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Sample records for mode network connectivity

  1. Default Mode Network Connectivity in Stroke Patients.

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    Tuladhar, Anil Man; Snaphaan, Liselore; Shumskaya, Elena; Rijpkema, Mark; Fernandez, Guillén; Norris, David G; de Leeuw, Frank-Erik

    2013-01-01

    The pathophysiology of episodic memory dysfunction after infarction is not completely understood. It has been suggested that infarctions located anywhere in the brain can induce widespread effects causing disruption of functional networks of the cortical regions. The default mode network, which includes the medial temporal lobe, is a functional network that is associated with episodic memory processing. We investigated whether the default mode network activity is reduced in stroke patients compared to healthy control subjects in the resting state condition. We assessed the whole brain network properties during resting state functional MRI in 21 control subjects and 20 'first-ever' stroke patients. Patients were scanned 9-12 weeks after stroke onset. Stroke lesions were located in various parts of the brain. Independent component analyses were conducted to identify the default mode network and to compare the group differences of the default mode network. Furthermore, region-of-interest based analysis was performed to explore the functional connectivity between the regions of the default mode network. Stroke patients performed significantly worse than control subjects on the delayed recall score on California verbal learning test. We found decreased functional connectivity in the left medial temporal lobe, posterior cingulate and medial prefrontal cortical areas within the default mode network and reduced functional connectivity between these regions in stroke patients compared with controls. There were no significant volumetric differences between the groups. These results demonstrate that connectivity within the default mode network is reduced in 'first-ever' stroke patients compared to control subjects. This phenomenon might explain the occurrence of post-stroke cognitive dysfunction in stroke patients.

  2. Default mode network connectivity during task execution.

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

    2015-11-15

    Initially described as task-induced deactivations during goal-directed paradigms of high attentional load, the unresolved functionality of default mode regions has long been assumed to interfere with task performance. However, recent evidence suggests a potential default mode network involvement in fulfilling cognitive demands. We tested this hypothesis in a finger opposition paradigm with task and fixation periods which we compared with an independent resting state scan using functional magnetic resonance imaging and a comprehensive analysis pipeline including activation, functional connectivity, behavioural and graph theoretical assessments. The results indicate task specific changes in the default mode network topography. Behaviourally, we show that increased connectivity of the posterior cingulate cortex with the left superior frontal gyrus predicts faster reaction times. Moreover, interactive and dynamic reconfiguration of the default mode network regions' functional connections illustrates their involvement with the task at hand with higher-level global parallel processing power, yet preserved small-world architecture in comparison with rest. These findings demonstrate that the default mode network does not disengage during this paradigm, but instead may be involved in task relevant processing. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Altered Functional Connectivity of the Default Mode Network in Low-Empathy Subjects.

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    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.

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

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

    2015-11-15

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

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

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

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    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…

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

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

    2017-03-01

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

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

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

    2015-01-01

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

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

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

    2013-07-30

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

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

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

    2016-11-10

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

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

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    Yan eTao

    2015-11-01

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

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

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

    2017-12-01

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

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

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    Ileana Pacheco-Colón

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

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

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

    2016-06-01

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

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

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    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.

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

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    David G. Weissman

    2018-04-01

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

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

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

    2018-04-01

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

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

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

    2016-03-01

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

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

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    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

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

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    Kathrin Koch

    2018-06-01

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

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

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    Fernanda Palhano-Fontes

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

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

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    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.

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

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    Youjun Li

    2017-08-01

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

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

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

    2012-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Xiao-Fei eYang

    2013-01-01

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

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

    Science.gov (United States)

    Washington, Stuart D; VanMeter, John W

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

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

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    Horne, Charlotte Mary; Norbury, Ray

    2018-04-20

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

  8. Altered effective connectivity within default mode network in major depression disorder

    Science.gov (United States)

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

    2016-03-01

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

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

    Science.gov (United States)

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

    2017-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Donna L Murdaugh

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

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

    Science.gov (United States)

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

    2017-05-01

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

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

    Science.gov (United States)

    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.

  13. The Default Mode Network and Social Understanding of Others: What do Brain Connectivity Studies Tell Us

    Directory of Open Access Journals (Sweden)

    Wanqing eLi

    2014-02-01

    Full Text Available The Default Mode Network (DMN has been found to be involved in various domains of cognitive and social processing. The present article will review brain connectivity results related to the DMN in the fields of social understanding of others: emotion perception, empathy, theory of mind, and morality. Most of the reviewed studies focused on healthy subjects with no neurological and psychiatric disease, but some studies on patients with autism and psychopathy will also be discussed. Common results show that the medial prefrontal cortex (MPFC plays a key role in the social understanding of others, and the subregions of the MPFC contribute differently to this function according to their roles in different subsystems of the DMN. At the bottom, the ventral MPFC in the medial temporal lobe subsystem and its connections with emotion regions are mainly associated with emotion engagement during social interactions. Above, the anterior MPFC (aMPFC in the cortical midline structures and its connections with posterior and anterior cingulate cortex contribute mostly to making self-other distinctions. At the top, the dorsal MPFC (dMPFC in the dMPFC subsystem and its connection with the temporo-parietal junction (TPJ are primarily related to the understanding of other’s mental states. As behaviors become more complex, the related regions in frontal cortex are located higher. This reflects the transfer of information processing from automatic to cognitive processes with the increase of the complexity of social interaction. Besides the MPFC and TPJ, the connectivities of posterior cingulate cortex also show some changes during tasks from the four social fields. These results indicate that the DMN is indispensable in the social understanding of others.

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

    OpenAIRE

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

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

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    Wei-Che Lin

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

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

    Science.gov (United States)

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

    2017-11-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

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

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

    2016-10-30

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

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

    NARCIS (Netherlands)

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

    2017-01-01

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

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

    OpenAIRE

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

    2018-01-01

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

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

    Science.gov (United States)

    Vemuri, Kavita; Surampudi, Bapi Raju

    2015-08-01

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

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

    Science.gov (United States)

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

    2015-04-15

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

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

    OpenAIRE

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2018-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Xiaofen Ma

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

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

    Science.gov (United States)

    Dodell-Feder, David; Delisi, Lynn E; Hooker, Christine I

    2014-06-01

    Unaffected first-degree relatives of individuals with schizophrenia (i.e., those at familial high-risk [FHR]), demonstrate social dysfunction qualitatively similar though less severe than that of their affected relatives. These social difficulties may be the consequence of genetically conferred disruption to aspects of the default mode network (DMN), such as the dMPFC subsystem, which overlaps with the network of brain regions recruited during social cognitive processes. In the present study, we investigate this possibility, testing DMN connectivity and its relationship to social functioning in FHR using resting-state fMRI. Twenty FHR individuals and 17 controls underwent fMRI during a resting-state scan. Hypothesis-driven functional connectivity analyses examined ROI-to-ROI correlations between the DMN's hubs, and regions of the dMPFC subsystem and MTL subsystem. Connectivity values were examined in relationship to a measure of social functioning and empathy/perspective-taking. Results demonstrate that FHR exhibit reduced connectivity specifically within the dMPFC subsystem of the DMN. Certain ROI-to-ROI correlations predicted aspects of social functioning and empathy/perspective-taking across all participants. Together, the data indicate that disruption to the dMPFC subsystem of the DMN may be associated with familial risk for schizophrenia, and that these intrinsic connections may carry measurable consequences for social functioning. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. The Association among Default Mode Network Functional Connectivity, Mentalization, and Psychopathology in a Nonclinical Sample: An eLORETA Study.

    Science.gov (United States)

    Farina, Benedetto; Della Marca, Giacomo; Maestoso, Giulia; Amoroso, Noemi; Valenti, Enrico Maria; Carbone, Giuseppe Alessio; Massullo, Chiara; Contardi, Anna; Imperatori, Claudio

    2018-01-01

    We investigated default mode network (DMN) electroencephalography (EEG) functional connectivity differences between individuals with self-reported high mentalization capability and low psychopathological symptoms, versus participants with mentalization impairments and high psychopathological symptoms. Forty-nine students (35 women) with a mean age of 22.92 ± 2.53 years were administered the Mentalization Questionnaire (MZQ) and the Symptom Checklist-90-Revised. Five minutes of EEG during resting state were also recorded for each participant. DMN functional connectivity analyses were conducted by means of the exact Low Resolution Electric Tomography software (eLORETA). Compared to the individuals with high mentalization capability and lower self-reported psychopathological symptoms, participants with mentalization impairments and high psychopathological symptoms showed a decrease of EEG beta connectivity between: (i) the right and left medial frontal lobe, and (ii) the left medial frontal lobe and the right anterior cingulate cortex. Furthermore, while MZQ total score was positively associated with DMN network connections (i.e., right and left medial frontal lobes), several psychopathological symptoms (i.e., interpersonal sensitivity, depression, and psychoticism) were negatively associated with DMN connectivity. Our results may reflect a top-down emotion regulation deficit which is associated with both internalizing and externalizing behavior problems. © 2018 S. Karger AG, Basel.

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

    Science.gov (United States)

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

    2016-01-01

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

  10. Effective connectivity within the default mode network: dynamic causal modeling of resting-state fMRI data

    Directory of Open Access Journals (Sweden)

    Maksim eSharaev

    2016-02-01

    Full Text Available 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 BOLD (Blood-oxygen-level dependent 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 fMRI (functional magnetic resonance imaging 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.

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

    Science.gov (United States)

    Rzepa, Ewelina; Tudge, Luke; McCabe, Ciara

    2015-09-10

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

  12. Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data.

    Science.gov (United States)

    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 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.

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

    Science.gov (United States)

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

    2017-11-01

    Rumination and cognitive reactivity (dysfunctional cognitions after sad mood-induction) remain high in remitted Major Depressive Disorder (MDD) and can contribute to new episodes. These factors have been linked to increased fMRI resting-state functional-connectivity within the Default-Mode Network (DMN). It remains unclear whether (I) increased DMN-connectivity persists during MDD-remission, and (II) whether sad mood-induction differentially affects DMN-connectivity in remitted-MDD vs controls. Moreover, DMN-connectivity studies in remitted-MDD were previously confounded by antidepressant-use. Sixty-two MDD-patients remitted from ≥2 episodes, psychotropic-medication free, and 41 controls, participated in two 5-min neutral and sad mood-inductions by autobiographical-recall and neutral/sad music, each followed by 8-min resting-state fMRI-scanning. We identified DMN-components using Independent Component Analysis and entered subject- and sessions-specific components into a repeated measures analysis of variance. Connectivity-differences were extracted and correlated with baseline cognitive reactivity and rumination as measures of vulnerability for recurrence. After sad vs neutral mood-induction, controls, but not remitted-MDD, showed an increase in connectivity between the posterior-DMN and a cluster consisting mostly of the hippocampus (P = 0.006). Less posterior-DMN-hippocampal connectivity was associated with higher cognitive reactivity (r = -0.21, P = 0.046) and rumination (r = -0.27, P = 0.017). After recalling sad autobiographical-memories, aberrant posterior-DMN-hippocampal connectivity, associated with cognitive reactivity and rumination, remains a neural vulnerability in MDD-remission. © The Author (2017). Published by Oxford University Press.

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

    Directory of Open Access Journals (Sweden)

    Thomas Alderson

    2017-11-01

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

  15. Subjective Cognitive Decline Is Associated With Altered Default Mode Network Connectivity in Individuals With a Family History of Alzheimer's Disease.

    Science.gov (United States)

    Verfaillie, Sander C J; Pichet Binette, Alexa; Vachon-Presseau, Etienne; Tabrizi, Shirin; Savard, Mélissa; Bellec, Pierre; Ossenkoppele, Rik; Scheltens, Philip; van der Flier, Wiesje M; Breitner, John C S; Villeneuve, Sylvia

    2018-05-01

    Both subjective cognitive decline (SCD) and a family history of Alzheimer's disease (AD) portend risk of brain abnormalities and progression to dementia. Posterior default mode network (pDMN) connectivity is altered early in the course of AD. It is unclear whether SCD predicts similar outcomes in cognitively normal individuals with a family history of AD. We studied 124 asymptomatic individuals with a family history of AD (age 64 ± 5 years). Participants were categorized as having SCD if they reported that their memory was becoming worse (SCD + ). We used extensive neuropsychological assessment to investigate five different cognitive domain performances at baseline (n = 124) and 1 year later (n = 59). We assessed interconnectivity among three a priori defined ROIs: pDMN, anterior ventral DMN, medial temporal memory system (MTMS), and the connectivity of each with the rest of brain. Sixty-eight (55%) participants reported SCD. Baseline cognitive performance was comparable between groups (all false discovery rate-adjusted p values > .05). At follow-up, immediate and delayed memory improved across groups, but the improvement in immediate memory was reduced in SCD + compared with SCD - (all false discovery rate-adjusted p values < .05). When compared with SCD - , SCD + subjects showed increased pDMN-MTMS connectivity (false discovery rate-adjusted p < .05). Higher connectivity between the MTMS and the rest of the brain was associated with better baseline immediate memory, attention, and global cognition, whereas higher MTMS and pDMN-MTMS connectivity were associated with lower immediate memory over time (all false discovery rate-adjusted p values < .05). SCD in cognitively normal individuals is associated with diminished immediate memory practice effects and a brain connectivity pattern that mirrors early AD-related connectivity failure. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

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

    2014-01-01

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

  17. Altered dynamic functional connectivity in the default mode network in patients with cirrhosis and minimal hepatic encephalopathy

    International Nuclear Information System (INIS)

    Chen, Hua-Jun; Lin, Hai-Long; Chen, Qiu-Feng; Liu, Peng-Fei

    2017-01-01

    Abnormal brain intrinsic functional connectivity (FC) has been documented in minimal hepatic encephalopathy (MHE) by static connectivity analysis. However, changes in dynamic FC (dFC) remain unknown. We aimed to identify altered dFC within the default mode network (DMN) associated with MHE. Resting-state functional MRI data were acquired from 20 cirrhotic patients with MHE and 24 healthy controls. DMN seed regions were defined using seed-based FC analysis (centered on the posterior cingulate cortex (PCC)). Dynamic FC architecture was calculated using a sliding time-window method. K-means clustering (number of clusters = 2-4) was applied to estimate FC states. When the number of clusters was 2, MHE patients presented weaker connectivity strengths compared with controls in states 1 and 2. In state 1, decreased FC strength was found between the PCC/precuneus (PCUN) and right medial temporal lobe (MTL)/bilateral lateral temporal cortex (LTC); left inferior parietal lobule (IPL) and right MTL/left LTC; right IPL and right MTL/bilateral LTC; right MTL and right LTC; and medial prefrontal cortex (MPFC) and right MTL/bilateral LTC. In state 2, reduced FC strength was observed between the PCC/PCUN and bilateral MTL/bilateral LTC; left IPL and left MTL/bilateral LTC/MPFC; and left LTC and right LTC. Altered connectivities from state 1 were correlated with patient cognitive performance. Similar findings were observed when the number of clusters was set to 3 or 4. Aberrant dynamic DMN connectivity is an additional characteristic of MHE. Dynamic connectivity analysis offers a novel paradigm for understanding MHE-related mechanisms. (orig.)

  18. Altered dynamic functional connectivity in the default mode network in patients with cirrhosis and minimal hepatic encephalopathy

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Hua-Jun; Lin, Hai-Long [Fujian Medical University Union Hospital, Department of Radiology, Fuzhou (China); Chen, Qiu-Feng; Liu, Peng-Fei [Central South University, School of Information Science and Engineering, Changsha (China)

    2017-09-15

    Abnormal brain intrinsic functional connectivity (FC) has been documented in minimal hepatic encephalopathy (MHE) by static connectivity analysis. However, changes in dynamic FC (dFC) remain unknown. We aimed to identify altered dFC within the default mode network (DMN) associated with MHE. Resting-state functional MRI data were acquired from 20 cirrhotic patients with MHE and 24 healthy controls. DMN seed regions were defined using seed-based FC analysis (centered on the posterior cingulate cortex (PCC)). Dynamic FC architecture was calculated using a sliding time-window method. K-means clustering (number of clusters = 2-4) was applied to estimate FC states. When the number of clusters was 2, MHE patients presented weaker connectivity strengths compared with controls in states 1 and 2. In state 1, decreased FC strength was found between the PCC/precuneus (PCUN) and right medial temporal lobe (MTL)/bilateral lateral temporal cortex (LTC); left inferior parietal lobule (IPL) and right MTL/left LTC; right IPL and right MTL/bilateral LTC; right MTL and right LTC; and medial prefrontal cortex (MPFC) and right MTL/bilateral LTC. In state 2, reduced FC strength was observed between the PCC/PCUN and bilateral MTL/bilateral LTC; left IPL and left MTL/bilateral LTC/MPFC; and left LTC and right LTC. Altered connectivities from state 1 were correlated with patient cognitive performance. Similar findings were observed when the number of clusters was set to 3 or 4. Aberrant dynamic DMN connectivity is an additional characteristic of MHE. Dynamic connectivity analysis offers a novel paradigm for understanding MHE-related mechanisms. (orig.)

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

    Science.gov (United States)

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

    2018-01-01

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

  20. Minimum cost connection networks

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Tvede, Mich

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

  1. High dimensional ICA analysis detects within-network functional connectivity damage of default mode and sensory motor networks in Alzheimer's disease

    Directory of Open Access Journals (Sweden)

    Ottavia eDipasquale

    2015-02-01

    Full Text Available High dimensional independent component analysis (ICA, compared to low dimensional ICA, allows performing a detailed parcellation of the resting state networks. The purpose of this study was to give further insight into functional connectivity (FC in Alzheimer’s disease (AD using high dimensional ICA. For this reason, we performed both low and high dimensional ICA analyses of resting state fMRI (rfMRI data of 20 healthy controls and 21 AD patients, focusing on the primarily altered default mode network (DMN and exploring the sensory motor network (SMN. As expected, results obtained at low dimensionality were in line with previous literature. Moreover, high dimensional results allowed us to observe either the presence of within-network disconnections and FC damage confined to some of the resting state sub-networks. Due to the higher sensitivity of the high dimensional ICA analysis, our results suggest that high-dimensional decomposition in sub-networks is very promising to better localize FC alterations in AD and that FC damage is not confined to the default mode network.

  2. Alpha/Theta Neurofeedback Increases Mentalization and Default Mode Network Connectivity in a Non-Clinical Sample.

    Science.gov (United States)

    Imperatori, Claudio; Della Marca, Giacomo; Amoroso, Noemi; Maestoso, Giulia; Valenti, Enrico Maria; Massullo, Chiara; Carbone, Giuseppe Alessio; Contardi, Anna; Farina, Benedetto

    2017-11-01

    Several studies showed the effectiveness of alpha/theta (A/T) neurofeedback training in treating some psychiatric conditions. Despite the evidence of A/T effectiveness, the psychological and neurobiological bases of its effects is still unclear. The aim of the present study was to explore the usefulness of the A/T training in increasing mentalization in a non-clinical sample. The modifications of electroencephalographic (EEG) functional connectivity in Default Mode Network (DMN) associated with A/T training were also investigated. Forty-four subjects were enrolled in the study and randomly assigned to receive ten sessions of A/T training [neurofeedback group (NFG) = 22], or to act as controls [waiting list group (WLG) = 22]. All participants were administered the mentalization questionnaire (MZQ) and the Symptom Checklist-90-Revised (SCL-90-R). In the post training assessment, compared to WLG, NFG showed a significant increase of MZQ total scores (3.94 ± 0.73 vs. 3.53 ± 0.77; F 1;43 = 8.19; p = 0.007; d = 0.863). Furthermore, A/T training was also associated with a significant increase of EEG functional connectivity in several DMN brain areas (e.g. Posterior Cingulate Cortex). Taken together our results support the usefulness of the A/T training in enhancing mentalization and DMN connectivity.

  3. Abnormal resting state effective connectivity within the default mode network in major depressive disorder: A spectral dynamic causal modeling study.

    Science.gov (United States)

    Li, Liang; Li, Baojuan; Bai, Yuanhan; Liu, Wenlei; Wang, Huaning; Leung, Hoi-Chung; Tian, Ping; Zhang, Linchuan; Guo, Fan; Cui, Long-Biao; Yin, Hong; Lu, Hongbing; Tan, Qingrong

    2017-07-01

    Understanding the neural basis underlying major depressive disorder (MDD) is essential for the diagnosis and treatment of this mental disorder. Aberrant activation and functional connectivity of the default mode network (DMN) have been consistently found in patients with MDD. It is not known whether effective connectivity within the DMN is altered in MDD. The primary object of this study is to investigate the effective connectivity within the DMN during resting state in MDD patients before and after eight weeks of antidepressant treatment. We defined four regions of the DMN (medial frontal cortex, posterior cingulate cortex, left parietal cortex, and right parietal cortex) for each participant using a group independent component analysis. The coupling parameters reflecting the causal interactions among the DMN regions were estimated using spectral dynamic causal modeling (DCM). Twenty-seven MDD patients and 27 healthy controls were included in the statistical analysis. Our results showed declined influences from the left parietal cortex to other DMN regions in the pre-treatment patients as compared with healthy controls. After eight weeks of treatment, the influence from the right parietal cortex to the posterior cingulate cortex significantly decreased. These findings suggest that the reduced excitatory causal influence of the left parietal cortex is the key alteration of the DMN in patients with MDD, and the disrupted causal influences that parietal cortex exerts on the posterior cingulate cortex is responsive to antidepressant treatment.

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

    Science.gov (United States)

    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.

  5. Network connectivity value.

    Science.gov (United States)

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

    2017-04-21

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

  6. Dynamic causal modeling of hippocampal links within the human default mode network: Lateralization and computational stability of effective connections

    Directory of Open Access Journals (Sweden)

    Vadim Leonidovich Ushakov

    2016-10-01

    Full Text Available The purpose of this paper was to study causal relationships between left and right hippocampal regions (LHIP and RHIP, respectively within the default mode network (DMN as represented by its key structures: the medial prefrontal cortex (MPFC, posterior cingulate cortex (PCC and the inferior parietal cortex of left (LIPC and right (RIPC hemispheres. Furthermore, we were interested in testing the stability of the connectivity patterns when adding or deleting regions of interest. The functional magnetic resonance imaging (fMRI data from a group of 30 healthy right-handed subjects in the resting state were collected and a connectivity analysis was performed. To model the effective connectivity, we used the spectral Dynamic Causal Modeling (DCM. Three DCM analyses were completed. Two of them modeled interaction between five nodes that included four DMN key structures in addition to either LHIP or RHIP. The last DCM analysis modeled interactions between four nodes whereby one of the main DMN structures, PCC, was excluded from the analysis. The results of all DCM analyses indicated a high level of stability in the computational method: those parts of the winning models that included the key DMN structures demonstrated causal relations known from recent research. However, we discovered new results as well. First of all, we found a pronounced asymmetry in LHIP and RHIP connections. LHIP demonstrated a high involvement of DMN activity with preponderant information outflow to all other DMN regions. Causal interactions of LHIP were bidirectional only in the case of LIPC. On the contrary, RHIP was primarily affected by inputs from LIPC, RIPC and LHIP without influencing these or other DMN key structures. For the first time, an inhibitory link was found from MPFC to LIPC, which may indicate the subjects’ effort to maintain a resting state. Functional connectivity data echoed these results, though they also showed links not reflected in the patterns of

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

    Directory of Open Access Journals (Sweden)

    Nicolai Franzmeier

    2017-08-01

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

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

    Science.gov (United States)

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

    2011-02-25

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

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Ricardo Cáceda

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

  11. Minimum cost connection networks

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Tvede, Mich

    2015-01-01

    In the present paper we consider the allocation of costs in connection networks. Agents have connection demands in form of pairs of locations they want to have connected. Connections between locations are costly to build. The problem is to allocate costs of networks satisfying all connection...... demands. We use a few axioms to characterize allocation rules that truthfully implement cost minimizing networks satisfying all connection demands in a game where: (1) a central planner announces an allocation rule and a cost estimation rule; (2) every agent reports her own connection demand as well...... as all connection costs; (3) the central planner selects a cost minimizing network satisfying reported connection demands based on the estimated costs; and, (4) the planner allocates the true costs of the selected network. It turns out that an allocation rule satisfies the axioms if and only if relative...

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

    Science.gov (United States)

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

    2017-07-10

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

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  14. Handbook of networking & connectivity

    CERN Document Server

    McClain, Gary R

    1994-01-01

    Handbook of Networking & Connectivity focuses on connectivity standards in use, including hardware and software options. The book serves as a guide for solving specific problems that arise in designing and maintaining organizational networks.The selection first tackles open systems interconnection, guide to digital communications, and implementing TCP/IP in an SNA environment. Discussions focus on elimination of the SNA backbone, routing SNA over internets, connectionless versus connection-oriented networks, internet concepts, application program interfaces, basic principles of layering, proto

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

    Science.gov (United States)

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

    2016-06-01

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

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

    OpenAIRE

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  18. Patients with first-episode, drug-naive schizophrenia and subjects at ultra-high risk of psychosis shared increased cerebellar-default mode network connectivity at rest.

    Science.gov (United States)

    Wang, Houliang; Guo, Wenbin; Liu, Feng; Wang, Guodong; Lyu, Hailong; Wu, Renrong; Chen, Jindong; Wang, Shuai; Li, Lehua; Zhao, Jingping

    2016-05-18

    Increased cerebellar-default mode network (DMN) connectivity has been observed in first-episode, drug-naive patients with schizophrenia. However, it remains unclear whether increased cerebellar-DMN connectivity starts earlier than disease onset. Thirty-four ultra-high risk (UHR) subjects, 31 first-episode, drug-naive patients with schizophrenia and 37 healthy controls were enrolled for a resting-state scan. The imaging data were analyzed using the seed-based functional connectivity (FC) method. Compared with the controls, UHR subjects and patients with schizophrenia shared increased connectivity between the right Crus I and bilateral posterior cingulate cortex/precuneus and between Lobule IX and the left superior medial prefrontal cortex. There are positive correlations between the right Crus I-bilateral precuneus connectivity and clinical variables (Structured Interview for Prodromal Syndromes/Positive and Negative Symptom Scale negative symptoms/total scores) in the UHR subjects. Increased cerebellar-DMN connectivity shared by the UHR subjects and the patients not only highlights the importance of the DMN in the pathophysiology of psychosis but also may be a trait alteration for psychosis.

  19. 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.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2018-03-01

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

  1. Adolescent Gender Differences in Cognitive Control Performance and Functional Connectivity Between Default Mode and Fronto-Parietal Networks Within a Self-Referential Context

    Directory of Open Access Journals (Sweden)

    Gabriela Alarcón

    2018-04-01

    Full Text Available Ineffective reduction of functional connectivity between the default mode network (DMN and frontoparietal network (FPN during cognitive control can interfere with performance in healthy individuals—a phenomenon present in psychiatric disorders, such as depression. Here, this mechanism is studied in healthy adolescents by examining gender differences in task-regressed functional connectivity using functional magnetic resonance imaging (MRI and a novel task designed to place the DMN—supporting self-referential processing (SRP—and FPN—supporting cognitive control—into conflict. Compared to boys, girls showed stronger functional connectivity between DMN and FPN during cognitive control in an SRP context (n = 40; boys = 20, a context that also elicited more errors of omission in girls. The gender difference in errors of omission was mediated by higher self-reported co-rumination—the extensive and repetitive discussion of problems and focus on negative feelings with a same-gender peer—by girls, compared to boys. These findings indicate that placing internal and external attentional demands in conflict lead to persistent functional connectivity between FPN and DMN in girls, but not boys; however, deficits in performance during this context were explained by co-rumination, such that youth with higher co-rumination displayed the largest performance deficits. Previous research shows that co-rumination predicts depressive symptoms during adolescence; thus, gender differences in the mechanisms involved with transitioning from internal to external processing may be relevant for understanding heightened vulnerability for depression in adolescent girls.

  2. Posttraumatic stress disorder symptom severity is associated with reduced default mode network connectivity in individuals with elevated genetic risk for psychopathology.

    Science.gov (United States)

    Miller, Danielle R; Logue, Mark W; Wolf, Erika J; Maniates, Hannah; Robinson, Meghan E; Hayes, Jasmeet P; Stone, Annjanette; Schichman, Steven; McGlinchey, Regina E; Milberg, William P; Miller, Mark W

    2017-07-01

    Accumulating evidence suggests that posttraumatic stress disorder (PTSD) is associated with disrupted default mode network (DMN) connectivity, but findings across studies have not been uniform. Individual differences in relevant genes may account for some of the reported variability in the relationship between DMN connectivity and PTSD. In this study, we investigated this possibility using genome-wide association study (GWAS) derived polygenic risk scores (PRSs) for relevant psychiatric traits. We hypothesized that the association between PTSD and DMN connectivity would be moderated by genetic risk for one or more psychiatric traits such that individuals with elevated polygenic risk for psychopathology and severe PTSD would exhibit disrupted DMN connectivity. Participants were 156 white, non-Hispanic veterans of the wars in Iraq and Afghanistan who were genotyped and underwent resting state functional magnetic resonance imaging and clinical assessment. PRSs for neuroticism, anxiety, major depressive disorder, and cross-disorder risk (based on five psychiatric disorders) were calculated using summary statistics from published large-scale consortia-based GWASs. Cross-disorder polygenic risk influenced the relationship between DMN connectivity and PTSD symptom severity such that individuals at greater genetic risk showed a significant negative association between PTSD symptom severity and connectivity between the posterior cingulate cortex and right middle temporal gyrus. Polygenic risk for neuroticism, anxiety, and major depressive disorder did not influence DMN connectivity directly or through an interaction with PTSD. Findings illustrate the potential power of genome-wide PRSs to advance understanding of the relationship between PTSD and DMN connectivity, a putative neural endophenotype of the disorder. © 2017 Wiley Periodicals, Inc.

