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  1. Altered default mode network functional connectivity in schizotypal personality disorder.

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    Zhang, Qing; Shen, Jing; Wu, Jianlin; Yu, Xiao; Lou, Wutao; Fan, Hongyu; Shi, Lin; Wang, Defeng

    2014-12-01

    The default mode network (DMN) has been identified to play a critical role in many mental disorders, but such abnormalities have not yet been determined in patients with schizotypal personality disorder (SPD). The purpose of this study was to analyze the alteration of the DMN functional connectivity in subjects with (SPD) and compared it to healthy control subjects. Eighteen DSM-IV diagnosed SPD subjects (all male, average age: 19.7±0.9) from a pool of 3000 first year college students, and eighteen age and gender matched healthy control subjects were recruited (all male, average age: 20.3±0.9). Independent component analysis (ICA) was used to analyze the DMN functional connectivity alteration. Compared to the healthy control group, SPD subjects had significantly decreased functional connectivity in the frontal areas, including the superior and medial frontal gyrus, and greater functional connectivity in the bilateral superior temporal gyrus and sub-lobar regions, including the bilateral putamen and caudate. Compared to subjects with SPD, the healthy control group showed decreased functional connectivity in the bilateral posterior cingulate gyrus, but showed greater functional connectivity in the right transverse temporal gyrus and left middle temporal gyrus. The healthy control group also showed greater activation in the cerebellum compared to the SPD group. These findings suggest that DMN functional connectivity, particularly that involving cognitive or emotional regulation, is altered in SPD subjects, and thus may be helpful in studying schizophrenia.

  2. Default mode, executive function, and language functional connectivity networks are compromised in mild Alzheimer's disease.

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    Weiler, Marina; Fukuda, Aya; Massabki, Lilian H P; Lopes, Tatila M; Franco, Alexandre R; Damasceno, Benito P; Cendes, Fernando; Balthazar, Marcio L F

    2014-03-01

    Alzheimer's disease (AD) is characterized by mental and cognitive problems, particularly with memory, language, visuospatial skills (VS), and executive functions (EF). Advances in the neuroimaging of AD have highlighted dysfunctions in functional connectivity networks (FCNs), especially in the memory related default mode network (DMN). However, little is known about the integrity and clinical significance of FNCs that process other cognitive functions than memory. We evaluated 22 patients with mild AD and 26 healthy controls through a resting state functional MRI scan. We aimed to identify different FCNs: the DMN, language, EF, and VS. Seed-based functional connectivity was calculated by placing a seed in the DMN (posterior cingulate cortex), language (Broca's and Wernicke's areas), EF (right and left dorsolateral prefrontal cortex), and VS networks (right and left associative visual cortex). We also performed regression analyses between individual connectivity maps for the different FCNs and the scores on cognitive tests. We found areas with significant decreases in functional connectivity in patients with mild AD in the DMN and Wernicke's area compared with controls. Increased connectivity in patients was observed in the EF network. Regarding multiple linear regression analyses, a significant correlation was only observed between the connectivity of the DMN and episodic memory (delayed recall) scores. In conclusion, functional connectivity alterations in mild AD are not restricted to the DMN. Other FCNs related to language and EF may be altered. However, we only found significant correlations between cognition and functional connectivity in the DMN and episodic memory performance.

  3. Default mode network in the effects of Δ9-Tetrahydrocannabinol (THC on human executive function.

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    Matthijs G Bossong

    Full Text Available Evidence is increasing for involvement of the endocannabinoid system in cognitive functions including attention and executive function, as well as in psychiatric disorders characterized by cognitive deficits, such as schizophrenia. Executive function appears to be associated with both modulation of active networks and inhibition of activity in the default mode network. In the present study, we examined the role of the endocannabinoid system in executive function, focusing on both the associated brain network and the default mode network. A pharmacological functional magnetic resonance imaging (fMRI study was conducted with a placebo-controlled, cross-over design, investigating effects of the endocannabinoid agonist Δ9-tetrahydrocannabinol (THC on executive function in 20 healthy volunteers, using a continuous performance task with identical pairs. Task performance was impaired after THC administration, reflected in both an increase in false alarms and a reduction in detected targets. This was associated with reduced deactivation in a set of brain regions linked to the default mode network, including posterior cingulate cortex and angular gyrus. Less deactivation was significantly correlated with lower performance after THC. Regions that were activated by the continuous performance task, notably bilateral prefrontal and parietal cortex, did not show effects of THC. These findings suggest an important role for the endocannabinoid system in both default mode modulation and executive function. This may be relevant for psychiatric disorders associated with executive function deficits, such as schizophrenia and ADHD.

  4. Default mode network in the effects of Δ9-Tetrahydrocannabinol (THC) on human executive function.

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    Bossong, Matthijs G; Jansma, J Martijn; van Hell, Hendrika H; Jager, Gerry; Kahn, René S; Ramsey, Nick F

    2013-01-01

    Evidence is increasing for involvement of the endocannabinoid system in cognitive functions including attention and executive function, as well as in psychiatric disorders characterized by cognitive deficits, such as schizophrenia. Executive function appears to be associated with both modulation of active networks and inhibition of activity in the default mode network. In the present study, we examined the role of the endocannabinoid system in executive function, focusing on both the associated brain network and the default mode network. A pharmacological functional magnetic resonance imaging (fMRI) study was conducted with a placebo-controlled, cross-over design, investigating effects of the endocannabinoid agonist Δ9-tetrahydrocannabinol (THC) on executive function in 20 healthy volunteers, using a continuous performance task with identical pairs. Task performance was impaired after THC administration, reflected in both an increase in false alarms and a reduction in detected targets. This was associated with reduced deactivation in a set of brain regions linked to the default mode network, including posterior cingulate cortex and angular gyrus. Less deactivation was significantly correlated with lower performance after THC. Regions that were activated by the continuous performance task, notably bilateral prefrontal and parietal cortex, did not show effects of THC. These findings suggest an important role for the endocannabinoid system in both default mode modulation and executive function. This may be relevant for psychiatric disorders associated with executive function deficits, such as schizophrenia and ADHD.

  5. 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…

  6. 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.)

  7. Impaired functional default mode network in patients with mild neurological Wilson's disease.

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    Han, Yongsheng; Cheng, Hewei; Toledo, Jon B; Wang, Xun; Li, Bo; Han, Yongzhu; Wang, Kai; Fan, Yong

    2016-09-01

    Wilson's disease (WD) is an autosomal recessive metabolic disorder characterized by cognitive, psychiatric and motor signs and symptoms that are associated with structural and pathological brain abnormalities, in addition to liver changes. However, functional brain connectivity pattern of WD patients remains largely unknown. In the present study, we investigated functional brain connectivity pattern of WD patients using resting state functional magnetic resonance imaging. Particularly, we studied default mode network (DMN) using posterior cingulate cortex (PCC) based seed functional connectivity analysis and graph theoretic functional brain network analysis tools, and investigated the relationship between the DMN's functional connectivity pattern of WD patients and their attention functions examined using the attention network test (ANT). Our results demonstrated that WD patients had altered DMN's functional connectivity and lower local and global network efficiency compared with normal controls (NCs). In addition, the functional connectivity between left inferior temporal cortex and right lateral parietal cortex was correlated with altering function, one of the attention functions, across WD and NC subjects. These findings indicated that the DMN's functional connectivity was altered in WD patients, which might be correlated with their attention dysfunction.

  8. A Review of the Functional and Anatomical Default Mode Network in Schizophrenia.

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    Hu, Mao-Lin; Zong, Xiao-Fen; Mann, J John; Zheng, Jun-Jie; Liao, Yan-Hui; Li, Zong-Chang; He, Ying; Chen, Xiao-Gang; Tang, Jin-Song

    2017-02-01

    Schizophrenia is a severe mental disorder characterized by impaired perception, delusions, thought disorder, abnormal emotion regulation, altered motor function, and impaired drive. The default mode network (DMN), since it was first proposed in 2001, has become a central research theme in neuropsychiatric disorders, including schizophrenia. In this review, first we define the DMN and describe its functional activity, functional and anatomical connectivity, heritability, and inverse correlation with the task positive network. Second, we review empirical studies of the anatomical and functional DMN, and anti-correlation between DMN and the task positive network in schizophrenia. Finally, we review preliminary evidence about the relationship between antipsychotic medications and regulation of the DMN, review the role of DMN as a treatment biomarker for this disease, and consider the DMN effects of individualized therapies for schizophrenia.

  9. Reduced functional segregation between the default mode network and the executive control network in healthy older adults: A longitudinal study.

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    Ng, Kwun Kei; Lo, June C; Lim, Joseph K W; Chee, Michael W L; Zhou, Juan

    2016-06-01

    The effects of age on functional connectivity (FC) of intrinsic connectivity networks (ICNs) have largely been derived from cross-sectional studies. Far less is known about longitudinal changes in FC and how they relate to ageing-related cognitive decline. We evaluated intra- and inter-network FC in 78 healthy older adults two or three times over a period of 4years. Using linear mixed modeling we found progressive loss of functional specialization with ageing, evidenced by a decline in intra-network FC within the executive control (ECN) and default mode networks (DMN). In contrast, longitudinal inter-network FC between ECN and DMN showed a u-shaped trajectory whereby functional segregation between these two networks initially increased over time and later decreased as participants aged. The rate of loss in functional segregation between ECN and DMN was associated with ageing-related decline in processing speed. The observed longitudinal FC changes and their associations with processing speed remained after correcting for longitudinal reduction in gray matter volume. These findings help connect ageing-related changes in FC with ageing-related decline in cognitive performance and underscore the value of collecting concurrent longitudinal imaging and behavioral data.

  10. Abnormal Default-Mode Network Activation in Cirrhotic Patients: A Functional Magnetic Resonance Imaging Study

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    Long Jiang Zhang; Guifen Yang; Jianzhong Yin; Yawu Liu; Ji Qi [Dept. of Radiology, Tianjin First Central Hospital, Tianjin Medical Univ., Tianjin (China)

    2007-09-15

    Background: Recently, increasing numbers of studies have demonstrated that, in humans, a default-mode functional network exists in the resting state. Abnormal default-mode network in various diseases has been reported; however, no report concerning hepatic cirrhosis has been published to date. Purpose: To prospectively explore whether the resting-state network in patients with hepatic cirrhosis is abnormal or not, using functional magnetic resonance imaging (fMRI). Material and Methods: 14 patients with hepatic cirrhosis (12 male, two female; 45{+-}9 years) and 14 age- and gender-matched healthy volunteers (12 male, two female; 42{+-}10 years) participated in a blocked-design fMRI study. A modified Stroop task with Chinese characters was used as the target stimulus. Statistical Parametric Mapping 99 software was employed to process the functional data. Individual maps and group data were generated for patients with hepatic cirrhosis and for healthy controls, respectively. Intergroup analysis between patients and healthy controls was also generated using the two-sample t-test model. Cluster analyses were done based on the group data, and an identical P value 0.01 with continuously connected voxels of no less than 10 was defined as significant deactivation. After fMRI scanning was complete, behavioral Stroop interference tests were performed on all subjects; reaction time and error number were recorded. Results: Functionally, deactivation of the posterior cingulate cortex (PCC) and precuneus was absent when subjects performed the incongruous word-reading task; deactivation of the PCC, precuneus, and ventral medial prefrontal cortex was increased when they performed the incongruous color-naming task. Conclusion: The functional as well as behavioral data suggest that cirrhotic patients may have an abnormal deactivation mode. The absence of deactivation in the PCC and precuneus may be a sensitive rather than specific marker in patients with hepatic cirrhosis.

  11. Escitalopram Decreases Cross-Regional Functional Connectivity within the Default-Mode Network.

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    Vincent van de Ven

    Full Text Available The default-mode network (DMN, which comprises medial frontal, temporal and parietal regions, is part of the brain's intrinsic organization. The serotonergic (5-HT neurotransmitter system projects to DMN regions from midbrain efferents, and manipulation of this system could thus reveal insights into the neurobiological mechanisms of DMN functioning. Here, we investigate intrinsic functional connectivity of the DMN as a function of activity of the serotonergic system, through the administration of the selective serotonin reuptake inhibitor (SSRI escitalopram. We quantified DMN functional connectivity using an approach based on dual-regression. Specifically, we decomposed group data of a subset of the functional time series using spatial independent component analysis, and projected the group spatial modes to the same and an independent resting state time series of individual participants. We found no effects of escitalopram on global functional connectivity of the DMN at the map-level; that is, escitalopram did not alter the global functional architecture of the DMN. However, we found that escitalopram decreased DMN regional pairwise connectivity, which included anterior and posterior cingulate cortex, hippocampal complex and lateral parietal regions. Further, regional DMN connectivity covaried with alertness ratings across participants. Our findings show that escitalopram altered intrinsic regional DMN connectivity, which suggests that the serotonergic system plays an important role in DMN connectivity and its contribution to cognition. Pharmacological challenge designs may be a useful addition to resting-state functional MRI to investigate intrinsic brain functional organization.

  12. Increased resting state functional connectivity in the default mode network in recovered anorexia nervosa.

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    Cowdrey, Felicity A; Filippini, Nicola; Park, Rebecca J; Smith, Stephen M; McCabe, Ciara

    2014-02-01

    Functional brain imaging studies have shown abnormal neural activity in individuals recovered from anorexia nervosa (AN) during both cognitive and emotional task paradigms. It has been suggested that this abnormal activity which persists into recovery might underpin the neurobiology of the disorder and constitute a neural biomarker for AN. However, no study to date has assessed functional changes in neural networks in the absence of task-induced activity in those recovered from AN. Therefore, the aim of this study was to investigate whole brain resting state functional connectivity in nonmedicated women recovered from anorexia nervosa. Functional magnetic resonance imaging scans were obtained from 16 nonmedicated participants recovered from anorexia nervosa and 15 healthy control participants. Independent component analysis revealed functionally relevant resting state networks. Dual regression analysis revealed increased temporal correlation (coherence) in the default mode network (DMN) which is thought to be involved in self-referential processing. Specifically, compared to healthy control participants the recovered anorexia nervosa participants showed increased temporal coherence between the DMN and the precuneus and the dorsolateral prefrontal cortex/inferior frontal gyrus. The findings support the view that dysfunction in resting state functional connectivity in regions involved in self-referential processing and cognitive control might be a vulnerability marker for the development of anorexia nervosa.

