigate the problem of PE assignment, which is the key of dual-homing design and is NP-hard. We formulate it as an integer programming problem, and propose heuristic solutions. Simulation results show that the proposed solutions work in a correct and effective way and the Load-Sharing mode has higher bandwidth efficiency than Active/Standby mode.
The Causal Inference of Cortical Neural Networks during Music Improvisations

PubMed Central

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.

PubMed

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.
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.

PubMed

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.
Spontaneous attentional fluctuations in impaired states and pathological conditions: a neurobiological hypothesis.

PubMed

Sonuga-Barke, Edmund J S; Castellanos, F Xavier

2007-01-01

In traditional accounts, fluctuations in sustained and focused attention and associated attentional lapses during task performance are regarded as the result of failures of top-down and effortful higher order processes. The current paper reviews an alternative hypothesis: that spontaneous patterns of very low frequency (<0.1 Hz) coherence within a specific brain network ('default-mode network') thought to support a pattern of generalized task-non-specific cognition during rest, can persist or intrude into periods of active task-specific processing, producing periodic fluctuations in attention that compete with goal-directed activity. We review recent studies supporting the existence of the resting state default network, examine the mechanism underpinning it, describe the consequent temporally distinctive effects on cognition and behaviour of default-mode interference into active processing periods, and suggest some factors that might predispose to it. Finally, we explore the putative role of default-mode interference as a cause of performance variability in attention deficit/hyperactivity disorder.
Reduced salience and default mode network activity in women with anorexia nervosa

PubMed Central

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 food. The alterations in the DMN and SMN observed only in women with anorexia nervosa suggest state-dependent abnormalities that could be related to altered interoception and body image in these women when they are underweight but that remit following recovery. PMID:24280181
Energy-Efficient Next-Generation Passive Optical Networks Based on Sleep Mode and Heuristic Optimization

NASA Astrophysics Data System (ADS)

Zulai, Luis G. T.; Durand, Fábio R.; Abrão, Taufik

2015-05-01

In this article, an energy-efficiency mechanism for next-generation passive optical networks is investigated through heuristic particle swarm optimization. Ten-gigabit Ethernet-wavelength division multiplexing optical code division multiplexing-passive optical network next-generation passive optical networks are based on the use of a legacy 10-gigabit Ethernet-passive optical network with the advantage of using only an en/decoder pair of optical code division multiplexing technology, thus eliminating the en/decoder at each optical network unit. The proposed joint mechanism is based on the sleep-mode power-saving scheme for a 10-gigabit Ethernet-passive optical network, combined with a power control procedure aiming to adjust the transmitted power of the active optical network units while maximizing the overall energy-efficiency network. The particle swarm optimization based power control algorithm establishes the optimal transmitted power in each optical network unit according to the network pre-defined quality of service requirements. The objective is controlling the power consumption of the optical network unit according to the traffic demand by adjusting its transmitter power in an attempt to maximize the number of transmitted bits with minimum energy consumption, achieving maximal system energy efficiency. Numerical results have revealed that it is possible to save 75% of energy consumption with the proposed particle swarm optimization based sleep-mode energy-efficiency mechanism compared to 55% energy savings when just a sleeping-mode-based mechanism is deployed.
Analog neural network control method proposed for use in a backup satellite control mode

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

Frigo, J.R.; Tilden, M.W.

1998-03-01

The authors propose to use an analog neural network controller implemented in hardware, independent of the active control system, for use in a satellite backup control mode. The controller uses coarse sun sensor inputs. The field of view of the sensors activate the neural controller, creating an analog dead band with respect to the direction of the sun on each axis. This network controls the orientation of the vehicle toward the sunlight to ensure adequate power for the system. The attitude of the spacecraft is stabilized with respect to the ambient magnetic field on orbit. This paper develops a modelmore » of the controller using real-time coarse sun sensor data and a dynamic model of a prototype system based on a satellite system. The simulation results and the feasibility of this control method for use in a satellite backup control mode are discussed.« less
fMRI reveals reciprocal inhibition between social and physical cognitive domains

PubMed Central

Jack, Anthony I.; Dawson, Abigail; Begany, Katelyn; Leckie, Regina L.; Barry, Kevin; Ciccia, Angela; Snyder, Abraham

2012-01-01

Two lines of evidence indicate that there exists a reciprocal inhibitory relationship between opposed brain networks. First, most attention-demanding cognitive tasks activate a stereotypical set of brain areas, known as the task-positive network and simultaneously deactivate a different set of brain regions, commonly referred to as the task negative or default mode network. Second, functional connectivity analyses show that these same opposed networks are anti-correlated in the resting state. We hypothesize that these reciprocally inhibitory effects reflect two incompatible cognitive modes, each of which is directed towards understanding the external world. Thus, engaging one mode activates one set of regions and suppresses activity in the other. We test this hypothesis by identifying two types of problem-solving task which, on the basis of prior work, have been consistently associated with the task positive and task negative regions: tasks requiring social cognition, i.e., reasoning about the mental states of other persons, and tasks requiring physical cognition, i.e., reasoning about the causal/mechanical properties of inanimate objects. Social and mechanical reasoning tasks were presented to neurologically normal participants during fMRI. Each task type was presented using both text and video clips. Regardless of presentation modality, we observed clear evidence of reciprocal suppression: social tasks deactivated regions associated with mechanical reasoning and mechanical tasks deactivated regions associated with social reasoning. These findings are not explained by self-referential processes, task engagement, mental simulation, mental time travel or external vs. internal attention, all factors previously hypothesized to explain default mode network activity. Analyses of resting state data revealed a close match between the regions our tasks identified as reciprocally inhibitory and regions of maximal anti-correlation in the resting state. These results indicate the reciprocal inhibition is not attributable to constraints inherent in the tasks, but is neural in origin. Hence, there is a physiological constraint on our ability to simultaneously engage two distinct cognitive modes. Further work is needed to more precisely characterize these opposing cognitive domains. PMID:23110882
Working memory activation of neural networks in the elderly as a function of information processing phase and task complexity.

PubMed

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.
On-line, adaptive state estimator for active noise control

NASA Technical Reports Server (NTRS)

Lim, Tae W.

1994-01-01

Dynamic characteristics of airframe structures are expected to vary as aircraft flight conditions change. Accurate knowledge of the changing dynamic characteristics is crucial to enhancing the performance of the active noise control system using feedback control. This research investigates the development of an adaptive, on-line state estimator using a neural network concept to conduct active noise control. In this research, an algorithm has been developed that can be used to estimate displacement and velocity responses at any locations on the structure from a limited number of acceleration measurements and input force information. The algorithm employs band-pass filters to extract from the measurement signal the frequency contents corresponding to a desired mode. The filtered signal is then used to train a neural network which consists of a linear neuron with three weights. The structure of the neural network is designed as simple as possible to increase the sampling frequency as much as possible. The weights obtained through neural network training are then used to construct the transfer function of a mode in z-domain and to identify modal properties of each mode. By using the identified transfer function and interpolating the mode shape obtained at sensor locations, the displacement and velocity responses are estimated with reasonable accuracy at any locations on the structure. The accuracy of the response estimates depends on the number of modes incorporated in the estimates and the number of sensors employed to conduct mode shape interpolation. Computer simulation demonstrates that the algorithm is capable of adapting to the varying dynamic characteristics of structural properties. Experimental implementation of the algorithm on a DSP (digital signal processing) board for a plate structure is underway. The algorithm is expected to reach the sampling frequency range of about 10 kHz to 20 kHz which needs to be maintained for a typical active noise control application.
Closed-loop control of a fragile network: application to seizure-like dynamics of an epilepsy model

PubMed Central

Ehrens, Daniel; Sritharan, Duluxan; Sarma, Sridevi V.

2015-01-01

It has recently been proposed that the epileptic cortex is fragile in the sense that seizures manifest through small perturbations in the synaptic connections that render the entire cortical network unstable. Closed-loop therapy could therefore entail detecting when the network goes unstable, and then stimulating with an exogenous current to stabilize the network. In this study, a non-linear stochastic model of a neuronal network was used to simulate both seizure and non-seizure activity. In particular, synaptic weights between neurons were chosen such that the network's fixed point is stable during non-seizure periods, and a subset of these connections (the most fragile) were perturbed to make the same fixed point unstable to model seizure events; and, the model randomly transitions between these two modes. The goal of this study was to measure spike train observations from this epileptic network and then apply a feedback controller that (i) detects when the network goes unstable, and then (ii) applies a state-feedback gain control input to the network to stabilize it. The stability detector is based on a 2-state (stable, unstable) hidden Markov model (HMM) of the network, and detects the transition from the stable mode to the unstable mode from using the firing rate of the most fragile node in the network (which is the output of the HMM). When the unstable mode is detected, a state-feedback gain is applied to generate a control input to the fragile node bringing the network back to the stable mode. Finally, when the network is detected as stable again, the feedback control input is switched off. High performance was achieved for the stability detector, and feedback control suppressed seizures within 2 s after onset. PMID:25784851
Allocation of spectral and spatial modes in multidimensional metro-access optical networks

NASA Astrophysics Data System (ADS)

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.
Abnormal brain activation in neurofibromatosis type 1: a link between visual processing and the default mode network.

PubMed

Violante, Inês R; Ribeiro, Maria J; Cunha, Gil; Bernardino, Inês; Duarte, João V; Ramos, Fabiana; Saraiva, Jorge; Silva, Eduardo; Castelo-Branco, Miguel

2012-01-01

Neurofibromatosis type 1 (NF1) is one of the most common single gene disorders affecting the human nervous system with a high incidence of cognitive deficits, particularly visuospatial. Nevertheless, neurophysiological alterations in low-level visual processing that could be relevant to explain the cognitive phenotype are poorly understood. Here we used functional magnetic resonance imaging (fMRI) to study early cortical visual pathways in children and adults with NF1. We employed two distinct stimulus types differing in contrast and spatial and temporal frequencies to evoke relatively different activation of the magnocellular (M) and parvocellular (P) pathways. Hemodynamic responses were investigated in retinotopically-defined regions V1, V2 and V3 and then over the acquired cortical volume. Relative to matched control subjects, patients with NF1 showed deficient activation of the low-level visual cortex to both stimulus types. Importantly, this finding was observed for children and adults with NF1, indicating that low-level visual processing deficits do not ameliorate with age. Moreover, only during M-biased stimulation patients with NF1 failed to deactivate or even activated anterior and posterior midline regions of the default mode network. The observation that the magnocellular visual pathway is impaired in NF1 in early visual processing and is specifically associated with a deficient deactivation of the default mode network may provide a neural explanation for high-order cognitive deficits present in NF1, particularly visuospatial and attentional. A link between magnocellular and default mode network processing may generalize to neuropsychiatric disorders where such deficits have been separately identified.
Interactions of the Salience Network and Its Subsystems with the Default-Mode and the Central-Executive Networks in Normal Aging and Mild Cognitive Impairment.

PubMed

Chand, Ganesh B; Wu, Junjie; Hajjar, Ihab; Qiu, Deqiang

2017-09-01

Previous functional magnetic resonance imaging (fMRI) investigations suggest that the intrinsically organized large-scale networks and the interaction between them might be crucial for cognitive activities. A triple network model, which consists of the default-mode network, salience network, and central-executive network, has been recently used to understand the connectivity patterns of the cognitively normal brains versus the brains with disorders. This model suggests that the salience network dynamically controls the default-mode and central-executive networks in healthy young individuals. However, the patterns of interactions have remained largely unknown in healthy aging or those with cognitive decline. In this study, we assess the patterns of interactions between the three networks using dynamical causal modeling in resting state fMRI data and compare them between subjects with normal cognition and mild cognitive impairment (MCI). In healthy elderly subjects, our analysis showed that the salience network, especially its dorsal subnetwork, modulates the interaction between the default-mode network and the central-executive network (Mann-Whitney U test; p < 0.05), which was consistent with the pattern of interaction reported in young adults. In contrast, this pattern of modulation by salience network was disrupted in MCI (p < 0.05). Furthermore, the degree of disruption in salience network control correlated significantly with lower overall cognitive performance measured by Montreal Cognitive Assessment (r = 0.295; p < 0.05). This study suggests that a disruption of the salience network control, especially the dorsal salience network, over other networks provides a neuronal basis for cognitive decline and may be a candidate neuroimaging biomarker of cognitive impairment.
An energy saving mechanism of EPON networks for real time video transmission

NASA Astrophysics Data System (ADS)

Liu, Chien-Ping; Wu, Ho-Ting; Chiang, Yun-Ting; Chien, Shieh-Chieh; Ke, Kai-Wei

2015-07-01

Modern access networks are constructed widely by passive optical networks (PONs) to meet the growing bandwidth demand. However, higher bandwidth means more energy consumption. To save energy, a few research works propose the dual-mode energy saving mechanism that allows the ONU to operate between active and sleep modes periodically. However, such dual-mode energy saving design may induce unnecessary power consumption or packet delay increase in the case where only downstream data exist for most of the time. In this paper, we propose a new tri-mode energy saving scheme for Ethernet PON (EPON). The new tri-mode energy saving design, combining the dual-mode saving mechanism with the doze mode, allows the ONU to switch among these three modes alternatively. In the doze mode, the ONU may receive downstream data while keeping its transmitter close. Such scenario is often observed for real time video downstream transmission. Furthermore, the low packet delay of high priority upstream data can be attained through the use of early wake-up mechanism employed in both energy saving modes. The energy saving and system efficiency can thus be achieved jointly while maintaining the differentiated QoS for data with various priorities. Performance results via simulation have demonstrated the effectiveness of such mechanism.

Network dysfunction predicts speech production after left hemisphere stroke.

PubMed

Geranmayeh, Fatemeh; Leech, Robert; Wise, Richard J S

2016-03-09

To investigate the role of multiple distributed brain networks, including the default mode, fronto-temporo-parietal, and cingulo-opercular networks, which mediate domain-general and task-specific processes during speech production after aphasic stroke. We conducted an observational functional MRI study to investigate the effects of a previous left hemisphere stroke on functional connectivity within and between distributed networks as patients described pictures. Study design included various baseline tasks, and we compared results to those of age-matched healthy participants performing the same tasks. We used independent component and psychophysiological interaction analyses. Although activity within individual networks was not predictive of speech production, relative activity between networks was a predictor of both within-scanner and out-of-scanner language performance, over and above that predicted from lesion volume, age, sex, and years of education. Specifically, robust functional imaging predictors were the differential activity between the default mode network and both the left and right fronto-temporo-parietal networks, respectively activated and deactivated during speech. We also observed altered between-network functional connectivity of these networks in patients during speech production. Speech production is dependent on complex interactions among widely distributed brain networks, indicating that residual speech production after stroke depends on more than the restoration of local domain-specific functions. Our understanding of the recovery of function following focal lesions is not adequately captured by consideration of ipsilesional or contralesional brain regions taking over lost domain-specific functions, but is perhaps best considered as the interaction between what remains of domain-specific networks and domain-general systems that regulate behavior. © 2016 American Academy of Neurology.
Network dysfunction predicts speech production after left hemisphere stroke

PubMed Central

Leech, Robert; Wise, Richard J.S.

2016-01-01

Objective: To investigate the role of multiple distributed brain networks, including the default mode, fronto-temporo-parietal, and cingulo-opercular networks, which mediate domain-general and task-specific processes during speech production after aphasic stroke. Methods: We conducted an observational functional MRI study to investigate the effects of a previous left hemisphere stroke on functional connectivity within and between distributed networks as patients described pictures. Study design included various baseline tasks, and we compared results to those of age-matched healthy participants performing the same tasks. We used independent component and psychophysiological interaction analyses. Results: Although activity within individual networks was not predictive of speech production, relative activity between networks was a predictor of both within-scanner and out-of-scanner language performance, over and above that predicted from lesion volume, age, sex, and years of education. Specifically, robust functional imaging predictors were the differential activity between the default mode network and both the left and right fronto-temporo-parietal networks, respectively activated and deactivated during speech. We also observed altered between-network functional connectivity of these networks in patients during speech production. Conclusions: Speech production is dependent on complex interactions among widely distributed brain networks, indicating that residual speech production after stroke depends on more than the restoration of local domain-specific functions. Our understanding of the recovery of function following focal lesions is not adequately captured by consideration of ipsilesional or contralesional brain regions taking over lost domain-specific functions, but is perhaps best considered as the interaction between what remains of domain-specific networks and domain-general systems that regulate behavior. PMID:26962070
Acupuncture, the limbic system, and the anticorrelated networks of the brain.

PubMed

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's disease. Published by Elsevier B.V.
Dynamics of brain networks in the aesthetic appreciation

PubMed Central

Cela-Conde, Camilo J.; García-Prieto, Juan; Ramasco, José J.; Mirasso, Claudio R.; Bajo, Ricardo; Munar, Enric; Flexas, Albert; del-Pozo, Francisco; Maestú, Fernando

2013-01-01

Neuroimage experiments have been essential for identifying active brain networks. During cognitive tasks as in, e.g., aesthetic appreciation, such networks include regions that belong to the default mode network (DMN). Theoretically, DMN activity should be interrupted during cognitive tasks demanding attention, as is the case for aesthetic appreciation. Analyzing the functional connectivity dynamics along three temporal windows and two conditions, beautiful and not beautiful stimuli, here we report experimental support for the hypothesis that aesthetic appreciation relies on the activation of two different networks, an initial aesthetic network and a delayed aesthetic network, engaged within distinct time frames. Activation of the DMN might correspond mainly to the delayed aesthetic network. We discuss adaptive and evolutionary explanations for the relationships existing between the DMN and aesthetic networks and offer unique inputs to debates on the mind/brain interaction. PMID:23754437
Did BICEP2 see vector modes? First B-mode constraints on cosmic defects.

PubMed

Moss, Adam; Pogosian, Levon

2014-05-02

Scaling networks of cosmic defects, such as strings and textures, actively generate scalar, vector, and tensor metric perturbations throughout the history of the Universe. In particular, vector modes sourced by defects are an efficient source of the cosmic microwave background B-mode polarization. We use the recently released BICEP2 and POLARBEAR B-mode polarization spectra to constrain properties of a wide range of different types of cosmic strings networks. We find that in order for strings to provide a satisfactory fit on their own, the effective interstring distance needs to be extremely large--spectra that fit the data best are more representative of global strings and textures. When a local string contribution is considered together with the inflationary B-mode spectrum, the fit is improved. We discuss implications of these results for theories that predict cosmic defects.
Star-coupled Hindmarsh-Rose neural network with chemical synapses

NASA Astrophysics Data System (ADS)

Usha, K.; Subha, P. A.

We analyze the patterns like synchrony, desynchrony, and Drum head mode in a network of Hindmarsh-Rose (HR) neurons interacting via chemical synapse in unidirectional and bidirectional star topology. A two-coupled system has been studied for synchronization by varying the coupling strength and the parameter describing the activation and inactivation of the fast ion channel. The transverse Lyapunov exponent spectrum is plotted to observe the point of transition from desynchrony to synchrony. The synchronized, desynchronized, and drum head mode regions are observed when the neurons are connected in unidirectional and bidirectional coupling configurations. A detailed analysis about the time evolution of membrane potential corresponding to each region is presented. The annihilation of synchronized region and the expansion of drum head mode region in bidirectional coupling is discussed using parameter space. Our work provides finer insight into the existence and stability of Drum head mode and is useful for designing communication networks.
Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics.

PubMed

Atasoy, Selen; Deco, Gustavo; Kringelbach, Morten L; Pearson, Joel

2018-06-01

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at "rest." Here, we introduce the concept of harmonic brain modes-fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.
Real-time identification of vehicle motion-modes using neural networks

NASA Astrophysics Data System (ADS)

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.
Analysis of optimal phenotypic space using elementary modes as applied to Corynebacterium glutamicum

PubMed Central

Gayen, Kalyan; Venkatesh, KV

2006-01-01

Background Quantification of the metabolic network of an organism offers insights into possible ways of developing mutant strain for better productivity of an extracellular metabolite. The first step in this quantification is the enumeration of stoichiometries of all reactions occurring in a metabolic network. The structural details of the network in combination with experimentally observed accumulation rates of external metabolites can yield flux distribution at steady state. One such methodology for quantification is the use of elementary modes, which are minimal set of enzymes connecting external metabolites. Here, we have used a linear objective function subject to elementary modes as constraint to determine the fluxes in the metabolic network of Corynebacterium glutamicum. The feasible phenotypic space was evaluated at various combinations of oxygen and ammonia uptake rates. Results Quantification of the fluxes of the elementary modes in the metabolism of C. glutamicum was formulated as linear programming. The analysis demonstrated that the solution was dependent on the criteria of objective function when less than four accumulation rates of the external metabolites were considered. The analysis yielded feasible ranges of fluxes of elementary modes that satisfy the experimental accumulation rates. In C. glutamicum, the elementary modes relating to biomass synthesis through glycolysis and TCA cycle were predominantly operational in the initial growth phase. At a later time, the elementary modes contributing to lysine synthesis became active. The oxygen and ammonia uptake rates were shown to be bounded in the phenotypic space due to the stoichiometric constraint of the elementary modes. Conclusion We have demonstrated the use of elementary modes and the linear programming to quantify a metabolic network. We have used the methodology to quantify the network of C. glutamicum, which evaluates the set of operational elementary modes at different phases of fermentation. The methodology was also used to determine the feasible solution space for a given set of substrate uptake rates under specific optimization criteria. Such an approach can be used to determine the optimality of the accumulation rates of any metabolite in a given network. PMID:17038164
fMRI reveals reciprocal inhibition between social and physical cognitive domains.

PubMed

Jack, Anthony I; Dawson, Abigail J; Begany, Katelyn L; Leckie, Regina L; Barry, Kevin P; Ciccia, Angela H; Snyder, Abraham Z

2013-02-01

Two lines of evidence indicate that there exists a reciprocal inhibitory relationship between opposed brain networks. First, most attention-demanding cognitive tasks activate a stereotypical set of brain areas, known as the task-positive network and simultaneously deactivate a different set of brain regions, commonly referred to as the task negative or default mode network. Second, functional connectivity analyses show that these same opposed networks are anti-correlated in the resting state. We hypothesize that these reciprocally inhibitory effects reflect two incompatible cognitive modes, each of which may be directed towards understanding the external world. Thus, engaging one mode activates one set of regions and suppresses activity in the other. We test this hypothesis by identifying two types of problem-solving task which, on the basis of prior work, have been consistently associated with the task positive and task negative regions: tasks requiring social cognition, i.e., reasoning about the mental states of other persons, and tasks requiring physical cognition, i.e., reasoning about the causal/mechanical properties of inanimate objects. Social and mechanical reasoning tasks were presented to neurologically normal participants during fMRI. Each task type was presented using both text and video clips. Regardless of presentation modality, we observed clear evidence of reciprocal suppression: social tasks deactivated regions associated with mechanical reasoning and mechanical tasks deactivated regions associated with social reasoning. These findings are not explained by self-referential processes, task engagement, mental simulation, mental time travel or external vs. internal attention, all factors previously hypothesized to explain default mode network activity. Analyses of resting state data revealed a close match between the regions our tasks identified as reciprocally inhibitory and regions of maximal anti-correlation in the resting state. These results indicate the reciprocal inhibition is not attributable to constraints inherent in the tasks, but is neural in origin. Hence, there is a physiological constraint on our ability to simultaneously engage two distinct cognitive modes. Further work is needed to more precisely characterize these opposing cognitive domains. Copyright © 2012 Elsevier Inc. All rights reserved.
Shared and disorder-specific task-positive and default mode network dysfunctions during sustained attention in paediatric Attention-Deficit/Hyperactivity Disorder and obsessive/compulsive disorder.

PubMed

Norman, Luke J; Carlisi, Christina O; Christakou, Anastasia; Cubillo, Ana; Murphy, Clodagh M; Chantiluke, Kaylita; Simmons, Andrew; Giampietro, Vincent; Brammer, Michael; Mataix-Cols, David; Rubia, Katya

2017-01-01

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

PubMed

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

2017-12-01

To identify abnormal thalamocortical circuits in the severe epilepsy of Lennox-Gastaut syndrome (LGS) that may explain the shared electroclinical phenotype and provide potential treatment targets. Twenty patients with a diagnosis of LGS (mean age = 28.5 years) and 26 healthy controls (mean age = 27.6 years) were compared using task-free functional magnetic resonance imaging (MRI). The thalamus was parcellated according to functional connectivity with 10 cortical networks derived using group-level independent component analysis. For each cortical network, we assessed between-group differences in thalamic functional connectivity strength using nonparametric permutation-based tests. Anatomical locations were identified by quantifying spatial overlap with a histologically informed thalamic MRI atlas. In both groups, posterior thalamic regions showed functional connectivity with visual, auditory, and sensorimotor networks, whereas anterior, medial, and dorsal thalamic regions were connected with networks of distributed association cortex (including the default-mode, anterior-salience, and executive-control networks). Four cortical networks (left and right executive-control network; ventral and dorsal default-mode network) showed significantly enhanced thalamic functional connectivity strength in patients relative to controls. Abnormal connectivity was maximal in mediodorsal and ventrolateral thalamic nuclei. Specific thalamocortical circuits are affected in LGS. Functional connectivity is abnormally enhanced between the mediodorsal and ventrolateral thalamus and the default-mode and executive-control networks, thalamocortical circuits that normally support diverse cognitive processes. In contrast, thalamic regions connecting with primary and sensory cortical networks appear to be less affected. Our previous neuroimaging studies show that epileptic activity in LGS is expressed via the default-mode and executive-control networks. Results of the present study suggest that the mediodorsal and ventrolateral thalamus may be candidate targets for modulating abnormal network behavior underlying LGS, potentially via emerging thalamic neurostimulation therapies. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.
Cognitive and default-mode resting state networks: do male and female brains "rest" differently?

PubMed

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.
Health impact assessment of cycling network expansions in European cities.

PubMed

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

PubMed

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.
A design for living technology: experiments with the mind time machine.

PubMed

Ikegami, Takashi

2013-01-01

Living technology aims to help people expand their experiences in everyday life. The environment offers people ways to interact with it, which we call affordances. Living technology is a design for new affordances. When we experience something new, we remember it by the way we perceive and interact with it. Recent studies in neuroscience have led to the idea of a default mode network, which is a baseline activity of a brain system. The autonomy of artificial life must be understood as a sort of default mode that self-organizes its baseline activity, preparing for its external inputs and its interaction with humans. I thus propose a method for creating a suitable default mode as a design principle for living technology. I built a machine called the mind time machine (MTM), which runs continuously for 10 h per day and receives visual data from its environment using 15 video cameras. The MTM receives and edits the video inputs while it self-organizes the momentary now. Its base program is a neural network that includes chaotic dynamics inside the system and a meta-network that consists of video feedback systems. Using this system as the hardware and a default mode network as a conceptual framework, I describe the system's autonomous behavior. Using the MTM as a testing ground, I propose a design principle for living technology.
Motorized CPM/CAM physiotherapy device with sliding-mode Fuzzy Neural Network control loop.

PubMed

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

PubMed

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.
Default mode of brain function in monkeys.

PubMed

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

2011-09-07

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.
Default Mode of Brain Function in Monkeys

PubMed Central

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

A computer program for the generation of logic networks from task chart data

NASA Technical Reports Server (NTRS)

Herbert, H. E.

1980-01-01

The Network Generation Program (NETGEN), which creates logic networks from task chart data is presented. NETGEN is written in CDC FORTRAN IV (Extended) and runs in a batch mode on the CDC 6000 and CYBER 170 series computers. Data is input via a two-card format and contains information regarding the specific tasks in a project. From this data, NETGEN constructs a logic network of related activities with each activity having unique predecessor and successor nodes, activity duration, descriptions, etc. NETGEN then prepares this data on two files that can be used in the Project Planning Analysis and Reporting System Batch Network Scheduling program and the EZPERT graphics program.
Resting-State Connectivity of the Left Frontal Cortex to the Default Mode and Dorsal Attention Network Supports Reserve in Mild Cognitive Impairment.

PubMed

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

2017-01-01

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

PubMed Central

Upadhyay, Jaymin; Baker, Scott J.; Chandran, Prasant; Miller, Loan; Lee, Younglim; Marek, Gerard J.; Sakoglu, Unal; Chin, Chih-Liang; Luo, Feng; Fox, Gerard B.; Day, Mark

2011-01-01

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. PMID:22125628
[Association of the physical activity of community-dwelling older adults with transportation modes, depression and social networks].

PubMed

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.
Salience network integrity predicts default mode network function after traumatic brain injury

PubMed Central

Bonnelle, Valerie; Ham, Timothy E.; Leech, Robert; Kinnunen, Kirsi M.; Mehta, Mitul A.; Greenwood, Richard J.; Sharp, David J.

2012-01-01

Efficient behavior involves the coordinated activity of large-scale brain networks, but the way in which these networks interact is uncertain. One theory is that the salience network (SN)—which includes the anterior cingulate cortex, presupplementary motor area, and anterior insulae—regulates dynamic changes in other networks. If this is the case, then damage to the structural connectivity of the SN should disrupt the regulation of associated networks. To investigate this hypothesis, we studied a group of 57 patients with cognitive impairments following traumatic brain injury (TBI) and 25 control subjects using the stop-signal task. The pattern of brain activity associated with stop-signal task performance was studied by using functional MRI, and the structural integrity of network connections was quantified by using diffusion tensor imaging. Efficient inhibitory control was associated with rapid deactivation within parts of the default mode network (DMN), including the precuneus and posterior cingulate cortex. TBI patients showed a failure of DMN deactivation, which was associated with an impairment of inhibitory control. TBI frequently results in traumatic axonal injury, which can disconnect brain networks by damaging white matter tracts. The abnormality of DMN function was specifically predicted by the amount of white matter damage in the SN tract connecting the right anterior insulae to the presupplementary motor area and dorsal anterior cingulate cortex. The results provide evidence that structural integrity of the SN is necessary for the efficient regulation of activity in the DMN, and that a failure of this regulation leads to inefficient cognitive control. PMID:22393019
Common Dimensional Reward Deficits Across Mood and Psychotic Disorders: A Connectome-Wide Association Study.

PubMed

Sharma, Anup; Wolf, Daniel H; Ciric, Rastko; Kable, Joseph W; Moore, Tyler M; Vandekar, Simon N; Katchmar, Natalie; Daldal, Aylin; Ruparel, Kosha; Davatzikos, Christos; Elliott, Mark A; Calkins, Monica E; Shinohara, Russell T; Bassett, Danielle S; Satterthwaite, Theodore D

2017-07-01

Anhedonia is central to multiple psychiatric disorders and causes substantial disability. A dimensional conceptualization posits that anhedonia severity is related to a transdiagnostic continuum of reward deficits in specific neural networks. Previous functional connectivity studies related to anhedonia have focused on case-control comparisons in specific disorders, using region-specific seed-based analyses. Here, the authors explore the entire functional connectome in relation to reward responsivity across a population of adults with heterogeneous psychopathology. In a sample of 225 adults from five diagnostic groups (major depressive disorder, N=32; bipolar disorder, N=50; schizophrenia, N=51; psychosis risk, N=39; and healthy control subjects, N=53), the authors conducted a connectome-wide analysis examining the relationship between a dimensional measure of reward responsivity (the reward sensitivity subscale of the Behavioral Activation Scale) and resting-state functional connectivity using multivariate distance-based matrix regression. The authors identified foci of dysconnectivity associated with reward responsivity in the nucleus accumbens, the default mode network, and the cingulo-opercular network. Follow-up analyses revealed dysconnectivity among specific large-scale functional networks and their connectivity with the nucleus accumbens. Reward deficits were associated with decreased connectivity between the nucleus accumbens and the default mode network and increased connectivity between the nucleus accumbens and the cingulo-opercular network. In addition, impaired reward responsivity was associated with default mode network hyperconnectivity and diminished connectivity between the default mode network and the cingulo-opercular network. These results emphasize the centrality of the nucleus accumbens in the pathophysiology of reward deficits and suggest that dissociable patterns of connectivity among large-scale networks are critical to the neurobiology of reward dysfunction across clinical diagnostic categories.
Network Mechanisms of Clinical Response to Transcranial Magnetic Stimulation in Posttraumatic Stress Disorder and Major Depressive Disorder.

PubMed

Philip, Noah S; Barredo, Jennifer; van 't Wout-Frank, Mascha; Tyrka, Audrey R; Price, Lawrence H; Carpenter, Linda L

2018-02-01

Repetitive transcranial magnetic stimulation (TMS) therapy can modulate pathological neural network functional connectivity in major depressive disorder (MDD). Posttraumatic stress disorder is often comorbid with MDD, and symptoms of both disorders can be alleviated with TMS therapy. This is the first study to evaluate TMS-associated changes in connectivity in patients with comorbid posttraumatic stress disorder and MDD. Resting-state functional connectivity magnetic resonance imaging was acquired before and after TMS therapy in 33 adult outpatients in a prospective open trial. TMS at 5 Hz was delivered, in up to 40 daily sessions, to the left dorsolateral prefrontal cortex. Analyses used a priori seeds relevant to TMS, posttraumatic stress disorder, or MDD (subgenual anterior cingulate cortex [sgACC], left dorsolateral prefrontal cortex, hippocampus, and basolateral amygdala) to identify imaging predictors of response and to evaluate clinically relevant changes in connectivity after TMS, followed by leave-one-out cross-validation. Imaging results were explored using data-driven multivoxel pattern activation. More negative pretreatment connectivity between the sgACC and the default mode network predicted clinical improvement, as did more positive amygdala-to-ventromedial prefrontal cortex connectivity. After TMS, symptom reduction was associated with reduced connectivity between the sgACC and the default mode network, left dorsolateral prefrontal cortex, and insula, and reduced connectivity between the hippocampus and the salience network. Multivoxel pattern activation confirmed seed-based predictors and correlates of treatment outcomes. These results highlight the central role of the sgACC, default mode network, and salience network as predictors of TMS response and suggest their involvement in mechanisms of action. Furthermore, this work indicates that there may be network-based biomarkers of clinical response relevant to these commonly comorbid disorders. Published by Elsevier Inc.
Functional subdivision of group-ICA results of fMRI data collected during cinema viewing.

PubMed

Pamilo, Siina; Malinen, Sanna; Hlushchuk, Yevhen; Seppä, Mika; Tikka, Pia; Hari, Riitta

2012-01-01

Independent component analysis (ICA) can unravel functional brain networks from functional magnetic resonance imaging (fMRI) data. The number of the estimated components affects both the spatial pattern of the identified networks and their time-course estimates. Here group-ICA was applied at four dimensionalities (10, 20, 40, and 58 components) to fMRI data collected from 15 subjects who viewed a 15-min silent film ("At land" by Maya Deren). We focused on the dorsal attention network, the default-mode network, and the sensorimotor network. The lowest dimensionalities demonstrated most prominent activity within the dorsal attention network, combined with the visual areas, and in the default-mode network; the sensorimotor network only appeared with ICA comprising at least 20 components. The results suggest that even very low-dimensional ICA can unravel the most prominent functionally-connected brain networks. However, increasing the number of components gives a more detailed picture and functionally feasible subdivision of the major networks. These results improve our understanding of the hierarchical subdivision of brain networks during viewing of a movie that provides continuous stimulation embedded in an attention-directing narrative.
Network-dependent modulation of brain activity during sleep.

PubMed

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

2014-09-01

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

PubMed Central

Khalil, Issa M.; Gadallah, Yasser; Hayajneh, Mohammad; Khreishah, Abdallah

2012-01-01

Underwater acoustic wireless sensor networks (UAWSNs) have many applications across various civilian and military domains. However, they suffer from the limited available bandwidth of acoustic signals and harsh underwater conditions. In this work, we present an Orthogonal Frequency Division Multiple Access (OFDMA)-based Media Access Control (MAC) protocol that is configurable to suit the operating requirements of the underwater sensor network. The protocol has three modes of operation, namely random, equal opportunity and energy-conscious modes of operation. Our MAC design approach exploits the multi-path characteristics of a fading acoustic channel to convert it into parallel independent acoustic sub-channels that undergo flat fading. Communication between node pairs within the network is done using subsets of these sub-channels, depending on the configurations of the active mode of operation. Thus, the available limited bandwidth gets fully utilized while completely avoiding interference. We derive the mathematical model for optimal power loading and subcarrier selection, which is used as basis for all modes of operation of the protocol. We also conduct many simulation experiments to evaluate and compare our protocol with other Code Division Multiple Access (CDMA)-based MAC protocols. PMID:23012517
An adaptive OFDMA-based MAC protocol for underwater acoustic wireless sensor networks.

PubMed

Khalil, Issa M; Gadallah, Yasser; Hayajneh, Mohammad; Khreishah, Abdallah

2012-01-01

Underwater acoustic wireless sensor networks (UAWSNs) have many applications across various civilian and military domains. However, they suffer from the limited available bandwidth of acoustic signals and harsh underwater conditions. In this work, we present an Orthogonal Frequency Division Multiple Access (OFDMA)-based Media Access Control (MAC) protocol that is configurable to suit the operating requirements of the underwater sensor network. The protocol has three modes of operation, namely random, equal opportunity and energy-conscious modes of operation. Our MAC design approach exploits the multi-path characteristics of a fading acoustic channel to convert it into parallel independent acoustic sub-channels that undergo flat fading. Communication between node pairs within the network is done using subsets of these sub-channels, depending on the configurations of the active mode of operation. Thus, the available limited bandwidth gets fully utilized while completely avoiding interference. We derive the mathematical model for optimal power loading and subcarrier selection, which is used as basis for all modes of operation of the protocol. We also conduct many simulation experiments to evaluate and compare our protocol with other Code Division Multiple Access (CDMA)-based MAC protocols.
Greater preference consistency during the Willingness-to-Pay task is related to higher resting state connectivity between the ventromedial prefrontal cortex and the ventral striatum.

PubMed

Mackey, Scott; Olafsson, Valur; Aupperle, Robin L; Lu, Kun; Fonzo, Greg A; Parnass, Jason; Liu, Thomas; Paulus, Martin P

2016-09-01

The significance of why a similar set of brain regions are associated with the default mode network and value-related neural processes remains to be clarified. Here, we examined i) whether brain regions exhibiting willingness-to-pay (WTP) task-related activity are intrinsically connected when the brain is at rest, ii) whether these regions overlap spatially with the default mode network, and iii) whether individual differences in choice behavior during the WTP task are reflected in functional brain connectivity at rest. Blood-oxygen-level dependent (BOLD) signal was measured by functional magnetic resonance imaging while subjects performed the WTP task and at rest with eyes open. Brain regions that tracked the value of bids during the WTP task were used as seed regions in an analysis of functional connectivity in the resting state data. The seed in the ventromedial prefrontal cortex was functionally connected to core regions of the WTP task-related network. Brain regions within the WTP task-related network, namely the ventral precuneus, ventromedial prefrontal and posterior cingulate cortex overlapped spatially with publically available maps of the default mode network. Also, those individuals with higher functional connectivity during rest between the ventromedial prefrontal cortex and the ventral striatum showed greater preference consistency during the WTP task. Thus, WTP task-related regions are an intrinsic network of the brain that corresponds spatially with the default mode network, and individual differences in functional connectivity within the WTP network at rest may reveal a priori biases in choice behavior.
Greater preference consistency during the Willingness-to-Pay task is related to higher resting state connectivity between the ventromedial prefrontal cortex and the ventral striatum

PubMed Central

Mackey, Scott; Olafsson, Valur; Aupperle, Robin; Lu, Kun; Fonzo, Greg; Parnass, Jason; Liu, Thomas; Paulus, Martin P.

2015-01-01

The significance of why a similar set of brain regions are associated with the default mode network and value-related neural processes remains to be clarified. Here, we examined i) whether brain regions exhibiting willingness-to-pay (WTP) task-related activity are intrinsically connected when the brain is at rest, ii) whether these regions overlap spatially with the default mode network, and iii) whether individual differences in choice behavior during the WTP task are reflected in functional brain connectivity at rest. Blood-oxygen-level dependent (BOLD) signal was measured by functional magnetic resonance imaging while subjects performed the WTP task and at rest with eyes open. Brain regions that tracked the value of bids during the WTP task were used as seed regions in an analysis of functional connectivity in the resting state data. The seed in the ventromedial prefrontal cortex was functionally connected to core regions of the WTP task-related network. Brain regions within the WTP task-related network, namely the ventral precuneus, ventromedial prefrontal and posterior cingulate cortex overlapped spatially with publically available maps of the default mode network. Also, those individuals with higher functional connectivity during rest between the ventromedial prefrontal cortex and the ventral striatum showed greater preference consistency during the WTP task. Thus, WTP task-related regions are an intrinsic network of the brain that corresponds spatially with the default mode network, and individual differences in functional connectivity within the WTP network at rest may reveal a priori biases in choice behavior. PMID:26271206
Insomnia Disorder and Brain's Default-Mode Network.

PubMed

Marques, Daniel Ruivo; Gomes, Ana Allen; Caetano, Gina; Castelo-Branco, Miguel

2018-06-09

Insomnia disorder (ID) is a prevalent sleep disorder that significantly compromises the physical and mental health of individuals. This article reviews novel approaches in the study of brain networks and impaired function in ID through the application of modern neuroimaging techniques such as functional magnetic resonance imaging (fMRI). The default-mode network (DMN) is presumed to be correlated with self-referential information processing, and it appears to be altered or unbalanced in insomnia. A growing body of evidence suggests the lack of deactivation of brain regions comprising the DMN when insomnia patients are at rest. Moreover, core areas of the DMN demonstrate greater activation in insomnia patients when compared to healthy controls in self-referential related tasks. Despite the few studies on the topic, underpinning the correlation between abnormal DMN activity and ID deserves further attention in the future. Implications for therapeutics are briefly outlined.
Putting age-related task activation into large-scale brain networks: A meta-analysis of 114 fMRI studies on healthy aging.

PubMed

Li, Hui-Jie; Hou, Xiao-Hui; Liu, Han-Hui; Yue, Chun-Lin; Lu, Guang-Ming; Zuo, Xi-Nian

2015-10-01

Normal aging is associated with cognitive decline and underlying brain dysfunction. Previous studies concentrated less on brain network changes at a systems level. Our goal was to examine these age-related changes of fMRI-derived activation with a common network parcellation of the human brain function, offering a systems-neuroscience perspective of healthy aging. We conducted a series of meta-analyses on a total of 114 studies that included 2035 older adults and 1845 young adults. Voxels showing significant age-related changes in activation were then overlaid onto seven commonly referenced neuronal networks. Older adults present moderate cognitive decline in behavioral performance during fMRI scanning, and hypo-activate the visual network and hyper-activate both the frontoparietal control and default mode networks. The degree of increased activation in frontoparietal network was associated with behavioral performance in older adults. Age-related changes in activation present different network patterns across cognitive domains. The systems neuroscience approach used here may be useful for elucidating the underlying network mechanisms of various brain plasticity processes during healthy aging. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Resting-state networks associated with cognitive processing show more age-related decline than those associated with emotional processing.

PubMed

Nashiro, Kaoru; Sakaki, Michiko; Braskie, Meredith N; Mather, Mara

2017-06-01

Correlations in activity across disparate brain regions during rest reveal functional networks in the brain. Although previous studies largely agree that there is an age-related decline in the "default mode network," how age affects other resting-state networks, such as emotion-related networks, is still controversial. Here we used a dual-regression approach to investigate age-related alterations in resting-state networks. The results revealed age-related disruptions in functional connectivity in all 5 identified cognitive networks, namely the default mode network, cognitive-auditory, cognitive-speech (or speech-related somatosensory), and right and left frontoparietal networks, whereas such age effects were not observed in the 3 identified emotion networks. In addition, we observed age-related decline in functional connectivity in 3 visual and 3 motor/visuospatial networks. Older adults showed greater functional connectivity in regions outside 4 out of the 5 identified cognitive networks, consistent with the dedifferentiation effect previously observed in task-based functional magnetic resonance imaging studies. Both reduced within-network connectivity and increased out-of-network connectivity were correlated with poor cognitive performance, providing potential biomarkers for cognitive aging. Copyright © 2017 Elsevier Inc. All rights reserved.
Post-installation activities in the Comprehensive Nuclear Test Ban Treaty (CTBT) International Monitoring System (IMS) infrasound network

NASA Astrophysics Data System (ADS)

Vivas Veloso, J. A.; Christie, D. R.; Hoffmann, T. L.; Campus, P.; Bell, M.; Langlois, A.; Martysevich, P.; Demirovik, E.; Carvalho, J.; Kramer, A.; Wu, Sean F.

2002-11-01

The provisional operation and maintenance of IMS infrasound stations after installation and subsequent certification has the objective to prepare the infrasound network for entry into force of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). The goal is to maintain and fine tune the technical capabilities of the network, to repair faulty equipment, and to ensure that stations continue to meet the minimum specifications through evaluation of data quality and station recalibration. Due to the globally dispersed nature of the network, this program constitutes a significant undertaking that requires careful consideration of possible logistic approaches and their financial implications. Currently, 11 of the 60 IMS infrasound stations are transmitting data in the post-installation Testing & Evaluation mode. Another 5 stations are under provisional operation and are maintained in post-certification mode. It is expected that 20% of the infrasound network will be certified by the end of 2002. This presentation will focus on the different phases of post-installation activities of the IMS infrasound program and the logistical challenges to be tackled to ensure a cost-efficient management of the network. Specific topics will include Testing & Evaluation and Certification of Infrasound Stations, as well as Configuration Management and Network Sustainment.
Visual Network Asymmetry and Default Mode Network Function in ADHD: An fMRI Study

PubMed Central

Hale, T. Sigi; Kane, Andrea M.; Kaminsky, Olivia; Tung, Kelly L.; Wiley, Joshua F.; McGough, James J.; Loo, Sandra K.; Kaplan, Jonas T.

2014-01-01

Background: A growing body of research has identified abnormal visual information processing in attention-deficit hyperactivity disorder (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 with 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 with 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. PMID:25076915
Gamification of Learning Deactivates the Default Mode Network

PubMed Central

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

2016-01-01

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. PMID:26779054

Gamification of Learning Deactivates the Default Mode Network.

PubMed

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.
Morphological and Electrochemical Characterization of Nanostructured Li 4Ti 5O 12 Electrodes Using Multiple Imaging Mode Synchrotron X-ray Computed Tomography

DOE PAGES

Kashkooli, Ali Ghorbani; Foreman, Evan; Farhad, Siamak; ...

2017-09-21

In this study, synchrotron X-ray computed tomography has been utilized using two different imaging modes, absorption and Zernike phase contrast, to reconstruct the real three-dimensional (3D) morphology of nanostructured Li 4Ti 5O 12 (LTO) electrodes. The morphology of the high atomic number active material has been obtained using the absorption contrast mode, whereas the percolated solid network composed of active material and carbon-doped polymer binder domain (CBD) has been obtained using the Zernike phase contrast mode. The 3D absorption contrast image revealed that some LTO nano-particles tend to agglomerate and form secondary micro-sized particles with varying degrees of sphericity. Themore » tortuosity of electrode’s pore and solid phases were found to have directional dependence, different from Bruggeman’s tortuosity commonly used in macro-homogeneous models. The electrode’s heterogeneous structure was investigated by developing a numerical model to simulate galvanostatic discharge process using the Zernike phase contrast mode. The inclusion of CBD in the Zernike phase contrast results in an integrated percolated network of active material and CBD that is highly suited for continuum modeling. As a result, the simulation results highlight the importance of using the real 3D geometry since the spatial distribution of physical and electrochemical properties have a strong non-uniformity due to microstructural heterogeneities.« less
Identifying and tracking dynamic processes in social networks

NASA Astrophysics Data System (ADS)

Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

2006-05-01

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.
Automatic network coupling analysis for dynamical systems based on detailed kinetic models.

PubMed

Lebiedz, Dirk; Kammerer, Julia; Brandt-Pollmann, Ulrich

2005-10-01

We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.
Psychopathic traits associated with abnormal hemodynamic activity in salience and default mode networks during auditory oddball task.

PubMed

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.
Systems for the Intermodal Routing of Spent Nuclear Fuel

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

Peterson, Steven K; Liu, Cheng

The safe and secure movement of spent nuclear fuel from shutdown and active reactor facilities to intermediate or long term storage sites may, in some instances, require the use of several modes of transportation to accomplish the move. To that end, a fully operable multi-modal routing system is being developed within Oak Ridge National Laboratory s (ORNL) WebTRAGIS (Transportation Routing Analysis Geographic Information System). This study aims to provide an overview of multi-modal routing, the existing state of the TRAGIS networks, the source data needs, and the requirements for developing structural relationships between various modes to create a suitable systemmore » for modeling the transport of spent nuclear fuel via a multimodal network. Modern transportation systems are comprised of interconnected, yet separate, modal networks. Efficient transportation networks rely upon the smooth transfer of cargoes at junction points that serve as connectors between modes. A key logistical impediment to the shipment of spent nuclear fuel is the absence of identified or designated transfer locations between transport modes. Understanding the potential network impacts on intermodal transportation of spent nuclear fuel is vital for planning transportation routes from origin to destination. By identifying key locations where modes intersect, routing decisions can be made to prioritize cost savings, optimize transport times and minimize potential risks to the population and environment. In order to facilitate such a process, ORNL began the development of a base intermodal network and associated routing code. The network was developed using previous intermodal networks and information from publicly available data sources to construct a database of potential intermodal transfer locations with likely capability to handle spent nuclear fuel casks. The coding development focused on modifying the existing WebTRAGIS routing code to accommodate intermodal transfers and the selection of prioritization constraints and modifiers to determine route selection. The limitations of the current model and future directions for development are discussed, including the current state of information on possible intermodal transfer locations for spent fuel.« less
Identification of Resting State Networks Involved in Executive Function.

PubMed

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.
A novel broadband bi-mode active frequency selective surface

NASA Astrophysics Data System (ADS)

Xu, Yang; Gao, Jinsong; Xu, Nianxi; Shan, Dongzhi; Song, Naitao

2017-05-01

A novel broadband bi-mode active frequency selective surface (AFSS) is presented in this paper. The proposed structure is composed of a periodic array of convoluted square patches and Jerusalem Crosses. According to simulation results, the frequency response of AFSS definitely exhibits a mode switch feature between band-pass and band-stop modes when the diodes stay in ON and OFF states. In order to apply a uniform bias to each PIN diode, an ingenious biasing network based on the extension of Wheatstone bridge is adopted in prototype AFSS. The test results are in good agreement with the simulation results. A further physical mechanism of the bi-mode AFSS is shown by contrasting the distribution of electric field on the AFSS patterns for the two working states.
Multi-load Groups Coordinated Load Control Strategy Considering Power Network Constraints

NASA Astrophysics Data System (ADS)

Liu, Meng; Zhao, Binchao; Wang, Jun; Zhang, Guohui; Wang, Xin

2017-05-01

Loads with energy storage property can actively participate in power balance for power systems, this paper takes air conditioner as a controllable load example, proposing a multi-load groups coordinated load control strategy considering power network constraints. Firstly, two load control modes considering recovery of load diversity are designed, blocking power oscillation of aggregated air conditioners. As the same time, air conditioner temperature setpoint recovery control strategy is presented to avoid power recovery peak. Considering inherent characteristics of two load control modes, an coordinated load control mode is designed by combining the both. Basing on this, a multi-load groups coordinated load control strategy is proposed. During the implementing of load control, power network constraints should be satisfied. An indice which can reflect the security of power system operating is defined. By minimizing its value through optimization, the change of air conditioning loads’ aggregated power on each load bus can be calculated. Simulations are conducted on an air conditioners group and New England 10-generator 39-bus system, verifying the effectiveness of the proposed multi-load groups coordinated load control strategy considering power network constraints.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Kashkooli, Ali Ghorbani; Foreman, Evan; Farhad, Siamak

In this study, synchrotron X-ray computed tomography has been utilized using two different imaging modes, absorption and Zernike phase contrast, to reconstruct the real three-dimensional (3D) morphology of nanostructured Li 4Ti 5O 12 (LTO) electrodes. The morphology of the high atomic number active material has been obtained using the absorption contrast mode, whereas the percolated solid network composed of active material and carbon-doped polymer binder domain (CBD) has been obtained using the Zernike phase contrast mode. The 3D absorption contrast image revealed that some LTO nano-particles tend to agglomerate and form secondary micro-sized particles with varying degrees of sphericity. Themore » tortuosity of electrode’s pore and solid phases were found to have directional dependence, different from Bruggeman’s tortuosity commonly used in macro-homogeneous models. The electrode’s heterogeneous structure was investigated by developing a numerical model to simulate galvanostatic discharge process using the Zernike phase contrast mode. The inclusion of CBD in the Zernike phase contrast results in an integrated percolated network of active material and CBD that is highly suited for continuum modeling. As a result, the simulation results highlight the importance of using the real 3D geometry since the spatial distribution of physical and electrochemical properties have a strong non-uniformity due to microstructural heterogeneities.« less
Functional Subdivision of Group-ICA Results of fMRI Data Collected during Cinema Viewing

PubMed Central

Pamilo, Siina; Malinen, Sanna; Hlushchuk, Yevhen; Seppä, Mika; Tikka, Pia; Hari, Riitta

2012-01-01

Independent component analysis (ICA) can unravel functional brain networks from functional magnetic resonance imaging (fMRI) data. The number of the estimated components affects both the spatial pattern of the identified networks and their time-course estimates. Here group-ICA was applied at four dimensionalities (10, 20, 40, and 58 components) to fMRI data collected from 15 subjects who viewed a 15-min silent film (“At land” by Maya Deren). We focused on the dorsal attention network, the default-mode network, and the sensorimotor network. The lowest dimensionalities demonstrated most prominent activity within the dorsal attention network, combined with the visual areas, and in the default-mode network; the sensorimotor network only appeared with ICA comprising at least 20 components. The results suggest that even very low-dimensional ICA can unravel the most prominent functionally-connected brain networks. However, increasing the number of components gives a more detailed picture and functionally feasible subdivision of the major networks. These results improve our understanding of the hierarchical subdivision of brain networks during viewing of a movie that provides continuous stimulation embedded in an attention-directing narrative. PMID:22860044
Independent Oscillatory Patterns Determine Performance Fluctuations in Children with Attention Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Yordanova, Juliana; Albrecht, Bjorn; Uebel, Henrik; Kirov, Roumen; Banaschewski, Tobias; Rothenberger, Aribert; Kolev, Vasil

2011-01-01

The maintenance of stable goal-directed behaviour is a hallmark of conscious executive control in humans. Notably, both correct and error human actions may have a subconscious activation-based determination. One possible source of subconscious interference may be the default mode network that, in contrast to attentional network, manifests…
Inferring genome-wide functional modulatory network: a case study on NF-κB/RelA transcription factor.

PubMed

Li, Xueling; Zhu, Min; Brasier, Allan R; Kudlicki, Andrzej S

2015-04-01

How different pathways lead to the activation of a specific transcription factor (TF) with specific effects is not fully understood. We model context-specific transcriptional regulation as a modulatory network: triplets composed of a TF, target gene, and modulator. Modulators usually affect the activity of a specific TF at the posttranscriptional level in a target gene-specific action mode. This action may be classified as enhancement, attenuation, or inversion of either activation or inhibition. As a case study, we inferred, from a large collection of expression profiles, all potential modulations of NF-κB/RelA. The predicted modulators include many proteins previously not reported as physically binding to RelA but with relevant functions, such as RNA processing, cell cycle, mitochondrion, ubiquitin-dependent proteolysis, and chromatin modification. Modulators from different processes exert specific prevalent action modes on distinct pathways. Modulators from noncoding RNA, RNA-binding proteins, TFs, and kinases modulate the NF-κB/RelA activity with specific action modes consistent with their molecular functions and modulation level. The modulatory networks of NF-κB/RelA in the context epithelial-mesenchymal transition (EMT) and burn injury have different modulators, including those involved in extracellular matrix (FBN1), cytoskeletal regulation (ACTN1), and metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), a long intergenic nonprotein coding RNA, and tumor suppression (FOXP1) for EMT, and TXNIP, GAPDH, PKM2, IFIT5, LDHA, NID1, and TPP1 for burn injury.
Changes in the interaction of resting-state neural networks from adolescence to adulthood.