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

    Science.gov (United States)

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

    2016-08-01

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

  4. 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.

    Science.gov (United States)

    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.

  5. 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

    Directory of Open Access Journals (Sweden)

    Ji Sun Hong

    2018-04-01

    Full Text Available 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.

  6. 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.

    Science.gov (United States)

    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.

  7. Increased functional connectivity in the default mode network in mild cognitive impairment: a maladaptive compensatory mechanism associated with poor semantic memory performance.

    Science.gov (United States)

    Gardini, Simona; Venneri, Annalena; Sambataro, Fabio; Cuetos, Fernando; Fasano, Fabrizio; Marchi, Massimo; Crisi, Girolamo; Caffarra, Paolo

    2015-01-01

    Semantic memory decline and changes of default mode network (DMN) connectivity have been reported in mild cognitive impairment (MCI). Only a few studies, however, have investigated the role of changes of activity in the DMN on semantic memory in this clinical condition. The present study aimed to investigate more extensively the relationship between semantic memory impairment and DMN intrinsic connectivity in MCI. Twenty-one MCI patients and 21 healthy elderly controls matched for demographic variables took part in this study. All participants underwent a comprehensive semantic battery including tasks of category fluency, visual naming and naming from definition for objects, actions and famous people, word-association for early and late acquired words and reading. A subgroup of the original sample (16 MCI patients and 20 healthy elderly controls) was also scanned with resting state functional magnetic resonance imaging and DMN connectivity was estimated using a seed-based approach. Compared with healthy elderly, patients showed an extensive semantic memory decline in category fluency, visual naming, naming from definition, words-association, and reading tasks. Patients presented increased DMN connectivity between the medial prefrontal regions and the posterior cingulate and between the posterior cingulate and the parahippocampus and anterior hippocampus. MCI patients also showed a significant negative correlation of medial prefrontal gyrus connectivity with parahippocampus and posterior hippocampus and visual naming performance. Our findings suggest that increasing DMN connectivity may contribute to semantic memory deficits in MCI, specifically in visual naming. Increased DMN connectivity with posterior cingulate and medio-temporal regions seems to represent a maladaptive reorganization of brain functions in MCI, which detrimentally contributes to cognitive impairment in this clinical population.

  8. Evidence of a dissociation pattern in resting-state default mode network connectivity in first-episode, treatment-naive major depression patients.

    Science.gov (United States)

    Zhu, Xueling; Wang, Xiang; Xiao, Jin; Liao, Jian; Zhong, Mingtian; Wang, Wei; Yao, Shuqiao

    2012-04-01

    Imaging studies have shown that major depressive disorder (MDD) is associated with altered activity patterns of the default mode network (DMN). However, the neural correlates of the resting-state DMN and MDD-related pathopsychological characteristics, such as depressive rumination and overgeneral autobiographical memory (OGM) phenomena, still remain unclear. Using independent component analysis, we analyzed resting-state functional magnetic resonance imaging data obtained from 35 first-episode, treatment-naive young adults with MDD and from 35 matched healthy control subjects. Patients with MDD exhibited higher levels of rumination and OGM than did the control subjects. We observed increased functional connectivity in the anterior medial cortex regions (especially the medial prefrontal cortex and anterior cingulate cortex) and decreased functional connectivity in the posterior medial cortex regions (especially the posterior cingulate cortex/precuneus) in MDD patients compared with control subjects. In the depressed group, the increased functional connectivity in the anterior medial cortex correlated positively with rumination score, while the decreased functional connectivity in the posterior medial cortex correlated negatively with OGM score. We report dissociation between anterior and posterior functional connectivity in resting-state DMNs of first-episode, treatment-naive young adults with MDD. Increased functional connectivity in anterior medial regions of the resting-state DMN was associated with rumination, whereas decreased functional connectivity in posterior medial regions was associated with OGM. These results provide new evidence for the importance of the DMN in the pathophysiology of MDD and suggest that abnormal DMN activity may be an MDD trait. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  9. Resting State Default Mode Network Connectivity, Dual Task Performance, Gait Speed, and Postural Sway in Older Adults with Mild Cognitive Impairment.

    Science.gov (United States)

    Crockett, Rachel A; Hsu, Chun Liang; Best, John R; Liu-Ambrose, Teresa

    2017-01-01

    Aging is associated with an increased risk of falling. In particular, older adults with mild cognitive impairment (MCI) are more vulnerable to falling compared with their healthy counterparts. Major contributors to this increased falls risk include a decline in dual task performance, gait speed, and postural sway. Recent evidence highlights the potential influence of the default mode network (DMN), the frontoparietal network (FPN), and the supplementary motor area (SMA) on dual task performance, gait speed, and postural sway. The DMN is active during rest and deactivates during task-oriented processes, to maintain attention and stay on task. The FPN and SMA are involved in top-down attentional control, motor planning, and motor execution. The DMN shows less deactivation during task in older adults with MCI. This lack of deactivation is theorized to increase competition for resources between the DMN and task-related brain regions (e.g., the FPN and SMA), increasing distraction from the task and reducing task performance. However, no study has yet investigated the relationship between the between-network connectivity of the DMN with these regions and dual task walking, gait speed or postural sway. We hypothesized that greater functional connectivity both within the DMN and between DMN-FPN and DMN-SMA, will be associated with poorer performance during dual task walking, slower gait speed, and greater postural sway in older adults with MCI. Forty older adults with MCI were measured on a dual task-walking paradigm, gait speed over a 4-m walk, and postural sway using a sway-meter. Greater within-DMN connectivity was significantly correlated with poorer dual task performance. Furthermore, greater inter-network connectivity between the DMN and SMA was significantly correlated with slower gait speed and greater postural sway on the eyes open floor sway task. Thus, greater resting state DMN functional connectivity may be an underlying neural mechanism for reduced dual task

  10. Evaluation of connected vehicle impact on mobility and mode choice

    Directory of Open Access Journals (Sweden)

    Simon Minelli

    2015-10-01

    Full Text Available Connected vehicle is emerging as a solution to exacerbating congestion problems in urban areas. It is important to understand the impacts of connected vehicle on network and travel behavior of road users. The main objective of this paper is to evaluate the impact of connected vehicle on the mode choice and mobility of transportation networks. An iterative methodology was used in this paper where demands for various modes were modified based on the changes in travel time between each origin-destination (OD pair caused by introduction of connected vehicle. Then a traffic assignment was performed in a micro-simulation model, which was able to accurately simulate vehicle-to-vehicle communication. It is assumed that vehicles are equipped with a dynamic route guidance technology to choose their own route using real-time traffic information obtained through communication. The travel times obtained from the micro-simulation model were compared with a base scenario with no connected vehicle. The methodology was tested for a portion of Downtown Toronto, Ontario, Canada. In order to quantify changes in mode share with changes in travel time associated with each OD pair, mode choice models were developed for auto, transit, cycling and pedestrians using data mainly from the Transportation Tomorrow Survey. The impact of connected vehicle on mode choice was evaluated for different market penetrations of connected vehicle. The results of this study show that average travel times for the whole auto mode will generally increase, with the largest increase from connected vehicles. This causes an overall move away from the auto mode for high market penetrations if a dynamic route guidance algorithm is implemented.

  11. [Dysfunctional resting-state connectivity of default mode network in adolescent patients with first-episode drug-naive major depressive disorder].

    Science.gov (United States)

    Li, S Y; Zhu, Y; Wang, Y L; Lü, P P; Zuo, W B; Li, F Y

    2017-12-05

    Objective: To study resting-state functional connectivity (FC) of default mode network (DMN) in adolescent patients with first-episode drug-naive major depressive disorder (MDD). Methods: We enrolled thirty first-episode and drug-naive adolescent MDD patients and twenty-nine adolescent healthy control (HC) participants in the First Affiliated Hospital of Zhengzhou University. There were no differences in age, sex, and education between the MDD and HC group. Resting-state functional magnetic resonance images (fMRI) was performed. We selected posterior cingulate cortex (PCC) and medial prefrontal cortex (MPFC) of DMN as regions of interests (ROI). The differences of these regions from the whole brain functional connectivity were analyzed. The relations between abnormalities in FCs of DMN and clinical variables were further investigated. Results: Compared to the HCs, the MDD patients had congruently reduced FCs between the PCC and cerebellum, temporal cortices, occipital cortices, fusiform, dorsolateral prefrontal cortex. MPFC not only had reduced FCs with fusiform, temporal cortices, anterior cingulate cortex, but also had enhanced FCs with occipital cortices, parietal cortices, and precentral gyrus. In addition, the increased FC between the right MPFC and right precentral gyrus was positive correlated with Hamilton Rating Scale for Depression (HAMD) scores ( r =0.38, P =0.04). The reduced FC between the left middle temporal gyrus and left PCC as well as the enhanced FC between the right middle cingulum and right MPFC were positive correlated with the duration of depression since onset ( r =0.39, P =0.03; r =0.38, P =0.04). Conclusions: These findings show dysfunctional DMN connectivity of adolescent MDD patients. Neurodevelopmental abnormalities in DMN may present in adolescent MDD.

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

    Science.gov (United States)

    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.

  13. Intrinsic Functional Connectivity in Salience and Default Mode Networks and Aberrant Social Processes in Youth at Ultra-High Risk for Psychosis.

    Science.gov (United States)

    Pelletier-Baldelli, Andrea; Bernard, Jessica A; Mittal, Vijay A

    2015-01-01

    Social processes are key to navigating the world, and investigating their underlying mechanisms and cognitive architecture can aid in understanding disease states such as schizophrenia, where social processes are highly impacted. Evidence suggests that social processes are impaired in individuals at ultra high-risk for the development of psychosis (UHR). Understanding these phenomena in UHR youth may clarify disease etiology and social processes in a period that is characterized by significantly fewer confounds than schizophrenia. Furthermore, understanding social processing deficits in this population will help explain these processes in healthy individuals. The current study examined resting state connectivity of the salience (SN) and default mode networks (DMN) in association with facial emotion recognition (FER), an integral aspect of social processes, as well as broader social functioning (SF) in UHR individuals and healthy controls. Consistent with the existing literature, UHR youth were impaired in FER and SF when compared with controls. In the UHR group, we found increased connectivity between the SN and the medial prefrontal cortex, an area of the DMN relative to controls. In UHR youth, the DMN exhibited both positive and negative correlations with the somatosensory cortex/cerebellum and precuneus, respectively, which was linked with better FER performance. For SF, results showed that sensory processing links with the SN might be important in allowing for better SF for both groups, but especially in controls where sensory processing is likely to be unimpaired. These findings clarify how social processing deficits may manifest in psychosis, and underscore the importance of SN and DMN connectivity for social processing more generally.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-11-15

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

  15. Connecting and Networking for Schools

    Science.gov (United States)

    Resources for connecting and networking for schools through e-newsletters, finding school IAQ Champions and other EPA school programs such as Asthma, Energy Star, Clean School Bus USA, School Flag, etc.

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

    Science.gov (United States)

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

    2018-03-14

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

  17. Network Connection Management

    CERN Document Server

    IT Department, Communication Systems and Network Group

    2005-01-01

    The CERN network database is a key element of the CERN network infrastructure. It is absolutely essential that its information is kept up-to-date for security reasons and to ensure a smooth running of the network infrastructure. Over the years, some of the information in the database has become obsolete. The database therefore needs to be cleaned up, for which we are requesting your help. In the coming weeks, you may receive an electronic mail from Netops.database@cern.ch relating to the clean-up. If you receive such a message, it will be for one of the following reasons: You are the person responsible for or the main user of a system for which a problem has been detected, or You have been the supervisor of a person who has now left CERN (according to the HR database), or The problem has been passed up to you because someone under your supervision has not taken the necessary action within four weeks of notification. Just open the link that will be included in the message and follow the instructions....

  18. Network Connection Management

    CERN Multimedia

    IT Department

    2005-01-01

    The CERN network database is a key element of the CERN network infrastructure. It is absolutely essential that its information is kept up-to-date for security reasons and to ensure smooth running of the network infrastructure. Over the years, some of the information in the database has become obsolete. The database therefore needs to be cleaned up, for which we are requesting your help. In the coming weeks, you may receive an electronic mail from Netops.database@cern.ch relating to the clean-up. If you receive such a message, it will be for one of the following reasons: You are the person responsible for or the main user of a system for which a problem has been detected, or You have been the supervisor of a person who has now left CERN (according to the HR database), or The problem has been passed up to you because someone under your supervision has not taken the necessary action within four weeks of notification. Just open the link that will be included in the message and follow the instructions. Thank ...

  19. Finite connectivity attractor neural networks

    International Nuclear Information System (INIS)

    Wemmenhove, B; Coolen, A C C

    2003-01-01

    We study a family of diluted attractor neural networks with a finite average number of (symmetric) connections per neuron. As in finite connectivity spin glasses, their equilibrium properties are described by order parameter functions, for which we derive an integral equation in replica symmetric approximation. A bifurcation analysis of this equation reveals the locations of the paramagnetic to recall and paramagnetic to spin-glass transition lines in the phase diagram. The line separating the retrieval phase from the spin-glass phase is calculated at zero temperature. All phase transitions are found to be continuous

  20. Default network connectivity in medial temporal lobe amnesia.

    Science.gov (United States)

    Hayes, Scott M; Salat, David H; Verfaellie, Mieke

    2012-10-17

    There is substantial overlap between the brain regions supporting episodic memory and the default network. However, in humans, the impact of bilateral medial temporal lobe (MTL) damage on a large-scale neural network such as the default mode network is unknown. To examine this issue, resting fMRI was performed with amnesic patients and control participants. Seed-based functional connectivity analyses revealed robust default network connectivity in amnesia in cortical default network regions such as medial prefrontal cortex, posterior medial cortex, and lateral parietal cortex, as well as evidence of connectivity to residual MTL tissue. Relative to control participants, decreased posterior cingulate cortex connectivity to MTL and increased connectivity to cortical default network regions including lateral parietal and medial prefrontal cortex were observed in amnesic patients. In contrast, somatomotor network connectivity was intact in amnesic patients, indicating that bilateral MTL lesions may selectively impact the default network. Changes in default network connectivity in amnesia were largely restricted to the MTL subsystem, providing preliminary support from MTL amnesic patients that the default network can be fractionated into functionally and structurally distinct components. To our knowledge, this is the first examination of the default network in amnesia.

  1. Scholastic performance and functional connectivity of brain networks in children.

    Directory of Open Access Journals (Sweden)

    Laura Chaddock-Heyman

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

  2. Altered network hub connectivity after acute LSD administration

    Directory of Open Access Journals (Sweden)

    Felix Müller

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

  3. Reduced Default Mode Connectivity in Adolescents With Conduct Disorder.

    Science.gov (United States)

    Broulidakis, M John; Fairchild, Graeme; Sully, Kate; Blumensath, Thomas; Darekar, Angela; Sonuga-Barke, Edmund J S

    2016-09-01

    Conduct disorder (CD) is characterized by impulsive, aggressive, and antisocial behaviors that might be related to deficits in empathy and moral reasoning. The brain's default mode network (DMN) has been implicated in self-referential cognitive processes of this kind. This study examined connectivity between key nodes of the DMN in 29 adolescent boys with CD and 29 age- and sex-matched typically developing adolescent boys. The authors ensured that group differences in DMN connectivity were not explained by comorbidity with other disorders by systematically controlling for the effects of substance use disorders (SUDs), attention-deficit/hyperactivity disorder (ADHD) symptoms, psychopathic traits, and other common mental health problems. Only after adjusting for co-occurring ADHD symptoms, the group with CD showed hypoconnectivity between core DMN regions compared with typically developing controls. ADHD symptoms were associated with DMN hyperconnectivity. There was no effect of psychopathic traits on DMN connectivity in the group with CD, and the key results were unchanged when controlling for SUDs and other common mental health problems. Future research should directly investigate the possibility that the aberrant DMN connectivity observed in the present study contributes to CD-related deficits in empathy and moral reasoning and examine self-referential cognitive processes in CD more generally. Copyright © 2016 American Academy of Child and Adolescent Psychiatry. All rights reserved.

  4. Aberrant cerebellar connectivity in motor and association networks in schizophrenia

    Directory of Open Access Journals (Sweden)

    Ann K. Shinn

    2015-03-01

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

  5. Are we connected? : Ports in Global Networks

    NARCIS (Netherlands)

    R.A. Zuidwijk (Rob)

    2015-01-01

    markdownabstractAbstract Global supply chains are built on organizational, information, and logistics networks. Ports are connected via these networks and also need to connect these networks. Synchromodality is an innovative concept for container transportation, and the port plays an important

  6. Nonrandom network connectivity comes in pairs

    Directory of Open Access Journals (Sweden)

    Felix Z. Hoffmann

    2017-02-01

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

  7. Connection between adiabaticity and the mirror mode

    International Nuclear Information System (INIS)

    Cohen, R.H.

    1976-01-01

    The size of magnetic moment jumps of a particle in a long, thin equilibrium magnetic mirror field is shown to be related to the complex zeroes of the mirror mode parameter B + 4πdP/sub perpendicular//dB. A consequence is that adiabaticity places a lower limit on β than does the mirror mode

  8. Switch-connected HyperX network

    Science.gov (United States)

    Chen, Dong; Heidelberger, Philip

    2018-02-13

    A network system includes a plurality of sub-network planes and global switches. The sub-network planes have a same network topology as each other. Each of the sub-network planes includes edge switches. Each of the edge switches has N ports. Each of the global switches is configured to connect a group of edge switches at a same location in the sub-network planes. In each of the sub-network planes, some of the N ports of each of the edge switches are connected to end nodes, and others of the N ports are connected to other edge switches in the same sub-network plane, other of the N ports are connected to at least one of the global switches.

  9. Leadership Networking Connect, Collaborate, Create

    CERN Document Server

    (CCL), Center for Creative Leadership; Baldwin, David

    2011-01-01

    Networking is essential to effective leadership in today's organizations. Leaders who are skilled networkers have access to people, information, and resources to help solve problems and create opportunities. Leaders who neglect their networks are missing out on a critical component of their role as leaders. This book will help leaders take a new view of networking and provide insight into how to enhance their networks and become effective at leadership networking.

  10. Synchronization from second order network connectivity statistics

    Directory of Open Access Journals (Sweden)

    Liqiong eZhao

    2011-07-01

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

  11. Emotional faces and the default mode network.

    Science.gov (United States)

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

    2012-01-11

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

  12. Visualizing neuronal network connectivity with connectivity pattern tables

    Directory of Open Access Journals (Sweden)

    Eilen Nordlie

    2010-01-01

    Full Text Available Complex ideas are best conveyed through well-designed illustrations. Up to now, computational neuroscientists have mostly relied on box-and-arrow diagrams of even complex neuronal networks, often using ad hoc notations with conflicting use of symbols from paper to paper. This significantly impedes the communication of ideas in neuronal network modeling. We present here Connectivity Pattern Tables (CPTs as a clutter-free visualization of connectivity in large neuronal networks containing two-dimensional populations of neurons. CPTs can be generated automatically from the same script code used to create the actual network in the NEST simulator. Through aggregation, CPTs can be viewed at different levels, providing either full detail or summary information. We also provide the open source ConnPlotter tool as a means to create connectivity pattern tables.

  13. Altered Functional Connectivity of the Default Mode Network in Patients With Schizo-obsessive Comorbidity: A Comparison Between Schizophrenia and Obsessive-compulsive Disorder

    DEFF Research Database (Denmark)

    Wang, Yongming; Zou, Lai-quan; Xie, Wen-lan

    2018-01-01

    increased rsFC between subregions of the DMN and the middle temporal gyrus, but the OCD group exhibited decreased rsFC between them. These findings highlight a specific alteration in functional connectivity in the DMN in patients with SOC, and provide new insights into the dysfunctional brain organization...

  14. Electrophysiological signatures of atypical intrinsic brain connectivity networks in autism

    Science.gov (United States)

    Shou, Guofa; Mosconi, Matthew W.; Wang, Jun; Ethridge, Lauren E.; Sweeney, John A.; Ding, Lei

    2017-08-01

    Objective. Abnormal local and long-range brain connectivity have been widely reported in autism spectrum disorder (ASD), yet the nature of these abnormalities and their functional relevance at distinct cortical rhythms remains unknown. Investigations of intrinsic connectivity networks (ICNs) and their coherence across whole brain networks hold promise for determining whether patterns of functional connectivity abnormalities vary across frequencies and networks in ASD. In the present study, we aimed to probe atypical intrinsic brain connectivity networks in ASD from resting-state electroencephalography (EEG) data via characterizing the whole brain network. Approach. Connectivity within individual ICNs (measured by spectral power) and between ICNs (measured by coherence) were examined at four canonical frequency bands via a time-frequency independent component analysis on high-density EEG, which were recorded from 20 ASD and 20 typical developing (TD) subjects during an eyes-closed resting state. Main results. Among twelve identified electrophysiological ICNs, individuals with ASD showed hyper-connectivity in individual ICNs and hypo-connectivity between ICNs. Functional connectivity alterations in ASD were more severe in the frontal lobe and the default mode network (DMN) and at low frequency bands. These functional connectivity measures also showed abnormal age-related associations in ICNs related to frontal, temporal and motor regions in ASD. Significance. Our findings suggest that ASD is characterized by the opposite directions of abnormalities (i.e. hypo- and hyper-connectivity) in the hierarchical structure of the whole brain network, with more impairments in the frontal lobe and the DMN at low frequency bands, which are critical for top-down control of sensory systems, as well as for both cognition and social skills.

  15. Intrinsic network connectivity and own body perception in gender dysphoria.

    Science.gov (United States)

    Feusner, Jamie D; Lidström, Andreas; Moody, Teena D; Dhejne, Cecilia; Bookheimer, Susan Y; Savic, Ivanka

    2017-08-01

    Gender dysphoria (GD) is characterized by incongruence between one's identity and gender assigned at birth. The biological mechanisms of GD are unclear. We investigated brain network connectivity patterns involved in own body perception in the context of self in GD. Twenty-seven female-to-male (FtM) individuals with GD, 27 male controls, and 27 female controls underwent resting state fMRI. We compared functional connections within intrinsic connectivity networks involved in self-referential processes and own body perception -default mode network (DMN) and salience network - and visual networks, using independent components analyses. Behavioral correlates of network connectivity were also tested using self-perception ratings while viewing own body images morphed to their sex assigned at birth, and to the sex of their gender identity. FtM exhibited decreased connectivity of anterior and posterior cingulate and precuneus within the DMN compared with controls. In FtM, higher "self" ratings for bodies morphed towards the sex of their gender identity were associated with greater connectivity of the anterior cingulate within the DMN, during long viewing times. In controls, higher ratings for bodies morphed towards their gender assigned at birth were associated with right insula connectivity within the salience network, during short viewing times. Within visual networks FtM showed weaker connectivity in occipital and temporal regions. Results suggest disconnectivity within networks involved in own body perception in the context of self in GD. Moreover, perception of bodies in relation to self may be reflective rather than reflexive, as a function of mesial prefrontal processes. These may represent neurobiological correlates to the subjective disconnection between perception of body and self-identification.

  16. Synchronization from Second Order Network Connectivity Statistics

    Science.gov (United States)

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

    2011-01-01

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

  17. Low-stress bicycling and network connectivity.

    Science.gov (United States)

    2012-05-01

    For a bicycling network to attract the widest possible segment of the population, its most fundamental attribute should be low-stress connectivity, that is, providing routes between peoples origins and destinations that do not require cyclists to ...

  18. Ecological connectivity networks in rapidly expanding cities.

    Science.gov (United States)

    Nor, Amal Najihah M; Corstanje, Ron; Harris, Jim A; Grafius, Darren R; Siriwardena, Gavin M

    2017-06-01

    Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow ( Passer montanus ) and Yellow-vented bulbul ( Pycnonotus goiavier ) in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines). The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance) were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such models for

  19. Ecological connectivity networks in rapidly expanding cities

    Directory of Open Access Journals (Sweden)

    Amal Najihah M. Nor

    2017-06-01

    Full Text Available Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow (Passer montanus and Yellow-vented bulbul (Pycnonotus goiavier in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines. The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such

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

    Science.gov (United States)

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

    2018-05-01

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

  1. Teleoperation system using Asynchronous transfer mode, ATM network

    International Nuclear Information System (INIS)

    Mohd Dani Baba; A Nasoruddin Mohamad

    1999-01-01

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

  2. Lumped Mass Modeling for Local-Mode-Suppressed Element Connectivity

    DEFF Research Database (Denmark)

    Joung, Young Soo; Yoon, Gil Ho; Kim, Yoon Young

    2005-01-01

    connectivity parameterization (ECP) is employed. On the way to the ultimate crashworthy structure optimization, we are now developing a local mode-free topology optimization formulation that can be implemented in the ECP method. In fact, the local mode-freeing strategy developed here can be also used directly...... experiencing large structural changes, appears to be still poor. In ECP, the nodes of the domain-discretizing elements are connected by zero-length one-dimensional elastic links having varying stiffness. For computational efficiency, every elastic link is now assumed to have two lumped masses at its ends....... Choosing appropriate penalization functions for lumped mass and link stiffness is important for local mode-free results. However, unless the objective and constraint functions are carefully selected, it is difficult to obtain clear black-and-white results. It is shown that the present formulation is also...

  3. Connecting Network Properties of Rapidly Disseminating Epizoonotics

    Science.gov (United States)

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

    2012-01-01

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

  4. Connecting Mobile Users Through Mobile Social Networks

    Directory of Open Access Journals (Sweden)

    Faisal Alkhateeb

    2012-10-01

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

  5. Connectivity, topology and dynamics in climate networks

    Czech Academy of Sciences Publication Activity Database

    Paluš, Milan; Hartman, David; Hlinka, Jaroslav; Vejmelka, Martin

    2012-01-01

    Roč. 14, - (2012), s. 8397 ISSN 1607-7962. [European Geosciences Union General Assembly 2012. 22.04.2012-27.04.2012, Vienna] R&D Projects: GA ČR GCP103/11/J068 Institutional support: RVO:67985807 Keywords : complex networks * climate network * connectivity * entropy rate * El Nino Southern Oscillation * North Atlantic Oscillation Subject RIV: BB - Applied Statistics, Operational Research

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

    Science.gov (United States)

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

    2018-04-01

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

  7. Default-mode-like network activation in awake rodents.

    Directory of Open Access Journals (Sweden)

    Jaymin Upadhyay

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

  8. Women’s connectivity in extreme networks

    Science.gov (United States)

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

    2016-01-01

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

  9. Discerning connectivity from dynamics in climate networks

    Czech Academy of Sciences Publication Activity Database

    Paluš, Milan; Hartman, David; Hlinka, Jaroslav; Vejmelka, Martin

    2011-01-01

    Roč. 18, č. 5 (2011), s. 751-763 ISSN 1023-5809 R&D Projects: GA ČR GCP103/11/J068 Institutional research plan: CEZ:AV0Z10300504 Keywords : complex networks * climate dynamics * connectivity * North Atlantic Oscillation * solar activity Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.597, year: 2011

  10. Network structure shapes spontaneous functional connectivity dynamics.

    Science.gov (United States)

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

    2015-04-08

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

  11. Asymmetric network connectivity using weighted harmonic averages

    Science.gov (United States)

    Morrison, Greg; Mahadevan, L.

    2011-02-01

    We propose a non-metric measure of the "closeness" felt between two nodes in an undirected, weighted graph using a simple weighted harmonic average of connectivity, that is a real-valued Generalized Erdös Number (GEN). While our measure is developed with a collaborative network in mind, the approach can be of use in a variety of artificial and real-world networks. We are able to distinguish between network topologies that standard distance metrics view as identical, and use our measure to study some simple analytically tractable networks. We show how this might be used to look at asymmetry in authorship networks such as those that inspired the integer Erdös numbers in mathematical coauthorships. We also show the utility of our approach to devise a ratings scheme that we apply to the data from the NetFlix prize, and find a significant improvement using our method over a baseline.

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

    Science.gov (United States)

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

    2011-05-15

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

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

    Directory of Open Access Journals (Sweden)

    Li Liu

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

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

    Science.gov (United States)

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

    2018-08-01

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

  15. Improved H-mode access in connected DND in MAST

    International Nuclear Information System (INIS)

    Meyer, H; Carolan, P G; Conway, N J; Counsell, G F; Cunningham, G; Field, A R; Kirk, A; McClements, K G; Price, M; Taylor, D

    2005-01-01

    In the Mega-Amp Spherical Tokamak, MAST, the formation of the edge transport barrier leading to the high-confinement (H-mode) regime is greatly facilitated by operating in a double null diverted (DND) configuration where both X-points are practically on the same flux surface. Ohmic H-modes are presently only obtained in these connected double null diverted (CDND) configurations. The ease of H-mode access is lost if the two flux surfaces passing through the X-points are radially separated by more than one ion Larmor radius (ρ i ∼ 6 mm) at the low-field-side mid-plane. The change of the magnetic configuration from disconnected to CDND is accompanied by a change in the radial electric field of about ΔE ψ ∼ -1 kV m -1 and a reduction of the electron temperature decay length in the high-field-side scrape-off-layer. Other parameters at the plasma edge, in particular those affecting the H-mode access criteria of common L/H transition theories, are not affected by the slight changes to the magnetic configuration. It is believed that the observed change in E ψ , which may result from differences in ion orbit losses, leads to a higher initial E x B flow shear in CDND configurations which could lead to the easier H-mode access

  16. Micro-generation network connection (renewables)

    Energy Technology Data Exchange (ETDEWEB)

    Thornycroft, J.; Russell, T.; Curran, J.