  13. Functional Connectivity with the Default Mode Network Is Altered in Fibromyalgia Patients

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    Chiu, Yee; Nurmikko, Turo; Stancak, Andrej

    2016-01-01

    Fibromyalgia syndrome (FMS) patients show altered connectivity with the network maintaining ongoing resting brain activity, known as the default mode network (DMN). The connectivity patterns of DMN with the rest of the brain in FMS patients are poorly understood. This study employed seed-based functional connectivity analysis to investigate resting-state functional connectivity with DMN structures in FMS. Sixteen female FMS patients and 15 age-matched, healthy control subjects underwent T2-weighted resting-state MRI scanning and functional connectivity analyses using DMN network seed regions. FMS patients demonstrated alterations to connectivity between DMN structures and anterior midcingulate cortex, right parahippocampal gyrus, left superior parietal lobule and left inferior temporal gyrus. Correlation analysis showed that reduced functional connectivity between the DMN and the right parahippocampal gyrus was associated with longer duration of symptoms in FMS patients, whereas augmented connectivity between the anterior midcingulate and posterior cingulate cortices was associated with tenderness and depression scores. Our findings demonstrate alterations to functional connectivity between DMN regions and a variety of regions which are important for pain, cognitive and emotional processing in FMS patients, and which may contribute to the development or maintenance of chronic symptoms in FMS. PMID:27442504

  14. Hemispheric asymmetries of functional connectivity and grey matter volume in the default mode network.

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    Saenger, Victor M; Barrios, Fernando A; Martínez-Gudiño, María L; Alcauter, Sarael

    2012-06-01

    Resting state networks such as the default mode network have been widely reported. Although a plethora of information on its functional relevance has been generated, little is known about lateralization or hemisphere asymmetry within the DMN. We used high-resolution resting state fMRI and T1 3D data to investigate such asymmetries in two groups of healthy subjects, one right-handed and one left-handed. Independent component analysis and the dual regression approach were carried out to identify functional asymmetries, while voxel-based morphometry was used to identify structural asymmetries in grey matter volume within the DMN. Greater leftward functional connectivity was observed in the posterior cingulate gyrus (PCG) for both groups. Leftward functional asymmetry was observed in the thalamus and rightward functional asymmetries were observed in the middle frontal and middle/superior temporal gyrus in the right-handed group. Rightward asymmetries in grey matter volume were observed in the posterior portion of the PCG for both groups. The right-handed group exhibited leftward structural asymmetries in the anterior portion of the PCG and in the middle frontal and posterior portion of the middle temporal gyrus, while rightward asymmetries were observed in the posterior portion of the PCG and anterior portions of temporal regions. These results suggest that functional connectivity and grey matter volume are not equally distributed between hemispheres within the DMN, and that functional asymmetries are not always reflected or determined by structural asymmetries.

  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. 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.

  17. Acupuncture Modulates the Functional Connectivity of the Default Mode Network in Stroke Patients

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    Yong Zhang

    2014-01-01

    Full Text Available Abundant evidence from previous fMRI studies on acupuncture has revealed significant modulatory effects at widespread brain regions. However, few reports on the modulation to the default mode network (DMN of stroke patients have been investigated in the field of acupuncture. To study the modulatory effects of acupuncture on the DMN of stroke patients, eight right hemispheric infarction and stable ischemic stroke patients and ten healthy subjects were recruited to undergo resting state fMRI scanning before and after acupuncture stimulation. Functional connectivity analysis was applied with the bilateral posterior cingulate cortices chosen as the seed regions. The main finding demonstrated that the interregional interactions between the ACC and PCC especially enhanced after acupuncture at GB34 in stroke patients, compared with healthy controls. The results indicated that the possible mechanisms of the modulatory effects of acupuncture on the DMN of stroke patients could be interpreted in terms of cognitive ability and motor function recovery.

  18. Decreased connectivity of the default mode network in pathological gambling: a resting state functional MRI study.

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    Jung, Myung Hun; Kim, Jae-Hun; Shin, Young-Chul; Jung, Wi Hoon; Jang, Joon Hwan; Choi, Jung-Seok; Kang, Do-Hyung; Yi, Jung-Seo; Choi, Chi-Hoon; Kwon, Jun Soo

    2014-11-01

    The default mode network (DMN) represents neuronal activity that is intrinsically generated during a resting state. The present study used resting-state fMRI to investigate whether functional connectivity is altered in pathological gambling (PG). Fifteen drug-naive male patients with PG and 15 age-matched male control subjects participated in the present study. The pathological gambling modification of the Yale-Brown Obsessive Compulsive Scale (PG-YBOCS), the Beck Depression Inventory, and the Beck Anxiety Inventory were used to determine symptom severity in all participants. Participants were instructed to keep their eyes closed and not to focus on any particular thoughts during the 4.68-min resting-state functional scan. The patients with PG displayed decreased default mode connectivity in the left superior frontal gyrus, right middle temporal gyrus, and precuneus compared with healthy controls. The severity of PG symptoms in patients with PG was negatively associated with connectivity between the posterior cingulate cortex seed region and the precuneus (r=-0.599, p=0.018). Decreased functional connectivity within DMN suggests that PG may share similar neurobiological abnormalities with other addictive disorders. Moreover, the severity of PG symptoms was correlated with decreased connectivity in the precuneus, which may be important in the response to treatment in patients with PG.

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

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    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

  20. Cognitive stimulation of the default-mode network modulates functional connectivity in healthy aging.

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    De Marco, Matteo; Meneghello, Francesca; Duzzi, Davide; Rigon, Jessica; Pilosio, Cristina; Venneri, Annalena

    2016-03-01

    A cognitive-stimulation tool was created to regulate functional connectivity within the brain Default-Mode Network (DMN). Computerized exercises were designed based on the hypothesis that repeated task-dependent coactivation of multiple DMN regions would translate into regulation of resting-state network connectivity. Forty seniors (mean age: 65.90 years; SD: 8.53) were recruited and assigned either to an experimental group (n=21) who received one month of intensive cognitive stimulation, or to a control group (n=19) who maintained a regime of daily-life activities explicitly focused on social interactions. An MRI protocol and a battery of neuropsychological tests were administered at baseline and at the end of the study. Changes in the DMN (measured via functional connectivity of posterior-cingulate seeds), in brain volumes, and in cognitive performance were measured with mixed models assessing group-by-timepoint interactions. Moreover, regression models were run to test gray-matter correlates of the various stimulation tasks. Significant associations were found between task performance and gray-matter volume of multiple DMN core regions. Training-dependent up-regulation of functional connectivity was found in the posterior DMN component. This interaction was driven by a pattern of increased connectivity in the training group, while little or no up-regulation was seen in the control group. Minimal changes in brain volumes were found, but there was no change in cognitive performance. The training-dependent regulation of functional connectivity within the posterior DMN component suggests that this stimulation program might exert a beneficial impact in the prevention and treatment of early AD neurodegeneration, in which this neurofunctional pathway is progressively affected by the disease.

  1. Functional connectivity of paired default mode network subregions in primary insomnia

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    Nie X

    2015-12-01

    Full Text Available Xiao Nie,1,* Yi Shao,2,* Si-yu Liu,3 Hai-jun Li,1 Ai-lan Wan,4 Si Nie,1 De-chang Peng,1 Xi-jian Dai1,5 1Department of Radiology, The First Affiliated Hospital of Nanchang University, Nangchang, Jiangxi, People’s Republic of China; 2Department of Ophthalmology,The First Affiliated Hospital of Nanchang University, Nangchang, Jiangxi, People’s Republic of China; 3Medical College of Nanchang University, Nangchang, Jiangxi, People’s Republic of China; 4Department of Psychosomatic Medicine, The First Affiliated Hospital of Nanchang University, Nangchang, Jiangxi, People’s Republic of China; 5Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, People’s Republic of China *These authors contributed equally to this work Objective: The aim of this study is to explore the resting-state functional connectivity (FC differences between the paired default mode network (DMN subregions in patients with primary insomnia (PIs.Methods: Forty-two PIs and forty-two age- and sex-matched good sleepers (GSs were recruited. All subjects underwent the resting-state functional magnetic resonance imaging scans. The seed-based region-to-region FC method was used to evaluate the abnormal connectivity within the DMN subregions between the PIs and the GSs. Pearson correlation analysis was used to investigate the relationships between the abnormal FC strength within the paired DMN subregions and the clinical features in PIs.Results: Compared with the GSs, the PIs showed higher Pittsburgh Sleep Quality Index score, Hamilton Anxiety Rating Scale score, Hamilton Depression Rating Scale score, Self-Rating Depression Scale score, Self Rating Anxiety Scale score, Self-Rating Scale of Sleep score, and Profile of Mood States score (P<0.001. Compared with the GSs, the PIs showed significant decreased region-to-region FC between the medial prefrontal cortex and the right medial temporal lobe (t=-2.275, P

  2. Negative mood-induction modulates default mode network resting-state functional connectivity in chronic depression

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    Renner, F.; Siep, N.; Arntz, A.; van de Ven, V.; Peeters, F.P.M.L.; Quaedflieg, C.W.E.M.; Huibers, M.J.H.

    2017-01-01

    BACKGROUND: The aim of this study was to investigate the effects of sad mood on default mode network (DMN) resting-state connectivity in persons with chronic major depressive disorder (cMDD). METHODS: Participants with a diagnosis of cMDD (n=18) and age, gender and education level matched

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

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    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.

  4. Functional MRI for Assessment of the Default Mode Network in Acute Brain Injury.

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    Kondziella, Daniel; Fisher, Patrick M; Larsen, Vibeke Andrée; Hauerberg, John; Fabricius, Martin; Møller, Kirsten; Knudsen, Gitte Moos

    2017-05-08

    Assessment of the default mode network (DMN) using resting-state functional magnetic resonance imaging (fMRI) may improve assessment of the level of consciousness in chronic brain injury, and therefore, fMRI may also have prognostic value in acute brain injury. However, fMRI is much more challenging in critically ill patients because of cardiovascular vulnerability, intravenous sedation, and artificial ventilation. Using resting-state fMRI, we investigated the DMN in a convenience sample of patients with acute brain injury admitted to the intensive care unit. The DMN was classified dichotomously into "normal" and "grossly abnormal." Clinical outcome was assessed at 3 months. Seven patients with acute brain injury (4 females; median age 37 years [range 14-71 years]; 1 traumatic brain injury [TBI]; 6 non-TBI) were investigated by fMRI a median of 15 days after injury (range 5-25 days). Neurological presentation included 2 coma, 1 vegetative state/unresponsive wakefulness syndrome (VS/UWS), 3 minimal conscious state (MCS) minus, and 1 MCS plus. Clinical outcomes at 3 months included 1 death, 1 VS/UWS, 1 MCS plus, and 4 conscious states (CS; 1 modified Rankin Scale 0; 2 mRS 4; 1 mRS 5). Normal DMNs were seen in 4 out of 7 patients (1 MCS plus, 3 CS at follow-up). It is feasible to assess the DMN by resting-state fMRI in patients with acute brain injury already in the very early period of intensive care unit admission. Although preliminary data, all patients with a preserved DMN regained consciousness levels at follow-up compatible with MCS+ or better.

  5. Effects of cognitive training on resting-state functional connectivity of default mode, salience and central executive networks

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    Weifang eCao

    2016-04-01

    Full Text Available Neuroimaging studies have documented that ageing can disrupt certain higher cognitive systems such as the default mode network (DMN, the salience network (SN and the central executive network (CEN. The effect of cognitive training on higher cognitive systems remains unclear. This study used a one-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 three-month period and the wait-list control group. All subjects underwent cognitive measurements and resting-state functional magnetic resonance imaging (fMRI scanning at baseline and at one 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 ageing-related dysfunction of higher cognitive networks.

  6. Increased resting state functional connectivity in the fronto-parietal and default mode network in anorexia nervosa

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    Ilka eBoehm

    2014-10-01

    Full Text Available The etiology of anorexia nervosa (AN is poorly understood. Results from functional brain imaging studies investigating the neural profile of AN using cognitive and emotional task paradigms are difficult to reconcile. Task-related imaging studies often require a high level of compliance and can only partially explore the distributed nature and complexity of brain function. In this study, resting state functional connectivity imaging was used to investigate well-characterized brain networks potentially relevant to understand the neural mechanisms underlying the symptomatology and etiology of AN. Resting state functional magnetic resonance imaging data was obtained from 35 unmedicated female acute AN patients and 35 closely matched healthy female participants (HC and decomposed using spatial group independent component analyses. Using validated templates, we identified components covering the fronto-parietal control network, the default mode network (DMN, the salience network, the visual and the sensory-motor network. Group comparison revealed an increased functional connectivity between the angular gyrus and the other parts of the fronto-parietal network in patients with AN in comparison to HC. Connectivity of the angular gyrus was positively associated with self-reported persistence in HC. In the DMN, AN patients also showed an increased functional connectivity strength in the anterior insula in comparison to HC. Anterior insula connectivity was associated with self-reported problems with interoceptive awareness. This study, with one of the largest sample to date, shows that acute AN is associated with abnormal brain connectivity in two major resting state networks. The finding of an increased functional connectivity in the fronto-parietal network adds novel support for the notion of AN as a disorder of excessive cognitive control, whereas the elevated functional connectivity of the anterior insula with the DMN may reflect the high levels of self

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

    Science.gov (United States)

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

    2015-09-01

    PTSD and TBI are two common conditions in veteran populations that can be difficult to distinguish clinically. The default mode network (DMN) is abnormal in a multitude of neurological and psychiatric disorders. We hypothesize that brain perfusion SPECT can be applied to diagnostically separate PTSD from TBI reliably in a veteran cohort using DMN regions. A group of 196 veterans (36 with PTSD, 115 with TBI, 45 with PTSD/TBI) were selected from a large multi-site population cohort of individuals with psychiatric disease. Inclusion criteria were peacetime or wartime veterans regardless of branch of service and included those for whom the traumatic brain injury was not service related. SPECT imaging was performed on this group both at rest and during a concentration task. These measures, as well as the baseline-concentration difference, were then inputted from DMN regions into separate binary logistic regression models controlling for age, gender, race, clinic site, co-morbid psychiatric diseases, TBI severity, whether or not the TBI was service related, and branch of armed service. Predicted probabilities were then inputted into a receiver operating characteristic analysis to compute sensitivity, specificity, and accuracy. Compared to PSTD, persons with TBI were older, male, and had higher rates of bipolar and major depressive disorder (p TBI in the veterans with 92 % sensitivity, 85 % specificity, and 94 % accuracy. With concentration scans, there was 85 % sensitivity, 83 % specificity and 89 % accuracy. Baseline-concentration (the difference metric between the two scans) scans were 85 % sensitivity, 80 % specificity, and 87 % accuracy. In separating TBI from PTSD/TBI visual readings of baseline scans had 85 % sensitivity, 81 % specificity, and 83 % accuracy. Concentration scans had 80 % sensitivity, 65 % specificity, and 79 % accuracy. Baseline-concentration scans had 82 % sensitivity, 69 % specificity, and 81 % accuracy. For separating PTSD

  8. 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.