PubMed

Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D

2009-08-01

This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12-30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system "causal density" estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and "default mode" networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. (c) 2009 Wiley-Liss, Inc.
[Brain activitivation of euthymic patients with Type I bipolar disorder in resting state Default Mode Network].

PubMed

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.
Out of focus - brain attention control deficits in adult ADHD.

PubMed

Salmi, Juha; Salmela, Viljami; Salo, Emma; Mikkola, Katri; Leppämäki, Sami; Tani, Pekka; Hokkanen, Laura; Laasonen, Marja; Numminen, Jussi; Alho, Kimmo

2018-04-24

Modern environments are full of information, and place high demands on the attention control mechanisms that allow the selection of information from one (focused attention) or multiple (divided attention) sources, react to changes in a given situation (stimulus-driven attention), and allocate effort according to demands (task-positive and task-negative activity). We aimed to reveal how attention deficit hyperactivity disorder (ADHD) affects the brain functions associated with these attention control processes in constantly demanding tasks. Sixteen adults with ADHD and 17 controls performed adaptive visual and auditory discrimination tasks during functional magnetic resonance imaging (fMRI). Overlapping brain activity in frontoparietal saliency and default-mode networks, as well as in the somato-motor, cerebellar, and striatal areas were observed in all participants. In the ADHD participants, we observed exclusive activity enhancement in the brain areas typically considered to be primarily involved in other attention control functions: During auditory-focused attention, we observed higher activation in the sensory cortical areas of irrelevant modality and the default-mode network (DMN). DMN activity also increased during divided attention in the ADHD group, in turn decreasing during a simple button-press task. Adding irrelevant stimulation resulted in enhanced activity in the salience network. Finally, the irrelevant distractors that capture attention in a stimulus-driven manner activated dorsal attention networks and the cerebellum. Our findings suggest that attention control deficits involve the activation of irrelevant sensory modality, problems in regulating the level of attention on demand, and may encumber top-down processing in cases of irrelevant information. Copyright © 2018. Published by Elsevier B.V.
Apparatus and method for fusion of compute and switching functions of exascale system into a single component by using configurable network-on-chip fabric with distributed dual mode input-output ports and programmable network interfaces

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

Khare, Surhud; Somasekhar, Dinesh; More, Ankit

Described is an apparatus which comprises: a Network-On-Chip fabric using crossbar switches, having distributed ingress and egress ports; and a dual-mode network interface coupled to at least one crossbar switch, the dual-mode network interface is to include: a dual-mode circuitry; a controller operable to: configure the dual-mode circuitry to transmit and receive differential signals via the egress and ingress ports, respectively, and configure the dual-mode circuitry to transmit and receive signal-ended signals via the egress and ingress ports, respectively.
The default mode network and recurrent depression: a neurobiological model of cognitive risk factors.

PubMed

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.
Altered Synchronizations among Neural Networks in Geriatric Depression

PubMed Central

Wang, Lihong; Chou, Ying-Hui; Potter, Guy G.; Steffens, David C.

2015-01-01

Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression. PMID:26180795
Altered Synchronizations among Neural Networks in Geriatric Depression.

PubMed

Wang, Lihong; Chou, Ying-Hui; Potter, Guy G; Steffens, David C

2015-01-01

Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.

Sex-specific neural activity when resolving cognitive interference in individuals with or without prior internalizing disorders.

PubMed

Wang, Zhishun; Jacobs, Rachel H; Marsh, Rachel; Horga, Guillermo; Qiao, Jianping; Warner, Virginia; Weissman, Myrna M; Peterson, Bradley S

2016-03-30

The processing of cognitive interference is a self-regulatory capacity that is impaired in persons with internalizing disorders. This investigation was to assess sex differences in the neural correlates of cognitive interference in individuals with and without an illness history of an internalizing disorder. We compared functional magnetic resonance imaging blood-oxygenation-level-dependent responses in both males (n=63) and females (n=80) with and without this illness history during performance of the Simon task. Females deactivated superior frontal gyrus, inferior parietal lobe, and posterior cingulate cortex to a greater extent than males. Females with a prior history of internalizing disorder also deactivated these regions more compared to males with that history, and they additionally demonstrated greater activation of right inferior frontal gyrus. These group differences were represented in a significant sex-by-illness interaction in these regions. These deactivated regions compose a task-negative or default mode network, whereas the inferior frontal gyrus usually activates when performing an attention-demanding task and is a key component of a task-positive network. Our findings suggest that a prior history of internalizing disorders disproportionately influences functioning of the default mode network and is associated with an accompanying activation of the task-positive network in females during the resolution of cognitive interference. Copyright © 2016. Published by Elsevier Ireland Ltd.
Modulation of working memory load distinguishes individuals with and without balance impairments following mild traumatic brain injury.

PubMed

Woytowicz, Elizabeth J; Sours, Chandler; Gullapalli, Rao P; Rosenberg, Joseph; Westlake, Kelly P

2018-01-01

Balance and gait deficits can persist after mild traumatic brain injury (TBI), yet an understanding of the underlying neural mechanism remains limited. The purpose of this study was to investigate differences in attention network modulation in patients with and without balance impairments 2-8 weeks following mild TBI. Using functional magnetic resonance imaging, we compared activity and functional connectivity of cognitive brain regions of the default mode, central-executive and salience networks during a 2-back working memory task in participants with mild TBI and balance impairments (n = 7, age 47 ± 15 years) or no balance impairments (n = 7, age 47 ± 15 years). We first identified greater activation in the lateral occipital cortex in the balance impaired group. Second, we observed stronger connectivity of left pre-supplementary motor cortex in the balance impaired group during the working memory task, which was related to decreased activation of regions within the salience and central executive networks and greater suppression of the default mode network. Results suggest a link between impaired balance and modulation of cognitive resources in patients in mTBI. Findings also highlight the potential importance of moving beyond traditional balance assessments towards an integrative assessment of cognition and balance in this population.
Creating Profiles from User Network Behavior

DTIC Science & Technology

2013-09-01

We varied the m-estimate in Naïve Bayes, m for pruning in Learning Tree, and how many k nearest neighbors to select from in KNN, before settling on the...N. Taft, “The cubicle vs. the coffee shop: behavioral modes in enterprise end-users,” in Proc. of the 9th Int. Conf. on Passive and Active Network
Prefrontal, posterior parietal and sensorimotor network activity underlying speed control during walking

PubMed Central

Bulea, Thomas C.; Kim, Jonghyun; Damiano, Diane L.; Stanley, Christopher J.; Park, Hyung-Soon

2015-01-01

Accumulating evidence suggests cortical circuits may contribute to control of human locomotion. Here, noninvasive electroencephalography (EEG) recorded from able-bodied volunteers during a novel treadmill walking paradigm was used to assess neural correlates of walking. A systematic processing method, including a recently developed subspace reconstruction algorithm, reduced movement-related EEG artifact prior to independent component analysis and dipole source localization. We quantified cortical activity while participants tracked slow and fast target speeds across two treadmill conditions: an active mode that adjusted belt speed based on user movements and a passive mode reflecting a typical treadmill. Our results reveal frequency specific, multi-focal task related changes in cortical oscillations elicited by active walking. Low γ band power, localized to the prefrontal and posterior parietal cortices, was significantly increased during double support and early swing phases, critical points in the gait cycle since the active controller adjusted speed based on pelvis position and swing foot velocity. These phasic γ band synchronizations provide evidence that prefrontal and posterior parietal networks, previously implicated in visuo-spatial and somotosensory integration, are engaged to enhance lower limb control during gait. Sustained μ and β band desynchronization within sensorimotor cortex, a neural correlate for movement, was observed during walking thereby validating our methods for isolating cortical activity. Our results also demonstrate the utility of EEG recorded during locomotion for probing the multi-regional cortical networks which underpin its execution. For example, the cortical network engagement elicited by the active treadmill suggests that it may enhance neuroplasticity for more effective motor training. PMID:26029077
Bayesian network analysis revealed the connectivity difference of the default mode network from the resting-state to task-state

PubMed Central

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
Response mode-dependent differences in neurofunctional networks during response inhibition: an EEG-beamforming study.

PubMed

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

2016-11-01

Response inhibition processes are one of the most important executive control functions and have been subject to intense research in cognitive neuroscience. However, knowledge on the neurophysiology and functional neuroanatomy on response inhibition is biased because studies usually employ experimental paradigms (e.g., sustained attention to response task, SART) in which behavior is susceptible to impulsive errors. Here, we investigate whether there are differences in neurophysiological mechanisms and networks depending on the response mode that predominates behavior in a response inhibition task. We do so comparing a SART with a traditionally formatted task paradigm. We use EEG-beamforming in two tasks inducing opposite response modes during action selection. We focus on theta frequency modulations, since these are implicated in cognitive control processes. The results show that a response mode that is susceptible to impulsive errors (response mode used in the SART) is associated with stronger theta band activity in the left temporo-parietal junction. The results suggest that the response modes applied during response inhibition differ in the encoding of surprise signals, or related processes of attentional sampling. Response modes during response inhibition seem to differ in processes necessary to update task representations relevant to behavioral control.
The default mode network in chimpanzees (Pan troglodytes) is similar to that of humans.

PubMed

Barks, Sarah K; Parr, Lisa A; Rilling, James K

2015-02-01

The human default mode network (DMN), comprising medial prefrontal cortex, precuneus, posterior cingulate cortex, lateral parietal cortex, and medial temporal cortex, is highly metabolically active at rest but deactivates during most focused cognitive tasks. The DMN and social cognitive networks overlap significantly in humans. We previously demonstrated that chimpanzees (Pan troglodytes) show highest resting metabolic brain activity in the cortical midline areas of the human DMN. Human DMN is defined by task-induced deactivations, not absolute resting metabolic levels; ergo, resting activity is insufficient to define a DMN in chimpanzees. Here, we assessed the chimpanzee DMN's deactivations relative to rest during cognitive tasks and the effect of social content on these areas' activity. Chimpanzees performed a match-to-sample task with conspecific behavioral stimuli of varying sociality. Using [(18)F]-FDG PET, brain activity during these tasks was compared with activity during a nonsocial task and at rest. Cortical midline areas in chimpanzees deactivated in these tasks relative to rest, suggesting a chimpanzee DMN anatomically and functionally similar to humans. Furthermore, when chimpanzees make social discriminations, these same areas (particularly precuneus) are highly active relative to nonsocial tasks, suggesting that, as in humans, the chimpanzee DMN may play a role in social cognition. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Aberrant functional connectivity of default-mode network in type 2 diabetes patients.

PubMed

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

2015-11-01

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

ERIC Educational Resources Information Center

Wang, Ying; Li, Bing; Xie, Bai-zhi

2007-01-01

Research-oriented learning mode that based on network is significant to cultivate comprehensive-developing innovative person with network teaching in education for all-around development. This paper establishes a research-oriented learning mode by aiming at the problems existing in research-oriented learning based on network environment, and…
High Efficiency, Transparent, Reusable, and Active PM2.5 Filters by Hierarchical Ag Nanowire Percolation Network.

PubMed

Jeong, Seongmin; Cho, Hyunmin; Han, Seonggeun; Won, Phillip; Lee, Habeom; Hong, Sukjoon; Yeo, Junyeob; Kwon, Jinhyeong; Ko, Seung Hwan

2017-07-12

Air quality has become a major public health issue in Asia including China, Korea, and India. Particulate matters are the major concern in air quality. We present the first environmental application demonstration of Ag nanowire percolation network for a novel, electrical type transparent, reusable, and active PM2.5 air filter although the Ag nanowire percolation network has been studied as a very promising transparent conductor in optoelectronics. Compared with previous particulate matter air filter study using relatively weaker short-range intermolecular force in polar polymeric nanofiber, Ag nanowire percolation network filters use stronger long-range electrostatic force to capture PM2.5, and they are highly efficient (>99.99%), transparent, working on an active mode, low power consumption, antibacterial, and reusable after simple washing. The proposed new particulate matter filter can be applied for a highly efficient, reusable, active and energy efficient filter for wearable electronics application.
Key role of coupling, delay, and noise in resting brain fluctuations

PubMed Central

Deco, Gustavo; Jirsa, Viktor; McIntosh, A. R.; Sporns, Olaf; Kötter, Rolf

2009-01-01

A growing body of neuroimaging research has documented that, in the absence of an explicit task, the brain shows temporally coherent activity. This so-called “resting state” activity or, more explicitly, the default-mode network, has been associated with daydreaming, free association, stream of consciousness, or inner rehearsal in humans, but similar patterns have also been found under anesthesia and in monkeys. Spatiotemporal activity patterns in the default-mode network are both complex and consistent, which raises the question whether they are the expression of an interesting cognitive architecture or the consequence of intrinsic network constraints. In numerical simulation, we studied the dynamics of a simplified cortical network using 38 noise-driven (Wilson–Cowan) oscillators, which in isolation remain just below their oscillatory threshold. Time delay coupling based on lengths and strengths of primate corticocortical pathways leads to the emergence of 2 sets of 40-Hz oscillators. The sets showed synchronization that was anticorrelated at <0.1 Hz across the sets in line with a wide range of recent experimental observations. Systematic variation of conduction velocity, coupling strength, and noise level indicate a high sensitivity of emerging synchrony as well as simulated blood flow blood oxygen level-dependent (BOLD) on the underlying parameter values. Optimal sensitivity was observed around conduction velocities of 1–2 m/s, with very weak coupling between oscillators. An additional finding was that the optimal noise level had a characteristic scale, indicating the presence of stochastic resonance, which allows the network dynamics to respond with high sensitivity to changes in diffuse feedback activity. PMID:19497858
The psychedelic state induced by ayahuasca modulates the activity and connectivity of the default mode network.

PubMed

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

2015-01-01

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

PubMed

Travis, Frederick; Parim, Niyazi

2017-02-01

This study used subjective reports and eLORETA analysis to assess to what extent Transcendental Meditation (TM) might involve focused attention-voluntary control of mental content. Eighty-seven TM subjects with one month to five years TM experience participated in this study. Regression analysis of years TM practice and self-reported transcendental experiences (lack of time, space and body sense) during meditation practice was flat (r=.07). Those practicing Transcendental Meditation for 1month reported as much transcending as those with 5years of practice. The eLORETA comparison of eyes-closed rest/task and TM practice/task identified similar areas of activation: theta and alpha activation during rest and TM in the posterior cingulate and precuneus, part of the default mode network, and beta2 and beta3 activation during the task in anterior cingulate, ventral lateral and dorsolateral prefrontal cortices, part of the central executive network. In addition, eLORETA comparison of rest and TM identified higher beta temporal activation during rest and higher theta orbitofrontal activation during TM. Thus, it does not seem accurate to include TM practice with meditations in the catgory of Focused Attention, which are characterized by gamma EEG and DMN deactivation. Mixing meditations with different procedures into a single study confounds exploration of meditation effects and confounds application of meditation practices to different subject populations. Copyright © 2016 Elsevier Inc. All rights reserved.
A Coordinate-Based Meta-Analysis of Overlaps in Regional Specialization and Functional Connectivity across Subjective Value and Default Mode Networks.

PubMed

Acikalin, M Yavuz; Gorgolewski, Krzysztof J; Poldrack, Russell A

2017-01-01

Previous research has provided qualitative evidence for overlap in a number of brain regions across the subjective value network (SVN) and the default mode network (DMN). In order to quantitatively assess this overlap, we conducted a series of coordinate-based meta-analyses (CBMA) of results from 466 functional magnetic resonance imaging experiments on task-negative or subjective value-related activations in the human brain. In these analyses, we first identified significant overlaps and dissociations across activation foci related to SVN and DMN. Second, we investigated whether these overlapping subregions also showed similar patterns of functional connectivity, suggesting a shared functional subnetwork. We find considerable overlap between SVN and DMN in subregions of central ventromedial prefrontal cortex (cVMPFC) and dorsal posterior cingulate cortex (dPCC). Further, our findings show that similar patterns of bidirectional functional connectivity between cVMPFC and dPCC are present in both networks. We discuss ways in which our understanding of how subjective value (SV) is computed and represented in the brain can be synthesized with what we know about the DMN, mind-wandering, and self-referential processing in light of our findings.
Dysfunctional default mode network and executive control network in people with Internet gaming disorder: Independent component analysis under a probability discounting task.

PubMed

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.
Three-mode mode-division-multiplexing passive optical network over 12-km low mode-crosstalk FMF using all-fiber mode MUX/DEMUX

NASA Astrophysics Data System (ADS)

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

2017-01-01

We propose three-mode mode-division-multiplexing passive optical network (MDM-PON) based on low mode-crosstalk few-mode fiber (FMF) and all-fiber mode multiplexer/demultiplexer (MUX/DEMUX). The FMF with step-index profile is designed and fabricated for effectively three-independent-spatial-mode transmission and low mode-crosstalk for MDM-PON transmission. The all-fiber mode MUX/DEMUX are composed of cascaded mode selective couplers (MSCs), which simultaneously multiplex or demultiplex multiple modes. Based on the low mode-crosstalk of the FMF and all-fiber mode MUX/DEMUX, each optical network unit (ONU) communicates with the optical line terminal (OLT) independently utilizing a different optical linearly polarized (LP) spatial mode in MDM-PON system. We experimentally demonstrate MDM-PON transmission of three independent-spatial-modes over 12-km FMF with 10-Gb/s optical on-off keying (OOK) signal and direct detection.
Prestimulus default mode activity influences depth of processing and recognition in an emotional memory task.

PubMed

Soravia, Leila M; Witmer, Joëlle S; Schwab, Simon; Nakataki, Masahito; Dierks, Thomas; Wiest, Roland; Henke, Katharina; Federspiel, Andrea; Jann, Kay

2016-03-01

Low self-referential thoughts are associated with better concentration, which leads to deeper encoding and increases learning and subsequent retrieval. There is evidence that being engaged in externally rather than internally focused tasks is related to low neural activity in the default mode network (DMN) promoting open mind and the deep elaboration of new information. Thus, reduced DMN activity should lead to enhanced concentration, comprehensive stimulus evaluation including emotional categorization, deeper stimulus processing, and better long-term retention over one whole week. In this fMRI study, we investigated brain activation preceding and during incidental encoding of emotional pictures and on subsequent recognition performance. During fMRI, 24 subjects were exposed to 80 pictures of different emotional valence and subsequently asked to complete an online recognition task one week later. Results indicate that neural activity within the medial temporal lobes during encoding predicts subsequent memory performance. Moreover, a low activity of the default mode network preceding incidental encoding leads to slightly better recognition performance independent of the emotional perception of a picture. The findings indicate that the suppression of internally-oriented thoughts leads to a more comprehensive and thorough evaluation of a stimulus and its emotional valence. Reduced activation of the DMN prior to stimulus onset is associated with deeper encoding and enhanced consolidation and retrieval performance even one week later. Even small prestimulus lapses of attention influence consolidation and subsequent recognition performance. © 2015 Wiley Periodicals, Inc.
Regional GABA Concentrations Modulate Inter-network Resting-state Functional Connectivity.

PubMed

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

2018-03-28

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

PubMed Central

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

2014-01-01

IMPORTANCE Interactions of large-scale brain networks may underlie cognitive dysfunctions in psychiatric and addictive disorders. OBJECTIVES 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. DESIGN, SETTING, AND PARTICIPANTS 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. INTERVENTIONS Twenty-four hours of abstinence vs smoking satiety. MAIN OUTCOMES AND MEASURES Inter-network connectivity strength (primary) and the relationship with subjective, behavioral, and neural measures of nicotine withdrawal during abstinence vs smoking satiety states (secondary). RESULTS 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). CONCLUSIONS AND RELEVANCE 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. PMID:24622915
Neural Network Substorm Identification: Enabling TREx Sensor Web Modes

NASA Astrophysics Data System (ADS)

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.

Fused-fiber-based 3-dB mode insensitive power splitters for few-mode optical fiber networks

NASA Astrophysics Data System (ADS)

Ren, Fang; Huang, Xiaoshan; Wang, Jianping

2017-11-01

We propose a 3-dB mode insensitive power splitter (MIPS) capable of broadcasting and combining optical signals. It is fabricated with two identical few-mode fibers (FMFs) by a heating and pulling technique. The mode-dependent power transfer characteristic as a function of pulling length is investigated. For exploiting its application, we experimentally demonstrate both FMF-based transmissive and reflective star couplers consisting of multiple 3-dB mode insensitive power splitters, which perform broadcasting and routing signals in few-mode optical fiber networks such as mode-division multiplexing (MDM) local area networks using star topology. For experimental demonstration, optical on-off keying signals at 10 Gb/s carried on three spatial modes are successfully processed with open and clear eye diagrams. Measured bit error ratio results show reasonable power penalties. It is found that a reflective star coupler in MDM networks can reduce half of the total amount of required fibers comparing to that of a transmissive star coupler. This MIPS is more efficient, more reliable, more flexible, and more cost-effective for future expansion and application in few-mode optical fiber networks.
Neighborhoods and Adolescent Health-Risk Behavior: An Ecological Network Approach1

PubMed Central

Browning, Christopher R.; Soller, Brian; Jackson, Aubrey L.

2014-01-01

This study integrates insights from social network analysis, activity space perspectives, and theories of urban and spatial processes to present an innovative approach to neighborhood effects on health-risk behavior among youth. We suggest spatial patterns of neighborhood residents’ non-home routine activities may be conceptualized as ecological, or “eco”-networks, which are two-mode networks that indirectly link residents through socio-spatial overlap in routine activities. We further argue structural configurations of eco-networks are consequential for youth’s behavioral health. In this study we focus on a key structural feature of eco-networks—the neighborhood-level extent to which households share two or more activity locations, or eco-network reinforcement—and its association with two dimensions of health-risk behavior, substance use and delinquency/sexual activity. Using geographic data on non-home routine activity locations among respondents from the Los Angeles Family and Neighborhood Survey (L.A.FANS), we constructed neighborhood-specific eco-networks by connecting sampled households to “activity clusters,” which are sets of spatially-proximate activity locations. We then measured eco-network reinforcement and examined its association with adolescent dimensions of health risk behavior employing a sample of 830 youth ages 12-17 nested in 65 census tracts. We also examined whether neighborhood-level social processes (collective efficacy and intergenerational closure) mediate the association between eco-network reinforcement and the outcomes considered. Results indicated eco-network reinforcement exhibits robust negative associations with both substance use and delinquency/sexual activity scales. Eco-network reinforcement effects were not explained by potential mediating variables. In addition to introducing a novel theoretical and empirical approach to neighborhood effects on youth, our findings highlight the importance of eco-network reinforcement for adolescent behavioral health. PMID:25011958
The prestimulus default mode network state predicts cognitive task performance levels on a mental rotation task.

PubMed

Kamp, Tabea; Sorger, Bettina; Benjamins, Caroline; Hausfeld, Lars; Goebel, Rainer

2018-06-22

Linking individual task performance to preceding, regional brain activation is an ongoing goal of neuroscientific research. Recently, it could be shown that the activation and connectivity within large-scale brain networks prior to task onset influence performance levels. More specifically, prestimulus default mode network (DMN) effects have been linked to performance levels in sensory near-threshold tasks, as well as cognitive tasks. However, it still remains uncertain how the DMN state preceding cognitive tasks affects performance levels when the period between task trials is long and flexible, allowing participants to engage in different cognitive states. We here investigated whether the prestimulus activation and within-network connectivity of the DMN are predictive of the correctness and speed of task performance levels on a cognitive (match-to-sample) mental rotation task, employing a sparse event-related functional magnetic resonance imaging (fMRI) design. We found that prestimulus activation in the DMN predicted the speed of correct trials, with a higher amplitude preceding correct fast response trials compared to correct slow response trials. Moreover, we found higher connectivity within the DMN before incorrect trials compared to correct trials. These results indicate that pre-existing activation and connectivity states within the DMN influence task performance on cognitive tasks, both effecting the correctness and speed of task execution. The findings support existing theories and empirical work on relating mind-wandering and cognitive task performance to the DMN and expand these by establishing a relationship between the prestimulus DMN state and the speed of cognitive task performance. © 2018 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.
An Energy-Efficient ASIC for Wireless Body Sensor Networks in Medical Applications.

PubMed

Xiaoyu Zhang; Hanjun Jiang; Lingwei Zhang; Chun Zhang; Zhihua Wang; Xinkai Chen

2010-02-01

An energy-efficient application-specific integrated circuit (ASIC) featured with a work-on-demand protocol is designed for wireless body sensor networks (WBSNs) in medical applications. Dedicated for ultra-low-power wireless sensor nodes, the ASIC consists of a low-power microcontroller unit (MCU), a power-management unit (PMU), reconfigurable sensor interfaces, communication ports controlling a wireless transceiver, and an integrated passive radio-frequency (RF) receiver with energy harvesting ability. The MCU, together with the PMU, provides quite flexible communication and power-control modes for energy-efficient operations. The always-on passive RF receiver with an RF energy harvesting block offers the sensor nodes the capability of work-on-demand with zero standby power. Fabricated in standard 0.18-¿m complementary metal-oxide semiconductor technology, the ASIC occupies a die area of 2 mm × 2.5 mm. A wireless body sensor network sensor-node prototype using this ASIC only consumes < 10-nA current under the passive standby mode, and < 10 ¿A under the active standby mode, when supplied by a 3-V battery.
Task positive and default mode networks during a working memory in children with primary monosymptomatic nocturnal enuresis and healthy controls.

PubMed

Zhang, Kaihua; Ma, Jun; Lei, Du; Wang, Mengxing; Zhang, Jilei; Du, Xiaoxia

2015-10-01

Nocturnal enuresis is a common developmental disorder in children, and primary monosymptomatic nocturnal enuresis (PMNE) is the dominant subtype. This study investigated brain functional abnormalities that are specifically related to working memory in children with PMNE using function magnetic resonance imaging (fMRI) in combination with an n-back task. Twenty children with PMNE and 20 healthy children, group-matched for age and sex, participated in this experiment. Several brain regions exhibited reduced activation during the n-back task in children with PMNE, including the right precentral gyrus and the right inferior parietal lobule extending to the postcentral gyrus. Children with PMNE exhibited decreased cerebral activation in the task-positive network, increased task-related cerebral deactivation during a working memory task, and longer response times. Patients exhibited different brain response patterns to different levels of working memory and tended to compensate by greater default mode network deactivation to sustain normal working memory function. Our results suggest that children with PMNE have potential working memory dysfunction.
Functional network dysfunction in anxiety and anxiety disorders

PubMed Central

Sylvester, C.M.; Corbetta, M.; Raichle, M.E.; Rodebaugh, T.; Schlaggar, B.L.; Sheline, Y.I.; Zorumski, C.F.; Lenze, E.J.

2012-01-01

A recent paradigm shift in systems neuroscience is the division of the human brain into functional networks. Functional networks are collections of brain regions with strongly correlated activity both at rest and during cognitive tasks, and each network is believed to implement a different aspect of cognition. Here, we propose that anxiety disorders and high trait anxiety are associated with a particular pattern of functional network dysfunction: increased functioning of the cingulo-opercular and ventral attention networks as well as decreased functioning of the fronto-parietal and default mode networks. This functional network model can be used to differentiate the pathology of anxiety disorders from other psychiatric illnesses such as major depression and provides targets for novel treatment strategies. PMID:22658924
Understanding spatial and temporal patterning of astrocyte calcium transients via interactions between network transport and extracellular diffusion

NASA Astrophysics Data System (ADS)

Shtrahman, E.; Maruyama, D.; Olariu, E.; Fink, C. G.; Zochowski, M.

2017-02-01

Astrocytes form interconnected networks in the brain and communicate via calcium signaling. We investigate how modes of coupling between astrocytes influence the spatio-temporal patterns of calcium signaling within astrocyte networks and specifically how these network interactions promote coordination within this group of cells. To investigate these complex phenomena, we study reduced cultured networks of astrocytes and neurons. We image the spatial temporal patterns of astrocyte calcium activity and quantify how perturbing the coupling between astrocytes influences astrocyte activity patterns. To gain insight into the pattern formation observed in these cultured networks, we compare the experimentally observed calcium activity patterns to the patterns produced by a reduced computational model, where we represent astrocytes as simple units that integrate input through two mechanisms: gap junction coupling (network transport) and chemical release (extracellular diffusion). We examine the activity patterns in the simulated astrocyte network and their dependence upon these two coupling mechanisms. We find that gap junctions and extracellular chemical release interact in astrocyte networks to modulate the spatiotemporal patterns of their calcium dynamics. We show agreement between the computational and experimental findings, which suggests that the complex global patterns can be understood as a result of simple local coupling mechanisms.
Spatial-spectral flexible optical networking: enabling switching solutions for a simplified and efficient SDM network platform

NASA Astrophysics Data System (ADS)

Tomkos, I.; Zakynthinos, P.; Klonidis, D.; Marom, D.; Sygletos, S.; Ellis, A.; Salvadori, E.; Siracusa, D.; Angelou, M.; Papastergiou, G.; Psaila, N.; Ferran, J. F.; Ben-Ezra, S.; Jimenez, F.; Fernández-Palacios, J. P.

2013-12-01

The traffic carried by core optical networks grows at a steady but remarkable pace of 30-40% year-over-year. Optical transmissions and networking advancements continue to satisfy the traffic requirements by delivering the content over the network infrastructure in a cost and energy efficient manner. Such core optical networks serve the information traffic demands in a dynamic way, in response to requirements for shifting of traffics demands, both temporally (day/night) and spatially (business district/residential). However as we are approaching fundamental spectral efficiency limits of singlemode fibers, the scientific community is pursuing recently the development of an innovative, all-optical network architecture introducing the spatial degree of freedom when designing/operating future transport networks. Spacedivision- multiplexing through the use of bundled single mode fibers, and/or multi-core fibers and/or few-mode fibers can offer up to 100-fold capacity increase in future optical networks. The EU INSPACE project is working on the development of a complete spatial-spectral flexible optical networking solution, offering the network ultra-high capacity, flexibility and energy efficiency required to meet the challenges of delivering exponentially growing traffic demands in the internet over the next twenty years. In this paper we will present the motivation and main research activities of the INSPACE consortium towards the realization of the overall project solution.
Pattern Formation on Networks: from Localised Activity to Turing Patterns

PubMed Central

McCullen, Nick; Wagenknecht, Thomas

2016-01-01

Networks of interactions between competing species are used to model many complex systems, such as in genetics, evolutionary biology or sociology and knowledge of the patterns of activity they can exhibit is important for understanding their behaviour. The emergence of patterns on complex networks with reaction-diffusion dynamics is studied here, where node dynamics interact via diffusion via the network edges. Through the application of a generalisation of dynamical systems analysis this work reveals a fundamental connection between small-scale modes of activity on networks and localised pattern formation seen throughout science, such as solitons, breathers and localised buckling. The connection between solutions with a single and small numbers of activated nodes and the fully developed system-scale patterns are investigated computationally using numerical continuation methods. These techniques are also used to help reveal a much larger portion of of the full number of solutions that exist in the system at different parameter values. The importance of network structure is also highlighted, with a key role being played by nodes with a certain so-called optimal degree, on which the interaction between the reaction kinetics and the network structure organise the behaviour of the system. PMID:27273339
[Changes of brain pain center and default mode network an electro acupuncture in Weizhong and Dachangshu acupoints: a task-fMRI study].

PubMed

Zhou, S; Cao, H X; Yu, L C; Jin, Y J; Jia, R H; Wen, Y R; Chen, X F

2016-02-23

To investigate the functional brain pain center and default mode network response to electro acupuncture stimulate in weizhong acupoints(BL40) and dachangshu acupoints(BL25). During January to February 2015, volunteers were enrolled in this study from the staff and student interns of Gansu Province Traditional Chinese Medicine Hospital. A total of 20 healthy, right-handed subjects, male 9, female 11, age (23±3) years, participated in this study. Block design task functional magnetic resonance imaging(fMRI) 3.0 T was performed in all subjects by electro acupuncture stimulating at BL40 and BL25 from the same experienced acupuncturist.The needle connected electric acupuncture apparatus through tow long coaxial-cable. A block design with five 120 s blocks of rest time (OFF block, electric acupuncture turn off ) interspersed between five 60 s blocks of stimulation (ON block, electric acupuncture turn on) fMRI scan. Magnetic resonance data of brain function was collected and FSL(fMRI Software Library) software was used to analyze the data. All subjects' data were analyzed except 2 cases whose head movement were more than 2 mm. Activated brain function regions by electro acupuncture stimulate included temporal lobe lateral sulcus, lobus insularis, thalamus, supramarginal gyrus, prefrontal medial frontal gyrus. Negative activated brain regions included middle frontal gyrus, parahippocampal gyrus, cingulate cortex abdominal segment, parietal cortex.The functional pain central and default mode network were changed when electro acupuncture stimulate in(BL40) and(BL25). There are several brain activation regions and negative activated brain regions when administering electro acupuncture stimulation at BL40 and BL25.
Functional alterations of fronto-limbic circuit and default mode network systems in first-episode, drug-naïve patients with major depressive disorder: A meta-analysis of resting-state fMRI data.

PubMed

Zhong, Xue; Pu, Weidan; Yao, Shuqiao

2016-12-01

The neurobiological mechanisms of depression are increasingly being explored through resting-state brain imaging studies. However, resting-state fMRI findings have varied, perhaps because of differences between study populations, which included the disorder course and medication use. The aim of our study was to integrate studies of resting-state fMRI and explore the alterations of abnormal brain activity in first-episode, drug-naïve patients with major depressive disorder. Relevant imaging reports in English were searched, retrieved, selected and subjected to analysis by activation likelihood estimation, a coordinate-based meta-analysis technique (final sample, 31 studies). Coordinates extracted from the original reports were assigned to two categories based on effect directionality. Compared with healthy controls, the first-episode, medication-naïve major depressive disorder patients showed decreased brain activity in the dorsolateral prefrontal cortex, superior temporal gyrus, posterior precuneus, and posterior cingulate, as well as in visual areas within the occipital lobe, lingual gyrus, and fusiform gyrus, and increased activity in the putamen and anterior precuneus. Not every study that has reported relevant data met the inclusion criteria. Resting-state functional alterations were located mainly in the fronto-limbic system, including the dorsolateral prefrontal cortex and putamen, and in the default mode network, namely the precuneus and superior/middle temporal gyrus. Abnormal functional alterations of the fronto-limbic circuit and default mode network may be characteristic of first-episode, drug-naïve major depressive disorder patients. Copyright © 2016 Elsevier B.V. All rights reserved.
Cascading network failure across the Alzheimer’s disease spectrum

PubMed Central

Knopman, David S.; Gunter, Jeffrey L.; Graff-Radford, Jonathan; Vemuri, Prashanthi; Boeve, Bradley F.; Petersen, Ronald C.; Weiner, Michael W.; Jack, Clifford R.

2016-01-01

Abstract Complex biological systems are organized across various spatiotemporal scales with particular scientific disciplines dedicated to the study of each scale (e.g. genetics, molecular biology and cognitive neuroscience). When considering disease pathophysiology, one must contemplate the scale at which the disease process is being observed and how these processes impact other levels of organization. Historically Alzheimer’s disease has been viewed as a disease of abnormally aggregated proteins by pathologists and molecular biologists and a disease of clinical symptoms by neurologists and psychologists. Bridging the divide between these scales has been elusive, but the study of brain networks appears to be a pivotal inroad to accomplish this task. In this study, we were guided by an emerging systems-based conceptualization of Alzheimer’s disease and investigated changes in brain networks across the disease spectrum. The default mode network has distinct subsystems with unique functional-anatomic connectivity, cognitive associations, and responses to Alzheimer’s pathophysiology. These distinctions provide a window into the systems-level pathophysiology of Alzheimer’s disease. Using clinical phenotyping, metadata, and multimodal neuroimaging data from the Alzheimer’s Disease Neuroimaging Initiative, we characterized the pattern of default mode network subsystem connectivity changes across the entire disease spectrum (n = 128). The two main findings of this paper are (i) the posterior default mode network fails before measurable amyloid plaques and appears to initiate a connectivity cascade that continues throughout the disease spectrum; and (ii) high connectivity between the posterior default mode network and hubs of high connectivity (many located in the frontal lobe) is associated with amyloid accumulation. These findings support a system model best characterized by a cascading network failure—analogous to cascading failures seen in power grids triggered by local overloads proliferating to downstream nodes eventually leading to widespread power outages, or systems failures. The failure begins in the posterior default mode network, which then shifts processing burden to other systems containing prominent connectivity hubs. This model predicts a connectivity ‘overload’ that precedes structural and functional declines and recasts the interpretation of high connectivity from that of a positive compensatory phenomenon to that of a load-shifting process transiently serving a compensatory role. It is unknown whether this systems-level pathophysiology is the inciting event driving downstream molecular events related to synaptic activity embedded in these systems. Possible interpretations include that the molecular-level events drive the network failure, a pathological interaction between the network-level and the molecular-level, or other upstream factors are driving both. PMID:26586695
Musical Creativity “Revealed” in Brain Structure: Interplay between Motor, Default Mode, and Limbic Networks

PubMed Central

Bashwiner, David M.; Wertz, Christopher J.; Flores, Ranee A.; Jung, Rex E.

2016-01-01

Creative behaviors are among the most complex that humans engage in, involving not only highly intricate, domain-specific knowledge and skill, but also domain-general processing styles and the affective drive to create. This study presents structural imaging data indicating that musically creative people (as indicated by self-report) have greater cortical surface area or volume in a) regions associated with domain-specific higher-cognitive motor activity and sound processing (dorsal premotor cortex, supplementary and pre-supplementary motor areas, and planum temporale), b) domain-general creative-ideation regions associated with the default mode network (dorsomedial prefrontal cortex, middle temporal gyrus, and temporal pole), and c) emotion-related regions (orbitofrontal cortex, temporal pole, and amygdala). These findings suggest that domain-specific musical expertise, default-mode cognitive processing style, and intensity of emotional experience might all coordinate to motivate and facilitate the drive to create music. PMID:26888383
A generalized network flow model for the multi-mode resource-constrained project scheduling problem with discounted cash flows

NASA Astrophysics Data System (ADS)

Chen, Miawjane; Yan, Shangyao; Wang, Sin-Siang; Liu, Chiu-Lan

2015-02-01

An effective project schedule is essential for enterprises to increase their efficiency of project execution, to maximize profit, and to minimize wastage of resources. Heuristic algorithms have been developed to efficiently solve the complicated multi-mode resource-constrained project scheduling problem with discounted cash flows (MRCPSPDCF) that characterize real problems. However, the solutions obtained in past studies have been approximate and are difficult to evaluate in terms of optimality. In this study, a generalized network flow model, embedded in a time-precedence network, is proposed to formulate the MRCPSPDCF with the payment at activity completion times. Mathematically, the model is formulated as an integer network flow problem with side constraints, which can be efficiently solved for optimality, using existing mathematical programming software. To evaluate the model performance, numerical tests are performed. The test results indicate that the model could be a useful planning tool for project scheduling in the real world.
Finding elementary flux modes in metabolic networks based on flux balance analysis and flux coupling analysis: application to the analysis of Escherichia coli metabolism.

PubMed

Tabe-Bordbar, Shayan; Marashi, Sayed-Amir

2013-12-01

Elementary modes (EMs) are steady-state metabolic flux vectors with minimal set of active reactions. Each EM corresponds to a metabolic pathway. Therefore, studying EMs is helpful for analyzing the production of biotechnologically important metabolites. However, memory requirements for computing EMs may hamper their applicability as, in most genome-scale metabolic models, no EM can be computed due to running out of memory. In this study, we present a method for computing randomly sampled EMs. In this approach, a network reduction algorithm is used for EM computation, which is based on flux balance-based methods. We show that this approach can be used to recover the EMs in the medium- and genome-scale metabolic network models, while the EMs are sampled in an unbiased way. The applicability of such results is shown by computing “estimated” control-effective flux values in Escherichia coli metabolic network.
Combinatorial complexity of pathway analysis in metabolic networks.

PubMed

Klamt, Steffen; Stelling, Jörg

2002-01-01

Elementary flux mode analysis is a promising approach for a pathway-oriented perspective of metabolic networks. However, in larger networks it is hampered by the combinatorial explosion of possible routes. In this work we give some estimations on the combinatorial complexity including theoretical upper bounds for the number of elementary flux modes in a network of a given size. In a case study, we computed the elementary modes in the central metabolism of Escherichia coli while utilizing four different substrates. Interestingly, although the number of modes occurring in this complex network can exceed half a million, it is still far below the upper bound. Hence, to a certain extent, pathway analysis of central catabolism is feasible to assess network properties such as flexibility and functionality.
The Psychedelic State Induced by Ayahuasca Modulates the Activity and Connectivity of the Default Mode Network

PubMed Central

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. PMID:25693169
Modeling fluctuations in default-mode brain network using a spiking neural network.

PubMed

Yamanishi, Teruya; Liu, Jian-Qin; Nishimura, Haruhiko

2012-08-01

Recently, numerous attempts have been made to understand the dynamic behavior of complex brain systems using neural network models. The fluctuations in blood-oxygen-level-dependent (BOLD) brain signals at less than 0.1 Hz have been observed by functional magnetic resonance imaging (fMRI) for subjects in a resting state. This phenomenon is referred to as a "default-mode brain network." In this study, we model the default-mode brain network by functionally connecting neural communities composed of spiking neurons in a complex network. Through computational simulations of the model, including transmission delays and complex connectivity, the network dynamics of the neural system and its behavior are discussed. The results show that the power spectrum of the modeled fluctuations in the neuron firing patterns is consistent with the default-mode brain network's BOLD signals when transmission delays, a characteristic property of the brain, have finite values in a given range.
Cost effective Internet access and video conferencing for a community cancer network.

PubMed Central

London, J. W.; Morton, D. E.; Marinucci, D.; Catalano, R.; Comis, R. L.

1995-01-01

Utilizing the ubiquitous personal computer as a platform, and Integrated Services Digital Network (ISDN) communications, cost effective medical information access and consultation can be provided for physicians at geographically remote sites. Two modes of access are provided: information retrieval via the Internet, and medical consultation video conferencing. Internet access provides general medical information such as current treatment options, literature citations, and active clinical trials. During video consultations, radiographic and pathology images, and medical text reports (e.g., history and physical, pathology, radiology, clinical laboratory reports), may be viewed and simultaneously annotated by either video conference participant. Both information access modes have been employed by physicians at community hospitals which are members of the Jefferson Cancer Network, and oncologists at Thomas Jefferson University Hospital. This project has demonstrated the potential cost effectiveness and benefits of this technology. Images Figure 1 Figure 2 Figure 3 PMID:8563397
Childhood poverty and stress reactivity are associated with aberrant functional connectivity in default mode network.

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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.
The "Quasar" Network Observations in e-VLBI Mode Within the Russian Domestic VLBI Programs

NASA Technical Reports Server (NTRS)

Finkelstein, Andrey; Ipatov, Alexander; Kaidanovsky, Michael; Bezrukov, Ilia; Mikhailov, Andrey; Salnikov, Alexander; Surkis, Igor; Skurikhina, Elena

2010-01-01

The purpose of the Russian VLBI "Quasar" Network is to carry out astrometrical and geodynamical investigations. Since 2006 purely domestic observational programs with data processing at the IAA correlator have been carried out. To maintain these geodynamical programs e-VLBI technology is being developed and tested. This paper describes the IAA activity of developing a real-time VLBI system using high-speed digital communication links.
Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

DOE PAGES

Aziz, H. M. Abdul; Nagle, Nicholas N.; Morton, April M.; ...

2017-02-06

Here, this study finds the effects of traffic safety, walk-bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk-bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the localmore » authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Furthermore, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The findings will help to make smart investment decisions in context of building sustainable transportation systems accounting for active transportation.« less
Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

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

Aziz, H. M. Abdul; Nagle, Nicholas N.; Morton, April M.

Here, this study finds the effects of traffic safety, walk-bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk-bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the localmore » authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Furthermore, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The findings will help to make smart investment decisions in context of building sustainable transportation systems accounting for active transportation.« less
Altered Functional Connectivity of the Default Mode Network in Low-Empathy Subjects

PubMed Central

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

2017-01-01

Empathy is the ability to identify with or make a vicariously experience of another person's feelings or thoughts based on memory and/or self-referential mental simulation. The default mode network in particular is related to self-referential empathy. In order to elucidate the possible neural mechanisms underlying empathy, we investigated the functional connectivity of the default mode network in subjects from a general population. Resting state functional magnetic resonance imaging data were acquired from 19 low-empathy subjects and 18 medium-empathy subjects. An independent component analysis was used to identify the default mode network, and differences in functional connectivity strength were compared between the two groups. The low-empathy group showed lower functional connectivity of the medial prefrontal cortex and anterior cingulate cortex (Brodmann areas 9 and 32) within the default mode network, compared to the medium-empathy group. The results of the present study suggest that empathy is related to functional connectivity of the medial prefrontal cortex/anterior cingulate cortex within the default mode network. Functional decreases in connectivity among low-empathy subjects may reflect an impairment of self-referential mental simulation. PMID:28792155
Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging.

PubMed

Voss, Michelle W; Weng, Timothy B; Burzynska, Agnieszka Z; Wong, Chelsea N; Cooke, Gillian E; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P; Olson, Erin A; McAuley, Edward; Kramer, Arthur F

2016-05-01

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the default mode network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. Copyright © 2015 Elsevier Inc. All rights reserved.
Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging

PubMed Central

Voss, Michelle W.; Weng, Timothy B.; Burzynska, Agnieszka Z.; Wong, Chelsea N.; Cooke, Gillian E.; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P.; Olson, Erin A.; McAuley, Edward; Kramer, Arthur F.

2015-01-01

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the Default Mode Network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. PMID:26493108
Ecological Networks and Community Attachment and Support Among Recently Resettled Refugees.

PubMed

Soller, Brian; Goodkind, Jessica R; Greene, R Neil; Browning, Christopher R; Shantzek, Cece

2018-03-25

Interventions aimed at enhancing mental health are increasingly centered around promoting community attachment and support. However, few have examined and tested the specific ecological factors that give rise to these key community processes. Drawing from insights from the ecological network perspective, we tested whether spatial and social overlap in routine activity settings (e.g., work, school, childcare) with fellow ethnic community members is associated with individuals' attachment to their ethnic communities and access to social resources embedded in their communities. Data on routine activity locations drawn from the Refugee Well-Being Project (based in a city in the Southwestern United States) were used to reconstruct the ecological networks of recently resettled refugee communities, which were two-mode networks that comprise individuals and their routine activity locations. Results indicated that respondents' community attachment and support increased with their ecological network extensity-which taps the extent to which respondents share routine activity locations with other community members. Our study highlights a key ecological process that potentially enhances individuals' ethnic community attachment that extends beyond residential neighborhoods. © Society for Community Research and Action 2018.
Abnormal neural activities of directional brain networks in patients with long-term bilateral hearing loss.

PubMed

Xu, Long-Chun; Zhang, Gang; Zou, Yue; Zhang, Min-Feng; Zhang, Dong-Sheng; Ma, Hua; Zhao, Wen-Bo; Zhang, Guang-Yu

2017-10-13

The objective of the study is to provide some implications for rehabilitation of hearing impairment by investigating changes of neural activities of directional brain networks in patients with long-term bilateral hearing loss. Firstly, we implemented neuropsychological tests of 21 subjects (11 patients with long-term bilateral hearing loss, and 10 subjects with normal hearing), and these tests revealed significant differences between the deaf group and the controls. Then we constructed the individual specific virtual brain based on functional magnetic resonance data of participants by utilizing effective connectivity and multivariate regression methods. We exerted the stimulating signal to the primary auditory cortices of the virtual brain and observed the brain region activations. We found that patients with long-term bilateral hearing loss presented weaker brain region activations in the auditory and language networks, but enhanced neural activities in the default mode network as compared with normally hearing subjects. Especially, the right cerebral hemisphere presented more changes than the left. Additionally, weaker neural activities in the primary auditor cortices were also strongly associated with poorer cognitive performance. Finally, causal analysis revealed several interactional circuits among activated brain regions, and these interregional causal interactions implied that abnormal neural activities of the directional brain networks in the deaf patients impacted cognitive function.
Stuck in default mode: inefficient cross-frequency synchronization may lead to age-related short-term memory decline.

PubMed

Pinal, Diego; Zurrón, Montserrat; Díaz, Fernando; Sauseng, Paul

2015-04-01

Aging-related decline in short-term memory capacity seems to be caused by deficient balancing of task-related and resting state brain networks activity; however, the exact neural mechanism underlying this deficit remains elusive. Here, we studied brain oscillatory activity in healthy young and old adults during visual information maintenance in a delayed match-to-sample task. Particular emphasis was on long range phase:amplitude coupling of frontal alpha (8-12 Hz) and posterior fast oscillatory activity (>30 Hz). It is argued that through posterior fast oscillatory activity nesting into the excitatory or the inhibitory phase of frontal alpha wave, long-range networks can be efficiently coupled or decoupled, respectively. On the basis of this mechanism, we show that healthy, elderly participants exhibit a lack of synchronization in task-relevant networks while maintaining synchronized regions of the resting state network. Lacking disconnection of this resting state network is predictive of aging-related short-term memory decline. These results support the idea of inefficient orchestration of competing brain networks in the aging human brain and identify the neural mechanism responsible for this control breakdown. Copyright © 2015 Elsevier Inc. All rights reserved.
Cognitive control in the self-regulation of physical activity and sedentary behavior

PubMed Central

Buckley, Jude; Cohen, Jason D.; Kramer, Arthur F.; McAuley, Edward; Mullen, Sean P.

2014-01-01

Cognitive control of physical activity and sedentary behavior is receiving increased attention in the neuroscientific and behavioral medicine literature as a means of better understanding and improving the self-regulation of physical activity. Enhancing individuals’ cognitive control capacities may provide a means to increase physical activity and reduce sedentary behavior. First, this paper reviews emerging evidence of the antecedence of cognitive control abilities in successful self-regulation of physical activity, and in precipitating self-regulation failure that predisposes to sedentary behavior. We then highlight the brain networks that may underpin the cognitive control and self-regulation of physical activity, including the default mode network, prefrontal cortical networks and brain regions and pathways associated with reward. We then discuss research on cognitive training interventions that document improved cognitive control and that suggest promise of influencing physical activity regulation. Key cognitive training components likely to be the most effective at improving self-regulation are also highlighted. The review concludes with suggestions for future research. PMID:25324754
Rethinking passive transport: bus fare exemptions and young people's wellbeing.

PubMed

Jones, Alasdair; Steinbach, Rebecca; Roberts, Helen; Goodman, Anna; Green, Judith

2012-05-01

Much recent public health research has emphasised the health impacts for young people of 'active travel' modes, typically defined as walking and cycling. Less research has focused on public transport modes. Drawing on qualitative data, we examine the links between bus travel and wellbeing in London, where young people currently have free bus travel. Our findings indicate that bus travel can be both a physically and socially active experience for young people. We suggest a more nuanced understanding of 'active travel' is now needed, alongside greater attention to urban public transport networks as key sites that impact on important determinants of wellbeing such as independent mobility and social inclusion. Copyright © 2012 Elsevier Ltd. All rights reserved.
Structural connectivity allows for multi-threading during rest: the structure of the cortex leads to efficient alternation between resting state exploratory behavior and default mode processing.

PubMed

Senden, Mario; Goebel, Rainer; Deco, Gustavo

2012-05-01

Despite the absence of stimulation or task conditions the cortex exhibits highly structured spatio-temporal activity patterns. These patterns are known as resting state networks (RSNs) and emerge as low-frequency fluctuations (<0.1 Hz) observed in the fMRI signal of human subjects during rest. We are interested in the relationship between structural connectivity of the cortex and the fluctuations exhibited during resting conditions. We are especially interested in the effect of degree of connectivity on resting state dynamics as the default mode network (DMN) is highly connected. We find in experimental resting fMRI data that the DMN is the functional network that is most frequently active and for the longest time. In large-scale computational simulations of the cortex based on the corresponding underlying DTI/DSI based neuroanatomical connectivity matrix, we additionally find a strong correlation between the mean degree of functional networks and the proportion of time they are active. By artificially modifying different types of neuroanatomical connectivity matrices in the model, we were able to demonstrate that only models based on structural connectivity containing hubs give rise to this relationship. We conclude that, during rest, the cortex alternates efficiently between explorations of its externally oriented functional repertoire and internally oriented processing as a consequence of the DMN's high degree of connectivity. Copyright © 2012 Elsevier Inc. All rights reserved.
Emotional faces and the default mode network.

PubMed

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.
Detection of the default mode network by an anisotropic analysis

NASA Astrophysics Data System (ADS)

Forero, Aura; Romero, Eduardo

2017-11-01

This document presents a proposal devoted to improve the detection of the default mode network (DMN) in resting state functional magnetic resonance imaging in noisy conditions caused by head movement. The proposed approach is inspired by the hierarchical treatment of information, in particular at the level of the brain basal ganglia. Essentially, the fact that information must be selected and reduced suggests propagation of information in the Central Nervous System (CNS) is anisotropic. Under this hypothesis, the reconstruction of information of activation should follow an anisotropic pattern. In this work, an anisotropic filter is used to recover the DMN that is perturbed by simulated motion artifacts. Results obtained show this approach outperforms the state-of-the-art methods by 5.93% PSNR.
The evolution analysis of listed companies co-holding non-listed financial companies based on two-mode heterogeneous networks

NASA Astrophysics Data System (ADS)

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

PubMed

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. A functional segregation of (left) parietal network nodes from the DMN and a rather segregated processing mode within the DMN might have positive implications/protective value for CD in patients with RE. Copyright © 2017 Elsevier Inc. All rights reserved.
Altered intrinsic organisation of brain networks implicated in attentional processes in adult attention-deficit/hyperactivity disorder: a resting-state study of attention, default mode and salience network connectivity.

PubMed

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

2016-06-01

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

PubMed Central

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

2016-01-01

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

PubMed

Lu, Shaojia; Pan, Fen; Gao, Weijia; Wei, Zhaoguo; Wang, Dandan; Hu, Shaohua; Huang, Manli; Xu, Yi; Li, Lingjiang

2017-10-03

The aim of this study was to investigate the relationship among childhood trauma, executive impairments, and altered resting-state brain function in young healthy adults. Twenty four subjects with childhood trauma and 24 age- and gender-matched subjects without childhood trauma were recruited. Executive function was assessed by a series of validated test procedures. Localized brain activity was evaluated by fractional amplitude of low frequency fluctuation (fALFF) method and compared between two groups. Areas with altered fALFF were further selected as seeds in subsequent functional connectivity analysis. Correlations of fALFF and connectivity values with severity of childhood trauma and executive dysfunction were analyzed as well. Subjects with childhood trauma exhibited impaired executive function as assessed by Wisconsin Card Sorting Test and Stroop Color Word Test. Traumatic individuals also showed increased fALFF in the right precuneus and decreased fALFF in the right superior temporal gyrus. Significant correlations of specific childhood trauma severity with executive dysfunction and fALFF value in the right precuneus were found in the whole sample. In addition, individuals with childhood trauma also exhibited diminished precuneus-based connectivity in default mode network with left ventromedial prefrontal cortex, left orbitofrontal cortex, and right cerebellum. Decreased default mode network connectivity was also associated with childhood trauma severity and executive dysfunction. The present findings suggest that childhood trauma is associated with executive deficits and aberrant default mode network functions even in healthy adults. Moreover, this study demonstrates that executive dysfunction is related to disrupted default mode network connectivity.