    2003-07-01

    The drive to reduce emissions of carbon dioxide will result in an increase in the number of small generation units seeking connection to the electric power distribution network. The objectives of this study were to consider connection issues relating to micro-generation from renewables and their integration into the UK distribution network. The document is divided into two sections. The first section describes the present system which includes input from micro-generation, the technical impacts and the financial considerations. The second part discusses technical, financial and governance options for the future. A summary of preferred options and recommendations is given. The study was carried out by the Halcrow Group Ltd under contract to the DTI.

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  18. Attention reorganizes connectivity across networks in a frequency specific manner

    DEFF Research Database (Denmark)

    Kwon, Soyoung; Watanabe, Masataka; Fischer, Elvira

    2017-01-01

    Attention allows our brain to focus its limited resources on a given task. It does so by selective modulation of neural activity and of functional connectivity (FC) across brain-wide networks. While there is extensive literature on activity changes, surprisingly few studies examined brain-wide FC...... modulations that can be cleanly attributed to attention compared to matched visual processing. In contrast to prior approaches, we used an ultra-long trial design that avoided transients from trial onsets, included slow fluctuations (...-segregated analyses. We found that FC derived from long blocks had a nearly two-fold higher gain compared to FC derived from traditional (short) block designs. Second, attention enhanced intrinsic (negative or positive) correlations across networks, such as between the default-mode network (DMN), the dorsal attention...

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

    Directory of Open Access Journals (Sweden)

    Cristina Solé-Padullés

    2016-02-01

    Full Text Available There is limited evidence on the effects of age and sex on intrinsic connectivity of networks underlying cognition during childhood and adolescence. Independent component analysis was conducted in 113 subjects aged 7–18; the default mode, executive control, anterior salience, basal ganglia, language and visuospatial networks were identified. The effect of age was examined with multiple regression, while sex and ‘age × sex’ interactions were assessed by dividing the sample according to age (7–12 and 13–18 years. As age increased, connectivity in the dorsal and ventral default mode network became more anterior and posterior, respectively, while in the executive control network, connectivity increased within frontoparietal regions. The basal ganglia network showed increased engagement of striatum, thalami and precuneus. The anterior salience network showed greater connectivity in frontal areas and anterior cingulate, and less connectivity of orbitofrontal, middle cingulate and temporoparietal regions. The language network presented increased connectivity of inferior frontal and decreased connectivity within the right middle frontal and left inferior parietal cortices. The visuospatial network showed greater engagement of inferior parietal and frontal cortices. No effect of sex, nor age by sex interactions was observed. These findings provide evidence of strengthening of cortico-cortical and cortico-subcortical networks across childhood and adolescence.

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

    Science.gov (United States)

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

    2016-04-01

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

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

    Science.gov (United States)

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

    2015-08-01

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

  2. Prioritizing connection requests in GMPLS-controlled optical networks

    DEFF Research Database (Denmark)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

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

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

  6. Social network models predict movement and connectivity in ecological landscapes

    Science.gov (United States)

    Fletcher, Robert J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.

    2011-01-01

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  7. Social network models predict movement and connectivity in ecological landscapes.

    Science.gov (United States)

    Fletcher, Robert J; Acevedo, Miguel A; Reichert, Brian E; Pias, Kyle E; Kitchens, Wiley M

    2011-11-29

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  8. Aberrant default-mode functional and structural connectivity in heroin-dependent individuals.

    Directory of Open Access Journals (Sweden)

    Xiaofen Ma

    Full Text Available Little is known about connectivity within the default mode network (DMN in heroin-dependent individuals (HDIs. In the current study, diffusion-tensor imaging (DTI and resting-state functional MRI (rs-fMRI were combined to investigate both structural and functional connectivity within the DMN in HDIs.Fourteen HDIs and 14 controls participated in the study. Structural (path length, tracts count, (fractional anisotropy FA and (mean diffusivity MD derived from DTI tractographyand functional (temporal correlation coefficient derived from rs-fMRI DMN connectivity changes were examined in HDIs. Pearson correlation analysis was performed to compare the structural/functional indices and duration of heroin use/Iowa gambling task(IGT performance in HDIs.HDIs had lower FA and higher MD in the tract connecting the posterior cingulate cortex/precuneus (PCC/PCUN to right parahippocampal gyrus (PHG, compared to the controls. HDIs also had decreased FA and track count in the tract connecting the PCC/PCUN and medial prefrontal cortex (MPFC, as well as decreased functional connectivity between the PCC/PCUN and bilateral PHG and MPFC, compared to controls. FA values for the tract connecting PCC/PCUN to the right PHG and connecting PCC/PCUN to the MPFC were negatively correlated to the duration of heroin use. The temporal correlation coefficients between the PCC/PCUN and the MPFC, and the FA values for the tract connecting the PCC/PCUN to the MPFC were positively correlated to IGT performance in HDIs.Structural and functional connectivity within the DMN are both disturbed in HDIs. This disturbance progresses as duration of heroin use increases and is related to deficits in decision making in HDIs.

  9. Directed connectivity of brain default networks in resting state using GCA and motif.

    Science.gov (United States)

    Jiao, Zhuqing; Wang, Huan; Ma, Kai; Zou, Ling; Xiang, Jianbo

    2017-06-01

    Nowadays, there is a lot of interest in assessing functional interactions between key brain regions. In this paper, Granger causality analysis (GCA) and motif structure are adopted to study directed connectivity of brain default mode networks (DMNs) in resting state. Firstly, the time series of functional magnetic resonance imaging (fMRI) data in resting state were extracted, and the causal relationship values of the nodes representing related brain regions are analyzed in time domain to construct a default network. Then, the network structures were searched from the default networks of controls and patients to determine the fixed connection mode in the networks. The important degree of motif structures in directed connectivity of default networks was judged according to p-value and Z-score. Both node degree and average distance were used to analyze the effect degree an information transfer rate of brain regions in motifs and default networks, and efficiency of the network. Finally, activity and functional connectivity strength of the default brain regions are researched according to the change of energy distributions between the normals and the patients' brain regions. Experimental results demonstrate that, both normal subjects and stroke patients have some corresponding fixed connection mode of three nodes, and the efficiency and power spectrum of the patient's default network is somewhat lower than that of the normal person. In particular, the Right Posterior Cingulate Gyrus (PCG.R) has a larger change in functional connectivity and its activity. The research results verify the feasibility of the application of GCA and motif structure to study the functional connectivity of default networks in resting state.

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

    DEFF Research Database (Denmark)

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

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

  11. LORETA EEG phase reset of the default mode network.

    Science.gov (United States)

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

    2014-01-01

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

  12. Intermittent Theta-Burst Stimulation of the Lateral Cerebellum Increases Functional Connectivity of the Default Network

    Science.gov (United States)

    Farzan, Faranak; Eldaief, Mark C.; Schmahmann, Jeremy D.; Pascual-Leone, Alvaro

    2014-01-01

    Cerebral cortical intrinsic connectivity networks share topographically arranged functional connectivity with the cerebellum. However, the contribution of cerebellar nodes to distributed network organization and function remains poorly understood. In humans, we applied theta-burst transcranial magnetic stimulation, guided by subject-specific connectivity, to regions of the cerebellum to evaluate the functional relevance of connections between cerebellar and cerebral cortical nodes in different networks. We demonstrate that changing activity in the human lateral cerebellar Crus I/II modulates the cerebral default mode network, whereas vermal lobule VII stimulation influences the cerebral dorsal attention system. These results provide novel insights into the distributed, but anatomically specific, modulatory impact of cerebellar effects on large-scale neural network function. PMID:25186750

  13. Light Manipulation in Metallic Nanowire Networks with Functional Connectivity

    KAUST Repository

    Galinski, Henning

    2016-12-27

    Guided by ideas from complex systems, a new class of network metamaterials is introduced for light manipulation, which are based on the functional connectivity among heterogeneous subwavelength components arranged in complex networks. The model system is a nanonetwork formed by dealloying a metallic thin film. The connectivity of the network is deterministically controlled, enabling the formation of tunable absorbing states.

  14. Antidepressants normalize the default mode network in patients with dysthymia.

    Science.gov (United States)

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

    2013-04-01

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

  15. Modeling the interdependent network based on two-mode networks

    Science.gov (United States)

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

    2017-10-01

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

  16. Interactions between default mode and control networks as a function of increasing cognitive reasoning complexity.

    Science.gov (United States)

    Hearne, Luke; Cocchi, Luca; Zalesky, Andrew; Mattingley, Jason B

    2015-07-01

    Successful performance of challenging cognitive tasks depends on a consistent functional segregation of activity within the default-mode network, on the one hand, and control networks encompassing frontoparietal and cingulo-opercular areas on the other. Recent work, however, has suggested that in some cognitive control contexts nodes within the default-mode and control networks may actually cooperate to achieve optimal task performance. Here, we used functional magnetic resonance imaging to examine whether the ability to relate variables while solving a cognitive reasoning problem involves transient increases in connectivity between default-mode and control regions. Participants performed a modified version of the classic Wason selection task, in which the number of variables to be related is systematically varied across trials. As expected, areas within the default-mode network showed a parametric deactivation with increases in relational complexity, compared with neural activity in null trials. Critically, some of these areas also showed enhanced connectivity with task-positive control regions. Specifically, task-based connectivity between the striatum and the angular gyri, and between the thalamus and right temporal pole, increased as a function of relational complexity. These findings challenge the notion that functional segregation between regions within default-mode and control networks invariably support cognitive task performance, and reveal previously unknown roles for the striatum and thalamus in managing network dynamics during cognitive reasoning. © 2015 Wiley Periodicals, Inc.

  17. Towards Designing PLC Networks for Ubiquitous Connectivity in Enterprises

    OpenAIRE

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

    2016-01-01

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

  18. Multimodal Hyper-connectivity Networks for MCI Classification.

    Science.gov (United States)

    Li, Yang; Gao, Xinqiang; Jie, Biao; Yap, Pew-Thian; Kim, Min-Jeong; Wee, Chong-Yaw; Shen, Dinggang

    2017-09-01

    Hyper-connectivity network is a network where every edge is connected to more than two nodes, and can be naturally denoted using a hyper-graph. Hyper-connectivity brain network, either based on structural or functional interactions among the brain regions, has been used for brain disease diagnosis. However, the conventional hyper-connectivity network is constructed solely based on single modality data, ignoring potential complementary information conveyed by other modalities. The integration of complementary information from multiple modalities has been shown to provide a more comprehensive representation about the brain disruptions. In this paper, a novel multimodal hyper-network modelling method was proposed for improving the diagnostic accuracy of mild cognitive impairment (MCI). Specifically, we first constructed a multimodal hyper-connectivity network by simultaneously considering information from diffusion tensor imaging and resting-state functional magnetic resonance imaging data. We then extracted different types of network features from the hyper-connectivity network, and further exploited a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Our proposed multimodal hyper-connectivity network demonstrated a better MCI classification performance than the conventional single modality based hyper-connectivity networks.

  19. Light Manipulation in Metallic Nanowire Networks with Functional Connectivity

    KAUST Repository

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

    2016-01-01

    Guided by ideas from complex systems, a new class of network metamaterials is introduced for light manipulation, which are based on the functional connectivity among heterogeneous subwavelength components arranged in complex networks. The model

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

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

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

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

    Science.gov (United States)

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

    2009-12-01

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

  2. Resting-state functional connectivity of orthographic networks in acquired dysgraphia

    Directory of Open Access Journals (Sweden)

    Gali Ellenblum

    2015-05-01

    The NTA findings indicate that the relationship between orthographic and default-mode networks is characterized by greater within- vs. across-network connectivity. Furthermore, we show for the first time a pattern of increasing within/across network “coherence normalization” following spelling rehabilitation. Additional dysgraphic participants and other networks (language, sensory-motor, etc. will be analyzed to develop a better understanding of the RS orthographic network and its response to damage and recovery. Acknowledgements. The work is part of a multi-site, NIDCD-supported project examining language recovery neurobiology in aphasia (DC006740. We thank Melissa Greenberger and Xiao-Wei Song.

  3. Accelerated Distributed Dual Averaging Over Evolving Networks of Growing Connectivity

    Science.gov (United States)

    Liu, Sijia; Chen, Pin-Yu; Hero, Alfred O.

    2018-04-01

    We consider the problem of accelerating distributed optimization in multi-agent networks by sequentially adding edges. Specifically, we extend the distributed dual averaging (DDA) subgradient algorithm to evolving networks of growing connectivity and analyze the corresponding improvement in convergence rate. It is known that the convergence rate of DDA is influenced by the algebraic connectivity of the underlying network, where better connectivity leads to faster convergence. However, the impact of network topology design on the convergence rate of DDA has not been fully understood. In this paper, we begin by designing network topologies via edge selection and scheduling. For edge selection, we determine the best set of candidate edges that achieves the optimal tradeoff between the growth of network connectivity and the usage of network resources. The dynamics of network evolution is then incurred by edge scheduling. Further, we provide a tractable approach to analyze the improvement in the convergence rate of DDA induced by the growth of network connectivity. Our analysis reveals the connection between network topology design and the convergence rate of DDA, and provides quantitative evaluation of DDA acceleration for distributed optimization that is absent in the existing analysis. Lastly, numerical experiments show that DDA can be significantly accelerated using a sequence of well-designed networks, and our theoretical predictions are well matched to its empirical convergence behavior.

  4. Modeling and control of distributed energy systems during transition between grid connected and standalone modes

    Science.gov (United States)

    Arafat, Md Nayeem

    Distributed generation systems (DGs) have been penetrating into our energy networks with the advancement in the renewable energy sources and energy storage elements. These systems can operate in synchronism with the utility grid referred to as the grid connected (GC) mode of operation, or work independently, referred to as the standalone (SA) mode of operation. There is a need to ensure continuous power flow during transition between GC and SA modes, referred to as the transition mode, in operating DGs. In this dissertation, efficient and effective transition control algorithms are developed for DGs operating either independently or collectively with other units. Three techniques are proposed in this dissertation to manage the proper transition operations. In the first technique, a new control algorithm is proposed for an independent DG which can operate in SA and GC modes. The proposed transition control algorithm ensures low total harmonic distortion (THD) and less voltage fluctuation during mode transitions compared to the other techniques. In the second technique, a transition control is suggested for a collective of DGs operating in a microgrid system architecture to improve the reliability of the system, reduce the cost, and provide better performance. In this technique, one of the DGs in a microgrid system, referred to as a dispatch unit , takes the additional responsibility of mode transitioning to ensure smooth transition and supply/demand balance in the microgrid. In the third technique, an alternative transition technique is proposed through hybridizing the current and droop controllers. The proposed hybrid transition control technique has higher reliability compared to the dispatch unit concept. During the GC mode, the proposed hybrid controller uses current control. During the SA mode, the hybrid controller uses droop control. During the transition mode, both of the controllers participate in formulating the inverter output voltage but with different

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  6. Connected Dominating Set Based Topology Control in Wireless Sensor Networks

    Science.gov (United States)

    He, Jing

    2012-01-01

    Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…

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

    Science.gov (United States)

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

    2015-01-01

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

  8. Attractor neural networks with resource-efficient synaptic connectivity

    Science.gov (United States)

    Pehlevan, Cengiz; Sengupta, Anirvan

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

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

    OpenAIRE

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

    2014-01-01

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

  10. EEG PHASE RESET OF THE DEFAULT MODE NETWORK

    Directory of Open Access Journals (Sweden)

    Robert W. Thatcher

    2014-07-01

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

  11. Activating and inhibiting connections in biological network dynamics

    Directory of Open Access Journals (Sweden)

    Knight Rob

    2008-12-01

    Full Text Available Abstract Background Many studies of biochemical networks have analyzed network topology. Such work has suggested that specific types of network wiring may increase network robustness and therefore confer a selective advantage. However, knowledge of network topology does not allow one to predict network dynamical behavior – for example, whether deleting a protein from a signaling network would maintain the network's dynamical behavior, or induce oscillations or chaos. Results Here we report that the balance between activating and inhibiting connections is important in determining whether network dynamics reach steady state or oscillate. We use a simple dynamical model of a network of interacting genes or proteins. Using the model, we study random networks, networks selected for robust dynamics, and examples of biological network topologies. The fraction of activating connections influences whether the network dynamics reach steady state or oscillate. Conclusion The activating fraction may predispose a network to oscillate or reach steady state, and neutral evolution or selection of this parameter may affect the behavior of biological networks. This principle may unify the dynamics of a wide range of cellular networks. Reviewers Reviewed by Sergei Maslov, Eugene Koonin, and Yu (Brandon Xia (nominated by Mark Gerstein. For the full reviews, please go to the Reviewers' comments section.

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

    Science.gov (United States)

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

    2018-06-01

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

  13. Sensitivity of marine protected area network connectivity to atmospheric variability.

    Science.gov (United States)

    Fox, Alan D; Henry, Lea-Anne; Corne, David W; Roberts, J Murray

    2016-11-01

    International efforts are underway to establish well-connected systems of marine protected areas (MPAs) covering at least 10% of the ocean by 2020. But the nature and dynamics of ocean ecosystem connectivity are poorly understood, with unresolved effects of climate variability. We used 40-year runs of a particle tracking model to examine the sensitivity of an MPA network for habitat-forming cold-water corals in the northeast Atlantic to changes in larval dispersal driven by atmospheric cycles and larval behaviour. Trajectories of Lophelia pertusa larvae were strongly correlated to the North Atlantic Oscillation (NAO), the dominant pattern of interannual atmospheric circulation variability over the northeast Atlantic. Variability in trajectories significantly altered network connectivity and source-sink dynamics, with positive phase NAO conditions producing a well-connected but asymmetrical network connected from west to east. Negative phase NAO produced reduced connectivity, but notably some larvae tracked westward-flowing currents towards coral populations on the mid-Atlantic ridge. Graph theoretical metrics demonstrate critical roles played by seamounts and offshore banks in larval supply and maintaining connectivity across the network. Larval longevity and behaviour mediated dispersal and connectivity, with shorter lived and passive larvae associated with reduced connectivity. We conclude that the existing MPA network is vulnerable to atmospheric-driven changes in ocean circulation.

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

    Science.gov (United States)

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

    2017-10-01

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

  15. Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

    Science.gov (United States)

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

    2016-01-01

    Recent work has demonstrated that human whole-brain functional connectivity patterns measured with fMRI contain information about cognitive abilities, including sustained attention. To derive behavioral predictions from connectivity patterns, our group developed a connectome-based predictive modeling (CPM) approach (Finn et al., 2015; Rosenberg et al., 2016). Previously using CPM, we defined a high-attention network, comprising connections positively correlated with performance on a sustained attention task, and a low-attention network, comprising connections negatively correlated with performance. Validating the networks as generalizable biomarkers of attention, models based on network strength at rest predicted attention-deficit/hyperactivity disorder (ADHD) symptoms in an independent group of individuals (Rosenberg et al., 2016). To investigate whether these networks play a causal role in attention, here we examined their strength in healthy adults given methylphenidate (Ritalin), a common ADHD treatment, compared with unmedicated controls. As predicted, individuals given methylphenidate showed patterns of connectivity associated with better sustained attention: higher high-attention and lower low-attention network strength than controls. There was significant overlap between the high-attention network and a network with greater strength in the methylphenidate group, and between the low-attention network and a network with greater strength in the control group. Network strength also predicted behavior on a stop-signal task, such that participants with higher go response rates showed higher high-attention and lower low-attention network strength. These results suggest that methylphenidate acts by modulating functional brain networks related to sustained attention, and that changing whole-brain connectivity patterns may help improve attention. SIGNIFICANCE STATEMENT Recent work identified a promising neuromarker of sustained attention based on whole

  16. Pramipexole Modulates Interregional Connectivity Within the Sensorimotor Network.

    Science.gov (United States)

    Ye, Zheng; Hammer, Anke; Münte, Thomas F

    2017-05-01

    Pramipexole is widely prescribed to treat Parkinson's disease but has been reported to cause impulse control disorders such as pathological gambling. Recent neurocomputational models suggested that D2 agonists may distort functional connections between the striatum and the motor cortex, resulting in impaired reinforcement learning and pathological gambling. To examine how D2 agonists modulate the striatal-motor connectivity, we carried out a pharmacological resting-state functional magnetic resonance imaging study with a double-blind randomized within-subject crossover design. We analyzed the medication-induced changes of network connectivity and topology with two approaches, an independent component analysis (ICA) and a graph theoretical analysis (GTA). The ICA identified the sensorimotor network (SMN) as well as other classical resting-state networks. Within the SMN, the connectivity between the right caudate nucleus and other cortical regions was weaker under pramipexole than under placebo. The GTA measured the topological properties of the whole-brain network at global and regional levels. Both the whole-brain network under placebo and that under pramipexole were identified as small-world networks. The two whole-brain networks were similar in global efficiency, clustering coefficient, small-world index, and modularity. However, the degree of the right caudate nucleus decreased under pramipexole mainly due to the loss of the connectivity with the supplementary motor area, paracentral lobule, and precentral and postcentral gyrus of the SMN. The two network analyses consistently revealed that pramipexole weakened the functional connectivity between the caudate nucleus and the SMN regions.

  17. Selectivity and sparseness in randomly connected balanced networks.

    Directory of Open Access Journals (Sweden)

    Cengiz Pehlevan

    Full Text Available Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected. This raises the question whether selectivity and sparseness can be generated and maintained in randomly connected networks. We consider a recurrent network of excitatory and inhibitory spiking neurons with random connectivity, driven by random projections from an input layer of stimulus selective neurons. In this architecture, the stimulus-to-stimulus and neuron-to-neuron modulation of total synaptic input is weak compared to the mean input. Surprisingly, we show that in the balanced state the network can still support high stimulus selectivity and sparse population response. In the balanced state, strong synapses amplify the variation in synaptic input and recurrent inhibition cancels the mean. Functional specificity in connectivity emerges due to the inhomogeneity caused by the generative statistical rule used to build the network. We further elucidate the mechanism behind and evaluate the effects of model parameters on population sparseness and stimulus selectivity. Network response to mixtures of stimuli is investigated. It is shown that a balanced state with unselective inhibition can be achieved with densely connected input to inhibitory population. Balanced networks exhibit the "paradoxical" effect: an increase in excitatory drive to inhibition leads to decreased inhibitory population firing rate. We compare and contrast selectivity and sparseness generated by the balanced network to randomly connected unbalanced networks. Finally, we discuss our results in light of experiments.

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

    Science.gov (United States)

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

    2018-06-01

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

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

    Science.gov (United States)

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

    2018-04-01

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

  20. Stability of a giant connected component in a complex network

    Science.gov (United States)

    Kitsak, Maksim; Ganin, Alexander A.; Eisenberg, Daniel A.; Krapivsky, Pavel L.; Krioukov, Dmitri; Alderson, David L.; Linkov, Igor

    2018-01-01

    We analyze the stability of the network's giant connected component under impact of adverse events, which we model through the link percolation. Specifically, we quantify the extent to which the largest connected component of a network consists of the same nodes, regardless of the specific set of deactivated links. Our results are intuitive in the case of single-layered systems: the presence of large degree nodes in a single-layered network ensures both its robustness and stability. In contrast, we find that interdependent networks that are robust to adverse events have unstable connected components. Our results bring novel insights to the design of resilient network topologies and the reinforcement of existing networked systems.

  1. Connecting Land-Based Networks to Ships

    Science.gov (United States)

    2013-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Kim SM

    2015-12-01

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

  3. Hyper-connectivity of functional networks for brain disease diagnosis.

    Science.gov (United States)

    Jie, Biao; Wee, Chong-Yaw; Shen, Dinggang; Zhang, Daoqiang

    2016-08-01

    Exploring structural and functional interactions among various brain regions enables better understanding of pathological underpinnings of neurological disorders. Brain connectivity network, as a simplified representation of those structural and functional interactions, has been widely used for diagnosis and classification of neurodegenerative diseases, especially for Alzheimer's disease (AD) and its early stage - mild cognitive impairment (MCI). However, the conventional functional connectivity network is usually constructed based on the pairwise correlation among different brain regions and thus ignores their higher-order relationships. Such loss of high-order information could be important for disease diagnosis, since neurologically a brain region predominantly interacts with more than one other brain regions. Accordingly, in this paper, we propose a novel framework for estimating the hyper-connectivity network of brain functions and then use this hyper-network for brain disease diagnosis. Here, the functional connectivity hyper-network denotes a network where each of its edges representing the interactions among multiple brain regions (i.e., an edge can connect with more than two brain regions), which can be naturally represented by a hyper-graph. Specifically, we first construct connectivity hyper-networks from the resting-state fMRI (R-fMRI) time series by using sparse representation. Then, we extract three sets of brain-region specific features from the connectivity hyper-networks, and further exploit a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Finally, we use multi-kernel support vector machine (SVM) for classification. The experimental results on both MCI dataset and attention deficit hyperactivity disorder (ADHD) dataset demonstrate that, compared with the conventional connectivity network-based methods, the proposed method can not only improve the classification performance, but also help

  4. Default network connectivity during a working memory task.

    Science.gov (United States)

    Bluhm, Robyn L; Clark, C Richard; McFarlane, Alexander C; Moores, Kathryn A; Shaw, Marnie E; Lanius, Ruth A

    2011-07-01

    The default network exhibits correlated activity at rest and has shown decreased activation during performance of cognitive tasks. There has been little investigation of changes in connectivity of this network during task performance. In this study, we examined task-related modulation of connectivity between two seed regions from the default network posterior cingulated cortex (PCC) and medial prefrontal cortex (mPFC) and the rest of the brain in 12 healthy adults. The purpose was to determine (1) whether connectivity within the default network differs between a resting state and performance of a cognitive (working memory) task and (2) whether connectivity differs between these nodes of the default network and other brain regions, particularly those implicated in cognitive tasks. There was little change in connectivity with the other main areas of the default network for either seed region, but moderate task-related changes in connectivity occurred between seed regions and regions outside the default network. For example, connectivity of the mPFC with the right insula and the right superior frontal gyrus decreased during task performance. Increased connectivity during the working memory task occurred between the PCC and bilateral inferior frontal gyri, and between the mPFC and the left inferior frontal gyrus, cuneus, superior parietal lobule, middle temporal gyrus and cerebellum. Overall, the areas showing greater correlation with the default network seed regions during task than at rest have been previously implicated in working memory tasks. These changes may reflect a decrease in the negative correlations occurring between the default and task-positive networks at rest. Copyright © 2010 Wiley-Liss, Inc.

  5. Aberrant Resting-State Functional Connectivity in the Salience Network of Adolescent Chronic Fatigue Syndrome.

    Directory of Open Access Journals (Sweden)

    Laura Anne Wortinger

    Full Text Available Neural network investigations are currently absent in adolescent chronic fatigue syndrome (CFS. In this study, we examine whether the core intrinsic connectivity networks (ICNs are altered in adolescent CFS patients. Eighteen adolescent patients with CFS and 18 aged matched healthy adolescent control subjects underwent resting-state functional magnetic resonance imaging (rfMRI. Data was analyzed using dual-regression independent components analysis, which is a data-driven approach for the identification of independent brain networks. Intrinsic connectivity was evaluated in the default mode network (DMN, salience network (SN, and central executive network (CEN. Associations between network characteristics and symptoms of CFS were also explored. Adolescent CFS patients displayed a significant decrease in SN functional connectivity to the right posterior insula compared to healthy comparison participants, which was related to fatigue symptoms. Additionally, there was an association between pain intensity and SN functional connectivity to the left middle insula and caudate that differed between adolescent patients and healthy comparison participants. Our findings of insula dysfunction and its association with fatigue severity and pain intensity in adolescent CFS demonstrate an aberration of the salience network which might play a role in CFS pathophysiology.

  6. Decreased triple network connectivity in patients with post-traumatic stress disorder

    Science.gov (United States)

    Liu, Yang; Li, Liang; Li, Baojuan; Zhang, Xi; Lu, Hongbing

    2017-03-01

    The triple network model provides a common framework for understanding affective and neurocognitive dysfunctions across multiple disorders, including central executive network (CEN), default mode network (DMN), and salience network (SN). Considering the effect of traumatic experience on post-traumatic stress disorder (PTSD), this study aims to explore the alteration of triple network connectivity in a specific PTSD induced by a single prolonged trauma exposure. With arterial spin labeling sequence, three networks were identified using independent component analysis in 10 PTSD patients and 10 healthy survivors, who experienced the same coal mining flood disaster. In PTSD patients, decreased connectivity was identified in left middle frontal gyrus of CEN, left precuneus and bilateral superior frontal gyrus of DMN, and right anterior insula of SN. The decreased connectivity in left middle frontal gyrus was identified to associate with clinical severity. These results indicated the decreased triple network connectivity, which not only supported the proposal of the triple network model, but also prompted possible neurobiology mechanism of cognitive dysfunction for this kind of PTSD.