  9. Functional connectivity comparison of the default mode network in non-depressed Parkinson disease and depressed Parkinson disease

    Science.gov (United States)

    Han, Yuan; Li, Rui; Liu, Jiangtao; Yao, Li; Wu, Xia

    2011-03-01

    Examining the spontaneous activity to understand the neural mechanism of brain disorders and establish neuroimaging-based disease-related biomarkers is a focus in recent resting-state functional MRI (fMRI) studies. The present study hypothesized that resting activity in the default mode network (DMN), which was used for characterizing the resting-state human brain might be different in patients with depressed Parkinson disease (dPD) compared with non-depressed Parkinson disease (ndPD) patients. To test the hypothesis, we firstly employed the Group independent component analysis (ICA) approach to isolate the DMN for the two groups by analyzing the resting-state fMRI data from a group of 12 patients with dPD and a group of 12 age-matched ndPD subjects. Between-group comparison of the functional connectivity in the DMN was then performed to examine the impact of depression on the intrinsic activity in PD. We found 1) the core region from the network the medial prefrontal cortex (MPFC) show significant decreased activity in dPD group compared with ndPD group; 2) the activity in MPFC has significant negative correlation with behavioral measure; 3) the resting activity intensity of MPFC is suggested to be a promising biomarker for distinguishing dPD from ndPD.

  10. Abnormal resting-state functional connectivity within the default mode network subregions in male patients with obstructive sleep apnea

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    Li HJ

    2016-01-01

    Full Text Available Hai-Jun Li,1 Xiao Nie,1 Hong-Han Gong,1 Wei Zhang,2 Si Nie,1 De-Chang Peng11Department of Radiology, 2Department of Pneumology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, People’s Republic of ChinaBackground and objective: Abnormal resting-state functional connectivity (rs-FC between the central executive network and the default mode network (DMN in patients with obstructive sleep apnea (OSA has been reported. However, the effect of OSA on rs-FC within the DMN subregions remains uncertain. This study was designed to investigate whether the rs-FC within the DMN subregions was disrupted and determine its relationship with clinical symptoms in patients with OSA. Methods: Forty male patients newly diagnosed with severe OSA and 40 male education- and age-matched good sleepers (GSs underwent functional magnetic resonance imaging (fMRI examinations and clinical and neuropsychologic assessments. Seed-based region of interest rs-FC method was used to analyze the connectivity between each pair of subregions within the DMN, including the medial prefrontal cortex (MPFC, posterior cingulate cortex (PCC, hippocampus formation (HF, inferior parietal cortices (IPC, and medial temporal lobe (MTL. The abnormal rs-FC strength within the DMN subregions was correlated with clinical and neuropsychologic assessments using Pearson correlation analysis in patients with OSA. Results: Compared with GSs, patients with OSA had significantly decreased rs-FC between the right HF and the PCC, MPFC, and left MTL. However, patients with OSA had significantly increased rs-FC between the MPFC and left and right IPC, and between the left IPC and right IPC. The rs-FC between the right HF and left MTL was positively correlated with rapid eye movement (r=0.335, P=0.035. The rs-FC between the PCC and right HF was negatively correlated with delayed memory (r=-0.338, P=0.033.Conclusion: OSA selectively impairs the rs-FC between right HF and PCC

  11. Transdiagnostic commonalities and differences in resting state functional connectivity of the default mode network in schizophrenia and major depression

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    L. Schilbach

    2016-01-01

    Full Text Available Schizophrenia and depression are prevalent psychiatric disorders, but their underlying neural bases remains poorly understood. Neuroimaging evidence has pointed towards the relevance of functional connectivity aberrations in default mode network (DMN hubs, dorso-medial prefrontal cortex and precuneus, in both disorders, but commonalities and differences in resting state functional connectivity of those two regions across disorders has not been formally assessed. Here, we took a transdiagnostic approach to investigate resting state functional connectivity of those two regions in 75 patients with schizophrenia and 82 controls from 4 scanning sites and 102 patients with depression and 106 controls from 3 sites. Our results demonstrate common dysconnectivity patterns as indexed by a significant reduction of functional connectivity between precuneus and bilateral superior parietal lobe in schizophrenia and depression. Furthermore, our findings highlight diagnosis-specific connectivity reductions of the parietal operculum in schizophrenia relative to depression. In light of evidence that points towards the importance of the DMN for social cognitive abilities and well documented impairments of social interaction in both patient groups, it is conceivable that the observed transdiagnostic connectivity alterations may contribute to interpersonal difficulties, but this could not be assessed directly in our study as measures of social behavior were not available. Given the operculum's role in somatosensory integration, diagnosis-specific connectivity reductions may indicate a pathophysiological mechanism for basic self-disturbances that is characteristic of schizophrenia, but not depression.

  12. Transdiagnostic commonalities and differences in resting state functional connectivity of the default mode network in schizophrenia and major depression.

    Science.gov (United States)

    Schilbach, L; Hoffstaedter, F; Müller, V; Cieslik, E C; Goya-Maldonado, R; Trost, S; Sorg, C; Riedl, V; Jardri, R; Sommer, I; Kogler, L; Derntl, B; Gruber, O; Eickhoff, S B

    2016-01-01

    Schizophrenia and depression are prevalent psychiatric disorders, but their underlying neural bases remains poorly understood. Neuroimaging evidence has pointed towards the relevance of functional connectivity aberrations in default mode network (DMN) hubs, dorso-medial prefrontal cortex and precuneus, in both disorders, but commonalities and differences in resting state functional connectivity of those two regions across disorders has not been formally assessed. Here, we took a transdiagnostic approach to investigate resting state functional connectivity of those two regions in 75 patients with schizophrenia and 82 controls from 4 scanning sites and 102 patients with depression and 106 controls from 3 sites. Our results demonstrate common dysconnectivity patterns as indexed by a significant reduction of functional connectivity between precuneus and bilateral superior parietal lobe in schizophrenia and depression. Furthermore, our findings highlight diagnosis-specific connectivity reductions of the parietal operculum in schizophrenia relative to depression. In light of evidence that points towards the importance of the DMN for social cognitive abilities and well documented impairments of social interaction in both patient groups, it is conceivable that the observed transdiagnostic connectivity alterations may contribute to interpersonal difficulties, but this could not be assessed directly in our study as measures of social behavior were not available. Given the operculum's role in somatosensory integration, diagnosis-specific connectivity reductions may indicate a pathophysiological mechanism for basic self-disturbances that is characteristic of schizophrenia, but not depression.

  13. Impaired resting-state functional integrations within default mode network of generalized tonic-clonic seizures epilepsy.

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    Ming Song

    Full Text Available Generalized tonic-clonic seizures (GTCS are characterized by unresponsiveness and convulsions, which cause complete loss of consciousness. Many recent studies have found that the ictal alterations in brain activity of the GTCS epilepsy patients are focally involved in some brain regions, including thalamus, upper brainstem, medial prefrontal cortex, posterior midbrain regions, and lateral parietal cortex. Notably, many of these affected brain regions are the same and overlap considerably with the components of the so-called default mode network (DMN. Here, we hypothesize that the brain activity of the DMN of the GTCS epilepsy patients are different from normal controls, even in the resting state. To test this hypothesis, we compared the DMN of the GTCS epilepsy patients and the controls using the resting state functional magnetic resonance imaging. Thirteen brain areas in the DMN were extracted, and a complete undirected weighted graph was used to model the DMN for each participant. When directly comparing the edges of the graph, we found significant decreased functional connectivities within the DMN of the GTCS epilepsy patients comparing to the controls. As for the nodes of the graph, we found that the degree of some brain areas within the DMN was significantly reduced in the GTCS epilepsy patients, including the anterior medial prefrontal cortex, the bilateral superior frontal cortex, and the posterior cingulate cortex. Then we investigated into possible mechanisms of how GTCS epilepsy could cause the reduction of the functional integrations of DMN. We suggested the damaged functional integrations of the DMN in the GTCS epilepsy patients even during the resting state, which could help to understand the neural correlations of the impaired consciousness of GTCS epilepsy patients.

  14. Catechol-O-methyltransferase Val158Met polymorphism modulates gray matter volume and functional connectivity of the default mode network.

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    Tian Tian

    Full Text Available The effect of catechol-O-methyltransferase (COMT Val158Met polymorphism on brain structure and function has been previously investigated separately and regionally; this prevents us from obtaining a full picture of the effect of this gene variant. Additionally, gender difference must not be overlooked because estrogen exerts an interfering effect on COMT activity. We examined 323 young healthy Chinese Han subjects and analyzed the gray matter volume (GMV differences between Val/Val individuals and Met carriers in a voxel-wise manner throughout the whole brain. We were interested in genotype effects and genotype × gender interactions. We then extracted these brain regions with GMV differences as seeds to compute resting-state functional connectivity (rsFC with the rest of the brain; we also tested the genotypic differences and gender interactions in the rsFCs. Val/Val individuals showed decreased GMV in the posterior cingulate cortex (PCC compared with Met carriers; decreased GMV in the medial superior frontal gyrus (mSFG was found only in male Val/Val subjects. The rsFC analysis revealed that both the PCC and mSFG were functionally correlated with brain regions of the default mode network (DMN. Both of these regions showed decreased rsFCs with different parts of the frontopolar cortex of the DMN in Val/Val individuals than Met carriers. Our findings suggest that the COMT Val158Met polymorphism modulates both the structure and functional connectivity within the DMN and that gender interactions should be considered in studies of the effect of this genetic variant, especially those involving prefrontal morphology.

  15. Acoustic modes in fluid networks

    Science.gov (United States)

    Michalopoulos, C. D.; Clark, Robert W., Jr.; Doiron, Harold H.

    Pressure and flow rate eigenvalue problems for one-dimensional flow of a fluid in a network of pipes are derived from the familiar transmission line equations. These equations are linearized by assuming small velocity and pressure oscillations about mean flow conditions. It is shown that the flow rate eigenvalues are the same as the pressure eigenvalues and the relationship between line pressure modes and flow rate modes is established. A volume at the end of each branch is employed which allows any combination of boundary conditions, from open to closed, to be used. The Jacobi iterative method is used to compute undamped natural frequencies and associated pressure/flow modes. Several numerical examples are presented which include acoustic modes for the Helium Supply System of the Space Shuttle Orbiter Main Propulsion System. It should be noted that the method presented herein can be applied to any one-dimensional acoustic system involving an arbitrary number of branches.

  16. Regional homogeneity within the default mode network in bipolar depression: a resting-state functional magnetic resonance imaging study.

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    Chun-Hong Liu

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

  17. Impact of functional MRI data preprocessing pipeline on default-mode network detectability in patients with disorders of consciousness

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    Adrian eAndronache

    2013-08-01

    Full Text Available An emerging application of resting-state functional MRI is the study of patients with disorders of consciousness (DoC, where integrity of default-mode network (DMN activity is associated to the clinical level of preservation of consciousness. Due to the inherent inability to follow verbal instructions, arousal induced by scanning noise and postural pain, these patients tend to exhibit substantial levels of movement. This results in spurious, non-neural fluctuations of the blood-oxygen level-dependent (BOLD signal, which impair the evaluation of residual functional connectivity. Here, the effect of data preprocessing choices on the detectability of the DMN was systematically evaluated in a representative cohort of 30 clinically and etiologically heterogeneous DoC patients and 33 healthy controls. Starting from a standard preprocessing pipeline, additional steps were gradually inserted, namely band-pass filtering, removal of co-variance with the movement vectors, removal of co-variance with the global brain parenchyma signal, rejection of realignment outlier volumes and ventricle masking. Both independent-component analysis (ICA and seed-based analysis (SBA were performed, and DMN detectability was assessed quantitatively as well as visually. The results of the present study strongly show that the detection of DMN activity in the sub-optimal fMRI series acquired on DoC patients is contingent on the use of adequate filtering steps. ICA and SBA are differently affected but give convergent findings for high-grade preprocessing. We propose that future studies in this area should adopt the described preprocessing procedures as a minimum standard to reduce the probability of wrongly inferring that DMN activity is absent.

  18. Impact of functional MRI data preprocessing pipeline on default-mode network detectability in patients with disorders of consciousness.

    Science.gov (United States)

    Andronache, Adrian; Rosazza, Cristina; Sattin, Davide; Leonardi, Matilde; D'Incerti, Ludovico; Minati, Ludovico

    2013-01-01

    An emerging application of resting-state functional MRI (rs-fMRI) is the study of patients with disorders of consciousness (DoC), where integrity of default-mode network (DMN) activity is associated to the clinical level of preservation of consciousness. Due to the inherent inability to follow verbal instructions, arousal induced by scanning noise and postural pain, these patients tend to exhibit substantial levels of movement. This results in spurious, non-neural fluctuations of the rs-fMRI signal, which impair the evaluation of residual functional connectivity. Here, the effect of data preprocessing choices on the detectability of the DMN was systematically evaluated in a representative cohort of 30 clinically and etiologically heterogeneous DoC patients and 33 healthy controls. Starting from a standard preprocessing pipeline, additional steps were gradually inserted, namely band-pass filtering (BPF), removal of co-variance with the movement vectors, removal of co-variance with the global brain parenchyma signal, rejection of realignment outlier volumes and ventricle masking. Both independent-component analysis (ICA) and seed-based analysis (SBA) were performed, and DMN detectability was assessed quantitatively as well as visually. The results of the present study strongly show that the detection of DMN activity in the sub-optimal fMRI series acquired on DoC patients is contingent on the use of adequate filtering steps. ICA and SBA are differently affected but give convergent findings for high-grade preprocessing. We propose that future studies in this area should adopt the described preprocessing procedures as a minimum standard to reduce the probability of wrongly inferring that DMN activity is absent.

  19. Deficient visuospatial working memory functions and neural correlates of the default-mode network in adolescents with autism spectrum disorder.

    Science.gov (United States)

    Chien, Hsiang-Yun; Gau, Susan Shur-Fen; Isaac Tseng, Wen-Yih

    2016-10-01

    In addition to the essential features of autism spectrum disorder (ASD), namely social communication deficits and repetitive behaviors, individuals with ASD may suffer from working memory deficits and an altered default-mode network (DMN). We hypothesized that an altered DMN is related to working memory deficits in those with ASD. A total of 37 adolescents with ASD and 36 age- and IQ-matched typically developing (TD) controls were analyzed. Visuospatial working memory performance was assessed using pattern recognition memory (PRM), spatial recognition memory (SRM), and paired-associates learning (PAL) tasks. The intrinsic functional connectivity (iFC) of the DMN was indexed by the temporal correlations between the resting-state functional magnetic resonance imaging signals of pairs of DMN regions, including those between the posterior cingulate cortex (PCC) and medial prefrontal cortex (mPFC) and between the PCC and parahippocampi (PHG). The corresponding structural connectivity of the DMN was indexed by the generalized fractional anisotropy (GFA) of the dorsal and ventral cingulum bundles on the basis of diffusion spectrum imaging data. The results showed that ASD adolescents exhibited delayed correct responses in PRM and SRM tasks and committed more errors in the PAL task than the TD controls did. The delayed responses during the PRM and SRM tasks were negatively correlated with bilateral PCC-mPFC iFCs, and PAL performance was negatively correlated with right PCC-PHG iFC in ASD adolescents. Furthermore, ASD adolescents showed significant lower GFA in the right cingulum bundles than the TD group did; the GFA value was negatively correlated with SRM performance in ASD. Our results provide empirical evidence for deficient visuospatial working memory and corresponding neural correlates within the DMN in adolescents with ASD. Autism Res 2016, 9: 1058-1072. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

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

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    Maija Pihlajamäki

    2009-01-01

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

  1. Altered functional connectivity in the brain default-mode network of earthquake survivors persists after 2 years despite recovery from anxiety symptoms.