Intrinsic brain abnormalities in young healthy adults with childhood trauma: A resting-state functional magnetic resonance imaging study of regional homogeneity and functional connectivity.

PubMed

Lu, Shaojia; Gao, Weijia; Wei, Zhaoguo; Wang, Dandan; Hu, Shaohua; Huang, Manli; Xu, Yi; Li, Lingjiang

2017-06-01

Childhood trauma confers great risk for the development of multiple psychiatric disorders; however, the neural basis for this association is still unknown. The present resting-state functional magnetic resonance imaging study aimed to detect the effects of childhood trauma on brain function in a group of young healthy adults. In total, 24 healthy individuals with childhood trauma and 24 age- and sex-matched adults without childhood trauma were recruited. Each participant underwent resting-state functional magnetic resonance imaging scanning. Intra-regional brain activity was evaluated by regional homogeneity method and compared between groups. Areas with altered regional homogeneity were further selected as seeds in subsequent functional connectivity analysis. Statistical analyses were performed by setting current depression and anxiety as covariates. Adults with childhood trauma showed decreased regional homogeneity in bilateral superior temporal gyrus and insula, and the right inferior parietal lobule, as well as increased regional homogeneity in the right cerebellum and left middle temporal gyrus. Regional homogeneity values in the left middle temporal gyrus, right insula and right cerebellum were correlated with childhood trauma severity. In addition, individuals with childhood trauma also exhibited altered default mode network, cerebellum-default mode network and insula-default mode network connectivity when the left middle temporal gyrus, right cerebellum and right insula were selected as seed area, respectively. The present outcomes suggest that childhood trauma is associated with disturbed intrinsic brain function, especially the default mode network, in adults even without psychiatric diagnoses, which may mediate the relationship between childhood trauma and psychiatric disorders in later life.
Advanced information society(5)

NASA Astrophysics Data System (ADS)

Tanizawa, Ippei

Based on the advancement of information network technology information communication forms informationalized society giving significant impact on business activities and life style in it. The information network has been backed up technologically by development of computer technology and has got great contribution by enhanced computer technology and communication equipments. Information is transferred by digital and analog methods. Technical development which has brought out multifunctioned modems of communication equipments in analog mode, and construction of advanced information communication network which has come out by joint work of computer and communication under digital technique, are described. The trend in institutional matter and standardization of electrical communication is also described showing some examples of value-added network (VAN).
Altered Functional Connectivity of the Default Mode Network in Low-Empathy Subjects.

PubMed

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

2017-09-01

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

PubMed Central

Armstrong, Seiji; Morizur, Jean-François; Janousek, Jiri; Hage, Boris; Treps, Nicolas; Lam, Ping Koy; Bachor, Hans-A.

2012-01-01

Entanglement between large numbers of quantum modes is the quintessential resource for future technologies such as the quantum internet. Conventionally, the generation of multimode entanglement in optics requires complex layouts of beamsplitters and phase shifters in order to transform the input modes into entangled modes. Here we report the highly versatile and efficient generation of various multimode entangled states with the ability to switch between different linear optics networks in real time. By defining our modes to be combinations of different spatial regions of one beam, we may use just one pair of multi-pixel detectors in order to measure multiple entangled modes. We programme virtual networks that are fully equivalent to the physical linear optics networks they are emulating. We present results for N=2 up to N=8 entangled modes here, including N=2, 3, 4 cluster states. Our approach introduces the highly sought after attributes of flexibility and scalability to multimode entanglement. PMID:22929783
Intrinsic Neuronal Properties Switch the Mode of Information Transmission in Networks

PubMed Central

Gjorgjieva, Julijana; Mease, Rebecca A.; Moody, William J.; Fairhall, Adrienne L.

2014-01-01

Diverse ion channels and their dynamics endow single neurons with complex biophysical properties. These properties determine the heterogeneity of cell types that make up the brain, as constituents of neural circuits tuned to perform highly specific computations. How do biophysical properties of single neurons impact network function? We study a set of biophysical properties that emerge in cortical neurons during the first week of development, eventually allowing these neurons to adaptively scale the gain of their response to the amplitude of the fluctuations they encounter. During the same time period, these same neurons participate in large-scale waves of spontaneously generated electrical activity. We investigate the potential role of experimentally observed changes in intrinsic neuronal properties in determining the ability of cortical networks to propagate waves of activity. We show that such changes can strongly affect the ability of multi-layered feedforward networks to represent and transmit information on multiple timescales. With properties modeled on those observed at early stages of development, neurons are relatively insensitive to rapid fluctuations and tend to fire synchronously in response to wave-like events of large amplitude. Following developmental changes in voltage-dependent conductances, these same neurons become efficient encoders of fast input fluctuations over few layers, but lose the ability to transmit slower, population-wide input variations across many layers. Depending on the neurons' intrinsic properties, noise plays different roles in modulating neuronal input-output curves, which can dramatically impact network transmission. The developmental change in intrinsic properties supports a transformation of a networks function from the propagation of network-wide information to one in which computations are scaled to local activity. This work underscores the significance of simple changes in conductance parameters in governing how neurons represent and propagate information, and suggests a role for background synaptic noise in switching the mode of information transmission. PMID:25474701
Suppressing turbulence of self-propelling rods by strongly coupled passive particles.

PubMed

Su, Yen-Shuo; Wang, Hao-Chen; I, Lin

2015-03-01

The strong turbulence suppression, mainly for large-scale modes, of two-dimensional self-propelling rods, by increasing the long-range coupling strength Γ of low-concentration passive particles, is numerically demonstrated. It is found that large-scale collective rod motion in forms of swirls or jets is mainly contributed from well-aligned dense patches, which can push small poorly aligned rod patches and uncoupled passive particles. The more efficient momentum transfer and dissipation through increasing passive particle coupling leads to the formation of a more ordered and slowed down network of passive particles, which competes with coherent dense active rod clusters. The frustration of active rod alignment ordering and coherent motion by the passive particle network, which interrupt the inverse cascading of forming large-scale swirls, is the key for suppressing collective rod motion with scales beyond the interpassive distance, even in the liquid phase of passive particles. The loosely packed active rods are weakly affected by increasing passive particle coupling due to the weak rod-particle interaction. They mainly contribute to the small-scale modes and high-speed motion.
Patterns of Default Mode Network Deactivation in Obsessive Compulsive Disorder

PubMed Central

Gonçalves, Óscar F.; Soares, José Miguel; Carvalho, Sandra; Leite, Jorge; Ganho-Ávila, Ana; Fernandes-Gonçalves, Ana; Pocinho, Fernando; Carracedo, Angel; Sampaio, Adriana

2017-01-01

The objective of the present study was to research the patterns of Default Mode Network (DMN) deactivation in Obsessive Compulsive Disorder (OCD) in the transition between a resting and a non-rest emotional condition. Twenty-seven participants, 15 diagnosed with OCD and 12 healthy controls (HC), underwent a functional neuroimaging paradigm in which DMN brain activation in a resting condition was contrasted with activity during a non-rest condition consisting in the presentation of emotionally pleasant and unpleasant images. Results showed that HC, when compared with OCD, had a significant deactivation in two anterior nodes of the DMN (medial frontal and superior frontal) in the non-rest pleasant stimuli condition. Additional analysis for the whole brain, contrasting the resting condition with all the non-rest conditions grouped together, showed that, compared with OCD, HC had a significantly deactivation of a widespread brain network (superior frontal, insula, middle and superior temporal, putamen, lingual, cuneus, and cerebellum). Concluding, the present study found that OCD patients had difficulties with the deactivation of DMN even when the non-rest condition includes the presentation of emotional provoking stimuli, particularly evident for images with pleasant content. PMID:28287615
Architectures for Device Aware Network

DTIC Science & Technology

2005-03-01

68 b. PDA in DAN Mode ............................................................. 69 c. Cell Phone in DAN Mode...68 Figure 15. PDA in DAN Mode - Reduced Resolution Image ..................................... 69 Figure 16. Cell Phone in DAN Mode -No Image...computer, notebook computer, cell phone and a host of networked embedded systems) may have extremely differing capabilities and resources to retrieve and
UNUSUAL TRENDS IN SOLAR P-MODE FREQUENCIES DURING THE CURRENT EXTENDED MINIMUM

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

Tripathy, S. C.; Jain, K.; Hill, F.

2010-03-10

We investigate the behavior of the intermediate-degree mode frequencies of the Sun during the current extended minimum phase to explore the time-varying conditions in the solar interior. Using contemporaneous helioseismic data from the Global Oscillation Network Group (GONG) and the Michelson Doppler Imager (MDI), we find that the changes in resonant mode frequencies during the activity minimum period are significantly greater than the changes in solar activity as measured by different proxies. We detect a seismic minimum in MDI p-mode frequency shifts during 2008 July-August but no such signature is seen in mean shifts computed from GONG frequencies. We alsomore » analyze the frequencies of individual oscillation modes from GONG data as a function of latitude and observe a signature of the onset of the solar cycle 24 in early 2009. Thus, the intermediate-degree modes do not confirm the onset of the cycle 24 during late 2007 as reported from the analysis of the low-degree Global Oscillations at Low Frequency frequencies. Further, both the GONG and MDI frequencies show a surprising anti-correlation between frequencies and activity proxies during the current minimum, in contrast to the behavior during the minimum between cycles 22 and 23.« less
Brain system for mental orientation in space, time, and person.

PubMed

Peer, Michael; Salomon, Roy; Goldberg, Ilan; Blanke, Olaf; Arzy, Shahar

2015-09-01

Orientation is a fundamental mental function that processes the relations between the behaving self to space (places), time (events), and person (people). Behavioral and neuroimaging studies have hinted at interrelations between processing of these three domains. To unravel the neurocognitive basis of orientation, we used high-resolution 7T functional MRI as 16 subjects compared their subjective distance to different places, events, or people. Analysis at the individual-subject level revealed cortical activation related to orientation in space, time, and person in a precisely localized set of structures in the precuneus, inferior parietal, and medial frontal cortex. Comparison of orientation domains revealed a consistent order of cortical activity inside the precuneus and inferior parietal lobes, with space orientation activating posterior regions, followed anteriorly by person and then time. Core regions at the precuneus and inferior parietal lobe were activated for multiple orientation domains, suggesting also common processing for orientation across domains. The medial prefrontal cortex showed a posterior activation for time and anterior for person. Finally, the default-mode network, identified in a separate resting-state scan, was active for all orientation domains and overlapped mostly with person-orientation regions. These findings suggest that mental orientation in space, time, and person is managed by a specific brain system with a highly ordered internal organization, closely related to the default-mode network.
Default mode network activity in male adolescents with conduct and substance use disorder*

PubMed Central

Dalwani, Manish S.; Tregellas, Jason R.; Andrews-Hanna, Jessica R.; Mikulich-Gilbertson, Susan K.; Raymond, Kristen M.; Banich, Marie T.; Crowley, Thomas J.; Sakai, Joseph T.

2013-01-01

Background Adolescents with conduct disorder (CD) and substance use disorders (SUD) experience difficulty evaluating and regulating their behavior in anticipation of future consequences. Given the role of the brain's default mode network (DMN) in self-reflection and future thought, this study investigates whether DMN is altered in adolescents with CD and SUD, relative to controls. Methods Twenty adolescent males with CD and SUD and 20 male controls of similar ages underwent functional magnetic resonance imaging as they completed a risk-taking decision task. We used independent component analysis as a data-driven approach to identify the DMN spatial component in individual subjects. DMN activity was then compared between groups. Results Compared to controls, patients showed reduced activity in superior, medial and middle frontal gyrus (Brodmann area (BA) 10), retrosplenial cortex (BA 30) and lingual gyrus (BA 18), and bilateral middle temporal gryus (BA 21/22) - DMN regions thought to support self-referential evaluation, memory, foresight, and perspective taking. Furthermore, this pattern of reduced activity in patients remained robust after adjusting for the effects of depression and attention-deficit hyperactivity disorder (ADHD). Conversely, when not adjusting for effects of depression and ADHD, patients demonstrated greater DMN activity than controls solely in the cuneus (BA 19). Conclusions Collectively, these results suggest that comorbid CD and SUD in adolescents is characterized by atypical activity in brain regions thought to play an important role in introspective processing. These functional imbalances in brain networks may provide further insight into the neural underpinnings of conduct and substance use disorders. PMID:24210423
Holding-based network of nations based on listed energy companies: An empirical study on two-mode affiliation network of two sets of actors

NASA Astrophysics Data System (ADS)

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.
Spatiotemporal Filtering Using Principal Component Analysis and Karhunen-Loeve Expansion Approaches for Regional GPS Network Analysis

NASA Technical Reports Server (NTRS)

Dong, D.; Fang, P.; Bock, F.; Webb, F.; Prawirondirdjo, L.; Kedar, S.; Jamason, P.

2006-01-01

Spatial filtering is an effective way to improve the precision of coordinate time series for regional GPS networks by reducing so-called common mode errors, thereby providing better resolution for detecting weak or transient deformation signals. The commonly used approach to regional filtering assumes that the common mode error is spatially uniform, which is a good approximation for networks of hundreds of kilometers extent, but breaks down as the spatial extent increases. A more rigorous approach should remove the assumption of spatially uniform distribution and let the data themselves reveal the spatial distribution of the common mode error. The principal component analysis (PCA) and the Karhunen-Loeve expansion (KLE) both decompose network time series into a set of temporally varying modes and their spatial responses. Therefore they provide a mathematical framework to perform spatiotemporal filtering.We apply the combination of PCA and KLE to daily station coordinate time series of the Southern California Integrated GPS Network (SCIGN) for the period 2000 to 2004. We demonstrate that spatially and temporally correlated common mode errors are the dominant error source in daily GPS solutions. The spatial characteristics of the common mode errors are close to uniform for all east, north, and vertical components, which implies a very long wavelength source for the common mode errors, compared to the spatial extent of the GPS network in southern California. Furthermore, the common mode errors exhibit temporally nonrandom patterns.
Resting-state low-frequency fluctuations reflect individual differences in spoken language learning.

PubMed

Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping; Wong, Patrick C M

2016-03-01

A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The "competition" (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest--ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success. Copyright © 2015 Elsevier Ltd. All rights reserved.
Resting-state low-frequency fluctuations reflect individual differences in spoken language learning

PubMed Central

Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping; Wong, Patrick C.M.

2016-01-01

A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The “competition” (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest – ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success. PMID:26866283
Mind-wandering and alterations to default mode network connectivity when listening to naturalistic versus artificial sounds.

PubMed

Gould van Praag, Cassandra D; Garfinkel, Sarah N; Sparasci, Oliver; Mees, Alex; Philippides, Andrew O; Ware, Mark; Ottaviani, Cristina; Critchley, Hugo D

2017-03-27

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, seed based functional connectivity showed a shift from anterior to posterior midline functional coupling in the naturalistic condition. These changes were accompanied by an increase in peak high frequency heart rate variability, indicating an increase in parasympathetic activity in the naturalistic condition in line with the Stress Recovery Theory of nature exposure. Changes in heart rate and the peak high frequency were correlated with baseline functional connectivity within the DMN and baseline parasympathetic tone respectively, highlighting the importance of individual neural and autonomic differences in the response to nature exposure. Our findings may help explain reported health benefits of exposure to natural environments, through identification of alterations to autonomic activity and functional coupling within the DMN when listening to naturalistic sounds.
Mind-wandering and alterations to default mode network connectivity when listening to naturalistic versus artificial sounds

PubMed Central

Gould van Praag, Cassandra D.; Garfinkel, Sarah N.; Sparasci, Oliver; Mees, Alex; Philippides, Andrew O.; Ware, Mark; Ottaviani, Cristina; Critchley, Hugo D.

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, seed based functional connectivity showed a shift from anterior to posterior midline functional coupling in the naturalistic condition. These changes were accompanied by an increase in peak high frequency heart rate variability, indicating an increase in parasympathetic activity in the naturalistic condition in line with the Stress Recovery Theory of nature exposure. Changes in heart rate and the peak high frequency were correlated with baseline functional connectivity within the DMN and baseline parasympathetic tone respectively, highlighting the importance of individual neural and autonomic differences in the response to nature exposure. Our findings may help explain reported health benefits of exposure to natural environments, through identification of alterations to autonomic activity and functional coupling within the DMN when listening to naturalistic sounds. PMID:28345604
Age-related differences in brain network activation and co-activation during multiple object tracking.

PubMed

Dørum, Erlend S; Alnæs, Dag; Kaufmann, Tobias; Richard, Geneviève; Lund, Martina J; Tønnesen, Siren; Sneve, Markus H; Mathiesen, Nina C; Rustan, Øyvind G; Gjertsen, Øivind; Vatn, Sigurd; Fure, Brynjar; Andreassen, Ole A; Nordvik, Jan Egil; Westlye, Lars T

2016-11-01

Multiple object tracking (MOT) is a powerful paradigm for measuring sustained attention. Although previous fMRI studies have delineated the brain activation patterns associated with tracking and documented reduced tracking performance in aging, age-related effects on brain activation during MOT have not been characterized. In particular, it is unclear if the task-related activation of different brain networks is correlated, and also if this coordination between activations within brain networks shows differential effects of age. We obtained fMRI data during MOT at two load conditions from a group of younger ( n = 25, mean age = 24.4 ± 5.1 years) and older ( n = 21, mean age = 64.7 ± 7.4 years) healthy adults. Using a combination of voxel-wise and independent component analysis, we investigated age-related differences in the brain network activation. In order to explore to which degree activation of the various brain networks reflect unique and common mechanisms, we assessed the correlations between the brain networks' activations. Behavioral performance revealed an age-related reduction in MOT accuracy. Voxel and brain network level analyses converged on decreased load-dependent activations of the dorsal attention network (DAN) and decreased load-dependent deactivations of the default mode networks (DMN) in the old group. Lastly, we found stronger correlations in the task-related activations within DAN and within DMN components for younger adults, and stronger correlations between DAN and DMN components for older adults. Using MOT as means for measuring attentional performance, we have demonstrated an age-related attentional decline. Network-level analysis revealed age-related alterations in network recruitment consisting of diminished activations of DAN and diminished deactivations of DMN in older relative to younger adults. We found stronger correlations within DMN and within DAN components for younger adults and stronger correlations between DAN and DMN components for older adults, indicating age-related alterations in the coordinated network-level activation during attentional processing.
Increased default mode network activity in socially anxious individuals during reward processing

PubMed Central

2014-01-01

Background Social anxiety has been associated with potentiated negative affect and, more recently, with diminished positive affect. It is unclear how these alterations in negative and positive affect are represented neurally in socially anxious individuals and, further, whether they generalize to non-social stimuli. To explore this, we used a monetary incentive paradigm to explore the association between social anxiety and both the anticipation and consumption of non-social incentives. Eighty-four individuals from a longitudinal community sample underwent functional magnetic resonance imaging (fMRI) while participating in a monetary incentive delay (MID) task. The MID task consisted of alternating cues indicating the potential to win or prevent losing varying amounts of money based on the speed of the participant’s response. We examined whether self-reported levels of social anxiety, averaged across approximately 7 years of data, moderated brain activity when contrasting gain or loss cues with neutral cues during the anticipation and outcome phases of incentive processing. Whole brain analyses and analyses restricted to the ventral striatum for the anticipation phase and the medial prefrontal cortex for the outcome phase were conducted. Results Social anxiety did not associate with differences in hit rates or reaction times when responding to cues. Further, socially anxious individuals did not exhibit decreased ventral striatum activity during anticipation of gains or decreased MPFC activity during the outcome of gain trials, contrary to expectations based on literature indicating blunted positive affect in social anxiety. Instead, social anxiety showed positive associations with extensive regions implicated in default mode network activity (for example, precuneus, posterior cingulate cortex, and parietal lobe) during anticipation and receipt of monetary gain. Social anxiety was further linked with decreased activity in the ventral striatum during anticipation of monetary loss. Conclusions Socially anxious individuals may increase default mode network activity during reward processing, suggesting high self-focused attention even in relation to potentially rewarding stimuli lacking explicit social connotations. Additionally, social anxiety may relate to decreased ventral striatum reactivity when anticipating potential losses. PMID:25075275
Mathematics anxiety reduces default mode network deactivation in response to numerical tasks.

PubMed

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.

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

PubMed Central

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. PMID:25954179
Dynamical Binding Modes Determine Agonistic and Antagonistic Ligand Effects in the Prostate-Specific G-Protein Coupled Receptor (PSGR).

PubMed

Wolf, Steffen; Jovancevic, Nikolina; Gelis, Lian; Pietsch, Sebastian; Hatt, Hanns; Gerwert, Klaus

2017-11-22

We analysed the ligand-based activation mechanism of the prostate-specific G-protein coupled receptor (PSGR), which is an olfactory receptor that mediates cellular growth in prostate cancer cells. Furthermore, it is an olfactory receptor with a known chemically near identic antagonist/agonist pair, α- and β-ionone. Using a combined theoretical and experimental approach, we propose that this receptor is activated by a ligand-induced rearrangement of a protein-internal hydrogen bond network. Surprisingly, this rearrangement is not induced by interaction of the ligand with the network, but by dynamic van der Waals contacts of the ligand with the involved amino acid side chains, altering their conformations and intraprotein connectivity. Ligand recognition in this GPCR is therefore highly stereo selective, but seemingly lacks any ligand recognition via polar contacts. A putative olfactory receptor-based drug design scheme will have to take this unique mode of protein/ligand action into account.
Bus-based park-and-ride system: a stochastic model on multimodal network with congestion pricing schemes

NASA Astrophysics Data System (ADS)

Liu, Zhiyuan; Meng, Qiang

2014-05-01

This paper focuses on modelling the network flow equilibrium problem on a multimodal transport network with bus-based park-and-ride (P&R) system and congestion pricing charges. The multimodal network has three travel modes: auto mode, transit mode and P&R mode. A continuously distributed value-of-time is assumed to convert toll charges and transit fares to time unit, and the users' route choice behaviour is assumed to follow the probit-based stochastic user equilibrium principle with elastic demand. These two assumptions have caused randomness to the users' generalised travel times on the multimodal network. A comprehensive network framework is first defined for the flow equilibrium problem with consideration of interactions between auto flows and transit (bus) flows. Then, a fixed-point model with unique solution is proposed for the equilibrium flows, which can be solved by a convergent cost averaging method. Finally, the proposed methodology is tested by a network example.
Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

NASA Technical Reports Server (NTRS)

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 table in the presence of various sources of laboratory noise is shown. The output of the neural network is called the degradable classification index. The curve was generated by a simultaneous comparison of means, and it shows a peak-to-peak sensitivity of about 100 nm. The following graph uses model generated data from a compressor blade to show that much higher sensitivities are possible when the environment can be controlled better. The peak-to-peak sensitivity here is about 20 nm. The training procedure was modified for the second graph, and the data were subjected to an intensity-dependent transformation called folding. All the measurements for this approach to calibration were optical. The peak-to-peak amplitudes of the vibration modes were measured using heterodyne interferometry, and the modes themselves were recorded using television (electronic) holography.
Dual regulation of gene expression mediated by extended MAPK activation and salicylic acid contributes to robust innate immunity in Arabidopsis thaliana.

PubMed

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

2013-01-01

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

PubMed

Siniatchkin, Michael; Capovilla, Giuseppe

2013-11-01

Epileptic encephalopathies (EEs) represent a group of severe epileptic disorders associated with cognitive and behavioral disturbances. The mechanisms of cognitive disability in EEs remain unclear. This review summarized neuroimaging studies that have tried to describe specific fingerprints of brain activation in EE. Although the epileptic activity can be generated individually in different brain regions, it seems likely that the activity propagates in a syndrome-specific way. In some EEs, the epileptiform discharges were associated with an interruption of activity in the default mode network. In another EE, other mechanisms seem to underlie cognitive disability associated with epileptic activity, for example, abnormal connectivity pattern or interfering activity in the thalamocortical network. Further neuroimaging studies are needed to investigate the short-term and long-term impact of epileptic activity on cognition and development. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.
Service offerings and interfaces for the ACTS network of earth stations

NASA Technical Reports Server (NTRS)

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

NASA Astrophysics Data System (ADS)

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.
Active-passive bistatic surveillance for long range air defense

NASA Astrophysics Data System (ADS)

Wardrop, B.; Molyneux-Berry, M. R. B.

1992-06-01

A hypothetical mobile support receiver capable of working within existing and future air defense networks as a means to maintain essential surveillance functions is considered. It is shown how multibeam receiver architecture supported by digital signal processing can substantially improve surveillance performance against chaff and jamming threats. A dual-mode support receiver concept is proposed which is based on the state-of-the-art phased-array technology, modular processing in industry standard hardware and existing networks.
Hippocampal Sharp-Wave Ripples Influence Selective Activation of the Default Mode Network

PubMed Central

Kaplan, Raphael; Adhikari, Mohit H.; Hindriks, Rikkert; Mantini, Dante; Murayama, Yusuke; Logothetis, Nikos K.; Deco, Gustavo

2016-01-01

Summary The default mode network (DMN) is a commonly observed resting-state network (RSN) that includes medial temporal, parietal, and prefrontal regions involved in episodic memory [1, 2, 3]. The behavioral relevance of endogenous DMN activity remains elusive, despite an emerging literature correlating resting fMRI fluctuations with memory performance [4, 5]—particularly in DMN regions [6, 7, 8]. Mechanistic support for the DMN’s role in memory consolidation might come from investigation of large deflections (sharp-waves) in the hippocampal local field potential that co-occur with high-frequency (>80 Hz) oscillations called ripples—both during sleep [9, 10] and awake deliberative periods [11, 12, 13]. Ripples are ideally suited for memory consolidation [14, 15], since the reactivation of hippocampal place cell ensembles occurs during ripples [16, 17, 18, 19]. Moreover, the number of ripples after learning predicts subsequent memory performance in rodents [20, 21, 22] and humans [23], whereas electrical stimulation of the hippocampus after learning interferes with memory consolidation [24, 25, 26]. A recent study in macaques showed diffuse fMRI neocortical activation and subcortical deactivation specifically after ripples [27]. Yet it is unclear whether ripples and other hippocampal neural events influence endogenous fluctuations in specific RSNs—like the DMN—unitarily. Here, we examine fMRI datasets from anesthetized monkeys with simultaneous hippocampal electrophysiology recordings, where we observe a dramatic increase in the DMN fMRI signal following ripples, but not following other hippocampal electrophysiological events. Crucially, we find increases in ongoing DMN activity after ripples, but not in other RSNs. Our results relate endogenous DMN fluctuations to hippocampal ripples, thereby linking network-level resting fMRI fluctuations with behaviorally relevant circuit-level neural dynamics. PMID:26898464
Spontaneous activity in default-mode network predicts ascription of self-relatedness to stimuli.

PubMed

Qin, Pengmin; Grimm, Simone; Duncan, Niall W; Fan, Yan; Huang, Zirui; Lane, Timothy; Weng, Xuchu; Bajbouj, Malek; Northoff, Georg

2016-04-01

Spontaneous activity levels prior to stimulus presentation can determine how that stimulus will be perceived. It has also been proposed that such spontaneous activity, particularly in the default-mode network (DMN), is involved in self-related processing. We therefore hypothesised that pre-stimulus activity levels in the DMN predict whether a stimulus is judged as self-related or not. Participants were presented in the MRI scanner with a white noise stimulus that they were instructed contained their name or another. They then had to respond with which name they thought they heard. Regions where there was an activity level difference between self and other response trials 2 s prior to the stimulus being presented were identified. Pre-stimulus activity levels were higher in the right temporoparietal junction, the right temporal pole and the left superior temporal gyrus in trials where the participant responded that they heard their own name than trials where they responded that they heard another. Pre-stimulus spontaneous activity levels in particular brain regions, largely overlapping with the DMN, predict the subsequent judgement of stimuli as self-related. This extends our current knowledge of self-related processing and its apparent relationship with intrinsic brain activity in what can be termed a rest-self overlap. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Experimental demonstration of time- and mode-division multiplexed passive optical network

NASA Astrophysics Data System (ADS)

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.
Crosstalk-aware virtual network embedding over inter-datacenter optical networks with few-mode fibers

NASA Astrophysics Data System (ADS)

Huang, Haibin; Guo, Bingli; Li, Xin; Yin, Shan; Zhou, Yu; Huang, Shanguo

2017-12-01

Virtualization of datacenter (DC) infrastructures enables infrastructure providers (InPs) to provide novel services like virtual networks (VNs). Furthermore, optical networks have been employed to connect the metro-scale geographically distributed DCs. The synergistic virtualization of the DC infrastructures and optical networks enables the efficient VN service over inter-DC optical networks (inter-DCONs). While the capacity of the used standard single-mode fiber (SSMF) is limited by their nonlinear characteristics. Thus, mode-division multiplexing (MDM) technology based on few-mode fibers (FMFs) could be employed to increase the capacity of optical networks. Whereas, modal crosstalk (XT) introduced by optical fibers and components deployed in the MDM optical networks impacts the performance of VN embedding (VNE) over inter-DCONs with FMFs. In this paper, we propose a XT-aware VNE mechanism over inter-DCONs with FMFs. The impact of XT is considered throughout the VNE procedures. The simulation results show that the proposed XT-aware VNE can achieves better performances of blocking probability and spectrum utilization compared to conventional VNE mechanisms.
The development of Human Functional Brain Networks

PubMed Central

Power, Jonathan D; Fair, Damien A; Schlaggar, Bradley L

2010-01-01

Recent advances in MRI technology have enabled precise measurements of correlated activity throughout the brain, leading to the first comprehensive descriptions of functional brain networks in humans. This article reviews the growing literature on the development of functional networks, from infancy through adolescence, as measured by resting state functional connectivity MRI. We note several limitations of traditional approaches to describing brain networks, and describe a powerful framework for analyzing networks, called graph theory. We argue that characterization of the development of brain systems (e.g. the default mode network) should be comprehensive, considering not only relationships within a given system, but also how these relationships are situated within wider network contexts. We note that, despite substantial reorganization of functional connectivity, several large-scale network properties appear to be preserved across development, suggesting that functional brain networks, even in children, are organized in manners similar to other complex systems. PMID:20826306
Boredom, sustained attention and the default mode network.

PubMed

Danckert, James; Merrifield, Colleen

2016-03-15

Boredom is a ubiquitous human experience that can best be described as an inability to engage with one's environment despite the motivation to do so. Boredom is perceived as a negative experience and demonstrates strong associations with other negatively valenced states including depression and aggression. Although boredom has been shown to be elevated in neurological and psychiatric illnesses, little is known about the neural underpinnings of the state. We scanned the brains of healthy participants under four separate conditions: a resting state scan, a sustained attention task and two video-based mood inductions, one known to produce boredom and another we validated to produce a state of interest or engagement. Using independent components analyses, results showed common regions of correlated activation in posterior regions of the so-called default mode network (DMN) of the brain across all four conditions. The sustained attention and boredom induction scans were differentiated from the resting state scan by the presence of anticorrelated activity-i.e. when DMN regions were active, this region was deactivated-in the anterior insula cortex. This same region demonstrated correlated activity with both the DMN and the regions associated with attentional control during the interest mood induction. We interpret these findings to suggest that boredom represents a failure to engage executive control networks when faced with a monotonous task-in other words, when the task demands some level of engagement (watch the movie, search for infrequent targets), but is so mundane that attempts to do so fail.
Performance evaluation of a burst-mode EDFA in an optical packet and circuit integrated network.

PubMed

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.
Patterns of thought: Population variation in the associations between large-scale network organisation and self-reported experiences at rest.

PubMed

Wang, Hao-Ting; Bzdok, Danilo; Margulies, Daniel; Craddock, Cameron; Milham, Michael; Jefferies, Elizabeth; Smallwood, Jonathan

2018-08-01

Contemporary cognitive neuroscience recognises unconstrained processing varies across individuals, describing variation in meaningful attributes, such as intelligence. It may also have links to patterns of on-going experience. This study examined whether dimensions of population variation in different modes of unconstrained processing can be described by the associations between patterns of neural activity and self-reports of experience during the same period. We selected 258 individuals from a publicly available data set who had measures of resting-state functional magnetic resonance imaging, and self-reports of experience during the scan. We used machine learning to determine patterns of association between the neural and self-reported data, finding variation along four dimensions. 'Purposeful' experiences were associated with lower connectivity - in particular default mode and limbic networks were less correlated with attention and sensorimotor networks. 'Emotional' experiences were associated with higher connectivity, especially between limbic and ventral attention networks. Experiences focused on themes of 'personal importance' were associated with reduced functional connectivity within attention and control systems. Finally, visual experiences were associated with stronger connectivity between visual and other networks, in particular the limbic system. Some of these patterns had contrasting links with cognitive function as assessed in a separate laboratory session - purposeful thinking was linked to greater intelligence and better abstract reasoning, while a focus on personal importance had the opposite relationship. Together these findings are consistent with an emerging literature on unconstrained states and also underlines that these states are heterogeneous, with distinct modes of population variation reflecting the interplay of different large-scale networks. Copyright © 2018 Elsevier Inc. All rights reserved.
Top-down regulation of default mode activity in spatial visual attention

PubMed Central

Wen, Xiaotong; Liu, Yijun; Yao, Li; Ding, Mingzhou

2013-01-01

Dorsal anterior cingulate and bilateral anterior insula form a task control network (TCN) whose primary function includes initiating and maintaining task-level cognitive set and exerting top-down regulation of sensorimotor processing. The default mode network (DMN), comprising an anatomically distinct set of cortical areas, mediates introspection and self-referential processes. Resting-state data show that TCN and DMN interact. The functional ramifications of their interaction remain elusive. Recording fMRI data from human subjects performing a visual spatial attention task and correlating Granger causal influences with behavioral performance and blood-oxygen-level-dependent (BOLD) activity we report three main findings. First, causal influences from TCN to DMN, i.e., TCN→DMN, are positively correlated with behavioral performance. Second, causal influences from DMN to TCN, i.e., DMN→TCN, are negatively correlated with behavioral performance. Third, stronger DMN→TCN are associated with less elevated BOLD activity in TCN, whereas the relationship between TCN→DMN and DMN BOLD activity is unsystematic. These results suggest that during visual spatial attention, top-down signals from TCN to DMN regulate the activity in DMN to enhance behavioral performance, whereas signals from DMN to TCN, acting possibly as internal noise, interfere with task control, leading to degraded behavioral performance. PMID:23575842
Portraying the unique contribution of the default mode network to internally driven mnemonic processes

PubMed Central

Shapira-Lichter, Irit; Oren, Noga; Jacob, Yael; Gruberger, Michal; Hendler, Talma

2013-01-01

Numerous neuroimaging studies have implicated default mode network (DMN) involvement in both internally driven processes and memory. Nevertheless, it is unclear whether memory operations reflect a particular case of internally driven processing or alternatively involve the DMN in a distinct manner, possibly depending on memory type. This question is critical for refining neurocognitive memory theorem in the context of other endogenic processes and elucidating the functional significance of this key network. We used functional MRI to examine DMN activity and connectivity patterns while participants overtly generated words according to nonmnemonic (phonemic) or mnemonic (semantic or episodic) cues. Overall, mnemonic word fluency was found to elicit greater DMN activity and stronger within-network functional connectivity compared with nonmnemonic fluency. Furthermore, two levels of functional organization of memory retrieval were shown. First, across both mnemonic tasks, activity was greater mainly in the posterior cingulate cortex, implying selective contribution to generic aspects of memory beyond its general involvement in endogenous processes. Second, parts of the DMN showed distinct selectivity for each of the mnemonic conditions; greater recruitment of the anterior prefrontal cortex, retroesplenial cortex, and hippocampi and elevated connectivity between anterior and posterior medial DMN nodes characterized the semantic condition, whereas increased recruitment of posterior DMN components and elevated connectivity between them characterized the episodic condition. This finding emphasizes the involvement of DMN elements in discrete aspects of memory retrieval. Altogether, our results show a specific contribution of the DMN to memory processes, corresponding to the specific type of memory retrieval. PMID:23479650
Episodic memory retrieval, parietal cortex, and the Default Mode Network: functional and topographic analyses

PubMed Central

Sestieri, Carlo; Corbetta, Maurizio; Romani, Gian Luca; Shulman, Gordon L.

2011-01-01

The default mode network (DMN) is often considered a functionally homogeneous system that is broadly associated with internally directed cognition (e.g. episodic memory, theory of mind, self-evaluation). However, few studies have examined how this network interacts with other networks during putative “default” processes such as episodic memory retrieval. Using fMRI, we investigated the topography and response profile of human parietal regions inside and outside the DMN, independently defined using task-evoked deactivations and resting state functional connectivity, during episodic memory retrieval. Memory retrieval activated posterior nodes of the DMN, particularly the angular gyrus, but also more anterior and dorsal parietal regions that were anatomically separate from the DMN. The two sets of parietal regions showed different resting-state functional connectivity and response profiles. During memory retrieval, responses in DMN regions peaked sooner than non-DMN regions, which in turn showed responses that were sustained until a final memory judgment was reached. Moreover, a parahippocampal region that showed strong resting-state connectivity with parietal DMN regions also exhibited a pattern of task-evoked activity similar to that exhibited by DMN regions. These results suggest that DMN parietal regions directly supported memory retrieval, whereas non-DMN parietal regions were more involved in post-retrieval processes such as memory-based decision making. Finally, a robust functional dissociation within the DMN was observed. While angular gyrus and posterior cingulate/precuneus were significantly activated during memory retrieval, an anterior DMN node in medial prefrontal cortex was strongly deactivated. This latter finding demonstrates functional heterogeneity rather than homogeneity within the DMN during episodic memory retrieval. PMID:21430142

Episodic memory retrieval, parietal cortex, and the default mode network: functional and topographic analyses.

PubMed

Sestieri, Carlo; Corbetta, Maurizio; Romani, Gian Luca; Shulman, Gordon L

2011-03-23

The default mode network (DMN) is often considered a functionally homogeneous system that is broadly associated with internally directed cognition (e.g., episodic memory, theory of mind, self-evaluation). However, few studies have examined how this network interacts with other networks during putative "default" processes such as episodic memory retrieval. Using functional magnetic resonance imaging, we investigated the topography and response profile of human parietal regions inside and outside the DMN, independently defined using task-evoked deactivations and resting-state functional connectivity, during episodic memory retrieval. Memory retrieval activated posterior nodes of the DMN, particularly the angular gyrus, but also more anterior and dorsal parietal regions that were anatomically separate from the DMN. The two sets of parietal regions showed different resting-state functional connectivity and response profiles. During memory retrieval, responses in DMN regions peaked sooner than non-DMN regions, which in turn showed responses that were sustained until a final memory judgment was reached. Moreover, a parahippocampal region that showed strong resting-state connectivity with parietal DMN regions also exhibited a pattern of task-evoked activity similar to that exhibited by DMN regions. These results suggest that DMN parietal regions directly supported memory retrieval, whereas non-DMN parietal regions were more involved in postretrieval processes such as memory-based decision making. Finally, a robust functional dissociation within the DMN was observed. Whereas angular gyrus and posterior cingulate/precuneus were significantly activated during memory retrieval, an anterior DMN node in medial prefrontal cortex was strongly deactivated. This latter finding demonstrates functional heterogeneity rather than homogeneity within the DMN during episodic memory retrieval.
Brains striving for coherence: Long-term cumulative plot formation in the default mode network.

PubMed

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.
Functional resting-state networks are differentially affected in schizophrenia

PubMed Central

Woodward, Neil D.; Rogers, Baxter; Heckers, Stephan

2011-01-01

Neurobiological theories posit that schizophrenia relates to disturbances in connectivity between brain regions. Resting-state functional magnetic resonance imaging is a powerful tool for examining functional connectivity and has revealed several canonical brain networks, including the default mode, dorsal attention, executive control, and salience networks. The purpose of this study was to examine changes in these networks in schizophrenia. 42 patients with schizophrenia and 61 healthy subjects completed a RS-fMRI scanning session. Seed-based region-of-interest correlation analysis was used to identify the default mode, dorsal attention, executive control, and salience networks. Compared to healthy subjects, individuals with schizophrenia demonstrated greater connectivity between the posterior cingulate cortex, a key hub of the default mode, and the left inferior gyrus, left middle frontal gyrus, and left middle temporal gyrus. Interestingly, these regions were more strongly connected to the executive control network in healthy control subjects. In contrast to the default mode, patients demonstrated less connectivity in the executive control and dorsal attention networks. No differences were observed in the salience network. The results indicate that resting-state networks are differentially affected in schizophrenia. The alterations are characterized by reduced segregation between the default mode and executive control networks in the prefrontal cortex and temporal lobe, and reduced connectivity in the dorsal attention and executive control networks. The changes suggest that the process of functional specialization is altered in schizophrenia. Further work is needed to determine if the alterations are related to disturbances in white matter connectivity, neurodevelopmental abnormalities, and genetic risk for schizophrenia. PMID:21458238
Low-frequency oscillations in default mode subnetworks are associated with episodic memory impairments in Alzheimer's disease.

PubMed

Veldsman, Michele; Egorova, Natalia; Singh, Baljeet; Mungas, Dan; DeCarli, Charles; Brodtmann, Amy

2017-11-01

Disruptions to functional connectivity in subsystems of the default mode network are evident in Alzheimer's disease (AD). Functional connectivity estimates correlations in the time course of low-frequency activity. Much less is known about other potential perturbations to this activity, such as changes in the amplitude of oscillations and how this relates to cognition. We examined the amplitude of low-frequency fluctuations in 44 AD patients and 128 cognitively normal participants and related this to episodic memory, the core deficit in AD. We show higher amplitudes of low-frequency oscillations in AD patients. Rather than being compensatory, this appears to be maladaptive, with greater amplitude in the ventral default mode subnetwork associated with poorer episodic memory. Perturbations to default mode subnetworks in AD are evident in the amplitude of low-frequency oscillations in the resting brain. These disruptions are associated with episodic memory demonstrating their behavioral and clinical relevance in AD. Copyright © 2017 Elsevier Inc. All rights reserved.
Individuals with more severe depression fail to sustain nucleus accumbens activity to preferred music over time.

PubMed

Jenkins, Lisanne M; Skerrett, Kristy A; DelDonno, Sophie R; Patrón, Víctor G; Meyers, Kortni K; Peltier, Scott; Zubieta, Jon-Kar; Langenecker, Scott A; Starkman, Monica N

2018-05-30

We investigated the ability of preferred classical music to activate the nucleus accumbens in patients with Major depressive disorder (MDD). Twelve males with MDD and 10 never mentally ill male healthy controls (HC) completed measures of anhedonia and depression severity, and listened to 90-second segments of preferred classical music during fMRI. Compared to HCs, individuals with MDD showed less activation of the left nucleus accumbens (NAcc). Individuals with MDD showed attenuation of the left NAcc response in later compared to earlier parts of the experiment, supporting theories that MDD involves an inability to sustain reward network activation. Counter intuitively, we found that NAcc activity during early music listening was associated with greater depression severity. In whole-brain analyses, anhedonia scores predicted activity in regions within the default mode network, supporting previous findings. Our results support theories that MDD involves an inability to sustain reward network activation. It also highlights that pleasant classical music can engage critical neural reward circuitry in MDD. Copyright © 2018 Elsevier B.V. All rights reserved.
Using Spatial Multiple Regression to Identify Intrinsic Connectivity Networks Involved in Working Memory Performance

PubMed Central

Gordon, Evan M.; Stollstorff, Melanie; Vaidya, Chandan J.

2012-01-01

Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship. PMID:21761505
Signal processing in local neuronal circuits based on activity-dependent noise and competition

NASA Astrophysics Data System (ADS)

Volman, Vladislav; Levine, Herbert

2009-09-01

We study the characteristics of weak signal detection by a recurrent neuronal network with plastic synaptic coupling. It is shown that in the presence of an asynchronous component in synaptic transmission, the network acquires selectivity with respect to the frequency of weak periodic stimuli. For nonperiodic frequency-modulated stimuli, the response is quantified by the mutual information between input (signal) and output (network's activity) and is optimized by synaptic depression. Introducing correlations in signal structure resulted in the decrease in input-output mutual information. Our results suggest that in neural systems with plastic connectivity, information is not merely carried passively by the signal; rather, the information content of the signal itself might determine the mode of its processing by a local neuronal circuit.
Forecasting outpatient visits using empirical mode decomposition coupled with back-propagation artificial neural networks optimized by particle swarm optimization

PubMed Central

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. PMID:28222194
Forecasting outpatient visits using empirical mode decomposition coupled with back-propagation artificial neural networks optimized by particle swarm optimization.

PubMed

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.
Extensive site-directed mutagenesis reveals interconnected functional units in the alkaline phosphatase active site

PubMed Central

Sunden, Fanny; Peck, Ariana; Salzman, Julia; Ressl, Susanne; Herschlag, Daniel

2015-01-01

Enzymes enable life by accelerating reaction rates to biological timescales. Conventional studies have focused on identifying the residues that have a direct involvement in an enzymatic reaction, but these so-called ‘catalytic residues’ are embedded in extensive interaction networks. Although fundamental to our understanding of enzyme function, evolution, and engineering, the properties of these networks have yet to be quantitatively and systematically explored. We dissected an interaction network of five residues in the active site of Escherichia coli alkaline phosphatase. Analysis of the complex catalytic interdependence of specific residues identified three energetically independent but structurally interconnected functional units with distinct modes of cooperativity. From an evolutionary perspective, this network is orders of magnitude more probable to arise than a fully cooperative network. From a functional perspective, new catalytic insights emerge. Further, such comprehensive energetic characterization will be necessary to benchmark the algorithms required to rationally engineer highly efficient enzymes. DOI: http://dx.doi.org/10.7554/eLife.06181.001 PMID:25902402
Single-mode glass waveguide technology for optical interchip communication on board level

NASA Astrophysics Data System (ADS)

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 hybrid packaging process and design issues are discussed.
Understanding marijuana's effects on functional connectivity of the default mode network in patients with schizophrenia and co-occurring cannabis use disorder: A pilot investigation.

PubMed

Whitfield-Gabrieli, Susan; Fischer, Adina S; Henricks, Angela M; Khokhar, Jibran Y; Roth, Robert M; Brunette, Mary F; Green, Alan I

2018-04-01

Nearly half of patients with schizophrenia (SCZ) have co-occurring cannabis use disorder (CUD), which has been associated with decreased treatment efficacy, increased risk of psychotic relapse, and poor global functioning. While reports on the effects of cannabis on cognitive performance in patients with SCZ have been mixed, study of brain networks related to executive function may clarify the relationship between cannabis use and cognition in these dual-diagnosis patients. In the present pilot study, patients with SCZ and CUD (n=12) and healthy controls (n=12) completed two functional magnetic resonance imaging (fMRI) resting scans. Prior to the second scan, patients smoked a 3.6% tetrahydrocannabinol (THC) cannabis cigarette or ingested a 15mg delta-9-tetrahydrocannabinol (THC) pill. We used resting-state functional connectivity to examine the default mode network (DMN) during both scans, as connectivity/activity within this network is negatively correlated with connectivity of the network involved in executive control and shows reduced activity during task performance in normal individuals. At baseline, relative to controls, patients exhibited DMN hyperconnectivity that correlated with positive symptom severity, and reduced anticorrelation between the DMN and the executive control network (ECN). Cannabinoid administration reduced DMN hyperconnectivity and increased DMN-ECN anticorrelation. Moreover, the magnitude of anticorrelation in the controls, and in the patients after cannabinoid administration, positively correlated with WM performance. The finding that DMN brain connectivity is plastic may have implications for future pharmacotherapeutic development, as treatment efficacy could be assessed through the ability of therapies to normalize underlying circuit-level dysfunction. Copyright © 2017. Published by Elsevier B.V.
Distant from input: Evidence of regions within the default mode network supporting perceptually-decoupled and conceptually-guided cognition.

PubMed

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.
Dopamine precursor depletion impairs structure and efficiency of resting state brain functional networks.

PubMed

Carbonell, Felix; Nagano-Saito, Atsuko; Leyton, Marco; Cisek, Paul; Benkelfat, Chawki; He, Yong; Dagher, Alain

2014-09-01

Spatial patterns of functional connectivity derived from resting brain activity may be used to elucidate the topological properties of brain networks. Such networks are amenable to study using graph theory, which shows that they possess small world properties and can be used to differentiate healthy subjects and patient populations. Of particular interest is the possibility that some of these differences are related to alterations in the dopamine system. To investigate the role of dopamine in the topological organization of brain networks at rest, we tested the effects of reducing dopamine synthesis in 13 healthy subjects undergoing functional magnetic resonance imaging. All subjects were scanned twice, in a resting state, following ingestion of one of two amino acid drinks in a randomized, double-blind manner. One drink was a nutritionally balanced amino acid mixture, and the other was tyrosine and phenylalanine deficient. Functional connectivity between 90 cortical and subcortical regions was estimated for each individual subject under each dopaminergic condition. The lowered dopamine state caused the following network changes: reduced global and local efficiency of the whole brain network, reduced regional efficiency in limbic areas, reduced modularity of brain networks, and greater connection between the normally anti-correlated task-positive and default-mode networks. We conclude that dopamine plays a role in maintaining the efficient small-world properties and high modularity of functional brain networks, and in segregating the task-positive and default-mode networks. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'. Copyright © 2014 Elsevier Ltd. All rights reserved.
77 FR 47828 - Amended Notice of Intent To Prepare the Hawai'i Clean Energy Programmatic Environmental Impact...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-10

... efficiency and renewable energy activities and technologies to be analyzed in the PEIS and, accordingly, has... Renewables, (4) Alternative Transportation Fuels and Modes, and (5) Electrical Transmission and Distribution... Kaua'i; electric vehicle public charging networks; efficient appliance rebates; solar water heating...
Why Universities Join Cross-Sector Social Partnerships: Theory and Evidence

ERIC Educational Resources Information Center

Siegel, David J.

2010-01-01

Cross-sector partnerships are an increasingly popular mode of organizing to address intractable social problems, yet theory and research have virtually ignored university involvement in such activity. This article attempts to ascertain the reasons universities join networks of other social actors to support a common cause. Theories on the…
Pressure and Temperature Studies of Glass Properties Related to Vibrational Spectra.

DTIC Science & Technology

1974-12-01

enters the glass, VST be- comes increasingly more positive and the anomaly de- 765 creases. Since Raman-active modes have not been ex- amined under...more ordered angular position and (ii) the network becomes increas- ingly disrupted. Our results are consistent with this .not appreciably vary with
DOE Office of Scientific and Technical Information (OSTI.GOV)

Veeraraghavan, Malathi

This report describes our accomplishments and activities for the project titled Terabit-Scale Hybrid Networking. The key accomplishment is that we developed, tested and deployed an Alpha Flow Characterization System (AFCS) in ESnet. It is being run in production mode since Sept. 2015. Also, a new QoS class was added to ESnet5 to support alpha flows.
Intelligent complementary sliding-mode control for LUSMS-based X-Y-theta motion control stage.

PubMed

Lin, Faa-Jeng; Chen, Syuan-Yi; Shyu, Kuo-Kai; Liu, Yen-Hung

2010-07-01

An intelligent complementary sliding-mode control (ICSMC) system using a recurrent wavelet-based Elman neural network (RWENN) estimator is proposed in this study to control the mover position of a linear ultrasonic motors (LUSMs)-based X-Y-theta motion control stage for the tracking of various contours. By the addition of a complementary generalized error transformation, the complementary sliding-mode control (CSMC) can efficiently reduce the guaranteed ultimate bound of the tracking error by half compared with the slidingmode control (SMC) while using the saturation function. To estimate a lumped uncertainty on-line and replace the hitting control of the CSMC directly, the RWENN estimator is adopted in the proposed ICSMC system. In the RWENN, each hidden neuron employs a different wavelet function as an activation function to improve both the convergent precision and the convergent time compared with the conventional Elman neural network (ENN). The estimation laws of the RWENN are derived using the Lyapunov stability theorem to train the network parameters on-line. A robust compensator is also proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher-order terms in Taylor series. Finally, some experimental results of various contours tracking show that the tracking performance of the ICSMC system is significantly improved compared with the SMC and CSMC systems.
Probing Intrinsic Resting-State Networks in the Infant Rat Brain

PubMed Central

Bajic, Dusica; Craig, Michael M.; Borsook, David; Becerra, Lino

2016-01-01

Resting-state functional magnetic resonance imaging (rs-fMRI) measures spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signal in the absence of external stimuli. It has become a powerful tool for mapping large-scale brain networks in humans and animal models. Several rs-fMRI studies have been conducted in anesthetized and awake adult rats, reporting consistent patterns of brain activity at the systems level. However, the evolution to adult patterns of resting-state activity has not yet been evaluated and quantified in the developing rat brain. In this study, we hypothesized that large-scale intrinsic networks would be easily detectable but not fully established as specific patterns of activity in lightly anesthetized 2-week-old rats (N = 11). Independent component analysis (ICA) identified 8 networks in 2-week-old-rats. These included Default mode, Sensory (Exteroceptive), Salience (Interoceptive), Basal Ganglia-Thalamic-Hippocampal, Basal Ganglia, Autonomic, Cerebellar, as well as Thalamic-Brainstem networks. Many of these networks consisted of more than one component, possibly indicative of immature, underdeveloped networks at this early time point. Except for the Autonomic network, infant rat networks showed reduced connectivity with subcortical structures in comparison to previously published adult networks. Reported slow fluctuations in the BOLD signal that correspond to functionally relevant resting-state networks in 2-week-old rats can serve as an important tool for future studies of brain development in the settings of different pharmacological applications or disease. PMID:27803653

When the Brain Takes a Break: A Model-Based Analysis of Mind Wandering

PubMed Central

Boekel, Wouter; Tucker, Adrienne M.; Turner, Brandon M.; Heathcote, Andrew; Forstmann, Birte U.

2014-01-01

Mind wandering is an ubiquitous phenomenon in everyday life. In the cognitive neurosciences, mind wandering has been associated with several distinct neural processes, most notably increased activity in the default mode network (DMN), suppressed activity within the anti-correlated (task-positive) network (ACN), and changes in neuromodulation. By using an integrative multimodal approach combining machine-learning techniques with modeling of latent cognitive processes, we show that mind wandering in humans is characterized by inefficiencies in executive control (task-monitoring) processes. This failure is predicted by a single-trial signature of (co)activations in the DMN, ACN, and neuromodulation, and accompanied by a decreased rate of evidence accumulation and response thresholds in the cognitive model. PMID:25471568
Multimode and multistate ladder oscillator and frequency recognition device

NASA Technical Reports Server (NTRS)

Aumann, Herbert M. (Inventor)

1976-01-01

A ladder oscillator composed of capacitive and inductive impedances connected together to form a ladder network which has a chosen number N oscillation modes at N different frequencies. Each oscillation mode is characterized by a unique standing wave voltage pattern along the nodes of the ladder oscillator, with the mode in which the ladder oscillator is oscillating being determinable from the amplitudes or phase of the oscillations at the nodes. A logic circuit may be connected to the nodes of the oscillator to compare the phases of selected nodes and thereby determine which mode the oscillator is oscillating in. A ladder oscillator composed of passive capacitive and inductive impedances can be utilized as a frequency recognition device, since the passive ladder oscillator will display the characteristic standing wave patterns if an input signal impressed upon the ladder oscillator is close to one of the mode frequencies of the oscillator. A CL ladder oscillator having series capacitive impedances and shunt inductive impedances can exhibit sustained and autonomous oscillations if active nonlinear devices are connected in parallel with the shunt inductive impedances. The active CL ladder oscillator can be synchronized to input frequencies impressed upon the oscillator, and will continue to oscillate after the input signal has been removed at a mode frequency which is, in general, nearest to the input signal frequency. Autonomous oscillations may also be obtained as desired from the active CL ladder oscillator at the mode frequencies.
Multimodal neuroimaging investigations of alterations to consciousness: the relationship between absence epilepsy and sleep.