  7. Connecting to the Internet Securely; Protecting Home Networks CIAC-2324

    Energy Technology Data Exchange (ETDEWEB)

    Orvis, W J; Krystosek, P; Smith, J

    2002-11-27

    With more and more people working at home and connecting to company networks via the Internet, the risk to company networks to intrusion and theft of sensitive information is growing. Working from home has many positive advantages for both the home worker and the company they work for. However, as companies encourage people to work from home, they need to start considering the interaction of the employee's home network and the company network he connects to. This paper discusses problems and solutions related to protection of home computers from attacks on those computers via the network connection. It does not consider protection of those systems from people who have physical access to the computers nor does it consider company laptops taken on-the-road. Home networks are often targeted by intruders because they are plentiful and they are usually not well secured. While companies have departments of professionals to maintain and secure their networks, home networks are maintained by the employee who may be less knowledgeable about network security matters. The biggest problems with home networks are that: Home networks are not designed to be secure and may use technologies (wireless) that are not secure; The operating systems are not secured when they are installed; The operating systems and applications are not maintained (for security considerations) after they are installed; and The networks are often used for other activities that put them at risk for being compromised. Home networks that are going to be connected to company networks need to be cooperatively secured by the employee and the company so they do not open up the company network to intruders. Securing home networks involves many of the same operations as securing a company network: Patch and maintain systems; Securely configure systems; Eliminate unneeded services; Protect remote logins; Use good passwords; Use current antivirus software; and Moderate your Internet usage habits. Most of these

  8. Mode Choice Modeling Using Artificial Neural Networks

    OpenAIRE

    Edara, Praveen Kumar

    2003-01-01

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

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

    Science.gov (United States)

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

    2011-01-01

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

  10. The Connect Effect Building Strong Personal, Professional, and Virtual Networks

    CERN Document Server

    Dulworth, Michael

    2008-01-01

    Entrepreneur and executive development expert Mike Dulworth's THE CONNECT EFFECT provides readers with a simple framework and practical tools for developing that crucial competitive advantage: a high-quality personal, professional/organizational and virtual network.

  11. Connectivities and synchronous firing in cortical neuronal networks

    International Nuclear Information System (INIS)

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

    2004-01-01

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

  12. Social network of an internationally connected nurse leader.

    Science.gov (United States)

    Benton, David

    2016-03-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

  14. Aberrant functional connectivity of resting state networks in transient ischemic attack.

    Directory of Open Access Journals (Sweden)

    Rong Li

    Full Text Available BACKGROUND: Transient ischemic attack (TIA is usually defined as a neurologic ischemic disorder without permanent cerebral infarction. Studies have showed that patients with TIA can have lasting cognitive functional impairment. Inherent brain activity in the resting state is spatially organized in a set of specific coherent patterns named resting state networks (RSNs, which epitomize the functional architecture of memory, language, attention, visual, auditory and somato-motor networks. Here, we aimed to detect differences in RSNs between TIA patients and healthy controls (HCs. METHODS: Twenty one TIA patients suffered an ischemic event and 21 matched HCs were enrolled in the study. All subjects were investigated using cognitive tests, psychiatric tests and functional magnetic resonance imaging (fMRI. Independent component analysis (ICA was adopted to acquire the eight brain RSNs. Then one-sample t-tests were calculated in each group to gather the spatial maps of each RSNs, followed by second level analysis to investigate statistical differences on RSNs between twenty one TIA patients and 21 controls. Furthermore, a correlation analysis was performed to explore the relationship between functional connectivity (FC and cognitive and psychiatric scales in TIA group. RESULTS: Compared with the controls, TIA patients exhibited both decreased and increased functional connectivity in default mode network (DMN and self-referential network (SRN, and decreased functional connectivity in dorsal attention network (DAN, central-executive network (CEN, core network (CN, somato-motor network (SMN, visual network (VN and auditory network (AN. There was no correlation between neuropsychological scores and functional connectivity in regions of RSNs. CONCLUSIONS: We observed selective impairments of RSN intrinsic FC in TIA patients, whose all eight RSNs had aberrant functional connectivity. These changes indicate that TIA is a disease with widely abnormal brain

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

    Science.gov (United States)

    Tripp, Bryan P; Orchard, Jeff

    2012-01-01

    This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behavior. However, population coding theory has often ignored network structure, or assumed discrete, fully connected populations (in contrast with the sparsely connected, continuous sheet of the cortex). In this study, we modeled a sheet of cortical neurons with sparse, primarily local connections, and found that a network with this structure could encode multiple internal state variables with high signal-to-noise ratio. However, we were unable to create high-fidelity networks by instantiating connections at random according to spatial connection probabilities. In our models, high-fidelity networks required additional structure, with higher cluster factors and correlations between the inputs to nearby neurons.

  16. Default Mode Network Subsystems are Differentially Disrupted in Posttraumatic Stress Disorder.

    Science.gov (United States)

    Miller, Danielle R; Hayes, Scott M; Hayes, Jasmeet P; Spielberg, Jeffrey M; Lafleche, Ginette; Verfaellie, Mieke

    2017-05-01

    Posttraumatic stress disorder (PTSD) is a psychiatric disorder characterized by debilitating re-experiencing, avoidance, and hyperarousal symptoms following trauma exposure. Recent evidence suggests that individuals with PTSD show disrupted functional connectivity in the default mode network, an intrinsic network that consists of a midline core, a medial temporal lobe (MTL) subsystem, and a dorsomedial prefrontal cortex (dMPFC) subsystem. The present study examined whether functional connectivity in these subsystems is differentially disrupted in PTSD. Sixty-nine returning war Veterans with PTSD and 44 trauma-exposed Veterans without PTSD underwent resting state functional MRI (rs-fMRI). To examine functional connectivity, seeds were placed in the core hubs of the default mode network, namely the posterior cingulate cortex (PCC) and anterior medial PFC (aMPFC), and in each subsystem. Compared to controls, individuals with PTSD had reduced functional connectivity between the PCC and the hippocampus, a region of the MTL subsystem. Groups did not differ in connectivity between the PCC and dMPFC subsystem or between the aMPFC and any region within either subsystem. In the PTSD group, connectivity between the PCC and hippocampus was negatively associated with avoidance/numbing symptoms. Examination of the MTL and dMPFC subsystems revealed reduced anticorrelation between the ventromedial PFC (vMPFC) seed of the MTL subsystem and the dorsal anterior cingulate cortex in the PTSD group. Our results suggest that selective alterations in functional connectivity in the MTL subsystem of the default mode network in PTSD may be an important factor in PTSD pathology and symptomatology.

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

    Science.gov (United States)

    Belleau, Emily L.; Taubitz, Lauren E.

    2015-01-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2013-05-01

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

  20. Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

    OpenAIRE

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

    2016-01-01

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

  1. Networks with fourfold connectivity in two dimensions.

    Science.gov (United States)

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

    2003-01-01

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

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

    Science.gov (United States)

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

    2013-12-01

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

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

    Science.gov (United States)

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

    2018-02-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

  5. Dual connectivity for LTE-advanced heterogeneous networks

    DEFF Research Database (Denmark)

    Wang, Hua; Rosa, Claudio; Pedersen, Klaus I.

    2016-01-01

    Dual connectivity (DC) allows user equipments (UEs) to receive data simultaneously from different eNodeBs (eNBs) in order to boost the performance in a heterogeneous network with dedicated carrier deployment. Yet, how to efficiently operate with DC opens a number of research questions. In this pa......Dual connectivity (DC) allows user equipments (UEs) to receive data simultaneously from different eNodeBs (eNBs) in order to boost the performance in a heterogeneous network with dedicated carrier deployment. Yet, how to efficiently operate with DC opens a number of research questions...... aggregation (CA) and virtually zerolatency fronthaul connections, and in any case it is significantly higher compared to the case without DC. Keywords: Dual connectivity Heterogeneous network LTE-advanced Radio resource management Performance evaluation...

  6. Learning Control Over Emotion Networks Through Connectivity-Based Neurofeedback.

    Science.gov (United States)

    Koush, Yury; Meskaldji, Djalel-E; Pichon, Swann; Rey, Gwladys; Rieger, Sebastian W; Linden, David E J; Van De Ville, Dimitri; Vuilleumier, Patrik; Scharnowski, Frank

    2017-02-01

    Most mental functions are associated with dynamic interactions within functional brain networks. Thus, training individuals to alter functional brain networks might provide novel and powerful means to improve cognitive performance and emotions. Using a novel connectivity-neurofeedback approach based on functional magnetic resonance imaging (fMRI), we show for the first time that participants can learn to change functional brain networks. Specifically, we taught participants control over a key component of the emotion regulation network, in that they learned to increase top-down connectivity from the dorsomedial prefrontal cortex, which is involved in cognitive control, onto the amygdala, which is involved in emotion processing. After training, participants successfully self-regulated the top-down connectivity between these brain areas even without neurofeedback, and this was associated with concomitant increases in subjective valence ratings of emotional stimuli of the participants. Connectivity-based neurofeedback goes beyond previous neurofeedback approaches, which were limited to training localized activity within a brain region. It allows to noninvasively and nonpharmacologically change interconnected functional brain networks directly, thereby resulting in specific behavioral changes. Our results demonstrate that connectivity-based neurofeedback training of emotion regulation networks enhances emotion regulation capabilities. This approach can potentially lead to powerful therapeutic emotion regulation protocols for neuropsychiatric disorders. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  7. Structural Connectivity Networks of Transgender People

    NARCIS (Netherlands)

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

    2015-01-01

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

  8. Intrinsic connectivity networks within cerebellum and beyond in eating disorders.

    Science.gov (United States)

    Amianto, F; D'Agata, F; Lavagnino, L; Caroppo, P; Abbate-Daga, G; Righi, D; Scarone, S; Bergui, M; Mortara, P; Fassino, S

    2013-10-01

    Cerebellum seems to have a role both in feeding behavior and emotion regulation; therefore, it is a region that warrants further neuroimaging studies in eating disorders, severe conditions that determine a significant impairment in the physical and psychological domain. The aim of this study was to examine the cerebellum intrinsic connectivity during functional magnetic resonance imaging resting state in anorexia nervosa (AN), bulimia nervosa (BN), and healthy controls (CN). Resting state brain activity was decomposed into intrinsic connectivity networks (ICNs) using group spatial independent component analysis on the resting blood oxygenation level dependent time courses of 12 AN, 12 BN, and 10 CN. We extracted the cerebellar ICN and compared it between groups. Intrinsic connectivity within the cerebellar network showed some common alterations in eating disordered compared to healthy subjects (e.g., a greater connectivity with insulae, vermis, and paravermis and a lesser connectivity with parietal lobe); AN and BN patients were characterized by some peculiar alterations in connectivity patterns (e.g., greater connectivity with the insulae in AN compared to BN, greater connectivity with anterior cingulate cortex in BN compared to AN). Our data are consistent with the presence of different alterations in the cerebellar network in AN and BN patients that could be related to psychopathologic dimensions of eating disorders.

  9. Data for default network reduced functional connectivity in meditators, negatively correlated with meditation expertise

    Directory of Open Access Journals (Sweden)

    Aviva Berkovich-Ohana

    2016-09-01

    Full Text Available FMRI data described here was recorded during resting-state in Mindfulness Meditators (MM and control participants (see “Task-induced activity and resting-state fluctuations undergo similar alterations in visual and DMN areas of long-term meditators” Berkovich-Ohana et al. (2016 [1] for details. MM participants were also scanned during meditation. Analyses focused on functional connectivity within and between the default mode network (DMN and visual network (Vis. Here we show data demonstrating that: 1 Functional connectivity within the DMN and the Visual networks were higher in the control group than in the meditators; 2 Data show an increase for the functional connectivity between the DMN and the Visual networks in the meditators compared to controls; 3 Data demonstrate that functional connectivity both within and between networks reduces during meditation, compared to the resting-state; and 4 A significant negative correlation was found between DMN functional connectivity and meditation expertise. The reader is referred to Berkovich-Ohana et al. (2016 [1] for further interpretation and discussion.

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

    Science.gov (United States)

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

    2018-03-01

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

  11. On Connectivity of Wireless Sensor Networks with Directional Antennas

    Directory of Open Access Journals (Sweden)

    Qiu Wang

    2017-01-01

    Full Text Available In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models.

  12. Shifted intrinsic connectivity of central executive and salience network in borderline personality disorder

    Directory of Open Access Journals (Sweden)

    Anselm eDoll

    2013-10-01

    Full Text Available Borderline personality disorder (BPD is characterized by stable instability of emotions and behavior and their regulation. This emotional and behavioral instability corresponds with a neurocognitive triple network model of psychopathology, which suggests that aberrant emotional saliency and cognitive control is associated with aberrant interaction across three intrinsic connectivity networks (ICN (i.e. the salience, default mode, and central executive network, SN, DMN, CEN. The objective of the current study was to investigate whether and how such triple network intrinsic functional connectivity (iFC is changed in patients with BPD. We acquired resting-state functional magnetic resonance imaging (rs-fMRI data from fourteen patients with BPD and sixteen healthy controls (HC. High-model order independent component analysis (ICA was used to extract spatiotemporal patterns of ongoing, coherent blood-oxygen-level-dependent (BOLD signal fluctuations from rs-fMRI data. Main outcome measures were iFC within networks (intra-iFC and between networks (i.e. network time course correlation inter-iFC.Aberrant intra-iFC was found in patients’ DMN, SN, and CEN, consistent with previous findings. While patients’ inter-iFC of the CEN was decreased, inter-iFC of the SN was increased. In particular, a balance index reflecting the relationship of CEN-and SN-inter-iFC across networks was strongly shifted from CEN to SN connectivity in patients. Results provide first preliminary evidence for aberrant triple network intrinsic functional connectivity in BPD. Our data suggest a shift of inter-network iFC from networks involved in cognitive control to those of emotion-related activity in BPD, potentially reflecting the persistent instability of emotion regulation in patients.

  13. Connections between classical and parametric network entropies.

    Directory of Open Access Journals (Sweden)

    Matthias Dehmer

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

  14. Age Differences in the Intrinsic Functional Connectivity of Default Network Subsystems

    Directory of Open Access Journals (Sweden)

    Karen eCampbell

    2013-11-01

    Full Text Available Recent work suggests that the default mode network (DMN includes two core regions, the ventromedial prefrontal cortex (vmPFC and posterior cingulate cortex (PCC, and several unique subsystems that are functionally distinct. These include a medial temporal lobe (MTL subsystem, active during remembering and future projection, and a dorsomedial PFC (dmPFC subsystem, active during self-reference. The PCC has been further subdivided into ventral (vPCC and dorsal (dPCC regions that are more strongly connected with the DMN and cognitive control networks, respectively. The goal of this study was to examine age differences in resting state functional connectivity within these subsystems. After applying a rigorous procedure to reduce the effects of head motion, we used a multivariate technique to identify both common and unique patterns of functional connectivity in the MTL vs. the dmPFC, and in vPCC vs. dPCC. All four areas had robust functional connectivity with other DMN regions, and each also showed distinct connectivity patterns in both age groups. Young and older adults had equivalent functional connectivity in the MTL subsystem. Older adults showed weaker connectivity in the vPCC and dmPFC subsystems, particularly with other DMN areas, but stronger connectivity than younger adults in the dPCC subsystem, which included areas involved in cognitive control. Our data provide evidence for distinct subsystems involving DMN nodes, which are maintained with age. Nevertheless, there are age differences in the strength of functional connectivity within these subsystems, supporting prior evidence that DMN connectivity is particularly vulnerable to age, whereas connectivity involving cognitive control regions is relatively maintained. These results suggest an age difference in the integrated activity among brain networks that can have implications for cognition in older adults.

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

    Science.gov (United States)

    Rich, Scott; Zochowski, Michal; Booth, Victoria

    2018-01-01

    Acetylcholine (ACh), one of the brain's most potent neuromodulators, can affect intrinsic neuron properties through blockade of an M-type potassium current. The effect of ACh on excitatory and inhibitory cells with this potassium channel modulates their membrane excitability, which in turn affects their tendency to synchronize in networks. Here, we study the resulting changes in dynamics in networks with inter-connected excitatory and inhibitory populations (E-I networks), which are ubiquitous in the brain. Utilizing biophysical models of E-I networks, we analyze how the network connectivity structure in terms of synaptic connectivity alters the influence of ACh on the generation of synchronous excitatory bursting. We investigate networks containing all combinations of excitatory and inhibitory cells with high (Type I properties) or low (Type II properties) modulatory tone. To vary network connectivity structure, we focus on the effects of the strengths of inter-connections between excitatory and inhibitory cells (E-I synapses and I-E synapses), and the strengths of intra-connections among excitatory cells (E-E synapses) and among inhibitory cells (I-I synapses). We show that the presence of ACh may or may not affect the generation of network synchrony depending on the network connectivity. Specifically, strong network inter-connectivity induces synchronous excitatory bursting regardless of the cellular propensity for synchronization, which aligns with predictions of the PING model. However, when a network's intra-connectivity dominates its inter-connectivity, the propensity for synchrony of either inhibitory or excitatory cells can determine the generation of network-wide bursting.

  16. Fast long-range connections in transportation networks

    International Nuclear Information System (INIS)

    Palhares Viana, Matheus; Fontoura Costa, Luciano da

    2011-01-01

    Multidimensional scaling is applied in order to visualize an analogue of the small-world effect implied by edges having different displacement velocities in transportation networks. Our findings are illustrated for two real-world systems, namely the London urban network (streets and underground) and the US highway network enhanced by some of the main US airlines routes. We also show that the travel time in these two networks is drastically changed by attacks targeting the edges with large displacement velocities. - Highlights: → Multidimensional scaling used to visualize the effects of fast long-range connections. → Fast long-range connections are important to decrease the average travel time. → The average travel time diverges quickly when the network is under target attacks.

  17. Population Coding in Sparsely Connected Networks of Noisy Neurons

    Directory of Open Access Journals (Sweden)

    Bryan Patrick Tripp

    2012-05-01

    Full Text Available This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behaviour. However, population coding theory has often ignored network structure, or assumed discrete, fully-connected populations (in contrast with the sparsely connected, continuous sheet of the cortex. In this study, we model a sheet of cortical neurons with sparse, primarily local connections, and find that a network with this structure can encode multiple internal state variables with high signal-to-noise ratio. However, in our model, although connection probability varies with the distance between neurons, we find that the connections cannot be instantiated at random according to these probabilities, but must have additional structure if information is to be encoded with high fidelity.

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

    International Nuclear Information System (INIS)

    Pleym, Anngjerd; Mogstad, Olve

    2002-01-01

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

  19. Modulating Brain Connectivity by Simultaneous Dual-Mode Stimulation over Bilateral Primary Motor Cortices in Subacute Stroke Patients

    Directory of Open Access Journals (Sweden)

    Jungsoo Lee

    2018-01-01

    Full Text Available Repetitive transcranial magnetic stimulation (rTMS or transcranial direct current stimulation (tDCS has been used for the modulation of stroke patients’ motor function. Recently, more challenging approaches have been studied. In this study, simultaneous stimulation using both rTMS and tDCS (dual-mode stimulation over bilateral primary motor cortices (M1s was investigated to compare its modulatory effects with single rTMS stimulation over the ipsilesional M1 in subacute stroke patients. Twenty-four patients participated; 12 participants were assigned to the dual-mode stimulation group while the other 12 participants were assigned to the rTMS-only group. We assessed each patient’s motor function using the Fugl-Meyer assessment score and acquired their resting-state fMRI data at two times: prior to stimulation and 2 months after stimulation. Twelve healthy subjects were also recruited as the control group. The interhemispheric connectivity of the contralesional M1, interhemispheric connectivity between bilateral hemispheres, and global efficiency of the motor network noticeably increased in the dual-mode stimulation group compared to the rTMS-only group. Contrary to the dual-mode stimulation group, there was no significant change in the rTMS-only group. These data suggested that simultaneous dual-mode stimulation contributed to the recovery of interhemispheric interaction than rTMS only in subacute stroke patients. This trial is registered with NCT03279640.

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

    Science.gov (United States)

    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.

  1. Evidence for anomalous network connectivity during working memory encoding in schizophrenia: an ICA based analysis.

    Directory of Open Access Journals (Sweden)

    Shashwath A Meda

    2009-11-01

    Full Text Available Numerous neuroimaging studies report abnormal regional brain activity during working memory performance in schizophrenia, but few have examined brain network integration as determined by "functional connectivity" analyses.We used independent component analysis (ICA to identify and characterize dysfunctional spatiotemporal networks in schizophrenia engaged during the different stages (encoding and recognition of a Sternberg working memory fMRI paradigm. 37 chronic schizophrenia and 54 healthy age/gender-matched participants performed a modified Sternberg Item Recognition fMRI task. Time series images preprocessed with SPM2 were analyzed using ICA. Schizophrenia patients showed relatively less engagement of several distinct "normal" encoding-related working memory networks compared to controls. These encoding networks comprised 1 left posterior parietal-left dorsal/ventrolateral prefrontal cortex, cingulate, basal ganglia, 2 right posterior parietal, right dorsolateral prefrontal cortex and 3 default mode network. In addition, the left fronto-parietal network demonstrated a load-dependent functional response during encoding. Network engagement that differed between groups during recognition comprised the posterior cingulate, cuneus and hippocampus/parahippocampus. As expected, working memory task accuracy differed between groups (p<0.0001 and was associated with degree of network engagement. Functional connectivity within all three encoding-associated functional networks correlated significantly with task accuracy, which further underscores the relevance of abnormal network integration to well-described schizophrenia working memory impairment. No network was significantly associated with task accuracy during the recognition phase.This study extends the results of numerous previous schizophrenia studies that identified isolated dysfunctional brain regions by providing evidence of disrupted schizophrenia functional connectivity using ICA within

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

    Science.gov (United States)

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

    2013-01-28

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

  3. Spreading Sequence System for Full Connectivity Relay Network

    Science.gov (United States)

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

    2018-01-01

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

  4. Connectivity effects in the dynamic model of neural networks

    International Nuclear Information System (INIS)

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

    2009-01-01

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

  5. Wave speed in excitable random networks with spatially constrained connections.

    Directory of Open Access Journals (Sweden)

    Nikita Vladimirov

    Full Text Available Very fast oscillations (VFO in neocortex are widely observed before epileptic seizures, and there is growing evidence that they are caused by networks of pyramidal neurons connected by gap junctions between their axons. We are motivated by the spatio-temporal waves of activity recorded using electrocorticography (ECoG, and study the speed of activity propagation through a network of neurons axonally coupled by gap junctions. We simulate wave propagation by excitable cellular automata (CA on random (Erdös-Rényi networks of special type, with spatially constrained connections. From the cellular automaton model, we derive a mean field theory to predict wave propagation. The governing equation resolved by the Fisher-Kolmogorov PDE fails to describe wave speed. A new (hyperbolic PDE is suggested, which provides adequate wave speed v( that saturates with network degree , in agreement with intuitive expectations and CA simulations. We further show that the maximum length of connection is a much better predictor of the wave speed than the mean length. When tested in networks with various degree distributions, wave speeds are found to strongly depend on the ratio of network moments / rather than on mean degree , which is explained by general network theory. The wave speeds are strikingly similar in a diverse set of networks, including regular, Poisson, exponential and power law distributions, supporting our theory for various network topologies. Our results suggest practical predictions for networks of electrically coupled neurons, and our mean field method can be readily applied for a wide class of similar problems, such as spread of epidemics through spatial networks.

  6. Preclinical cerebral network connectivity evidence of deficits in mild white matter lesions

    Directory of Open Access Journals (Sweden)

    Ying eLiang

    2016-02-01

    Full Text Available White matter lesions (WMLs are notable for their high prevalence and have been demonstrated to be a potential neuroimaging biomarker of early diagnosis of Alzheimer’s disease. This study aimed to identify the brain functional and structural mechanisms underlying cognitive decline observed in mild WMLs. Multi-domain cognitive tests, as well as resting-state, diffusion tensor and structural images were obtained on 42 mild WMLs and 42 age/sex-matched healthy controls. For each participant, we examined the functional connectivity of three resting-state networks related to the changed cognitive domains: the default mode network (DMN and the bilateral fronto-parietal network (FPN. We also performed voxel-based morphometry analysis to compare whole-brain gray matter volume, atlas-based quantification of the white matter tracts interconnecting the RSNs, and the relationship between functional connectivity and structural connectivity. We observed functional connectivity alterations in the DMN and the right FPN combined with related white matter integrity disruption in mild WMLs. However, no significant gray matter atrophy difference was found. Furthermore, the right precuneus functional connectivity in the DMN exhibited a significantly negative correlation with the memory test scores. Our study suggests that in mild WMLs, dysfunction of RSNs might be a consequence of decreased white matter structural connectivity, which further affects cognitive performance.

  7. Network value and optimum analysis on the mode of networked marketing in TV media

    Directory of Open Access Journals (Sweden)

    Xiao Dongpo

    2012-12-01

    Full Text Available Purpose: With the development of the networked marketing in TV media, it is important to do the research on network value and optimum analysis in this field.Design/methodology/approach: According to the research on the mode of networked marketing in TV media and Correlation theory, the essence of media marketing is creating, spreading and transferring values. The Participants of marketing value activities are in network, and value activities proceed in networked form. Network capability is important to TV media marketing activities.Findings: This article raises the direction of research of analysis and optimization about network based on the mode of networked marketing in TV media by studying TV media marketing Development Mechanism , network analysis and network value structure.

  8. Flexible modulation of network connectivity related to cognition in Alzheimer’s disease

    Science.gov (United States)

    McLaren, Donald G.; Sperling, Reisa A.; Atria, Alireza

    2014-01-01

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

  9. Periodic Hydraulic Testing for Discerning Fracture Network Connections

    Science.gov (United States)

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

    2015-12-01

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

  10. Chaotic Modes in Scale Free Opinion Networks

    Science.gov (United States)

    Kusmartsev, Feo V.; Kürten, Karl E.

    2010-12-01

    In this paper, we investigate processes associated with formation of public opinion in varies directed random, scale free and small-world social networks. The important factor of the opinion formation is the existence of contrarians which were discovered by Granovetter in various social psychology experiments1,2,3 long ago and later introduced in sociophysics by Galam.4 When the density of contrarians increases the system behavior drastically changes at some critical value. At high density of contrarians the system can never arrive to a consensus state and periodically oscillates with different periods depending on specific structure of the network. At small density of the contrarians the behavior is manifold. It depends primary on the initial state of the system. If initially the majority of the population agrees with each other a state of stable majority may be easily reached. However when originally the population is divided in nearly equal parts consensus can never be reached. We model the emergence of collective decision making by considering N interacting agents, whose opinions are described by two state Ising spin variable associated with YES and NO. We show that the dynamical behaviors are very sensitive not only to the density of the contrarians but also to the network topology. We find that a phase of social chaos may arise in various dynamical processes of opinion formation in many realistic models. We compare the prediction of the theory with data describing the dynamics of the average opinion of the USA population collected on a day-by-day basis by varies media sources during the last six month before the final Obama-McCain election. The qualitative ouctome is in reasonable agreement with the prediction of our theory. In fact, the analyses of these data made within the paradigm of our theory indicates that even in this campaign there were chaotic elements where the public opinion migrated in an unpredictable chaotic way. The existence of such a phase

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

    Science.gov (United States)

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

    2013-11-12

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

  12. Population coding in sparsely connected networks of noisy neurons

    OpenAIRE

    Tripp, Bryan P.; Orchard, Jeff

    2012-01-01

    This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and be...

  13. Coverage and Connectivity Issue in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Rachit Trivedi

    2013-04-01

    Full Text Available Wireless sensor networks (WSNs are an emerging area of interest in research and development. It finds use in military surveillance, health care, environmental monitoring, forest fire detection and smart environments. An important research issue in WSNs is the coverage since cost, area and lifetime are directly validated to it.In this paper we present an overview of WSNs and try to refine the coverage and connectivity issues in wireless sensor networks.

  14. Functional Connectivity with Distinct Neural Networks Tracks Fluctuations in Gain/Loss Framing Susceptibility

    Science.gov (United States)

    Smith, David V.; Sip, Kamila E.; Delgado, Mauricio R.

    2016-01-01

    Multiple large-scale neural networks orchestrate a wide range of cognitive processes. For example, interoceptive processes related to self-referential thinking have been linked to the default-mode network (DMN); whereas exteroceptive processes related to cognitive control have been linked to the executive-control network (ECN). Although the DMN and ECN have been postulated to exert opposing effects on cognition, it remains unclear how connectivity with these spatially overlapping networks contribute to fluctuations in behavior. While previous work has suggested the medial prefrontal cortex (MPFC) is involved in behavioral change following feedback, these observations could be linked to interoceptive processes tied to DMN or exteroceptive processes tied to ECN because MPFC is positioned in both networks. To address this problem, we employed independent component analysis combined with dual-regression functional connectivity analysis. Participants made a series of financial decisions framed as monetary gains or losses. In some sessions, participants received feedback from a peer observing their choices; in other sessions, feedback was not provided. Following feedback, framing susceptibility—indexed as the increase in gambling behavior in loss frames compared to gain frames—was heightened in some participants and diminished in others. We examined whether these individual differences were linked to differences in connectivity by contrasting sessions containing feedback against those that did not contain feedback. We found two key results. As framing susceptibility increased, the MPFC increased connectivity with DMN; in contrast, temporal-parietal junction decreased connectivity with the ECN. Our results highlight how functional connectivity patterns with distinct neural networks contribute to idiosyncratic behavioral changes. PMID:25858445

  15. Diffusion Tensor Imaging Tractography Reveals Disrupted White Matter Structural Connectivity Network in Healthy Adults with Insomnia Symptoms

    Directory of Open Access Journals (Sweden)

    Feng-Mei Lu

    2017-11-01

    Full Text Available Neuroimaging studies have revealed that insomnia is characterized by aberrant neuronal connectivity in specific brain regions, but the topological disruptions in the white matter (WM structural connectivity networks remain largely unknown in insomnia. The current study uses diffusion tensor imaging (DTI tractography to construct the WM structural networks and graph theory analysis to detect alterations of the brain structural networks. The study participants comprised 30 healthy subjects with insomnia symptoms (IS and 62 healthy subjects without IS. Both the two groups showed small-world properties regarding their WM structural connectivity networks. By contrast, increased local efficiency and decreased global efficiency were identified in the IS group, indicating an insomnia-related shift in topology away from regular networks. In addition, the IS group exhibited disrupted nodal topological characteristics in regions involving the fronto-limbic and the default-mode systems. To our knowledge, this is the first study to explore the topological organization of WM structural network connectivity in insomnia. More importantly, the dysfunctions of large-scale brain systems including the fronto-limbic pathways, salience network and default-mode network in insomnia were identified, which provides new insights into the insomnia connectome. Topology-based brain network analysis thus could be a potential biomarker for IS.