    Science.gov (United States)

    Du, Ming-Ying; Liao, Wei; Lui, Su; Huang, Xiao-Qi; Li, Fei; Kuang, Wei-Hong; Li, Jing; Chen, Hua-Fu; Kendrick, Keith Maurice; Gong, Qi-Yong

    2015-11-01

    Although acute impact of traumatic experiences on brain function in disaster survivors is similar to that observed in post-traumatic stress disorders (PTSD), little is known about the long-term impact of this experience. We have used structural and functional magnetic resonance imaging to investigate resting-state functional connectivity and gray and white matter (WM) changes occurring in the brains of healthy Wenchuan earthquake survivors both 3 weeks and 2 years after the disaster. Results show that while functional connectivity changes 3 weeks after the disaster involved both frontal-limbic-striatal and default-mode networks (DMN), at the 2-year follow-up only changes in the latter persisted, despite complete recovery from high initial levels of anxiety. No gray or WM volume changes were found at either time point. Taken together, our findings provide important new evidence that while altered functional connectivity in the frontal-limbic-striatal network may underlie the post-trauma anxiety experienced by survivors, parallel changes in the DMN persist despite the apparent absence of anxiety symptoms. This suggests that long-term changes occur in neural networks involved in core aspects of self-processing, cognitive and emotional functioning in disaster survivors which are independent of anxiety symptoms and which may also confer increased risk of subsequent development of PTSD. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  2. A Coordinate-Based Meta-Analysis of Overlaps in Regional Specialization and Functional Connectivity across Subjective Value and Default Mode Networks

    Science.gov (United States)

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

    2017-01-01

    Previous research has provided qualitative evidence for overlap in a number of brain regions across the subjective value network (SVN) and the default mode network (DMN). In order to quantitatively assess this overlap, we conducted a series of coordinate-based meta-analyses (CBMA) of results from 466 functional magnetic resonance imaging experiments on task-negative or subjective value-related activations in the human brain. In these analyses, we first identified significant overlaps and dissociations across activation foci related to SVN and DMN. Second, we investigated whether these overlapping subregions also showed similar patterns of functional connectivity, suggesting a shared functional subnetwork. We find considerable overlap between SVN and DMN in subregions of central ventromedial prefrontal cortex (cVMPFC) and dorsal posterior cingulate cortex (dPCC). Further, our findings show that similar patterns of bidirectional functional connectivity between cVMPFC and dPCC are present in both networks. We discuss ways in which our understanding of how subjective value (SV) is computed and represented in the brain can be synthesized with what we know about the DMN, mind-wandering, and self-referential processing in light of our findings. PMID:28154520

  3. Model-free adaptive sliding mode controller design for generalized projective synchronization of the fractional-order chaotic system via radial basis function neural networks

    Indian Academy of Sciences (India)

    L M WANG

    2017-09-01

    A novel model-free adaptive sliding mode strategy is proposed for a generalized projective synchronization (GPS) between two entirely unknown fractional-order chaotic systems subject to the external disturbances. To solve the difficulties from the little knowledge about the master–slave system and to overcome the bad effects of the external disturbances on the generalized projective synchronization, the radial basis function neural networks are used to approach the packaged unknown master system and the packaged unknown slave system (including the external disturbances). Consequently, based on the slide mode technology and the neural network theory, a model-free adaptive sliding mode controller is designed to guarantee asymptotic stability of the generalized projective synchronization error. The main contribution of this paper is that a control strategy is provided for the generalized projective synchronization between two entirely unknown fractional-order chaotic systems subject to the unknown external disturbances, and the proposed control strategy only requires that the master system has the same fractional orders as the slave system. Moreover, the proposed method allows us to achieve all kinds of generalized projective chaos synchronizations by turning the user-defined parameters onto the desired values. Simulation results show the effectiveness of the proposed method and the robustness of the controlled system.

  4. Model-free adaptive sliding mode controller design for generalized projective synchronization of the fractional-order chaotic system via radial basis function neural networks

    Science.gov (United States)

    Wang, L. M.

    2017-09-01

    A novel model-free adaptive sliding mode strategy is proposed for a generalized projective synchronization (GPS) between two entirely unknown fractional-order chaotic systems subject to the external disturbances. To solve the difficulties from the little knowledge about the master-slave system and to overcome the bad effects of the external disturbances on the generalized projective synchronization, the radial basis function neural networks are used to approach the packaged unknown master system and the packaged unknown slave system (including the external disturbances). Consequently, based on the slide mode technology and the neural network theory, a model-free adaptive sliding mode controller is designed to guarantee asymptotic stability of the generalized projective synchronization error. The main contribution of this paper is that a control strategy is provided for the generalized projective synchronization between two entirely unknown fractional-order chaotic systems subject to the unknown external disturbances, and the proposed control strategy only requires that the master system has the same fractional orders as the slave system. Moreover, the proposed method allows us to achieve all kinds of generalized projective chaos synchronizations by turning the user-defined parameters onto the desired values. Simulation results show the effectiveness of the proposed method and the robustness of the controlled system.

  5. 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

    2017-08-17

    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.

  6. The Default Mode Network is functionally and structurally disrupted in amnestic mild cognitive impairment — A bimodal MEG–DTI study

    Directory of Open Access Journals (Sweden)

    Pilar Garcés

    2014-01-01

    Full Text Available Over the past years, several studies on Mild Cognitive Impairment (MCI and Alzheimer's disease (AD have reported Default Mode Network (DMN deficits. This network is attracting increasing interest in the AD community, as it seems to play an important role in cognitive functioning and in beta amyloid deposition. Attention has been particularly drawn to how different DMN regions are connected using functional or structural connectivity. To this end, most studies have used functional Magnetic Resonance Imaging (fMRI, Positron Emission Tomography (PET or Diffusion Tensor Imaging (DTI. In this study we evaluated (1 functional connectivity from resting state magnetoencephalography (MEG and (2 structural connectivity from DTI in 26 MCI patients and 31 age-matched controls. Compared to controls, the DMN in the MCI group was functionally disrupted in the alpha band, while no differences were found for delta, theta, beta and gamma frequency bands. In addition, structural disconnection could be assessed through a decreased fractional anisotropy along tracts connecting different DMN regions. This suggests that the DMN functional and anatomical disconnection could represent a core feature of MCI.

  7. Mode Selection in Compressible Active Flow Networks

    Science.gov (United States)

    Forrow, Aden; Woodhouse, Francis G.; Dunkel, Jörn

    2017-07-01

    Coherent, large-scale dynamics in many nonequilibrium physical, biological, or information transport networks are driven by small-scale local energy input. Here, we introduce and explore an analytically tractable nonlinear model for compressible active flow networks. In contrast to thermally driven systems, we find that active friction selects discrete states with a limited number of oscillation modes activated at distinct fixed amplitudes. Using perturbation theory, we systematically predict the stationary states of noisy networks and find good agreement with a Bayesian state estimation based on a hidden Markov model applied to simulated time series data. Our results suggest that the macroscopic response of active network structures, from actomyosin force networks to cytoplasmic flows, can be dominated by a significantly reduced number of modes, in contrast to energy equipartition in thermal equilibrium. The model is also well suited to study topological sound modes and spectral band gaps in active matter.

  8. Sliding-mode and proportional-derivative-type motion control with radial basis function neural network based estimators for wheeled vehicles

    Science.gov (United States)

    Pamosoaji, Anugrah K.; Thuong Cat, Pham; Hong, Keum-Shik

    2014-12-01

    An obstacle avoidance problem of rear-steered wheeled vehicles in consideration of the presence of uncertainties is addressed. Modelling errors and additional uncertainties are taken into consideration. Controller designs for driving and steering motors are designed. A proportional-derivative-type driving motor controller and a sliding-mode steering controller combined with radial basis function neural network (RBFNN) based estimators are proposed. The convergence properties of the RBFNN-based estimators are proven by the Stone-Weierstrass theorem. The stability of the proposed control law is proven using Lyapunov stability analysis. The obstacle avoidance strategy utilising the sliding surface adjustment to an existing navigation method is presented. It is concluded that the driving velocity and steering-angle performances of the proposed control system are satisfactory.

  9. Fluctuating Elasticity Mode in Transient Molecular Networks

    Science.gov (United States)

    Nava, Giovanni; Rossi, Marina; Biffi, Silvia; Sciortino, Francesco; Bellini, Tommaso

    2017-08-01

    Transient molecular networks, a class of adaptive soft materials with remarkable application potential, display complex, and intriguing dynamic behavior. By performing dynamic light scattering on a wide angular range, we study the relaxation dynamics of a reversible network formed by DNA tetravalent nanoparticles, finding a slow relaxation mode that is wave vector independent at large q and crosses over to a standard q-2 viscoelastic relaxation at low q . Exploiting the controlled properties of our DNA network, we attribute this mode to fluctuations in local elasticity induced by connectivity rearrangement. We propose a simple beads and springs model that captures the basic features of this q0 behavior.

  10. Anatomical and functional connectivity in the default mode network of post-traumatic stress disorder patients after civilian and military-related trauma.

    Science.gov (United States)

    Reuveni, Inbal; Bonne, Omer; Giesser, Ruti; Shragai, Tamir; Lazarovits, Gilad; Isserles, Moshe; Schreiber, Shaul; Bick, Atira S; Levin, Netta

    2016-02-01

    Posttraumatic stress disorder (PTSD) is characterized by unwanted intrusive thoughts and hyperarousal at rest. As these core symptoms reflect disturbance in resting-state mechanisms, we investigated the functional and anatomical involvement of the default mode network (DMN) in this disorder. The relation between symptomatology and trauma characteristics was considered. Twenty PTSD patients and 20 matched trauma-exposed controls that were exposed to a similar traumatic event were recruited for this study. In each group, 10 patients were exposed to military trauma, and 10 to civilian trauma. PTSD, anxiety, and depression symptom severity were assessed. DMN maps were identified in resting-state scans using independent component analysis. Regions of interest (medial prefrontal, precuneus, and bilateral inferior parietal) were defined and average z-scores were extracted for use in the statistical analysis. The medial prefrontal and the precuneus regions were used for cingulum tractography whose integrity was measured and compared between groups. Similar functional and anatomical connectivity patterns were identified in the DMN of PTSD patients and trauma-exposed controls. In the PTSD group, functional and anatomical connectivity parameters were strongly correlated with clinical measures, and there was evidence of coupling between the anatomical and functional properties. Type of trauma and time from trauma were found to modulate connectivity patterns. To conclude, anatomical and functional connectivity patterns are related to PTSD symptoms and trauma characteristics influence connectivity beyond clinical symptoms. Hum Brain Mapp 37:589-599, 2016. © 2015 Wiley Periodicals, Inc.

  11. Cocaine addiction related reproducible brain regions of abnormal default-mode network functional connectivity: a group ICA study with different model orders.

    Science.gov (United States)

    Ding, Xiaoyu; Lee, Seong-Whan

    2013-08-26

    Model order selection in group independent component analysis (ICA) has a significant effect on the obtained components. This study investigated the reproducible brain regions of abnormal default-mode network (DMN) functional connectivity related with cocaine addiction through different model order settings in group ICA. Resting-state fMRI data from 24 cocaine addicts and 24 healthy controls were temporally concatenated and processed by group ICA using model orders of 10, 20, 30, 40, and 50, respectively. For each model order, the group ICA approach was repeated 100 times using the ICASSO toolbox and after clustering the obtained components, centrotype-based anterior and posterior DMN components were selected for further analysis. Individual DMN components were obtained through back-reconstruction and converted to z-score maps. A whole brain mixed effects factorial ANOVA was performed to explore the differences in resting-state DMN functional connectivity between cocaine addicts and healthy controls. The hippocampus, which showed decreased functional connectivity in cocaine addicts for all the tested model orders, might be considered as a reproducible abnormal region in DMN associated with cocaine addiction. This finding suggests that using group ICA to examine the functional connectivity of the hippocampus in the resting-state DMN may provide an additional insight potentially relevant for cocaine-related diagnoses and treatments. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  12. 网络营销的方式与作用%The mode and function of the network marketing

    Institute of Scientific and Technical Information of China (English)

    肖勠

    2014-01-01

    With the rapid development of network marketing,has greatly changed the basis for the existence of marketing theory and practice of the original,making the network marketing has changed deeply in the aspects of concept,information communication,nature of market,consumer concept and behavior.Businesses need to keep the advantage in the competition of economic globalization,we must use the modern network marketing,so how to use network marketing system to integrate the marketing resources,improve the efficiency of marketing,network marketing system to provide flexible,initiative is to study.Through the study of commercial network marketing system under electronic commerce environment,the business relationship can correctly handle the marketing costs and benefits,improve the service ability,timely and accurately determine the marketing strategy.%网络营销的出现与快速发展,极大地改变了原有的市场营销理论和实务存在的基础,使得网络营销在观念、信息传播模式、市场性质、消费者概念和行为等方面都发生了深刻的变化。商家要在经济全球化的竞争中保持优势,必须利用现代化的网络营销,所以如何利用网络营销系统整合企业营销资源,提高营销效率,提供灵活、主动的网络营销系统是现在必须研究的课题。通过对电子商务环境下的商业网络营销系统的研究,使商家能够正确处理营销成本与利益的关系,提高服务能力,及时准确地确定营销策略。

  13. The salience network causally influences default mode network activity during moral reasoning

    Science.gov (United States)

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

    2013-01-01

    Large-scale brain networks are integral to the coordination of human behaviour, and their anatomy provides insights into the clinical presentation and progression of neurodegenerative illnesses such as Alzheimer’s disease, which targets the default mode network, and behavioural variant frontotemporal dementia, which targets a more anterior salience network. Although the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, patients with Alzheimer’s disease give normal responses to these dilemmas whereas patients with behavioural variant frontotemporal dementia give abnormal responses to these dilemmas. We hypothesized that this apparent discrepancy between activation- and patient-based studies of moral reasoning might reflect a modulatory role for the salience network in regulating default mode network activation. Using functional magnetic resonance imaging to characterize network activity of patients with behavioural variant frontotemporal dementia and healthy control subjects, we present four converging lines of evidence supporting a causal influence from the salience network to the default mode network during moral reasoning. First, as previously reported, the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, but patients with behavioural variant frontotemporal dementia producing atrophy in the salience network give abnormally utilitarian responses to these dilemmas. Second, patients with behavioural variant frontotemporal dementia have reduced recruitment of the default mode network compared with healthy control subjects when deliberating about these dilemmas. Third, a Granger causality analysis of functional neuroimaging data from healthy control subjects demonstrates directed functional connectivity from nodes of the salience network to nodes of the default mode network during moral reasoning. Fourth, this Granger causal influence is diminished in

  14. Single-mode fiber systems for deep space communication network

    Science.gov (United States)

    Lutes, G.