PubMed

Bagshaw, Andrew P; Rollings, David T; Khalsa, Sakh; Cavanna, Andrea E

2014-01-01

The link between epilepsy and sleep is well established on many levels. The focus of the current review is on recent neuroimaging investigations into the alterations of consciousness that are observed during absence seizures and the descent into sleep. Functional neuroimaging provides simultaneous cortical and subcortical recording of activity throughout the brain, allowing a detailed definition and characterization of large-scale brain networks and the interactions between them. This has led to the identification of a set of regions which collectively form the consciousness system, which includes contributions from the default mode network (DMN), ascending arousal systems, and the thalamus. Electrophysiological and neuroimaging investigations have also clearly demonstrated the importance of thalamocortical and corticothalamic networks in the evolution of sleep and absence epilepsy, two phenomena in which the subject experiences an alteration to the conscious state and a disconnection from external input. However, the precise relationship between the consciousness system, thalamocortical networks, and consciousness itself remains to be clarified. One of the fundamental challenges is to understand how distributed brain networks coordinate their activity in order to maintain and implement complex behaviors such as consciousness and how modifications to this network activity lead to alterations in consciousness. By taking into account not only the level of activation of individual brain regions but also their connectivity within specific networks and the activity and connectivity of other relevant networks, a more specific quantification of brain states can be achieved. This, in turn, may provide a more fundamental understanding of the alterations to consciousness experienced in sleep and epilepsy. © 2013.
Brain system for mental orientation in space, time, and person

PubMed Central

Peer, Michael; Salomon, Roy; Goldberg, Ilan; Blanke, Olaf; Arzy, Shahar

2015-01-01

Orientation is a fundamental mental function that processes the relations between the behaving self to space (places), time (events), and person (people). Behavioral and neuroimaging studies have hinted at interrelations between processing of these three domains. To unravel the neurocognitive basis of orientation, we used high-resolution 7T functional MRI as 16 subjects compared their subjective distance to different places, events, or people. Analysis at the individual-subject level revealed cortical activation related to orientation in space, time, and person in a precisely localized set of structures in the precuneus, inferior parietal, and medial frontal cortex. Comparison of orientation domains revealed a consistent order of cortical activity inside the precuneus and inferior parietal lobes, with space orientation activating posterior regions, followed anteriorly by person and then time. Core regions at the precuneus and inferior parietal lobe were activated for multiple orientation domains, suggesting also common processing for orientation across domains. The medial prefrontal cortex showed a posterior activation for time and anterior for person. Finally, the default-mode network, identified in a separate resting-state scan, was active for all orientation domains and overlapped mostly with person-orientation regions. These findings suggest that mental orientation in space, time, and person is managed by a specific brain system with a highly ordered internal organization, closely related to the default-mode network. PMID:26283353
Altered resting-state neural activity and changes following a craving behavioral intervention for Internet gaming disorder.

PubMed

Zhang, Jin-Tao; Yao, Yuan-Wei; Potenza, Marc N; Xia, Cui-Cui; Lan, Jing; Liu, Lu; Wang, Ling-Jiao; Liu, Ben; Ma, Shan-Shan; Fang, Xiao-Yi

2016-07-06

Internet gaming disorder (IGD) has become a serious mental health issue worldwide. Evaluating the benefits of interventions for IGD is of great significance. Thirty-six young adults with IGD and 19 healthy comparison (HC) subjects were recruited and underwent resting-state fMRI scanning. Twenty IGD subjects participated in a group craving behavioral intervention (CBI) and were scanned before and after the intervention. The remaining 16 IGD subjects did not receive an intervention. The results showed that IGD subjects showed decreased amplitude of low fluctuation in the orbital frontal cortex and posterior cingulate cortex, and exhibited increased resting-state functional connectivity between the posterior cingulate cortex and dorsolateral prefrontal cortex, compared with HC subjects. Compared with IGD subjects who did not receive the intervention, those receiving CBI demonstrated significantly reduced resting-state functional connectivity between the: (1) orbital frontal cortex with hippocampus/parahippocampal gyrus; and, (2) posterior cingulate cortex with supplementary motor area, precentral gyrus, and postcentral gyrus. These findings suggest that IGD is associated with abnormal resting-state neural activity in reward-related, default mode and executive control networks. Thus, the CBI may exert effects by reducing interactions between regions within a reward-related network, and across the default mode and executive control networks.
Altered resting-state neural activity and changes following a craving behavioral intervention for Internet gaming disorder

PubMed Central

Zhang, Jin-Tao; Yao, Yuan-Wei; Potenza, Marc N.; Xia, Cui-Cui; Lan, Jing; Liu, Lu; Wang, Ling-Jiao; Liu, Ben; Ma, Shan-Shan; Fang, Xiao-Yi

2016-01-01

Internet gaming disorder (IGD) has become a serious mental health issue worldwide. Evaluating the benefits of interventions for IGD is of great significance. Thirty-six young adults with IGD and 19 healthy comparison (HC) subjects were recruited and underwent resting-state fMRI scanning. Twenty IGD subjects participated in a group craving behavioral intervention (CBI) and were scanned before and after the intervention. The remaining 16 IGD subjects did not receive an intervention. The results showed that IGD subjects showed decreased amplitude of low fluctuation in the orbital frontal cortex and posterior cingulate cortex, and exhibited increased resting-state functional connectivity between the posterior cingulate cortex and dorsolateral prefrontal cortex, compared with HC subjects. Compared with IGD subjects who did not receive the intervention, those receiving CBI demonstrated significantly reduced resting-state functional connectivity between the: (1) orbital frontal cortex with hippocampus/parahippocampal gyrus; and, (2) posterior cingulate cortex with supplementary motor area, precentral gyrus, and postcentral gyrus. These findings suggest that IGD is associated with abnormal resting-state neural activity in reward-related, default mode and executive control networks. Thus, the CBI may exert effects by reducing interactions between regions within a reward-related network, and across the default mode and executive control networks. PMID:27381822
Mind wandering away from pain dynamically engages antinociceptive and default mode brain networks

PubMed Central

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

2013-01-01

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. PMID:24167282
Mind wandering away from pain dynamically engages antinociceptive and default mode brain networks.

PubMed

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

PubMed

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

2013-12-01

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

PubMed

Gujar, Ninad; Yoo, Seung-Schik; Hu, Peter; Walker, Matthew P

2010-08-01

The sleep-deprived brain has principally been characterized by examining dysfunction during cognitive task performance. However, far less attention has been afforded the possibility that sleep deprivation may be as, if not more, accurately characterized on the basis of abnormal resting-state brain activity. Here we report that one night of sleep deprivation significantly disrupts the canonical signature of task-related deactivation, resulting in a double dissociation within anterior as well as posterior midline regions of the default network. Indeed, deactivation within these regions alone discriminated sleep-deprived from sleep-control subjects with a 93% degree of sensitivity and 92% specificity. In addition, the relative balance of deactivation within these default nodes significantly correlated with the amount of prior sleep in the control group (and not extended time awake in the deprivation group). Therefore, the stability and the balance of task-related deactivation in key default-mode regions may be dependent on prior sleep, such that a lack thereof disrupts this signature pattern of brain activity, findings that may offer explanatory insights into conditions associated with sleep loss at both a clinical as well as societal level.
Is Rest Really Rest? Resting State Functional Connectivity during Rest and Motor Task Paradigms.

PubMed

Jurkiewicz, Michael T; Crawley, Adrian P; Mikulis, David J

2018-04-18

Numerous studies have identified the default mode network (DMN) within the brain of healthy individuals, which has been attributed to the ongoing mental activity of the brain during the wakeful resting-state. While engaged during specific resting-state fMRI paradigms, it remains unclear as to whether traditional block-design simple movement fMRI experiments significantly influence the default mode network or other areas. Using blood-oxygen level dependent (BOLD) fMRI we characterized the pattern of functional connectivity in healthy subjects during a resting-state paradigm and compared this to the same resting-state analysis performed on motor task data residual time courses after regressing out the task paradigm. Using seed-voxel analysis to define the DMN, the executive control network (ECN), and sensorimotor, auditory and visual networks, the resting-state analysis of the residual time courses demonstrated reduced functional connectivity in the motor network and reduced connectivity between the insula and the ECN compared to the standard resting-state datasets. Overall, performance of simple self-directed motor tasks does little to change the resting-state functional connectivity across the brain, especially in non-motor areas. This would suggest that previously acquired fMRI studies incorporating simple block-design motor tasks could be mined retrospectively for assessment of the resting-state connectivity.
Electro-acupuncture at different acupoints modulating the relative specific brain functional network

NASA Astrophysics Data System (ADS)

Fang, Jiliang; Wang, Xiaoling; Wang, Yin; Liu, Hesheng; Hong, Yang; Liu, Jun; Zhou, Kehua; Wang, Lei; Xue, Chao; Song, Ming; Liu, Baoyan; Zhu, Bing

2010-11-01

Objective: The specific brain effects of acupoint are important scientific concern in acupuncture. However, previous acupuncture fMRI studies focused on acupoints in muscle layer on the limb. Therefore, researches on acupoints within connective tissue at trunk are warranted. Material and Methods: Brain effects of acupuncture on abdomen at acupoints Guanyuan (CV4) and Zhongwan (CV12) were tested using fMRI on 21 healthy volunteers. The data acquisition was performed at resting state, during needle retention, electroacupuncture (EA) and post-EA resting state. Needling sensations were rated after every electroacupuncture (EA) procedure. The needling sensations and the brain functional activity and connectivity were compared between CV4 and CV12 using SPSS, SPM2 and the local and remote connectivity maps. Results and conclusion: EA at CV4 and CV12 induced apparent deactivation effects in the limbic-paralimbic-neocortical network. The default mode of the brain was modified by needle retention and EA, respectively. The functional brain network was significantly changed post EA. However, the minor differences existed between these two acupoints. The results demonstrated similarity between functional brain network mode of acupuncture modulation and functional circuits of emotional and cognitive regulation. Acupuncture may produce analgesia, anti-anxiety and anti-depression via the limbic-paralimbic-neocortical network (LPNN).
Ad hoc Laser networks component technology for modular spacecraft

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

NASA Astrophysics Data System (ADS)

Huang, Xiujun; Shi, Dele; Shen, Jingshi

2017-10-01

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

NASA Astrophysics Data System (ADS)

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.
Excessive coupling of the salience network with intrinsic neurocognitive brain networks during rectal distension in adolescents with irritable bowel syndrome: a preliminary report

PubMed Central

Liu, Xiaolin; Silverman, Alan; Kern, Mark; Ward, B. Douglas; Li, Shi-Jiang; Shaker, Reza; Sood, Manu R.

2015-01-01

Background The neural network mechanisms underlying visceral hypersensitivity in irritable bowel syndrome (IBS) are incompletely understood. It has been proposed that an intrinsic salience network plays an important role in chronic pain and IBS symptoms. Using neuroimaging, we examined brain responses to rectal distension in adolescent IBS patients, focusing on determining the alteration of salience network integrity in IBS and its functional implications in current theoretical frameworks. We hypothesized that (1) brain responses to visceral stimulation in adolescents are similar to those in adults, and (2) IBS is associated with an altered salience network interaction with other neurocognitive networks, particularly the default mode network (DMN) and executive control network (ECN), as predicted by the theoretical models. Methods IBS patients and controls received subliminal and liminal rectal distension during imaging. Stimulus-induced brain activations were determined. Salience network integrity was evaluated by functional connectivity of its seed regions activated by rectal distension in the insular and cingulate cortices. Key Results Compared with controls, IBS patients demonstrated greater activation to rectal distension in neural structures of the homeostatic afferent and emotional arousal networks, especially the anterior cingulate and insular cortices. Greater brain responses to liminal vs. subliminal distension were observed in both groups. Particularly, IBS is uniquely associated with an excessive coupling of the salience network with the DMN and ECN in their key frontal and parietal node areas. Conclusions & Inferences Our study provided consistent evidence supporting the theoretical predictions of altered salience network functioning as a neuropathological mechanism of IBS symptoms. PMID:26467966
Integration and segregation of large-scale brain networks during short-term task automatization

PubMed Central

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

2016-01-01

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. PMID:27808095
A multiscale method for a robust detection of the default mode network

NASA Astrophysics Data System (ADS)

Baquero, Katherine; Gómez, Francisco; Cifuentes, Christian; Guldenmund, Pieter; Demertzi, Athena; Vanhaudenhuyse, Audrey; Gosseries, Olivia; Tshibanda, Jean-Flory; Noirhomme, Quentin; Laureys, Steven; Soddu, Andrea; Romero, Eduardo

2013-11-01

The Default Mode Network (DMN) is a resting state network widely used for the analysis and diagnosis of mental disorders. It is normally detected in fMRI data, but for its detection in data corrupted by motion artefacts or low neuronal activity, the use of a robust analysis method is mandatory. In fMRI it has been shown that the signal-to-noise ratio (SNR) and the detection sensitivity of neuronal regions is increased with di erent smoothing kernels sizes. Here we propose to use a multiscale decomposition based of a linear scale-space representation for the detection of the DMN. Three main points are proposed in this methodology: rst, the use of fMRI data at di erent smoothing scale-spaces, second, detection of independent neuronal components of the DMN at each scale by using standard preprocessing methods and ICA decomposition at scale-level, and nally, a weighted contribution of each scale by the Goodness of Fit measurement. This method was applied to a group of control subjects and was compared with a standard preprocesing baseline. The detection of the DMN was improved at single subject level and at group level. Based on these results, we suggest to use this methodology to enhance the detection of the DMN in data perturbed with artefacts or applied to subjects with low neuronal activity. Furthermore, the multiscale method could be extended for the detection of other resting state neuronal networks.
Structural and functional connectivity underlying grey matter covariance: impact of developmental insult.

PubMed

Paquola, Casey; Bennett, Maxwell; Lagopoulos, Jim

2018-05-15

Structural covariance networks (SCNs) may offer unique insights into the developmental impact of childhood maltreatment because they are thought to reflect coordinated maturation of distinct grey matter regions. T1-weighted magnetic resonance images were acquired from 121 young people with emerging mental illness. Diffusion weighted and resting state functional imaging was also acquired from a random subset of the participants (n=62). Ten study-specific SCNs were identified using a whole brain grey matter independent component analysis. The effects of childhood maltreatment and age on average grey matter density and the expression of each SCN were calculated. Childhood maltreatment was linked to age-related decreases in grey matter density across a SCN that overlapped with the default mode and fronto-parietal networks. Resting state functional connectivity and structural connectivity were calculated in the study-specific SCN and across the whole brain. Grey matter covariance was significantly correlated with rsFC across the SCN, and rsFC fully mediated the relationship between grey matter covariance and structural connectivity in the non-maltreated group. A unique association of grey matter covariance with structural connectivity was detected amongst individuals with a history of childhood maltreatment. Perturbation of grey matter development across the default mode and fronto-parietal networks following childhood maltreatment may have significant implications for mental well-being, given the networks' roles in self-referential activity. Cross-modal comparisons suggest reduced grey matter following childhood maltreatment could arise from deficient functional activity earlier in life.
Fault detection and diagnosis using neural network approaches

NASA Technical Reports Server (NTRS)

Kramer, Mark A.

1992-01-01

Neural networks can be used to detect and identify abnormalities in real-time process data. Two basic approaches can be used, the first based on training networks using data representing both normal and abnormal modes of process behavior, and the second based on statistical characterization of the normal mode only. Given data representative of process faults, radial basis function networks can effectively identify failures. This approach is often limited by the lack of fault data, but can be facilitated by process simulation. The second approach employs elliptical and radial basis function neural networks and other models to learn the statistical distributions of process observables under normal conditions. Analytical models of failure modes can then be applied in combination with the neural network models to identify faults. Special methods can be applied to compensate for sensor failures, to produce real-time estimation of missing or failed sensors based on the correlations codified in the neural network.

New cryogenic temperature monitor: PLT-HPT-32

NASA Astrophysics Data System (ADS)

Viera Curbelo, Teodora Aleida; Martín-Fernández, Sergio Gonzáles; Hoyland, R.; Vega-Moreno, A.; Cozar Castellano, Juan; Gómez Reñasco, M. F.; Aguiar-González, M.; Pérez de Taoro, Angeles; Sánchez-de la Rosa, V.; Rubiño-Martín, J. A.; Génova-Santos, R.

2016-07-01

The PLT-HPT-32, a new cryogenic temperature monitor, has been developed by the Institute of Astrophysics of the Canary Islands (IAC) and an external engineering company (Sergio González Martín-Fernandez). The PLT-HPT-32 temperature monitor offers precision measurement in a wide range of cryogenic and higher-temperature applications with the ability to easily monitor up to 32 sensor channels. It provides better measurement performance in applications where researchers need to ensure accuracy and precision in their low cryogenic temperature monitoring. The PLT-HPT-32 supports PTC RTDs such as platinum sensors, and diodes such as the Lake Shore DT-670 Series. Used with silicon diodes, it provides accurate measurements in cryo-cooler applications from 16 K to above room temperature. The resolution of the measurement is less than 0.1K. Measurements can be displayed in voltage units or Kelvin units. For it, two different tables can be used. One can be programmed by the user, and the other one corresponds to Lake Shore DT670 sensor that comes standard. There are two modes of measuring, the instantaneous mode and averaged mode. In this moment, all channels must work in the same mode but in the near future it expected to be used in blocks of eight channels. The instantaneous mode takes three seconds to read all channels. The averaged mode takes one minute to average twenty samples in all channels. Alarm thresholds can be configured independently for each input. The alarm events, come from the first eight channels, can activate the unit's relay outputs for hard-wired triggering of other systems or audible annunciators. Activate relays on high, low, or both alarms for any input. For local monitoring, "Stand-Alone Mode", the front panel of the PLT-HPT-32 features a bright liquid crystal display with an LED backlight that shows up to 32 readings simultaneously. Plus, monitoring can be done over a network "Remote Control Mode". Using the Ethernet port on the PLT-HPT-32, you can keep an eye on temperatures, log measurement and configured remotely via a Networked local PC or even remotely over a TCP/IP Internet connection from anywhere.
Neural network topology in ADHD; evidence for maturational delay and default-mode network alterations.

PubMed

Janssen, T W P; Hillebrand, A; Gouw, A; Geladé, K; Van Mourik, R; Maras, A; Oosterlaan, J

2017-11-01

Attention-deficit/hyperactivity disorder (ADHD) has been associated with widespread brain abnormalities in white and grey matter, affecting not only local, but global functional networks as well. In this study, we explored these functional networks using source-reconstructed electroencephalography in ADHD and typically developing (TD) children. We expected evidence for maturational delay, with underlying abnormalities in the default mode network. Electroencephalograms were recorded in ADHD (n=42) and TD (n=43) during rest, and functional connectivity (phase lag index) and graph (minimum spanning tree) parameters were derived. Dependent variables were global and local network metrics in theta, alpha and beta bands. We found evidence for a more centralized functional network in ADHD compared to TD children, with decreased diameter in the alpha band (η p 2 =0.06) and increased leaf fraction (η p 2 =0.11 and 0.08) in the alpha and beta bands, with underlying abnormalities in hub regions of the brain, including default mode network. The finding of a more centralized network is in line with maturational delay models of ADHD and should be replicated in longitudinal designs. This study contributes to the literature by combining high temporal and spatial resolution to construct EEG network topology, and associates maturational-delay and default-mode interference hypotheses of ADHD. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Brain Activity and Functional Connectivity Associated with Hypnosis.

PubMed

Jiang, Heidi; White, Matthew P; Greicius, Michael D; Waelde, Lynn C; Spiegel, David

2017-08-01

Hypnosis has proven clinical utility, yet changes in brain activity underlying the hypnotic state have not yet been fully identified. Previous research suggests that hypnosis is associated with decreased default mode network (DMN) activity and that high hypnotizability is associated with greater functional connectivity between the executive control network (ECN) and the salience network (SN). We used functional magnetic resonance imaging to investigate activity and functional connectivity among these three networks in hypnosis. We selected 57 of 545 healthy subjects with very high or low hypnotizability using two hypnotizability scales. All subjects underwent four conditions in the scanner: rest, memory retrieval, and two different hypnosis experiences guided by standard pre-recorded instructions in counterbalanced order. Seeds for the ECN, SN, and DMN were left and right dorsolateral prefrontal cortex, dorsal anterior cingulate cortex (dACC), and posterior cingulate cortex (PCC), respectively. During hypnosis there was reduced activity in the dACC, increased functional connectivity between the dorsolateral prefrontal cortex (DLPFC;ECN) and the insula in the SN, and reduced connectivity between the ECN (DLPFC) and the DMN (PCC). These changes in neural activity underlie the focused attention, enhanced somatic and emotional control, and lack of self-consciousness that characterizes hypnosis. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Signal propagation and logic gating in networks of integrate-and-fire neurons.

PubMed

Vogels, Tim P; Abbott, L F

2005-11-16

Transmission of signals within the brain is essential for cognitive function, but it is not clear how neural circuits support reliable and accurate signal propagation over a sufficiently large dynamic range. Two modes of propagation have been studied: synfire chains, in which synchronous activity travels through feedforward layers of a neuronal network, and the propagation of fluctuations in firing rate across these layers. In both cases, a sufficient amount of noise, which was added to previous models from an external source, had to be included to support stable propagation. Sparse, randomly connected networks of spiking model neurons can generate chaotic patterns of activity. We investigate whether this activity, which is a more realistic noise source, is sufficient to allow for signal transmission. We find that, for rate-coded signals but not for synfire chains, such networks support robust and accurate signal reproduction through up to six layers if appropriate adjustments are made in synaptic strengths. We investigate the factors affecting transmission and show that multiple signals can propagate simultaneously along different pathways. Using this feature, we show how different types of logic gates can arise within the architecture of the random network through the strengthening of specific synapses.
Affective mentalizing and brain activity at rest in the behavioral variant of frontotemporal dementia.

PubMed

Caminiti, Silvia P; Canessa, Nicola; Cerami, Chiara; Dodich, Alessandra; Crespi, Chiara; Iannaccone, Sandro; Marcone, Alessandra; Falini, Andrea; Cappa, Stefano F

2015-01-01

bvFTD patients display an impairment in the attribution of cognitive and affective states to others, reflecting GM atrophy in brain regions associated with social cognition, such as amygdala, superior temporal cortex and posterior insula. Distinctive patterns of abnormal brain functioning at rest have been reported in bvFTD, but their relationship with defective attribution of affective states has not been investigated. To investigate the relationship among resting-state brain activity, gray matter (GM) atrophy and the attribution of mental states in the behavioral variant of fronto-temporal degeneration (bvFTD). We compared 12 bvFTD patients with 30 age- and education-matched healthy controls on a) performance in a task requiring the attribution of affective vs. cognitive mental states; b) metrics of resting-state activity in known functional networks; and c) the relationship between task-performances and resting-state metrics. In addition, we assessed a connection between abnormal resting-state metrics and GM atrophy. Compared with controls, bvFTD patients showed a reduction of intra-network coherent activity in several components, as well as decreased strength of activation in networks related to attentional processing. Anomalous resting-state activity involved networks which also displayed a significant reduction of GM density. In patients, compared with controls, higher affective mentalizing performance correlated with stronger functional connectivity between medial prefrontal sectors of the default-mode and attentional/performance monitoring networks, as well as with increased coherent activity in components of the executive, sensorimotor and fronto-limbic networks. Some of the observed effects may reflect specific compensatory mechanisms for the atrophic changes involving regions in charge of affective mentalizing. The analysis of specific resting-state networks thus highlights an intermediate level of analysis between abnormal brain structure and impaired behavioral performance in bvFTD, reflecting both dysfunction and compensation mechanisms.
Understanding Student Travel Behaviour in Semarang City

NASA Astrophysics Data System (ADS)

Manullang, O. R.; Tyas, W. P.; Anas, N.; Aji, F. N.

2018-02-01

The highest movement in Semarang City is dominated by motorcycles, which reached 79% of the number of vehicles. Highest percentage movement use motorcycle caused the highest percentage accident by motorcycle users, which reached 66% and 9% involving high school students. This happens because of the dependence of motorcycles usage in fulfilling the needs of movement in the city of Semarang. Understanding student travel behavior based on their activities is used to know travel needs and the cause of dependence on motorcycle usage. Analysis method in this study use network analysis to compare the potential accessibility and actual accessibility to known why motorcycle chosen by students as the main mode. In addition, phenomenology analysis is used to explain the intent and reasons the data produced by network analysis. The analysis result indicates that the high use of motorcycles by high school students in the Semarang city due to the absence of other effective and efficient modes in fulfilling the movement needs. Even, the student which can potentially use public transport preferred to use a motorcycle. This mode is more effective and efficient because of its flexibility and lower costs.
An Exploratory Investigation of Functional Network Connectivity of Empathy and Default Mode Networks in a Free-Viewing Task.

PubMed

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 deviations in functional synergies of large complex networks associated with empathy responses and DMN in clinical applications like autism and schizophrenia.
Using minimal spanning trees to compare the reliability of network topologies

NASA Technical Reports Server (NTRS)

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.
The maturing architecture of the brain's default network

PubMed Central

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

2008-01-01

In recent years, the brain's “default network,” a set of regions characterized by decreased neural activity during goal-oriented tasks, has generated a significant amount of interest, as well as controversy. Much of the discussion has focused on the relationship of these regions to a “default mode” of brain function. In early studies, investigators suggested that, the brain's default mode supports “self-referential” or “introspective” mental activity. Subsequently, regions of the default network have been more specifically related to the “internal narrative,” the “autobiographical self,” “stimulus independent thought,” “mentalizing,” and most recently “self-projection.” However, the extant literature on the function of the default network is limited to adults, i.e., after the system has reached maturity. We hypothesized that further insight into the network's functioning could be achieved by characterizing its development. In the current study, we used resting-state functional connectivity MRI (rs-fcMRI) to characterize the development of the brain's default network. We found that the default regions are only sparsely functionally connected at early school age (7–9 years old); over development, these regions integrate into a cohesive, interconnected network. PMID:18322013
Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models

PubMed Central

Cowley, Benjamin R.; Doiron, Brent; Kohn, Adam

2016-01-01

Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction—shared dimensionality and percent shared variance—with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure. PMID:27926936
A Dynamic Programming Approach for Base Station Sleeping in Cellular Networks

NASA Astrophysics Data System (ADS)

Gong, Jie; Zhou, Sheng; Niu, Zhisheng

The energy consumption of the information and communication technology (ICT) industry, which has become a serious problem, is mostly due to the network infrastructure rather than the mobile terminals. In this paper, we focus on reducing the energy consumption of base stations (BSs) by adjusting their working modes (active or sleep). Specifically, the objective is to minimize the energy consumption while satisfying quality of service (QoS, e.g., blocking probability) requirement and, at the same time, avoiding frequent mode switching to reduce signaling and delay overhead. The problem is modeled as a dynamic programming (DP) problem, which is NP-hard in general. Based on cooperation among neighboring BSs, a low-complexity algorithm is proposed to reduce the size of state space as well as that of action space. Simulations demonstrate that, with the proposed algorithm, the active BS pattern well meets the time variation and the non-uniform spatial distribution of system traffic. Moreover, the tradeoff between the energy saving from BS sleeping and the cost of switching is well balanced by the proposed scheme.
Combination of a proteomics approach and reengineering of meso scale network models for prediction of mode-of-action for tyrosine kinase inhibitors.

PubMed

Balabanov, Stefan; Wilhelm, Thomas; Venz, Simone; Keller, Gunhild; Scharf, Christian; Pospisil, Heike; Braig, Melanie; Barett, Christine; Bokemeyer, Carsten; Walther, Reinhard; Brümmendorf, Tim H; Schuppert, Andreas

2013-01-01

In drug discovery, the characterisation of the precise modes of action (MoA) and of unwanted off-target effects of novel molecularly targeted compounds is of highest relevance. Recent approaches for identification of MoA have employed various techniques for modeling of well defined signaling pathways including structural information, changes in phenotypic behavior of cells and gene expression patterns after drug treatment. However, efficient approaches focusing on proteome wide data for the identification of MoA including interference with mutations are underrepresented. As mutations are key drivers of drug resistance in molecularly targeted tumor therapies, efficient analysis and modeling of downstream effects of mutations on drug MoA is a key to efficient development of improved targeted anti-cancer drugs. Here we present a combination of a global proteome analysis, reengineering of network models and integration of apoptosis data used to infer the mode-of-action of various tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) cell lines expressing wild type as well as TKI resistance conferring mutants of BCR-ABL. The inferred network models provide a tool to predict the main MoA of drugs as well as to grouping of drugs with known similar kinase inhibitory activity patterns in comparison to drugs with an additional MoA. We believe that our direct network reconstruction approach, demonstrated on proteomics data, can provide a complementary method to the established network reconstruction approaches for the preclinical modeling of the MoA of various types of targeted drugs in cancer treatment. Hence it may contribute to the more precise prediction of clinically relevant on- and off-target effects of TKIs.
Combination of a Proteomics Approach and Reengineering of Meso Scale Network Models for Prediction of Mode-of-Action for Tyrosine Kinase Inhibitors

PubMed Central

Balabanov, Stefan; Wilhelm, Thomas; Venz, Simone; Keller, Gunhild; Scharf, Christian; Pospisil, Heike; Braig, Melanie; Barett, Christine; Bokemeyer, Carsten; Walther, Reinhard

2013-01-01

In drug discovery, the characterisation of the precise modes of action (MoA) and of unwanted off-target effects of novel molecularly targeted compounds is of highest relevance. Recent approaches for identification of MoA have employed various techniques for modeling of well defined signaling pathways including structural information, changes in phenotypic behavior of cells and gene expression patterns after drug treatment. However, efficient approaches focusing on proteome wide data for the identification of MoA including interference with mutations are underrepresented. As mutations are key drivers of drug resistance in molecularly targeted tumor therapies, efficient analysis and modeling of downstream effects of mutations on drug MoA is a key to efficient development of improved targeted anti-cancer drugs. Here we present a combination of a global proteome analysis, reengineering of network models and integration of apoptosis data used to infer the mode-of-action of various tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) cell lines expressing wild type as well as TKI resistance conferring mutants of BCR-ABL. The inferred network models provide a tool to predict the main MoA of drugs as well as to grouping of drugs with known similar kinase inhibitory activity patterns in comparison to drugs with an additional MoA. We believe that our direct network reconstruction approach, demonstrated on proteomics data, can provide a complementary method to the established network reconstruction approaches for the preclinical modeling of the MoA of various types of targeted drugs in cancer treatment. Hence it may contribute to the more precise prediction of clinically relevant on- and off-target effects of TKIs. PMID:23326482
Connectionist Models: Proceedings of the Summer School Held in San Diego, California on 1990

DTIC Science & Technology

1990-01-01

modes: control network continues activation spreading based There is the sequential version and the parallel version on the actual inputs instead of...ent). 2. Execute all motoric actions based on activations of r a ent.The parallel version of the algorithm is local in time, units in A. Update the...a- movements that help o recognize an entering person.) tions like ’move focus left’, ’rotate focus’ are based on the activations of the C’s output
A Bayesian network model for predicting aquatic toxicity mode of action using two dimensional theoretical molecular descriptors-abstract

EPA Science Inventory

The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity but MoA classification in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity mode of action using a recently published dataset contain...
Ongoing activity in temporally coherent networks predicts intra-subject fluctuation of response time to sporadic executive control demands.

PubMed

Nozawa, Takayuki; Sugiura, Motoaki; Yokoyama, Ryoichi; Ihara, Mizuki; Kotozaki, Yuka; Miyauchi, Carlos Makoto; Kanno, Akitake; Kawashima, Ryuta

2014-01-01

Can ongoing fMRI BOLD signals predict fluctuations in swiftness of a person's response to sporadic cognitive demands? This is an important issue because it clarifies whether intrinsic brain dynamics, for which spatio-temporal patterns are expressed as temporally coherent networks (TCNs), have effects not only on sensory or motor processes, but also on cognitive processes. Predictivity has been affirmed, although to a limited extent. Expecting a predictive effect on executive performance for a wider range of TCNs constituting the cingulo-opercular, fronto-parietal, and default mode networks, we conducted an fMRI study using a version of the color-word Stroop task that was specifically designed to put a higher load on executive control, with the aim of making its fluctuations more detectable. We explored the relationships between the fluctuations in ongoing pre-trial activity in TCNs and the task response time (RT). The results revealed the existence of TCNs in which fluctuations in activity several seconds before the onset of the trial predicted RT fluctuations for the subsequent trial. These TCNs were distributed in the cingulo-opercular and fronto-parietal networks, as well as in perceptual and motor networks. Our results suggest that intrinsic brain dynamics in these networks constitute "cognitive readiness," which plays an active role especially in situations where information for anticipatory attention control is unavailable. Fluctuations in these networks lead to fluctuations in executive control performance.
Trait or state? A longitudinal neuropsychological evaluation and fMRI study in schizoaffective disorder.

PubMed

Madre, Merce; Radua, Joaquim; Landin-Romero, Ramon; Alonso-Lana, Silvia; Salvador, Raimond; Panicali, Francesco; Pomarol-Clotet, Edith; Amann, Benedikt L

2014-11-01

Schizoaffective patients can have neurocognitive deficits and default mode network dysfunction while being acutely ill. It remains unclear to what extent these abnormalities persist when they go into clinical remission. Memory and executive function were tested in 22 acutely ill schizoaffective patients; they also underwent fMRI scanning during performance of the n-back working memory test. The same measures were obtained after they had been in remission for ≥ 2 months. Twenty-two matched healthy individuals were also examined. In clinical remission, schizomanic patients showed an improvement of memory but not of executive function, while schizodepressive patients did not change in either domain. All schizoaffective patients in clinical remission showed memory and executive impairment compared to the controls. On fMRI, acutely ill schizomanic patients had reversible frontal hypo-activation when compared to clinical remission, while activation patterns in ill and remitted schizodepressive patients were similar. The whole group of schizoaffective patients in clinical remission showed a failure of de-activation in the medial frontal gyrus compared to the healthy controls. There was evidence for memory improvement and state dependent changes in activation in schizomanic patients across relapse and remission. Medial frontal failure of de-activation in remitted schizoaffective patients, which probably reflects default mode network dysfunction, appears to be a state independent feature of the illness. Copyright © 2014 Elsevier B.V. All rights reserved.
Characterizing individual differences in reward sensitivity from the brain networks involved in response inhibition.

PubMed

Fuentes-Claramonte, Paola; Ávila, César; Rodríguez-Pujadas, Aina; Costumero, Víctor; Ventura-Campos, Noelia; Bustamante, Juan Carlos; Rosell-Negre, Patricia; Barrós-Loscertales, Alfonso

2016-01-01

A "disinhibited" cognitive profile has been proposed for individuals with high reward sensitivity, characterized by increased engagement in goal-directed responses and reduced processing of negative or unexpected cues, which impairs adequate behavioral regulation after feedback in these individuals. This pattern is manifested through deficits in inhibitory control and/or increases in RT variability. In the present work, we aimed to test whether this profile is associated with the activity of functional networks during a stop-signal task using independent component analysis (ICA). Sixty-one participants underwent fMRI while performing a stop-signal task, during which a manual response had to be inhibited. ICA was used to mainly replicate the functional networks involved in the task (Zhang and Li, 2012): two motor networks involved in the go response, the left and right fronto-parietal networks for stopping, a midline error-processing network, and the default-mode network (DMN), which was further subdivided into its anterior and posterior parts. Reward sensitivity was mainly associated with greater activity of motor networks, reduced activity in the midline network during correct stop trials and, behaviorally, increased RT variability. All these variables explained 36% of variance of the SR scores. This pattern of associations suggests that reward sensitivity involves greater motor engagement in the dominant response, more distractibility and reduced processing of salient or unexpected events, which may lead to disinhibited behavior. Copyright © 2015 Elsevier Inc. All rights reserved.
Differential brain network activity across mood states in bipolar disorder.

PubMed

Brady, Roscoe O; Tandon, Neeraj; Masters, Grace A; Margolis, Allison; Cohen, Bruce M; Keshavan, Matcheri; Öngür, Dost

2017-01-01

This study aimed to identify how the activity of large-scale brain networks differs between mood states in bipolar disorder. The authors measured spontaneous brain activity in subjects with bipolar disorder in mania and euthymia and compared these states to a healthy comparison population. 23 subjects with bipolar disorder type I in a manic episode, 24 euthymic bipolar I subjects, and 23 matched healthy comparison (HC) subjects underwent resting state fMRI scans. Using an existing parcellation of the whole brain, we measured functional connectivity between brain regions and identified significant differences between groups. In unbiased whole-brain analyses, functional connectivity between parietal, occipital, and frontal nodes within the dorsal attention network (DAN) were significantly greater in mania than euthymia or HC subjects. In the default mode network (DMN), connectivity between dorsal frontal nodes and the rest of the DMN differentiated both mood state and diagnosis. The bipolar groups were separate cohorts rather than subjects imaged longitudinally across mood states. Bipolar mood states are associated with highly significant alterations in connectivity in two large-scale brain networks. These same networks also differentiate bipolar mania and euthymia from a HC population. State related changes in DAN and DMN connectivity suggest a circuit based pathology underlying cognitive dysfunction as well as activity/reactivity in bipolar mania. Altered activities in neural networks may be biomarkers of bipolar disorder diagnosis and mood state that are accessible to neuromodulation and are promising novel targets for scientific investigation and possible clinical intervention. Copyright © 2016 Elsevier B.V. All rights reserved.
Neural networks supporting switching, hypothesis testing, and rule application

PubMed Central

Liu, Zhiya; Braunlich, Kurt; Wehe, Hillary S.; Seger, Carol A.

2015-01-01

We identified dynamic changes in recruitment of neural connectivity networks across three phases of a flexible rule learning and set-shifting task similar to the Wisconsin Card Sort Task: switching, rule learning via hypothesis testing, and rule application. During fMRI scanning, subjects viewed pairs of stimuli that differed across four dimensions (letter, color, size, screen location), chose one stimulus, and received feedback. Subjects were informed that the correct choice was determined by a simple unidimensional rule, for example “choose the blue letter.” Once each rule had been learned and correctly applied for 4-7 trials, subjects were cued via either negative feedback or visual cues to switch to learning a new rule. Task performance was divided into three phases: Switching (first trial after receiving the switch cue), hypothesis testing (subsequent trials through the last error trial), and rule application (correct responding after the rule was learned). We used both univariate analysis to characterize activity occurring within specific regions of the brain, and a multivariate method, constrained principal component analysis for fMRI (fMRI-CPCA), to investigate how distributed regions coordinate to subserve different processes. As hypothesized, switching was subserved by a limbic network including the ventral striatum, thalamus, and parahippocampal gyrus, in conjunction with cortical salience network regions including the anterior cingulate and frontoinsular cortex. Activity in the ventral striatum was associated with switching regardless of how switching was cued; visually cued shifts were associated with additional visual cortical activity. After switching, as subjects moved into the hypothesis testing phase, a broad fronto-parietal-striatal network (associated with the cognitive control, dorsal attention, and salience networks) increased in activity. This network was sensitive to rule learning speed, with greater extended activity for the slowest learning speed late in the time course of learning. As subjects shifted from hypothesis testing to rule application, activity in this network decreased and activity in the somatomotor and default mode networks increased. PMID:26197092

Neural networks supporting switching, hypothesis testing, and rule application.

PubMed

Liu, Zhiya; Braunlich, Kurt; Wehe, Hillary S; Seger, Carol A

2015-10-01

We identified dynamic changes in recruitment of neural connectivity networks across three phases of a flexible rule learning and set-shifting task similar to the Wisconsin Card Sort Task: switching, rule learning via hypothesis testing, and rule application. During fMRI scanning, subjects viewed pairs of stimuli that differed across four dimensions (letter, color, size, screen location), chose one stimulus, and received feedback. Subjects were informed that the correct choice was determined by a simple unidimensional rule, for example "choose the blue letter". Once each rule had been learned and correctly applied for 4-7 trials, subjects were cued via either negative feedback or visual cues to switch to learning a new rule. Task performance was divided into three phases: Switching (first trial after receiving the switch cue), hypothesis testing (subsequent trials through the last error trial), and rule application (correct responding after the rule was learned). We used both univariate analysis to characterize activity occurring within specific regions of the brain, and a multivariate method, constrained principal component analysis for fMRI (fMRI-CPCA), to investigate how distributed regions coordinate to subserve different processes. As hypothesized, switching was subserved by a limbic network including the ventral striatum, thalamus, and parahippocampal gyrus, in conjunction with cortical salience network regions including the anterior cingulate and frontoinsular cortex. Activity in the ventral striatum was associated with switching regardless of how switching was cued; visually cued shifts were associated with additional visual cortical activity. After switching, as subjects moved into the hypothesis testing phase, a broad fronto-parietal-striatal network (associated with the cognitive control, dorsal attention, and salience networks) increased in activity. This network was sensitive to rule learning speed, with greater extended activity for the slowest learning speed late in the time course of learning. As subjects shifted from hypothesis testing to rule application, activity in this network decreased and activity in the somatomotor and default mode networks increased. Copyright © 2015 Elsevier Ltd. All rights reserved.
Impulsive Internet Game Play Is Associated With Increased Functional Connectivity Between the Default Mode and Salience Networks in Depressed Patients With Short Allele of Serotonin Transporter Gene.

PubMed

Hong, Ji Sun; Kim, Sun Mi; Bae, Sujin; Han, Doug Hyun

2018-01-01

Problematic Internet game play is often accompanied by major depressive disorder (MDD). Depression seems to be closely related to altered functional connectivity (FC) within (and between) the default mode network (DMN) and salience network. In addition, serotonergic neurotransmission may regulate the symptoms of depression, including impulsivity, potentially by modulating the DMN. We hypothesized that altered connectivity between the DMN and salience network could mediate an association between the 5HTTLPR genotype and impulsivity in patients with depression. A total of 54 participants with problematic Internet game play and MDD completed the research protocol. We genotyped for 5HTTLPR and assessed the DMN FC using resting-state functional magnetic resonance imaging. The severity of Internet game play, depressive symptoms, anxiety, attention and impulsivity, and behavioral inhibition and activation were assessed using the Young Internet Addiction Scale (YIAS), Beck Depressive Inventory, Beck Anxiety Inventory (BAI), Korean Attention Deficit Hyperactivity Disorder scale, and the Behavioral Inhibition and Activation Scales (BIS-BAS), respectively. The SS allele was associated with increased FC within the DMN, including the middle prefrontal cortex (MPFC) to the posterior cingulate cortex, and within the salience network, including the right supramarginal gyrus (SMG) to the right rostral prefrontal cortex (RPFC), right anterior insular (AInsular) to right SMG, anterior cingulate cortex (ACC) to left RPFC, and left AInsular to right RPFC, and between the DMN and salience network, including the MPFC to the ACC. In addition, the FC from the MPFC to ACC positively correlated with the BIS and YIAS scores in the SS allele group. The SS allele of 5HTTLPR might modulate the FC within and between the DMN and salience network, which may ultimately be a risk factor for impulsive Internet game play in patients with MDD.
In Search of Neural Endophenotypes of Postpartum Psychopathology and Disrupted Maternal Caregiving

PubMed Central

Moses-Kolko, E. L.; Horner, M. S.; Phillips, M. L.; Hipwell, A. E.; Swain, J. E.

2015-01-01

This is a selective review that provides the context for the study of perinatal affective disorder mechanisms and outlines directions for future research. We integrate existing literature along neural networks of interest for affective disorders and maternal caregiving: (i) the salience/fear network; (ii) the executive network; (iii) the reward/social attachment network; and (iv) the default mode network. Extant salience/fear network research reveals disparate responses and corticolimbic coupling to various stimuli based upon a predominantly depressive versus anxious (post-traumatic stress disorder) clinical phenotype. Executive network and default mode connectivity abnormalities have been described in postpartum depression (PPD), although studies are very limited in these domains. Reward/social attachment studies confirm a robust ventral striatal response to infant stimuli, including cry and happy infant faces, which is diminished in depressed, insecurely attached and substance-using mothers. The adverse parenting experiences received and the attachment insecurity of current mothers are factors that are associated with a diminution in infant stimulus-related neural activity similar to that in PPD, and raise the need for additional studies that integrate mood and attachment concepts in larger study samples. Several studies examining functional connectivity in resting state and emotional activation functional magnetic resonance imaging paradigms have revealed attenuated corticolimbic connectivity, which remains an important outcome that requires dissection with increasing precision to better define neural treatment targets. Methodological progress is expected in the coming years in terms of refining clinical phenotypes of interest and experimental paradigms, as well as enlarging samples to facilitate the examination of multiple constructs. Functional imaging promises to determine neural mechanisms underlying maternal psychopathology and impaired caregiving, such that earlier and more precise detection of abnormalities will be possible. Ultimately, the discovery of such mechanisms will promote the refinement of treatment approaches toward maternal affective disturbance, parenting behaviours and the augmentation of parenting resiliency. PMID:25059408
Prediction of human errors by maladaptive changes in event-related brain networks.

PubMed

Eichele, Tom; Debener, Stefan; Calhoun, Vince D; Specht, Karsten; Engel, Andreas K; Hugdahl, Kenneth; von Cramon, D Yves; Ullsperger, Markus

2008-04-22

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve approximately 30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations.
Prediction of human errors by maladaptive changes in event-related brain networks

PubMed Central

Eichele, Tom; Debener, Stefan; Calhoun, Vince D.; Specht, Karsten; Engel, Andreas K.; Hugdahl, Kenneth; von Cramon, D. Yves; Ullsperger, Markus

2008-01-01

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve ≈30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations. PMID:18427123
Alternative Dual Mode Network Control Strategies

DOT National Transportation Integrated Search

1972-03-01

From a literature survey a qualitative evaluation was made of four network control strategies for the fundamental control philosophy of the moving synchronous slot. In the literature concerning automated transportation systems, such as dual mode, a g...
Brain Activation During Autobiographical Memory Retrieval with Special Reference to Default Mode Network

PubMed Central

Ino, Tadashi; Nakai, Ryusuke; Azuma, Takashi; Kimura, Toru; Fukuyama, Hidenao

2011-01-01

Recent neuroimaging studies have suggested that brain regions activated during retrieval of autobiographical memory (ABM) overlap with the default mode network (DMN), which shows greater activation during rest than cognitively demanding tasks and is considered to be involved in self-referential processing. However, detailed overlap and segregation between ABM and DMN remain unclear. This fMRI study focuses first on revealing components of the DMN which are related to ABM and those which are unrelated to ABM, and second on extracting the neural bases which are specifically devoted to ABM. Brain activities relative to rest during three tasks matched in task difficulty assessed by reaction time were investigated by fMRI; category cued recall from ABM, category cued recall from semantic memory, and number counting task. We delineated the overlap between the regions that showed less activation during semantic memory and number counting relative to rest, which correspond to the DMN, and the areas that showed greater or less activation during ABM relative to rest. ABM-specific activation was defined as the overlap between the contrast of ABM versus rest and the contrast of ABM versus semantic memory. The fMRI results showed that greater activation as well as less activation during ABM relative to rest overlapped considerably with the DMN, indicating that the DMN is segregated to the regions which are functionally related to ABM and the regions which are unrelated to ABM. ABM-specific activation was observed in the left-lateralized brain regions and most of them fell within the DMN. PMID:21643504
Modulation of the brain's functional network architecture in the transition from wake to sleep

PubMed Central

Larson-Prior, Linda J.; Power, Jonathan D.; Vincent, Justin L.; Nolan, Tracy S.; Coalson, Rebecca S.; Zempel, John; Snyder, Abraham Z.; Schlaggar, Bradley L.; Raichle, Marcus E.; Petersen, Steven E.

2013-01-01

The transition from quiet wakeful rest to sleep represents a period over which attention to the external environment fades. Neuroimaging methodologies have provided much information on the shift in neural activity patterns in sleep, but the dynamic restructuring of human brain networks in the transitional period from wake to sleep remains poorly understood. Analysis of electrophysiological measures and functional network connectivity of these early transitional states shows subtle shifts in network architecture that are consistent with reduced external attentiveness and increased internal and self-referential processing. Further, descent to sleep is accompanied by the loss of connectivity in anterior and posterior portions of the default-mode network and more locally organized global network architecture. These data clarify the complex and dynamic nature of the transitional period between wake and sleep and suggest the need for more studies investigating the dynamics of these processes. PMID:21854969
A revised limbic system model for memory, emotion and behaviour.

PubMed

Catani, Marco; Dell'acqua, Flavio; Thiebaut de Schotten, Michel

2013-09-01

Emotion, memories and behaviour emerge from the coordinated activities of regions connected by the limbic system. Here, we propose an update of the limbic model based on the seminal work of Papez, Yakovlev and MacLean. In the revised model we identify three distinct but partially overlapping networks: (i) the Hippocampal-diencephalic and parahippocampal-retrosplenial network dedicated to memory and spatial orientation; (ii) The temporo-amygdala-orbitofrontal network for the integration of visceral sensation and emotion with semantic memory and behaviour; (iii) the default-mode network involved in autobiographical memories and introspective self-directed thinking. The three networks share cortical nodes that are emerging as principal hubs in connectomic analysis. This revised network model of the limbic system reconciles recent functional imaging findings with anatomical accounts of clinical disorders commonly associated with limbic pathology. Copyright © 2013 Elsevier Ltd. All rights reserved.
Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks

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

Visweswara Sathanur, Arun; Halappanavar, Mahantesh; Shi, Yi

In many complex networked systems such as online social networks, at any given time, activity originates at certain nodes and subsequently spreads on the network through influence. To model the spread of influence in such a scenario, we consider the problem of identification of influential entities in a complex network when nodal activation can happen through two different mechanisms. The first mode of activation is due mechanisms intrinsic to the node. The second mechanism is through the influence of connected neighbors. In this work, we present a simple probabilistic formulation that models such self-evolving systems where information diffusion occurs primarilymore » because of the intrinsic activity of users and the spread of activity occurs due to influence. We provide an algorithm to mine for the influential seeds in such a scenario by modifying the well-known influence maximization framework with the independent cascade diffusion model. We provide small motivating examples to provide an intuitive understanding of the effect of including the intrinsic activation mechanism. We sketch a proof of the submodularity of the influence function under the new formulation and demonstrate the same with larger graphs. We then show by means of additional experiments on a real-world twitter dataset how the formulation can be applied to real-world social media datasets. Finally we derive a computationally efficient centrality metric that takes into account, both the mechanisms of activation and provides for an accurate as well as computationally efficient alternative approach to the problem of identifying influencers under intrinsic activation.« less
Terminal Sliding Mode-Based Consensus Tracking Control for Networked Uncertain Mechanical Systems on Digraphs.

PubMed

Chen, Gang; Song, Yongduan; Guan, Yanfeng

2018-03-01

This brief investigates the finite-time consensus tracking control problem for networked uncertain mechanical systems on digraphs. A new terminal sliding-mode-based cooperative control scheme is developed to guarantee that the tracking errors converge to an arbitrarily small bound around zero in finite time. All the networked systems can have different dynamics and all the dynamics are unknown. A neural network is used at each node to approximate the local unknown dynamics. The control schemes are implemented in a fully distributed manner. The proposed control method eliminates some limitations in the existing terminal sliding-mode-based consensus control methods and extends the existing analysis methods to the case of directed graphs. Simulation results on networked robot manipulators are provided to show the effectiveness of the proposed control algorithms.
Modifications of resting state networks in spinocerebellar ataxia type 2.

PubMed

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.
Aberrant coupling within and across the default mode, task-positive, and salience network in subjects at risk for psychosis.

PubMed

Wotruba, Diana; Michels, Lars; Buechler, Roman; Metzler, Sibylle; Theodoridou, Anastasia; Gerstenberg, Miriam; Walitza, Susanne; Kollias, Spyros; Rössler, Wulf; Heekeren, Karsten

2014-09-01

The task-positive network (TPN) is anticorrelated with activity in the default mode network (DMN), and possibly reflects competition between the processing of external and internal information, while the salience network (SN) is pivotal in regulating TPN and DMN activity. Because abnormal functional connectivity in these networks has been related to schizophrenia, we tested whether alterations are also evident in subjects at risk for psychosis. Resting-state functional magnetic resonance imaging was tested in 28 subjects with basic symptoms reporting subjective cognitive-perceptive symptoms; 19 with attenuated or brief, limited psychotic symptoms; and 29 matched healthy controls. We characterized spatial differences in connectivity patterns, as well as internetwork connectivity. Right anterior insula (rAI) was selected as seed region for identifying the SN; medioprefrontal cortex (MPFC) for the DMN and TPN. The 3 groups differed in connectivity patterns between the MPFC and right dorsolateral prefrontal cortex (rDLPFC), and between the rAI and posterior cingulate cortex (PCC). In particular, the typically observed antagonistic relationship in MPFC-rDLPFC, rAI-PCC, and internetwork connectivity of DMN-TPN was absent in both at-risk groups. Notably, those connectivity patterns were associated with symptoms related to reality distortions, whereas enhanced connectivity strengths of MPFC-rDLPFC and TPN-DMN were related to poor performance in cognitive functions. We propose that the loss of a TPN-DMN anticorrelation, accompanied by an aberrant spatial extent in the DMN, TPN, and SN in the psychosis risk state, reflects the confusion of internally and externally focused states and disturbance of cognition, as seen in psychotic disorders. © The Author 2013. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Microelectromechanical filter formed from parallel-connected lattice networks of contour-mode resonators

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

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 latticemore » 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.« less
Altered effective connectivity of default model brain network underlying amnestic MCI

NASA Astrophysics Data System (ADS)

Yan, Hao; Wang, Yonghui; Tian, Jie

2012-02-01

Mild cognitive impairment (MCI) is the transitional, heterogeneous continuum from healthy elderly to Alzheimer's disease (AD). Previous studies have shown that brain functional activity in the default mode network (DMN) is impaired in MCI patients. However, the altered effective connectivity of the DMN in MCI patients remains largely unknown. The present study combined an independent component analysis (ICA) approach with Granger causality analysis (mGCA) to investigate the effective connectivity within the DMN in 12 amnestic MCI patients and 12 age-matched healthy elderly. Compared to the healthy control, the MCI exhibited decreased functional activity in the posterior DMN regions, as well as a trend towards activity increases in anterior DMN regions. Results from mGCA further supported this conclusion that the causal influence projecting to the precuneus/PCC became much weaker in MCI, while stronger interregional interactions emerged within the frontal-parietal cortices. These findings suggested that abnormal effective connectivity within the DMN may elucidate the dysfunctional and compensatory processes in MCI brain networks.
A Tabu-Search Heuristic for Deterministic Two-Mode Blockmodeling of Binary Network Matrices

ERIC Educational Resources Information Center

Brusco, Michael; Steinley, Douglas

2011-01-01

Two-mode binary data matrices arise in a variety of social network contexts, such as the attendance or non-attendance of individuals at events, the participation or lack of participation of groups in projects, and the votes of judges on cases. A popular method for analyzing such data is two-mode blockmodeling based on structural equivalence, where…
Systemic risk and spatiotemporal dynamics of the consumer market of China

NASA Astrophysics Data System (ADS)

Wang, Minggang; Tian, Lixin; Xu, Hua; Li, Weiyu; Du, Ruijin; Dong, Gaogao; Wang, Jie; Gu, Jiani

2017-05-01

The consumer price index (CPI) contains rich information of the consumer market, in order to characterize the essential characteristics of the consumer market of China, a novel method by using complex network theory is proposed to visualizing the evolution and transformation characteristics of correlated modes among the regional consumer markets. CPI data of 31 provinces and cities of China are selected as sample data. Underlying dynamics of time-evolving correlation networks are revealed. A formula to measure the systemic risk in the consumer market is designed. And the correlation modes transmission network of the regional consumer markets is obtained. Numerical simulations show that the consumer market network has co-movement, group-occurring and small-word property. Different regions played different roles in the consumer market of China. The risk in the consumer market presented a decreasing trend from April 2013 but remain at the high level. Different from the stochastic system, the consumer market of China both has the short-range correlation and the long-range correlation. The strength of correlation modes transmission network basically satisfies a power-law distribution. The correlation modes are transferred into each other conveniently, although the consumer market system is highly complicated. The transformation of the correlation patterns of the regional consumer markets mainly revolves around three core correlation modes and each transformation needs to undergo 4 non-core modes.
Synchrony-induced modes of oscillation of a neural field model

NASA Astrophysics Data System (ADS)

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.
Synchrony-induced modes of oscillation of a neural field model.