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

    Science.gov (United States)

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

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

  17. Connectivity, excitability and activity patterns in neuronal networks

    International Nuclear Information System (INIS)

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

    2014-01-01

    Extremely synchronized firing patterns such as those observed in brain diseases like epilepsy may result from excessive network excitability. Although network excitability is closely related to (excitatory) connectivity, a direct measure for network excitability remains unavailable. Several methods currently exist for estimating network connectivity, most of which are related to cross-correlation. An example is the conditional firing probability (CFP) analysis which calculates the pairwise probability (CFP i,j ) that electrode j records an action potential at time t = τ, given that electrode i recorded a spike at t = 0. However, electrode i often records multiple spikes within the analysis interval, and CFP values are biased by the on-going dynamic state of the network. Here we show that in a linear approximation this bias may be removed by deconvoluting CFP i,j with the autocorrelation of i (i.e. CFP i,i ), to obtain the single pulse response (SPR i,j )—the average response at electrode j to a single spike at electrode i. Thus, in a linear system SPRs would be independent of the dynamic network state. Nonlinear components of synaptic transmission, such as facilitation and short term depression, will however still affect SPRs. Therefore SPRs provide a clean measure of network excitability. We used carbachol and ghrelin to moderately activate cultured cortical networks to affect their dynamic state. Both neuromodulators transformed the bursting firing patterns of the isolated networks into more dispersed firing. We show that the influence of the dynamic state on SPRs is much smaller than the effect on CFPs, but not zero. The remaining difference reflects the alteration in network excitability. We conclude that SPRs are less contaminated by the dynamic network state and that mild excitation may decrease network excitability, possibly through short term synaptic depression. (papers)

  18. Functional connectivity within and between intrinsic brain networks correlates with trait mind wandering.

    Science.gov (United States)

    Godwin, Christine A; Hunter, Michael A; Bezdek, Matthew A; Lieberman, Gregory; Elkin-Frankston, Seth; Romero, Victoria L; Witkiewitz, Katie; Clark, Vincent P; Schumacher, Eric H

    2017-08-01

    Individual differences across a variety of cognitive processes are functionally associated with individual differences in intrinsic networks such as the default mode network (DMN). The extent to which these networks correlate or anticorrelate has been associated with performance in a variety of circumstances. Despite the established role of the DMN in mind wandering processes, little research has investigated how large-scale brain networks at rest relate to mind wandering tendencies outside the laboratory. Here we examine the extent to which the DMN, along with the dorsal attention network (DAN) and frontoparietal control network (FPCN) correlate with the tendency to mind wander in daily life. Participants completed the Mind Wandering Questionnaire and a 5-min resting state fMRI scan. In addition, participants completed measures of executive function, fluid intelligence, and creativity. We observed significant positive correlations between trait mind wandering and 1) increased DMN connectivity at rest and 2) increased connectivity between the DMN and FPCN at rest. Lastly, we found significant positive correlations between trait mind wandering and fluid intelligence (Ravens) and creativity (Remote Associates Task). We interpret these findings within the context of current theories of mind wandering and executive function and discuss the possibility that certain instances of mind wandering may not be inherently harmful. Due to the controversial nature of global signal regression (GSReg) in functional connectivity analyses, we performed our analyses with and without GSReg and contrast the results from each set of analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Xia Wu

    2016-09-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2013-11-06

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

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

    Science.gov (United States)

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

    2016-01-01

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

  4. Connectivity, cycles, and persistence thresholds in metapopulation networks.

    Directory of Open Access Journals (Sweden)

    Yael Artzy-Randrup

    2010-08-01

    Full Text Available Synthesising the relationships between complexity, connectivity, and the stability of large biological systems has been a longstanding fundamental quest in theoretical biology and ecology. With the many exciting developments in modern network theory, interest in these issues has recently come to the forefront in a range of multidisciplinary areas. Here we outline a new theoretical analysis specifically relevant for the study of ecological metapopulations focusing primarily on marine systems, where subpopulations are generally connected via larval dispersal. Our work determines the qualitative and quantitative conditions by which dispersal and network structure control the persistence of a set of age-structured patch populations. Mathematical modelling combined with a graph theoretic analysis demonstrates that persistence depends crucially on the topology of cycles in the dispersal network which tend to enhance the effect of larvae "returning home." Our method clarifies the impact directly due to network structure, but this almost by definition can only be achieved by examining the simplified case in which patches are identical; an assumption that we later relax. The methodology identifies critical migration routes, whose presence are vital to overall stability, and therefore should have high conservation priority. In contrast, "lonely links," or links in the network that do not participate in a cyclical component, have no impact on persistence and thus have low conservation priority. A number of other intriguing criteria for persistence are derived. Our modelling framework reveals new insights regarding the determinants of persistence, stability, and thresholds in complex metapopulations. In particular, while theoretical arguments have, in the past, suggested that increasing connectivity is a destabilizing feature in complex systems, this is not evident in metapopulation networks where connectivity, cycles, coherency, and heterogeneity all tend

  5. Exponential stability of neural networks with asymmetric connection weights

    International Nuclear Information System (INIS)

    Yang Jinxiang; Zhong Shouming

    2007-01-01

    This paper investigates the exponential stability of a class of neural networks with asymmetric connection weights. By dividing the network state variables into various parts according to the characters of the neural networks, some new sufficient conditions of exponential stability are derived via constructing a Lyapunov function and using the method of the variation of constant. The new conditions are associated with the initial values and are described by some blocks of the interconnection matrix, and do not depend on other blocks. Examples are given to further illustrate the theory

  6. Hidden Connectivity in Networks with Vulnerable Classes of Nodes

    Directory of Open Access Journals (Sweden)

    Sebastian M. Krause

    2016-10-01

    Full Text Available In many complex systems representable as networks, nodes can be separated into different classes. Often these classes can be linked to a mutually shared vulnerability. Shared vulnerabilities may be due to a shared eavesdropper or correlated failures. In this paper, we show the impact of shared vulnerabilities on robust connectivity and how the heterogeneity of node classes can be exploited to maintain functionality by utilizing multiple paths. Percolation is the field of statistical physics that is generally used to analyze connectivity in complex networks, but in its existing forms, it cannot treat the heterogeneity of multiple vulnerable classes. To analyze the connectivity under these constraints, we describe each class as a color and develop a “color-avoiding” percolation. We present an analytic theory for random networks and a numerical algorithm for all networks, with which we can determine which nodes are color-avoiding connected and whether the maximal set percolates in the system. We find that the interaction of topology and color distribution implies a rich critical behavior, with critical values and critical exponents depending both on the topology and on the color distribution. Applying our physics-based theory to the Internet, we show how color-avoiding percolation can be used as the basis for new topologically aware secure communication protocols. Beyond applications to cybersecurity, our framework reveals a new layer of hidden structure in a wide range of natural and technological systems.

  7. Two Distinct Scene-Processing Networks Connecting Vision and Memory.

    Science.gov (United States)

    Baldassano, Christopher; Esteva, Andre; Fei-Fei, Li; Beck, Diane M

    2016-01-01

    A number of regions in the human brain are known to be involved in processing natural scenes, but the field has lacked a unifying framework for understanding how these different regions are organized and interact. We provide evidence from functional connectivity and meta-analyses for a new organizational principle, in which scene processing relies upon two distinct networks that split the classically defined parahippocampal place area (PPA). The first network of strongly connected regions consists of the occipital place area/transverse occipital sulcus and posterior PPA, which contain retinotopic maps and are not strongly coupled to the hippocampus at rest. The second network consists of the caudal inferior parietal lobule, retrosplenial complex, and anterior PPA, which connect to the hippocampus (especially anterior hippocampus), and are implicated in both visual and nonvisual tasks, including episodic memory and navigation. We propose that these two distinct networks capture the primary functional division among scene-processing regions, between those that process visual features from the current view of a scene and those that connect information from a current scene view with a much broader temporal and spatial context. This new framework for understanding the neural substrates of scene-processing bridges results from many lines of research, and makes specific functional predictions.

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

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

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

  9. Quantifying Discrete Fracture Network Connectivity in Hydraulic Fracturing Stimulation

    Science.gov (United States)

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

    2017-12-01

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

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

    Science.gov (United States)

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

    2012-01-01

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

  11. Embedded generation connection incentives for distribution network operators

    Energy Technology Data Exchange (ETDEWEB)

    Williams, P.; Andrews, S.

    2002-07-01

    This is the final report with respect to work commissioned by the Department of Trade and Industry (DTI) as part of the New and Renewable Energy Programme into incentives for distribution network operators (DNOs) for the connection of embedded generation. This report, which incorporates the contents of the interim report submitted in February 2002, considers the implications of changes in the structure and regulation in the UK electricity industry on the successful technical and commercial integrated of embedded generation into distribution networks. The report examines: the obligations of public electricity suppliers (PESs); current DNO practices regarding the connection of embedded generation; the changes introduced by the Utilities Act 2000, including the impact of new obligations placed on DNOs on the connection of embedded generation and the requirements of the new Electricity Distribution Standard Licence conditions; and problems and prospects for DNO incentives.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-07-01

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

  13. Resting-state functional under-connectivity within and between large-scale cortical networks across three low-frequency bands in adolescents with autism.

    Science.gov (United States)

    Duan, Xujun; Chen, Heng; He, Changchun; Long, Zhiliang; Guo, Xiaonan; Zhou, Yuanyue; Uddin, Lucina Q; Chen, Huafu

    2017-10-03

    Although evidence is accumulating that autism spectrum disorder (ASD) is associated with disruption of functional connections between and within brain networks, it remains largely unknown whether these abnormalities are related to specific frequency bands. To address this question, network contingency analysis was performed on brain functional connectomes obtained from 213 adolescent participants across nine sites in the Autism Brain Imaging Data Exchange (ABIDE) multisite sample, to determine the disrupted connections between and within seven major cortical networks in adolescents with ASD at Slow-5, Slow-4 and Slow-3 frequency bands and further assess whether the aberrant intra- and inter-network connectivity varied as a function of ASD symptoms. Overall under-connectivity within and between large-scale intrinsic networks in ASD was revealed across the three frequency bands. Specifically, decreased connectivity strength within the default mode network (DMN), between DMN and visual network (VN), ventral attention network (VAN), and between dorsal attention network (DAN) and VAN was observed in the lower frequency band (slow-5, slow-4), while decreased connectivity between limbic network (LN) and frontal-parietal network (FPN) was observed in the higher frequency band (slow-3). Furthermore, weaker connectivity within and between specific networks correlated with poorer communication and social interaction skills in the slow-5 band, uniquely. These results demonstrate intrinsic under-connectivity within and between multiple brain networks within predefined frequency bands in ASD, suggesting that frequency-related properties underlie abnormal brain network organization in the disorder. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Edith J Liemburg

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

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

    Science.gov (United States)

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

    2014-11-01

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

  16. Connectivity and Nestedness in Bipartite Networks from Community Ecology

    International Nuclear Information System (INIS)

    Corso, Gilberto; De Araujo, A I Levartoski; De Almeida, Adriana M

    2011-01-01

    Bipartite networks and the nestedness concept appear in two different contexts in theoretical ecology: community ecology and islands biogeography. From a mathematical perspective nestedness is a pattern in a bipartite network. There are several nestedness indices in the market, we used the index ν. The index ν is found using the relation ν = 1 - τ where τ is the temperature of the adjacency matrix of the bipartite network. By its turn τ is defined with help of the Manhattan distance of the occupied elements of the adjacency matrix of the bipartite network. We prove that the nestedness index ν is a function of the connectivities of the bipartite network. In addition we find a concise way to find ν which avoid cumbersome algorithm manupulation of the adjacency matrix.

  17. Connectivity and Nestedness in Bipartite Networks from Community Ecology

    Energy Technology Data Exchange (ETDEWEB)

    Corso, Gilberto [Departamento de Biofisica e Farmacologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil); De Araujo, A I Levartoski [Instituto Federal de Educacao, Ciencia e Tecnologia do Ceara Av. Treze de Maio, 2081 - Benfica CEP 60040-531 - Fortaleza, CE (Brazil); De Almeida, Adriana M, E-mail: corso@cb.ufrn.br [Departamento de Botanica, Ecologia e Zoologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil)

    2011-03-01

    Bipartite networks and the nestedness concept appear in two different contexts in theoretical ecology: community ecology and islands biogeography. From a mathematical perspective nestedness is a pattern in a bipartite network. There are several nestedness indices in the market, we used the index {nu}. The index {nu} is found using the relation {nu} = 1 - {tau} where {tau} is the temperature of the adjacency matrix of the bipartite network. By its turn {tau} is defined with help of the Manhattan distance of the occupied elements of the adjacency matrix of the bipartite network. We prove that the nestedness index {nu} is a function of the connectivities of the bipartite network. In addition we find a concise way to find {nu} which avoid cumbersome algorithm manupulation of the adjacency matrix.

  18. Performance evaluation of a 2-mode PV grid connected system in Thailand -- Case study

    Energy Technology Data Exchange (ETDEWEB)

    Jivacate, C.; Mongconvorawan, S.; Sinratanapukdee, E.; Limsawatt, W. [Electricity Generating Authority of Thailand, Nontha Buri (Thailand)

    1994-12-31

    A PV grid connected system with small battery bank has been set up in a rural district, North Thailand in order to demonstrate a 2-mode operation concept. The objective is to gain experience on the PV grid connected concept without battery storage. However, due to the evening peak demand and a rather weak distribution grid which is typical in rural areas, small battery bank is still required to enable the maximum energy transfer to grid for the time being before moving fully to the no battery mode. The analyzed data seems to indicate possible performance improvement by re-arranging the number of PV modules and battery in the string.

  19. Flexible Mode Control of Grid Connected Wind Energy Conversion System Using Wavelet

    Directory of Open Access Journals (Sweden)

    Bhavna Jain

    2015-01-01

    Full Text Available Small wind turbine systems offer services to critical loads during grid faults and also connected back to grid in normal condition. The connection of a wind energy conversion system to the grid requires a robust phase locked loop (PLL and continuous monitoring of the grid conditions such as overvoltage, undervoltage, overfrequency, underfrequency, and grid outages. This paper describes a flexible control operation to operate a small wind turbine in both stand-alone mode via planned islanding and grid connected mode as well. In particular, a proper monitoring and control algorithm is required for transition between the modes. A wavelet based energy function is used for detection of grid disturbances as well as recovery of grid so that transition between the modes is made. To obtain good power quality LCL filter is used to reduce ripples. PLL is used for synchronization whenever mode changes from stand-alone to grid connected. Simulation results from a 10 kW wind energy conversion system are included to show the usefulness of the proposed methods. The control method is tested by generated gate pulses for single phase bridge inverter using field programmable gate array (FPGA.

  20. Whole-brain functional connectivity during acquisition of novel grammar: Distinct functional networks depend on language learning abilities.

    Science.gov (United States)

    Kepinska, Olga; de Rover, Mischa; Caspers, Johanneke; Schiller, Niels O

    2017-03-01

    In an effort to advance the understanding of brain function and organisation accompanying second language learning, we investigate the neural substrates of novel grammar learning in a group of healthy adults, consisting of participants with high and average language analytical abilities (LAA). By means of an Independent Components Analysis, a data-driven approach to functional connectivity of the brain, the fMRI data collected during a grammar-learning task were decomposed into maps representing separate cognitive processes. These included the default mode, task-positive, working memory, visual, cerebellar and emotional networks. We further tested for differences within the components, representing individual differences between the High and Average LAA learners. We found high analytical abilities to be coupled with stronger contributions to the task-positive network from areas adjacent to bilateral Broca's region, stronger connectivity within the working memory network and within the emotional network. Average LAA participants displayed stronger engagement within the task-positive network from areas adjacent to the right-hemisphere homologue of Broca's region and typical to lower level processing (visual word recognition), and increased connectivity within the default mode network. The significance of each of the identified networks for the grammar learning process is presented next to a discussion on the established markers of inter-individual learners' differences. We conclude that in terms of functional connectivity, the engagement of brain's networks during grammar acquisition is coupled with one's language learning abilities. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    Reybrouck, Mark; Vuust, Peter; Brattico, Elvira

    2018-06-12

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

  2. Flexible Mode Control of Grid Connected Wind Energy Conversion System Using Wavelet

    OpenAIRE

    Jain, Bhavna; Singh, Sameer; Jain, Shailendra; Nema, R. K.

    2015-01-01

    Small wind turbine systems offer services to critical loads during grid faults and also connected back to grid in normal condition. The connection of a wind energy conversion system to the grid requires a robust phase locked loop (PLL) and continuous monitoring of the grid conditions such as overvoltage, undervoltage, overfrequency, underfrequency, and grid outages. This paper describes a flexible control operation to operate a small wind turbine in both stand-alone mode via planned islanding...

  3. Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks

    Directory of Open Access Journals (Sweden)

    Lindsay eRutter

    2013-07-01

    Full Text Available Complex networks have been observed to comprise small-world properties, believed to represent an optimal organization of local specialization and global integration of information processing at reduced wiring cost. Here, we applied magnitude squared coherence to resting magnetoencephalographic time series in reconstructed source space, acquired from controls and patients with schizophrenia, and generated frequency-dependent adjacency matrices modeling functional connectivity between virtual channels. After configuring undirected binary and weighted graphs, we found that all human networks demonstrated highly localized clustering and short characteristic path lengths. The most conservatively thresholded networks showed efficient wiring, with topographical distance between connected vertices amounting to one-third as observed in surrogate randomized topologies. Nodal degrees of the human networks conformed to a heavy-tailed exponentially truncated power-law, compatible with the existence of hubs, which included theta and alpha bilateral cerebellar tonsil, beta and gamma bilateral posterior cingulate, and bilateral thalamus across all frequencies. We conclude that all networks showed small-worldness, minimal physical connection distance, and skewed degree distributions characteristic of physically-embedded networks, and that these calculations derived from graph theoretical mathematics did not quantifiably distinguish between subject populations, independent of bandwidth. However, post-hoc measurements of edge computations at the scale of the individual vertex revealed trends of reduced gamma connectivity across the posterior medial parietal cortex in patients, an observation consistent with our prior resting activation study that found significant reduction of synthetic aperture magnetometry gamma power across similar regions. The basis of these small differences remains unclear.

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

    Directory of Open Access Journals (Sweden)

    Junhao Pan

    2018-03-01

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

  5. Interactions of the Salience Network and Its Subsystems with the Default-Mode and the Central-Executive Networks in Normal Aging and Mild Cognitive Impairment.

    Science.gov (United States)

    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 control correlated significantly with lower overall cognitive performance measured by Montreal Cognitive Assessment (r = 0.295; p 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.

  6. Optimal Operation of Network-Connected Combined Heat and Powers for Customer Profit Maximization

    Directory of Open Access Journals (Sweden)

    Da Xie

    2016-06-01

    Full Text Available Network-connected combined heat and powers (CHPs, owned by a community, can export surplus heat and electricity to corresponding heat and electric networks after community loads are satisfied. This paper proposes a new optimization model for network-connected CHP operation. Both CHPs’ overall efficiency and heat to electricity ratio (HTER are assumed to vary with loading levels. Based on different energy flow scenarios where heat and electricity are exported to the network from the community or imported, four profit models are established accordingly. They reflect the different relationships between CHP energy supply and community load demand across time. A discrete optimization model is then developed to maximize the profit for the community. The models are derived from the intervals determined by the daily operation modes of CHP and real-time buying and selling prices of heat, electricity and natural gas. By demonstrating the proposed models on a 1 MW network-connected CHP, results show that the community profits are maximized in energy markets. Thus, the proposed optimization approach can help customers to devise optimal CHP operating strategies for maximizing benefits.

  7. Obesity is marked by distinct functional connectivity in brain networks involved in food reward and salience.

    Science.gov (United States)

    Wijngaarden, M A; Veer, I M; Rombouts, S A R B; van Buchem, M A; Willems van Dijk, K; Pijl, H; van der Grond, J

    2015-01-01

    We hypothesized that brain circuits involved in reward and salience respond differently to fasting in obese versus lean individuals. We compared functional connectivity networks related to food reward and saliency after an overnight fast (baseline) and after a prolonged fast of 48 h in lean versus obese subjects. We included 13 obese (2 males, 11 females, BMI 35.4 ± 1.2 kg/m(2), age 31 ± 3 years) and 11 lean subjects (2 males, 9 females, BMI 23.2 ± 0.5 kg/m(2), age 28 ± 3 years). Resting-state functional magnetic resonance imaging scans were made after an overnight fast (baseline) and after a prolonged 48 h fast. Functional connectivity of the amygdala, hypothalamus and posterior cingulate cortex (default-mode) networks was assessed using seed-based correlations. At baseline, we found a stronger connectivity between hypothalamus and left insula in the obese subjects. This effect diminished upon the prolonged fast. After prolonged fasting, connectivity of the hypothalamus with the dorsal anterior cingulate cortex (dACC) increased in lean subjects and decreased in obese subjects. Amygdala connectivity with the ventromedial prefrontal cortex was stronger in lean subjects at baseline, which did not change upon the prolonged fast. No differences in posterior cingulate cortex connectivity were observed. In conclusion, obesity is marked by alterations in functional connectivity networks involved in food reward and salience. Prolonged fasting differentially affected hypothalamic connections with the dACC and the insula between obese and lean subjects. Our data support the idea that food reward and nutrient deprivation are differently perceived and/or processed in obesity. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Just-in-time connectivity for large spiking networks.

    Science.gov (United States)

    Lytton, William W; Omurtag, Ahmet; Neymotin, Samuel A; Hines, Michael L

    2008-11-01

    The scale of large neuronal network simulations is memory limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed: just in time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities, and weights, as well as run-time connectivity state: the event queue. Comparison of the JitCon implementation to NEURON's standard NetCon connectivity method showed substantial space savings, with associated run-time penalty. Although JitCon saved space by eliminating connectivity parameters, larger simulations were still memory limited due to growth of the synaptic event queue. We therefore designed a JitEvent algorithm that added items to the queue only when required: instead of alerting multiple postsynaptic cells, a spiking presynaptic cell posted a callback event at the shortest synaptic delay time. At the time of the callback, this same presynaptic cell directly notified the first postsynaptic cell and generated another self-callback for the next delay time. The JitEvent implementation yielded substantial additional time and space savings. We conclude that just-in-time strategies are necessary for very large network simulations but that a variety of alternative strategies should be considered whose optimality will depend on the characteristics of the simulation to be run.

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

    Science.gov (United States)

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

    2018-02-01

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

  10. Tunable deformation modes shape contractility in active biopolymer networks

    Science.gov (United States)

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

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

  11. Genes2FANs: connecting genes through functional association networks

    Science.gov (United States)

    2012-01-01

    Background Protein-protein, cell signaling, metabolic, and transcriptional interaction networks are useful for identifying connections between lists of experimentally identified genes/proteins. However, besides physical or co-expression interactions there are many ways in which pairs of genes, or their protein products, can be associated. By systematically incorporating knowledge on shared properties of genes from diverse sources to build functional association networks (FANs), researchers may be able to identify additional functional interactions between groups of genes that are not readily apparent. Results Genes2FANs is a web based tool and a database that utilizes 14 carefully constructed FANs and a large-scale protein-protein interaction (PPI) network to build subnetworks that connect lists of human and mouse genes. The FANs are created from mammalian gene set libraries where mouse genes are converted to their human orthologs. The tool takes as input a list of human or mouse Entrez gene symbols to produce a subnetwork and a ranked list of intermediate genes that are used to connect the query input list. In addition, users can enter any PubMed search term and then the system automatically converts the returned results to gene lists using GeneRIF. This gene list is then used as input to generate a subnetwork from the user’s PubMed query. As a case study, we applied Genes2FANs to connect disease genes from 90 well-studied disorders. We find an inverse correlation between the counts of links connecting disease genes through PPI and links connecting diseases genes through FANs, separating diseases into two categories. Conclusions Genes2FANs is a useful tool for interpreting the relationships between gene/protein lists in the context of their various functions and networks. Combining functional association interactions with physical PPIs can be useful for revealing new biology and help form hypotheses for further experimentation. Our finding that disease genes in

  12. An improved algorithm for connectivity analysis of distribution networks

    International Nuclear Information System (INIS)

    Kansal, M.L.; Devi, Sunita

    2007-01-01

    In the present paper, an efficient algorithm for connectivity analysis of moderately sized distribution networks has been suggested. Algorithm is based on generation of all possible minimal system cutsets. The algorithm is efficient as it identifies only the necessary and sufficient conditions of system failure conditions in n-out-of-n type of distribution networks. The proposed algorithm is demonstrated with the help of saturated and unsaturated distribution networks. The computational efficiency of the algorithm is justified by comparing the computational efforts with the previously suggested appended spanning tree (AST) algorithm. The proposed technique has the added advantage as it can be utilized for generation of system inequalities which is useful in reliability estimation of capacitated networks

  13. Altered causal connectivity of resting state brain networks in amnesic MCI.

    Directory of Open Access Journals (Sweden)

    Peipeng Liang

    Full Text Available Most neuroimaging studies of resting state networks in amnesic mild cognitive impairment (aMCI have concentrated on functional connectivity (FC based on instantaneous correlation in a single network. The purpose of the current study was to investigate effective connectivity in aMCI patients based on Granger causality of four important networks at resting state derived from functional magnetic resonance imaging data--default mode network (DMN, hippocampal cortical memory network (HCMN, dorsal attention network (DAN and fronto-parietal control network (FPCN. Structural and functional MRI data were collected from 16 aMCI patients and 16 age, gender-matched healthy controls. Correlation-purged Granger causality analysis was used, taking gray matter atrophy as covariates, to compare the group difference between aMCI patients and healthy controls. We found that the causal connectivity between networks in aMCI patients was significantly altered with both increases and decreases in the aMCI group as compared to healthy controls. Some alterations were significantly correlated with the disease severity as measured by mini-mental state examination (MMSE, and California verbal learning test (CVLT scores. When the whole-brain signal averaged over the entire brain was used as a nuisance co-variate, the within-group maps were significantly altered while the between-group difference maps did not. These results suggest that the alterations in causal influences may be one of the possible underlying substrates of cognitive impairments in aMCI. The present study extends and complements previous FC studies and demonstrates the coexistence of causal disconnection and compensation in aMCI patients, and thus might provide insights into biological mechanism of the disease.

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

    Directory of Open Access Journals (Sweden)

    Marwan N Baliki

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

  15. Connectivity, flow and transport in network models of fractured media

    International Nuclear Information System (INIS)

    Robinson, P.C.

    1984-10-01

    In order to evaluate the safety of radioactive waste disposal underground it is important to understand the way in which radioactive material is transported through the rock to the surface. If the rock is fractured the usual models may not be applicable. In this work we look at three aspects of fracture networks: connectivity, flow and transport. These are studied numerically by generating fracture networks in a computer and modelling the processes which occur. Connectivity relates to percolation theory, and critical densities for fracture systems are found in two and three dimensions. The permeability of two-dimensional networks is studied. The way that permeability depends on fracture density, network size and spread of fracture length can be predicted using a cut lattice model. Transport through the fracture network by convection through the fractures and mixing at the intersections is studied. The Fickian dispersion equation does not describe the resulting hydrodynamic dispersion. Extensions to the techniques to three dimensions and to include other processes are discussed. (author)

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

    Directory of Open Access Journals (Sweden)

    Silvia Tommasin

    2017-07-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-07-01

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

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

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano

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

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

    Science.gov (United States)

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

    2010-11-01

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

  1. Dynamics of coupled mode solitons in bursting neural networks

    Science.gov (United States)

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

    2018-02-01

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

  2. 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.

    Science.gov (United States)

    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 (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.

  3. The value of less connected agents in Boolean networks

    Science.gov (United States)

    Epstein, Daniel; Bazzan, Ana L. C.

    2013-11-01

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

  4. Restoration of lost connectivity of partitioned wireless sensor networks

    Directory of Open Access Journals (Sweden)

    Virender Ranga

    2016-05-01

    Full Text Available The lost connectivity due to failure of large scale nodes plays major role to degrade the system performance by generating unnecessary overhead or sometimes totally collapse the active network. There are many issues and challenges to restore the lost connectivity in an unattended scenario, i.e. how many recovery nodes will be sufficient and on which locations these recovery nodes have to be placed. A very few centralized and distributed approaches have been proposed till now. The centralized approaches are good for a scenario where information about the disjoint network, i.e. number of disjoint segments and their locations are well known in advance. However, for a scenario where such information is unknown due to the unattended harsh environment, a distributed approach is a better solution to restore the partitioned network. In this paper, we have proposed and implemented a semi-distributed approach called Relay node Placement using Fermat Point (RPFP. The proposed approach is capable of restoring lost connectivity with small number of recovery relay nodes and it works for any number of disjoint segments. The simulation experiment results show effectiveness of our approach as compared to existing benchmark approaches.