    1982-01-01

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

  15. Default mode of brain function in monkeys.

    Science.gov (United States)

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

    2011-09-07

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

  16. The Default Mode Network and Altered Consciousness in Epilepsy

    Directory of Open Access Journals (Sweden)

    Nathan B. Danielson

    2011-01-01

    Full Text Available The default mode network has been hypothesized based on the observation that specific regions of the brain are consistently activated during the resting state and deactivated during engagement with task. The primary nodes of this network, which typically include the precuneus/posterior cingulate, the medial frontal and lateral parietal cortices, are thought to be involved in introspective and social cognitive functions. Interestingly, this same network has been shown to be selectively impaired during epileptic seizures associated with loss of consciousness. Using a wide range of neuroimaging and electrophysiological modalities, decreased activity in the default mode network has been confirmed during complex partial, generalized tonic-clonic, and absence seizures. In this review we will discuss these three seizure types and will focus on possible mechanisms by which decreased default mode network activity occurs. Although the specific mechanisms of onset and propagation differ considerably across these seizure types, we propose that the resulting loss of consciousness in all three types of seizures is due to active inhibition of subcortical arousal systems that normally maintain default mode network activity in the awake state. Further, we suggest that these findings support a general “network inhibition hypothesis”, by which active inhibition of arousal systems by seizures in certain cortical regions leads to cortical deactivation in other cortical areas. This may represent a push-pull mechanism similar to that seen operating between cortical networks under normal conditions.

  17. The default mode network and altered consciousness in epilepsy.

    Science.gov (United States)

    Danielson, Nathan B; Guo, Jennifer N; Blumenfeld, Hal

    2011-01-01

    The default mode network has been hypothesized based on the observation that specific regions of the brain are consistently activated during the resting state and deactivated during engagement with task. The primary nodes of this network, which typically include the precuneus/posterior cingulate, the medial frontal and lateral parietal cortices, are thought to be involved in introspective and social cognitive functions. Interestingly, this same network has been shown to be selectively impaired during epileptic seizures associated with loss of consciousness. Using a wide range of neuroimaging and electrophysiological modalities, decreased activity in the default mode network has been confirmed during complex partial, generalized tonic-clonic, and absence seizures. In this review we will discuss these three seizure types and will focus on possible mechanisms by which decreased default mode network activity occurs. Although the specific mechanisms of onset and propagation differ considerably across these seizure types, we propose that the resulting loss of consciousness in all three types of seizures is due to active inhibition of subcortical arousal systems that normally maintain default mode network activity in the awake state. Further, we suggest that these findings support a general "network inhibition hypothesis", by which active inhibition of arousal systems by seizures in certain cortical regions leads to cortical deactivation in other cortical areas. This may represent a push-pull mechanism similar to that seen operating between cortical networks under normal conditions.

  18. Aging and functional brain networks

    Energy Technology Data Exchange (ETDEWEB)

    Tomasi D.; Tomasi, D.; Volkow, N.D.

    2011-07-11

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

  19. Differences and the relationship in default mode network intrinsic activity and functional connectivity in mild Alzheimer's disease and amnestic mild cognitive impairment.

    Science.gov (United States)

    Weiler, Marina; Teixeira, Camila Vieira Ligo; Nogueira, Mateus Henrique; de Campos, Brunno Machado; Damasceno, Benito Pereira; Cendes, Fernando; Balthazar, Marcio Luiz Figueredo

    2014-10-01

    There is evidence that the default mode network (DMN) functional connectivity is impaired in Alzheimer's disease (AD) and few studies also reported a decrease in DMN intrinsic activity, measured by the amplitude of low-frequency fluctuations (ALFFs). In this study, we analyzed the relationship between DMN intrinsic activity and functional connectivity, as well as their possible implications on cognition in patients with mild AD and amnestic mild cognitive impairment (aMCI) and healthy controls. In addition, we evaluated the differences both in connectivity and ALFF values between these groups. We recruited 29 controls, 20 aMCI, and 32 mild AD patients. To identify the DMN, functional connectivity was calculated by placing a seed in the posterior cingulate cortex (PCC). Within the DMN mask obtained, we calculated regional average ALFFs. Compared with controls, aMCI patients showed decreased ALFFs in the temporal region; compared with AD, aMCI showed higher values in the PCC but lower in the temporal area. The mild AD group had lower ALFFs in the PCC compared with controls. There was no difference between the connectivity in the aMCI group compared with the other groups, but AD patients showed decreased connectivity in the frontal, parietal, and PCC. Also, PCC ALFFs correlated to functional connectivity in nearly all subregions. Cognitive tests correlated to connectivity values but not to ALFFs. In conclusion, we found that DMN connectivity and ALFFs are correlated in these groups. Decreased PCC ALFFs disrupt the DMN functional organization, leading to cognitive problems in the AD spectrum.

  20. Power-functional network

    Science.gov (United States)

    Sun, Yong; Kurths, Jürgen; Zhan, Meng

    2017-08-01

    Power grids and their properties have been studied broadly in many aspects. In this paper, we propose a novel concept, power-flow-based power grid, as a typical power-functional network, based on the calculation of power flow distribution from power electrical engineering. We compare it with structural networks based on the shortest path length and effective networks based on the effective electrical distance and study the relationship among these three kinds of networks. We find that they have roughly positive correlations with each other, indicating that in general any close nodes in the topological structure are actually connected in function. However, we do observe some counter-examples that two close nodes in a structural network can have a long distance in a power-functional network, namely, two physically connected nodes can actually be separated in function. In addition, we find that power grids in the structural network tend to be heterogeneous, whereas those in the effective and power-functional networks tend to be homogeneous. These findings are expected to be significant not only for power grids but also for various other complex networks.

  1. On Network Functional Compression

    CERN Document Server

    Feizi, Soheil

    2010-01-01

    In this paper, we consider different aspects of the network functional compression problem where computation of a function (or, some functions) of sources located at certain nodes in a network is desired at receiver(s). The rate region of this problem has been considered in the literature under certain restrictive assumptions, particularly in terms of the network topology, the functions and the characteristics of the sources. In this paper, we present results that significantly relax these assumptions. Firstly, we consider this problem for an arbitrary tree network and asymptotically lossless computation. We show that, for depth one trees with correlated sources, or for general trees with independent sources, a modularized coding scheme based on graph colorings and Slepian-Wolf compression performs arbitrarily closely to rate lower bounds. For a general tree network with independent sources, optimal computation to be performed at intermediate nodes is derived. We introduce a necessary and sufficient condition...

  2. Network Flows for Functions

    CERN Document Server

    Shah, Virag; Manjunath, D

    2010-01-01

    We consider in-network computation of an arbitrary function over an arbitrary communication network. A network with capacity constraints on the links is given. Some nodes in the network generate data, e.g., like sensor nodes in a sensor network. An arbitrary function of this distributed data is to be obtained at a terminal node. The structure of the function is described by a given computation schema, which in turn is represented by a directed tree. We design computing and communicating schemes to obtain the function at the terminal at the maximum rate. For this, we formulate linear programs to determine network flows that maximize the computation rate. We then develop fast combinatorial primal-dual algorithm to obtain $\\epsilon$-approximate solutions to these linear programs. We then briefly describe extensions of our techniques to the cases of multiple terminals wanting different functions, multiple computation schemas for a function, computation with a given desired precision, and to networks with energy c...

  3. Alteration of default mode network in high school football athletes due to repetitive subconcussive mild traumatic brain injury: a resting-state functional magnetic resonance imaging study.

    Science.gov (United States)

    Abbas, Kausar; Shenk, Trey E; Poole, Victoria N; Breedlove, Evan L; Leverenz, Larry J; Nauman, Eric A; Talavage, Thomas M; Robinson, Meghan E

    2015-03-01

    Long-term neurological damage as a result of head trauma while playing sports is a major concern for football athletes today. Repetitive concussions have been linked to many neurological disorders. Recently, it has been reported that repetitive subconcussive events can be a significant source of accrued damage. Since football athletes can experience hundreds of subconcussive hits during a single season, it is of utmost importance to understand their effect on brain health in the short and long term. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) was used to study changes in the default mode network (DMN) after repetitive subconcussive mild traumatic brain injury. Twenty-two high school American football athletes, clinically asymptomatic, were scanned using the rs-fMRI for a single season. Baseline scans were acquired before the start of the season, and follow-up scans were obtained during and after the season to track the potential changes in the DMN as a result of experienced trauma. Ten noncollision-sport athletes were scanned over two sessions as controls. Overall, football athletes had significantly different functional connectivity measures than controls for most of the year. The presence of this deviation of football athletes from their healthy peers even before the start of the season suggests a neurological change that has accumulated over the years of playing the sport. Football athletes also demonstrate short-term changes relative to their own baseline at the start of the season. Football athletes exhibited hyperconnectivity in the DMN compared to controls for most of the sessions, which indicates that, despite the absence of symptoms typically associated with concussion, the repetitive trauma accrued produced long-term brain changes compared to their healthy peers.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2017-01-01

    The present study used functional near-infrared spectroscopy (fNIRS) to measure 5- to 6-month-old infants’ hemodynamic response in the prefrontal cortex (PFC) to visual stimuli differing in saliency and social value. Nineteen Japanese 5- to 6-month-old infants watched video clips of Peek-a-Boo (social signal) performed by an anime character (AC) or a human, and hand movements without social signal performed by an AC. The PFC activity of infants was measured by 22-channel fNIRS, while behaviors including looking time were recorded simultaneously. NIRS data showed that infants’ hemodynamic responses in the PFC generally decreased due to these stimuli, and the decrease was most prominent in the frontopolar (FP), covering medial PFC (MPFC), when infants were viewing Peek-a-Boo performed by an AC. Moreover, the decrease was more pronounced in the dorsolateral PFC (DLPFC) when infants were viewing Peek-a-Boo performed by an AC than by a human. Accordingly, behavioral data revealed significantly longer looking times when Peek-a-Boo was performed by an AC than by a human. No significant difference between Peek-a-Boo and non-Peek-a-Boo conditions was observed in either measure. These findings indicate that infants at this age may prefer stimuli with more salient features, which may be more effective in attracting their attentions. In conjunction with our previous findings on responses to self-name calling in infants of similar age, we hypothesize that the dynamic function of the MPFC and its vicinity (as part of default mode network (DMN): enhanced by self-focused stimuli, attenuated by externally focused stimuli), which is consistently observed in adults, may have already emerged in 5- to 6-month-old infants. PMID:28119586

  6. Bioprinting: Functional droplet networks

    Science.gov (United States)

    Durmus, Naside Gozde; Tasoglu, Savas; Demirci, Utkan

    2013-06-01

    Tissue-mimicking printed networks of droplets separated by lipid bilayers that can be functionalized with membrane proteins are able to spontaneously fold and transmit electrical currents along predefined paths.

  7. Integration and Segregation of Default Mode Network Resting-state Functional Connectivity in Transition-age Males with High-functioning Autism Spectrum Disorder: A Proof of Concept Study.

    Science.gov (United States)

    Joshi, Gagan; Arnold Anteraper, Sheeba; Patil, Kaustubh; Semwal, Meha; Goldin, Rachel; Furtak, Stephannie; Chai, Xiaoqian Jenny; Saygin, Zeynep; Gabrieli, John D; Biederman, Joseph; Whitfield-Gabrieli, Susan

    2017-09-24

    To assess the resting-state functional connectivity (RsFc) profile of the default mode network (DMN) in transition-age males with autism spectrum disorder (ASD). Resting-state blood oxygen level dependent functional MRI (fMRI) data were acquired from adolescent and young adult males with high-functioning ASD (N=15) and from age-, sex-, and IQ-matched healthy controls (HC; N=16). The DMN was examined by assessing the positive and negative RsFc correlations of an average of the literature-based conceptualized major DMN nodes (medial prefrontal cortex [mPFC], posterior cingulate cortex, bilateral angular and inferior temporal gyrii regions). RsFc data analysis was performed using a seed driven approach. ASD was characterized by an altered pattern of RsFc in the DMN. The ASD group exhibited a weaker pattern of intra- and extra- DMN positive and negative RsFc correlations respectively. In ASD the strength of intra-DMN coupling was significantly reduced with the mPFC and the bilateral angular gyrii regions. In addition, the polarity of the extra-DMN correlation with the right hemispheric task-positive regions of fusiform gyrus and supramarginal gyrus was reversed from typically negative to positive in the ASD group. A wide variability was observed in the presentation of the RsFc profile of the DMN in both HC and ASD groups that revealed a distinct pattern of sub-grouping using pattern recognition analyses. These findings imply that the functional architecture profile of the DMN is altered in ASD with weaker than expected integration and segregation of the DMN RsFc. Future studies with larger sample sizes are warranted. Key Words: autism spectrum disorder, resting-state fMRI, default mode network.

  8. Voxelwise eigenvector centrality mapping of the human functional connectome reveals an influence of the catechol-O-methyltransferase val158met polymorphism on the default mode and somatomotor network.

    Science.gov (United States)

    Markett, Sebastian; Montag, Christian; Heeren, Behrend; Saryiska, Rayna; Lachmann, Bernd; Weber, Bernd; Reuter, Martin

    2016-06-01

    Functional connections between brain regions constitute the substrate of the human functional connectome, whose topography has been discussed as an endophenotype for psychiatric disorders. Genetic influences on the entire connectome, however, have been rarely investigated so far. We tested for connectome-wide influences of the val158met (rs4860) polymorphism on the catechol-O-methyltransferase (COMT) gene by applying formal network analysis and eigenvector centrality mapping on the voxel level to resting-state functional magnetic imaging data. This approach finds brain regions that are central in the network by aggregating local and global connectivity patterns, most importantly without the requirement to select regions or networks of interest. The COMT variant linked to high enzyme activity increased network centrality in distributed brain areas that are known to constitute the brain's default mode network. Further results also indicated a COMT influence on areas implicated in the somatomotor network. These findings are in line with the polymorphism's alleged role in cognitive processing and its role in psychotic disorders. The study is the first to demonstrate the influence of a functional and behaviorally relevant genetic variant on connectome-wide functional connectivity and is an important step toward establishing the functional connectome as an endophenotype for psychiatric and behavioral phenotypes.