PubMed

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.
Flight Test of an Intelligent Flight-Control System

NASA Technical Reports Server (NTRS)

Davidson, Ron; Bosworth, John T.; Jacobson, Steven R.; Thomson, Michael Pl; Jorgensen, Charles C.

2003-01-01

The F-15 Advanced Controls Technology for Integrated Vehicles (ACTIVE) airplane (see figure) was the test bed for a flight test of an intelligent flight control system (IFCS). This IFCS utilizes a neural network to determine critical stability and control derivatives for a control law, the real-time gains of which are computed by an algorithm that solves the Riccati equation. These derivatives are also used to identify the parameters of a dynamic model of the airplane. The model is used in a model-following portion of the control law, in order to provide specific vehicle handling characteristics. The flight test of the IFCS marks the initiation of the Intelligent Flight Control System Advanced Concept Program (IFCS ACP), which is a collaboration between NASA and Boeing Phantom Works. The goals of the IFCS ACP are to (1) develop the concept of a flight-control system that uses neural-network technology to identify aircraft characteristics to provide optimal aircraft performance, (2) develop a self-training neural network to update estimates of aircraft properties in flight, and (3) demonstrate the aforementioned concepts on the F-15 ACTIVE airplane in flight. The activities of the initial IFCS ACP were divided into three Phases, each devoted to the attainment of a different objective. The objective of Phase I was to develop a pre-trained neural network to store and recall the wind-tunnel-based stability and control derivatives of the vehicle. The objective of Phase II was to develop a neural network that can learn how to adjust the stability and control derivatives to account for failures or modeling deficiencies. The objective of Phase III was to develop a flight control system that uses the neural network outputs as a basis for controlling the aircraft. The flight test of the IFCS was performed in stages. In the first stage, the Phase I version of the pre-trained neural network was flown in a passive mode. The neural network software was running using flight data inputs with the outputs provided to instrumentation only. The IFCS was not used to control the airplane. In another stage of the flight test, the Phase I pre-trained neural network was integrated into a Phase III version of the flight control system. The Phase I pretrained neural network provided realtime stability and control derivatives to a Phase III controller that was based on a stochastic optimal feedforward and feedback technique (SOFFT). This combined Phase I/III system was operated together with the research flight-control system (RFCS) of the F-15 ACTIVE during the flight test. The RFCS enables the pilot to switch quickly from the experimental- research flight mode back to the safe conventional mode. These initial IFCS ACP flight tests were completed in April 1999. The Phase I/III flight test milestone was to demonstrate, across a range of subsonic and supersonic flight conditions, that the pre-trained neural network could be used to supply real-time aerodynamic stability and control derivatives to the closed-loop optimal SOFFT flight controller. Additional objectives attained in the flight test included (1) flight qualification of a neural-network-based control system; (2) the use of a combined neural-network/closed-loop optimal flight-control system to obtain level-one handling qualities; and (3) demonstration, through variation of control gains, that different handling qualities can be achieved by setting new target parameters. In addition, data for the Phase-II (on-line-learning) neural network were collected, during the use of stacked-frequency- sweep excitation, for post-flight analysis. Initial analysis of these data showed the potential for future flight tests that will incorporate the real-time identification and on-line learning aspects of the IFCS.

Musical Imagery Involves Wernicke's Area in Bilateral and Anti-Correlated Network Interactions in Musicians.

PubMed

Zhang, Yizhen; Chen, Gang; Wen, Haiguang; Lu, Kun-Han; Liu, Zhongming

2017-12-06

Musical imagery is the human experience of imagining music without actually hearing it. The neural basis of this mental ability is unclear, especially for musicians capable of engaging in accurate and vivid musical imagery. Here, we created a visualization of an 8-minute symphony as a silent movie and used it as real-time cue for musicians to continuously imagine the music for repeated and synchronized sessions during functional magnetic resonance imaging (fMRI). The activations and networks evoked by musical imagery were compared with those elicited by the subjects directly listening to the same music. Musical imagery and musical perception resulted in overlapping activations at the anterolateral belt and Wernicke's area, where the responses were correlated with the auditory features of the music. Whereas Wernicke's area interacted within the intrinsic auditory network during musical perception, it was involved in much more complex networks during musical imagery, showing positive correlations with the dorsal attention network and the motor-control network and negative correlations with the default-mode network. Our results highlight the important role of Wernicke's area in forming vivid musical imagery through bilateral and anti-correlated network interactions, challenging the conventional view of segregated and lateralized processing of music versus language.
Cavitation in Poly(4-methyl-1-pentene) during Tensile Deformation.

PubMed

Chen, Ran; Lu, Ying; Jiang, Zhiyong; Men, Yongfeng

2018-04-12

The poly(4-methyl-1-pentene) sample was used to investigate the cavitation-induced stress-whitening phenomenon during stretching at different temperatures via the ultrasmall-angle X-ray scattering technique. Two modes of cavitation were found that mode I cavitation activated around yield point followed by mode II cavitation generated in highly oriented state. The critical strain for initiating the mode II cavitation increases with the increase of the stretching temperature, whereas the critical stress grew steadily in the lower temperature regime (30-60 °C) and reached a plateau at 70 °C. The appearance of mode II cavitation at large strains was independent of the mode I cavitation. The mode I cavitation was attributed to the competitive process between the formation of cavities and shearing yield of lamellae, whereas the mode II cavitation was proven to be related to the failure of the whole highly oriented entangled amorphous network because of the breaking of interfibrillar load-bearing tie molecules. Size distribution of cavities has been successfully calculated using a model fitting procedure. The results showed that the quantity of cavities increased heavily while the size was kept nearly constant during the propagation of the mode II cavitation.
Phthalimide neovascular factor 1 (PNF1) modulates MT1-MMP activity in human microvascular endothelial cells

PubMed Central

Wieghaus, Kristen A.; Gianchandani, Erwin P.; Neal, Rebekah A.; Paige, Mikell A.; Brown, Milton L.; Papin, Jason A.; Botchwey, Edward A.

2009-01-01

We are creating synthetic pharmaceuticals with angiogenic activity and potential to promote vascular invasion. We previously demonstrated that one of these molecules, phthalimide neovascular factor 1 (PNF1), significantly expands microvascular networks in vivo following sustained release from poly(lactic-co-glycolic acid) (PLAGA) films. In addition, to probe PNF1 mode-of-action, we recently applied a novel pathway-based compendium analysis to a multi-timepoint, controlled microarray dataset of PNF1-treated (versus control) human microvascular endothelial cells (HMVECs), and we identified induction of tumor necrosis factor-alpha (TNF-α) and, subsequently, transforming growth factor-beta (TGF-β) signaling networks by PNF1. Here we validate this microarray data-set with quantitative real-time polymerase chain reaction (RT-PCR) analysis. Subsequently, we probe this dataset and identify three specific TGF-β-induced genes with regulation by PNF1 conserved over multiple timepoints—amyloid beta (A4) precursor protein (APP), early growth response 1 (EGR-1), and matrix metalloproteinase 14 (MMP14 or MT1-MMP)—that are also implicated in angiogenesis. We further focus on MMP14 given its unique role in angiogenesis, and we validate MT1-MMP modulation by PNF1 with an in vitro fluorescence assay that demonstrates the direct effects that PNF1 exerts on functional metalloproteinase activity. We also utilize endothelial cord formation in collagen gels to show that PNF1-induced stimulation of endothelial cord network formation in vitro is in some way MT1-MMP-dependent. Ultimately, this new network analysis of our transcriptional footprint characterizing PNF1 activity 1–48 h post-supplementation in HMVECs coupled with corresponding validating experiments suggests a key set of a few specific targets that are involved in PNF1 mode-of-action and important for successful promotion of the neovascularization that we have observed by the drug in vivo. PMID:19326468
Phthalimide neovascular factor 1 (PNF1) modulates MT1-MMP activity in human microvascular endothelial cells.

PubMed

Wieghaus, Kristen A; Gianchandani, Erwin P; Neal, Rebekah A; Paige, Mikell A; Brown, Milton L; Papin, Jason A; Botchwey, Edward A

2009-07-01

We are creating synthetic pharmaceuticals with angiogenic activity and potential to promote vascular invasion. We previously demonstrated that one of these molecules, phthalimide neovascular factor 1 (PNF1), significantly expands microvascular networks in vivo following sustained release from poly(lactic-co-glycolic acid) (PLAGA) films. In addition, to probe PNF1 mode of action, we recently applied a novel pathway-based compendium analysis to a multi-timepoint, controlled microarray data set of PNF1-treated (vs. control) human microvascular endothelial cells (HMVECs), and we identified induction of tumor necrosis factor-alpha (TNF-alpha) and, subsequently, transforming growth factor-beta (TGF-beta) signaling networks by PNF1. Here we validate this microarray data set with quantitative real-time polymerase chain reaction (RT-PCR) analysis. Subsequently, we probe this data set and identify three specific TGF-beta-induced genes with regulation by PNF1 conserved over multiple timepoints-amyloid beta (A4) precursor protein (APP), early growth response 1 (EGR-1), and matrix metalloproteinase 14 (MMP14 or MT1-MMP)-that are also implicated in angiogenesis. We further focus on MMP14 given its unique role in angiogenesis, and we validate MT1-MMP modulation by PNF1 with an in vitro fluorescence assay that demonstrates the direct effects that PNF1 exerts on functional metalloproteinase activity. We also utilize endothelial cord formation in collagen gels to show that PNF1-induced stimulation of endothelial cord network formation in vitro is in some way MT1-MMP-dependent. Ultimately, this new network analysis of our transcriptional footprint characterizing PNF1 activity 1-48 h post-supplementation in HMVECs coupled with corresponding validating experiments suggests a key set of a few specific targets that are involved in PNF1 mode of action and important for successful promotion of the neovascularization that we have observed by the drug in vivo.
Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer's disease.

PubMed

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

2017-11-01

Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer's disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer's disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer's disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks-the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer's disease patients with and without cerebrovascular disease. Alzheimer's disease patients without cerebrovascular disease, but not Alzheimer's disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer's disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer's disease patients with and without cerebrovascular disease. Across Alzheimer's disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer's disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer's disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer's disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer's disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer's disease network degeneration phenotype. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.
Rest but busy: Aberrant resting-state functional connectivity of triple network model in insomnia.

PubMed

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

2018-02-01

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

NASA Astrophysics Data System (ADS)

Namaki, A.; Shirazi, A. H.; Raei, R.; Jafari, G. R.

2011-10-01

A financial market is an example of an adaptive complex network consisting of many interacting units. This network reflects market’s behavior. In this paper, we use Random Matrix Theory (RMT) notion for specifying the largest eigenvector of correlation matrix as the market mode of stock network. For a better risk management, we clean the correlation matrix by removing the market mode from data and then construct this matrix based on the residuals. We show that this technique has an important effect on correlation coefficient distribution by applying it for Dow Jones Industrial Average (DJIA). To study the topological structure of a network we apply the removing market mode technique and the threshold method to Tehran Stock Exchange (TSE) as an example. We show that this network follows a power-law model in certain intervals. We also show the behavior of clustering coefficients and component numbers of this network for different thresholds. These outputs are useful for both theoretical and practical purposes such as asset allocation and risk management.
The CB1 Neutral Antagonist Tetrahydrocannabivarin Reduces Default Mode Network and Increases Executive Control Network Resting State Functional Connectivity in Healthy Volunteers.

PubMed

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.
Phase-locking and bistability in neuronal networks with synaptic depression

NASA Astrophysics Data System (ADS)

Akcay, Zeynep; Huang, Xinxian; Nadim, Farzan; Bose, Amitabha

2018-02-01

We consider a recurrent network of two oscillatory neurons that are coupled with inhibitory synapses. We use the phase response curves of the neurons and the properties of short-term synaptic depression to define Poincaré maps for the activity of the network. The fixed points of these maps correspond to phase-locked modes of the network. Using these maps, we analyze the conditions that allow short-term synaptic depression to lead to the existence of bistable phase-locked, periodic solutions. We show that bistability arises when either the phase response curve of the neuron or the short-term depression profile changes steeply enough. The results apply to any Type I oscillator and we illustrate our findings using the Quadratic Integrate-and-Fire and Morris-Lecar neuron models.
Common and distinct changes of default mode and salience network in schizophrenia and major depression.

PubMed

Shao, Junming; Meng, Chun; Tahmasian, Masoud; Brandl, Felix; Yang, Qinli; Luo, Guangchun; Luo, Cheng; Yao, Dezhong; Gao, Lianli; Riedl, Valentin; Wohlschläger, Afra; Sorg, Christian

2018-02-19

Brain imaging reveals schizophrenia as a disorder of macroscopic brain networks. In particular, default mode and salience network (DMN, SN) show highly consistent alterations in both interacting brain activity and underlying brain structure. However, the same networks are also altered in major depression. This overlap in network alterations induces the question whether DMN and SN changes are different across both disorders, potentially indicating distinct underlying pathophysiological mechanisms. To address this question, we acquired T1-weighted, diffusion-weighted, and resting-state functional MRI in patients with schizophrenia, patients with major depression, and healthy controls. We measured regional gray matter volume, inter-regional structural and intrinsic functional connectivity of DMN and SN, and compared these measures across groups by generalized Wilcoxon rank tests, while controlling for symptoms and medication. When comparing patients with controls, we found in each patient group SN volume loss, impaired DMN structural connectivity, and aberrant DMN and SN functional connectivity. When comparing patient groups, SN gray matter volume loss and DMN structural connectivity reduction did not differ between groups, but in schizophrenic patients, functional hyperconnectivity between DMN and SN was less in comparison to depressed patients. Results provide evidence for distinct functional hyperconnectivity between DMN and SN in schizophrenia and major depression, while structural changes in DMN and SN were similar. Distinct hyperconnectivity suggests different pathophysiological mechanism underlying aberrant DMN-SN interactions in schizophrenia and depression.
Avoiding the Enumeration of Infeasible Elementary Flux Modes by Including Transcriptional Regulatory Rules in the Enumeration Process Saves Computational Costs

PubMed Central

Jungreuthmayer, Christian; Ruckerbauer, David E.; Gerstl, Matthias P.; Hanscho, Michael; Zanghellini, Jürgen

2015-01-01

Despite the significant progress made in recent years, the computation of the complete set of elementary flux modes of large or even genome-scale metabolic networks is still impossible. We introduce a novel approach to speed up the calculation of elementary flux modes by including transcriptional regulatory information into the analysis of metabolic networks. Taking into account gene regulation dramatically reduces the solution space and allows the presented algorithm to constantly eliminate biologically infeasible modes at an early stage of the computation procedure. Thereby, computational costs, such as runtime, memory usage, and disk space, are extremely reduced. Moreover, we show that the application of transcriptional rules identifies non-trivial system-wide effects on metabolism. Using the presented algorithm pushes the size of metabolic networks that can be studied by elementary flux modes to new and much higher limits without the loss of predictive quality. This makes unbiased, system-wide predictions in large scale metabolic networks possible without resorting to any optimization principle. PMID:26091045
Modelling the Energy Efficient Sensor Nodes for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Dahiya, R.; Arora, A. K.; Singh, V. R.

2015-09-01

Energy is an important requirement of wireless sensor networks for better performance. A widely employed energy-saving technique is to place nodes in sleep mode, corresponding to low-power consumption as well as to reduce operational capabilities. In this paper, Markov model of a sensor network is developed. The node is considered to enter a sleep mode. This model is used to investigate the system performance in terms of energy consumption, network capacity and data delivery delay.
Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease

PubMed Central

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

2017-01-01

Abstract Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer’s disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer’s disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer’s disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks—the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer’s disease patients with and without cerebrovascular disease. Alzheimer’s disease patients without cerebrovascular disease, but not Alzheimer’s disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer’s disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer’s disease patients with and without cerebrovascular disease. Across Alzheimer’s disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer’s disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer’s disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer’s disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer’s disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer’s disease network degeneration phenotype. PMID:29053778
Neurofeedback and the Neural Representation of Self: Lessons From Awake State and Sleep.

PubMed

Ioannides, Andreas A

2018-01-01

Neurofeedback has been around for half a century, but despite some promising results it is not yet widely appreciated. Recently, some of the concerns about neurofeedback have been addressed with functional magnetic resonance imaging and magnetoencephalography adding their contributions to the long history of neurofeedback with electroencephalography. Attempts to address other concerns related to methodological issues with new experiments and meta-analysis of earlier studies, have opened up new questions about its efficacy. A key concern about neurofeedback is the missing framework to explain how improvements in very different and apparently unrelated conditions are achieved. Recent advances in neuroscience begin to address this concern. A particularly promising approach is the analysis of resting state of fMRI data, which has revealed robust covariations in brain networks that maintain their integrity in sleep and even anesthesia. Aberrant activity in three brain wide networks (i.e., the default mode, central executive and salience networks) has been associated with a number of psychiatric disorders. Recent publications have also suggested that neurofeedback guides the restoration of "normal" activity in these three networks. Using very recent results from our analysis of whole night MEG sleep data together with key concepts from developmental psychology, cloaked in modern neuroscience terms, a theoretical framework is proposed for a neural representation of the self, located at the core of a double onion-like structure of the default mode network. This framework fits a number of old and recent neuroscientific findings, and unites the way attention and memory operate in awake state and during sleep. In the process, safeguards are uncovered, put in place by evolution, before any interference with the core representation of self can proceed. Within this framework, neurofeedback is seen as set of methods for restoration of aberrant activity in large scale networks. The framework also admits quantitative measures of improvements to be made by personalized neurofeedback protocols. Finally, viewed through the framework developed, neurofeedback's safe nature is revealed while raising some concerns for interventions that attempt to alter the neural self-representation bypassing the safeguards evolution has put in place.
Neurofeedback and the Neural Representation of Self: Lessons From Awake State and Sleep

PubMed Central

Ioannides, Andreas A.

2018-01-01

Neurofeedback has been around for half a century, but despite some promising results it is not yet widely appreciated. Recently, some of the concerns about neurofeedback have been addressed with functional magnetic resonance imaging and magnetoencephalography adding their contributions to the long history of neurofeedback with electroencephalography. Attempts to address other concerns related to methodological issues with new experiments and meta-analysis of earlier studies, have opened up new questions about its efficacy. A key concern about neurofeedback is the missing framework to explain how improvements in very different and apparently unrelated conditions are achieved. Recent advances in neuroscience begin to address this concern. A particularly promising approach is the analysis of resting state of fMRI data, which has revealed robust covariations in brain networks that maintain their integrity in sleep and even anesthesia. Aberrant activity in three brain wide networks (i.e., the default mode, central executive and salience networks) has been associated with a number of psychiatric disorders. Recent publications have also suggested that neurofeedback guides the restoration of “normal” activity in these three networks. Using very recent results from our analysis of whole night MEG sleep data together with key concepts from developmental psychology, cloaked in modern neuroscience terms, a theoretical framework is proposed for a neural representation of the self, located at the core of a double onion-like structure of the default mode network. This framework fits a number of old and recent neuroscientific findings, and unites the way attention and memory operate in awake state and during sleep. In the process, safeguards are uncovered, put in place by evolution, before any interference with the core representation of self can proceed. Within this framework, neurofeedback is seen as set of methods for restoration of aberrant activity in large scale networks. The framework also admits quantitative measures of improvements to be made by personalized neurofeedback protocols. Finally, viewed through the framework developed, neurofeedback’s safe nature is revealed while raising some concerns for interventions that attempt to alter the neural self-representation bypassing the safeguards evolution has put in place. PMID:29755332
Variability in baseline travel behaviour as a predictor of changes in commuting by active travel, car and public transport: a natural experimental study

PubMed Central

Heinen, Eva; Ogilvie, David

2016-01-01

Purpose To strengthen our understanding of the impact of baseline variability in mode choice on the likelihood of travel behaviour change. Methods Quasi-experimental analyses in a cohort study of 450 commuters exposed to a new guided busway with a path for walking and cycling in Cambridge, UK. Exposure to the intervention was defined using the shortest network distance from each participant’s home to the busway. Variability in commuter travel behaviour at baseline was defined using the Herfindahl–Hirschman Index, the number of different modes of transport used over a week, and the proportion of trips made by the main (combination of) mode(s). The outcomes were changes in the share of commute trips (i) involving any active travel, (ii) involving any public transport, and (iii) made entirely by car. Variability and change data were derived from a self-reported seven-day record collected before (2009) and after (2012) the intervention. Separate multinomial regression models were estimated to assess the influence of baseline variability on behaviour change, both independently and as an interaction effect with exposure to the intervention. Results All three measures of variability predicted changes in mode share in most models. The effect size for the intervention was slightly strengthened after including variability. Commuters with higher baseline variability were more likely to increase their active mode share (e.g. for HHI: relative risk ratio [RRR] for interaction 3.34, 95% CI 1.41, 7.89) and decrease their car mode share in response to the intervention (e.g. for HHI: RRR 7.50, 95% CI 2.52, 22.34). Conclusions People reporting a higher level of variability in mode choice were more likely to change their travel behaviour following an intervention. Future research should consider such variability as a potential predictor and effect modifier of travel and physical activity behaviour change, and its significance for the design and targeting of interventions. PMID:27200265
Ultra-thin silicon (UTSi) on insulator CMOS transceiver and time-division multiplexed switch chips for smart pixel integration

NASA Astrophysics Data System (ADS)

Zhang, Liping; Sawchuk, Alexander A.

2001-12-01

We describe the design, fabrication and functionality of two different 0.5 micron CMOS optoelectronic integrated circuit (OEIC) chips based on the Peregrine Semiconductor Ultra-Thin Silicon on insulator technology. The Peregrine UTSi silicon- on-sapphire (SOS) technology is a member of the silicon-on- insulator (SOI) family. The low-loss synthetic sapphire substrate is optically transparent and has good thermal conductivity and coefficient of thermal expansion properties, which meet the requirements for flip-chip bonding of VCSELs and other optoelectronic input-output components. One chip contains transceiver and network components, including four channel high-speed CMOS transceiver modules, pseudo-random bit stream (PRBS) generators, a voltage controlled oscillator (VCO) and other test circuits. The transceiver chips can operate in both self-testing mode and networking mode. An on- chip clock and true-single-phase-clock (TSPC) D-flip-flop have been designed to generate a PRBS at over 2.5 Gb/s for the high-speed transceiver arrays to operate in self-testing mode. In the networking mode, an even number of transceiver chips forms a ring network through free-space or fiber ribbon interconnections. The second chip contains four channel optical time-division multiplex (TDM) switches, optical transceiver arrays, an active pixel detector and additional test devices. The eventual applications of these chips will require monolithic OEICs with integrated optical input and output. After fabrication and testing, the CMOS transceiver array dies will be packaged with 850 nm vertical cavity surface emitting lasers (VCSELs), and metal-semiconductor- metal (MSM) or GaAs p-i-n detector die arrays to achieve high- speed optical interconnections. The hybrid technique could be either wire bonding or flip-chip bonding of the CMOS SOS smart-pixel arrays with arrays of VCSELs and photodetectors onto an optoelectronic chip carrier as a multi-chip module (MCM).
Physics of Financial Markets: Can we Understand the Unpredictable Phenomenon of Flash Crashes

NASA Astrophysics Data System (ADS)

Stanley, H. Eugene

2015-03-01

Dangerous vulnerability is hiding in complex systems. Indeed, disasters ranging from abrupt financial ``flash crashes'' and large-scale power outages to sudden death among the elderly dramatically exemplify this fact. While we can understand the cause of most events in complex systems, sudden unexpected ``black swans'' whether in economics or in the ``physicists world'' cry out for insight. To design more resilient systems we will describe recent results seeking understanding of these black swans. In many real-world phenomena, such as brain seizures in neuroscience or sudden market crashes in finance, after an inactive period of time a significant part of the damaged network is capable of spontaneously becoming active again. The process often occurs repeatedly. To model this marked network recovery, we examine the effect of local node recoveries and stochastic contiguous spreading, and find that they can lead to the spontaneous emergence of macroscopic ``phase-flipping'' phenomena. The fraction of active nodes switches back and forth between the two network collective modes characterized by high network activity and low network activity. Furthermore, the system exhibits a strong hysteresis behavior analogous to phase transitions near a critical point [A. Majdandzic, B. Podobnik, S. V. Buldyrev, D. Y. Kenett, S. Havlin, and H. E. Stanley, ``Spontaneous Recovery in Dynamic Networks,'' Nature Physics 10, 34 (2014)]. This work was carried out in collaboration with a number of colleagues, chief among whom are A. Majdanzic, B. Podobnik, S. V. Buldyrev, D. Y. Kenett, and S. Havlin.
Information Flow in Interaction Networks II: Channels, Path Lengths, and Potentials

PubMed Central

Stojmirović, Aleksandar

2012-01-01

Abstract In our previous publication, a framework for information flow in interaction networks based on random walks with damping was formulated with two fundamental modes: emitting and absorbing. While many other network analysis methods based on random walks or equivalent notions have been developed before and after our earlier work, one can show that they can all be mapped to one of the two modes. In addition to these two fundamental modes, a major strength of our earlier formalism was its accommodation of context-specific directed information flow that yielded plausible and meaningful biological interpretation of protein functions and pathways. However, the directed flow from origins to destinations was induced via a potential function that was heuristic. Here, with a theoretically sound approach called the channel mode, we extend our earlier work for directed information flow. This is achieved by constructing a potential function facilitating a purely probabilistic interpretation of the channel mode. For each network node, the channel mode combines the solutions of emitting and absorbing modes in the same context, producing what we call a channel tensor. The entries of the channel tensor at each node can be interpreted as the amount of flow passing through that node from an origin to a destination. Similarly to our earlier model, the channel mode encompasses damping as a free parameter that controls the locality of information flow. Through examples involving the yeast pheromone response pathway, we illustrate the versatility and stability of our new framework. PMID:22409812
Frontoparietal cognitive control of verbal memory recall in Alzheimer's disease.

PubMed

Dhanjal, Novraj S; Wise, Richard J S

2014-08-01

Episodic memory retrieval is reliant upon cognitive control systems, of which 2 have been identified with functional neuroimaging: a cingulo-opercular salience network (SN) and a frontoparietal executive network (EN). In Alzheimer's disease (AD), pathology is distributed throughout higher-order cortices. The hypotheses were that this frontoparietal pathology would impair activity associated with verbal memory recall; and that central cholinesterase inhibition (ChI) would modulate this, improving memory recall. Functional magnetic resonance imaging was used to study normal participants and 2 patient groups: mild cognitive impairment (MCI) and AD. Activity within the EN and SN was observed during free recall of previously heard sentences, and related to measures of recall accuracy. In normal subjects, trials with reduced recall were associated with greater activity in both the SN and EN. Better recall was associated with greater activity in medial regions of the default mode network. By comparison, AD patients showed attenuated responses in both the SN and EN compared with either controls or MCI patients, even after recall performance was matched between groups. Following ChI, AD patients showed no modulation of activity within the SN, but increased activity within the EN. There was also enhanced activity within regions associated with episodic and semantic memory during less successful recall, requiring greater cognitive control. The results indicate that in AD, impaired responses of cognitive control networks during verbal memory recall are partly responsible for reduced recall performance. One action of symptom-modifying treatment is partially to reverse the abnormal function of frontoparietal cognitive control and temporal lobe memory networks. © 2014 American Neurological Association.

Transcranial light-emitting diode therapy for neuropsychological improvement after traumatic brain injury: a new perspective for diffuse axonal lesion management

PubMed Central

dos Santos, João Gustavo Rocha Peixoto; Paiva, Wellingson Silva; Teixeira, Manoel Jacobsen

2018-01-01

The cost of traumatic brain injury (TBI) for public health policies is undeniable today. Even patients who suffer from mild TBI may persist with cognitive symptoms weeks after the accident. Most of them show no lesion in computed tomography or conventional magnetic resonance imaging, but microstructural white matter abnormalities (diffuse axonal lesion) can be found in diffusion tensor imaging. Different brain networks work together to form an important part of the cognition process, and they can be affected by TBI. The default mode network (DMN) plays an important central role in normal brain activities, presenting greater relative deactivation during more cognitively demanding tasks. After deactivation, it allows a distinct network to activate. This network (the central executive network) acts mainly during tasks involving executive functions. The salience network is another network necessary for normal executive function, and its activation leads to deactivation of the DMN. The use of red or near-infrared (NIR) light to stimulate or regenerate tissue is known as photobiomodulation. It was discovered that NIR (wavelength 800–900 nm) and red (wavelength 600 nm) light-emitting diodes (LEDs) are able to penetrate through scalp and skull and have the potential to improve the subnormal, cellular activity of compromised brain tissue. Based on this, different experimental and clinical studies were done to test LED therapy for TBI, and promising results were found. It leads us to consider developing different approaches to maximize the positive effects of this therapy and improve the quality of life of TBI patients. PMID:29731669
Transcranial light-emitting diode therapy for neuropsychological improvement after traumatic brain injury: a new perspective for diffuse axonal lesion management.

PubMed

Dos Santos, João Gustavo Rocha Peixoto; Paiva, Wellingson Silva; Teixeira, Manoel Jacobsen

2018-01-01

The cost of traumatic brain injury (TBI) for public health policies is undeniable today. Even patients who suffer from mild TBI may persist with cognitive symptoms weeks after the accident. Most of them show no lesion in computed tomography or conventional magnetic resonance imaging, but microstructural white matter abnormalities (diffuse axonal lesion) can be found in diffusion tensor imaging. Different brain networks work together to form an important part of the cognition process, and they can be affected by TBI. The default mode network (DMN) plays an important central role in normal brain activities, presenting greater relative deactivation during more cognitively demanding tasks. After deactivation, it allows a distinct network to activate. This network (the central executive network) acts mainly during tasks involving executive functions. The salience network is another network necessary for normal executive function, and its activation leads to deactivation of the DMN. The use of red or near-infrared (NIR) light to stimulate or regenerate tissue is known as photobiomodulation. It was discovered that NIR (wavelength 800-900 nm) and red (wavelength 600 nm) light-emitting diodes (LEDs) are able to penetrate through scalp and skull and have the potential to improve the subnormal, cellular activity of compromised brain tissue. Based on this, different experimental and clinical studies were done to test LED therapy for TBI, and promising results were found. It leads us to consider developing different approaches to maximize the positive effects of this therapy and improve the quality of life of TBI patients.
Intrinsic brain connectivity in fibromyalgia is associated with chronic pain intensity.

PubMed

Napadow, Vitaly; LaCount, Lauren; Park, Kyungmo; As-Sanie, Sawsan; Clauw, Daniel J; Harris, Richard E

2010-08-01

Fibromyalgia (FM) is considered to be the prototypical central chronic pain syndrome and is associated with widespread pain that fluctuates spontaneously. Multiple studies have demonstrated altered brain activity in these patients. The objective of this study was to investigate the degree of connectivity between multiple brain networks in patients with FM, as well as how activity in these networks correlates with the level of spontaneous pain. Resting-state functional magnetic resonance imaging (FMRI) data from 18 patients with FM and 18 age-matched healthy control subjects were analyzed using dual-regression independent components analysis, which is a data-driven approach for the identification of independent brain networks. Intrinsic, or resting-state, connectivity was evaluated in multiple brain networks: the default mode network (DMN), the executive attention network (EAN), and the medial visual network (MVN), with the MVN serving as a negative control. Spontaneous pain levels were also analyzed for covariance with intrinsic connectivity. Patients with FM had greater connectivity within the DMN and right EAN (corrected P [P(corr)] < 0.05 versus controls), and greater connectivity between the DMN and the insular cortex, which is a brain region known to process evoked pain. Furthermore, greater intensity of spontaneous pain at the time of the FMRI scan correlated with greater intrinsic connectivity between the insula and both the DMN and right EAN (P(corr) < 0.05). These findings indicate that resting brain activity within multiple networks is associated with spontaneous clinical pain in patients with FM. These findings may also have broader implications for how subjective experiences such as pain arise from a complex interplay among multiple brain networks.
Intrinsic Brain Connectivity in Fibromyalgia is Associated with Chronic Pain Intensity

PubMed Central

Napadow, Vitaly; LaCount, Lauren; Park, Kyungmo; As-Sanie, Suzie; Clauw, Daniel J; Harris, Richard E

2010-01-01

OBJECTIVE Fibromyalgia (FM) is considered to be the prototypical central chronic pain syndrome and is associated with widespread pain that fluctuates spontaneously. Multiple studies have demonstrated altered brain activity in these patients. Our objective was to investigate the degree of connectivity between multiple brain networks in FM, as well as how activity in these networks correlates with spontaneous pain. METHODS Resting functional magnetic resonance imaging (fMRI) data in FM patients (n=18) and age-matched healthy controls (HC, n=18) were analyzed using dual regression independent component analysis (ICA) - a data driven approach used to identify independent brain networks. We evaluated intrinsic, or resting, connectivity in multiple brain networks: the default mode network (DMN), the executive attention network (EAN), and the medial visual network (MVN), with the MVN serving as a negative control. Spontaneous pain levels were also covaried with intrinsic connectivity. RESULTS We found that FM patients had greater connectivity within the DMN and right EAN (rEAN; p<0.05, corrected), and greater connectivity between the DMN and the insular cortex – a brain region known to process evoked pain. Furthermore, greater spontaneous pain at the time of the scan correlated with greater intrinsic connectivity between the insula and both the DMN and rEAN (p<0.05, corrected). CONCLUSION Our findings indicate that resting brain activity within multiple networks is associated with spontaneous clinical pain in FM. These findings may also have broader implications for how subjective experiences such as pain arise from a complex interplay amongst multiple brain networks. PMID:20506181
Default mode network abnormalities during state switching in attention deficit hyperactivity disorder.

PubMed

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.
Violence-related content in video game may lead to functional connectivity changes in brain networks as revealed by fMRI-ICA in young men.

PubMed

Zvyagintsev, M; Klasen, M; Weber, R; Sarkheil, P; Esposito, F; Mathiak, K A; Schwenzer, M; Mathiak, K

2016-04-21

In violent video games, players engage in virtual aggressive behaviors. Exposure to virtual aggressive behavior induces short-term changes in players' behavior. In a previous study, a violence-related version of the racing game "Carmageddon TDR2000" increased aggressive affects, cognitions, and behaviors compared to its non-violence-related version. This study investigates the differences in neural network activity during the playing of both versions of the video game. Functional magnetic resonance imaging (fMRI) recorded ongoing brain activity of 18 young men playing the violence-related and the non-violence-related version of the video game Carmageddon. Image time series were decomposed into functional connectivity (FC) patterns using independent component analysis (ICA) and template-matching yielded a mapping to established functional brain networks. The FC patterns revealed a decrease in connectivity within 6 brain networks during the violence-related compared to the non-violence-related condition: three sensory-motor networks, the reward network, the default mode network (DMN), and the right-lateralized frontoparietal network. Playing violent racing games may change functional brain connectivity, in particular and even after controlling for event frequency, in the reward network and the DMN. These changes may underlie the short-term increase of aggressive affects, cognitions, and behaviors as observed after playing violent video games. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.
Evidence for hubs in human functional brain networks

PubMed Central

Power, Jonathan D; Schlaggar, Bradley L; Lessov-Schlaggar, Christina N; Petersen, Steven E

2013-01-01

Summary Hubs integrate and distribute information in powerful ways due to the number and positioning of their contacts in a network. Several resting state functional connectivity MRI reports have implicated regions of the default mode system as brain hubs; we demonstrate that previous degree-based approaches to hub identification may have identified portions of large brain systems rather than critical nodes of brain networks. We utilize two methods to identify hub-like brain regions: 1) finding network nodes that participate in multiple sub-networks of the brain, and 2) finding spatial locations where several systems are represented within a small volume. These methods converge on a distributed set of regions that differ from previous reports on hubs. This work identifies regions that support multiple systems, leading to spatially constrained predictions about brain function that may be tested in terms of lesions, evoked responses, and dynamic patterns of activity. PMID:23972601
How far can we go in chronic disorders of consciousness differential diagnosis? The use of neuromodulation in detecting internal and external awareness.

PubMed

Naro, Antonino; Leo, Antonino; Manuli, Alfredo; Cannavò, Antonino; Bramanti, Alessia; Bramanti, Placido; Calabrò, Rocco Salvatore

2017-05-04

Awareness generation and modulation may depend on a balanced information integration and differentiation across default mode network (DMN) and external awareness networks (EAN). Neuromodulation approaches, capable of shaping information processing, may highlight residual network activities supporting awareness, which are not detectable through active paradigms, thus allowing to differentiate chronic disorders of consciousness (DoC). We studied aftereffects of repetitive transcranial magnetic stimulation (rTMS) by applying graph theory within canonical frequency bands to compare the markers of these networks in the electroencephalographic data from 20 patients with DoC. We found that patients' high-frequency networks suffered from a large-scale connectivity breakdown, paralleled by a local hyperconnectivity, whereas low-frequency networks showed a preserved but dysfunctional large-scale connectivity. There was a correlation between metrics and the behavioral awareness. Interestingly, two persons with UWS showed a residual rTMS-induced modulation of the functional correlations between the DMN and the EAN, as observed in patients with MCS. Hence, we may hypothesize that the patients with UWS who demonstrate evidence of residual DMN-EAN functional correlation may be misdiagnosed, given that such residual network correlations could support covert consciousness. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.
Amelioration de la qualite d'energie d'un systeme de conversion d'energie eolienne a base de machine asynchrone a double alimentation et connecte au reseau electrique =

NASA Astrophysics Data System (ADS)

Abderrahim, Iheb

Wind power generation has grown strongly in the last decade. This results in the development of Wind Energy Conversion System WECS at the levels of modeling and electrical control. Modern WECS operate at varying wind speeds and are equipped with synchronous and asynchronous generators. Among these generators, the Doubly-Fed Induction Generator (DFIG) offers several advantages and capabilities of active and reactive power in four quadrants. WECS based DFIG also causes less conversion costs and minimum energy losses compared with a WECS based on a synchronous generator powered entirely by full scale of power converters. The connection of such a system to the electrical distribution network involves bidirectional operation of networks. This is clearly established in sub and super synchronous operating modes of DFIG. The grid provides the active power to the rotor of DFIG in sub synchronous operating mode and receives the active power of the rotor in super synchronous operating mode of DFIG. Energy quality is thus of major importance during the integration of wind power to the grid. Poor wave quality can affect network stability and could even cause major problems and consequences. This is even more critical where non-linear loads such as the switching power supplies and variable speed drives, are connected to the grid. The idea of this research work is how to mitigate the problems associated with the wave quality while ensuring better implementation of DFIG so that the whole of WECS remains insensitive to external disturbances and parametric variations. The Grid Side Converter (GSC) must be able to compensate harmonics, current unbalance and reactive power injected by a nonlinear three-phase unbalanced load connected to the grid. In addition to these innovative features to improve the conditions of operation of the grid, it provides also the power flow during different modes of operation of the DFIG. It is considered a simple, efficient and cost competitive solution by saving the use of other power equipment. At the same time, the energy efficiency of wind power conversion chain should be improved by extracting the MPPT. Searching allows us to select vector control and control in synchronous reference to achieve these objectives. WECS based DFIG is simulated in MATLAB SIMULINK in the presence of a non-linear balanced and unbalanced three-phase load.
The effect of visual and musical suspense on brain activation and memory during naturalistic viewing.

PubMed

Bezdek, Matthew A; Wenzel, William G; Schumacher, Eric H

2017-10-01

We tested the hypothesis that, during naturalistic viewing, moments of increasing narrative suspense narrow the scope of attentional focus. We also tested how changes in the emotional congruency of the music would affect brain responses to suspense, as well as subsequent memory for narrative events. In our study, participants viewed suspenseful film excerpts while brain activation was measured with functional magnetic resonance imaging. Results indicated that suspense produced a pattern of activation consistent with the attention-narrowing hypothesis. For example, we observed decreased activation in the anterior calcarine sulcus, which processes the visual periphery, and increased activity in nodes of the ventral attention network and decreased activity in nodes of the default mode network. Memory recall was more accurate for high suspense than low suspense moments, but did not differ by soundtrack congruency. These findings provide neural evidence that perceptual, attentional, and memory processes respond to suspense on a moment-by-moment basis. Copyright © 2017 Elsevier B.V. All rights reserved.
Allosteric mechanism of quinoline inhibitors for HIV RT-associated RNase with MD simulation and dynamics fluctuation network.

PubMed

Cai, Yi; Liu, Hao; Chen, Haifeng

2018-03-01

The human immunodeficiency virus (HIV) is a retrovirus which infects T lymphocyte of human body and causes immunodeficiency. Reverse transcriptase inhibitors (RTIs) can inhibit some functions of RT, preventing virus synthesis (double-stranded DNA), so that HIV virus replication can be reduced. Experimental results indicate a series of benzimidazole-based inhibitors which target HIV RT-associated RNase to inhibit the reverse transcription of HIV virus. However, the allosteric mechanism is still unclear. Here, molecular dynamics simulations and dynamics fluctuation network analysis were used to reveal the binding mode between the inhibitors and RT-associated RNase. The most active molecule has more hydrophobic and electrostatic interactions than the less active inhibitor. Dynamics correlation network analysis indicates that the most active inhibitor perturbs the network of RT-associated RNase and decreases the correlation of nodes. 3D-QSAR model suggests that two robust and reliable models were constructed and validated by independent test set. 3D-QSAR model also shows that bulky negatively charged or hydrophilic substituent is favorable to bioactivity. These results reveal the allosteric mechanism of quinoline inhibitors and help to improve the bioactivity. © 2017 John Wiley & Sons A/S.
Impact of fiber ring laser configuration on detection capabilities in FBG based sensor systems

NASA Astrophysics Data System (ADS)

Osuch, Tomasz; Kossek, Tomasz; Markowski, Konrad

2014-11-01

In this paper fiber ring lasers (FRL) as interrogation units for distributed fiber Bragg grating (FBG) based sensor networks are studied. In particular, two configurations of the fiber laser with erbium-doped fiber amplifier (EDFA) and semiconductor optical amplifier (SOA) as gain medium were analyzed. In the case of EDFA-based fiber interrogation systems, CW as well as active-mode locking operation were taken into account. The influence of spectral overlapping of FBGs spectra on detection capabilities of examined FRLs are presented. Experimental results show that the SOA-based fiber laser interrogation unit can operate as a multi-parametric sensing system. In turn, using an actively mode-locked fiber ring laser with an EDFA, an electronically switchable FBG based sensing system can be realized.
Shared protection based virtual network mapping in space division multiplexing optical networks

NASA Astrophysics Data System (ADS)

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.
Brain Connectivity in Pathological and Pharmacological Coma

PubMed Central

Noirhomme, Quentin; Soddu, Andrea; Lehembre, Rémy; Vanhaudenhuyse, Audrey; Boveroux, Pierre; Boly, Mélanie; Laureys, Steven

2010-01-01

Recent studies in patients with disorders of consciousness (DOC) tend to support the view that awareness is not related to activity in a single brain region but to thalamo-cortical connectivity in the frontoparietal network. Functional neuroimaging studies have shown preserved albeit disconnected low-level cortical activation in response to external stimulation in patients in a “vegetative state” or unresponsive wakefulness syndrome. While activation of these “primary” sensory cortices does not necessarily reflect conscious awareness, activation in higher-order associative cortices in minimally conscious state patients seems to herald some residual perceptual awareness. PET studies have identified a metabolic dysfunction in a widespread frontoparietal “global neuronal workspace” in DOC patients including the midline default mode network (“intrinsic” system) and the lateral frontoparietal cortices or “extrinsic system.” Recent studies have investigated the relation of awareness to the functional connectivity within intrinsic and extrinsic networks, and with the thalami in both pathological and pharmacological coma. In brain damaged patients, connectivity in all default network areas was found to be non-linearly correlated with the degree of clinical consciousness impairment, ranging from healthy controls and locked-in syndrome to minimally conscious, vegetative, coma, and brain dead patients. Anesthesia-induced loss of consciousness was also shown to correlate with a global decrease in cortico-cortical and thalamo-cortical connectivity in both intrinsic and extrinsic networks, but not in auditory, or visual networks. In anesthesia, unconsciousness was also associated with a loss of cross-modal interactions between networks. These results suggest that conscious awareness critically depends on the functional integrity of thalamo-cortical and cortico-cortical frontoparietal connectivity within and between “intrinsic” and “extrinsic” brain networks. PMID:21191476
Maturation of language networks in children: A systematic review of 22years of functional MRI.

PubMed

Weiss-Croft, Louise J; Baldeweg, Torsten

2015-12-01

Understanding how language networks change during childhood is important for theories of cognitive development and for identifying the neural causes of language impairment. Despite this, there is currently little systematic evidence regarding the typical developmental trajectory for language from the field of neuroimaging. We reviewed functional MRI (fMRI) studies published between 1992 and 2014, and quantified the evidence for age-related changes in localisation and lateralisation of fMRI activation in the language network (excluding the cerebellum and subcortical regions). Although age-related changes differed according to task type and input modality, we identified four consistent findings concerning the typical maturation of the language system. First, activation in core semantic processing regions increases with age. Second, activation in lower-level sensory and motor regions increases with age as activation in higher-level control regions reduces. We suggest that this reflects increased automaticity of language processing as children become more proficient. Third, the posterior cingulate cortex and precuneus (regions associated with the default mode network) show increasing attenuation across childhood and adolescence. Finally, language lateralisation is established by approximately 5years of age. Small increases in leftward lateralisation are observed in frontal regions, but these are tightly linked to performance. Copyright © 2015 Elsevier Inc. All rights reserved.
Single-mode fiber systems for deep space communication network

NASA Technical Reports Server (NTRS)

Lutes, G.

1982-01-01

The present investigation is concerned with the development of single-mode optical fiber distribution systems. It is pointed out that single-mode fibers represent potentially a superior medium for the distribution of frequency and timing reference signals and wideband (400 MHz) IF signals. In this connection, single-mode fibers have the potential to improve the capability and precision of NASA's Deep Space Network (DSN). Attention is given to problems related to precise time synchronization throughout the DSN, questions regarding the selection of a transmission medium, and the function of the distribution systems, taking into account specific improvements possible by an employment of single-mode fibers.
Dynamic Brain Network Correlates of Spontaneous Fluctuations in Attention.

PubMed

Kucyi, Aaron; Hove, Michael J; Esterman, Michael; Hutchison, R Matthew; Valera, Eve M

2017-03-01

Human attention is intrinsically dynamic, with focus continuously shifting between elements of the external world and internal, self-generated thoughts. Communication within and between large-scale brain networks also fluctuates spontaneously from moment to moment. However, the behavioral relevance of dynamic functional connectivity and possible link with attentional state shifts is unknown. We used a unique approach to examine whether brain network dynamics reflect spontaneous fluctuations in moment-to-moment behavioral variability, a sensitive marker of attentional state. Nineteen healthy adults were instructed to tap their finger every 600 ms while undergoing fMRI. This novel, but simple, approach allowed us to isolate moment-to-moment fluctuations in behavioral variability related to attention, independent of common confounds in cognitive tasks (e.g., stimulus changes, response inhibition). Spontaneously increasing tap variance ("out-of-the-zone" attention) was associated with increasing activation in dorsal-attention and salience network regions, whereas decreasing tap variance ("in-the-zone" attention) was marked by increasing activation of default mode network (DMN) regions. Independent of activation, tap variance representing out-of-the-zone attention was also time-locked to connectivity both within DMN and between DMN and salience network regions. These results provide novel mechanistic data on the understudied neural dynamics of everyday, moment-to-moment attentional fluctuations, elucidating the behavioral importance of spontaneous, transient coupling within and between attention-relevant networks. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Reorganization of functional brain networks mediates the improvement of cognitive performance following real-time neurofeedback training of working memory.

PubMed

Zhang, Gaoyan; Yao, Li; Shen, Jiahui; Yang, Yihong; Zhao, Xiaojie

2015-05-01

Working memory (WM) is essential for individuals' cognitive functions. Neuroimaging studies indicated that WM fundamentally relied on a frontoparietal working memory network (WMN) and a cinguloparietal default mode network (DMN). Behavioral training studies demonstrated that the two networks can be modulated by WM training. Different from the behavioral training, our recent study used a real-time functional MRI (rtfMRI)-based neurofeedback method to conduct WM training, demonstrating that WM performance can be significantly improved after successfully upregulating the activity of the target region of interest (ROI) in the left dorsolateral prefrontal cortex (Zhang et al., [2013]: PloS One 8:e73735); however, the neural substrate of rtfMRI-based WM training remains unclear. In this work, we assessed the intranetwork and internetwork connectivity changes of WMN and DMN during the training, and their correlations with the change of brain activity in the target ROI as well as with the improvement of post-training behavior. Our analysis revealed an "ROI-network-behavior" correlation relationship underlying the rtfMRI training. Further mediation analysis indicated that the reorganization of functional brain networks mediated the effect of self-regulation of the target brain activity on the improvement of cognitive performance following the neurofeedback training. The results of this study enhance our understanding of the neural basis of real-time neurofeedback and suggest a new direction to improve WM performance by regulating the functional connectivity in the WM related networks. © 2014 Wiley Periodicals, Inc.
Networked dynamical systems with linear coupling: synchronisation patterns, coherence and other behaviours.

PubMed

Judd, Kevin

2013-12-01

Many physical and biochemical systems are well modelled as a network of identical non-linear dynamical elements with linear coupling between them. An important question is how network structure affects chaotic dynamics, for example, by patterns of synchronisation and coherence. It is shown that small networks can be characterised precisely into patterns of exact synchronisation and large networks characterised by partial synchronisation at the local and global scale. Exact synchronisation modes are explained using tools of symmetry groups and invariance, and partial synchronisation is explained by finite-time shadowing of exact synchronisation modes.
Parallelization of Nullspace Algorithm for the computation of metabolic pathways

PubMed Central

Jevremović, Dimitrije; Trinh, Cong T.; Srienc, Friedrich; Sosa, Carlos P.; Boley, Daniel

2011-01-01

Elementary mode analysis is a useful metabolic pathway analysis tool in understanding and analyzing cellular metabolism, since elementary modes can represent metabolic pathways with unique and minimal sets of enzyme-catalyzed reactions of a metabolic network under steady state conditions. However, computation of the elementary modes of a genome- scale metabolic network with 100–1000 reactions is very expensive and sometimes not feasible with the commonly used serial Nullspace Algorithm. In this work, we develop a distributed memory parallelization of the Nullspace Algorithm to handle efficiently the computation of the elementary modes of a large metabolic network. We give an implementation in C++ language with the support of MPI library functions for the parallel communication. Our proposed algorithm is accompanied with an analysis of the complexity and identification of major bottlenecks during computation of all possible pathways of a large metabolic network. The algorithm includes methods to achieve load balancing among the compute-nodes and specific communication patterns to reduce the communication overhead and improve efficiency. PMID:22058581

Genetic Interaction Is Associated with Lower Metabolic Connectivity and Memory Impairment in Clinically Mild Alzheimer's Disease.

PubMed

Chang, Ya-Ting; Huang, Chi-Wei; Huang, Shu-Hua; Hsu, Shih-Wei; Chang, Wen-Neng; Lee, Jun-Jun; Chang, Chiung-Chih

2018-06-08

Metabolic connectivity as revealed by [18F] fluorodeoxyglucose positron emission tomography reflects neuronal connectivity. The aim of this study was to investigate the genetic impact on metabolic connectivity in default mode subnetworks and its clinical-pathological relationships in patients with Alzheimer's disease. We separately investigated the modulation of two default mode subnetworks, as identified with independent component analysis, by comparing APOE-ε4 carriers to non-carriers with Alzheimer's disease. We further analyzed the interaction effects of APOE (APOE-ε4 carriers versus non-carriers) with PICALM (rs3851179-GG versus rs3851179-A-allele carriers) on episodic memory deficits, reduction in cerebral metabolic rate for glucose, and decreased metabolic connectivity in default mode subnetworks. The metabolic connectivity in the ventral default mode network was positively correlated with episodic memory scores (β= 0.441, p< 0.001). The APOE-ε4 carriers had significantly lower metabolic connectivity in the ventral default mode network than the APOE-ε4 carriers (t(96)= -2.233, P= 0.028). There was an effect of the APOE-PICALM (rs3851179) interactions on reduced cerebral metabolic rate for glucose in regions of ventral default mode network (p< 0.001), and on memory deficits (F3,93= 5.568, p= 0.020). This study identified that PICALM may modulates memory deficits, reduced cerebral metabolic rate for glucose, and decreased metabolic connectivity in the ventral default mode network in APOE-ε4 carriers. [18F] fluorodeoxyglucose positron emission tomography-based metabolic connectivity may serve a useful tool to elucidate the neural networks underlying clinical-pathological relationships in Alzheimer's disease. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
On the Synchronization of EEG Spindle Waves

NASA Astrophysics Data System (ADS)

Long, Wen; Zhang, ChengFu; Zhao, SiLan; Shi, RuiHong

2000-06-01

Based on recently sleeping cellular substrates, a network model synaptically coupled by N three-cell circuits is provided. Simulation results show that: (i) the dynamic behavior of every circuit is chaotic; (ii) the synchronization of the network is incomplete; (iii) the incomplete synchronization can integrate burst firings of cortical cells into waxing-and-wanning EEG spindle waves. These results enlighten us that this kind of incomplete synchronization may integrate microscopic, electrical activities of neurons in billions into macroscopic, functional states in human brain. In addition, the effects of coupling strength, connectional mode and noise to the synchronization are discussed.
The Financing of Community and Public Access Channels on Cable Television Networks in Member Countries of the Council of Europe.

ERIC Educational Resources Information Center

International Inst. of Communications, London (England).