  5. Neural Network Substorm Identification: Enabling TREx Sensor Web Modes

    Science.gov (United States)

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

    2017-12-01

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

  6. How has climate change altered network connectivity in a mountain stream network?

    Science.gov (United States)

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

    2017-12-01

    Connectivity along river networks is broadly recognized as dynamic, with seasonal and event-based expansion and contraction of the network extent. Intermittently flowing streams are particularly important as they define a crucial threshold for continuously connected waters that enable migration by aquatic species. In the Pacific northwestern U.S., changes in atmospheric circulation have been found to alter rainfall patterns and result in decreased summer low-flows in the region. However, the impact of this climate dynamic on network connectivity is heretofore unstudied. Thus, we ask: How has connectivity in the riparian corridor changed in response to observed changes in climate? In this study we take the well-studied H.J. Andrews Experimental Forest as representative of mountain river networks in the Pacific northwestern U.S. First, we analyze 63 years of stream gauge information from a network of 11 gauges to document observed changes in timing and magnitude of stream discharge. We found declining magnitudes of seasonal low-flows and shifting seasonality of water export from the catchment, both of which we attribute to changes in precipitation timing and storage as snow vs. rainfall. Next, we use these discharge data to drive a reduced-complexity model of the river network to simulate network connectivity over 63 years. Model results show that network contraction (i.e., minimum network extent) has decreased over the past 63 years. Unexpectedly, the increasing winter peak flows did not correspond with increasing network expansion, suggesting a geologic control on maximum flowing network extent. We find dynamic expansion and contraction of the network primarily occurs during period of catchment discharge less than about 1 m3/s at the outlet, whereas the network extent is generally constant for discharges from 1 to 300 m3/s. Results of our study are of interest to scientists focused on connectivity as a control on ecological processes both directly (e.g., fish

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

    Directory of Open Access Journals (Sweden)

    Umberto Esposito

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2010-03-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2004-07-01

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

  11. Evaluating the impact of connectivity, continuity, and topography of sidewalk network on pedestrian safety.

    Science.gov (United States)

    Osama, Ahmed; Sayed, Tarek

    2017-10-01

    With the increasing demand for sustainability, walking is being encouraged as one of the main active modes of transportation. However, pedestrians are vulnerable to severe injuries when involved in crashes which can discourage road users from walking. Therefore, studying factors that affect the safety of pedestrians is important. This paper investigates the relationship between pedestrian-motorist crashes and various sidewalk network indicators in the city of Vancouver. The goal is to assess the impact of network connectivity, directness, and topography on pedestrian safety using macro-level collision prediction models. The models were developed using generalized linear regression and full Bayesian techniques. Both walking trips and vehicle kilometers travelled were used as the main traffic exposure variables in the models. The safety models supported the safety in numbers hypothesis showing a non-linear positive association between pedestrian-motorist crashes and the increase in walking trips and vehicle traffic. The model results also suggested that higher continuity, linearity, coverage, and slope of sidewalk networks were associated with lower crash occurrence. However, network connectivity was associated with higher crash occurrence. The spatial effects were accounted for in the full Bayes models and were found significant. The models provide insights about the factors that influence pedestrian safety and the spatial variability of pedestrian crashes within a city, which can be useful for the planning of pedestrian networks. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    International Nuclear Information System (INIS)

    Li Chunguang; Chen Guanrong

    2003-01-01

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

  13. Quasi-TEM electromagnetic modes of a plasma waveguide with a nonsimply connected cross section in an external magnetic field

    International Nuclear Information System (INIS)

    Kartashov, I. N.; Kuzelev, M. V.

    2014-01-01

    Electromagnetic modes of a plasma waveguide with a nonsimply connected cross section in an external magnetic field are investigated. The existence of quasi-TEM modes in a finite-strength magnetic field is demonstrated. It is shown that, in the limits of infinitely strong and zero magnetic fields, this mode transforms into a true TEM mode. The possibility of excitation of such modes by an electron beam in the regime of the anomalous Doppler effect is analyzed

  14. Common mode voltage in case of transformerless PV inverters connected to the grid

    DEFF Research Database (Denmark)

    Kerekes, Tamas; Teodorescu, Remus; Liserre, Marco

    2008-01-01

    For safety reasons grid connected PV systems include galvanic isolation. In case of transformerless inverters, the leakage ground current through the parasitic capacitance of the PV panels, can reach very high values. A common-mode model based on analytical approach is introduced, used to predict...... the common-mode behavior, at frequencies lower than 50kHz, of the selected topologies and to explain the influence of system imbalance on the leakage current. It will be demonstrated that the neutral inductance has a crucial influence on the leakage current. Finally experimental results will be shown...

  15. Dynamical graph theory networks techniques for the analysis of sparse connectivity networks in dementia

    Science.gov (United States)

    Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke

    2017-05-01

    Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.

  16. Connected or informed?: Local Twitter networking in a London neighbourhood

    Directory of Open Access Journals (Sweden)

    John Bingham-Hall

    2015-08-01

    Full Text Available This paper asks whether geographically localised, or ‘hyperlocal’, uses of Twitter succeed in creating peer-to-peer neighbourhood networks or simply act as broadcast media at a reduced scale. Literature drawn from the smart cities discourse and from a UK research project into hyperlocal media, respectively, take on these two opposing interpretations. Evidence gathered in the case study presented here is consistent with the latter, and on this basis we criticise the notion that hyperlocal social media can be seen as a community in itself. We demonstrate this by creating a network map of Twitter followers of a popular hyperlocal blog in Brockley, southeast London. We describe various attributes of this network including its average degree and clustering coefficient to suggest that a small and highly connected cluster of visible local entities such as businesses form a clique at the centre of this network, with individual residents following these but not one another. We then plot the locations of these entities and demonstrate that sub-communities in the network are formed due to close geographical proximity between smaller sets of businesses. These observations are illustrated with qualitative evidence from interviews with users who suggest instead that rather than being connected to one another they benefit from what has been described as ‘neighbourhood storytelling’. Despite the limitations of working with Twitter data, we propose that this multi-modal approach offers a valuable way to investigate the experience of using social media as a communication tool in urban neighbourhoods.

  17. Harmonics Suppression for Single-Phase Grid-Connected Photovoltaic Systems in Different Operation Modes

    DEFF Research Database (Denmark)

    Yang, Yongheng; Zhou, Keliang; Blaabjerg, Frede

    2013-01-01

    -connected PV inverters may be severely affected in different operation modes. In this paper, a detailed analysis is conducted to reveal the relationship between the harmonics level with the power factor and the current level in the PV systems. A current control solution which employs an Internal Model...... Principle (IMP) is proposed to suppress the harmonic currents injected into the grid. Experiments are carried out to verify the analysis and the performance of the proposed control method. It is demonstrated that the proposed method presents an effective solution to harmonics suppression for single......-phase grid-connected PV systems in different operation modes. Especially, it can remove higher order harmonics effectively leading to a better power quality compared to the Proportional plus Multi-Resonant Controller, and it has less computational burden....

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

    Directory of Open Access Journals (Sweden)

    Tao Ye

    2018-06-01

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

  19. Trapped modes in linear quantum stochastic networks with delays

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-12-15

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

  20. Microgrid energy management in grid-connected and islanding modes based on SVC

    International Nuclear Information System (INIS)

    Gabbar, Hossam A.; Abdelsalam, Abdelazeem A.

    2014-01-01

    Highlights: • SVC is used to enhance the performance of a microgrid (MG). • MG performance is measured by some key performance indicators (KPIs). • KPIs comprise power loss, voltage deviation, power factor, THD and v/f deviation. • The microgrid is simulated in grid-connected and islanded modes. • Results show SVC stabilizes voltage, reduce losses and THD and enhance power factor. - Abstract: Microgrids are small scale energy grids that can provide adequate energy supply to cover regional demand by integrating renewable energy generation and storage technologies. This paper develops a high performance dynamic model of a microgrid system comprising a wind turbine, a PV, a fuel cell, a micro gas turbine generator, an energy storage, electric loads with variable load profile and flexible AC transmission system (FACTS) devices. The FACTS devices based on static VAR compensators have been employed as a supervisory controller. Key performance indicators such as microgrid power losses, buses voltage deviations, buses power factor, buses voltage total harmonic distortion and voltage-frequency deviation are used to evaluate the performance of this microgrid in grid-connected and islanding modes. The results obtained from the Matlab/Simulink environment show that the proposed microgrid design with SVC has the ability to meet its special requirements such as bus voltages stabilization, reduction of feeder losses, power factor enhancement and mitigation of total harmonic distortion using SVC in grid-connected and islanding modes

  1. Long-term intensive gymnastic training induced changes in intra- and inter-network functional connectivity: an independent component analysis.

    Science.gov (United States)

    Huang, Huiyuan; Wang, Junjing; Seger, Carol; Lu, Min; Deng, Feng; Wu, Xiaoyan; He, Yuan; Niu, Chen; Wang, Jun; Huang, Ruiwang

    2018-01-01

    Long-term intensive gymnastic training can induce brain structural and functional reorganization. Previous studies have identified structural and functional network differences between world class gymnasts (WCGs) and non-athletes at the whole-brain level. However, it is still unclear how interactions within and between functional networks are affected by long-term intensive gymnastic training. We examined both intra- and inter-network functional connectivity of gymnasts relative to non-athletes using resting-state fMRI (R-fMRI). R-fMRI data were acquired from 13 WCGs and 14 non-athlete controls. Group-independent component analysis (ICA) was adopted to decompose the R-fMRI data into spatial independent components and associated time courses. An automatic component identification method was used to identify components of interest associated with resting-state networks (RSNs). We identified nine RSNs, the basal ganglia network (BG), sensorimotor network (SMN), cerebellum (CB), anterior and posterior default mode networks (aDMN/pDMN), left and right fronto-parietal networks (lFPN/rFPN), primary visual network (PVN), and extrastriate visual network (EVN). Statistical analyses revealed that the intra-network functional connectivity was significantly decreased within the BG, aDMN, lFPN, and rFPN, but increased within the EVN in the WCGs compared to the controls. In addition, the WCGs showed uniformly decreased inter-network functional connectivity between SMN and BG, CB, and PVN, BG and PVN, and pDMN and rFPN compared to the controls. We interpret this generally weaker intra- and inter-network functional connectivity in WCGs during the resting state as a result of greater efficiency in the WCGs' brain associated with long-term motor skill training.

  2. Understanding magnetotransport signatures in networks of connected permalloy nanowires

    Science.gov (United States)

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

    2017-02-01

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

  3. Voter dynamics on an adaptive network with finite average connectivity

    Science.gov (United States)

    Mukhopadhyay, Abhishek; Schmittmann, Beate

    2009-03-01

    We study a simple model for voter dynamics in a two-party system. The opinion formation process is implemented in a random network of agents in which interactions are not restricted by geographical distance. In addition, we incorporate the rapidly changing nature of the interpersonal relations in the model. At each time step, agents can update their relationships, so that there is no history dependence in the model. This update is determined by their own opinion, and by their preference to make connections with individuals sharing the same opinion and with opponents. Using simulations and analytic arguments, we determine the final steady states and the relaxation into these states for different system sizes. In contrast to earlier studies, the average connectivity (``degree'') of each agent is constant here, independent of the system size. This has significant consequences for the long-time behavior of the model.

  4. Reward networks in the brain as captured by connectivity measures

    Directory of Open Access Journals (Sweden)

    Estela Camara

    2009-12-01

    Full Text Available An assortment of human behaviors is thought to be driven by rewards including reinforcement learning, novelty processing, learning, decision making, economic choice, incentive motivation, and addiction. In each case the ventral tegmental area / ventral striatum (Nucleus accumbens system (VTA-VS has been implicated as a key structure by functional imaging studies, mostly on the basis of standard, univariate analyses. Here we propose that standard fMRI analysis needs to be complemented by methods that take into account the differential connectivity of the VTA-VS system in the different behavioral contexts in order to describe reward based processes more appropriately. We first consider the wider network for reward processing as it emerged from animal experimentation. Subsequently, an example for a method to assess functional connectivity is given. Finally, we illustrate the usefulness of such analyses by examples regarding reward valuation, reward expectation and the role of reward in addiction.

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

    Science.gov (United States)

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

    2017-04-01

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

  6. Controlling Voltage Levels of Distribution Network-Radial Feeder after Connecting Wind Turbines to the Network

    Directory of Open Access Journals (Sweden)

    Muhammad Al Badri

    2017-11-01

    Full Text Available Several factors in power generation and supply need to be taken into account such as shortages of energy supply, system stability, and energy quality and system disruption due to network losses, industrial development and population expansion. The addition of wind turbines to the distribution network is of great benefit in providing additional power and solving these problems, but this addition is accompanied by the problem of low voltage network. This research found optimal solutions to the problem of low voltage distribution network after connecting wind turbines. The main idea of this paper is to optimize the low-voltage problem as a result of connecting the wind turbines to the "far end" of the radial feeder for a distribution network and to obtain a voltage level within an acceptable and stable range. The problem of low voltage solved by using the load-drop compensation, capacitor-bank and “doubly-fed” induction generators. The results of this study were based on the operation of the entire design of the simulation system which would be compatible with the reality of the energy flow of all network components by using the PSCAD program. The present analysis program revealed an optimum solution for the low voltage profile of the distribution network after connecting the wind turbine.

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

    Science.gov (United States)

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

    2016-07-01

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

  8. Network robustness assessed within a dual connectivity framework: joint dynamics of the Active and Idle Networks.

    Science.gov (United States)

    Tejedor, Alejandro; Longjas, Anthony; Zaliapin, Ilya; Ambroj, Samuel; Foufoula-Georgiou, Efi

    2017-08-17

    Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. But current definition of robustness is only accounting for half of the story: the connectivity of the nodes unaffected by the attack. Here we propose a new framework to assess network robustness, wherein the connectivity of the affected nodes is also taken into consideration, acknowledging that it plays a crucial role in properly evaluating the overall network robustness in terms of its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and that of building-up the IN. We show, via analysis of well-known prototype networks and real world data, that trade-offs between the efficiency of Active and Idle Network dynamics give rise to surprising robustness crossovers and re-rankings, which can have significant implications for decision making.

  9. Fully connected network of superconducting qubits in a cavity

    International Nuclear Information System (INIS)

    Tsomokos, Dimitris I; Ashhab, Sahel; Nori, Franco

    2008-01-01

    A fully connected qubit network is considered, where every qubit interacts with every other one. When the interactions between the qubits are homogeneous, the system is a special case of the finite Lipkin-Meshkov-Glick (LMG) model. We propose a natural implementation of this model using superconducting qubits in state-of-the-art circuit QED. The ground state, the low-lying energy spectrum and the dynamical evolution are investigated. We find that, under realistic conditions, highly entangled states of Greenberger-Horne-Zeilinger (GHZ) and W types can be generated. We also comment on the influence of disorder on the system and discuss the possibility of simulating complex quantum systems, such as Sherrington-Kirkpatrick (SK) spin glasses, with superconducting qubit networks.

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

    Science.gov (United States)

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

    2017-11-22

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

  11. Pathloss Measurements and Modeling for UAVs Connected to Cellular Networks

    DEFF Research Database (Denmark)

    Amorim, Rafhael Medeiros de; Mogensen, Preben Elgaard; Sørensen, Troels Bundgaard

    2017-01-01

    . The measurements were conducted in an operating LTE network (850 MHz), using a commercial cell phone, placed inside the frame of the UAV. Trials were conducted for UAV flying at 5 different heights measured above ground level (20, 40, 60, 80 and 100m) and a pathloss regression line was obtained from results. Then......This paper assess field measurements, as part of the investigation of the suitability of cellular networks for providing connectivity to UAVs (unmanned aerial vehicles). Evaluation is done by means of field measurements obtained in a rural environment in Denmark with an airbone UAV......, downlink (DL) SINR levels obtained during flight measurements are also presented. An important result obtained from the measurents reveal that there is a height-related DL SINR degradation. Three main sources of uncertainty on the pathloss model that could be responsible for the SINR degradation are also...

  12. Ketamine decreases resting state functional network connectivity in healthy subjects: implications for antidepressant drug action.

    Directory of Open Access Journals (Sweden)

    Milan Scheidegger

    Full Text Available Increasing preclinical and clinical evidence underscores the strong and rapid antidepressant properties of the glutamate-modulating NMDA receptor antagonist ketamine. Targeting the glutamatergic system might thus provide a novel molecular strategy for antidepressant treatment. Since glutamate is the most abundant and major excitatory neurotransmitter in the brain, pathophysiological changes in glutamatergic signaling are likely to affect neurobehavioral plasticity, information processing and large-scale changes in functional brain connectivity underlying certain symptoms of major depressive disorder. Using resting state functional magnetic resonance imaging (rsfMRI, the "dorsal nexus "(DN was recently identified as a bilateral dorsal medial prefrontal cortex region showing dramatically increased depression-associated functional connectivity with large portions of a cognitive control network (CCN, the default mode network (DMN, and a rostral affective network (AN. Hence, Sheline and colleagues (2010 proposed that reducing increased connectivity of the DN might play a critical role in reducing depression symptomatology and thus represent a potential therapy target for affective disorders. Here, using a randomized, placebo-controlled, double-blind, crossover rsfMRI challenge in healthy subjects we demonstrate that ketamine decreases functional connectivity of the DMN to the DN and to the pregenual anterior cingulate (PACC and medioprefrontal cortex (MPFC via its representative hub, the posterior cingulate cortex (PCC. These findings in healthy subjects may serve as a model to elucidate potential biomechanisms that are addressed by successful treatment of major depression. This notion is further supported by the temporal overlap of our observation of subacute functional network modulation after 24 hours with the peak of efficacy following an intravenous ketamine administration in treatment-resistant depression.

  13. Aberrant functional network connectivity in psychopathy from a large (N = 985) forensic sample.

    Science.gov (United States)

    Espinoza, Flor A; Vergara, Victor M; Reyes, Daisy; Anderson, Nathaniel E; Harenski, Carla L; Decety, Jean; Rachakonda, Srinivas; Damaraju, Eswar; Rashid, Barnaly; Miller, Robyn L; Koenigs, Michael; Kosson, David S; Harenski, Keith; Kiehl, Kent A; Calhoun, Vince D

    2018-06-01

    Psychopathy is a personality disorder characterized by antisocial behavior, lack of remorse and empathy, and impaired decision making. The disproportionate amount of crime committed by psychopaths has severe emotional and economic impacts on society. Here we examine the neural correlates associated with psychopathy to improve early assessment and perhaps inform treatments for this condition. Previous resting-state functional magnetic resonance imaging (fMRI) studies in psychopathy have primarily focused on regions of interest. This study examines whole-brain functional connectivity and its association to psychopathic traits. Psychopathy was hypothesized to be characterized by aberrant functional network connectivity (FNC) in several limbic/paralimbic networks. Group-independent component and regression analyses were applied to a data set of resting-state fMRI from 985 incarcerated adult males. We identified resting-state networks (RSNs), estimated FNC between RSNs, and tested their association to psychopathy factors and total summary scores (Factor 1, interpersonal/affective; Factor 2, lifestyle/antisocial). Factor 1 scores showed both increased and reduced functional connectivity between RSNs from seven brain domains (sensorimotor, cerebellar, visual, salience, default mode, executive control, and attentional). Consistent with hypotheses, RSNs from the paralimbic system-insula, anterior and posterior cingulate cortex, amygdala, orbital frontal cortex, and superior temporal gyrus-were related to Factor 1 scores. No significant FNC associations were found with Factor 2 and total PCL-R scores. In summary, results suggest that the affective and interpersonal symptoms of psychopathy (Factor 1) are associated with aberrant connectivity in multiple brain networks, including paralimbic regions. © 2018 Wiley Periodicals, Inc.

  14. Quetiapine modulates functional connectivity in brain aggression networks.

    Science.gov (United States)

    Klasen, Martin; Zvyagintsev, Mikhail; Schwenzer, Michael; Mathiak, Krystyna A; Sarkheil, Pegah; Weber, René; Mathiak, Klaus

    2013-07-15

    Aggressive behavior is associated with dysfunctions in an affective regulation network encompassing amygdala and prefrontal areas such as orbitofrontal (OFC), anterior cingulate (ACC), and dorsolateral prefrontal cortex (DLPFC). In particular, prefrontal regions have been postulated to control amygdala activity by inhibitory projections, and this process may be disrupted in aggressive individuals. The atypical antipsychotic quetiapine successfully attenuates aggressive behavior in various disorders; the underlying neural processes, however, are unknown. A strengthened functional coupling in the prefrontal-amygdala system may account for these anti-aggressive effects. An inhibition of this network has been reported for virtual aggression in violent video games as well. However, there have been so far no in-vivo observations of pharmacological influences on corticolimbic projections during human aggressive behavior. In a double-blind, placebo-controlled study, quetiapine and placebo were administered for three successive days prior to an fMRI experiment. In this experiment, functional brain connectivity was assessed during virtual aggressive behavior in a violent video game and an aggression-free control task in a non-violent modification. Quetiapine increased the functional connectivity of ACC and DLPFC with the amygdala during virtual aggression, whereas OFC-amygdala coupling was attenuated. These effects were observed neither for placebo nor for the non-violent control. These results demonstrate for the first time a pharmacological modification of aggression-related human brain networks in a naturalistic setting. The violence-specific modulation of prefrontal-amygdala networks appears to control aggressive behavior and provides a neurobiological model for the anti-aggressive effects of quetiapine. Copyright © 2013 Elsevier Inc. All rights reserved.

  15. Altered temporal features of intrinsic connectivity networks in boys with combined type of attention deficit hyperactivity disorder

    International Nuclear Information System (INIS)

    Wang, Xun-Heng; Li, Lihua

    2015-01-01

    Highlights: • Temporal patterns within ICNs provide new way to investigate ADHD brains. • ADHD exhibits enhanced temporal activities within and between ICNs. • Network-wise ALFF influences functional connectivity between ICNs. • Univariate patterns within ICNs are correlated to behavior scores. - Abstract: Purpose: Investigating the altered temporal features within and between intrinsic connectivity networks (ICNs) for boys with attention-deficit/hyperactivity disorder (ADHD); and analyzing the relationships between altered temporal features within ICNs and behavior scores. Materials and methods: A cohort of boys with combined type of ADHD and a cohort of age-matched healthy boys were recruited from ADHD-200 Consortium. All resting-state fMRI datasets were preprocessed and normalized into standard brain space. Using general linear regression, 20 ICNs were taken as spatial templates to analyze the time-courses of ICNs for each subject. Amplitude of low frequency fluctuations (ALFFs) were computed as univariate temporal features within ICNs. Pearson correlation coefficients and node strengths were computed as bivariate temporal features between ICNs. Additional correlation analysis was performed between temporal features of ICNs and behavior scores. Results: ADHD exhibited more activated network-wise ALFF than normal controls in attention and default mode-related network. Enhanced functional connectivities between ICNs were found in ADHD. The network-wise ALFF within ICNs might influence the functional connectivity between ICNs. The temporal pattern within posterior default mode network (pDMN) was positively correlated to inattentive scores. The subcortical network, fusiform-related DMN and attention-related networks were negatively correlated to Intelligence Quotient (IQ) scores. Conclusion: The temporal low frequency oscillations of ICNs in boys with ADHD were more activated than normal controls during resting state; the temporal features within ICNs could

  16. Altered temporal features of intrinsic connectivity networks in boys with combined type of attention deficit hyperactivity disorder

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xun-Heng, E-mail: xhwang@hdu.edu.cn [College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018 (China); School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096 (China); Li, Lihua [College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018 (China)

    2015-05-15

    Highlights: • Temporal patterns within ICNs provide new way to investigate ADHD brains. • ADHD exhibits enhanced temporal activities within and between ICNs. • Network-wise ALFF influences functional connectivity between ICNs. • Univariate patterns within ICNs are correlated to behavior scores. - Abstract: Purpose: Investigating the altered temporal features within and between intrinsic connectivity networks (ICNs) for boys with attention-deficit/hyperactivity disorder (ADHD); and analyzing the relationships between altered temporal features within ICNs and behavior scores. Materials and methods: A cohort of boys with combined type of ADHD and a cohort of age-matched healthy boys were recruited from ADHD-200 Consortium. All resting-state fMRI datasets were preprocessed and normalized into standard brain space. Using general linear regression, 20 ICNs were taken as spatial templates to analyze the time-courses of ICNs for each subject. Amplitude of low frequency fluctuations (ALFFs) were computed as univariate temporal features within ICNs. Pearson correlation coefficients and node strengths were computed as bivariate temporal features between ICNs. Additional correlation analysis was performed between temporal features of ICNs and behavior scores. Results: ADHD exhibited more activated network-wise ALFF than normal controls in attention and default mode-related network. Enhanced functional connectivities between ICNs were found in ADHD. The network-wise ALFF within ICNs might influence the functional connectivity between ICNs. The temporal pattern within posterior default mode network (pDMN) was positively correlated to inattentive scores. The subcortical network, fusiform-related DMN and attention-related networks were negatively correlated to Intelligence Quotient (IQ) scores. Conclusion: The temporal low frequency oscillations of ICNs in boys with ADHD were more activated than normal controls during resting state; the temporal features within ICNs could

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

    Directory of Open Access Journals (Sweden)

    Mingsheng Tang

    2014-01-01

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

  18. Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation.

    Science.gov (United States)

    Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Razi, Adeel; Geerligs, Linda; Ham, Timothy E; Rowe, James B

    2016-03-16

    The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population

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

    Science.gov (United States)

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

    2015-10-15

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

  20. Changes in default mode network as automaticity develops in a categorization task.

    Science.gov (United States)

    Shamloo, Farzin; Helie, Sebastien

    2016-10-15

    The default mode network (DMN) is a set of brain regions in which blood oxygen level dependent signal is suppressed during attentional focus on the external environment. Because automatic task processing requires less attention, development of automaticity in a rule-based categorization task may result in less deactivation and altered functional connectivity of the DMN when compared to the initial learning stage. We tested this hypothesis by re-analyzing functional magnetic resonance imaging data of participants trained in rule-based categorization for over 10,000 trials (Helie et al., 2010) [12,13]. The results show that some DMN regions are deactivated in initial training but not after automaticity has developed. There is also a significant decrease in DMN deactivation after extensive practice. Seed-based functional connectivity analyses with the precuneus, medial prefrontal cortex (two important DMN regions) and Brodmann area 6 (an important region in automatic categorization) were also performed. The results show increased functional connectivity with both DMN and non-DMN regions after the development of automaticity, and a decrease in functional connectivity between the medial prefrontal cortex and ventromedial orbitofrontal cortex. Together, these results further support the hypothesis of a strategy shift in automatic categorization and bridge the cognitive and neuroscientific conceptions of automaticity in showing that the reduced need for cognitive resources in automatic processing is accompanied by a disinhibition of the DMN and stronger functional connectivity between DMN and task-related brain regions. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2014-10-01

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

  2. Finite Element Analysis of Reinforced Concrete Beam-Column Connections with Governing Joint Shear Failure Mode

    Directory of Open Access Journals (Sweden)

    M.A. Najafgholipour

    Full Text Available Abstract Reinforced concrete (RC beam-column connections especially those without transverse reinforcement in joint region can exhibit brittle behavior when intensive damage is concentrated in the joint region during an earthquake event. Brittle behavior in the joint region can compromise the ductile design philosophy and the expected overall performance of structure when subjected to seismic loading. Considering the importance of joint shear failure influences on strength, ductility and stability of RC moment resisting frames, a finite element modeling which focuses on joint shear behavior is presented in this article. Nonlinear finite element analysis (FEA of RC beam-column connections is performed in order to investigate the joint shear failure mode in terms of joint shear capacity, deformations and cracking pattern. A 3D finite element model capable of appropriately modeling the concrete stress-strain behavior, tensile cracking and compressive damage of concrete and indirect modeling of steel-concrete bond is used. In order to define nonlinear behavior of concrete material, the concrete damage plasticity is applied to the numerical model as a distributed plasticity over the whole geometry. Finite element model is then verified against experimental results of two non-ductile beam-column connections (one exterior and one interior which are vulnerable to joint shear failure. The comparison between experimental and numerical results indicates that the FE model is able to simulate the performance of the beam-column connections and is able to capture the joint shear failure in RC beam-column connections.

  3. Effect of voltage sags on digitally controlled line connected switched-mode power supplies

    DEFF Research Database (Denmark)

    Török, Lajos; Munk-Nielsen, Stig

    2012-01-01

    Different voltage disorders like voltage fluctuations, sags, frequency variations may occur in the power supply networks due to different fault conditions. These deviations from normal operation affects in different ways the line connected devices. Standards were developed to protect and ensure...... of voltage sags is analyzed. Fault tolerant control algorithm was designed, implemented and is discussed. The fault conditions and their effects were investigated at different power levels....

  4. Disrupted functional connectivity of cerebellar default network areas in attention-deficit/hyperactivity disorder

    Science.gov (United States)

    Kucyi, Aaron; Hove, Michael J.; Biederman, Joseph; Van Dijk, Koene R.A.; Valera, Eve M.