  9. 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.

  10. Travel Mode Detection Exploiting Cellular Network Data

    Directory of Open Access Journals (Sweden)

    Kalatian Arash

    2016-01-01

    Full Text Available There has been growing interest in exploiting cellular network data for transportation planning purposes in recent years. In this paper, we utilize these data for determining mode of travel in the city of Shiraz, Iran. Cellular data records -including location updates in 5minute time intervals- of 300,000 users from the city of Shiraz has been collected for 40 hours in three consecutive days in a cooperation with the major telecommunications service provider of the country. Depending on the density of mobile BTS’s in different zones of the city, the user location can be located within an average of 200 meters. Considering data filtering and smoothing, data preparation and converting them to comprehensible traces is a large portion of the work. A novel approach to identify stay locations is proposed and implemented in this paper. Origin-Destination matrices are then created based on trips detected, which shows acceptable consistency with current O-D matrices. Finally, Travel times for all trips of a user is estimated as the main attribute for clustering. Trips between same origin and destination zones are combined together in a group. Using K-means algorithm, records within each group are the portioned in two or three clusters, based on their travel speeds. Each cluster represents a certain mode of travel; walking, public transportation or driving a private car.

  11. Automatic determination of important mode-mode correlations in many-mode vibrational wave functions.

    Science.gov (United States)

    König, Carolin; Christiansen, Ove

    2015-04-14

    We introduce new automatic procedures for parameterizing vibrational coupled cluster (VCC) and vibrational configuration interaction wave functions. Importance measures for individual mode combinations in the wave function are derived based on upper bounds to Hamiltonian matrix elements and/or the size of perturbative corrections derived in the framework of VCC. With a threshold, this enables an automatic, system-adapted way of choosing which mode-mode correlations are explicitly parameterized in the many-mode wave function. The effect of different importance measures and thresholds is investigated for zero-point energies and infrared spectra for formaldehyde and furan. Furthermore, the direct link between important mode-mode correlations and coordinates is illustrated employing water clusters as examples: Using optimized coordinates, a larger number of mode combinations can be neglected in the correlated many-mode vibrational wave function than with normal coordinates for the same accuracy. Moreover, the fraction of important mode-mode correlations compared to the total number of correlations decreases with system size. This underlines the potential gain in efficiency when using optimized coordinates in combination with a flexible scheme for choosing the mode-mode correlations included in the parameterization of the correlated many-mode vibrational wave function. All in all, it is found that the introduced schemes for parameterizing correlated many-mode vibrational wave functions lead to at least as systematic and accurate calculations as those using more standard and straightforward excitation level definitions. This new way of defining approximate calculations offers potential for future calculations on larger systems.

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

    OpenAIRE

    Yong Tao; Jiaqi Zheng; Yuanchang Lin

    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...

  13. Functional network organization of the human brain.

    Science.gov (United States)

    Power, Jonathan D; Cohen, Alexander L; Nelson, Steven M; Wig, Gagan S; Barnes, Kelly Anne; Church, Jessica A; Vogel, Alecia C; Laumann, Timothy O; Miezin, Fran M; Schlaggar, Bradley L; Petersen, Steven E

    2011-11-17

    Real-world complex systems may be mathematically modeled as graphs, revealing properties of the system. Here we study graphs of functional brain organization in healthy adults using resting state functional connectivity MRI. We propose two novel brain-wide graphs, one of 264 putative functional areas, the other a modification of voxelwise networks that eliminates potentially artificial short-distance relationships. These graphs contain many subgraphs in good agreement with known functional brain systems. Other subgraphs lack established functional identities; we suggest possible functional characteristics for these subgraphs. Further, graph measures of the areal network indicate that the default mode subgraph shares network properties with sensory and motor subgraphs: it is internally integrated but isolated from other subgraphs, much like a "processing" system. The modified voxelwise graph also reveals spatial motifs in the patterning of systems across the cortex.

  14. 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.)

  15. 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.

  16. Localizing and placement of network node functions in a network

    NARCIS (Netherlands)

    Strijkers, R.J.; Meulenhoff, P.J.

    2014-01-01

    The invention enables placement and use of a network node function in a second network node instead of using the network node function in a first network node. The network node function is e.g. a server function or a router function. The second network node is typically located in or close to the cl

  17. Localizing and placement of network node functions in a network

    NARCIS (Netherlands)

    Strijkers, R.J.; Meulenhoff, P.J.

    2014-01-01

    The invention enables placement and use of a network node function in a second network node instead of using the network node function in a first network node. The network node function is e.g. a server function or a router function. The second network node is typically located in or close to the

  18. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1999-01-01

    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  19. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1998-01-01

    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  20. Executive attention networks show altered relationship with default mode network in PD

    Directory of Open Access Journals (Sweden)

    Peter Boord

    2017-01-01

    Full Text Available Attention dysfunction is a common but often undiagnosed cognitive impairment in Parkinson's disease that significantly reduces quality of life. We sought to increase understanding of the mechanisms underlying attention dysfunction using functional neuroimaging. Functional MRI was acquired at two repeated sessions in the resting state and during the Attention Network Test, for 25 non-demented subjects with Parkinson's disease and 21 healthy controls. Behavioral and MRI contrasts were calculated for alerting, orienting, and executive control components of attention. Brain regions showing group differences in attention processing were used as seeds in a functional connectivity analysis of a separate resting state run. Parkinson's disease subjects showed more activation during increased executive challenge in four regions of the dorsal attention and frontoparietal networks, namely right frontal eye field, left and right intraparietal sulcus, and precuneus. In three regions we saw reduced resting state connectivity to the default mode network. Further, whereas higher task activation in the right intraparietal sulcus correlated with reduced resting state connectivity between right intraparietal sulcus and the precuneus in healthy controls, this relationship was absent in Parkinson's disease subjects. Our results suggest that a weakened interaction between the default mode and task positive networks might alter the way in which the executive response is processed in PD.

  1. Multiple relaxation modes in associative polymer networks with varying connectivity

    Science.gov (United States)

    Bohdan, M.; Sprakel, J.; van der Gucht, J.

    2016-09-01

    The dynamics and mechanics of networks depend sensitively on their spatial connectivity. To explore the effect of connectivity on local network dynamics, we prepare transient polymer networks in which we systematically cut connecting bonds. We do this by creating networks formed from hydrophobically modified difunctionalized polyethylene glycol chains. These form physical gels, consisting of flowerlike micelles that are transiently cross-linked by connecting bridges. By introducing monofunctionalized chains, we can systematically reduce the number of bonds between micelles and thus lower the network connectivity, which strongly reduces the network elasticity and relaxation time. Dynamic light scattering reveals a complex relaxation dynamics that are not apparent in bulk rheology. We observe three distinct relaxation modes. First we find a fast diffusive mode that does not depend on the number of bridges and is attributed to the diffusion of micelles within a cage formed by neighboring micelles. A second, intermediate mode depends strongly on network connectivity but surprisingly is independent of the scattering vector q . We attribute this viscoelastic mode to fluctuations in local connectivity of the network. The third, slowest mode is also diffusive and is attributed to the diffusion of micelle clusters through the viscoelastic matrix. These results shed light on the microscopic dynamics in weakly interconnected transient networks.

  2. Biological couplings: Function, characteristics and implementation mode

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Through rigorous natural selection, biological organisms have evolved exceptional functions highly adaptable to their living environments. Biological organisms can achieve a variety of biological functions efficiently by using the synergic actions of two or more different parts of the body, or the coupling effects of multiple factors, and demonstrate optimal adaptations to the living environment. In this paper, the function, characteristics and types of biological couplings are analyzed, the implementation mechanism and mode of biological coupling functions are revealed from the bionic viewpoint. Finally, the technological prospects of the bionic implementation of biological coupling function are predicted.

  3. Links among resting-state default-mode network, salience network, and symptomatology in schizophrenia.

    Science.gov (United States)

    Orliac, François; Naveau, Mickael; Joliot, Marc; Delcroix, Nicolas; Razafimandimby, Annick; Brazo, Perrine; Dollfus, Sonia; Delamillieure, Pascal

    2013-08-01

    Neuroimaging data support the idea that schizophrenia is a brain disorder with altered brain structure and function. New resting-state functional connectivity techniques allow us to highlight synchronization of large-scale networks, such as the default-mode network (DMN) and salience network (SN). A large body of work suggests that disruption of these networks could give rise to specific schizophrenia symptoms. We examined the intra-network connectivity strength and gray matter content (GMC) of DMN and SN in 26 schizophrenia patients using resting-state functional magnetic resonance imaging and voxel-based morphometry. Resting-state data were analyzed with independent component analysis and dual-regression techniques. We reported reduced functional connectivity within both DMN and SN in patients with schizophrenia. Concerning the DMN, patients showed weaker connectivity in a cluster located in the right paracingulate cortex. Moreover, patients showed decreased GMC in this cluster. With regard to the SN, patients showed reduced connectivity in the left and right striatum. Decreased connectivity in the paracingulate cortex was correlated with difficulties in abstract thinking. The connectivity decrease in the left striatum was correlated with delusion and depression scores. Correlation between the connectivity of DMN frontal regions and difficulties in abstract thinking emphasizes the link between negative symptoms and the likely alteration of the frontal medial cortex in schizophrenia. Correlation between the connectivity of SN striatal regions and delusions supports the aberrant salience hypothesis. This work provides new insights into dysfunctional brain organization in schizophrenia and its contribution to specific schizophrenia symptoms.

  4. The brain's code and its canonical computational motifs. From sensory cortex to the default mode network: A multi-scale model of brain function in health and disease.

    Science.gov (United States)

    Turkheimer, Federico E; Leech, Robert; Expert, Paul; Lord, Louis-David; Vernon, Anthony C

    2015-08-01

    A variety of anatomical and physiological evidence suggests that the brain performs computations using motifs that are repeated across species, brain areas, and modalities. The computational architecture of cortex, for example, is very similar from one area to another and the types, arrangements, and connections of cortical neurons are highly stereotyped. This supports the idea that each cortical area conducts calculations using similarly structured neuronal modules: what we term canonical computational motifs. In addition, the remarkable self-similarity of the brain observables at the micro-, meso- and macro-scale further suggests that these motifs are repeated at increasing spatial and temporal scales supporting brain activity from primary motor and sensory processing to higher-level behaviour and cognition. Here, we briefly review the biological bases of canonical brain circuits and the role of inhibitory interneurons in these computational elements. We then elucidate how canonical computational motifs can be repeated across spatial and temporal scales to build a multiplexing information system able to encode and transmit information of increasing complexity. We point to the similarities between the patterns of activation observed in primary sensory cortices by use of electrophysiology and those observed in large scale networks measured with fMRI. We then employ the canonical model of brain function to unify seemingly disparate evidence on the pathophysiology of schizophrenia in a single explanatory framework. We hypothesise that such a framework may also be extended to cover multiple brain disorders which are grounded in dysfunction of GABA interneurons and/or these computational motifs.

  5. Default mode network dissociation in depressive and anxiety states.

    Science.gov (United States)

    Coutinho, Joana Fernandes; Fernandesl, Sara Veiga; Soares, José Miguel; Maia, Liliana; Gonçalves, Óscar Filipe; Sampaio, Adriana

    2016-03-01

    The resting state brain networks, particularly the Default Mode Network (DMN), have been found to be altered in several psychopathological conditions such as depression and anxiety. In this study we hypothesized that cortical areas of the DMN, particularly the anterior regions--medial prefrontal cortex and anterior cingulate cortex--would show an increased functional connectivity associated with both anxiety and depression. Twenty-four healthy participants were assessed using Hamilton Depression and Anxiety Rating Scales and completed a resting-state functional magnetic resonance imaging scan. Multiple regression was performed in order to identify which areas of the DMN were associated with anxiety and depression scores. We found that the functional connectivity of the anterior portions of DMN, involved in self-referential and emotional processes, was positively correlated with anxiety and depression scores, whereas posterior areas of the DMN, involved in episodic memory and perceptual processing were negatively correlated with anxiety and depression scores. The dissociation between anterior and posterior cortical midline regions, raises the possibility of a functional specialization within the DMN in terms of self-referential tasks and contributes to the understanding of the cognitive and affective alterations in depressive and anxiety states.

  6. Network-based functional enrichment

    Directory of Open Access Journals (Sweden)

    Poirel Christopher L

    2011-11-01

    Full Text Available Abstract Background Many methods have been developed to infer and reason about molecular interaction networks. These approaches often yield networks with hundreds or thousands of nodes and up to an order of magnitude more edges. It is often desirable to summarize the biological information in such networks. A very common approach is to use gene function enrichment analysis for this task. A major drawback of this method is that it ignores information about the edges in the network being analyzed, i.e., it treats the network simply as a set of genes. In this paper, we introduce a novel method for functional enrichment that explicitly takes network interactions into account. Results Our approach naturally generalizes Fisher’s exact test, a gene set-based technique. Given a function of interest, we compute the subgraph of the network induced by genes annotated to this function. We use the sequence of sizes of the connected components of this sub-network to estimate its connectivity. We estimate the statistical significance of the connectivity empirically by a permutation test. We present three applications of our method: i determine which functions are enriched in a given network, ii given a network and an interesting sub-network of genes within that network, determine which functions are enriched in the sub-network, and iii given two networks, determine the functions for which the connectivity improves when we merge the second network into the first. Through these applications, we show that our approach is a natural alternative to network clustering algorithms. Conclusions We presented a novel approach to functional enrichment that takes into account the pairwise relationships among genes annotated by a particular function. Each of the three applications discovers highly relevant functions. We used our methods to study biological data from three different organisms. Our results demonstrate the wide applicability of our methods. Our algorithms are

  7. A potential biomarker in sports-related concussion: brain functional connectivity alteration of the default-mode network measured with longitudinal resting-state fMRI over thirty days.