This survey of the current situation in 12 European countries, where cable television has moved from only passive distribution of broadcast signals to the active mode of local origination, includes both official and unofficial discussion about future cable possibilities. The study begins by clarifying the different contexts in which local…
Regional Homogeneity within the Default Mode Network in Bipolar Depression: A Resting-State Functional Magnetic Resonance Imaging Study

PubMed Central

Liu, Chun-Hong; Ma, Xin; Li, Feng; Wang, Yong-Jun; Tie, Chang-Le; Li, Su-Fang; Chen, Tao-Lin; Fan, Ting-ting; Zhang, Yu; Dong, Jie; Yao, Li; Wu, Xia; Wang, Chuan-Yue

2012-01-01

Aim We sought to use a regional homogeneity (ReHo) approach as an index in resting-state functional magnetic resonance imaging (fMRI) to investigate the features of spontaneous brain activity within the default mode network (DMN) in patients suffering from bipolar depression (BD). Methods Twenty-six patients with BD and 26 gender-, age-, and education-matched healthy subjects participated in the resting-state fMRI scans. We compared the differences in ReHo between the two groups within the DMN and investigated the relationships between sex, age, years of education, disease duration, the Hamilton Rating Scale for Depression (HAMD) total score, and ReHo in regions with significant group differences. Results Our results revealed that bipolar depressed patients had increased ReHo in the left medial frontal gyrus and left inferior parietal lobe compared to healthy controls. No correlations were found between regional ReHo values and sex, age, and clinical features within the BD group. Conclusions Our findings indicate that abnormal brain activity is mainly distributed within prefrontal-limbic circuits, which are believed to be involved in the pathophysiological mechanisms underlying bipolar depression. PMID:23133615
Objective assessment of the contribution of the RECOPESCA network to the monitoring of 3D coastal ocean variables in the Bay of Biscay and the English Channel

NASA Astrophysics Data System (ADS)

Lamouroux, Julien; Charria, Guillaume; De Mey, Pierre; Raynaud, Stéphane; Heyraud, Catherine; Craneguy, Philippe; Dumas, Franck; Le Hénaff, Matthieu

2016-04-01

In the Bay of Biscay and the English Channel, in situ observations represent a key element to monitor and to understand the wide range of processes in the coastal ocean and their direct impacts on human activities. An efficient way to measure the hydrological content of the water column over the main part of the continental shelf is to consider ships of opportunity as the surface to cover is wide and could be far from the coast. In the French observation strategy, the RECOPESCA programme, as a component of the High frequency Observation network for the environment in coastal SEAs (HOSEA), aims to collect environmental observations from sensors attached to fishing nets. In the present study, we assess that network using the Array Modes (ArM) method (a stochastic implementation of Le Hénaff et al. Ocean Dyn 59: 3-20. doi: 10.1007/s10236-008-0144-7, 2009). That model ensemble-based method is used here to compare model and observation errors and to quantitatively evaluate the performance of the observation network at detecting prior (model) uncertainties, based on hypotheses on error sources. A reference network, based on fishing vessel observations in 2008, is assessed using that method. Considering the various seasons, we show the efficiency of the network at detecting the main model uncertainties. Moreover, three scenarios, based on the reference network, a denser network in 2010 and a fictive network aggregated from a pluri-annual collection of profiles, are also analysed. Our sensitivity study shows the importance of the profile positions with respect to the sheer number of profiles for ensuring the ability of the network to describe the main error modes. More generally, we demonstrate the capacity of this method, with a low computational cost, to assess and to design new in situ observation networks.
A TDMA Broadcast Satellite/Ground Architecture for the Aeronautical Telecommunications Network

NASA Technical Reports Server (NTRS)

Shamma, Mohammed A.; Raghavan, Rajesh S.

2003-01-01

An initial evaluation of a TDMA satellite broadcast architecture with an integrated ground network is proposed in this study as one option for the Aeronautical Telecommunications Network (ATN). The architecture proposed consists of a ground based network that is dedicated to the reception and transmissions of Automatic Dependent Surveillance Broadcast (ADS-B) messages from Mode-S or UAT type systems, along with tracks from primary and secondary surveillance radars. Additionally, the ground network could contain VHF Digital Link Mode 2, 3 or 4 transceivers for the reception and transmissions of Controller-Pilot Data Link Communications (CPDLC) messages and for voice. The second part of the ATN network consists of a broadcast satellite based system that is mainly dedicated for the transmission of surveillance data as well as En-route Flight Information Service Broadcast (FIS-B) to all aircraft. The system proposed integrates those two network to provide a nation wide comprehensive service utilizing near term or existing technologies and hence keeping the economic factor in prospective. The next few sections include a background introduction, the ground subnetwork, the satellite subnetwork, modeling and simulations, and conclusion and recommendations.
Integrated Model of Chemical Perturbations of a Biological ...

EPA Pesticide Factsheets

We demonstrate a computational network model that integrates 18 in vitro, high-throughput screening assays measuring estrogen receptor (ER) binding, dimerization, chromatin binding, transcriptional activation and ER-dependent cell proliferation. The network model uses activity patterns across the in vitro assays to predict whether a chemical is an ER agonist or antagonist, or is otherwise influencing the assays through a manner dependent on the physics and chemistry of the technology platform (“”assay interference”). The method is applied to a library of 1812 commercial and environmental chemicals, including 45 ER positive and negative reference chemicals. Among the reference chemicals, the network model correctly identified the agonists and antagonists with the exception of very weak compounds whose activity was outside the concentration range tested. The model agonist score also correlated with the expected potency class of the active reference chemicals. Of the 1812 chemicals evaluated, 52 (2.8%) were predicted to be strongly ER active in agonist or antagonist mode. This dataset and model were also used to begin a systematic investigation of assay interference. The most prominent cause of false-positive activity (activity in an assay that is likely not due to interaction of the chemical with ER) is cytotoxicity. The model provides the ability to prioritize a large set of important environmental chemicals with human exposure potential for additional in v
Few-mode fiber, splice and SDM component characterization by spatially-diverse optical vector network analysis.

PubMed

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.
Decentralized Energy Management System for Networked Microgrids in Grid-connected and Islanded Modes

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

Wang, Zhaoyu; Chen, Bokan; Wang, Jianhui

This paper proposes a decentralized energy management system (EMS) for the coordinated operation of networked Microgirds (MGs) in a distribution system. In the grid-connected mode, the distribution network operator (DNO) and each MG are considered as distinct entities with individual objectives to minimize their own operation costs. It is assumed that both dispatchable and renewable energy source (RES)-based distributed generators (DGs) exist in the distribution network and the networked MGs. In order to coordinate the operation of all entities, we apply a decentralized bi-level algorithm to solve the problem with the first level to conduct negotiations among all entities andmore » the second level to update the non-converging penalties. In the islanded mode, the objective of each MG is to maintain a reliable power supply to its customers. In order to take into account the uncertainties of DG outputs and load consumption, we formulate the problems as two-stage stochastic programs. The first stage is to determine base generation setpoints based on the forecasts and the second stage is to adjust the generation outputs based on the realized scenarios. Case studies of a distribution system with networked MGs demonstrate the effectiveness of the proposed methodology in both grid-connected and islanded modes.« less
Affective mentalizing and brain activity at rest in the behavioral variant of frontotemporal dementia

PubMed Central

Caminiti, Silvia P.; Canessa, Nicola; Cerami, Chiara; Dodich, Alessandra; Crespi, Chiara; Iannaccone, Sandro; Marcone, Alessandra; Falini, Andrea; Cappa, Stefano F.

2015-01-01

Background bvFTD patients display an impairment in the attribution of cognitive and affective states to others, reflecting GM atrophy in brain regions associated with social cognition, such as amygdala, superior temporal cortex and posterior insula. Distinctive patterns of abnormal brain functioning at rest have been reported in bvFTD, but their relationship with defective attribution of affective states has not been investigated. Objective To investigate the relationship among resting-state brain activity, gray matter (GM) atrophy and the attribution of mental states in the behavioral variant of fronto-temporal degeneration (bvFTD). Methods We compared 12 bvFTD patients with 30 age- and education-matched healthy controls on a) performance in a task requiring the attribution of affective vs. cognitive mental states; b) metrics of resting-state activity in known functional networks; and c) the relationship between task-performances and resting-state metrics. In addition, we assessed a connection between abnormal resting-state metrics and GM atrophy. Results Compared with controls, bvFTD patients showed a reduction of intra-network coherent activity in several components, as well as decreased strength of activation in networks related to attentional processing. Anomalous resting-state activity involved networks which also displayed a significant reduction of GM density. In patients, compared with controls, higher affective mentalizing performance correlated with stronger functional connectivity between medial prefrontal sectors of the default-mode and attentional/performance monitoring networks, as well as with increased coherent activity in components of the executive, sensorimotor and fronto-limbic networks. Conclusions Some of the observed effects may reflect specific compensatory mechanisms for the atrophic changes involving regions in charge of affective mentalizing. The analysis of specific resting-state networks thus highlights an intermediate level of analysis between abnormal brain structure and impaired behavioral performance in bvFTD, reflecting both dysfunction and compensation mechanisms. PMID:26594631
Imaging the where and when of tic generation and resting state networks in adult Tourette patients

PubMed Central

Neuner, Irene; Werner, Cornelius J.; Arrubla, Jorge; Stöcker, Tony; Ehlen, Corinna; Wegener, Hans P.; Schneider, Frank; Shah, N. Jon

2014-01-01

Introduction: Tourette syndrome (TS) is a neuropsychiatric disorder with the core phenomenon of tics, whose origin and temporal pattern are unclear. We investigated the When and Where of tic generation and resting state networks (RSNs) via functional magnetic resonance imaging (fMRI). Methods: Tic-related activity and the underlying RSNs in adult TS were studied within one fMRI session. Participants were instructed to lie in the scanner and to let tics occur freely. Tic onset times, as determined by video-observance were used as regressors and added to preceding time-bins of 1 s duration each to detect prior activation. RSN were identified by independent component analysis (ICA) and correlated to disease severity by the means of dual regression. Results: Two seconds before a tic, the supplementary motor area (SMA), ventral primary motor cortex, primary sensorimotor cortex and parietal operculum exhibited activation; 1 s before a tic, the anterior cingulate, putamen, insula, amygdala, cerebellum and the extrastriatal-visual cortex exhibited activation; with tic-onset, the thalamus, central operculum, primary motor and somatosensory cortices exhibited activation. Analysis of resting state data resulted in 21 components including the so-called default-mode network. Network strength in those regions in SMA of two premotor ICA maps that were also active prior to tic occurrence, correlated significantly with disease severity according to the Yale Global Tic Severity Scale (YGTTS) scores. Discussion: We demonstrate that the temporal pattern of tic generation follows the cortico-striato-thalamo-cortical circuit, and that cortical structures precede subcortical activation. The analysis of spontaneous fluctuations highlights the role of cortical premotor structures. Our study corroborates the notion of TS as a network disorder in which abnormal RSN activity might contribute to the generation of tics in SMA. PMID:24904391
The Cerebral Cost of Breathing: An fMRI Case-Study in Congenital Central Hypoventilation Syndrome

PubMed Central

Sharman, Mike; Gallea, Cécile; Lehongre, Katia; Galanaud, Damien; Nicolas, Nathalie; Similowski, Thomas; Cohen, Laurent; Straus, Christian; Naccache, Lionel

2014-01-01

Certain motor activities - like walking or breathing - present the interesting property of proceeding either automatically or under voluntary control. In the case of breathing, brainstem structures located in the medulla are in charge of the automatic mode, whereas cortico-subcortical brain networks - including various frontal lobe areas - subtend the voluntary mode. We speculated that the involvement of cortical activity during voluntary breathing could impact both on the “resting state” pattern of cortical-subcortical connectivity, and on the recruitment of executive functions mediated by the frontal lobe. In order to test this prediction we explored a patient suffering from central congenital hypoventilation syndrome (CCHS), a very rare developmental condition secondary to brainstem dysfunction. Typically, CCHS patients demonstrate efficient cortically-controlled breathing while awake, but require mechanically-assisted ventilation during sleep to overcome the inability of brainstem structures to mediate automatic breathing. We used simultaneous EEG-fMRI recordings to compare patterns of brain activity between these two types of ventilation during wakefulness. As compared with spontaneous breathing (SB), mechanical ventilation (MV) restored the default mode network (DMN) associated with self-consciousness, mind-wandering, creativity and introspection in healthy subjects. SB on the other hand resulted in a specific increase of functional connectivity between brainstem and frontal lobe. Behaviorally, the patient was more efficient in cognitive tasks requiring executive control during MV than during SB, in agreement with her subjective reports in everyday life. Taken together our results provide insight into the cognitive and neural costs of spontaneous breathing in one CCHS patient, and suggest that MV during waking periods may free up frontal lobe resources, and make them available for cognitive recruitment. More generally, this study reveals how the active maintenance of cortical control over a continuous motor activity impacts on brain functioning and cognition. PMID:25268234
Introducing Co-Activation Pattern Metrics to Quantify Spontaneous Brain Network Dynamics

PubMed Central

Chen, Jingyuan E.; Chang, Catie; Greicius, Michael D.; Glover, Gary H.

2015-01-01

Recently, fMRI researchers have begun to realize that the brain's intrinsic network patterns may undergo substantial changes during a single resting state (RS) scan. However, despite the growing interest in brain dynamics, metrics that can quantify the variability of network patterns are still quite limited. Here, we first introduce various quantification metrics based on the extension of co-activation pattern (CAP) analysis, a recently proposed point-process analysis that tracks state alternations at each individual time frame and relies on very few assumptions; then apply these proposed metrics to quantify changes of brain dynamics during a sustained 2-back working memory (WM) task compared to rest. We focus on the functional connectivity of two prominent RS networks, the default-mode network (DMN) and executive control network (ECN). We first demonstrate less variability of global Pearson correlations with respect to the two chosen networks using a sliding-window approach during WM task compared to rest; then we show that the macroscopic decrease in variations in correlations during a WM task is also well characterized by the combined effect of a reduced number of dominant CAPs, increased spatial consistency across CAPs, and increased fractional contributions of a few dominant CAPs. These CAP metrics may provide alternative and more straightforward quantitative means of characterizing brain network dynamics than time-windowed correlation analyses. PMID:25662866
Scale invariant rearrangement of resting state networks in the human brain under sustained stimulation.

PubMed

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

2018-06-14

Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may be not the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation. Copyright © 2018. Published by Elsevier Inc.
Energy-saving scheme based on downstream packet scheduling in ethernet passive optical networks

NASA Astrophysics Data System (ADS)

Zhang, Lincong; Liu, Yejun; Guo, Lei; Gong, Xiaoxue

2013-03-01

With increasing network sizes, the energy consumption of Passive Optical Networks (PONs) has grown significantly. Therefore, it is important to design effective energy-saving schemes in PONs. Generally, energy-saving schemes have focused on sleeping the low-loaded Optical Network Units (ONUs), which tends to bring large packet delays. Further, the traditional ONU sleep modes are not capable of sleeping the transmitter and receiver independently, though they are not required to transmit or receive packets. Clearly, this approach contributes to wasted energy. Thus, in this paper, we propose an Energy-Saving scheme that is based on downstream Packet Scheduling (ESPS) in Ethernet PON (EPON). First, we design both an algorithm and a rule for downstream packet scheduling at the inter- and intra-ONU levels, respectively, to reduce the downstream packet delay. After that, we propose a hybrid sleep mode that contains not only ONU deep sleep mode but also independent sleep modes for the transmitter and the receiver. This ensures that the energy consumed by the ONUs is minimal. To realize the hybrid sleep mode, a modified GATE control message is designed that involves 10 time points for sleep processes. In ESPS, the 10 time points are calculated according to the allocated bandwidths in both the upstream and the downstream. The simulation results show that ESPS outperforms traditional Upstream Centric Scheduling (UCS) scheme in terms of energy consumption and the average delay for both real-time and non-real-time packets downstream. The simulation results also show that the average energy consumption of each ONU in larger-sized networks is less than that in smaller-sized networks; hence, our ESPS is better suited for larger-sized networks.
Random sampling of elementary flux modes in large-scale metabolic networks.

PubMed

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.
Aberrant cerebellar connectivity in motor and association networks in schizophrenia

PubMed Central

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

2015-01-01

Schizophrenia is a devastating illness characterized by disturbances in multiple domains. The cerebellum is involved in both motor and non-motor functions, and the “cognitive dysmetria” and “dysmetria of thought” models propose that abnormalities of the cerebellum may contribute to schizophrenia signs and symptoms. The cerebellum and cerebral cortex are reciprocally connected via a modular, closed-loop network architecture, but few schizophrenia neuroimaging studies have taken into account the topographical and functional heterogeneity of the cerebellum. In this study, using a previously defined 17-network cerebral cortical parcellation system as the basis for our functional connectivity seeds, we systematically investigated connectivity abnormalities within the cerebellum of 44 schizophrenia patients and 28 healthy control participants. We found selective alterations in cerebro-cerebellar functional connectivity. Specifically, schizophrenia patients showed decreased cerebro-cerebellar functional connectivity in higher level association networks (ventral attention, salience, control, and default mode networks) relative to healthy control participants. Schizophrenia patients also showed increased cerebro-cerebellar connectivity in somatomotor and default mode networks, with the latter showing no overlap with the regions found to be hypoconnected within the same default mode network. Finally, we found evidence to suggest that somatomotor and default mode networks may be inappropriately linked in schizophrenia. The relationship of these dysconnectivities to schizophrenia symptoms, such as neurological soft signs and altered sense of agency, is discussed. We conclude that the cerebellum ought to be considered for analysis in all future studies of network abnormalities in SZ, and further suggest the cerebellum as a potential target for further elucidation, and possibly treatment, of the underlying mechanisms and network abnormalities producing symptoms of schizophrenia. PMID:25852520
Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis

PubMed Central

Gopal, Shruti; Miller, Robyn L.; Michael, Andrew; Adali, Tulay; Cetin, Mustafa; Rachakonda, Srinivas; Bustillo, Juan R.; Cahill, Nathan; Baum, Stefi A.; Calhoun, Vince D.

2016-01-01

Spatial variability in resting functional MRI (fMRI) brain networks has not been well studied in schizophrenia, a disease known for both neurodevelopmental and widespread anatomic changes. Motivated by abundant evidence of neuroanatomical variability from previous studies of schizophrenia, we draw upon a relatively new approach called independent vector analysis (IVA) to assess this variability in resting fMRI networks. IVA is a blind-source separation algorithm, which segregates fMRI data into temporally coherent but spatially independent networks and has been shown to be especially good at capturing spatial variability among subjects in the extracted networks. We introduce several new ways to quantify differences in variability of IVA-derived networks between schizophrenia patients (SZs = 82) and healthy controls (HCs = 89). Voxelwise amplitude analyses showed significant group differences in the spatial maps of auditory cortex, the basal ganglia, the sensorimotor network, and visual cortex. Tests for differences (HC-SZ) in the spatial variability maps suggest, that at rest, SZs exhibit more activity within externally focused sensory and integrative network and less activity in the default mode network thought to be related to internal reflection. Additionally, tests for difference of variance between groups further emphasize that SZs exhibit greater network variability. These results, consistent with our prediction of increased spatial variability within SZs, enhance our understanding of the disease and suggest that it is not just the amplitude of connectivity that is different in schizophrenia, but also the consistency in spatial connectivity patterns across subjects. PMID:26106217
Mnemonic training reshapes brain networks to support superior memory

PubMed Central

Dresler, Martin; Shirer, William R.; Konrad, Boris N.; Müller, Nils C.J.; Wagner, Isabella C.; Fernández, Guillén; Czisch, Michael; Greicius, Michael D.

2017-01-01

Summary Memory skills strongly differ across the general population, however little is known about the brain characteristics supporting superior memory performance. Here, we assess functional brain network organization of 23 of the world’s most successful memory athletes and matched controls by fMRI during both task-free resting state baseline and active memory encoding. We demonstrate that in a group of naïve controls, functional connectivity changes induced by six weeks of mnemonic training were correlated with the network organization that distinguishes athletes from controls. During rest, this effect was mainly driven by connections between rather than within the visual, medial temporal lobe and default mode networks, whereas during task it was driven by connectivity within these networks. Similarity with memory athlete connectivity patterns predicted memory improvements up to 4 months after training. In conclusion, mnemonic training drives distributed rather than regional changes, reorganizing the brain’s functional network organization to enable superior memory performance. PMID:28279356
Network Solutions.

ERIC Educational Resources Information Center

Vietzke, Robert; And Others

1996-01-01

This special section explains the latest developments in networking technologies, profiles school districts benefiting from successful implementations, and reviews new products for building networks. Highlights include ATM (asynchronous transfer mode), cable modems, networking switches, Internet screening software, file servers, network management…

Effects of behavioral activation on default mode network connectivity in subthreshold depression: A preliminary resting-state fMRI study.

PubMed

Yokoyama, Satoshi; Okamoto, Yasumasa; Takagaki, Koki; Okada, Go; Takamura, Masahiro; Mori, Asako; Shiota, Syouichi; Ichikawa, Naho; Jinnin, Ran; Yamawaki, Shigeto

2018-02-01

Subthreshold depression is a risk factor for major depressive disorder, and it is known to have a negative impact on quality of life (QOL). Although behavioral activation, which is one type of cognitive behavioral therapy, is an effective psychological intervention for subthreshold depression, neural mechanisms of behavioral activation are unclear. Enhanced functional connectivity between default mode network (DMN) and the other regions has been demonstrated in participants with subthreshold depression. The purpose of this study was to examine the effects of behavioral activation on DMN abnormalities by using resting-state functional MRI (rs-fMRI). Participants with subthreshold depression (N =40) were randomly assigned to either an intervention group or a non-intervention group. They were scanned using rs-fMRI before and after the intervention. Independent component analysis indicated three subnetworks of the DMN. Analyzing intervention effects on functional connectivity of each subnetwork indicated that connectivity of the anterior DMN subnetwork with the dorsal anterior cingulate was reduced after the intervention. Moreover, this reduction was correlated with an increase in health-related QOL. We did not compare the findings with healthy participants. Further research should be conducted by including healthy controls to verify the results of this study. Mechanisms of behavioral activation might be related to enhanced ability to independently use the dACC and the DMN, which increases an attention control to positive external stimuli. This is the first study to investigate neural mechanisms of behavioral activation using rs-fMRI. Copyright © 2017 Elsevier B.V. All rights reserved.
Functional dissociation of ventral frontal and dorsomedial default mode network components during resting state and emotional autobiographical recall

PubMed Central

Bado, Patricia; Engel, Annerose; de Oliveira-Souza, Ricardo; Bramati, Ivanei E; Paiva, Fernando F; Basilio, Rodrigo; Sato, João R; Tovar-Moll, Fernanda; Moll, Jorge

2014-01-01

Humans spend a substantial share of their lives mind-wandering. This spontaneous thinking activity usually comprises autobiographical recall, emotional, and self-referential components. While neuroimaging studies have demonstrated that a specific brain “default mode network” (DMN) is consistently engaged by the “resting state” of the mind, the relative contribution of key cognitive components to DMN activity is still poorly understood. Here we used fMRI to investigate whether activity in neural components of the DMN can be differentially explained by active recall of relevant emotional autobiographical memories as compared with the resting state. Our study design combined emotional autobiographical memory, neutral memory and resting state conditions, separated by a serial subtraction control task. Shared patterns of activation in the DMN were observed in both emotional autobiographical and resting conditions, when compared with serial subtraction. Directly contrasting autobiographical and resting conditions demonstrated a striking dissociation within the DMN in that emotional autobiographical retrieval led to stronger activation of the dorsomedial core regions (medial prefrontal cortex, posterior cingulate cortex), whereas the resting state condition engaged a ventral frontal network (ventral striatum, subgenual and ventral anterior cingulate cortices) in addition to the IPL. Our results reveal an as yet unreported dissociation within the DMN. Whereas the dorsomedial component can be explained by emotional autobiographical memory, the ventral frontal one is predominantly associated with the resting state proper, possibly underlying fundamental motivational mechanisms engaged during spontaneous unconstrained ideation. Hum Brain Mapp 35:3302–3313, 2014. © 2013 Wiley Periodicals, Inc. PMID:25050426
Situating the default-mode network along a principal gradient of macroscale cortical organization

PubMed Central

Margulies, Daniel S.; Goulas, Alexandros; Falkiewicz, Marcel; Huntenburg, Julia M.; Langs, Georg; Bezgin, Gleb; Eickhoff, Simon B.; Castellanos, F. Xavier; Petrides, Michael; Jefferies, Elizabeth; Smallwood, Jonathan

2016-01-01

Understanding how the structure of cognition arises from the topographical organization of the cortex is a primary goal in neuroscience. Previous work has described local functional gradients extending from perceptual and motor regions to cortical areas representing more abstract functions, but an overarching framework for the association between structure and function is still lacking. Here, we show that the principal gradient revealed by the decomposition of connectivity data in humans and the macaque monkey is anchored by, at one end, regions serving primary sensory/motor functions and at the other end, transmodal regions that, in humans, are known as the default-mode network (DMN). These DMN regions exhibit the greatest geodesic distance along the cortical surface—and are precisely equidistant—from primary sensory/motor morphological landmarks. The principal gradient also provides an organizing spatial framework for multiple large-scale networks and characterizes a spectrum from unimodal to heteromodal activity in a functional metaanalysis. Together, these observations provide a characterization of the topographical organization of cortex and indicate that the role of the DMN in cognition might arise from its position at one extreme of a hierarchy, allowing it to process transmodal information that is unrelated to immediate sensory input. PMID:27791099
The Default Mode Network Differentiates Biological From Non-Biological Motion

PubMed Central

Dayan, Eran; Sella, Irit; Mukovskiy, Albert; Douek, Yehonatan; Giese, Martin A.; Malach, Rafael; Flash, Tamar

2016-01-01

The default mode network (DMN) has been implicated in an array of social-cognitive functions, including self-referential processing, theory of mind, and mentalizing. Yet, the properties of the external stimuli that elicit DMN activity in relation to these domains remain unknown. Previous studies suggested that motion kinematics is utilized by the brain for social-cognitive processing. Here, we used functional MRI to examine whether the DMN is sensitive to parametric manipulations of observed motion kinematics. Preferential responses within core DMN structures differentiating non-biological from biological kinematics were observed for the motion of a realistically looking, human-like avatar, but not for an abstract object devoid of human form. Differences in connectivity patterns during the observation of biological versus non-biological kinematics were additionally observed. Finally, the results additionally suggest that the DMN is coupled more strongly with key nodes in the action observation network, namely the STS and the SMA, when the observed motion depicts human rather than abstract form. These findings are the first to implicate the DMN in the perception of biological motion. They may reflect the type of information used by the DMN in social-cognitive processing. PMID:25217472
Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data.

PubMed

Sharaev, Maksim G; Zavyalova, Viktoria V; Ushakov, Vadim L; Kartashov, Sergey I; Velichkovsky, Boris M

2016-01-01

The Default Mode Network (DMN) is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of Blood-oxygen-level dependent (BOLD) activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e., effective connectivity), however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), left and right intraparietal cortex (LIPC and RIPC). For this purpose functional magnetic resonance imaging (fMRI) data from 30 healthy subjects (1000 time points from each one) was acquired and spectral dynamic causal modeling (DCM) on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078-0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (p < 0.05). Connections between mPFC and PCC are bidirectional, significant in the group and weaker than connections originating from bilateral IPC. In general, all connections from LIPC/RIPC to other DMN regions are much stronger. One can assume that these regions have a driving role within the DMN. Our results replicate some data from earlier works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain's functioning at resting state.
Multistability of the Brain Network for Self-other Processing

PubMed Central

Chen, Yi-An; Huang, Tsung-Ren

2017-01-01

Early fMRI studies suggested that brain areas processing self-related and other-related information were highly overlapping. Hypothesising functional localisation of the cortex, researchers have tried to locate “self-specific” and “other-specific” regions within these overlapping areas by subtracting suspected confounding signals in task-based fMRI experiments. Inspired by recent advances in whole-brain dynamic modelling, we instead explored an alternative hypothesis that similar spatial activation patterns could be associated with different processing modes in the form of different synchronisation patterns. Combining an automated synthesis of fMRI data with a presumption-free diffusion spectrum image (DSI) fibre-tracking algorithm, we isolated a network putatively composed of brain areas and white matter tracts involved in self-other processing. We sampled synchronisation patterns from the dynamical systems of this network using various combinations of physiological parameters. Our results showed that the self-other processing network, with simulated gamma-band activity, tended to stabilise at a number of distinct synchronisation patterns. This phenomenon, termed “multistability,” could serve as an alternative model in theorising the mechanism of processing self-other information. PMID:28256520
Reconfigurable optical interconnection network for multimode optical fiber sensor arrays

NASA Technical Reports Server (NTRS)

Chen, R. T.; Robinson, D.; Lu, H.; Wang, M. R.; Jannson, T.; Baumbick, R.

1992-01-01

A single-source, single-detector architecture has been developed to implement a reconfigurable optical interconnection network multimode optical fiber sensor arrays. The network was realized by integrating LiNbO3 electrooptic (EO) gratings working at the Raman Na regime and a massive fan-out waveguide hologram (WH) working at the Bragg regime onto a multimode glass waveguide. The glass waveguide utilized the whole substrate as a guiding medium. A 1-to-59 massive waveguide fan-out was demonstrated using a WH operating at 514 nm. Measured diffraction efficiency of 59 percent was experimentally confirmed. Reconfigurability of the interconnection was carried out by generating an EO grating through an externally applied electric field. Unlike conventional single-mode integrated optical devices, the guided mode demonstrated has an azimuthal symmetry in mode profile which is the same as that of a fiber mode.
Elementary signaling modes predict the essentiality of signal transduction network components

PubMed Central

2011-01-01

Background Understanding how signals propagate through signaling pathways and networks is a central goal in systems biology. Quantitative dynamic models help to achieve this understanding, but are difficult to construct and validate because of the scarcity of known mechanistic details and kinetic parameters. Structural and qualitative analysis is emerging as a feasible and useful alternative for interpreting signal transduction. Results In this work, we present an integrative computational method for evaluating the essentiality of components in signaling networks. This approach expands an existing signaling network to a richer representation that incorporates the positive or negative nature of interactions and the synergistic behaviors among multiple components. Our method simulates both knockout and constitutive activation of components as node disruptions, and takes into account the possible cascading effects of a node's disruption. We introduce the concept of elementary signaling mode (ESM), as the minimal set of nodes that can perform signal transduction independently. Our method ranks the importance of signaling components by the effects of their perturbation on the ESMs of the network. Validation on several signaling networks describing the immune response of mammals to bacteria, guard cell abscisic acid signaling in plants, and T cell receptor signaling shows that this method can effectively uncover the essentiality of components mediating a signal transduction process and results in strong agreement with the results of Boolean (logical) dynamic models and experimental observations. Conclusions This integrative method is an efficient procedure for exploratory analysis of large signaling and regulatory networks where dynamic modeling or experimental tests are impractical. Its results serve as testable predictions, provide insights into signal transduction and regulatory mechanisms and can guide targeted computational or experimental follow-up studies. The source codes for the algorithms developed in this study can be found at http://www.phys.psu.edu/~ralbert/ESM. PMID:21426566
Attention reorganizes connectivity across networks in a frequency specific manner.

PubMed

Kwon, Soyoung; Watanabe, Masataka; Fischer, Elvira; Bartels, Andreas

2017-01-01

Attention allows our brain to focus its limited resources on a given task. It does so by selective modulation of neural activity and of functional connectivity (FC) across brain-wide networks. While there is extensive literature on activity changes, surprisingly few studies examined brain-wide FC modulations that can be cleanly attributed to attention compared to matched visual processing. In contrast to prior approaches, we used an ultra-long trial design that avoided transients from trial onsets, included slow fluctuations (<0.1Hz) that carry important information on FC, and allowed for frequency-segregated analyses. We found that FC derived from long blocks had a nearly two-fold higher gain compared to FC derived from traditional (short) block designs. Second, attention enhanced intrinsic (negative or positive) correlations across networks, such as between the default-mode network (DMN), the dorsal attention network (DAN), and the visual system (VIS). In contrast attention de-correlated the intrinsically correlated visual regions. Third, the de-correlation within VIS was driven primarily by high frequencies, whereas the increase in DAN-VIS predominantly by low frequencies. These results pinpoint two fundamentally distinct effects of attention on connectivity. Information flow increases between distinct large-scale networks, and de-correlation within sensory cortex indicates decreased redundancy. Copyright © 2016 Elsevier Inc. All rights reserved.
Perturbed connectivity of the amygdala and its subregions with the central executive and default mode networks in chronic pain.

PubMed

Jiang, Ying; Oathes, Desmond; Hush, Julia; Darnall, Beth; Charvat, Mylea; Mackey, Sean; Etkin, Amit

2016-09-01

Maladaptive responses to pain-related distress, such as pain catastrophizing, amplify the impairments associated with chronic pain. Many of these aspects of chronic pain are similar to affective distress in clinical anxiety disorders. In light of the role of the amygdala in pain and affective distress, disruption of amygdalar functional connectivity in anxiety states, and its implication in the response to noxious stimuli, we investigated amygdala functional connectivity in 17 patients with chronic low back pain and 17 healthy comparison subjects, with respect to normal targets of amygdala subregions (basolateral vs centromedial nuclei), and connectivity to large-scale cognitive-emotional networks, including the default mode network, central executive network, and salience network. We found that patients with chronic pain had exaggerated and abnormal amygdala connectivity with central executive network, which was most exaggerated in patients with the greatest pain catastrophizing. We also found that the normally basolateral-predominant amygdala connectivity to the default mode network was blunted in patients with chronic pain. Our results therefore highlight the importance of the amygdala and its network-level interaction with large-scale cognitive/affective cortical networks in chronic pain, and help link the neurobiological mechanisms of cognitive theories for pain with other clinical states of affective distress.
Reorganization of large-scale cognitive networks during automation of imagination of a complex sequential movement.

PubMed

Sauvage, C; De Greef, N; Manto, M; Jissendi, P; Nioche, C; Habas, C

2015-04-01

We investigated the functional reconfiguration of the cerebral networks involved in imagination of sequential movements of the left foot, both performed at regular and fast speed after mental imagery training. Thirty-five volunteers were scanned with a 3T MRI while they imagined a sequence of ankle movements (dorsiflexion, plantar flexion, varus and valgus) before and after mental practice. Subjects were distributed in two groups: the first group executed regular movements whereas the second group made fast movements. We applied the general linear model (GLM) and model-free, exploratory tensorial independent component analytic (TICA) approaches to identify plastic post-training effects on brain activation. GLM showed that post-training imagination of movement was accompanied by a dual effect: a specific recruitment of a medial prefronto-cingulo-parietal circuit reminiscent of the default-mode network, with the left putamen, and a decreased activity of a lateral fronto-parietal network. Training-related subcortical changes only consisted in an increased activity in the left striatum. Unexpectedly, no difference was observed in the cerebellum. TICA also revealed involvement of the left executive network, and of the dorsal control executive network but no significant differences were found between pre- and post-training phases. Therefore, repetitive motor mental imagery induced specific putamen (motor rehearsal) recruitment that one previously observed during learning of overt movements, and, simultaneously, a specific shift of activity from the dorsolateral prefrontal cortex (attention, working memory) to the medial posterior parietal and cingulate cortices (mental imagery and memory rehearsal). Our data complement and confirm the notion that differential and coupled recruitment of cognitive networks can constitute a neural marker of training effects. Copyright © 2014 Elsevier Masson SAS. All rights reserved.
Resting-state EEG delta power is associated with psychological pain in adults with a history of depression.

PubMed

Meerwijk, Esther L; Ford, Judith M; Weiss, Sandra J

2015-02-01

Psychological pain is a prominent symptom of clinical depression. We asked if frontal alpha asymmetry, frontal EEG power, and frontal fractal dimension asymmetry predicted psychological pain in adults with a history of depression. Resting-state frontal EEG (F3/F4) was recorded while participants (N=35) sat upright with their eyes closed. Frontal delta power predicted psychological pain while controlling for depressive symptoms, with participants who exhibited less power experiencing greater psychological pain. Frontal fractal dimension asymmetry, a nonlinear measure of complexity, also predicted psychological pain, such that greater left than right complexity was associated with greater psychological pain. Frontal alpha asymmetry did not contribute unique variance to any regression model of psychological pain. As resting-state delta power is associated with the brain's default mode network, results suggest that the default mode network was less activated during high psychological pain. Findings are consistent with a state of arousal associated with psychological pain. Copyright © 2015 Elsevier B.V. All rights reserved.
Altered resting-state functional activity in isolated pontine infarction patients with pathological laughing and crying.

PubMed

Liu, Tao; Li, Jianjun; Huang, Shixiong; Li, Changqinq; Zhao, Zhongyan; Wen, Guoqiang; Chen, Feng

2017-10-13

We used resting-state functional magnetic resonance imaging to investigate the global spontaneous neural activity involved in pathological laughing and crying after stroke. Twelve pathological laughing and crying patients with isolated pontine infarction were included, along with 12 age- and gender-matched acute isolated pontine infarction patients without pathological laughing and crying, and 12 age- and gender-matched healthy controls. We examined both the amplitude of low-frequency fluctuation and the regional homogeneity in order to comprehensively evaluate the intrinsic activity in patients with post-stroke pathological laughing and crying. In the post-stroke pathological laughing and crying group, changes in these measures were observed mainly in components of the default mode network (medial prefrontal cortex/anterior cingulate cortex, middle temporal gyrus, inferior temporal gyrus, superior frontal gyrus, middle frontal gyrus and inferior parietal lobule), sensorimotor network (supplementary motor area, precentral gyrus and paracentral lobule), affective network (medial prefrontal cortex/anterior cingulate cortex, parahippocampal gyrus, middle temporal gyrus and inferior temporal gyrus) and cerebellar lobes (cerebellum posterior lobe). We therefore speculate that when disinhibition of the volitional system is lost, increased activation of the emotional system causes pathological laughing and crying.
Network Analysis Reveals a Common Host-Pathogen Interaction Pattern in Arabidopsis Immune Responses.

PubMed

Li, Hong; Zhou, Yuan; Zhang, Ziding

2017-01-01

Many plant pathogens secrete virulence effectors into host cells to target important proteins in host cellular network. However, the dynamic interactions between effectors and host cellular network have not been fully understood. Here, an integrative network analysis was conducted by combining Arabidopsis thaliana protein-protein interaction network, known targets of Pseudomonas syringae and Hyaloperonospora arabidopsidis effectors, and gene expression profiles in the immune response. In particular, we focused on the characteristic network topology of the effector targets and differentially expressed genes (DEGs). We found that effectors tended to manipulate key network positions with higher betweenness centrality. The effector targets, especially those that are common targets of an individual effector, tended to be clustered together in the network. Moreover, the distances between the effector targets and DEGs increased over time during infection. In line with this observation, pathogen-susceptible mutants tended to have more DEGs surrounding the effector targets compared with resistant mutants. Our results suggest a common plant-pathogen interaction pattern at the cellular network level, where pathogens employ potent local impact mode to interfere with key positions in the host network, and plant organizes an in-depth defense by sequentially activating genes distal to the effector targets.
Energy star compliant voice over internet protocol (VoIP) telecommunications network including energy star compliant VoIP devices

DOEpatents

Kouchri, Farrokh Mohammadzadeh

2012-11-06

A Voice over Internet Protocol (VoIP) communications system, a method of managing a communications network in such a system and a program product therefore. The system/network includes an ENERGY STAR (E-star) aware softswitch and E-star compliant communications devices at system endpoints. The E-star aware softswitch allows E-star compliant communications devices to enter and remain in power saving mode. The E-star aware softswitch spools messages and forwards only selected messages (e.g., calls) to the devices in power saving mode. When the E-star compliant communications devices exit power saving mode, the E-star aware softswitch forwards spooled messages.
Temporal relationship between the 2000 Miyake-Kozu seismovolcanic activity and the 2000 Tokai slow-slip event

NASA Astrophysics Data System (ADS)

Kawamura, Masashi; Yamaoka, Koshun

2009-02-01

We investigated the temporal relationship between the two events, namely, the seismovolcanic activity near the Miyakejima and Kozushima islands and the slow-slip event along the plate boundary in the Tokai district. The islands are located on the east of Tokai, and the Tokai slow-slip event was discovered immediately after the large crustal deformation caused by the volcanic activity in the Miyakejima-Kozushima regions ceased. However, the order of occurrence of these events is still controversial and its recognition will help us to understand the tectonic processes of the central part of Japan, where many volcanic and seismic activities occur. For this purpose, we applied the statistical approach (Kawamura, M., Yamaoka, K., 2006. Spatiotemporal characteristics of the displacement field revealed with principal component analysis and the mode-rotation technique, Tectonophys., 419, 55-73), which consists of principal component analysis (PCA) and a mode rotation procedure, to the displacement field provided by the nationwide GPS network (GEONET) in order to obtain the characteristic structures of spatiotemporal crustal deformation caused by the above two events. We divided the time period of analysis into two sections (namely, June 26, 1999 to June 25, 2000 and June 26, 2000 to June 25, 2002) by the day when the magma intrusion occurred beneath the Miyakejima volcano on June 26, 2000. The spatial and temporal modes for the first time period did not indicate any significant spatiotemporal patterns corresponding to the two events. This indicates the absence of episodic crustal deformations during this time period. On the contrary, the modes for the latter time period included the changes caused by these events. The two major modes included the spatiotemporal structures of the first and latter half periods of the Miyake-Kozu seismovolcanic activity. The characteristic pattern of the crustal deformation corresponding to the Tokai slow-slip event was found in the fourth mode, which was prominent after the beginning of the Miyake-Kozu seismovolcanic activity. From these results, we conclude that the crustal deformation caused by the Tokai slow-slip event did not start before the Miyake-Kozu seismovolcanic activity.
Synchronous activation within the default mode network correlates with perceived social support.

PubMed

Che, Xianwei; Zhang, Qinglin; Zhao, Jizheng; Wei, Dongtao; Li, Bingbing; Guo, Yanan; Qiu, Jiang; Liu, Yijun

2014-10-01

Perceived social support emphasizes subjective feeling of provisions offered by family, friends and significant others. In consideration of the great significance of perceived social support to health outcomes, attempt to reveal the neural substrates of perceived social support will facilitate its application in a series of mental disorders. Perceived social support potentially relies on healthy interpersonal relationships calling for cognitive processes like perspective taking, empathy and theory of mind. Interestingly, functional activations and connectivity within the default mode network (DMN) are extensively involved in these interpersonal skills. As a result, it is proposed that synchronous activities among brain regions within the DMN will correlate with self-report of perceived social support. In the present study, we tried to investigate the associations between coherence among the DMN regions and perceived social support at resting state. A total of 333 (145 men) participants were directed to fulfill the Multidimensional Scale of Perceived Social Support (MSPSS) after a 484-s functional magnetic resonance imaging (fMRI) scanning without any task. As a result, seed-based functional connectivity and power spectrum analyses revealed that heightened synchronicity among the DMN regions was associated with better performance on perceived social support. Moreover, results in the present study were independent of different methods, structural changes, and general cognitive performance. Copyright © 2014 Elsevier Ltd. All rights reserved.
Establishing the resting state default mode network derived from functional magnetic resonance imaging tasks as an endophenotype: A twins study.

PubMed

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

PubMed

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.
DRD2 Genotype-Based Variation of Default Mode Network Activity and of Its Relationship With Striatal DAT Binding

PubMed Central

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 ([123I]-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. PMID:21976709

Resting-State Brain and the FTO Obesity Risk Allele: Default Mode, Sensorimotor, and Salience Network Connectivity Underlying Different Somatosensory Integration and Reward Processing between Genotypes.

PubMed

Olivo, Gaia; Wiemerslage, Lyle; Nilsson, Emil K; Solstrand Dahlberg, Linda; Larsen, Anna L; Olaya Búcaro, Marcela; Gustafsson, Veronica P; Titova, Olga E; Bandstein, Marcus; Larsson, Elna-Marie; Benedict, Christian; Brooks, Samantha J; Schiöth, Helgi B

2016-01-01

Single-nucleotide polymorphisms (SNPs) of the fat mass and obesity associated (FTO) gene are linked to obesity, but how these SNPs influence resting-state neural activation is unknown. Few brain-imaging studies have investigated the influence of obesity-related SNPs on neural activity, and no study has investigated resting-state connectivity patterns. We tested connectivity within three, main resting-state networks: default mode (DMN), sensorimotor (SMN), and salience network (SN) in 30 male participants, grouped based on genotype for the rs9939609 FTO SNP, as well as punishment and reward sensitivity measured by the Behavioral Inhibition (BIS) and Behavioral Activation System (BAS) questionnaires. Because obesity is associated with anomalies in both systems, we calculated a BIS/BAS ratio (BBr) accounting for features of both scores. A prominence of BIS over BAS (higher BBr) resulted in increased connectivity in frontal and paralimbic regions. These alterations were more evident in the obesity-associated AA genotype, where a high BBr was also associated with increased SN connectivity in dopaminergic circuitries, and in a subnetwork involved in somatosensory integration regarding food. Participants with AA genotype and high BBr, compared to corresponding participants in the TT genotype, also showed greater DMN connectivity in regions involved in the processing of food cues, and in the SMN for regions involved in visceral perception and reward-based learning. These findings suggest that neural connectivity patterns influence the sensitivity toward punishment and reward more closely in the AA carriers, predisposing them to developing obesity. Our work explains a complex interaction between genetics, neural patterns, and behavioral measures in determining the risk for obesity and may help develop individually-tailored strategies for obesity prevention.
Resting-State Brain and the FTO Obesity Risk Allele: Default Mode, Sensorimotor, and Salience Network Connectivity Underlying Different Somatosensory Integration and Reward Processing between Genotypes

PubMed Central

Olivo, Gaia; Wiemerslage, Lyle; Nilsson, Emil K.; Solstrand Dahlberg, Linda; Larsen, Anna L.; Olaya Búcaro, Marcela; Gustafsson, Veronica P.; Titova, Olga E.; Bandstein, Marcus; Larsson, Elna-Marie; Benedict, Christian; Brooks, Samantha J.; Schiöth, Helgi B.

2016-01-01

Single-nucleotide polymorphisms (SNPs) of the fat mass and obesity associated (FTO) gene are linked to obesity, but how these SNPs influence resting-state neural activation is unknown. Few brain-imaging studies have investigated the influence of obesity-related SNPs on neural activity, and no study has investigated resting-state connectivity patterns. We tested connectivity within three, main resting-state networks: default mode (DMN), sensorimotor (SMN), and salience network (SN) in 30 male participants, grouped based on genotype for the rs9939609 FTO SNP, as well as punishment and reward sensitivity measured by the Behavioral Inhibition (BIS) and Behavioral Activation System (BAS) questionnaires. Because obesity is associated with anomalies in both systems, we calculated a BIS/BAS ratio (BBr) accounting for features of both scores. A prominence of BIS over BAS (higher BBr) resulted in increased connectivity in frontal and paralimbic regions. These alterations were more evident in the obesity-associated AA genotype, where a high BBr was also associated with increased SN connectivity in dopaminergic circuitries, and in a subnetwork involved in somatosensory integration regarding food. Participants with AA genotype and high BBr, compared to corresponding participants in the TT genotype, also showed greater DMN connectivity in regions involved in the processing of food cues, and in the SMN for regions involved in visceral perception and reward-based learning. These findings suggest that neural connectivity patterns influence the sensitivity toward punishment and reward more closely in the AA carriers, predisposing them to developing obesity. Our work explains a complex interaction between genetics, neural patterns, and behavioral measures in determining the risk for obesity and may help develop individually-tailored strategies for obesity prevention. PMID:26924971
The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository.

PubMed

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

2017-02-01

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

PubMed

Lopes, Renaud; Moeller, Friederike; Besson, Pierre; Ogez, François; Szurhaj, William; Leclerc, Xavier; Siniatchkin, Michael; Chipaux, Mathilde; Derambure, Philippe; Tyvaert, Louise

2014-01-01

Simultaneous recording of electroencephalogram and functional MRI (EEG-fMRI) is a powerful tool for localizing epileptic networks via the detection of hemodynamic changes correlated with interictal epileptic discharges (IEDs). fMRI can be used to study the long-lasting effect of epileptic activity by assessing stationary functional connectivity during the resting-state period [especially, the connectivity of the default mode network (DMN)]. Temporal lobe epilepsy (TLE) and idiopathic generalized epilepsy (IGE) are associated with low responsiveness and disruption of DMN activity. A dynamic functional connectivity approach might enable us to determine the effect of IEDs on DMN connectivity and to better understand the correlation between DMN connectivity changes and altered consciousness. We studied dynamic changes in DMN intrinsic connectivity and their relation to IEDs. Six IGE patients (with generalized spike and slow-waves) and 6 TLE patients (with unilateral left temporal spikes) were included. Functional connectivity before, during, and after IEDs was estimated using a sliding window approach and compared with the baseline period. No dependence on window size was observed. The baseline DMN connectivity was decreased in the left hemisphere (ipsilateral to the epileptic focus) in TLEs and was less strong but remained bilateral in IGEs. We observed an overall increase in DMN intrinsic connectivity prior to the onset of IEDs in both IGEs and TLEs. After IEDs in TLEs, we found that DMN connectivity increased before it returned to baseline values. Most of the DMN regions with increased connectivity before and after IEDs were lateralized to the left hemisphere in TLE (i.e., ipsilateral to the epileptic focus). RESULTS suggest that DMN connectivity may facilitate IED generation and may be affected at the time of the IED. However, these results need to be confirmed in a larger independent cohort.
Angular default mode network connectivity across working memory load.

PubMed

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

2017-01-01

Initially identified during no-task, baseline conditions, it has now been suggested that the default mode network (DMN) engages during a variety of working memory paradigms through its flexible interactions with other large-scale brain networks. Nevertheless, its contribution to whole-brain connectivity dynamics across increasing working memory load has not been explicitly assessed. The aim of our study was to determine which DMN hubs relate to working memory task performance during an fMRI-based n-back paradigm with parametric increases in difficulty. Using a voxel-wise metric, termed the intrinsic connectivity contrast (ICC), we found that the bilateral angular gyri (core DMN hubs) displayed the greatest change in global connectivity across three levels of n-back task load. Subsequent seed-based functional connectivity analysis revealed that the angular DMN regions robustly interact with other large-scale brain networks, suggesting a potential involvement in the global integration of information. Further support for this hypothesis comes from the significant correlations we found between angular gyri connectivity and reaction times to correct responses. The implication from our study is that the DMN is actively involved during the n-back task and thus plays an important role related to working memory, with its core angular regions contributing to the changes in global brain connectivity in response to increasing environmental demands. Hum Brain Mapp 38:41-52, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Desynchronization and Plasticity of Striato-frontal Connectivity in Major Depressive Disorder.

PubMed

Leaver, Amber M; Espinoza, Randall; Joshi, Shantanu H; Vasavada, Megha; Njau, Stephanie; Woods, Roger P; Narr, Katherine L

2016-10-17

Major depressive disorder (MDD) is associated with dysfunctional corticolimbic networks, making functional connectivity studies integral for understanding the mechanisms underlying MDD pathophysiology and treatment. Resting-state functional connectivity (RSFC) studies analyze patterns of temporally coherent intrinsic brain activity in "resting-state networks" (RSNs). The default-mode network (DMN) has been of particular interest to depression research; however, a single RSN is unlikely to capture MDD pathophysiology in its entirety, and the DMN itself can be characterized by multiple RSNs. This, coupled with conflicting previous results, underscores the need for further research. Here, we measured RSFC in MDD by targeting RSNs overlapping with corticolimbic regions and further determined whether altered patterns of RSFC were restored with electroconvulsive therapy (ECT). MDD patients exhibited hyperconnectivity between ventral striatum (VS) and the ventral default-mode network (vDMN), while simultaneously demonstrating hypoconnectivity with the anterior DMN (aDMN). ECT influenced this pattern: VS-vDMN hyperconnectivity was significantly reduced while VS-aDMN hypoconnectivity only modestly improved. RSFC between the salience RSN and dorsomedial prefrontal cortex was also reduced in MDD, but was not affected by ECT. Taken together, our results support a model of ventral/dorsal imbalance in MDD and further suggest that the VS is a key structure contributing to this desynchronization. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
ONU power saving modes in next generation optical access networks: progress, efficiency and challenges.

PubMed

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.
Distributed fault detection over sensor networks with Markovian switching topologies

NASA Astrophysics Data System (ADS)

Ge, Xiaohua; Han, Qing-Long

2014-05-01

This paper deals with the distributed fault detection for discrete-time Markov jump linear systems over sensor networks with Markovian switching topologies. The sensors are scatteredly deployed in the sensor field and the fault detectors are physically distributed via a communication network. The system dynamics changes and sensing topology variations are modeled by a discrete-time Markov chain with incomplete mode transition probabilities. Each of these sensor nodes firstly collects measurement outputs from its all underlying neighboring nodes, processes these data in accordance with the Markovian switching topologies, and then transmits the processed data to the remote fault detector node. Network-induced delays and accumulated data packet dropouts are incorporated in the data transmission between the sensor nodes and the distributed fault detector nodes through the communication network. To generate localized residual signals, mode-independent distributed fault detection filters are proposed. By means of the stochastic Lyapunov functional approach, the residual system performance analysis is carried out such that the overall residual system is stochastically stable and the error between each residual signal and the fault signal is made as small as possible. Furthermore, a sufficient condition on the existence of the mode-independent distributed fault detection filters is derived in the simultaneous presence of incomplete mode transition probabilities, Markovian switching topologies, network-induced delays, and accumulated data packed dropouts. Finally, a stirred-tank reactor system is given to show the effectiveness of the developed theoretical results.
Convergence analysis of sliding mode trajectories in multi-objective neural networks learning.