    2015-01-01

    Attention-deficit/hyperactivity disorder (ADHD) is increasingly understood as a disorder of spontaneous brain-network interactions. The default mode network (DMN), implicated in ADHD-linked behaviors including mind-wandering and attentional fluctuations, has been shown to exhibit abnormal spontaneous functional connectivity (FC) within-network and with other networks (salience, dorsal attention and frontoparietal) in ADHD. Although the cerebellum has been implicated in the pathophysiology of ADHD, it remains unknown whether cerebellar areas of the DMN (CerDMN) exhibit altered FC with cortical networks in ADHD. Here, 23 adults with ADHD and 23 age-, IQ-, and sex-matched controls underwent resting state fMRI. The mean time series of CerDMN areas was extracted, and FC with the whole brain was calculated. Whole-brain between-group differences in FC were assessed. Additionally, relationships between inattention and individual differences in FC were assessed for between-group interactions. In ADHD, CerDMN areas showed positive FC (in contrast to average FC in the negative direction in controls) with widespread regions of salience, dorsal attention and sensorimotor networks. ADHD individuals also exhibited higher FC (more positive correlation) of CerDMN areas with frontoparietal and visual network regions. Within the control group, but not in ADHD, participants with higher inattention had higher FC between CerDMN and regions in the visual and dorsal attention networks. This work provides novel evidence of impaired CerDMN coupling with cortical networks in ADHD and highlights a role of the cerebro-cerebellar interactions in cognitive function. These data provide support for the potential targeting of CerDMN areas for therapeutic interventions in ADHD. PMID:26109476

  5. Disrupted functional connectivity of cerebellar default network areas in attention-deficit/hyperactivity disorder.

    Science.gov (United States)

    Kucyi, Aaron; Hove, Michael J; Biederman, Joseph; Van Dijk, Koene R A; Valera, Eve M

    2015-09-01

    Attention-deficit/hyperactivity disorder (ADHD) is increasingly understood as a disorder of spontaneous brain-network interactions. The default mode network (DMN), implicated in ADHD-linked behaviors including mind-wandering and attentional fluctuations, has been shown to exhibit abnormal spontaneous functional connectivity (FC) within-network and with other networks (salience, dorsal attention and frontoparietal) in ADHD. Although the cerebellum has been implicated in the pathophysiology of ADHD, it remains unknown whether cerebellar areas of the DMN (CerDMN) exhibit altered FC with cortical networks in ADHD. Here, 23 adults with ADHD and 23 age-, IQ-, and sex-matched controls underwent resting state fMRI. The mean time series of CerDMN areas was extracted, and FC with the whole brain was calculated. Whole-brain between-group differences in FC were assessed. Additionally, relationships between inattention and individual differences in FC were assessed for between-group interactions. In ADHD, CerDMN areas showed positive FC (in contrast to average FC in the negative direction in controls) with widespread regions of salience, dorsal attention and sensorimotor networks. ADHD individuals also exhibited higher FC (more positive correlation) of CerDMN areas with frontoparietal and visual network regions. Within the control group, but not in ADHD, participants with higher inattention had higher FC between CerDMN and regions in the visual and dorsal attention networks. This work provides novel evidence of impaired CerDMN coupling with cortical networks in ADHD and highlights a role of cerebro-cerebellar interactions in cognitive function. These data provide support for the potential targeting of CerDMN areas for therapeutic interventions in ADHD. © 2015 Wiley Periodicals, Inc.

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

    Directory of Open Access Journals (Sweden)

    Kaitlyn J. Rathwell

    2012-06-01

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

  7. Network science and the effects of music preference on functional brain connectivity: from Beethoven to Eminem.

    Science.gov (United States)

    Wilkins, R W; Hodges, D A; Laurienti, P J; Steen, M; Burdette, J H

    2014-08-28

    Most people choose to listen to music that they prefer or 'like' such as classical, country or rock. Previous research has focused on how different characteristics of music (i.e., classical versus country) affect the brain. Yet, when listening to preferred music--regardless of the type--people report they often experience personal thoughts and memories. To date, understanding how this occurs in the brain has remained elusive. Using network science methods, we evaluated differences in functional brain connectivity when individuals listened to complete songs. We show that a circuit important for internally-focused thoughts, known as the default mode network, was most connected when listening to preferred music. We also show that listening to a favorite song alters the connectivity between auditory brain areas and the hippocampus, a region responsible for memory and social emotion consolidation. Given that musical preferences are uniquely individualized phenomena and that music can vary in acoustic complexity and the presence or absence of lyrics, the consistency of our results was unexpected. These findings may explain why comparable emotional and mental states can be experienced by people listening to music that differs as widely as Beethoven and Eminem. The neurobiological and neurorehabilitation implications of these results are discussed.

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

    Science.gov (United States)

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

    2017-08-01

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

  9. Implementation of fuzzy-sliding mode based control of a grid connected photovoltaic system.

    Science.gov (United States)

    Menadi, Abdelkrim; Abdeddaim, Sabrina; Ghamri, Ahmed; Betka, Achour

    2015-09-01

    The present work describes an optimal operation of a small scale photovoltaic system connected to a micro-grid, based on both sliding mode and fuzzy logic control. Real time implementation is done through a dSPACE 1104 single board, controlling a boost chopper on the PV array side and a voltage source inverter (VSI) on the grid side. The sliding mode controller tracks permanently the maximum power of the PV array regardless of atmospheric condition variations, while The fuzzy logic controller (FLC) regulates the DC-link voltage, and ensures via current control of the VSI a quasi-total transit of the extracted PV power to the grid under a unity power factor operation. Simulation results, carried out via Matlab-Simulink package were approved through experiment, showing the effectiveness of the proposed control techniques. Copyright © 2015. Published by Elsevier Ltd.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Djurfeldt, Mikael

    2012-07-01

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

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

    Science.gov (United States)

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

    2009-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Istvan eMolnar-Szakacs

    2013-09-01

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

  14. Link prediction boosted psychiatry disorder classification for functional connectivity network

    Science.gov (United States)

    Li, Weiwei; Mei, Xue; Wang, Hao; Zhou, Yu; Huang, Jiashuang

    2017-02-01

    Functional connectivity network (FCN) is an effective tool in psychiatry disorders classification, and represents cross-correlation of the regional blood oxygenation level dependent signal. However, FCN is often incomplete for suffering from missing and spurious edges. To accurate classify psychiatry disorders and health control with the incomplete FCN, we first `repair' the FCN with link prediction, and then exact the clustering coefficients as features to build a weak classifier for every FCN. Finally, we apply a boosting algorithm to combine these weak classifiers for improving classification accuracy. Our method tested by three datasets of psychiatry disorder, including Alzheimer's Disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. The experimental results show our method not only significantly improves the classification accuracy, but also efficiently reconstructs the incomplete FCN.

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

    Science.gov (United States)

    Di, Xin; Biswal, Bharat B

    2014-02-01

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

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

    Science.gov (United States)

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

    2018-03-05

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

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

    Science.gov (United States)

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

    2017-12-01

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

  18. Detrital shadows: estuarine food web connectivity depends on fluvial influence and consumer feeding mode.

    Science.gov (United States)

    Howe, Emily; Simenstad, Charles A; Ogston, Andrea

    2017-10-01

    We measured the influence of landscape setting on estuarine food web connectivity in five macrotidal Pacific Northwest estuaries across a gradient of freshwater influence. We used stable isotopes (δ 13 C, δ 15 N, δ 34 S) in combination with a Bayesian mixing model to trace primary producer contributions to suspension- and deposit-feeding bivalve consumers (Mytilus trossulus and Macoma nasuta) transplanted into three estuarine vegetation zones: emergent marsh, mudflat, and eelgrass. Eelgrass includes both Japanese eelgrass (Zostera japonica) and native eelgrass (Zostera marina). Fluvial discharge and consumer feeding mode strongly influenced the strength and spatial scale of observed food web linkages, while season played a secondary role. Mussels displayed strong cross-ecosystem connectivity in all estuaries, with decreasing marine influence in the more fluvial estuaries. Mussel diets indicated homogenization of detrital sources within the water column of each estuary. In contrast, the diets of benthic deposit-feeding clams indicated stronger compartmentalization in food web connectivity, especially in the largest river delta where clam diets were trophically disconnected from marsh sources of detritus. This suggests detritus deposition is patchy across space, and less homogenous than the suspended detritus pool. In addition to fluvial setting, other estuary-specific environmental drivers, such as marsh area or particle transport speed, influenced the degree of food web linkages across space and time, often accounting for unexpected patterns in food web connectivity. Transformations of the estuarine landscape that alter river hydrology or availability of detritus sources can thus potentially disrupt natural food web connectivity at the landscape scale, especially for sedentary organisms, which cannot track their food sources through space. © 2017 by the Ecological Society of America.

  19. Gamification of learning deactivates the Default Mode Network

    Directory of Open Access Journals (Sweden)

    Paul Alexander Howard-Jones

    2016-01-01

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

  20. Gamification of Learning Deactivates the Default Mode Network.

    Science.gov (United States)

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

    2015-01-01

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

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

    OpenAIRE

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

    2016-01-01

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

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

    Science.gov (United States)

    Peng, Z W; Xu, T; He, Q H; Shi, C Z; Wei, Z; Miao, G D; Jing, J; Lim, K O; Zuo, X N; Chan, R C K

    2014-05-01

    Aberrant functional connectivity within the default network is generally assumed to be involved in the pathophysiology of obsessive compulsive disorder (OCD); however, the genetic risk of default network connectivity in OCD remains largely unknown. Here, we systematically investigated default network connectivity in 15 OCD patients, 15 paired unaffected siblings and 28 healthy controls. We sought to examine the profiles of default network connectivity in OCD patients and their siblings, exploring the correlation between abnormal default network connectivity and genetic risk for this population. Compared with healthy controls, OCD patients exhibited reduced strength of default network functional connectivity with the posterior cingulate cortex (PCC), and increased functional connectivity in the right inferior frontal lobe, insula, superior parietal cortex and superior temporal cortex, while their unaffected first-degree siblings only showed reduced local connectivity in the PCC. These findings suggest that the disruptions of default network functional connectivity might be associated with family history of OCD. The decreased default network connectivity in both OCD patients and their unaffected siblings may serve as a potential marker of OCD.

  3. Chaos in complex motor networks induced by Newman—Watts small-world connections

    International Nuclear Information System (INIS)

    Wei Du-Qu; Luo Xiao-Shu; Zhang Bo

    2011-01-01

    We investigate how dynamical behaviours of complex motor networks depend on the Newman—Watts small-world (NWSW) connections. Network elements are described by the permanent magnet synchronous motor (PMSM) with the values of parameters at which each individual PMSM is stable. It is found that with the increase of connection probability p, the motor in networks becomes periodic and falls into chaotic motion as p further increases. These phenomena imply that NWSW connections can induce and enhance chaos in motor networks. The possible mechanism behind the action of NWSW connections is addressed based on stability theory. (interdisciplinary physics and related areas of science and technology)

  4. Connection Management and Recovery Strategies under Epidemic Network Failures in Optical Transport Networks

    DEFF Research Database (Denmark)

    Fagertun, Anna Manolova; Ruepp, Sarah Renée

    2014-01-01

    The current trend in deploying automatic control plane solutions for increased flexibility in the optical transport layer leads to numerous advantages for both the operators and the customers, but also pose challenges related to the stability of the network and its ability to operate in a robust...... manner under attacks. This work proposes four policies for failure handling in a connection-oriented optical transport network, under Generalized MultiProtocol Label Switching control plane, and evaluates their performance under multiple correlated large-scale failures. We employ the Susceptible...... of their transport infrastructures. Applying proactive methods for avoiding areas where epidemic failures spread results in 50% less connections requiring recovery, which translates in improved quality of service to customers....

  5. Multimodal functional network connectivity: an EEG-fMRI fusion in network space.

    Directory of Open Access Journals (Sweden)

    Xu Lei

    Full Text Available EEG and fMRI recordings measure the functional activity of multiple coherent networks distributed in the cerebral cortex. Identifying network interaction from the complementary neuroelectric and hemodynamic signals may help to explain the complex relationships between different brain regions. In this paper, multimodal functional network connectivity (mFNC is proposed for the fusion of EEG and fMRI in network space. First, functional networks (FNs are extracted using spatial independent component analysis (ICA in each modality separately. Then the interactions among FNs in each modality are explored by Granger causality analysis (GCA. Finally, fMRI FNs are matched to EEG FNs in the spatial domain using network-based source imaging (NESOI. Investigations of both synthetic and real data demonstrate that mFNC has the potential to reveal the underlying neural networks of each modality separately and in their combination. With mFNC, comprehensive relationships among FNs might be unveiled for the deep exploration of neural activities and metabolic responses in a specific task or neurological state.

  6. Introspection-based Periodicity Awareness Model for Intermittently Connected Mobile Networks

    NARCIS (Netherlands)

    Türkes, Okan; Scholten, Johan; Havinga, Paul J.M.

    Recently, context awareness in Intermittently Connected Mobile Networks (ICMNs) has gained popularity in order to discover social similarities among mobile entities. Nevertheless, most of the contextual methods depend on network knowledge obtained with unrealistic scenarios. Mobile entities should

  7. Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

    Directory of Open Access Journals (Sweden)

    Christopher E Hart

    2006-12-01

    Full Text Available A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes are explicitly disfavored in one network module (G2, relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of

  8. Aberrant development of functional connectivity among resting state-related functional networks in medication-naïve ADHD children.

    Directory of Open Access Journals (Sweden)

    Jeewook Choi

    Full Text Available OBJECTIVE: The aim of this study was to investigate the compromised developmental trajectory of the functional connectivity among resting-state-related functional networks (RSFNs in medication-naïve children with attention-deficit/hyperactivity disorder (ADHD. SUBJECTS AND METHODS: Using both independent component analysis and dual regression, subject-specific time courses of 12 RSFNs were extracted from both 20 medication-naïve children with ADHD, and 20 age and gender-matched control children showing typical development (TDC. Both partial correlation coefficients among the 12 RSFNs and a resting-state resource allocation index (rsRAI of the salience network (SN were entered into multiple linear regression analysis to investigate the compromised, age-related change in medication-naïve ADHD children. Finally, correlation analyses were performed between the compromised RSFN connections showing significant group-by-age interaction and rsRAI of SN or clinical variables. RESULTS: Medication-naïve ADHD subjects failed to show age-related increment of functional connectivity in both rsRAI of SN and two RSFN connections, SN-Sensory/motor and posterior default mode/precuneus network (pDMN/prec--anterior DMN. Lower SN-Sensory/motor connectivity was related with higher scores on the ADHD Rating Scale, and with poor scores on the continuous performance test. The pDMN/prec-aDMN connectivity was positively related with rsRAI of SN. CONCLUSIONS: Our results suggest that medication-naïve ADHD subjects may have delayed maturation of the two functional connections, SN-Sensory/Motor and aDMN-pDMN/prec. Interventions that enhance the functional connectivity of these two connections may merit attention as potential therapeutic or preventive options in both ADHD and TDC.

  9. Neural Network Prediction of Disruptions Caused by Locked Modes on J-TEXT Tokamak

    International Nuclear Information System (INIS)

    Ding Yonghua; Jin Xuesong; Chen Zhenzhen; Zhuang Ge

    2013-01-01

    Prediction of disruptions caused by locked modes using the Back-Propagation (BP) neural network is completed on J-TEXT tokamak. The network, which is based on the BP neural network, uses Mirnov coils and locked mode coils signals as input data, and outputs a signal including information of prediction of locked mode. The rate of successful prediction of locked modes is more than 90%. For intrinsic locked mode disruptions, the network can give a prewarning signal about 1 ms ahead of the locking-time. For the disruption caused by resonant magnetic perturbation (RMPs) locked modes, the network can give a prewarning signal about 10 ms ahead of the locking-time

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

    Science.gov (United States)

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

    2009-02-01

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

  11. Modelling life trajectories and mode choice using Bayesian belief networks

    NARCIS (Netherlands)

    Verhoeven, M.

    2010-01-01

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

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

    Science.gov (United States)

    Ho, Hung-Jung; Chen, Tien-Chi

    2009-11-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2013-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Young-Ji Byon

    2017-09-01

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

  16. Adaptive Protection Scheme for a Distribution System Considering Grid-Connected and Islanded Modes of Operation

    Directory of Open Access Journals (Sweden)

    Yavuz Ates

    2016-05-01

    Full Text Available The renewable energy-based distributed generation (DG implementation in power systems has been an active research area during the last few decades due to several environmental, economic and political factors. Although the integration of DG offers many advantages, several concerns, including protection schemes in systems with the possibility of bi-directional power flow, are raised. Thus, new protection schemes are strongly required in power systems with a significant presence of DG. In this study, an adaptive protection strategy for a distribution system with DG integration is proposed. The proposed strategy considers both grid-connected and islanded operating modes, while the adaptive operation of the protection is dynamically realized considering the availability of DG power production (related to faults or meteorological conditions in each time step. Besides, the modular structure and fast response of the proposed strategy is validated via simulations conducted on the IEEE 13-node test system.

  17. MDD diagnosis based on partial-brain functional connection network

    Science.gov (United States)

    Yan, Gaoliang; Hu, Hailong; Zhao, Xiang; Zhang, Lin; Qu, Zehui; Li, Yantao

    2018-04-01

    Artificial intelligence (AI) is a hotspot in computer science research nowadays. To apply AI technology in all industries has been the developing direction for researchers. Major depressive disorder (MDD) is a common disease of serious mental disorders. The World Health Organization (WHO) reports that MDD is projected to become the second most common cause of death and disability by 2020. At present, the way of MDD diagnosis is single. Applying AI technology to MDD diagnosis and pathophysiological research will speed up the MDD research and improve the efficiency of MDD diagnosis. In this study, we select the higher degree of brain network functional connectivity by statistical methods. And our experiments show that the average accuracy of Logistic Regression (LR) classifier using feature filtering reaches 88.48%. Compared with other classification methods, both the efficiency and accuracy of this method are improved, which will greatly improve the process of MDD diagnose. In these experiments, we also define the brain regions associated with MDD, which plays a vital role in MDD pathophysiological research.

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

    Science.gov (United States)

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

    2011-05-01

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

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

    Science.gov (United States)

    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.

  20. Study on Communication Mode of Wireless Sensor Networks Based on Effective Result

    International Nuclear Information System (INIS)

    Shi, J F; Zhong, X X; Chen, S

    2006-01-01

    The key challenge in wireless sensor networks is maximizing network lifetime. It will significantly reduce energy consumption of communication and prolong networks lifetime to choose appropriate communication mode. In this paper, energy model and communication topology are proposed, and then from the viewpoint of effective result, expression for communication energy cost of single sensor node and overall system in different communication mode is derived, impact that sensor nodes amount, communication radius and propagation loss exponent pose on communication mode based on simulations is analyzed, and the justification for choosing communication mode is summarized

  1. Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

    Science.gov (United States)

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

    2016-03-29

    We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

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

    KAUST Repository

    Elsawy, Hesham

    2014-11-01

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

  3. The effect of regulatory mode on procrastination: Bi-stable parahippocampus connectivity with dorsal anterior cingulate and anterior prefrontal cortex.

    Science.gov (United States)

    Zhang, Chenyan; Ni, Yan; Feng, Tingyong

    2017-06-30

    Previous research has elucidated that procrastination can be influenced by regulatory mode orientations. However, the neural mechanism of regulatory modes affecting procrastination is not well understood. To address this question, we employed resting-state functional magnetic resonance imaging (RS-fMRI) to test the influence of two regulatory modes (assessment and locomotion) on procrastination. The behavioral results showed that procrastination was positively correlated with assessment orientation but negatively correlated with locomotion orientation. Neuroimaging results indicated that the functional connectivity between parahippocampal cortex (PHC) and dorsal anterior cingulate (dACC) was negatively correlated with assessment scores, while the functional connectivity between anterior prefrontal cortex (aPFC) and parahippocampal cortex (PHC) was negatively correlated with locomotion scores. Critically, mediation analysis showed that the different effects of two distinct regulatory modes on procrastination were mediated by PHC-dACC and aPFC-PHC functional connectivity respectively. These results suggested that people's procrastination could be predicted by regulatory mode orientations, which is mediated by PHC connectivity with dACC and aPFC respectively. The present study extends our knowledge on procrastination and provides neural mechanism for understanding the link between regulatory mode orientations and procrastination. Copyright © 2017. Published by Elsevier B.V.

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

    Science.gov (United States)

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

    2017-09-16

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

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

    Science.gov (United States)

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

    2017-01-01

    The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants’ awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns. PMID:28917059

  6. Abnormal Functional Connectivity of Resting State Network Detection Based on Linear ICA Analysis in Autism Spectrum Disorder.

    Science.gov (United States)

    Bi, Xia-An; Zhao, Junxia; Xu, Qian; Sun, Qi; Wang, Zhigang

    2018-01-01

    Some functional magnetic resonance imaging (fMRI) researches in autism spectrum disorder (ASD) patients have shown that ASD patients have significant impairment in brain response. However, few researchers have studied the functional structure changes of the eight resting state networks (RSNs) in ASD patients. Therefore, research on statistical differences of RSNs between 42 healthy controls (HC) and 50 ASD patients has been studied using linear independent component analysis (ICA) in this paper. Our researches showed that there was abnormal functional connectivity (FC) of RSNs in ASD patients. The RSNs with the decreased FC and increased FC in ASD patients included default mode network (DMN), central executive network (CEN), core network (CN), visual network (VN), self-referential network (SRN) compared to HC. The RSNs with the increased FC in ASD patients included auditory network (AN), somato-motor network (SMN). The dorsal attention network (DAN) in ASD patients showed the decreased FC. Our findings indicate that the abnormal FC in RSNs extensively exists in ASD patients. Our results have important contribution for the study of neuro-pathophysiological mechanisms in ASD patients.

  7. Photovoltaic power, lithium batteries and network connection; Energia fotovoltaica, baterias de litio e conexao a rede

    Energy Technology Data Exchange (ETDEWEB)

    Schmiegel, A.U.; Koch, K.; Meissner, A.; Knaup, P. [Voltwerk Electronics (Germany); Jehoulet, C.; Schuh, H. [Saft Batteries (France); Landau, M.; Braun, M.; Bundenbender, K.; Geipel, R.; Vachette, C. [Fraunhofer IWES (Germany); Sauer, D.-U.; Magnor, D. [RWTH Aachen University (Germany). Institute for Solar Energy Systems - ISEA; Marcel, J.-C. [Tenosol (France)

    2011-11-15

    The Sun-ion, the system described in this article, combines storage technology based on the lithium ions with the high efficiency photovoltaic inverters, and supports two philosophies for personal use: off-grid, where the loads are directly connected to the inverter; and connected to the network, which makes up their own consumption when the load balancing in the network connection is zero. Performance measurements demonstrate the feasibility of the concept.

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

    Science.gov (United States)

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

    2017-12-01

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

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

    OpenAIRE

    Tao, Yong; Zheng, Jiaqi; Lin, Yuanchang

    2016-01-01

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

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

    Science.gov (United States)

    Li, Z.; Li, C.

    2017-12-01

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

  11. Salience and Default Mode Network Coupling Predicts Cognition in Aging and Parkinson's Disease.

    Science.gov (United States)

    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.

  12. Internal and external attention and the default mode network.

    Science.gov (United States)

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

    2017-03-01

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

  13. Reentrant Information Flow in Electrophysiological Rat Default Mode Network.

    Science.gov (United States)

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

    2017-01-01

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

  14. Impact of connected vehicle guidance information on network-wide average travel time

    Directory of Open Access Journals (Sweden)

    Jiangfeng Wang

    2016-12-01

    Full Text Available With the emergence of connected vehicle technologies, the potential positive impact of connected vehicle guidance on mobility has become a research hotspot by data exchange among vehicles, infrastructure, and mobile devices. This study is focused on micro-modeling and quantitatively evaluating the impact of connected vehicle guidance on network-wide travel time by introducing various affecting factors. To evaluate the benefits of connected vehicle guidance, a simulation architecture based on one engine is proposed representing the connected vehicle–enabled virtual world, and connected vehicle route guidance scenario is established through the development of communication agent and intelligent transportation systems agents using connected vehicle application programming interface considering the communication properties, such as path loss and transmission power. The impact of connected vehicle guidance on network-wide travel time is analyzed by comparing with non-connected vehicle guidance in response to different market penetration rate, following rate, and congestion level. The simulation results explore that average network-wide travel time in connected vehicle guidance shows a significant reduction versus that in non–connected vehicle guidance. Average network-wide travel time in connected vehicle guidance have an increase of 42.23% comparing to that in non-connected vehicle guidance, and average travel time variability (represented by the coefficient of variance increases as the travel time increases. Other vital findings include that higher penetration rate and following rate generate bigger savings of average network-wide travel time. The savings of average network-wide travel time increase from 17% to 38% according to different congestion levels, and savings of average travel time in more serious congestion have a more obvious improvement for the same penetration rate or following rate.

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

    Science.gov (United States)

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

    2015-06-17

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

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

    Directory of Open Access Journals (Sweden)

    T. Sigi eHale

    2014-07-01

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

  17. Connecting the Dots: Understanding the Flow of Research Knowledge within a Research Brokering Network

    Science.gov (United States)

    Rodway, Joelle

    2015-01-01

    Networks are frequently cited as an important knowledge mobilization strategy; however, there is little empirical research that considers how they connect research and practice. Taking a social network perspective, I explore how central office personnel find, understand and share research knowledge within a research brokering network. This mixed…

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

    OpenAIRE

    Opdam, P.F.M.

    2014-01-01

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

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

    OpenAIRE

    Hussein, Abd Ali

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Yundi Chu

    2015-01-01

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

  1. Multi-mode optical fibers for connecting space-based spectrometers

    Science.gov (United States)

    Roberts, W. T.; Lindenmisth, C. A.; Bender, S.; Miller, E. A.; Motts, E.; Ott, M.; LaRocca, F.; Thomes, J.

    2017-11-01

    significantly smaller, less massive and less robust. Large core multi-mode optical fibers are often used to accommodate the optical connection of the two separated portions of such instrumentation. In some cases, significant throughput efficiency improvement can be realized by judiciously orienting the strands of multi-fiber cable, close-bunching them to accommodate a tight focus of the optical system on the optical side of the connection, and splaying them out linearly along a spectrometer slit on the other end. For such instrumentation to work effectively in identifying elements and molecules, and especially to produce accurate quantitative results, the spectral throughput of the optical fiber connection must be consistent over varying temperatures, over the range of motion of the optical head (and it's implied optical cable stresses), and over angle-aperture invariant of the total system. While the first two of these conditions have been demonstrated[4], spectral observations of the latter present a cause for concern, and may have an impact on future design of fiber-connected LIBS and Raman spectroscopy instruments. In short, we have observed that the shape of the spectral efficiency curve of a large multi-mode core optical fiber changes as a function of input angle.

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

    Science.gov (United States)

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

    2016-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Ye. I. Sokol

    2017-06-01

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

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

    Science.gov (United States)

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

    2017-07-01

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

  5. Structural and functional abnormalities of default mode network in minimal hepatic encephalopathy: a study combining DTI and fMRI.

    Directory of Open Access Journals (Sweden)

    Rongfeng Qi

    Full Text Available BACKGROUND AND PURPOSE: Live failure can cause brain edema and aberrant brain function in cirrhotic patients. In particular, decreased functional connectivity within the brain default-mode network (DMN has been recently reported in overt hepatic encephalopathy (HE patients. However, so far, little is known about the connectivity among the DMN in the minimal HE (MHE, the mildest form of HE. Here, we combined diffusion tensor imaging (DTI and resting-state functional MRI (rs-fMRI to test our hypothesis that both structural and functional connectivity within the DMN were disturbed in MHE. MATERIALS AND METHODS: Twenty MHE patients and 20 healthy controls participated in the study. We explored the changes of structural (path length, tracts count, fractional anisotropy [FA] and mean diffusivity [MD] derived from DTI tractography and functional (temporal correlation coefficient derived from rs-fMRI connectivity of the DMN in MHE patients. Pearson correlation analysis was performed between the structural/functional indices and venous blood ammonia levels/neuropsychological tests scores of patients. All thresholds were set at P<0.05, Bonferroni corrected. RESULTS: Compared to the healthy controls, MHE patients showed both decreased FA and increased MD in the tract connecting the posterior cingulate cortex/precuneus (PCC/PCUN to left parahippocampal gyrus (PHG, and decreased functional connectivity between the PCC/PCUN and left PHG, and medial prefrontal cortex (MPFC. MD values of the tract connecting PCC/PCUN to the left PHG positively correlated to the ammonia levels, the temporal correlation coefficients between the PCC/PCUN and the MPFC showed positive correlation to the digital symbol tests scores of patients. CONCLUSION: MHE patients have both disturbed structural and functional connectivity within the DMN. The decreased functional connectivity was also detected between some regions without abnormal structural connectivity, suggesting that the

  6. Sliding-Mode Controller for Maximum Power Point Tracking in Grid-Connected Photovoltaic Systems

    Directory of Open Access Journals (Sweden)

    Paula Andrea Ortiz Valencia

    2015-11-01

    Full Text Available The maximum power point tracking (MPPT of photovoltaic systems must be as fast and accurate as possible to increase the power production, which eventually increases the PV system profitability. This paper proposes and mathematically analyses a sliding-mode controller to provide a fast and accurate maximum power point tracking in grid-connected photovoltaic systems using a single control stage. This approach avoids the circular dependency in the design of classical cascade controllers used to optimize the photovoltaic system operation, and at the same time, it reduces the number of controllers and avoids the use of linearized models to provide global stability in all the operation range. Such a compact solution also reduces the system cost and implementation complexity. To ensure the stability of the proposed solution, detailed mathematical analyses are performed to demonstrate the fulfillment of the transversality, reachability and equivalent control conditions. Finally, the performance of the proposed solution is validated using detailed simulations, executed in the power electronics simulator PSIM, accounting for both environmental and load perturbations.