    Science.gov (United States)

    Zhu, David C; Covassin, Tracey; Nogle, Sally; Doyle, Scarlett; Russell, Doozie; Pearson, Randolph L; Monroe, Jeffrey; Liszewski, Christine M; DeMarco, J Kevin; Kaufman, David I

    2015-03-01

    Current diagnosis and monitoring of sports-related concussion rely on clinical signs and symptoms, and balance, vestibular, and neuropsychological examinations. Conventional brain imaging often does not reveal abnormalities. We sought to assess if the longitudinal change of functional and structural connectivity of the default-mode network (DMN) can serve as a potential biomarker. Eight concussed Division I collegiate football student-athletes in season (one participated twice) and 11 control subjects participated in this study. ImPACT (Immediate Post-Concussion Assessment and Cognitive Testing) was administered over the course of recovery. High-resolution three dimensional T1-weighted, T2*-weighted diffusion-tensor images and resting-state functional magnetic resonance imaging (rs-fMRI) scans were collected from each subject within 24 h, 7±1 d and 30±1 d after concussion. Both network based and whole-brain based functional correlation analyses on DMN were performed. ImPACT findings demonstrated significant cognitive impairment across multiple categories and a significant increase of symptom severity on Day 1 following a concussion but full recovery by 6.0±2.4 d. While the structural connectivity within DMN and gross anatomy appeared unchanged, a significantly reduced functional connectivity within DMN from Day 1 to Day 7 was found in the concussed group in this small pilot study. This reduction was seen in eight of our nine concussion cases. Compared with the control group, there appears a general trend of increased DMN functional connectivity on Day 1, a significant drop on Day 7, and partial recovery on Day 30. The results of this pilot study suggest that the functional connectivity of DMN measured with longitudinal rs-fMRI can serve as a potential biomarker to monitor the dynamically changing brain function after sports-related concussion, even in patients who have shown clinical improvement.

  8. 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.

  9. Instantaneous Gradient Based Dual Mode Feed-Forward Neural Network Blind Equalization Algorithm

    Directory of Open Access Journals (Sweden)

    Ying Xiao

    2013-01-01

    Full Text Available To further improve the performance of feed-forward neural network blind equalization based on Constant Modulus Algorithm (CMA cost function, an instantaneous gradient based dual mode between Modified Constant Modulus Algorithm (MCMA and Decision Directed (DD algorithm was proposed. The neural network weights change quantity of the adjacent iterative process is defined as instantaneous gradient. After the network converges, the weights of neural network to achieve a stable energy state and the instantaneous gradient would be zero. Therefore dual mode algorithm can be realized by criterion which set according to the instantaneous gradient. Computer simulation results show that the dual mode feed-forward neural network blind equalization algorithm proposed in this study improves the convergence rate and convergence precision effectively, at the same time, has good restart and tracking ability under channel burst interference condition.

  10. 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

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

    Science.gov (United States)

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

    2017-01-01

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

  12. Physical activity over a decade modifies age-related decline in perfusion, gray matter volume, and functional connectivity of the posterior default-mode network-A multimodal approach.

    Science.gov (United States)

    Boraxbekk, Carl-Johan; Salami, Alireza; Wåhlin, Anders; Nyberg, Lars

    2016-05-01

    One step toward healthy brain aging may be to entertain a physically active lifestyle. Studies investigating physical activity effects on brain integrity have, however, mainly been based on single brain markers, and few used a multimodal imaging approach. In the present study, we used cohort data from the Betula study to examine the relationships between scores reflecting current and accumulated physical activity and brain health. More specifically, we first examined if physical activity scores modulated negative effects of age on seven resting state networks previously identified by Salami, Pudas, and Nyberg (2014). The results revealed that one of the most age-sensitive RSN was positively altered by physical activity, namely, the posterior default-mode network involving the posterior cingulate cortex (PCC). Second, within this physical activity-sensitive RSN, we further analyzed the association between physical activity and gray matter (GM) volumes, white matter integrity, and cerebral perfusion using linear regression models. Regions within the identified DMN displayed larger GM volumes and stronger perfusion in relation to both current and 10-years accumulated scores of physical activity. No associations of physical activity and white matter integrity were observed. Collectively, our findings demonstrate strengthened PCC-cortical connectivity within the DMN, larger PCC GM volume, and higher PCC perfusion as a function of physical activity. In turn, these findings may provide insights into the mechanisms of how long-term regular exercise can contribute to healthy brain aging. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Patterns of Default Mode Network Deactivation in Obsessive Compulsive Disorder

    Science.gov (United States)

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

    2017-01-01

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

  14. 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

  15. Comparison of VDL Modes in the Aeronautical Telecommunications Network

    Science.gov (United States)

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

    2002-01-01

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

  16. Edge Detection System using Pulse Mode Neural Network for Image Enhancement

    Directory of Open Access Journals (Sweden)

    S.Jagadeesh Babu

    2012-04-01

    Full Text Available Edge detection of an image reduces significantly the amount of data and filters out information that may be regarded as less irrelevant. Edge detection is efficient in medical imaging. Pulse mode neural networks are becoming an attractive solution for function approximation based on frequency modulation. Early pulse mode implementation suffers from some network constraints due to weight range limitations. To provide the best edge detection, the basic algorithm is modified to have pulse mode operations for effective hardware implementation. In this project a new pulse mode network architecture using floating point operations is used in the activation function. By using floating point number system for synapse weight value representation, any function can be approximated by the network. The proposed pulse mode MNN is used to detect the edges in images forming a heterogeneous data base. It shows good learning capability. In addition, four edge detection techniques have been compared. The coding is written in verilog and the final result have been simulated using Xilinx ISE simulator.

  17. Resting-state connectivity in the default mode network and insula during experimental low back pain

    Institute of Scientific and Technical Information of China (English)

    Shanshan Zhang; Wen Wu; Guozhi Huang; Ziping Liu; Shigui Guo; Jianming Yang; Kangling Wang

    2014-01-01

    Functional magnetic resonance imaging studies have shown that the insular cortex has a signif-icant role in pain identiifcation and information integration, while the default mode network is associated with cognitive and memory-related aspects of pain perception. However, changes in the functional connectivity between the default mode network and insula during pain remain unclear. This study used 3.0 T functional magnetic resonance imaging scans in 12 healthy sub-jects aged 24.8 ± 3.3 years to compare the differences in the functional activity and connectivity of the insula and default mode network between the baseline and pain condition induced by intramuscular injection of hypertonic saline. Compared with the baseline, the insula was more functionally connected with the medial prefrontal and lateral temporal cortices, whereas there was lower connectivity with the posterior cingulate cortex, precuneus and inferior parietal lobule in the pain condition. In addition, compared with baseline, the anterior cingulate cortex exhibited greater connectivity with the posterior insula, but lower connectivity with the anterior insula, during the pain condition. These data indicate that experimental low back pain led to dysfunction in the connectivity between the insula and default mode network resulting from an impairment of the regions of the brain related to cognition and emotion, suggesting the impor-tance of the interaction between these regions in pain processing.

  18. Aging Influence on Gray Matter Structural Associations within the Default Mode Network Utilizing Bayesian Network Modeling.

    Science.gov (United States)

    Wang, Yan; Chen, Kewei; Zhang, Jiacai; Yao, Li; Li, Ke; Jin, Zhen; Ye, Qing; Guo, Xiaojuan

    2014-01-01

    Recent neuroimaging studies have revealed normal aging-related alterations in functional and structural brain networks such as the default mode network (DMN). However, less is understood about specific brain structural dependencies or interactions between brain regions within the DMN in the normal aging process. In this study, using Bayesian network (BN) modeling, we analyzed gray matter volume data from 109 young and 82 old subjects to characterize the influence of aging on associations between core brain regions within the DMN. Furthermore, we investigated the discriminability of the aging-associated BN models for the young and old groups. Compared to their young counterparts, the old subjects showed significant reductions in connections from right inferior temporal cortex (ITC) to medial prefrontal cortex (mPFC), right hippocampus (HP) to right ITC, and mPFC to posterior cingulate cortex and increases in connections from left HP to mPFC and right inferior parietal cortex to right ITC. Moreover, the classification results showed that the aging-related BN models could predict group membership with 88.48% accuracy, 88.07% sensitivity, and 89.02% specificity. Our findings suggest that structural associations within the DMN may be affected by normal aging and provide crucial information about aging effects on brain structural networks.

  19. Aging influence on grey matter structural associations within the default mode network utilizing Bayesian network modeling

    Directory of Open Access Journals (Sweden)

    Yan eWang

    2014-05-01

    Full Text Available Recent neuroimaging studies have revealed normal aging-related alterations in functional and structural brain networks such as the default mode network (DMN. However, less is understood about specific brain structural dependencies or interactions between brain regions within the DMN in the normal aging process. In this study, using Bayesian network (BN modeling, we analyzed grey matter volume data from 109 young and 82 old subjects to characterize the influence of aging on associations between core brain regions within the DMN. Furthermore, we investigated the discriminability of the aging-associated BN models for the young and old groups. Compared to their young counterparts, the old subjects showed significant reductions in connections from right inferior temporal cortex (ITC to medial prefrontal cortex (mPFC, right hippocampus (HP to right ITC, and mPFC to posterior cingulate cortex (PCC and increases in connections from left HP to mPFC and right inferior parietal cortex (IPC to right ITC. Moreover, the classification results showed that the aging-related BN models could predict group membership with 88.48% accuracy, 88.07% sensitivity and 89.02% specificity. Our findings suggest that structural associations within the DMN may be affected by normal aging and provide crucial information about aging effects on brain structural networks.

  20. Differential evolutionary conservation of motif modes in the yeast protein interaction network

    Directory of Open Access Journals (Sweden)

    Yu Chang-Yung

    2006-04-01

    Full Text Available Abstract Background The importance of a network motif (a recurring interconnected pattern of special topology which is over-represented in a biological network lies in its position in the hierarchy between the protein molecule and the module in a protein-protein interaction network. Until now, however, the methods available have greatly restricted the scope of research. While they have focused on the analysis in the resolution of a motif topology, they have not been able to distinguish particular motifs of the same topology in a protein-protein interaction network. Results We have been able to assign the molecular function annotations of Gene Ontology to each protein in the protein-protein interactions of Saccharomyces cerevisiae. For various motif topologies, we have developed an algorithm, enabling us to unveil one million "motif modes", each of which features a unique topological combination of molecular functions. To our surprise, the conservation ratio, i.e., the extent of the evolutionary constraints upon the motif modes of the same motif topology, varies significantly, clearly indicative of distinct differences in the evolutionary constraints upon motifs of the same motif topology. Equally important, for all motif modes, we have found a power-law distribution of the motif counts on each motif mode. We postulate that motif modes may very well represent the evolutionary-conserved topological units of a protein interaction network. Conclusion For the first time, the motifs of a protein interaction network have been investigated beyond the scope of motif topology. The motif modes determined in this study have not only enabled us to differentiate among different evolutionary constraints on motifs of the same topology but have also opened up new avenues through which protein interaction networks can be analyzed.

  1. Multi-mode clustering model for hierarchical wireless sensor networks

    Science.gov (United States)

    Hu, Xiangdong; Li, Yongfu; Xu, Huifen

    2017-03-01

    The topology management, i.e., clusters maintenance, of wireless sensor networks (WSNs) is still a challenge due to its numerous nodes, diverse application scenarios and limited resources as well as complex dynamics. To address this issue, a multi-mode clustering model (M2 CM) is proposed to maintain the clusters for hierarchical WSNs in this study. In particular, unlike the traditional time-trigger model based on the whole-network and periodic style, the M2 CM is proposed based on the local and event-trigger operations. In addition, an adaptive local maintenance algorithm is designed for the broken clusters in the WSNs using the spatial-temporal demand changes accordingly. Numerical experiments are performed using the NS2 network simulation platform. Results validate the effectiveness of the proposed model with respect to the network maintenance costs, node energy consumption and transmitted data as well as the network lifetime.

  2. Functional MRI observation of the aging selective degradation mode of large-scale brain functional networks%功能磁共振观察老年人大尺度脑功能网络选择性的退化模式

    Institute of Scientific and Technical Information of China (English)

    吴晶涛; 陈文新; 张洪英; 田彤彤; 杨海山

    2016-01-01

    目的 探讨功能磁共振大尺度脑网络在脑衰老进程中的变化特征和内在机制. 方法 招募健康青年人和老年人受试者,老年组20例,平均年龄(72.4±4.6)岁;青年人18例,平均年龄(23.9±1.8)岁.受试者接受血氧水平依赖的静息功能磁共振检查,采用种子区方法及双回归处理功能数据,提取默认网络、注意网络、执行控制网络、突显网络,视觉网络,进行统计学比较. 结果 相对于青年组,老年组的网络连接性损害呈现了明显不同的变化模式,执行控制网络受损最重,其次是注意网络,默认网络和突显网络轻度受影响,这些高级认知功能相关网络受损,而较低级的视觉感觉网络未见明显变化. 结论 健康人的脑衰老表现为在网络水平上呈现有组织性的变化;老年期大尺度的脑网络呈现选择性的损害,高级认知网络较低级脑功能网络退变更突出.%Objective To investigate the degradation characteristics of the large-scale brain functional networks during aging by functional magnetic resonance imaging measurement and explore its intrinsic mechanism.Methods 40 healthy subjects including 20 elderly persons [mean aged(72.4 ±4.6)years] and 18 young persons [mean aged(23.9± 1.8) years] were enrolled in this study.All subjects underwent functional MRI scanning at blood oxygenation level-dependent contrast resting state.Four canonical resting-state networks,including the default mode network (DMN),dorsal attention network (DAN),executive control network (ECN),salience network,and visual network,were extracted by the seed zone and double regression methods.The functional connectivities in these canonical networks were compared between the young and elderly persons.Results Compared with young persons,the elderly showed the distinct and disruptive alterations in the large-scale aging-related resting brain networks.The impairment of ECN was the most serious,followed by the impairment of DAN

  3. Impact of Transit Network Layout on Resident Mode Choice

    Directory of Open Access Journals (Sweden)

    Jian Gao

    2013-01-01

    Full Text Available This study reviews the impact of public transit network layout (TNL on resident mode choice. The review of TNL as a factor uses variables divided into three groups: a variable set without considering the TNL, one considering TNL from the zone level, and one considering TNL from the individual level. Using Baoding’s travel survey data, a Multinomial Logit (MNL model is used, and the parameter estimation result shows that TNL has significant effect on resident mode choice. Based on parameter estimation, the factors affecting mode choice are further screened. The screened variable set is regarded as the input data to the BP neural network’s training and forecasting. Both forecasting results indicate that introducing TNL can improve the performance of mode choice forecasting.

  4. Changes in cognitive state alter human functional brain networks

    Directory of Open Access Journals (Sweden)

    Malaak Nasser Moussa

    2011-08-01

    Full Text Available The study of the brain as a whole system can be accomplished using network theory principles. Research has shown that human functional brain networks during a resting state exhibit small-world properties and high degree nodes, or hubs, localized to brain areas consistent with the default mode network (DMN. However, the study of brain networks across different tasks and or cognitive states has been inconclusive. Research in this field is important because the underpinnings of behavioral output are inherently dependent on whether or not brain networks are dynamic. This is the first comprehensive study to evaluate multiple network metrics at a voxel-wise resolution in the human brain at both the whole brain and regional level under various conditions: resting state, visual stimulation, and multisensory (auditory and visual stimulation. Our results show that despite global network stability, functional brain networks exhibit considerable task-induced changes in connectivity, efficiency, and community structure at the regional level.