PubMed

Costa, Marcelo Azevedo; Braga, Antonio Padua; de Menezes, Benjamin Rodrigues

2012-09-01

The Pareto-optimality concept is used in this paper in order to represent a constrained set of solutions that are able to trade-off the two main objective functions involved in neural networks supervised learning: data-set error and network complexity. The neural network is described as a dynamic system having error and complexity as its state variables and learning is presented as a process of controlling a learning trajectory in the resulting state space. In order to control the trajectories, sliding mode dynamics is imposed to the network. It is shown that arbitrary learning trajectories can be achieved by maintaining the sliding mode gains within their convergence intervals. Formal proofs of convergence conditions are therefore presented. The concept of trajectory learning presented in this paper goes further beyond the selection of a final state in the Pareto set, since it can be reached through different trajectories and states in the trajectory can be assessed individually against an additional objective function. Copyright © 2012 Elsevier Ltd. All rights reserved.
Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology

PubMed Central

Hsin, Kun-Yi; Ghosh, Samik; Kitano, Hiroaki

2013-01-01

Increased availability of bioinformatics resources is creating opportunities for the application of network pharmacology to predict drug effects and toxicity resulting from multi-target interactions. Here we present a high-precision computational prediction approach that combines two elaborately built machine learning systems and multiple molecular docking tools to assess binding potentials of a test compound against proteins involved in a complex molecular network. One of the two machine learning systems is a re-scoring function to evaluate binding modes generated by docking tools. The second is a binding mode selection function to identify the most predictive binding mode. Results from a series of benchmark validations and a case study show that this approach surpasses the prediction reliability of other techniques and that it also identifies either primary or off-targets of kinase inhibitors. Integrating this approach with molecular network maps makes it possible to address drug safety issues by comprehensively investigating network-dependent effects of a drug or drug candidate. PMID:24391846
Ecological Networks and Neighborhood Social Organization1

PubMed Central

Browning, Christopher R.; Calder, Catherine A.; Soller, Brian; Jackson, Aubrey L.; Dirlam, Jonathan

2017-01-01

Drawing on the social disorganization tradition and the social ecological perspective of Jane Jacobs, the authors hypothesize that neighborhoods composed of residents who intersect in space more frequently as a result of routine activities will exhibit higher levels of collective efficacy, intergenerational closure, and social network interaction and exchange. They develop this approach employing the concept of ecological networks—two-mode networks that indirectly link residents through spatial overlap in routine activities. Using data from the Los Angeles Family and Neighborhood Survey, they find evidence that econetwork extensity (the average proportion of households in the neighborhood to which a given household is tied through any location) and intensity (the degree to which household dyads are characterized by ties through multiple locations) are positively related to changes in social organization between 2000–2001 and 2006–2008. These findings demonstrate the relevance of econetwork characteristics—heretofore neglected in research on urban neighborhoods—for consequential dimensions of neighborhood social organization. PMID:29379218
Selective excitation of LG 00, LG 01, and LG 02 modes by a solid core PCF based mode selector in MDM-Ro-FSO transmission systems

NASA Astrophysics Data System (ADS)

Chaudhary, Sushank; Amphawan, Angela

2018-07-01

Radio over free space (Ro-FSO) provides an ambitious platform for seamless integration of radio networks to optical networks. Three independent channels, each carrying 2.5 Gbps–5 GHz data, are successfully transmitted over a free space link of 2.5 km by using mode division multiplexing (MDM) of three modes LG 00, LG 01, and LG 02 modes in conjunction with solid core photonic crystal fibers (SC-PCFs). Moreover, SC-PCFs are used as a mode selector in the proposed MDM-Ro-FSO system. The results are reported in terms of bit error rate, mode spectrum, and spatial profiles. The performance of the proposed Ro-FSO system is also evaluated under the influence of atmospheric turbulence in the form of different levels of fog, namely, light fog, thin fog, and heavy fog.
Default Mode Network Connectivity in Children with a History of Preschool Onset Depression

ERIC Educational Resources Information Center

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

2012-01-01

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

PubMed

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.
Differentiating unipolar and bipolar depression by alterations in large-scale brain networks.

PubMed

Goya-Maldonado, Roberto; Brodmann, Katja; Keil, Maria; Trost, Sarah; Dechent, Peter; Gruber, Oliver

2016-02-01

Misdiagnosing bipolar depression can lead to very deleterious consequences of mistreatment. Although depressive symptoms may be similarly expressed in unipolar and bipolar disorder, changes in specific brain networks could be very distinct, being therefore informative markers for the differential diagnosis. We aimed to characterize specific alterations in candidate large-scale networks (frontoparietal, cingulo-opercular, and default mode) in symptomatic unipolar and bipolar patients using resting state fMRI, a cognitively low demanding paradigm ideal to investigate patients. Networks were selected after independent component analysis, compared across 40 patients acutely depressed (20 unipolar, 20 bipolar), and 20 controls well-matched for age, gender, and education levels, and alterations were correlated to clinical parameters. Despite comparable symptoms, patient groups were robustly differentiated by large-scale network alterations. Differences were driven in bipolar patients by increased functional connectivity in the frontoparietal network, a central executive and externally-oriented network. Conversely, unipolar patients presented increased functional connectivity in the default mode network, an introspective and self-referential network, as much as reduced connectivity of the cingulo-opercular network to default mode regions, a network involved in detecting the need to switch between internally and externally oriented demands. These findings were mostly unaffected by current medication, comorbidity, and structural changes. Moreover, network alterations in unipolar patients were significantly correlated to the number of depressive episodes. Unipolar and bipolar groups displaying similar symptomatology could be clearly distinguished by characteristic changes in large-scale networks, encouraging further investigation of network fingerprints for clinical use. Hum Brain Mapp 37:808-818, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
Modeling carbachol-induced hippocampal network synchronization using hidden Markov models

NASA Astrophysics Data System (ADS)

Dragomir, Andrei; Akay, Yasemin M.; Akay, Metin

2010-10-01

In this work we studied the neural state transitions undergone by the hippocampal neural network using a hidden Markov model (HMM) framework. We first employed a measure based on the Lempel-Ziv (LZ) estimator to characterize the changes in the hippocampal oscillation patterns in terms of their complexity. These oscillations correspond to different modes of hippocampal network synchronization induced by the cholinergic agonist carbachol in the CA1 region of mice hippocampus. HMMs are then used to model the dynamics of the LZ-derived complexity signals as first-order Markov chains. Consequently, the signals corresponding to our oscillation recordings can be segmented into a sequence of statistically discriminated hidden states. The segmentation is used for detecting transitions in neural synchronization modes in data recorded from wild-type and triple transgenic mice models (3xTG) of Alzheimer's disease (AD). Our data suggest that transition from low-frequency (delta range) continuous oscillation mode into high-frequency (theta range) oscillation, exhibiting repeated burst-type patterns, occurs always through a mode resembling a mixture of the two patterns, continuous with burst. The relatively random patterns of oscillation during this mode may reflect the fact that the neuronal network undergoes re-organization. Further insight into the time durations of these modes (retrieved via the HMM segmentation of the LZ-derived signals) reveals that the mixed mode lasts significantly longer (p < 10-4) in 3xTG AD mice. These findings, coupled with the documented cholinergic neurotransmission deficits in the 3xTG mice model, may be highly relevant for the case of AD.
The independent influences of age and education on functional brain networks and cognition in healthy older adults.

PubMed

Perry, Alistair; Wen, Wei; Kochan, Nicole A; Thalamuthu, Anbupalam; Sachdev, Perminder S; Breakspear, Michael

2017-10-01

Healthy aging is accompanied by a constellation of changes in cognitive processes and alterations in functional brain networks. The relationships between brain networks and cognition during aging in later life are moderated by demographic and environmental factors, such as prior education, in a poorly understood manner. Using multivariate analyses, we identified three latent patterns (or modes) linking resting-state functional connectivity to demographic and cognitive measures in 101 cognitively normal elders. The first mode (P = 0.00043) captures an opposing association between age and core cognitive processes such as attention and processing speed on functional connectivity patterns. The functional subnetwork expressed by this mode links bilateral sensorimotor and visual regions through key areas such as the parietal operculum. A strong, independent association between years of education and functional connectivity loads onto a second mode (P = 0.012), characterized by the involvement of key hub regions. A third mode (P = 0.041) captures weak, residual brain-behavior relations. Our findings suggest that circuits supporting lower level cognitive processes are most sensitive to the influence of age in healthy older adults. Education, and to a lesser extent, executive functions, load independently onto functional networks-suggesting that the moderating effect of education acts upon networks distinct from those vulnerable with aging. This has important implications in understanding the contribution of education to cognitive reserve during healthy aging. Hum Brain Mapp 38:5094-5114, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Living on the edge of chaos: minimally nonlinear models of genetic regulatory dynamics.

PubMed

Hanel, Rudolf; Pöchacker, Manfred; Thurner, Stefan

2010-12-28

Linearized catalytic reaction equations (modelling, for example, the dynamics of genetic regulatory networks), under the constraint that expression levels, i.e. molecular concentrations of nucleic material, are positive, exhibit non-trivial dynamical properties, which depend on the average connectivity of the reaction network. In these systems, an inflation of the edge of chaos and multi-stability have been demonstrated to exist. The positivity constraint introduces a nonlinearity, which makes chaotic dynamics possible. Despite the simplicity of such minimally nonlinear systems, their basic properties allow us to understand the fundamental dynamical properties of complex biological reaction networks. We analyse the Lyapunov spectrum, determine the probability of finding stationary oscillating solutions, demonstrate the effect of the nonlinearity on the effective in- and out-degree of the active interaction network, and study how the frequency distributions of oscillatory modes of such a system depend on the average connectivity.
Timeline Resource Analysis Program (TRAP): User's manual and program document

NASA Technical Reports Server (NTRS)

Sessler, J. G.

1981-01-01

The Timeline Resource Analysis Program (TRAP), developed for scheduling and timelining problems, is described. Given an activity network, TRAP generates timeline plots, resource histograms, and tabular summaries of the network, schedules, and resource levels. It is written in ANSI FORTRAN for the Honeywell SIGMA 5 computer and operates in the interactive mode using the TEKTRONIX 4014-1 graphics terminal. The input network file may be a standard SIGMA 5 file or one generated using the Interactive Graphics Design System. The timeline plots can be displayed in two orderings: according to the sequence in which the tasks were read on input, and a waterfall sequence in which the tasks are ordered by start time. The input order is especially meaningful when the network consists of several interacting subnetworks. The waterfall sequence is helpful in assessing the project status at any point in time.
Default mode network in young people with familial risk for psychosis--the Oulu Brain and Mind study.

PubMed

Jukuri, Tuomas; Kiviniemi, Vesa; Nikkinen, Juha; Miettunen, Jouko; Mäki, Pirjo; Jääskeläinen, Erika; Mukkala, Sari; Koivukangas, Jenni; Nordström, Tanja; Taanila, Anja; Moilanen, Irma; Heinimaa, Markus; Barnett, Jennifer H; Jones, Peter B; Murray, Graham K; Veijola, Juha

2013-02-01

The default mode network (DMN) is active in the brain at rest and de-activated during cognitive tasks. Abnormal function in the DMN has been reported in people with schizophrenia but it is not known whether this applies also to people with a familial risk for psychosis (FR). We compared the activity of the DMN between FR participants and controls. We conducted a resting state functional MRI (R-fMRI) in 72 young adults without psychosis and with a history of psychosis in one or both parents (FR group) and 72 age matched controls without parental psychosis, and without current psychosis or a current prodromal syndrome. Both groups were drawn from the Northern Finland Birth Cohort 1986 (Oulu Brain and Mind study). Parental psychosis was established using the Finnish hospital discharge register. We pre-processed R-fMRI data using independent component analysis followed by a dual regression approach to assess differences between the groups. The FR vs. Control group differences were assessed using non-parametric permutation tests utilizing threshold-free cluster enhancement and correcting for multiple comparisons (p<0.05). FR participants demonstrated significantly lower activity compared with controls in the posterior cingulate cortex, the central node of the DMN. The size of the region was 41 mm(3). The activity of the DMN differed between FR and control groups. This suggests that familial risk for psychotic disorders may be mediated through genetic effects on connectivity in the posterior cingulate cortex. Copyright © 2012 Elsevier B.V. All rights reserved.

Implementing the sine transform of fermionic modes as a tensor network

NASA Astrophysics Data System (ADS)

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.
Antagonistic neural networks underlying differentiated leadership roles.

PubMed

Boyatzis, Richard E; Rochford, Kylie; Jack, Anthony I

2014-01-01

The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950s. Recent research in neuroscience suggests that the division between task-oriented and socio-emotional-oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks - the task-positive network (TPN) and the default mode network (DMN). Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task-oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions, and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success.
Antagonistic neural networks underlying differentiated leadership roles

PubMed Central

Boyatzis, Richard E.; Rochford, Kylie; Jack, Anthony I.

2014-01-01

The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950s. Recent research in neuroscience suggests that the division between task-oriented and socio-emotional-oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks – the task-positive network (TPN) and the default mode network (DMN). Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task-oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions, and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success. PMID:24624074
Counterfactual thinking: an fMRI study on changing the past for a better future

PubMed Central

Ma, Ning; Ampe, Lisa; Baetens, Kris; Van Overwalle, Frank

2013-01-01

Recent studies suggest that a brain network mainly associated with episodic memory has a more general function in imagining oneself in another time, place or perspective (e.g. episodic future thought, theory of mind, default mode). If this is true, counterfactual thinking (e.g. ‘If I had left the office earlier, I wouldn’t have missed my train.’) should also activate this network. Present functional magnetic resonance imaging (fMRI) study explores the common and distinct neural activity of counterfactual and episodic thinking by directly comparing the imagining of upward counterfactuals (creating better outcomes for negative past events) with the re-experiencing of negative past events and the imagining of positive future events. Results confirm that episodic and counterfactual thinking share a common brain network, involving a core memory network (hippocampal area, temporal lobes, midline, and lateral parietal lobes) and prefrontal areas that might be related to mentalizing (medial prefrontal cortex) and performance monitoring (right prefrontal cortex). In contrast to episodic past and future thinking, counterfactual thinking recruits some of these areas more strongly and extensively, and additionally activates the bilateral inferior parietal lobe and posterior medial frontal cortex. We discuss these findings in view of recent fMRI evidence on the working of episodic memory and theory of mind. PMID:22403155
Comparison of VDL Modes in the Aeronautical Telecommunications Network

NASA Technical Reports Server (NTRS)

Bretmersky, Steven; Konangi, Vijay K.; Kerczewski, Robert J.

2002-01-01

VHF Digital Link (VDL) has been identified as a method of communication between aircraft and ground stations in the Aeronautical Telecommunications Network (ATN). Three different modes of VDL have been suggested for implementation. Simulations were conducted to compare the data transfer capabilities of VDL Modes 2, 3, and 4. These simulations focus on up to 50 aircraft communicating with a single VDL ground station. The data traffic is generated by the standard File Transfer Protocol (FTP) and Hyper Text Transfer Protocol (HTTP) applications in the aircraft. Comparisons of the modes are based on the number of files and pages transferred and the response time.
Synchronization of discrete-time neural networks with delays and Markov jump topologies based on tracker information.

PubMed

Yang, Xinsong; Feng, Zhiguo; Feng, Jianwen; Cao, Jinde

2017-01-01

In this paper, synchronization in an array of discrete-time neural networks (DTNNs) with time-varying delays coupled by Markov jump topologies is considered. It is assumed that the switching information can be collected by a tracker with a certain probability and transmitted from the tracker to controller precisely. Then the controller selects suitable control gains based on the received switching information to synchronize the network. This new control scheme makes full use of received information and overcomes the shortcomings of mode-dependent and mode-independent control schemes. Moreover, the proposed control method includes both the mode-dependent and mode-independent control techniques as special cases. By using linear matrix inequality (LMI) method and designing new Lyapunov functionals, delay-dependent conditions are derived to guarantee that the DTNNs with Markov jump topologies to be asymptotically synchronized. Compared with existing results on Markov systems which are obtained by separately using mode-dependent and mode-independent methods, our result has great flexibility in practical applications. Numerical simulations are finally given to demonstrate the effectiveness of the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.
Progress Toward Standards for the Seamless Interoperability of Broadband Satellite Communication Networks

NASA Technical Reports Server (NTRS)

Ivancic, William D.; Glover, Daniel R.; vonDeak, Thomas C.; Bhasin, Kul B.

1998-01-01

The realization of the full potential of the National Information Infrastructure (NH) and Global Information Infrastructure (GII) requires seamless interoperability of emerging satellite networks with terrestrial networks. This requires a cooperative effort between industry, academia and government agencies to develop and advocate new, satellite-friendly communication protocols and modifications to existing communication protocol standards. These groups have recently come together to actively participating in a number of standards making bodies including: the Internet Engineering Task Force (IETF), the Asynchronous Transfer Mode (ATM) Forum, the International Telecommunication Union (ITU) and the Telecommunication Industry Association MA) to ensure that issues regarding efficient use of these protocols over satellite links are not overlooked. This paper will summarize the progress made toward standards development to achieve seamless integration and accelerate the deployment of multimedia applications.
A Network Method of Measuring Affiliation-based Peer Influence: Assessing the Influences of Teammates’ Smoking on Adolescent Smoking

PubMed Central

Fujimoto, Kayo; Unger, Jennifer B.; Valente, Thomas W.

2011-01-01

Using a network analytic framework, this study introduces a new method to measure peer influence based on adolescents’ affiliations or two-mode social network data. Exposure based on affiliations is referred to as the “affiliation exposure model.” This study demonstrates the methodology using data on young adolescent smoking being influenced by joint participation in school-based organized sports activities with smokers. The analytic sample consisted of 1260 American adolescents from age 10 to 13 in middle schools, and the results of the longitudinal regression analyses showed that adolescents were more likely to smoke as they were increasingly exposed to teammates who smoke. This study illustrates the importance of peer influence via affiliation through team sports. PMID:22313152
Load matters: neural correlates of verbal working memory in children with autism spectrum disorder.

PubMed

Vogan, Vanessa M; Francis, Kaitlyn E; Morgan, Benjamin R; Smith, Mary Lou; Taylor, Margot J

2018-06-01

Autism spectrum disorder (ASD) is a pervasive neurodevelopmental disorder characterised by diminished social reciprocity and communication skills and the presence of stereotyped and restricted behaviours. Executive functioning deficits, such as working memory, are associated with core ASD symptoms. Working memory allows for temporary storage and manipulation of information and relies heavily on frontal-parietal networks of the brain. There are few reports on the neural correlates of working memory in youth with ASD. The current study identified the neural systems underlying verbal working memory capacity in youth with and without ASD using functional magnetic resonance imaging (fMRI). Fifty-seven youth, 27 with ASD and 30 sex- and age-matched typically developing (TD) controls (9-16 years), completed a one-back letter matching task (LMT) with four levels of difficulty (i.e. cognitive load) while fMRI data were recorded. Linear trend analyses were conducted to examine brain regions that were recruited as a function of increasing cognitive load. We found similar behavioural performance on the LMT in terms of reaction times, but in the two higher load conditions, the ASD youth had lower accuracy than the TD group. Neural patterns of activations differed significantly between TD and ASD groups. In TD youth, areas classically used for working memory, including the lateral and medial frontal, as well as superior parietal brain regions, increased in activation with increasing task difficulty, while areas related to the default mode network (DMN) showed decreasing activation (i.e., deactivation). The youth with ASD did not appear to use this opposing cognitive processing system; they showed little recruitment of frontal and parietal regions across the load but did show similar modulation of the DMN. In a working memory task, where the load was manipulated without changing executive demands, TD youth showed increasing recruitment with increasing load of the classic fronto-parietal brain areas and decreasing involvement in default mode regions. In contrast, although they modulated the default mode network, youth with ASD did not show the modulation of increasing brain activation with increasing load, suggesting that they may be unable to manage increasing verbal information. Impaired verbal working memory in ASD would interfere with the youths' success academically and socially. Thus, determining the nature of atypical neural processing could help establish or monitor working memory interventions for ASD.
Compact Feeding Network for Array Radiations of Spoof Surface Plasmon Polaritons

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

PubMed

Kucyi, Aaron; Esterman, Michael; Riley, Clay S; Valera, Eve M

2016-11-29

The brain's default mode network (DMN) is highly active during wakeful rest when people are not overtly engaged with a sensory stimulus or externally oriented task. In multiple contexts, increased spontaneous DMN activity has been associated with self-reported episodes of mind-wandering, or thoughts that are unrelated to the present sensory environment. Mind-wandering characterizes much of waking life and is often associated with error-prone, variable behavior. However, increased spontaneous DMN activity has also been reliably associated with stable, rather than variable, behavior. We aimed to address this seeming contradiction and to test the hypothesis that single measures of attentional states, either based on self-report or on behavior, are alone insufficient to account for DMN activity fluctuations. Thus, we simultaneously measured varying levels of self-reported mind-wandering, behavioral variability, and brain activity with fMRI during a unique continuous performance task optimized for detecting attentional fluctuations. We found that even though mind-wandering co-occurred with increased behavioral variability, highest DMN signal levels were best explained by intense mind-wandering combined with stable behavior simultaneously, compared with considering either single factor alone. These brain-behavior-experience relationships were highly consistent within known DMN subsystems and across DMN subregions. In contrast, such relationships were absent or in the opposite direction for other attention-relevant networks (salience, dorsal attention, and frontoparietal control networks). Our results suggest that the cognitive processes that spontaneous DMN activity specifically reflects are only partially related to mind-wandering and include also attentional state fluctuations that are not captured by self-report.
Spontaneous default network activity reflects behavioral variability independent of mind-wandering

PubMed Central

Kucyi, Aaron; Esterman, Michael; Riley, Clay S.; Valera, Eve M.

2016-01-01

The brain’s default mode network (DMN) is highly active during wakeful rest when people are not overtly engaged with a sensory stimulus or externally oriented task. In multiple contexts, increased spontaneous DMN activity has been associated with self-reported episodes of mind-wandering, or thoughts that are unrelated to the present sensory environment. Mind-wandering characterizes much of waking life and is often associated with error-prone, variable behavior. However, increased spontaneous DMN activity has also been reliably associated with stable, rather than variable, behavior. We aimed to address this seeming contradiction and to test the hypothesis that single measures of attentional states, either based on self-report or on behavior, are alone insufficient to account for DMN activity fluctuations. Thus, we simultaneously measured varying levels of self-reported mind-wandering, behavioral variability, and brain activity with fMRI during a unique continuous performance task optimized for detecting attentional fluctuations. We found that even though mind-wandering co-occurred with increased behavioral variability, highest DMN signal levels were best explained by intense mind-wandering combined with stable behavior simultaneously, compared with considering either single factor alone. These brain–behavior–experience relationships were highly consistent within known DMN subsystems and across DMN subregions. In contrast, such relationships were absent or in the opposite direction for other attention-relevant networks (salience, dorsal attention, and frontoparietal control networks). Our results suggest that the cognitive processes that spontaneous DMN activity specifically reflects are only partially related to mind-wandering and include also attentional state fluctuations that are not captured by self-report. PMID:27856733
Track and mode controller (TMC): a software executive for a high-altitude pointing and tracking experiment

NASA Astrophysics Data System (ADS)

Michnovicz, Michael R.

1997-06-01

A real-time executive has been implemented to control a high altitude pointing and tracking experiment. The track and mode controller (TMC) implements a table driven design, in which the track mode logic for a tracking mission is defined within a state transition diagram (STD). THe STD is implemented as a state transition table in the TMC software. Status Events trigger the state transitions in the STD. Each state, as it is entered, causes a number of processes to be activated within the system. As these processes propagate through the system, the status of key processes are monitored by the TMC, allowing further transitions within the STD. This architecture is implemented in real-time, using the vxWorks operating system. VxWorks message queues allow communication of status events from the Event Monitor task to the STD task. Process commands are propagated to the rest of the system processors by means of the SCRAMNet shared memory network. The system mode logic contained in the STD will autonomously sequence in acquisition, tracking and pointing system through an entire engagement sequence, starting with target detection and ending with aimpoint maintenance. Simulation results and lab test results will be presented to verify the mode controller. In addition to implementing the system mode logic with the STD, the TMC can process prerecorded time sequences of commands required during startup operations. It can also process single commands from the system operator. In this paper, the author presents (1) an overview, in which he describes the TMC architecture, the relationship of an end-to-end simulation to the flight software and the laboratory testing environment, (2) implementation details, including information on the vxWorks message queues and the SCRAMNet shared memory network, (3) simulation results and lab test results which verify the mode controller, and (4) plans for the future, specifically as to how this executive will expedite transition to a fully functional system.
On nodes and modes in resting state fMRI

PubMed Central

Friston, Karl J.; Kahan, Joshua; Razi, Adeel; Stephan, Klaas Enno; Sporns, Olaf

2014-01-01

This paper examines intrinsic brain networks in light of recent developments in the characterisation of resting state fMRI timeseries — and simulations of neuronal fluctuations based upon the connectome. Its particular focus is on patterns or modes of distributed activity that underlie functional connectivity. We first demonstrate that the eigenmodes of functional connectivity – or covariance among regions or nodes – are the same as the eigenmodes of the underlying effective connectivity, provided we limit ourselves to symmetrical connections. This symmetry constraint is motivated by appealing to proximity graphs based upon multidimensional scaling. Crucially, the principal modes of functional connectivity correspond to the dynamically unstable modes of effective connectivity that decay slowly and show long term memory. Technically, these modes have small negative Lyapunov exponents that approach zero from below. Interestingly, the superposition of modes – whose exponents are sampled from a power law distribution – produces classical 1/f (scale free) spectra. We conjecture that the emergence of dynamical instability – that underlies intrinsic brain networks – is inevitable in any system that is separated from external states by a Markov blanket. This conjecture appeals to a free energy formulation of nonequilibrium steady-state dynamics. The common theme that emerges from these theoretical considerations is that endogenous fluctuations are dominated by a small number of dynamically unstable modes. We use this as the basis of a dynamic causal model (DCM) of resting state fluctuations — as measured in terms of their complex cross spectra. In this model, effective connectivity is parameterised in terms of eigenmodes and their Lyapunov exponents — that can also be interpreted as locations in a multidimensional scaling space. Model inversion provides not only estimates of edges or connectivity but also the topography and dimensionality of the underlying scaling space. Here, we focus on conceptual issues with simulated fMRI data and provide an illustrative application using an empirical multi-region timeseries. PMID:24862075
Default mode network, motor network, dorsal and ventral basal ganglia networks in the rat brain: comparison to human networks using resting state-fMRI.

PubMed

Sierakowiak, Adam; Monnot, Cyril; Aski, Sahar Nikkhou; Uppman, Martin; Li, Tie-Qiang; Damberg, Peter; Brené, Stefan

2015-01-01

Rodent models are developed to enhance understanding of the underlying biology of different brain disorders. However, before interpreting findings from animal models in a translational aspect to understand human disease, a fundamental step is to first have knowledge of similarities and differences of the biological systems studied. In this study, we analyzed and verified four known networks termed: default mode network, motor network, dorsal basal ganglia network, and ventral basal ganglia network using resting state functional MRI (rsfMRI) in humans and rats. Our work supports the notion that humans and rats have common robust resting state brain networks and that rsfMRI can be used as a translational tool when validating animal models of brain disorders. In the future, rsfMRI may be used, in addition to short-term interventions, to characterize longitudinal effects on functional brain networks after long-term intervention in humans and rats.
Default Mode Network, Motor Network, Dorsal and Ventral Basal Ganglia Networks in the Rat Brain: Comparison to Human Networks Using Resting State-fMRI

PubMed Central

Sierakowiak, Adam; Monnot, Cyril; Aski, Sahar Nikkhou; Uppman, Martin; Li, Tie-Qiang; Damberg, Peter; Brené, Stefan

2015-01-01

Rodent models are developed to enhance understanding of the underlying biology of different brain disorders. However, before interpreting findings from animal models in a translational aspect to understand human disease, a fundamental step is to first have knowledge of similarities and differences of the biological systems studied. In this study, we analyzed and verified four known networks termed: default mode network, motor network, dorsal basal ganglia network, and ventral basal ganglia network using resting state functional MRI (rsfMRI) in humans and rats. Our work supports the notion that humans and rats have common robust resting state brain networks and that rsfMRI can be used as a translational tool when validating animal models of brain disorders. In the future, rsfMRI may be used, in addition to short-term interventions, to characterize longitudinal effects on functional brain networks after long-term intervention in humans and rats. PMID:25789862
Multifaceted brain networks reconfiguration in disorders of consciousness uncovered by co-activation patterns.

PubMed

Di Perri, Carol; Amico, Enrico; Heine, Lizette; Annen, Jitka; Martial, Charlotte; Larroque, Stephen Karl; Soddu, Andrea; Marinazzo, Daniele; Laureys, Steven

2018-01-01

Given that recent research has shown that functional connectivity is not a static phenomenon, we aim to investigate the dynamic properties of the default mode network's (DMN) connectivity in patients with disorders of consciousness. Resting-state fMRI volumes of a convenience sample of 17 patients in unresponsive wakefulness syndrome (UWS) and controls were reduced to a spatiotemporal point process by selecting critical time points in the posterior cingulate cortex (PCC). Spatial clustering was performed on the extracted PCC time frames to obtain 8 different co-activation patterns (CAPs). We investigated spatial connectivity patterns positively and negatively correlated with PCC using both CAPs and standard stationary method. We calculated CAPs occurrences and the total number of frames. Compared to controls, patients showed (i) decreased within-network positive correlations and between-network negative correlations, (ii) emergence of "pathological" within-network negative correlations and between-network positive correlations (better defined with CAPs), and (iii) "pathological" increases in within-network positive correlations and between-network negative correlations (only detectable using CAPs). Patients showed decreased occurrence of DMN-like CAPs (1-2) compared to controls. No between-group differences were observed in the total number of frames CONCLUSION: CAPs reveal at a more fine-grained level the multifaceted spatial connectivity reconfiguration following the DMN disruption in UWS patients, which is more complex than previously thought and suggests alternative anatomical substrates for consciousness. BOLD fluctuations do not seem to differ between patients and controls, suggesting that BOLD response represents an intrinsic feature of the signal, and therefore that spatial configuration is more important for consciousness than BOLD activation itself. Hum Brain Mapp 39:89-103, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Alternative parallel ring protocols

NASA Technical Reports Server (NTRS)

Mukkamala, R.; Foudriat, E. C.; Maly, Kurt J.; Kale, V.

1990-01-01

Communication protocols are know to influence the utilization and performance of communication network. The effect of two token ring protocols on a gigabit network with multiple ring structure is investigated. In the first protocol, a mode sends at most one message on receiving a token. In the second protocol, a mode sends all the waiting messages when a token is received. The behavior of these protocols is shown to be highly dependent on the number of rings as well as the load in the network.
From Anomalies to Essential Scientific Revolution? Intrinsic Brain Activity in the Light of Kuhn's Philosophy of Science.

PubMed

Havlík, Marek

2017-01-01

The first step toward a modern understanding of fMRI resting brain activity was made by Bharat Biswal in 1995. This surprising, and at first rejected, discovery is now associated with many resting state networks, notably the famous default mode network (DMN). Resting state activity and DMN significantly reassessed our traditional beliefs and conventions about the functioning of the brain. For the majority of the twentieth century, neuroscientists assumed that the brain is mainly the "reactive engine" to the environment operating mostly through stimulation. This "reactive convention" was very influential and convenient for the goals of twentieth century neuroscience-non-invasive functional localization based on stimulation. Largely unchallenged, "reactive convention" determined the direction of scientific research for a long time and became the "reactive paradigm" of the twentieth century. Resting state activity brought knowledge that was quite different of the "reactive paradigm." Current research of the DMN, probably the best known resting state network, leads to entirely new observations and conclusions, which were not achievable from the perspective of the "reactive paradigm." This shift from reactive activity to resting state activity of the brain is accompanied by an important question: "Can resting state activity be considered a scientific revolution and the new paradigm of neuroscience, or is it only significant for one branch of neuroscience, such as fMRI?"
Phonological experience modulates voice discrimination: Evidence from functional brain networks analysis.

PubMed

Hu, Xueping; Wang, Xiangpeng; Gu, Yan; Luo, Pei; Yin, Shouhang; Wang, Lijun; Fu, Chao; Qiao, Lei; Du, Yi; Chen, Antao

2017-10-01

Numerous behavioral studies have found a modulation effect of phonological experience on voice discrimination. However, the neural substrates underpinning this phenomenon are poorly understood. Here we manipulated language familiarity to test the hypothesis that phonological experience affects voice discrimination via mediating the engagement of multiple perceptual and cognitive resources. The results showed that during voice discrimination, the activation of several prefrontal regions was modulated by language familiarity. More importantly, the same effect was observed concerning the functional connectivity from the fronto-parietal network to the voice-identity network (VIN), and from the default mode network to the VIN. Our findings indicate that phonological experience could bias the recruitment of cognitive control and information retrieval/comparison processes during voice discrimination. Therefore, the study unravels the neural substrates subserving the modulation effect of phonological experience on voice discrimination, and provides new insights into studying voice discrimination from the perspective of network interactions. Copyright © 2017. Published by Elsevier Inc.

Dynamic boundary layer based neural network quasi-sliding mode control for soft touching down on asteroid

NASA Astrophysics Data System (ADS)

Liu, Xiaosong; Shan, Zebiao; Li, Yuanchun

2017-04-01

Pinpoint landing is a critical step in some asteroid exploring missions. This paper is concerned with the descent trajectory control for soft touching down on a small irregularly-shaped asteroid. A dynamic boundary layer based neural network quasi-sliding mode control law is proposed to track a desired descending path. The asteroid's gravitational acceleration acting on the spacecraft is described by the polyhedron method. Considering the presence of input constraint and unmodeled acceleration, the dynamic equation of relative motion is presented first. The desired descending path is planned using cubic polynomial method, and a collision detection algorithm is designed. To perform trajectory tracking, a neural network sliding mode control law is given first, where the sliding mode control is used to ensure the convergence of system states. Two radial basis function neural networks (RBFNNs) are respectively used as an approximator for the unmodeled term and a compensator for the difference between the actual control input with magnitude constraint and nominal control. To improve the chattering induced by the traditional sliding mode control and guarantee the reachability of the system, a specific saturation function with dynamic boundary layer is proposed to replace the sign function in the preceding control law. Through the Lyapunov approach, the reachability condition of the control system is given. The improved control law can guarantee the system state move within a gradually shrinking quasi-sliding mode band. Numerical simulation results demonstrate the effectiveness of the proposed control strategy.
Hallucination- and speech-specific hypercoupling in frontotemporal auditory and language networks in schizophrenia using combined task-based fMRI data: An fBIRN study.

PubMed

Lavigne, Katie M; Woodward, Todd S

2018-04-01

Hypercoupling of activity in speech-perception-specific brain networks has been proposed to play a role in the generation of auditory-verbal hallucinations (AVHs) in schizophrenia; however, it is unclear whether this hypercoupling extends to nonverbal auditory perception. We investigated this by comparing schizophrenia patients with and without AVHs, and healthy controls, on task-based functional magnetic resonance imaging (fMRI) data combining verbal speech perception (SP), inner verbal thought generation (VTG), and nonverbal auditory oddball detection (AO). Data from two previously published fMRI studies were simultaneously analyzed using group constrained principal component analysis for fMRI (group fMRI-CPCA), which allowed for comparison of task-related functional brain networks across groups and tasks while holding the brain networks under study constant, leading to determination of the degree to which networks are common to verbal and nonverbal perception conditions, and which show coordinated hyperactivity in hallucinations. Three functional brain networks emerged: (a) auditory-motor, (b) language processing, and (c) default-mode (DMN) networks. Combining the AO and sentence tasks allowed the auditory-motor and language networks to separately emerge, whereas they were aggregated when individual tasks were analyzed. AVH patients showed greater coordinated activity (deactivity for DMN regions) than non-AVH patients during SP in all networks, but this did not extend to VTG or AO. This suggests that the hypercoupling in AVH patients in speech-perception-related brain networks is specific to perceived speech, and does not extend to perceived nonspeech or inner verbal thought generation. © 2017 Wiley Periodicals, Inc.
Resting-state functional connectivity of the default mode network associated with happiness

PubMed Central

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

2016-01-01

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. PMID:26500289
Brain activation associated with eccentric movement: A narrative review of the literature.

PubMed

Perrey, Stéphane

2018-02-01

The movement occurring when a muscle exerts tension while lengthening is known as eccentric muscle action. Literature contains limited evidence on how our brain controls eccentric movement. However, how the cortical regions in the motor network are activated during eccentric muscle actions may be critical for understanding the underlying control mechanism of eccentric movements encountered in daily tasks. This is a novel topic that has only recently begun to be investigated through advancements in neuroimaging methods (electroencephalography, EEG; functional magnetic resonance imaging, fMRI). This review summarizes a selection of seven studies indicating mainly: longer time and higher cortical signal amplitude (EEG) for eccentric movement preparation and execution, greater magnitude of cortical signals with wider activated brain area (EEG, fMRI), and weaker brain functional connectivity (fMRI) between primary motor cortex (M1) and other cortical areas involved in the motor network during eccentric muscle actions. Only some differences among studies due to the forms of movement with overload were observed in the contralateral (to the active hand) M1 activity during eccentric movement. Altogether, the findings indicate an important challenge to the brain for controlling the eccentric movement. However, our understanding remains limited regarding the acute effects of eccentric exercise on cortical regions and their cooperation as functional networks that support motor functions. Further analysis and standardized protocols will provide deeper insights into how different cortical regions of the underlying motor network interplay with each other in increasingly demanding muscle exertions in eccentric mode.
The role of the dorsal anterior insula in sexual risk: Evidence from an erotic Go/NoGo task and real-world risk-taking.

PubMed

Xue, Feng; Droutman, Vita; Barkley-Levenson, Emily E; Smith, Benjamin J; Xue, Gui; Miller, Lynn C; Bechara, Antoine; Lu, Zhong-Lin; Read, Stephen J

2018-04-01

The insula plays an important role in response inhibition. Most relevant here, it has been proposed that the dorsal anterior insular cortex (dAIC) plays a central role in a salience network that is responsible for switching between the default mode network and the executive control network. However, the insula's role in sexually motivated response inhibition has not yet been studied. In this study, eighty-five 18- to 30-year-old sexually active men who have sex with men (MSM) performed an erotic Go/NoGo task while in an MRI scanner. Participants' real-world sexual risk-taking (frequency of condomless anal intercourse over the past 90 days) was then correlated with their neural activity during the task. We found greater activity in bilateral anterior insular cortex (both dorsal and ventral) on contrasts with stronger motivational information (attractive naked male pictures versus pictures of clothed, middle-aged females) and on contrasts requiring greater response inhibition (NoGo versus Go). We also found that activity in the right dAIC was negatively correlated with participants' real-world sexual risk-taking. Our results confirmed the involvement of the insular cortex in motivated response inhibition. Especially, the decreased right dAIC activity may reduce the likelihood that the executive control network will come online when individuals are faced with situations requiring inhibitory control and thus lead them to make more risky choices. © 2018 Wiley Periodicals, Inc.
Gradual emergence of spontaneous correlated brain activity during fading of general anesthesia in rats: Evidences from fMRI and local field potentials

PubMed Central

Bettinardi, Ruggero G.; Tort-Colet, Núria; Ruiz-Mejias, Marcel; Sanchez-Vives, Maria V.; Deco, Gustavo

2015-01-01

Intrinsic brain activity is characterized by the presence of highly structured networks of correlated fluctuations between different regions of the brain. Such networks encompass different functions, whose properties are known to be modulated by the ongoing global brain state and are altered in several neurobiological disorders. In the present study, we induced a deep state of anesthesia in rats by means of a ketamine/medetomidine peritoneal injection, and analyzed the time course of the correlation between the brain activity in different areas while anesthesia spontaneously decreased over time. We compared results separately obtained from fMRI and local field potentials (LFPs) under the same anesthesia protocol, finding that while most profound phases of anesthesia can be described by overall sparse connectivity, stereotypical activity and poor functional integration, during lighter states different frequency-specific functional networks emerge, endowing the gradual restoration of structured large-scale activity seen during rest. Noteworthy, our in vivo results show that those areas belonging to the same functional network (the default-mode) exhibited sustained correlated oscillations around 10 Hz throughout the protocol, suggesting the presence of a specific functional backbone that is preserved even during deeper phases of anesthesia. Finally, the overall pattern of results obtained from both imaging and in vivo-recordings suggests that the progressive emergence from deep anesthesia is reflected by a corresponding gradual increase of organized correlated oscillations across the cortex. PMID:25804643
Cognitive Vulnerability to Major Depression: View from the Intrinsic Network and Cross-network Interactions

PubMed Central

Wang, Xiang; Öngür, Dost; Auerbach, Randy P.; Yao, Shuqiao

2016-01-01

Abstract Although it is generally accepted that cognitive factors contribute to the pathogenesis of major depressive disorder (MDD), there are missing links between behavioral and biological models of depression. Nevertheless, research employing neuroimaging technologies has elucidated some of the neurobiological mechanisms related to cognitive-vulnerability factors, especially from a whole-brain, dynamic perspective. In this review, we integrate well-established cognitive-vulnerability factors for MDD and corresponding neural mechanisms in intrinsic networks using a dual-process framework. We propose that the dynamic alteration and imbalance among the intrinsic networks, both in the resting-state and the rest-task transition stages, contribute to the development of cognitive vulnerability and MDD. Specifically, we propose that abnormally increased resting-state default mode network (DMN) activity and connectivity (mainly in anterior DMN regions) contribute to the development of cognitive vulnerability. Furthermore, when subjects confront negative stimuli in the period of rest-to-task transition, the following three kinds of aberrant network interactions have been identified as facilitators of vulnerability and dysphoric mood, each through a different cognitive mechanism: DMN dominance over the central executive network (CEN), an impaired salience network–mediated switching between the DMN and CEN, and ineffective CEN modulation of the DMN. This focus on interrelated networks and brain-activity changes between rest and task states provides a neural-system perspective for future research on cognitive vulnerability and resilience, and may potentially guide the development of new intervention strategies for MDD. PMID:27148911
Interaction of acupuncture treatment and manipulation laterality modulated by the default mode network

PubMed Central

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

2016-01-01

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 lobule, inferior parietal lobule, precuneus, and left posterior cingulate cortex. It is also proved that disruptions of the default mode network may account for the cognitive and behavioral impairments in chronic pain patients. Our findings further suggested that default mode network participates in the modulation of spatial-oriented attention on placebo analgesia as a mechanism underlying the degree to which treatment side corresponding to the pain. PMID:28326925
Interaction of acupuncture treatment and manipulation laterality modulated by the default mode network.

PubMed

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 lobule, inferior parietal lobule, precuneus, and left posterior cingulate cortex. It is also proved that disruptions of the default mode network may account for the cognitive and behavioral impairments in chronic pain patients. Our findings further suggested that default mode network participates in the modulation of spatial-oriented attention on placebo analgesia as a mechanism underlying the degree to which treatment side corresponding to the pain.
Social network based dynamic transit service through the OMITS system.

DOT National Transportation Integrated Search

2014-02-01

The Open Mode Integrated Transportation System (OMITS) forms a sustainable information infrastructure for communication within and between the mobile/Internet network, the roadway : network, and the users social network. It manipulates the speed g...
Remote Spectroscopy in the Visible Using Fibers on the Optical Internet Network

ERIC Educational Resources Information Center

Ribeiro, Rafael A. S.; de Oliveira, Anderson R.; Zilio, Sergio C.

2010-01-01

The work presented here demonstrates the feasibility of using the single-mode fibers of an optical Internet network to deliver visible light between separate laboratories as a way to perform remote spectroscopy in the visible for teaching purposes. The coupling of a broadband light source into the single-mode fiber (SMF) and the characterization…
A Bayesian network model for predicting aquatic toxicity mode of action using two dimensional theoretical molecular descriptors

EPA Science Inventory

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 pu...
Demonstration of hybrid orbital angular momentum multiplexing and time-division multiplexing passive optical network.

PubMed

Wang, Andong; Zhu, Long; Liu, Jun; Du, Cheng; Mo, Qi; Wang, Jian

2015-11-16

Mode-division multiplexing passive optical network (MDM-PON) is a promising scheme for next-generation access networks to further increase fiber transmission capacity. In this paper, we demonstrate the proof-of-concept experiment of hybrid mode-division multiplexing (MDM) and time-division multiplexing (TDM) PON architecture by exploiting orbital angular momentum (OAM) modes. Bidirectional transmissions with 2.5-Gbaud 4-level pulse amplitude modulation (PAM-4) downstream and 2-Gbaud on-off keying (OOK) upstream are demonstrated in the experiment. The observed optical signal-to-noise ratio (OSNR) penalties for downstream and upstream transmissions at a bit-error rate (BER) of 2 × 10(-3) are less than 2.0 dB and 3.0 dB, respectively.
Decentralised fixed modes of networked MIMO systems

NASA Astrophysics Data System (ADS)

Hao, Yuqing; Duan, Zhisheng; Chen, Guanrong

2018-04-01

In this paper, decentralised fixed modes (DFMs) of a networked system are studied. The network topology is directed and weighted and the nodes are higher-dimensional linear time-invariant (LTI) dynamical systems. The effects of the network topology, the node-system dynamics, the external control inputs, and the inner interactions on the existence of DFMs for the whole networked system are investigated. A necessary and sufficient condition for networked multi-input/multi-output (MIMO) systems in a general topology to possess no DFMs is derived. For networked single-input/single-output (SISO) LTI systems in general as well as some typical topologies, some specific conditions for having no DFMs are established. It is shown that the existence of DFMs is an integrated result of the aforementioned relevant factors which cannot be decoupled into individual DFMs of the node-systems and the properties solely determined by the network topology.
Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata

PubMed Central

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-01-01

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research. PMID:28353664
Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.

PubMed

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-03-29

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.
IEEE 802.16J-Relay Fortified Aeromacs Networks; Benefits and Challenges

NASA Technical Reports Server (NTRS)

Kamali, Behnam; Apaza, Rafael D.

2014-01-01

Aeronautical Mobile Airport Communications System (AeroMACS) is an IEEE 802.16 standard-based (WiMAX) broadband aviation transmission technology, developed to provide safety critical communications coverage for airport surface in support of fixed and mobile ground to ground applications and services. We have previously demonstrated that IEEE 802.16j-amendment-based WiMAX is most feasible for AeroMACS applications. The principal argument in favor of application of IEEE 802.16j technology is the flexible and cost effective extension of radio coverage that is afforded by relay fortified WiMAX networks, with virtually no increase in the power requirements. In this article, following introductory remarks on airport surface communications, WiMAX and AeroMACS; the IEEE 802.16j-based WiMAX technology and multihop relay systems are briefly described. The two modes of relay operation supported by IEEE 802.16j amendment; i.e., transparent (TRS) and non-transparent (NTRS) modes, are discussed in some detail. Advantages and disadvantages of using TRS and NTRS in AeroMACS networks are summarized in a table. Practical issues vis--vis the inclusion of relays in AeroMACS networks are addressed. It is argued that the selection of relay type may affect a number of network parameters. A discussion on specific benefits and challenges of inclusion of relays in AeroMACS networks is provided. The article concludes that in case it is desired or necessary to exclusively employ one type of relay mode for all applications throughout an AeroMACS network, the proper selection would be the non-transparent mode.
Accessible cultural mind-set modulates default mode activity: evidence for the culturally situated brain.

PubMed

Wang, Chenbo; Oyserman, Daphna; Liu, Qiang; Li, Hong; Han, Shihui

2013-01-01

Self-construal priming modulates human behavior and associated neural activity. However, the neural activity associated with the self-construal priming procedure itself remains unknown. It is also unclear whether and how self-construal priming affects neural activity prior to engaging in a particular task. To address this gap, we scanned Chinese adults, using functional magnetic resonance imaging, during self-construal priming and a following resting state. We found that, relative to a calculation task, both interdependent and independent self-construal priming activated the ventral medial prefrontal cortex (MPFC) and the posterior cingulate cortex (PCC). The contrast of interdependent vs. independent self-construal priming also revealed increased activity in the dorsal MPFC and left middle frontal cortex. The regional homogeneity analysis of the resting-state activity revealed increased local synchronization of spontaneous activity in the dorsal MPFC but decreased local synchronization of spontaneous activity in the PCC when contrasting interdependent vs. independent self-construal priming. The functional connectivity analysis of the resting-state activity, however, did not show significant difference in synchronization of activities in remote brain regions between different priming conditions. Our findings suggest that accessible collectivistic/individualistic mind-set induced by self-construal priming is associated with modulations of both task-related and resting-state activity in the default mode network.
Modulation of dynamic modes by interplay between positive and negative feedback loops in gene regulatory networks

NASA Astrophysics Data System (ADS)

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

PubMed

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

2016-11-01

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

Effects of low frequency rTMS treatment on brain networks for inner speech in patients with schizophrenia and auditory verbal hallucinations.

PubMed

Bais, Leonie; Liemburg, Edith; Vercammen, Ans; Bruggeman, Richard; Knegtering, Henderikus; Aleman, André

2017-08-01

Efficacy of repetitive Transcranial Magnetic Stimulation (rTMS) targeting the temporo-parietal junction (TPJ) for the treatment of auditory verbal hallucinations (AVH) remains under debate. We assessed the influence of a 1Hz rTMS treatment on neural networks involved in a cognitive mechanism proposed to subserve AVH. Patients with schizophrenia (N=24) experiencing medication-resistant AVH completed a 10-day 1Hz rTMS treatment. Participants were randomized to active stimulation of the left or bilateral TPJ, or sham stimulation. The effects of rTMS on neural networks were investigated with an inner speech task during fMRI. Changes within and between neural networks were analyzed using Independent Component Analysis. rTMS of the left and bilateral TPJ areas resulted in a weaker network contribution of the left supramarginal gyrus to the bilateral fronto-temporal network. Left-sided rTMS resulted in stronger network contributions of the right superior temporal gyrus to the auditory-sensorimotor network, right inferior gyrus to the left fronto-parietal network, and left middle frontal gyrus to the default mode network. Bilateral rTMS was associated with a predominant inhibitory effect on network contribution. Sham stimulation showed different patterns of change compared to active rTMS. rTMS of the left temporo-parietal region decreased the contribution of the left supramarginal gyrus to the bilateral fronto-temporal network, which may reduce the likelihood of speech intrusions. On the other hand, left rTMS appeared to increase the contribution of functionally connected regions involved in perception, cognitive control and self-referential processing. These findings hint to potential neural mechanisms underlying rTMS for hallucinations but need corroboration in larger samples. Copyright © 2017 Elsevier Inc. All rights reserved.
Halting the fuse discharge propagation using optical fiber microwires.

PubMed

Rocha, A M; Fernandes, G; Domingues, F; Niehus, M; Pinto, A N; Facão, M; André, P S

2012-09-10

We report and analyze the halting of the fuse effect propagation in optical fiber microwires. The increase of the mode field diameter in the tapered region decreases the optical intensity resulting in the extinction of the fuse effect. This fiber element presents a low insertion loss and can be introduced in the optical network in order to protect the active equipment from the damage caused by the fuse effect.
Whispering - The hidden side of auditory communication.

PubMed

Frühholz, Sascha; Trost, Wiebke; Grandjean, Didier

2016-11-15

Whispering is a unique expression mode that is specific to auditory communication. Individuals switch their vocalization mode to whispering especially when affected by inner emotions in certain social contexts, such as in intimate relationships or intimidating social interactions. Although this context-dependent whispering is adaptive, whispered voices are acoustically far less rich than phonated voices and thus impose higher hearing and neural auditory decoding demands for recognizing their socio-affective value by listeners. The neural dynamics underlying this recognition especially from whispered voices are largely unknown. Here we show that whispered voices in humans are considerably impoverished as quantified by an entropy measure of spectral acoustic information, and this missing information needs large-scale neural compensation in terms of auditory and cognitive processing. Notably, recognizing the socio-affective information from voices was slightly more difficult from whispered voices, probably based on missing tonal information. While phonated voices elicited extended activity in auditory regions for decoding of relevant tonal and time information and the valence of voices, whispered voices elicited activity in a complex auditory-frontal brain network. Our data suggest that a large-scale multidirectional brain network compensates for the impoverished sound quality of socially meaningful environmental signals to support their accurate recognition and valence attribution. Copyright © 2016 Elsevier Inc. All rights reserved.
Internal and external attention and the default mode network.

PubMed

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-wandering, independent of the practitioner's attention focus (i.e., internal vs. external). Copyright © 2017 Elsevier Inc. All rights reserved.
White matter integrity in brain networks relevant to anxiety and depression: evidence from the human connectome project dataset.

PubMed

De Witte, Nele A J; Mueller, Sven C

2017-12-01

Anxiety and depression are associated with altered communication within global brain networks and between these networks and the amygdala. Functional connectivity studies demonstrate an effect of anxiety and depression on four critical brain networks involved in top-down attentional control (fronto-parietal network; FPN), salience detection and error monitoring (cingulo-opercular network; CON), bottom-up stimulus-driven attention (ventral attention network; VAN), and default mode (default mode network; DMN). However, structural evidence on the white matter (WM) connections within these networks and between these networks and the amygdala is lacking. The current study in a large healthy sample (n = 483) observed that higher trait anxiety-depression predicted lower WM integrity in the connections between amygdala and specific regions of the FPN, CON, VAN, and DMN. We discuss the possible consequences of these anatomical alterations for cognitive-affective functioning and underscore the need for further theory-driven research on individual differences in anxiety and depression on brain structure.
Carrying the past to the future: Distinct brain networks underlie individual differences in human spatial working memory capacity.

PubMed

Liu, Siwei; Poh, Jia-Hou; Koh, Hui Li; Ng, Kwun Kei; Loke, Yng Miin; Lim, Joseph Kai Wei; Chong, Joanna Su Xian; Zhou, Juan

2018-08-01

Spatial working memory (SWM) relies on the interplay of anatomically separated and interconnected large-scale brain networks. EEG studies often observe load-associated sustained negative activity during SWM retention. Yet, whether and how such sustained negative activity in retention relates to network-specific functional activation/deactivation and relates to individual differences in SWM capacity remain to be elucidated. To cover these gaps, we recorded concurrent EEG-fMRI data in 70 healthy young adults during the Sternberg delayed-match-to-sample SWM task with three memory load levels. To a subset of participants (N = 28) that performed the task properly and had artefact-free fMRI and EEG data, we employed a novel temporo-spatial principal component analysis to derive load-dependent negative slow wave (NSW) from retention-related event-related potentials. The associations between NSW responses with SWM capacity were divergent in the higher (N = 14) and lower (N = 14) SWM capacity groups. Specifically, larger load-related increase in NSW amplitude was associated with greater SWM capacity for the higher capacity group but lower SWM capacity for the lower capacity group. Furthermore, for the higher capacity group, larger NSW amplitude was related to greater activation in bilateral parietal areas of the fronto-parietal network (FPN) and greater deactivation in medial frontal gyrus and posterior mid-cingulate cortex of the default mode network (DMN) during retention. In contrast, the lower capacity group did not show similar pattern. Instead, greater NSW was linked to higher deactivation in right posterior middle temporal gyrus. Our findings shed light on the possible differential EEG-informed neural network mechanism during memory maintenance underlying individual differences in SWM capacity. Copyright © 2018 Elsevier Inc. All rights reserved.
Photonic and phononic surface and edge modes in three-dimensional phoxonic crystals

NASA Astrophysics Data System (ADS)

Ma, Tian-Xue; Wang, Yue-Sheng; Zhang, Chuanzeng

2018-04-01

We investigate the photonic and phononic surface and edge modes in finite-size three-dimensional phoxonic crystals. By appropriately terminating the phoxonic crystals, the photons and phonons can be simultaneously guided at the two-dimensional surface and/or the one-dimensional edge of the terminated crystals. The Bloch surface and edge modes show that the electromagnetic and acoustic waves are highly localized near the surface and edge, respectively. The surface and edge geometries play important roles in tailoring the dispersion relations of the surface and edge modes, and dual band gaps for the surface or edge modes can be simultaneously achieved by changing the geometrical configurations. Furthermore, as the band gaps for the bulk modes are the essential prerequisites for the realization of dual surface and edge modes, the photonic and phononic bulk-mode band gap properties of three different types of phoxonic crystals with six-connected networks are revealed. It is found that the geometrical characteristic of the crystals with six-connected networks leads to dual large bulk-mode band gaps. Compared with the conventional bulk modes, the surface and edge modes provide a new approach for the photon and phonon manipulation and show great potential for phoxonic crystal devices and optomechanics.
Generating broadband vortex modes in ring-core fiber by using a plasmonic q-plate.

PubMed

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.
Principal States of Dynamic Functional Connectivity Reveal the Link Between Resting-State and Task-State Brain: An fMRI Study.