  7. Experimental Study of a Centralized Control Strategy of a DC Microgrid Working in Grid Connected Mode

    Directory of Open Access Journals (Sweden)

    Robert Salas-Puente

    2017-10-01

    Full Text Available The results concerning the integration of a set of power management strategies and serial communications for the efficient coordination of the power converters composing an experimental DC microgrid is presented. The DC microgrid operates in grid connected mode by means of an interlinking converter. The overall control is carried out by means of a centralized microgrid controller implemented on a Texas Instruments TMS320F28335 DSP. The main objectives of the applied control strategies are to ensure the extract/inject power limits established by the grid operator as well as the renewable generation limits if it is required; to devise a realistic charging procedure of the energy storage batteries as a function of the microgrid status; to manage sudden changes of the available power from the photovoltaic energy sources, of the load power demand and of the power references established by the central controller; and to implement a load shedding functionality. The experimental results demonstrate that the proposed power management methodology allows the control of the power dispatch inside the DC microgrid properly.

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

    Science.gov (United States)

    Kesler, Shelli R.

    2014-01-01

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

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

    Science.gov (United States)

    Gao, Wenbo; Cvijetic, Milorad

    2018-04-01

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

  10. Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

    Science.gov (United States)

    Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán

    2017-01-01

    Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.

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

    Science.gov (United States)

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

    2015-01-01

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

  12. Logistics Mode and Network Planning for Recycle of Crop Straw Resources

    OpenAIRE

    Zhou, Lingyun; Gu, Weidong; Zhang, Qing

    2013-01-01

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

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

    OpenAIRE

    Kirwin, John P.

    1999-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Dan eZhu

    2014-05-01

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

  15. Functional organization of intrinsic connectivity networks in Chinese-chess experts.

    Science.gov (United States)

    Duan, Xujun; Long, Zhiliang; Chen, Huafu; Liang, Dongmei; Qiu, Lihua; Huang, Xiaoqi; Liu, Timon Cheng-Yi; Gong, Qiyong

    2014-04-16

    The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low-frequency coherent neuronal fluctuations during a resting state condition. Accumulating evidence suggests that the overall organization of functional connectivity networks is associated with individual differences in cognitive performance and prior experience. Such an association raises the question of how cognitive expertise exerts an influence on the topological properties of large-scale functional networks. To address this question, we examined the overall organization of brain functional networks in 20 grandmaster and master level Chinese-chess players (GM/M) and twenty novice players, by means of resting-state functional connectivity and graph theoretical analyses. We found that, relative to novices, functional connectivity was increased in GM/Ms between basal ganglia, thalamus, hippocampus, and several parietal and temporal areas, suggesting the influence of cognitive expertise on intrinsic connectivity networks associated with learning and memory. Furthermore, we observed economical small-world topology in the whole-brain functional connectivity networks in both groups, but GM/Ms exhibited significantly increased values of normalized clustering coefficient which resulted in increased small-world topology. These findings suggest an association between the functional organization of brain networks and individual differences in cognitive expertise, which might provide further evidence of the mechanisms underlying expert behavior. Copyright © 2014 Elsevier B.V. All rights reserved.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-07-01

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

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

    Science.gov (United States)

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

    2017-09-01

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

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

    Science.gov (United States)

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

    2013-12-30

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

  19. Polymeric electrochemical element for adaptive networks: Pulse mode

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  20. Wireless sensor communications and internet connectivity for sensor networks

    Energy Technology Data Exchange (ETDEWEB)

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

    2001-07-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  2. On the Connectivity of Wireless Network Systems and an Application in Teacher-Student Interactive Platforms

    Directory of Open Access Journals (Sweden)

    Xun Ge

    2014-01-01

    Full Text Available A wireless network system is a pair (U;B, where B is a family of some base stations and U is a set of their users. To investigate the connectivity of wireless network systems, this paper takes covering approximation spaces as mathematical models of wireless network systems. With the help of covering approximation operators, this paper characterizes the connectivity of covering approximation spaces by their definable subsets. Furthermore, it is obtained that a wireless network system is connected if and only if the relevant covering approximation space has no nonempty definable proper subset. As an application of this result, the connectivity of a teacher-student interactive platform is discussed, which is established in the School of Mathematical Sciences of Soochow University. This application further demonstrates the usefulness of rough set theory in pedagogy and makes it possible to research education by logical methods and mathematical methods.

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

    Science.gov (United States)

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

    2013-01-01

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

  4. Traffic grooming in WDM optical network with grooming resources at Max Connectivity nodes

    Science.gov (United States)

    Paul, Partha; Rawat, Balbeer Singh; Ghorai, S. K.

    2012-12-01

    In this paper, we propose Max Connectivity grooming in WDM mesh networks under static lightpath connection requests. The grooming and wavelength conversion resources are placed at the nodes having maximum connections. We propose a heuristic genetic algorithm (GA) model to solve grooming, routing and wavelength assignment. The GA algorithm has been used to optimize the cost of grooming and wavelength conversion resources. The blocking probability has been investigated under different lightpath connections. The performance of Max Connectivity grooming has been compared with other grooming policies. Our results indicate the improvement of resource utilization with minimum blocking probability.

  5. Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

    Science.gov (United States)

    Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

    2018-01-01

    Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are

  6. THE OPERATION MODES OPTIMIZATION OF THE NEUTRAL DISTRIBUTION NETWORKS

    Directory of Open Access Journals (Sweden)

    F. P. Shkarbets

    2009-03-01

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

  7. Inventory theory, mode choice and network structure in freight transport

    NARCIS (Netherlands)

    Combes, F.; Tavasszy, L.A.

    2016-01-01

    In passenger transport, hub-and-spoke networks allow the transportation of small passenger flows with competitive frequencies, in a way that direct line networks cannot. Equivalently, in freight transport, it can be expected that small shipper-receiver flows of high added value commodities transit

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

    Directory of Open Access Journals (Sweden)

    V. I. Lukovnikov

    2005-01-01

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

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

    Science.gov (United States)

    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.

  10. The default modes of reading: Modulation of posterior cingulate and medial prefrontal cortex connectivity associated with subjective and objective differences in reading experience

    Directory of Open Access Journals (Sweden)

    Jonathan eSmallwood

    2013-11-01

    Full Text Available Reading is a fundamental human capacity and yet it can easily be derailed by the simple act of mind-wandering. A large-scale brain network, referred to as the default mode network (DMN, has been shown to be involved in both mind-wandering and reading, raising the question as to how the same neural system could be implicated in processes with both costs and benefits to narrative comprehension. Resting-state functional magnetic resonance imaging (rs-fMRI was used to explore whether the intrinsic functional connectivity of the two key midline hubs of the DMN — the posterior cingulate (PCC and medial prefrontal cortex (aMPFC — was predictive of individual differences in reading effectiveness (better comprehension, superior and task focus recorded outside of the scanner. Worse comprehension was associated with greater functional connectivity between the PCC and a region of the ventral striatum. By contrast reports of increasing task focus were associated with functional connectivity from the aMPFC to clusters in the PCC, the left parietal and temporal cortex, and the cerebellum. Our results suggest that the DMN has both costs (such as poor comprehension and benefits to reading (such as an on-task focus because its midline core can couple its activity with other regions to form distinct functional communities that allow seemingly opposing mental states to occur. This flexible coupling allows the DMN to participate in cognitive states that complement the act of reading as well as others that do not.

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

    Science.gov (United States)

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

    2017-01-01

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

  12. Topological probability and connection strength induced activity in complex neural networks

    International Nuclear Information System (INIS)

    Du-Qu, Wei; Bo, Zhang; Dong-Yuan, Qiu; Xiao-Shu, Luo

    2010-01-01

    Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world (SW) connections. Network elements are described by two-dimensional map neurons (2DMNs) with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied. (general)

  13. Connection of OWPPs to HVDC networks using VSCs and Diode Rectifiers: an Overview

    DEFF Research Database (Denmark)

    Saborío-Romano, Oscar; Bidadfar, Ali; Göksu, Ömer

    This paper provides an overview of two technologies for connecting offshore wind power plants (offshore WPPs, OWPPs) to high-voltage direct current (HVDC) networks: voltage source converters (VSCs) and diode rectifiers (DRs). Current grid code requirements for the connection of such power plants...

  14. Community access networks: how to connect the next billion to the ...

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

    Community access networks: how to connect the next billion to the Internet. Despite recent progress with mobile technology diffusion, more than four billion people worldwide are unconnected and have limited access to global communication infrastructure. The cost of implementing connectivity infrastructure in underserved ...

  15. A Riding-through Technique for Seamless Transition between Islanded and Grid-Connected Modes of Droop-Controlled Inverters

    DEFF Research Database (Denmark)

    Hu, Shang-hung; Lee, Tzung-Lin; Kuo, Chun-Yi

    2016-01-01

    This paper presents a seamless transition method for a droop-controlled inverter. The droop control is suitable to make the inverter work as a voltage source in both islanded and grid-connected modes, however, the transfer between theses modes can result in a big inrush current that may damage...... a smooth transition between them, requiring neither synchronization signals nor grid-side information. The control algorithm and design procedure are presented. Experimental results from a laboratory prototype validate the effectiveness of the proposed method....... the system. The proposed method allows the droop-controlled inverter to improve the transient response when transferring between modes, by detecting the inrush current, activating a current control loop during transients, and then transferring back to droop-controlled mode smoothly by using a virtual...

  16. Changes in dynamic resting state network connectivity following aphasia therapy.

    Science.gov (United States)

    Duncan, E Susan; Small, Steven L

    2017-10-24

    Resting state magnetic resonance imaging (rsfMRI) permits observation of intrinsic neural networks produced by task-independent correlations in low frequency brain activity. Various resting state networks have been described, with each thought to reflect common engagement in some shared function. There has been limited investigation of the plasticity in these network relationships after stroke or induced by therapy. Twelve individuals with language disorders after stroke (aphasia) were imaged at multiple time points before (baseline) and after an imitation-based aphasia therapy. Language assessment using a narrative production task was performed at the same time points. Group independent component analysis (ICA) was performed on the rsfMRI data to identify resting state networks. A sliding window approach was then applied to assess the dynamic nature of the correlations among these networks. Network correlations during each 30-second window were used to cluster the data into ten states for each window at each time point for each subject. Correlation was performed between changes in time spent in each state and therapeutic gains on the narrative task. The amount of time spent in a single one of the (ten overall) dynamic states was positively associated with behavioral improvement on the narrative task at the 6-week post-therapy maintenance interval, when compared with either baseline or assessment immediately following therapy. This particular state was characterized by minimal correlation among the task-independent resting state networks. Increased functional independence and segregation of resting state networks underlies improvement on a narrative production task following imitation-based aphasia treatment. This has important clinical implications for the targeting of noninvasive brain stimulation in post-stroke remediation.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-04-13

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

  19. Graph Analysis and Modularity of Brain Functional Connectivity Networks: Searching for the Optimal Threshold

    Directory of Open Access Journals (Sweden)

    Cécile Bordier

    2017-08-01

    Full Text Available Neuroimaging data can be represented as networks of nodes and edges that capture the topological organization of the brain connectivity. Graph theory provides a general and powerful framework to study these networks and their structure at various scales. By way of example, community detection methods have been widely applied to investigate the modular structure of many natural networks, including brain functional connectivity networks. Sparsification procedures are often applied to remove the weakest edges, which are the most affected by experimental noise, and to reduce the density of the graph, thus making it theoretically and computationally more tractable. However, weak links may also contain significant structural information, and procedures to identify the optimal tradeoff are the subject of active research. Here, we explore the use of percolation analysis, a method grounded in statistical physics, to identify the optimal sparsification threshold for community detection in brain connectivity networks. By using synthetic networks endowed with a ground-truth modular structure and realistic topological features typical of human brain functional connectivity networks, we show that percolation analysis can be applied to identify the optimal sparsification threshold that maximizes information on the networks' community structure. We validate this approach using three different community detection methods widely applied to the analysis of brain connectivity networks: Newman's modularity, InfoMap and Asymptotical Surprise. Importantly, we test the effects of noise and data variability, which are critical factors to determine the optimal threshold. This data-driven method should prove particularly useful in the analysis of the community structure of brain networks in populations characterized by different connectivity strengths, such as patients and controls.

  20. Geometry of river networks. III. Characterization of component connectivity

    International Nuclear Information System (INIS)

    Dodds, Peter Sheridan; Rothman, Daniel H.

    2001-01-01

    Essential to understanding the overall structure of river networks is a knowledge of their detailed architecture. Here we explore the presence of randomness in river network structure and the details of its consequences. We first show that an averaged view of network architecture is provided by a proposed self-similarity statement about the scaling of drainage density, a local measure of stream concentration. This scaling of drainage density is shown to imply Tokunaga's law, a description of the scaling of side branch abundance along a given stream, as well as a scaling law for stream lengths. We then consider fluctuations in drainage density and consequently the numbers of side branches. Data are analyzed for the Mississippi River basin and a model of random directed networks. Numbers of side streams are found to follow exponential distributions, as are intertributary distances along streams. Finally, we derive a joint variation of side stream abundance with stream length, affording a full description of fluctuations in network structure. Fluctuations in side stream numbers are shown to be a direct result of fluctuations in stream lengths. This is the last paper in a series of three on the geometry of river networks

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

    Science.gov (United States)

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

    2017-08-28

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

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

    Science.gov (United States)

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

    2018-01-01

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

  3. Effect of wind generation system types on Micro-Grid (MG) fault performance during both standalone and grid connected modes

    International Nuclear Information System (INIS)

    Kamel, Rashad M.

    2014-01-01

    Highlights: • This paper evaluated the effects of different wind system types on fault performance of Micro-Grid. • Both standalone and grid connected modes are considered. • The MG earthing system configuration is taken in consideration. - Abstract: Recently, there are three wind generation (WG) system types. The first type is called Fixed Speed Wind Generation (FSWG) system, which employs squirrel cage induction generators. Double Fed Induction Generator (DFIG) is utilized in the second type. The third type is called Full Converter Wind Generation (FCWG) system, which is interfaced with Micro-Grid (MG) through a back to back converter. During fault occurrence, each WG has its performance and characteristics which are determined by the generator physical characteristics and the MG earthing system configuration. For some WG types, the fault current depends also on the control algorithm of the power converter. The main target of this paper is to investigate and estimate how the fault performance of MG during both standalone and grid-connected modes is influenced by the type of WG. It is found during standalone mode that the type of the employed WG has a dominant impact on the MG performance under fault disturbance. On the contrary, the type of the employed WG has a negligible effect on the MG fault performance during grid-connected mode. This is because the main grid contributes most of the fault current. Effects of earthing system type on MG performance are highlighted

  4. Extended Kalman Filter Based Sliding Mode Control of Parallel-Connected Two Five-Phase PMSM Drive System

    Directory of Open Access Journals (Sweden)

    Tounsi Kamel

    2018-01-01

    Full Text Available This paper presents sliding mode control of sensor-less parallel-connected two five-phase permanent magnet synchronous machines (PMSMs fed by a single five-leg inverter. For both machines, the rotor speeds and rotor positions as well as load torques are estimated by using Extended Kalman Filter (EKF scheme. Fully decoupled control of both machines is possible via an appropriate phase transposition while connecting the stator windings parallel and employing proposed speed sensor-less method. In the resulting parallel-connected two-machine drive, the independent control of each machine in the group is achieved by controlling the stator currents and speed of each machine under vector control consideration. The effectiveness of the proposed Extended Kalman Filter in conjunction with the sliding mode control is confirmed through application of different load torques for wide speed range operation. Comparison between sliding mode control and PI control of the proposed two-motor drive is provided. The speed response shows a short rise time, an overshoot during reverse operation and settling times is 0.075 s when PI control is used. The speed response obtained by SMC is without overshoot and follows its reference and settling time is 0.028 s. Simulation results confirm that, in transient periods, sliding mode controller remarkably outperforms its counterpart PI controller.

  5. Social Connection Dynamics in a Health Promotion Network

    NARCIS (Netherlands)

    Fernandes de Mello Araujo, Eric; Klein, Michel; van Halteren, Aart

    2016-01-01

    The influence of social connections on human behaviour has been demonstrated in many occasions. This paper presents the analysis of the dynamic properties of longitudinal (335 days) community data (n=3,375 participants) from an online health promotion program. The community data is unique as it

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

    Directory of Open Access Journals (Sweden)

    Tat-Bao-Thien Nguyen

    2014-01-01

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

  7. Cost and Availability Analysis of 2- and 3-Connected WDM Networks Physical Interconnection

    DEFF Research Database (Denmark)

    Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir; Pedersen, Jens Myrup

    2012-01-01

    for the best trade-off among the relevant parameters for the network. In this paper we analyze this trade-off by studying 2-and 3-connected graphs to be used as WDM (Wavelength Division Multiplexing) networks physical infrastructure. The experiments show how the way links are distributed to interconnect...

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

    International Nuclear Information System (INIS)

    Koroutchev, K.; Korutcheva, E.

    2004-09-01

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

  9. Network performance, hub connectivity potential, and competitive position of primary airports in Asia/Pacific region

    NARCIS (Netherlands)

    Matsumoto, H.; Veldhuis, J.; de Wit, J.; Burghouwt, G.

    2008-01-01

    Recently, hub-and-spoke network configurations are more and more developed in the Asia/Pacific region. In this paper, it is argued that the measurement of network performance in hub-and-spoke systems should take into account the quantity and quality of both direct and indirect connections. The

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

    Science.gov (United States)

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

    2010-04-01

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

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

    International Nuclear Information System (INIS)

    Janaki, T.M.; Gupte, Neelima

    2003-01-01

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

  12. Measurement campaign on connectivity of mesh networks formed by mobile devices

    DEFF Research Database (Denmark)

    Pietrarca, Beatrice; Sasso, Giovanni; Perrucci, Gian Paolo

    2007-01-01

    This paper reports the results of a measurement campaign on the connectivity level of mobile devices using Bluetooth (BT) to form cooperative mobile mesh networks. Such mobile mesh networks composed of mobile devices are the basis for any peer-to-peer communication like wireless grids or social...

  13. A fully connected network of Bernoulli units with correlation learning

    Science.gov (United States)

    Dente, J. A.; Vilela Mendes, R.

    1996-02-01

    Biological evidence suggests that pattern recognition and associative memory in the mammalian nervous system operates through the establishment of spatio-temporal patterns of activity and not by the evolution towards an equilibrium point as in attractor neural networks. Information is carried by the space-time correlation of the activity intensities rather than by the details of individual neuron signals. Furthermore the fast recognition times that are achieved with relatively slow biological neurons seem to be associated to the chaotic nature of the basal nervous activity. To copy the biology hardware may not be technologically sound, but to look for inspiration in the efficient biological information processing methods is an idea that deserves consideration. Inspired by the mechanisms at work in the mammalian olfactory system we study a network where, in the absence of external inputs, the units have a dynamics of the Bernoulli shift type. When an external signal is presented, the pattern of excitation bursts depends on the learning history of the network. Association and pattern identification in the network operates by the selection, by the external stimulus, of distinct invariant measures in the chaotic system. The simplicity of the node dynamics, that is chosen, allows a reasonable analytical control of the network behavior.

  14. Flexible Control of Small Wind Turbines With Grid Failure Detection Operating in Stand-Alone and Grid-Connected Mode

    DEFF Research Database (Denmark)

    Teodorescu, Remus; Blaabjerg, Frede

    2004-01-01

    nonlinear load and excess or deficit of generated power. Grid-connection mode with current control is also enabled for the case of isolated local grid involving other dispersed power generators such as other wind turbines or diesel generators. A novel automatic mode switch method based on a phase......-to-back power conversion configuration is chosen where the generator converter uses a built-in standard flux vector control to control the speed of the turbine shaft while the grid-side converter uses a standard pulse-width modulation active rectifier control strategy implemented in a DSP controller. The design...

  15. An efficient optical architecture for sparsely connected neural networks

    Science.gov (United States)

    Hine, Butler P., III; Downie, John D.; Reid, Max B.

    1990-01-01

    An architecture for general-purpose optical neural network processor is presented in which the interconnections and weights are formed by directing coherent beams holographically, thereby making use of the space-bandwidth products of the recording medium for sparsely interconnected networks more efficiently that the commonly used vector-matrix multiplier, since all of the hologram area is in use. An investigation is made of the use of computer-generated holograms recorded on such updatable media as thermoplastic materials, in order to define the interconnections and weights of a neural network processor; attention is given to limits on interconnection densities, diffraction efficiencies, and weighing accuracies possible with such an updatable thin film holographic device.

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

    Science.gov (United States)

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

    2014-08-01

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

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

    CERN Document Server

    McManus, Sean

    2010-01-01

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

  18. Network-based analysis reveals functional connectivity related to internet addiction tendency

    Directory of Open Access Journals (Sweden)

    Tanya eWen

    2016-02-01

    Full Text Available IntroductionPreoccupation and compulsive use of the internet can have negative psychological effects, such that it is increasingly being recognized as a mental disorder. The present study employed network-based statistics to explore how whole-brain functional connections at rest is related to the extent of individual’s level of internet addiction, indexed by a self-rated questionnaire. We identified two topologically significant networks, one with connections that are positively correlated with internet addiction tendency, and one with connections negatively correlated with internet addiction tendency. The two networks are interconnected mostly at frontal regions, which might reflect alterations in the frontal region for different aspects of cognitive control (i.e., for control of internet usage and gaming skills. Next, we categorized the brain into several large regional subgroupings, and found that the majority of proportions of connections in the two networks correspond to the cerebellar model of addiction which encompasses the four-circuit model. Lastly, we observed that the brain regions with the most inter-regional connections associated with internet addiction tendency replicate those often seen in addiction literature, and is corroborated by our meta-analysis of internet addiction studies. This research provides a better understanding of large-scale networks involved in internet addiction tendency and shows that pre-clinical levels of internet addiction are associated with similar regions and connections as clinical cases of addiction.

  19. Functional Connectivity Between Anterior Insula and Key Nodes of Frontoparietal Executive Control and Salience Networks Distinguish Bipolar Depression From Unipolar Depression and Healthy Control Subjects.

    Science.gov (United States)

    Ellard, Kristen K; Zimmerman, Jared P; Kaur, Navneet; Van Dijk, Koene R A; Roffman, Joshua L; Nierenberg, Andrew A; Dougherty, Darin D; Deckersbach, Thilo; Camprodon, Joan A

    2018-05-01

    Patients with bipolar depression are characterized by dysregulation across the full spectrum of mood, differentiating them from patients with unipolar depression. The ability to switch neural resources among the default mode network, salience network, and executive control network (ECN) has been proposed as a key mechanism for adaptive mood regulation. The anterior insula is implicated in the modulation of functional network switching. Differential connectivity between anterior insula and functional networks may provide insights into pathophysiological differences between bipolar and unipolar mood disorders, with implications for diagnosis and treatment. Resting-state functional magnetic resonance imaging data were collected from 98 subjects (35 unipolar, 24 bipolar, and 39 healthy control subjects). Pearson correlations were computed between bilateral insula seed regions and a priori defined target regions from the default mode network, salience network, and ECN. After r-to-z transformation, a one-way multivariate analysis of covariance was conducted to identify significant differences in connectivity between groups. Post hoc pairwise comparisons were conducted and Bonferroni corrections were applied. Receiver-operating characteristics were computed to assess diagnostic sensitivity. Patients with bipolar depression evidenced significantly altered right anterior insula functional connectivity with the inferior parietal lobule of the ECN relative to patients with unipolar depression and control subjects. Right anterior insula-inferior parietal lobule connectivity significantly discriminated patients with bipolar depression. Impaired functional connectivity between the anterior insula and the inferior parietal lobule of the ECN distinguishes patients with bipolar depression from those with unipolar depression and healthy control subjects. This finding highlights a pathophysiological mechanism with potential as a therapeutic target and a clinical biomarker for bipolar

  20. Bridges over troubled water: suppliers as connective nodes in global supply networks

    DEFF Research Database (Denmark)

    Christensen, Poul Rind; Andersen, Poul Houman

    2005-01-01

    -oriented, focusing on the leading contractor's supply chain management. However, the increased demand for flexibility echoes down in supply network, decentralising the coordination task. We focus on subcontractors as connective nodes in supply networks and outline how coordinative roles are linked to the diversity......Increasingly, industrial selling and purchasing is embedded in supplier networks extending national borders. The internationalisation of supply activities adds considerable complexity to the coordination tasks performed by suppliers. Traditionally, supply chain management was upstream...

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

    Science.gov (United States)

    2015-10-16

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

  2. Accelerated Monte Carlo system reliability analysis through machine-learning-based surrogate models of network connectivity

    International Nuclear Information System (INIS)

    Stern, R.E.; Song, J.; Work, D.B.

    2017-01-01

    The two-terminal reliability problem in system reliability analysis is known to be computationally intractable for large infrastructure graphs. Monte Carlo techniques can estimate the probability of a disconnection between two points in a network by selecting a representative sample of network component failure realizations and determining the source-terminal connectivity of each realization. To reduce the runtime required for the Monte Carlo approximation, this article proposes an approximate framework in which the connectivity check of each sample is estimated using a machine-learning-based classifier. The framework is implemented using both a support vector machine (SVM) and a logistic regression based surrogate model. Numerical experiments are performed on the California gas distribution network using the epicenter and magnitude of the 1989 Loma Prieta earthquake as well as randomly-generated earthquakes. It is shown that the SVM and logistic regression surrogate models are able to predict network connectivity with accuracies of 99% for both methods, and are 1–2 orders of magnitude faster than using a Monte Carlo method with an exact connectivity check. - Highlights: • Surrogate models of network connectivity are developed by machine-learning algorithms. • Developed surrogate models can reduce the runtime required for Monte Carlo simulations. • Support vector machine and logistic regressions are employed to develop surrogate models. • Numerical example of California gas distribution network demonstrate the proposed approach. • The developed models have accuracies 99%, and are 1–2 orders of magnitude faster than MCS.

  3. Cluster Head Selection in a Homogeneous Wireless Sensor Network Ensuring Full Connectivity with Minimum Isolated Nodes

    Directory of Open Access Journals (Sweden)

    Tapan Kumar Jain

    2014-01-01

    Full Text Available The research work proposes a cluster head selection algorithm for a wireless sensor network. A node can be a cluster head if it is connected to at least one unique neighbor node where the unique neighbor is the one that is not connected to any other node. If there is no connected unique node then the CH is selected on the basis of residual energy and the number of neighbor nodes. With the increase in number of clusters, the processing energy of the network increases; hence, this algorithm proposes minimum number of clusters which further leads to increased network lifetime. The major novel contribution of the proposed work is an algorithm that ensures a completely connected network with minimum number of isolated nodes. An isolated node will remain only if it is not within the transmission range of any other node. With the maximum connectivity, the coverage of the network is automatically maximized. The superiority of the proposed design is verified by simulation results done in MATLAB, where it clearly depicts that the total numbers of rounds before the network dies out are maximum compared to other existing protocols.

  4. Insecure Network, Unknown Connection: Understanding Wi-Fi Privacy Assumptions of Mobile Device Users

    Directory of Open Access Journals (Sweden)

    Bram Bonné

    2017-07-01

    Full Text Available Smartphones and other mobile devices have proliferated in the past five years. The expectation of mobile device users to always be online has led to Wi-Fi networks being offered by a variety of providers. Using these networks introduces multiple security risks. In this work, we assess to what extent the privacy stance of mobile device users corresponds with their actual behavior by conducting a study with 108 participants. Our methodology consists of monitoring Wi-Fi networks that the participants’ devices connect to and the connections made by apps on these devices, for a period of 30 days. Afterwards, participants are surveyed about their awareness and privacy sensitiveness. We show that while a higher expertise in computer networks corresponds to more awareness about the connections made by apps, neither this expertise nor the actual privacy stance of the participant translates to better security habits. Moreover, participants in general were unaware about a significant part of connections made by apps on their devices, a matter that is worsened by the fact that one third of Wi-Fi networks that participants connect to do not have any security enabled. Based on our results, we provide recommendations to network providers, developers and users on how to improve Wi-Fi security for mobile devices.

  5. Effects of gratitude meditation on neural network functional connectivity and brain-heart coupling.

    Science.gov (United States)

    Kyeong, Sunghyon; Kim, Joohan; Kim, Dae Jin; Kim, Hesun Erin; Kim, Jae-Jin

    2017-07-11

    A sense of gratitude is a powerful and positive experience that can promote a happier life, whereas resentment is associated with life dissatisfaction. To explore the effects of gratitude and resentment on mental well-being, we acquired functional magnetic resonance imaging and heart rate (HR) data before, during, and after the gratitude and resentment interventions. Functional connectivity (FC) analysis was conducted to identify the modulatory effects of gratitude on the default mode, emotion, and reward-motivation networks. The average HR was significantly lower during the gratitude intervention than during the resentment intervention. Temporostriatal FC showed a positive correlation with HR during the gratitude intervention, but not during the resentment intervention. Temporostriatal resting-state FC was significantly decreased after the gratitude intervention compared to the resentment intervention. After the gratitude intervention, resting-sta