PubMed

Cheng, Lin; Zhu, Yang; Sun, Junfeng; Deng, Lifu; He, Naying; Yang, Yang; Ling, Huawei; Ayaz, Hasan; Fu, Yi; Tong, Shanbao

2018-01-25

Task-related reorganization of functional connectivity (FC) has been widely investigated. Under classic static FC analysis, brain networks under task and rest have been demonstrated a general similarity. However, brain activity and cognitive process are believed to be dynamic and adaptive. Since static FC inherently ignores the distinct temporal patterns between rest and task, dynamic FC may be more a suitable technique to characterize the brain's dynamic and adaptive activities. In this study, we adopted [Formula: see text]-means clustering to investigate task-related spatiotemporal reorganization of dynamic brain networks and hypothesized that dynamic FC would be able to reveal the link between resting-state and task-state brain organization, including broadly similar spatial patterns but distinct temporal patterns. In order to test this hypothesis, this study examined the dynamic FC in default-mode network (DMN) and motor-related network (MN) using Blood-Oxygenation-Level-Dependent (BOLD)-fMRI data from 26 healthy subjects during rest (REST) and a hand closing-and-opening (HCO) task. Two principal FC states in REST and one principal FC state in HCO were identified. The first principal FC state in REST was found similar to that in HCO, which appeared to represent intrinsic network architecture and validated the broadly similar spatial patterns between REST and HCO. However, the second FC principal state in REST with much shorter "dwell time" implied the transient functional relationship between DMN and MN during REST. In addition, a more frequent shifting between two principal FC states indicated that brain network dynamically maintained a "default mode" in the motor system during REST, whereas the presence of a single principal FC state and reduced FC variability implied a more temporally stable connectivity during HCO, validating the distinct temporal patterns between REST and HCO. Our results further demonstrated that dynamic FC analysis could offer unique insights in understanding how the brain reorganizes itself during rest and task states, and the ways in which the brain adaptively responds to the cognitive requirements of tasks.
Default Mode Network Mechanisms of Transcranial Magnetic Stimulation in Depression

PubMed Central

Liston, Conor; Chen, Ashley C.; Zebley, Benjamin D.; Drysdale, Andrew T.; Gordon, Rebecca; Leuchter, Bruce; Voss, Henning U.; Casey, B.J.; Etkin, Amit; Dubin, Marc J.

2014-01-01

Background Repetitive transcranial magnetic stimulation (TMS) of the dorsolateral prefrontal cortex (DLPFC) is an established treatment for depression, but its underlying mechanism of action remains unknown. Abnormalities in two large-scale neuronal networks—the frontoparietal central executive network (CEN) and the medial prefrontal-medial parietal default mode network (DMN)—are consistent findings in depression and potential therapeutic targets for TMS. Here, we assessed the impact of TMS on activity in these networks and their relation to treatment response. Methods We used resting state functional magnetic resonance imaging (rs-fMRI) to measure functional connectivity within and between the DMN and CEN in 17 depressed patients, before and after a five-week course of TMS. Motivated by prior reports, we focused on connectivity seeded from the DLPFC and the subgenual cingulate, a key region closely aligned with the DMN in depression. Connectivity was also compared to a cohort of 35 healthy controls. Results Prior to treatment, functional connectivity in depressed patients was abnormally elevated within the DMN and diminished within the CEN, and connectivity between these two networks was altered. TMS normalized depression-related subgenual hyperconnectivity in the DMN but did not alter connectivity in the CEN. TMS also induced anticorrelated connectivity between the DLPFC and medial prefrontal DMN nodes. Baseline subgenual connectivity predicted subsequent clinical improvement. Conclusions TMS selectively modulates functional connectivity both within and between the CEN and DMN, and modulation of subgenual cingulate connectivity may play an important mechanistic role in alleviating depression. The results also highlight potential neuroimaging biomarkers for predicting treatment response. PMID:24629537
A high-efficiency HPGe coincidence system for environmental analysis.

PubMed

Britton, R; Davies, A V; Burnett, J L; Jackson, M J

2015-08-01

The Comprehensive Nuclear-Test-Ban Treaty (CTBT) is supported by a network of certified laboratories which must meet certain sensitivity requirements for CTBT relevant radionuclides. At the UK CTBT Radionuclide Laboratory (GBL15), a high-efficiency, dual-detector gamma spectroscopy system has been developed to improve the sensitivity of measurements for treaty compliance, greatly reducing the time required for each sample. Utilising list-mode acquisition, each sample can be counted once, and processed multiple times to further improve sensitivity. For the 8 key radionuclides considered, Minimum Detectable Activities (MDA's) were improved by up to 37% in standard mode (when compared to a typical CTBT detector system), with the acquisition time required to achieve the CTBT sensitivity requirements reduced from 6 days to only 3. When utilising the system in coincidence mode, the MDA for (60) Co in a high-activity source was improved by a factor of 34 when compared to a standard CTBT detector, and a factor of 17 when compared to the dual-detector system operating in standard mode. These MDA improvements will allow the accurate and timely quantification of radionuclides that decay via both singular and cascade γ emission, greatly enhancing the effectiveness of CTBT laboratories. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.
Erratum to "10 Gbit/s mode-multiplexed QPSK transmission using MDM-to-MFDM based single coherent receiver for intra- and inter data center networking" [Opt. Commun. 391 (2017) 106-110

NASA Astrophysics Data System (ADS)

Asif, Rameez; Haithem, Mustafa

2018-03-01

We revisited our previous work "10 Gbit/s mode-multiplexed QPSK transmission using MDM-to-MFDM based single coherent receiver for intraand inter data center networking" [Opt. Commun. 391 (2017) 106-110] and discover a mistake in the Appendix 'A', i.e. mode-selective coherent detection technique. In this section, the direct referencing of the previous work at appropriate points is not adequate (page no. 109).
A tri-state optical switch for local area network communications

NASA Technical Reports Server (NTRS)

Simms, Garfield

1993-01-01

This novel structure is a heterojunction phototransistor which can be used as an emitter-detector, and when placed in a quiescent mode, the device becomes a passive transmitter. By varying the voltage bias, this novel device will switch between all three modes of operation. Such a device has broad application in network environments with operation speeds of less than 50 MHz and distances of less than 1 km, e.g. automobiles, airplanes, and intra-instrumentation. During this period, the emission mode for this device was studied and mathematically modeled.
Solvated dissipative electro-elastic network model of hydrated proteins

NASA Astrophysics Data System (ADS)

Martin, Daniel

2013-03-01

Elastic network models coarse grain proteins into a network of residue beads connected by springs. We add dissipative dynamics to this mechanical system by applying overdamped Langevin equations of motion to normal-mode vibrations of the network. In addition, the network is made heterogeneous and softened at the protein surface by accounting for hydration of the ionized residues. Solvation changes the network Hessian in two ways. Diagonal solvation terms soften the spring constants and off-diagonal dipole-dipole terms correlate displacements of the ionized residues. The model is used to formulate the response functions of the electrostatic potential and electric field appearing in theories of redox reactions and spectroscopy. We also formulate the dielectric response of the protein and find that solvation of the surface ionized residues leads to a slow relaxation peak in the dielectric loss spectrum, about two orders of magnitude slower than the main peak of protein relaxation. Finally, the solvated network is used to formulate the allosteric response of the protein to ion binding. The global thermodynamics of ion binding is not strongly affected by the network solvation, but it dramatically enhances conformational changes in response to placing a charge at the a the active site.
Solvated dissipative electro-elastic network model of hydrated proteins

NASA Astrophysics Data System (ADS)

Martin, Daniel R.; Matyushov, Dmitry V.

2012-10-01

Elastic network models coarse grain proteins into a network of residue beads connected by springs. We add dissipative dynamics to this mechanical system by applying overdamped Langevin equations of motion to normal-mode vibrations of the network. In addition, the network is made heterogeneous and softened at the protein surface by accounting for hydration of the ionized residues. Solvation changes the network Hessian in two ways. Diagonal solvation terms soften the spring constants and off-diagonal dipole-dipole terms correlate displacements of the ionized residues. The model is used to formulate the response functions of the electrostatic potential and electric field appearing in theories of redox reactions and spectroscopy. We also formulate the dielectric response of the protein and find that solvation of the surface ionized residues leads to a slow relaxation peak in the dielectric loss spectrum, about two orders of magnitude slower than the main peak of protein relaxation. Finally, the solvated network is used to formulate the allosteric response of the protein to ion binding. The global thermodynamics of ion binding is not strongly affected by the network solvation, but it dramatically enhances conformational changes in response to placing a charge at the active site of the protein.
The hydrogen-bond network of water supports propagating optical phonon-like modes.

PubMed

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.
Impaired Long Distance Functional Connectivity and Weighted Network Architecture in Alzheimer's Disease

PubMed Central

Liu, Yong; Yu, Chunshui; Zhang, Xinqing; Liu, Jieqiong; Duan, Yunyun; Alexander-Bloch, Aaron F.; Liu, Bing; Jiang, Tianzi; Bullmore, Ed

2014-01-01

Alzheimer's disease (AD) is increasingly recognized as a disconnection syndrome, which leads to cognitive impairment due to the disruption of functional activity across large networks or systems of interconnected brain regions. We explored abnormal functional magnetic resonance imaging (fMRI) resting-state dynamics, functional connectivity, and weighted functional networks, in a sample of patients with severe AD (N = 18) and age-matched healthy volunteers (N = 21). We found that patients had reduced amplitude and regional homogeneity of low-frequency fMRI oscillations, and reduced the strength of functional connectivity, in several regions previously described as components of the default mode network, for example, medial posterior parietal cortex and dorsal medial prefrontal cortex. In patients with severe AD, functional connectivity was particularly attenuated between regions that were separated by a greater physical distance; and loss of long distance connectivity was associated with less efficient global and nodal network topology. This profile of functional abnormality in severe AD was consistent with the results of a comparable analysis of data on 2 additional groups of patients with mild AD (N = 17) and amnestic mild cognitive impairment (MCI; N = 18). A greater degree of cognitive impairment, measured by the mini-mental state examination across all patient groups, was correlated with greater attenuation of functional connectivity, particularly over long connection distances, for example, between anterior and posterior components of the default mode network, and greater reduction of global and nodal network efficiency. These results indicate that neurodegenerative disruption of fMRI oscillations and connectivity in AD affects long-distance connections to hub nodes, with the consequent loss of network efficiency. This profile was evident also to a lesser degree in the patients with less severe cognitive impairment, indicating that the potential of resting-state fMRI measures as biomarkers or predictors of disease progression in AD. PMID:23314940
Differential regulation of NMDA receptors by d-serine and glycine in mammalian spinal locomotor networks

PubMed Central

Acton, David

2017-01-01

Activation of N-methyl-d-aspartate receptors (NMDARs) requires the binding of a coagonist, either d-serine or glycine, in addition to glutamate. Changes in occupancy of the coagonist binding site are proposed to modulate neural networks including those controlling swimming in frog tadpoles. Here, we characterize regulation of the NMDAR coagonist binding site in mammalian spinal locomotor networks. Blockade of NMDARs by d(−)-2-amino-5-phosphonopentanoic acid (d-APV) or 5,7-dichlorokynurenic acid reduced the frequency and amplitude of pharmacologically induced locomotor-related activity recorded from the ventral roots of spinal-cord preparations from neonatal mice. Furthermore, d-APV abolished synchronous activity induced by blockade of inhibitory transmission. These results demonstrate an important role for NMDARs in murine locomotor networks. Bath-applied d-serine enhanced the frequency of locomotor-related but not disinhibited bursting, indicating that coagonist binding sites are saturated during the latter but not the former mode of activity. Depletion of endogenous d-serine by d-amino acid oxidase or the serine-racemase inhibitor erythro-β-hydroxy-l-aspartic acid (HOAsp) increased the frequency of locomotor-related activity, whereas application of l-serine to enhance endogenous d-serine synthesis reduced burst frequency, suggesting a requirement for d-serine at a subset of synapses onto inhibitory interneurons. Consistent with this, HOAsp was ineffective during disinhibited activity. Bath-applied glycine (1–100 µM) failed to alter locomotor-related activity, whereas ALX 5407, a selective inhibitor of glycine transporter-1 (GlyT1), enhanced burst frequency, supporting a role for GlyT1 in NMDAR regulation. Together these findings indicate activity-dependent and synapse-specific regulation of the coagonist binding site within spinal locomotor networks, illustrating the importance of NMDAR regulation in shaping motor output. NEW & NOTEWORTHY We provide evidence that NMDARs within murine spinal locomotor networks determine the frequency and amplitude of ongoing locomotor-related activity in vitro and that NMDARs are regulated by d-serine and glycine in a synapse-specific and activity-dependent manner. In addition, glycine transporter-1 is shown to be an important regulator of NMDARs during locomotor-related activity. These results show how excitatory transmission can be tuned to diversify the output repertoire of spinal locomotor networks in mammals. PMID:28202572
Linked functional network abnormalities during intrinsic and extrinsic activity in schizophrenia as revealed by a data-fusion approach.

PubMed

Hashimoto, Ryu-Ichiro; Itahashi, Takashi; Okada, Rieko; Hasegawa, Sayaka; Tani, Masayuki; Kato, Nobumasa; Mimura, Masaru

2018-01-01

Abnormalities in functional brain networks in schizophrenia have been studied by examining intrinsic and extrinsic brain activity under various experimental paradigms. However, the identified patterns of abnormal functional connectivity (FC) vary depending on the adopted paradigms. Thus, it is unclear whether and how these patterns are inter-related. In order to assess relationships between abnormal patterns of FC during intrinsic activity and those during extrinsic activity, we adopted a data-fusion approach and applied partial least square (PLS) analyses to FC datasets from 25 patients with chronic schizophrenia and 25 age- and sex-matched normal controls. For the input to the PLS analyses, we generated a pair of FC maps during the resting state (REST) and the auditory deviance response (ADR) from each participant using the common seed region in the left middle temporal gyrus, which is a focus of activity associated with auditory verbal hallucinations (AVHs). PLS correlation (PLS-C) analysis revealed that patients with schizophrenia have significantly lower loadings of a component containing positive FCs in default-mode network regions during REST and a component containing positive FCs in the auditory and attention-related networks during ADR. Specifically, loadings of the REST component were significantly correlated with the severities of positive symptoms and AVH in patients with schizophrenia. The co-occurrence of such altered FC patterns during REST and ADR was replicated using PLS regression, wherein FC patterns during REST are modeled to predict patterns during ADR. These findings provide an integrative understanding of altered FCs during intrinsic and extrinsic activity underlying core schizophrenia symptoms.
Reconfiguration of a Multi-oscillator Network by Light in the Drosophila Circadian Clock.

PubMed

Chatterjee, Abhishek; Lamaze, Angélique; De, Joydeep; Mena, Wilson; Chélot, Elisabeth; Martin, Béatrice; Hardin, Paul; Kadener, Sebastian; Emery, Patrick; Rouyer, François

2018-06-07

The brain clock that drives circadian rhythms of locomotor activity relies on a multi-oscillator neuronal network. In addition to synchronizing the clock with day-night cycles, light also reformats the clock-driven daily activity pattern. How changes in lighting conditions modify the contribution of the different oscillators to remodel the daily activity pattern remains largely unknown. Our data in Drosophila indicate that light readjusts the interactions between oscillators through two different modes. We show that a morning s-LNv > DN1p circuit works in series, whereas two parallel evening circuits are contributed by LNds and other DN1ps. Based on the photic context, the master pacemaker in the s-LNv neurons swaps its enslaved partner-oscillator-LNd in the presence of light or DN1p in the absence of light-to always link up with the most influential phase-determining oscillator. When exposure to light further increases, the light-activated LNd pacemaker becomes independent by decoupling from the s-LNvs. The calibration of coupling by light is layered on a clock-independent network interaction wherein light upregulates the expression of the PDF neuropeptide in the s-LNvs, which inhibits the behavioral output of the DN1p evening oscillator. Thus, light modifies inter-oscillator coupling and clock-independent output-gating to achieve flexibility in the network. It is likely that the light-induced changes in the Drosophila brain circadian network could reveal general principles of adapting to varying environmental cues in any neuronal multi-oscillator system. Copyright © 2018 Elsevier Ltd. All rights reserved.

Emotions promote social interaction by synchronizing brain activity across individuals

PubMed Central

Nummenmaa, Lauri; Glerean, Enrico; Viinikainen, Mikko; Jääskeläinen, Iiro P.; Hari, Riitta; Sams, Mikko

2012-01-01

Sharing others’ emotional states may facilitate understanding their intentions and actions. Here we show that networks of brain areas “tick together” in participants who are viewing similar emotional events in a movie. Participants’ brain activity was measured with functional MRI while they watched movies depicting unpleasant, neutral, and pleasant emotions. After scanning, participants watched the movies again and continuously rated their experience of pleasantness–unpleasantness (i.e., valence) and of arousal–calmness. Pearson’s correlation coefficient was used to derive multisubject voxelwise similarity measures [intersubject correlations (ISCs)] of functional MRI data. Valence and arousal time series were used to predict the moment-to-moment ISCs computed using a 17-s moving average. During movie viewing, participants' brain activity was synchronized in lower- and higher-order sensory areas and in corticolimbic emotion circuits. Negative valence was associated with increased ISC in the emotion-processing network (thalamus, ventral striatum, insula) and in the default-mode network (precuneus, temporoparietal junction, medial prefrontal cortex, posterior superior temporal sulcus). High arousal was associated with increased ISC in the somatosensory cortices and visual and dorsal attention networks comprising the visual cortex, bilateral intraparietal sulci, and frontal eye fields. Seed-voxel–based correlation analysis confirmed that these sets of regions constitute dissociable, functional networks. We propose that negative valence synchronizes individuals’ brain areas supporting emotional sensations and understanding of another’s actions, whereas high arousal directs individuals’ attention to similar features of the environment. By enhancing the synchrony of brain activity across individuals, emotions may promote social interaction and facilitate interpersonal understanding. PMID:22623534
Decreased Efficiency of Task-Positive and Task-Negative Networks During Working Memory in Schizophrenia

PubMed Central

Metzak, Paul D.; Riley, Jennifer D.; Wang, Liang; Whitman, Jennifer C.; Ngan, Elton T. C.; Woodward, Todd S.

2012-01-01

Working memory (WM) is one of the most impaired cognitive processes in schizophrenia. Functional magnetic resonance imaging (fMRI) studies in this area have typically found a reduction in information processing efficiency but have focused on the dorsolateral prefrontal cortex. In the current study using the Sternberg Item Recognition Test, we consider networks of regions supporting WM and measure the activation of functionally connected neural networks over different WM load conditions. We used constrained principal component analysis with a finite impulse response basis set to compare the estimated hemodynamic response associated with different WM load condition for 15 healthy control subjects and 15 schizophrenia patients. Three components emerged, reflecting activated (task-positive) and deactivated (task-negative or default-mode) neural networks. Two of the components (with both task-positive and task-negative aspects) were load dependent, were involved in encoding and delay phases (one exclusively encoding and the other both encoding and delay), and both showed evidence for decreased efficiency in patients. The results suggest that WM capacity is reached sooner for schizophrenia patients as the overt levels of WM load increase, to the point that further increases in overt memory load do not increase fMRI activation, and lead to performance impairments. These results are consistent with an account holding that patients show reduced efficiency in task-positive and task-negative networks during WM and also partially support the shifted inverted-U-shaped curve theory of the relationship between WM load and fMRI activation in schizophrenia. PMID:21224491
Implication of the Slow-5 Oscillations in the Disruption of the Default-Mode Network in Healthy Aging and Stroke

PubMed Central

Nair, Veena A.; Mossahebi, Pouria; Young, Brittany M.; Chacon, Marcus; Jensen, Matthew; Birn, Rasmus M.; Meyerand, Mary E.; Prabhakaran, Vivek

2016-01-01

Abstract The processes of normal aging and aging-related pathologies subject the brain to an active re-organization of its brain networks. Among these, the default-mode network (DMN) is consistently implicated with a demonstrated reduction in functional connectivity within the network. However, no clear stipulation on the underlying mechanisms of the de-synchronization has yet been provided. In this study, we examined the spectral distribution of the intrinsic low-frequency oscillations (LFOs) of the DMN sub-networks in populations of young normals, older subjects, and acute and subacute ischemic stroke patients. The DMN sub-networks were derived using a mid-order group independent component analysis with 117 eyes-closed resting-state functional magnetic resonance imaging (rs-fMRI) sessions from volunteers in those population groups, isolating three robust components of the DMN among other resting-state networks. The posterior component of the DMN presented noticeable differences. Measures of amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) of the network component demonstrated a decrease in resting-state cortical oscillation power in the elderly (normal and patient), specifically in the slow-5 (0.01–0.027 Hz) range of oscillations. Furthermore, the contribution of the slow-5 oscillations during the resting state was diminished for a greater influence of the slow-4 (0.027–0.073 Hz) oscillations in the subacute stroke group, not only suggesting a vulnerability of the slow-5 oscillations to disruption but also indicating a change in the distribution of the oscillations within the resting-state frequencies. The reduction of network slow-5 fALFF in the posterior DMN component was found to present a potential association with behavioral measures, suggesting a brain–behavior relationship to those oscillations, with this change in behavior potentially resulting from an altered network integrity induced by a weakening of the slow-5 oscillations during the resting state. The repeated identification of those frequencies in the disruption of DMN stresses a critical role of the slow-5 oscillations in network disruption, and it accentuates the importance of managing those oscillations in the health of the DMN. PMID:27130180
Closed loop supply chain network design with fuzzy tactical decisions

NASA Astrophysics Data System (ADS)

Sherafati, Mahtab; Bashiri, Mahdi

2016-09-01

One of the most strategic and the most significant decisions in supply chain management is reconfiguration of the structure and design of the supply chain network. In this paper, a closed loop supply chain network design model is presented to select the best tactical and strategic decision levels simultaneously considering the appropriate transportation mode in activated links. The strategic decisions are made for a long term; thus, it is more satisfactory and more appropriate when the decision variables are considered uncertain and fuzzy, because it is more flexible and near to the real world. This paper is the first research which considers fuzzy decision variables in the supply chain network design model. Moreover, in this study a new fuzzy optimization approach is proposed to solve a supply chain network design problem with fuzzy tactical decision variables. Finally, the proposed approach and model are verified using several numerical examples. The comparison of the results with other existing approaches confirms efficiency of the proposed approach. Moreover the results confirms that by considering the vagueness of tactical decisions some properties of the supply chain network will be improved.
Bluetooth Low Power Modes Applied to the Data Transportation Network in Home Automation Systems.

PubMed

Etxaniz, Josu; Aranguren, Gerardo

2017-04-30

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

PubMed Central

Etxaniz, Josu; Aranguren, Gerardo

2017-01-01

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

PubMed

Dayan, Eran; Sella, Irit; Mukovskiy, Albert; Douek, Yehonatan; Giese, Martin A; Malach, Rafael; Flash, Tamar

2016-01-01

The default mode network (DMN) has been implicated in an array of social-cognitive functions, including self-referential processing, theory of mind, and mentalizing. Yet, the properties of the external stimuli that elicit DMN activity in relation to these domains remain unknown. Previous studies suggested that motion kinematics is utilized by the brain for social-cognitive processing. Here, we used functional MRI to examine whether the DMN is sensitive to parametric manipulations of observed motion kinematics. Preferential responses within core DMN structures differentiating non-biological from biological kinematics were observed for the motion of a realistically looking, human-like avatar, but not for an abstract object devoid of human form. Differences in connectivity patterns during the observation of biological versus non-biological kinematics were additionally observed. Finally, the results additionally suggest that the DMN is coupled more strongly with key nodes in the action observation network, namely the STS and the SMA, when the observed motion depicts human rather than abstract form. These findings are the first to implicate the DMN in the perception of biological motion. They may reflect the type of information used by the DMN in social-cognitive processing. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Prefrontal Cortex Networks Shift from External to Internal Modes during Learning.

PubMed

Brincat, Scott L; Miller, Earl K

2016-09-14

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. 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. Copyright © 2016 the authors 0270-6474/16/369739-16$15.00/0.
Prefrontal Cortex Networks Shift from External to Internal Modes during Learning

PubMed Central

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
Network and Atomistic Simulations Unveil the Structural Determinants of Mutations Linked to Retinal Diseases

PubMed Central

Mariani, Simona; Dell'Orco, Daniele; Felline, Angelo; Raimondi, Francesco; Fanelli, Francesca

2013-01-01

A number of incurable retinal diseases causing vision impairments derive from alterations in visual phototransduction. Unraveling the structural determinants of even monogenic retinal diseases would require network-centered approaches combined with atomistic simulations. The transducin G38D mutant associated with the Nougaret Congenital Night Blindness (NCNB) was thoroughly investigated by both mathematical modeling of visual phototransduction and atomistic simulations on the major targets of the mutational effect. Mathematical modeling, in line with electrophysiological recordings, indicates reduction of phosphodiesterase 6 (PDE) recognition and activation as the main determinants of the pathological phenotype. Sub-microsecond molecular dynamics (MD) simulations coupled with Functional Mode Analysis improve the resolution of information, showing that such impairment is likely due to disruption of the PDEγ binding cavity in transducin. Protein Structure Network analyses additionally suggest that the observed slight reduction of theRGS9-catalyzed GTPase activity of transducin depends on perturbed communication between RGS9 and GTP binding site. These findings provide insights into the structural fundamentals of abnormal functioning of visual phototransduction caused by a missense mutation in one component of the signaling network. This combination of network-centered modeling with atomistic simulations represents a paradigm for future studies aimed at thoroughly deciphering the structural determinants of genetic retinal diseases. Analogous approaches are suitable to unveil the mechanism of information transfer in any signaling network either in physiological or pathological conditions. PMID:24009494
Dynamic functional connectivity of the default mode network tracks daydreaming.

PubMed

Kucyi, Aaron; Davis, Karen D

2014-10-15

Humans spend much of their time engaged in stimulus-independent thoughts, colloquially known as "daydreaming" or "mind-wandering." A fundamental question concerns how awake, spontaneous brain activity represents the ongoing cognition of daydreaming versus unconscious processes characterized as "intrinsic." Since daydreaming involves brief cognitive events that spontaneously fluctuate, we tested the hypothesis that the dynamics of brain network functional connectivity (FC) are linked with daydreaming. We determined the general tendency to daydream in healthy adults based on a daydreaming frequency scale (DDF). Subjects then underwent both resting state functional magnetic resonance imaging (rs-fMRI) and fMRI during sensory stimulation with intermittent thought probes to determine the occurrences of mind-wandering events. Brain regions within the default mode network (DMN), purported to be involved in daydreaming, were assessed for 1) static FC across the entire fMRI scans, and 2) dynamic FC based on FC variability (FCV) across 30s progressively sliding windows of 2s increments within each scan. We found that during both resting and sensory stimulation states, individual differences in DDF were negatively correlated with static FC between the posterior cingulate cortex and a ventral DMN subsystem involved in future-oriented thought. Dynamic FC analysis revealed that DDF was positively correlated with FCV within the same DMN subsystem in the resting state but not during stimulation. However, dynamic but not static FC, in this subsystem, was positively correlated with an individual's degree of self-reported mind-wandering during sensory stimulation. These findings identify temporal aspects of spontaneous DMN activity that reflect conscious and unconscious processes. Copyright © 2014 Elsevier Inc. All rights reserved.
Microwave applicator for in-drum processing of radioactive waste slurry

DOEpatents

White, Terry L.

1994-01-01

A microwave applicator for processing of radioactive waste slurry uses a waveguide network which splits an input microwave of TE.sub.10 rectangular mode to TE.sub.01 circular mode. A cylindrical body has four openings, each receiving 1/4 of the power input. The waveguide network includes a plurality of splitters to effect the 1/4 divisions of power.
Features of the Asynchronous Correlation between the China Coal Price Index and Coal Mining Accidental Deaths.

PubMed

Huang, Yuecheng; Cheng, Wuyi; Luo, Sida; Luo, Yun; Ma, Chengchen; He, Tailin

2016-01-01

The features of the asynchronous correlation between accident indices and the factors that influence accidents can provide an effective reference for warnings of coal mining accidents. However, what are the features of this correlation? To answer this question, data from the China coal price index and the number of deaths from coal mining accidents were selected as the sample data. The fluctuation modes of the asynchronous correlation between the two data sets were defined according to the asynchronous correlation coefficients, symbolization, and sliding windows. We then built several directed and weighted network models, within which the fluctuation modes and the transformations between modes were represented by nodes and edges. Then, the features of the asynchronous correlation between these two variables could be studied from a perspective of network topology. We found that the correlation between the price index and the accidental deaths was asynchronous and fluctuating. Certain aspects, such as the key fluctuation modes, the subgroups characteristics, the transmission medium, the periodicity and transmission path length in the network, were analyzed by using complex network theory, analytical methods and spectral analysis method. These results provide a scientific reference for generating warnings for coal mining accidents based on economic indices.
Metabolic networks evolve towards states of maximum entropy production.

PubMed

Unrean, Pornkamol; Srienc, Friedrich

2011-11-01

A metabolic network can be described by a set of elementary modes or pathways representing discrete metabolic states that support cell function. We have recently shown that in the most likely metabolic state the usage probability of individual elementary modes is distributed according to the Boltzmann distribution law while complying with the principle of maximum entropy production. To demonstrate that a metabolic network evolves towards such state we have carried out adaptive evolution experiments with Thermoanaerobacterium saccharolyticum operating with a reduced metabolic functionality based on a reduced set of elementary modes. In such reduced metabolic network metabolic fluxes can be conveniently computed from the measured metabolite secretion pattern. Over a time span of 300 generations the specific growth rate of the strain continuously increased together with a continuous increase in the rate of entropy production. We show that the rate of entropy production asymptotically approaches the maximum entropy production rate predicted from the state when the usage probability of individual elementary modes is distributed according to the Boltzmann distribution. Therefore, the outcome of evolution of a complex biological system can be predicted in highly quantitative terms using basic statistical mechanical principles. Copyright Â© 2011 Elsevier Inc. All rights reserved.
Aberrant Intrinsic Activity and Connectivity in Cognitively Normal Parkinson's Disease.

PubMed

Harrington, Deborah L; Shen, Qian; Castillo, Gabriel N; Filoteo, J Vincent; Litvan, Irene; Takahashi, Colleen; French, Chelsea

2017-01-01

Disturbances in intrinsic activity during resting-state functional MRI (rsfMRI) are common in Parkinson's disease (PD), but have largely been studied in a priori defined subnetworks. The cognitive significance of abnormal intrinsic activity is also poorly understood, as are abnormalities that precede the onset of mild cognitive impairment. To address these limitations, we leveraged three different analytic approaches to identify disturbances in rsfMRI metrics in 31 cognitively normal PD patients (PD-CN) and 30 healthy adults. Subjects were screened for mild cognitive impairment using the Movement Disorders Society Task Force Level II criteria. Whole-brain data-driven analytic approaches first analyzed the amplitude of low-frequency intrinsic fluctuations (ALFF) and regional homogeneity (ReHo), a measure of local connectivity amongst functionally similar regions. We then examined if regional disturbances in these metrics altered functional connectivity with other brain regions. We also investigated if abnormal rsfMRI metrics in PD-CN were related to brain atrophy and executive, visual organization, and episodic memory functioning. The results revealed abnormally increased and decreased ALFF and ReHo in PD-CN patients within the default mode network (posterior cingulate, inferior parietal cortex, parahippocampus, entorhinal cortex), sensorimotor cortex (primary motor, pre/post-central gyrus), basal ganglia (putamen, caudate), and posterior cerebellar lobule VII, which mediates cognition. For default mode network regions, we also observed a compound profile of altered ALFF and ReHo. Most regional disturbances in ALFF and ReHo were associated with strengthened long-range interactions in PD-CN, notably with regions in different networks. Stronger long-range functional connectivity in PD-CN was also partly expanded to connections that were outside the networks of the control group. Abnormally increased activity and functional connectivity appeared to have a pathological, rather than compensatory influence on cognitive abilities tested in this study. Receiver operating curve analyses demonstrated excellent sensitivity (≥90%) of rsfMRI variables in distinguishing patients from controls, but poor accuracy for brain volume and cognitive variables. Altogether these results provide new insights into the topology, cognitive relevance, and sensitivity of aberrant intrinsic activity and connectivity that precedes clinically significant cognitive impairment. Longitudinal studies are needed to determine if these neurocognitive associations presage the development of future mild cognitive impairment or dementia.
Age differences in default and reward networks during processing of personally relevant information.

PubMed

Grady, Cheryl L; Grigg, Omer; Ng, Charisa

2012-06-01

We recently found activity in default mode and reward-related regions during self-relevant tasks in young adults. Here we examine the effect of aging on engagement of the default network (DN) and reward network (RN) during these tasks. Previous studies have shown reduced engagement of the DN and reward areas in older adults, but the influence of age on these circuits during self-relevant tasks has not been examined. The tasks involved judging personality traits about one's self or a well known other person. There were no age differences in reaction time on the tasks but older adults had more positive Self and Other judgments, whereas younger adults had more negative judgments. Both groups had increased DN and RN activity during the self-relevant tasks, relative to non-self tasks, but this increase was reduced in older compared to young adults. Functional connectivity of both networks during the tasks was weaker in the older relative to younger adults. Intrinsic functional connectivity, measured at rest, also was weaker in the older adults in the DN, but not in the RN. These results suggest that, in younger adults, the processing of personally relevant information involves robust activation of and functional connectivity within these two networks, in line with current models that emphasize strong links between the self and reward. The finding that older adults had more positive judgments, but weaker engagement and less consistent functional connectivity in these networks, suggests potential brain mechanisms for the "positivity bias" with aging. Copyright © 2012 Elsevier Ltd. All rights reserved.
Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia.

PubMed

Whitfield-Gabrieli, Susan; Thermenos, Heidi W; Milanovic, Snezana; Tsuang, Ming T; Faraone, Stephen V; McCarley, Robert W; Shenton, Martha E; Green, Alan I; Nieto-Castanon, Alfonso; LaViolette, Peter; Wojcik, Joanne; Gabrieli, John D E; Seidman, Larry J

2009-01-27

We examined the status of the neural network mediating the default mode of brain function, which typically exhibits greater activation during rest than during task, in patients in the early phase of schizophrenia and in young first-degree relatives of persons with schizophrenia. During functional MRI, patients, relatives, and controls alternated between rest and performance of working memory (WM) tasks. As expected, controls exhibited task-related suppression of activation in the default network, including medial prefrontal cortex (MPFC) and posterior cingulate cortex/precuneus. Patients and relatives exhibited significantly reduced task-related suppression in MPFC, and these reductions remained after controlling for performance. Increased task-related MPFC suppression correlated with better WM performance in patients and relatives and with less psychopathology in all 3 groups. For WM task performance, patients and relatives had greater activation in right dorsolateral prefrontal cortex (DLPFC) than controls. During rest and task, patients and relatives exhibited abnormally high functional connectivity within the default network. The magnitudes of default network connectivity during rest and task correlated with psychopathology in the patients. Further, during both rest and task, patients exhibited reduced anticorrelations between MPFC and DLPFC, a region that was hyperactivated by patients and relatives during WM performance. Among patients, the magnitude of MPFC task suppression negatively correlated with default connectivity, suggesting an association between the hyperactivation and hyperconnectivity in schizophrenia. Hyperactivation (reduced task-related suppression) of default regions and hyperconnectivity of the default network may contribute to disturbances of thought in schizophrenia and risk for the illness.
Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia

PubMed Central

Whitfield-Gabrieli, Susan; Thermenos, Heidi W.; Milanovic, Snezana; Tsuang, Ming T.; Faraone, Stephen V.; McCarley, Robert W.; Shenton, Martha E.; Green, Alan I.; Nieto-Castanon, Alfonso; LaViolette, Peter; Wojcik, Joanne; Gabrieli, John D. E.; Seidman, Larry J.

2009-01-01

We examined the status of the neural network mediating the default mode of brain function, which typically exhibits greater activation during rest than during task, in patients in the early phase of schizophrenia and in young first-degree relatives of persons with schizophrenia. During functional MRI, patients, relatives, and controls alternated between rest and performance of working memory (WM) tasks. As expected, controls exhibited task-related suppression of activation in the default network, including medial prefrontal cortex (MPFC) and posterior cingulate cortex/precuneus. Patients and relatives exhibited significantly reduced task-related suppression in MPFC, and these reductions remained after controlling for performance. Increased task-related MPFC suppression correlated with better WM performance in patients and relatives and with less psychopathology in all 3 groups. For WM task performance, patients and relatives had greater activation in right dorsolateral prefrontal cortex (DLPFC) than controls. During rest and task, patients and relatives exhibited abnormally high functional connectivity within the default network. The magnitudes of default network connectivity during rest and task correlated with psychopathology in the patients. Further, during both rest and task, patients exhibited reduced anticorrelations between MPFC and DLPFC, a region that was hyperactivated by patients and relatives during WM performance. Among patients, the magnitude of MPFC task suppression negatively correlated with default connectivity, suggesting an association between the hyperactivation and hyperconnectivity in schizophrenia. Hyperactivation (reduced task-related suppression) of default regions and hyperconnectivity of the default network may contribute to disturbances of thought in schizophrenia and risk for the illness. PMID:19164577
Age differences in default and reward networks during processing of personally relevant information

PubMed Central

Grady, Cheryl L.; Grigg, Omer; Ng, Charisa

2013-01-01

We recently found activity in default mode and reward-related regions during self-relevant tasks in young adults. Here we examine the effect of aging on engagement of the default network (DN) and reward network (RN) during these tasks. Previous studies have shown reduced engagement of the DN and reward areas in older adults, but the influence of age on these circuits during self-relevant tasks has not been examined. The tasks involved judging personality traits about one’s self or a well known other person. There were no age differences in reaction time on the tasks but older adults had more positive Self and Other judgments, whereas younger adults had more negative judgments. Both groups had increased DN and RN activity during the self-relevant tasks, relative to non-self tasks, but this increase was reduced in older compared to young adults. Functional connectivity of both networks during the tasks was weaker in the older relative to younger adults. Intrinsic functional connectivity, measured at rest, also was weaker in the older adults in the DN, but not in the RN. These results suggest that, in younger adults, the processing of personally relevant information involves robust activation of and functional connectivity within these two networks, in line with current models that emphasize strong links between the self and reward. The finding that older adults had more positive judgments, but weaker engagement and less consistent functional connectivity in these networks, suggests potential brain mechanisms for the “positivity bias” with aging. PMID:22484520
The Operational Role of the Belgian User Support and Operations Centre for the Atmosphere-Space Interactions Monitor (ASIM) on-board the International Space Station.

NASA Astrophysics Data System (ADS)

Muller, C.; Moreau, D., Sr.; Pandey, P. K.; Crosby, N. B.

2014-12-01

The Belgian User Support and Operations Centre (B.USOC) is an operational centre managing technological and scientific payloads on the International Space Station (ISS). B.USOC is the Facility Responsible Centre (FRC) for the European Space Agency's (ESA) Atmosphere-Space Interactions Monitor (ASIM) payload and also manages the Scientific Mission Centre of the Centre National d'Etudes Spatiales (CNES) PICARD satellite that monitors solar activity, among various other space missions. In this respect, B.USOC is ideally positioned to manage possible synergies between ASIM, the satellite TARANIS (Tool for the Analysis of RAdiation from lightNIng and Sprites), other space missions and ground-based networks. The ASIM mission (Neubert, 2009) consists of a package of two nadir instruments: one for the visible spectrum and another for X-ray and gamma-ray frequencies. In the normal operating mode "trigger mode" both instruments continuously measure, but, do not record data below certain thresholds. Another mode is a "timed mode", where, during a certain time the observations are recorded even in the absence of triggers. The "timed mode" demands a lot of flexibility from both scientific teams and B.USOC, as, ASIM's main targets of investigation (sprites and elves) are related to intense thunderstorms and thus, require reliable meteorological forecasts in the entire range of ISS latitudes. Moreover, ASIM is sensitive to a large number of phenomena of which most have a direct relationship with solar activity and therefore would probably need support from the ESA SSA (Space Situational Awareness) Space Weather Coordination Centre (SSCC) that shares the same campus with B.USOC. Local cooperation between the two centres, together with other space payloads such as TARANIS and ground-based networks will greatly optimize ASIM payload operations as well as scientific return. Neubert, T., and the ASIM Team, ASIM - an Instrument Suite for the International Space Station, Corte Workshop 2008, Coupling of Thunderstorms and Lightning Discharges to Near-Earth, Corsica, 2008, edited by N. B. Crosby et al, American Institute of Physics, 978-0-7354-0657-5/09/, 2009.

Elementary Mode Analysis: A Useful Metabolic Pathway Analysis Tool for Characterizing Cellular Metabolism

PubMed Central

Trinh, Cong T.; Wlaschin, Aaron; Srienc, Friedrich

2010-01-01

Elementary Mode Analysis is a useful Metabolic Pathway Analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering. PMID:19015845
The study of RMB exchange rate complex networks based on fluctuation mode

NASA Astrophysics Data System (ADS)

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.
Engineering online and in-person social networks to sustain physical activity: application of a conceptual model.

PubMed

Rovniak, Liza S; Sallis, James F; Kraschnewski, Jennifer L; Sciamanna, Christopher N; Kiser, Elizabeth J; Ray, Chester A; Chinchilli, Vernon M; Ding, Ding; Matthews, Stephen A; Bopp, Melissa; George, Daniel R; Hovell, Melbourne F

2013-08-14

High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants' online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary outcomes will be analyzed using general linear modeling (GLM), or generalized linear modeling if the assumptions for GLM cannot be met. Results will contribute to greater understanding of how to conceptualize and implement social networks to support long-term PA. Establishing social networks for PA across multiple life settings could contribute to cultural norms that sustain active living. ClinicalTrials.gov NCT01142804.
Service offerings and interfaces for the ACTS network of Earth stations

NASA Technical Reports Server (NTRS)

Coney, Thom A.

1988-01-01

The Advanced Communications Satellite (ACTS) is capable of two modes of communication. Mode 1 is a mesh network of Earth stations using baseband-switched, time-division multiple-access (BBS-TDMA) and hopping beams. Mode 2 is a mesh network using satellite-switched, time-division multiple-access (SS-TDMA) and fixed (or hopping) beams. The purpose of this paper is to present the functional requirements and the design of the ACTS Mode 1 Earth station terrestrial interface. Included among the requirements are that: (1) the interface support standard telecommunications service offerings (i.e., voice, video and data at rates ranging from 9.6 kbps to 44 Mbps); (2) the interface support the unique design characteristics of the ACTS communications systems (e.g., the real time demand assignment of satellite capacity); and (3) the interface support test hardware capable of validating ACTS communications processes. The resulting interface design makes use of an appropriate combination of T1 or T3 multiplexers and a small central office (maximum capacity 56 subscriber lines per unit).
How do you make me feel better? Social cognitive emotion regulation and the default mode network.

PubMed

Xie, Xiyao; Mulej Bratec, Satja; Schmid, Gabriele; Meng, Chun; Doll, Anselm; Wohlschläger, Afra; Finke, Kathrin; Förstl, Hans; Zimmer, Claus; Pekrun, Reinhard; Schilbach, Leonhard; Riedl, Valentin; Sorg, Christian

2016-07-01

Socially-induced cognitive emotion regulation (Social-Reg) is crucial for emotional well-being and social functioning; however, its brain mechanisms remain poorly understood. Given that both social cognition and cognitive emotion regulation engage key regions of the default-mode network (DMN), we hypothesized that Social-Reg would rely on the DMN, and that its effectiveness would be associated with social functioning. During functional MRI, negative emotions were elicited by pictures, and - via short instructions - a psychotherapist either down-regulated participants' emotions by employing reappraisal (Reg), or asked them to simply look at the pictures (Look). Adult Attachment Scale was used to measure social functioning. Contrasting Reg versus Look, aversive emotions were successfully reduced during Social-Reg, with increased activations in the prefrontal and parietal cortices, precuneus and the left temporo-parietal junction. These activations covered key nodes of the DMN and were associated with Social-Reg success. Furthermore, participants' attachment security was positively correlated with both Social-Reg success and orbitofrontal cortex involvement during Social-Reg. In addition, specificity of the neural correlates of Social-Reg was confirmed by comparisons with participants' DMN activity at rest and their brain activations during a typical emotional self-regulation task based on the same experimental paradigm without a psychotherapist. Our results provide first evidence for the specific involvement of the DMN in Social-Reg, and the association of Social-Reg with individual differences in attachment security. The findings suggest that DMN dysfunction, found in many neuropsychiatric disorders, may impair the ability to benefit from Social-Reg. Copyright © 2016 Elsevier Inc. All rights reserved.
Geographically distributed environmental sensor system

DOEpatents

French, Patrick; Veatch, Brad; O'Connor, Mike

2006-10-03

The present invention is directed to a sensor network that includes a number of sensor units and a base unit. The base station operates in a network discovery mode (in which network topology information is collected) in a data polling mode (in which sensed information is collected from selected sensory units). Each of the sensor units can include a number of features, including an anemometer, a rain gauge, a compass, a GPS receiver, a barometric pressure sensor, an air temperature sensor, a humidity sensor, a level, and a radiant temperature sensor.
Dynamics of coupled mode solitons in bursting neural networks

NASA Astrophysics Data System (ADS)

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.
Dynamics of coupled mode solitons in bursting neural networks.

PubMed

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.
Attention Network Dysfunction in Bulimia Nervosa - An fMRI Study

PubMed Central

Dahmen, Brigitte; Schulte-Rüther, Martin; Legenbauer, Tanja; Herpertz-Dahlmann, Beate; Konrad, Kerstin

2016-01-01

Objective Recent evidence has suggested an increased rate of comorbid ADHD and subclinical attentional impairments in bulimia nervosa (BN) patients. However, little is known regarding the underlying neural mechanisms of attentional functions in BN. Method Twenty BN patients and twenty age- and weight-matched healthy controls (HC) were investigated using a modified version of the Attention Network Task (ANT) in an fMRI study. This design enabled an investigation of the neural mechanisms associated with the three attention networks involved in alerting, reorienting and executive attention. Results The BN patients showed hyperactivation in parieto-occipital regions and reduced deactivation of default-mode-network (DMN) areas during alerting compared with HCs. Posterior cingulate activation during alerting correlated with the severity of eating-disorder symptoms within the patient group. Conversely, BN patients showed hypoactivation during reorienting and executive attention in anterior cingulate regions, the temporo-parietal junction (TPJ) and parahippocampus compared with HCs, which was negatively associated with global ADHD symptoms and impulsivity, respectively. Discussion Our findings demonstrate altered brain mechanisms in BN associated with all three attentional networks. Failure to deactivate the DMN and increased parieto-occipital activation required for alerting might be associated with a constant preoccupation with food or body image-related thoughts. Hypoactivation of executive control networks and TPJ might increase the likelihood of inattentive and impulsive behaviors and poor emotion regulation. Thus, dysfunction in the attentional network in BN goes beyond an altered executive attentional domain and needs to be considered in the diagnosis and treatment of BN. PMID:27607439
The brain's default network: anatomy, function, and relevance to disease.

PubMed

Buckner, Randy L; Andrews-Hanna, Jessica R; Schacter, Daniel L

2008-03-01

Thirty years of brain imaging research has converged to define the brain's default network-a novel and only recently appreciated brain system that participates in internal modes of cognition. Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment. Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system. Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others. Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems. The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation. The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations. These two subsystems converge on important nodes of integration including the posterior cingulate cortex. The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world. We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer's disease.
Examining the Efficacy of the Modified Story Memory Technique (mSMT) in Persons With TBI Using Functional Magnetic Resonance Imaging (fMRI): The TBI-MEM Trial.

PubMed

Chiaravalloti, Nancy D; Dobryakova, Ekaterina; Wylie, Glenn R; DeLuca, John

2015-01-01

New learning and memory deficits are common following traumatic brain injury (TBI). Yet few studies have examined the efficacy of memory retraining in TBI through the most methodologically vigorous randomized clinical trial. Our previous research has demonstrated that the modified Story Memory Technique (mSMT) significantly improves new learning and memory in multiple sclerosis. The present double-blind, placebo-controlled, randomized clinical trial examined changes in cerebral activation on functional magnetic resonance imaging following mSMT treatment in persons with TBI. Eighteen individuals with TBI were randomly assigned to treatment (n = 9) or placebo (n = 9) groups. Baseline and follow-up functional magnetic resonance imaging was collected during a list-learning task. Significant differences in cerebral activation from before to after treatment were noted in regions belonging to the default mode network and executive control network in the treatment group only. Results are interpreted in light of these networks. Activation differences between the groups likely reflect increased use of strategies taught during treatment. This study demonstrates a significant change in cerebral activation resulting from the mSMT in a TBI sample. Findings are consistent with previous work in multiple sclerosis. Behavioral interventions can show significant changes in the brain, validating clinical utility.
The high speed interconnect system architecture and operation

NASA Astrophysics Data System (ADS)

Anderson, Steven C.

The design and operation of a fiber-optic high-speed interconnect system (HSIS) being developed to meet the requirements of future avionics and flight-control hardware with distributed-system architectures are discussed. The HSIS is intended for 100-Mb/s operation of a local-area network with up to 256 stations. It comprises a bus transmission system (passive star couplers and linear media linked by active elements) and network interface units (NIUs). Each NIU is designed to perform the physical, data link, network, and transport functions defined by the ISO OSI Basic Reference Model (1982 and 1983) and incorporates a fiber-optic transceiver, a high-speed protocol based on the SAE AE-9B linear token-passing data bus (1986), and a specialized application interface unit. The operating modes and capabilities of HSIS are described in detail and illustrated with diagrams.
A Regularizer Approach for RBF Networks Under the Concurrent Weight Failure Situation.

PubMed

Leung, Chi-Sing; Wan, Wai Yan; Feng, Ruibin

2017-06-01

Many existing results on fault-tolerant algorithms focus on the single fault source situation, where a trained network is affected by one kind of weight failure. In fact, a trained network may be affected by multiple kinds of weight failure. This paper first studies how the open weight fault and the multiplicative weight noise degrade the performance of radial basis function (RBF) networks. Afterward, we define the objective function for training fault-tolerant RBF networks. Based on the objective function, we then develop two learning algorithms, one batch mode and one online mode. Besides, the convergent conditions of our online algorithm are investigated. Finally, we develop a formula to estimate the test set error of faulty networks trained from our approach. This formula helps us to optimize some tuning parameters, such as RBF width.
Normal modes of weak colloidal gels

NASA Astrophysics Data System (ADS)

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 physics, our results indicate that long-ranged hydrodynamic interactions play a crucial role in determining the microscopic dynamics and macroscopic properties of weak colloidal gels.
Upgrading a CD-ROM Network for Multimedia Applications.

ERIC Educational Resources Information Center

Sylvia, Margaret

1995-01-01

Addresses issues to consider when upgrading library CD-ROM networks for multimedia applications. Topics includes security issues; workstation requirements such as soundboards and monitors; local area network configurations that avoid bottlenecks: Asynchronous Transfer Mode, Ethernet, and Integrated Services Digital Network; server performance…
Analysis of Dual Mode Systems in an Urban Area : Volume 4A. Program Documentation of the Transportation Economic Analysis Model.

DOT National Transportation Integrated Search

1973-12-01

Various forms of Dual Mode Transportation were analyzed in order to assess the economic viability of the Dual Mode concept. A Dual Mode vehicle is one which operates under manual control on a streee network for some portionof its trip, and operates u...
Second-Order Consensus in Multiagent Systems via Distributed Sliding Mode Control.

PubMed

Yu, Wenwu; Wang, He; Cheng, Fei; Yu, Xinghuo; Wen, Guanghui

2016-11-22

In this paper, the new decoupled distributed sliding-mode control (DSMC) is first proposed for second-order consensus in multiagent systems, which finally solves the fundamental unknown problem for sliding-mode control (SMC) design of coupled networked systems. A distributed full-order sliding-mode surface is designed based on the homogeneity with dilation for reaching second-order consensus in multiagent systems, under which the sliding-mode states are decoupled. Then, the SMC is applied to the decoupled sliding-mode states to reach their origin in finite time, which is the sliding-mode surface. The states of agents can first reach the designed sliding-mode surface in finite time and then move to the second-order consensus state along the surface in finite time as well. The DSMC designed in this paper can eliminate the influence of singularity problems and weaken the influence of chattering, which is still very difficult in the SMC systems. In addition, DSMC proposes a general decoupling framework for designing SMC in networked multiagent systems. Simulations are presented to verify the theoretical results in this paper.
Atomistic modeling of the low-frequency mechanical modes and Raman spectra of icosahedral virus capsids

NASA Astrophysics Data System (ADS)

Dykeman, Eric C.; Sankey, Otto F.

2010-02-01

We describe a technique for calculating the low-frequency mechanical modes and frequencies of a large symmetric biological molecule where the eigenvectors of the Hessian matrix are determined with full atomic detail. The method, which follows order N methods used in electronic structure theory, determines the subset of lowest-frequency modes while using group theory to reduce the complexity of the problem. We apply the method to three icosahedral viruses of various T numbers and sizes; the human viruses polio and hepatitis B, and the cowpea chlorotic mottle virus, a plant virus. From the normal-mode eigenvectors, we use a bond polarizability model to predict a low-frequency Raman scattering profile for the viruses. The full atomic detail in the displacement patterns combined with an empirical potential-energy model allows a comparison of the fully atomic normal modes with elastic network models and normal-mode analysis with only dihedral degrees of freedom. We find that coarse-graining normal-mode analysis (particularly the elastic network model) can predict the displacement patterns for the first few (˜10) low-frequency modes that are global and cooperative.
Functional segregation of the human cingulate cortex is confirmed by functional connectivity based neuroanatomical parcellation.

PubMed

Yu, Chunshui; Zhou, Yuan; Liu, Yong; Jiang, Tianzi; Dong, Haiwei; Zhang, Yunting; Walter, Martin

2011-02-14

The four-region model with 7 specified subregions represents a theoretical construct of functionally segregated divisions of the cingulate cortex based on integrated neurobiological assessments. Under this framework, we aimed to investigate the functional specialization of the human cingulate cortex by analyzing the resting-state functional connectivity (FC) of each subregion from a network perspective. In 20 healthy subjects we systematically investigated the FC patterns of the bilateral subgenual (sACC) and pregenual (pACC) anterior cingulate cortices, anterior (aMCC) and posterior (pMCC) midcingulate cortices, dorsal (dPCC) and ventral (vPCC) posterior cingulate cortices and retrosplenial cortices (RSC). We found that each cingulate subregion was specifically integrated in the predescribed functional networks and showed anti-correlated resting-state fluctuations. The sACC and pACC were involved in an affective network and anti-correlated with the sensorimotor and cognitive networks, while the pACC also correlated with the default-mode network and anti-correlated with the visual network. In the midcingulate cortex, however, the aMCC was correlated with the cognitive and sensorimotor networks and anti-correlated with the visual, affective and default-mode networks, whereas the pMCC only correlated with the sensorimotor network and anti-correlated with the cognitive and visual networks. The dPCC and vPCC involved in the default-mode network and anti-correlated with the sensorimotor, cognitive and visual networks, in contrast, the RSC was mainly correlated with the PCC and thalamus. Based on a strong hypothesis driven approach of anatomical partitions of the cingulate cortex, we could confirm their segregation in terms of functional neuroanatomy, as suggested earlier by task studies or exploratory multi-seed investigations. Copyright © 2010 Elsevier Inc. All rights reserved.
Sox2: A multitasking networker

PubMed Central

Reiprich, Simone; Wegner, Michael

2014-01-01

The transcription factor Sox2 is best known as a pluripotency factor in stem and precursor cells and its expression generally correlates with an undifferentiated state. Proposed modes of action include those as classical transcription factor and pre-patterning factor with influence on histone modifications and chromatin structure. Recently, we provided the first detailed analysis of Sox2 expression and function during development of oligodendrocytes, the myelin-forming cells of the CNS. Surprisingly, we found evidence for a role of Sox2 as differentiation factor and found it to act through modulation of microRNA levels. Thus, we add new facets to the functional repertoire of Sox2 and throw light on the networking activity of this multitasking developmental regulator. PMID:27502481

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