  5. On Functional Module Detection in Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Ina Koch

    2013-08-01

    Full Text Available Functional modules of metabolic networks are essential for understanding the metabolism of an organism as a whole. With the vast amount of experimental data and the construction of complex and large-scale, often genome-wide, models, the computer-aided identification of functional modules becomes more and more important. Since steady states play a key role in biology, many methods have been developed in that context, for example, elementary flux modes, extreme pathways, transition invariants and place invariants. Metabolic networks can be studied also from the point of view of graph theory, and algorithms for graph decomposition have been applied for the identification of functional modules. A prominent and currently intensively discussed field of methods in graph theory addresses the Q-modularity. In this paper, we recall known concepts of module detection based on the steady-state assumption, focusing on transition-invariants (elementary modes and their computation as minimal solutions of systems of Diophantine equations. We present the Fourier-Motzkin algorithm in detail. Afterwards, we introduce the Q-modularity as an example for a useful non-steady-state method and its application to metabolic networks. To illustrate and discuss the concepts of invariants and Q-modularity, we apply a part of the central carbon metabolism in potato tubers (Solanum tuberosum as running example. The intention of the paper is to give a compact presentation of known steady-state concepts from a graph-theoretical viewpoint in the context of network decomposition and reduction and to introduce the application of Q-modularity to metabolic Petri net models.

  6. Caffeine Modulates Attention Network Function

    Science.gov (United States)

    Brunye, Tad T.; Mahoney, Caroline R.; Lieberman, Harris R.; Taylor, Holly A.

    2010-01-01

    The present work investigated the effects of caffeine (0 mg, 100 mg, 200 mg, 400 mg) on a flanker task designed to test Posner's three visual attention network functions: alerting, orienting, and executive control [Posner, M. I. (2004). "Cognitive neuroscience of attention". New York, NY: Guilford Press]. In a placebo-controlled, double-blind…

  7. Caffeine Modulates Attention Network Function

    Science.gov (United States)

    Brunye, Tad T.; Mahoney, Caroline R.; Lieberman, Harris R.; Taylor, Holly A.

    2010-01-01

    The present work investigated the effects of caffeine (0 mg, 100 mg, 200 mg, 400 mg) on a flanker task designed to test Posner's three visual attention network functions: alerting, orienting, and executive control [Posner, M. I. (2004). "Cognitive neuroscience of attention". New York, NY: Guilford Press]. In a placebo-controlled, double-blind…

  8. Analysis of oversized sliding waveguide by mode matching and multi-mode network theory

    Energy Technology Data Exchange (ETDEWEB)

    Ohkubo, K.; Kubo, S.; Idei, H.; Shimozuma, T.; Yoshimura, Y.; Sato, M.; Takita, Y. [National Inst. for Fusion Science, Toki, Gifu (Japan); Leuterer, F. [Max-Planck Institut fuer Plasmaphysik, Garching (Germany)

    2000-12-01

    Transmission and reflection coefficients of HE{sub 11} hybrid modes in the sliding waveguide are discussed on the basis of mode matching method and multi-mode network theory. The sliding waveguide is composed of the corrugated waveguide with 88.9 mm{phi} and the smooth-wall waveguide with 110 mm{phi} in inner diameter. It is confirmed that the decrease in power of <0.2% at 84 GHz is obtained for 2 cm in gap of the sliding waveguide. At the sliding length near multi-half-wavelength in vacuum, transmission and reflection powers in the sliding waveguide change slightly, because the very small amount of standing wave of higher-order TE or TM modes is produced resonantly. (author)

  9. Damage to the default mode network disrupts autobiographical memory retrieval.

    Science.gov (United States)

    Philippi, Carissa L; Tranel, Daniel; Duff, Melissa; Rudrauf, David

    2015-03-01

    Functional neuroimaging studies have implicated the default mode network (DMN) in autobiographical memory (AM). Convergent evidence from a lesion approach would help clarify the role of the DMN in AM. In this study, we used a voxelwise lesion-deficit approach to test the hypothesis that regions of the DMN are necessary for AM. We also explored whether the neural correlates of semantic AM (SAM) and episodic AM (EAM) were overlapping or distinct. Using the Iowa Autobiographical Memory Questionnaire, we tested AM retrieval in 92 patients with focal, stable brain lesions. In support of our hypothesis, damage to regions within the DMN (medial prefrontal cortex, mPFC; posterior cingulate cortex, PCC; inferior parietal lobule, IPL; medial temporal lobe, MTL) was associated with AM impairments. Within areas of effective lesion coverage, the neural correlates of SAM and EAM were largely distinct, with limited areas of overlap in right IPL. Whereas SAM deficits were associated with left mPFC and MTL damage, EAM deficits were associated with right mPFC and MTL damage. These results provide novel neuropsychological evidence for the necessary role of parts of the DMN in AM. More broadly, the findings shed new light on how the DMN participates in self-referential processing.

  10. Boolean networks with veto functions

    Science.gov (United States)

    Ebadi, Haleh; Klemm, Konstantin

    2014-08-01

    Boolean networks are discrete dynamical systems for modeling regulation and signaling in living cells. We investigate a particular class of Boolean functions with inhibiting inputs exerting a veto (forced zero) on the output. We give analytical expressions for the sensitivity of these functions and provide evidence for their role in natural systems. In an intracellular signal transduction network [Helikar et al., Proc. Natl. Acad. Sci. USA 105, 1913 (2008), 10.1073/pnas.0705088105], the functions with veto are over-represented by a factor exceeding the over-representation of threshold functions and canalyzing functions in the same system. In Boolean networks for control of the yeast cell cycle [Li et al., Proc. Natl. Acad. Sci. USA 101, 4781 (2004), 10.1073/pnas.0305937101; Davidich et al., PLoS ONE 3, e1672 (2008), 10.1371/journal.pone.0001672], no or minimal changes to the wiring diagrams are necessary to formulate their dynamics in terms of the veto functions introduced here.

  11. Applying Network Technology to Improve TV News Production Mode

    Institute of Scientific and Technical Information of China (English)

    冷劲松; 林成栋

    2003-01-01

    With the development of database and computer network technology, traditional TV news production mode (TVNPM) faces great challenge. Up to now, evolution of TVNPM has experienced two stages: In the beginning, TV news is produced completely by hand, named as pipelining TVNPM in this paper. This production mode is limited to space and time, so its production cycle is very time-consuming, and it requires a lot of harmony in different departments; Subsequently, thanks to applications of database technology, a new TVNPM appears, which is named as pooled information resource TVNPM. Compared with pipelining TVNPM, this mode promotes information sharing. However, with the development of network technology, especially the Intranet and the Internet, the pooled information resource TVNPM receives strong impact, and it is referred to contrive a new TVNPM. This new TVNPM must support information sharing, remote collaboration, and interaction in communications so as to improve group work efficiency. In this paper, we present such a new TVNPM, namely, Network TVNPM, give a suit of system solution to support the new TVNPM, introduce the new workflow, and in the end analyze the advantages of Network TVNPM.

  12. Stability of Rotor Hopfield Neural Networks With Synchronous Mode.

    Science.gov (United States)

    Kobayashi, Masaki

    2016-12-29

    A complex-valued Hopfield neural network (CHNN) is a model of a Hopfield neural network using multistate neurons. The stability conditions of CHNNs have been widely studied. A CHNN with a synchronous mode will converge to a fixed point or a cycle of length 2. A rotor Hopfield neural network (RHNN) is also a model of a multistate Hopfield neural network. RHNNs have much higher storage capacity and noise tolerance than CHNNs. We extend the theories regarding the stability of CHNNs to RHNNs. In addition, we investigate the stability of RHNNs with the projection rule. Although a CHNN with projection rule can be trapped at a cycle, an RHNN with projection rule converges to a fixed point. This is one of the great advantages of RHNNs.

  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. PMID:28289373

  14. EEG PHASE RESET OF THE DEFAULT MODE NETWORK

    OpenAIRE

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

    2014-01-01

    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 c...

  15. APPROXIMATION MULTIDIMENSION FUCTION WITH FUNCTIONAL NETWORK

    Institute of Scientific and Technical Information of China (English)

    Li Weibin; Liu Fang; Jiao Licheng; Zhang Shuling; Li Zongling

    2006-01-01

    The functional network was introduced by E.Catillo, which extended the neural network. Not only can it solve the problems solved, but also it can formulate the ones that cannot be solved by traditional network.This paper applies functional network to approximate the multidimension function under the ridgelet theory.The method performs more stable and faster than the traditional neural network. The numerical examples demonstrate the performance.

  16. Multisubject independent component analysis of fMRI: a decade of intrinsic networks, default mode, and neurodiagnostic discovery.

    Science.gov (United States)

    Calhoun, Vince D; Adalı, Tülay

    2012-01-01

    Since the discovery of functional connectivity in fMRI data (i.e., temporal correlations between spatially distinct regions of the brain) there has been a considerable amount of work in this field. One important focus has been on the analysis of brain connectivity using the concept of networks instead of regions. Approximately ten years ago, two important research areas grew out of this concept. First, a network proposed to be "a default mode of brain function" since dubbed the default mode network was proposed by Raichle. Secondly, multisubject or group independent component analysis (ICA) provided a data-driven approach to study properties of brain networks, including the default mode network. In this paper, we provide a focused review of how ICA has contributed to the study of intrinsic networks. We discuss some methodological considerations for group ICA and highlight multiple analytic approaches for studying brain networks. We also show examples of some of the differences observed in the default mode and resting networks in the diseased brain. In summary, we are in exciting times and still just beginning to reap the benefits of the richness of functional brain networks as well as available analytic approaches.

  17. Resting-state brain organization revealed by functional covariance networks.

    Directory of Open Access Journals (Sweden)

    Zhiqiang Zhang

    Full Text Available BACKGROUND: Brain network studies using techniques of intrinsic connectivity network based on fMRI time series (TS-ICN and structural covariance network (SCN have mapped out functional and structural organization of human brain at respective time scales. However, there lacks a meso-time-scale network to bridge the ICN and SCN and get insights of brain functional organization. METHODOLOGY AND PRINCIPAL FINDINGS: We proposed a functional covariance network (FCN method by measuring the covariance of amplitude of low-frequency fluctuations (ALFF in BOLD signals across subjects, and compared the patterns of ALFF-FCNs with the TS-ICNs and SCNs by mapping the brain networks of default network, task-positive network and sensory networks. We demonstrated large overlap among FCNs, ICNs and SCNs and modular nature in FCNs and ICNs by using conjunctional analysis. Most interestingly, FCN analysis showed a network dichotomy consisting of anti-correlated high-level cognitive system and low-level perceptive system, which is a novel finding different from the ICN dichotomy consisting of the default-mode network and the task-positive network. CONCLUSION: The current study proposed an ALFF-FCN approach to measure the interregional correlation of brain activity responding to short periods of state, and revealed novel organization patterns of resting-state brain activity from an intermediate time scale.

  18. Sandia`s network for supercomputing `95: Validating the progress of Asynchronous Transfer Mode (ATM) switching

    Energy Technology Data Exchange (ETDEWEB)

    Pratt, T.J.; Vahle, O.; Gossage, S.A.

    1996-04-01

    The Advanced Networking Integration Department at Sandia National Laboratories has used the annual Supercomputing conference sponsored by the IEEE and ACM for the past three years as a forum to demonstrate and focus communication and networking developments. For Supercomputing `95, Sandia elected: to demonstrate the functionality and capability of an AT&T Globeview 20Gbps Asynchronous Transfer Mode (ATM) switch, which represents the core of Sandia`s corporate network, to build and utilize a three node 622 megabit per second Paragon network, and to extend the DOD`s ACTS ATM Internet from Sandia, New Mexico to the conference`s show floor in San Diego, California, for video demonstrations. This paper documents those accomplishments, discusses the details of their implementation, and describes how these demonstrations supports Sandia`s overall strategies in ATM networking.

  19. The radio luminosity function and redshift evolution of radio-mode and quasar-mode AGN

    Science.gov (United States)

    Pracy, Mike

    2016-08-01

    The properties of the AGN population indicate that there are two fundamentally different accretion modes operating. In the quasar-mode, material is accreted onto the supermassive black hole via a small, thin, optically luminous accretion disc. Accretion in this mode is recognisable by emission lines in the optical spectrum. However, there is a population of AGN observable only by their radio emission and without optical emission lines. These radio-mode AGN are likely powered by radiatively inefficient accretion from a hot gas halo. I will describe the cosmic evolution of these two populations via radio luminosity functions. The radio luminosity functions are constructed from a new survey of over 4000 radio galaxies out to z=1, all with confirmed redshifts and their accretion mode classified from their optical spectra. This is 20 times larger than the only other survey used to make such a measurement. The radio-mode AGN population displays no statistically significant evolution in space density out to redshift z=1. In contrast the quasar mode AGN exhibits rapid evolution in space density, increasing by a factor of 8 over the same redshift range. The characteristic break in the radio luminosity function occurs at a significantly higher power for the quasar-mode AGN in comparison to the radio-mode AGN and we demonstrate this is consistent with the two populations representing fundamentally different accretion modes. The radio luminosity function is used to estimate the total amount of mechanical energy available for radio mode feedback as a function of redshift, and is found to be in good agreement with cosmological models and previous measurements. Again, by separating by accretion mode, the previously estimated increase in available mechanical energy per unit volume out to z=1 (approximately a factor of 2) can be attributed to the rapid evolution of the quasar-mode AGN, while for the classical radio-mode AGN the total mechanical energy output remains roughly

  20. Temporal stability of network centrality in control and default mode networks: Specific associations with externalizing psychopathology in children and adolescents.

    Science.gov (United States)

    Sato, João Ricardo; Biazoli, Claudinei Eduardo; Salum, Giovanni Abrahão; Gadelha, Ary; Crossley, Nicolas; Satterthwaite, Theodore D; Vieira, Gilson; Zugman, André; Picon, Felipe Almeida; Pan, Pedro Mario; Hoexter, Marcelo Queiroz; Anés, Mauricio; Moura, Luciana Monteiro; Del'aquilla, Marco Antonio Gomes; Amaro, Edson; McGuire, Philip; Lacerda, Acioly L T; Rohde, Luis Augusto; Miguel, Euripedes Constantino; Jackowski, Andrea Parolin; Bressan, Rodrigo Affonseca

    2015-12-01

    Abnormal connectivity patterns have frequently been reported as involved in pathological mental states. However, most studies focus on "static," stationary patterns of connectivity, which may miss crucial biological information. Recent methodological advances have allowed the investigation of dynamic functional connectivity patterns that describe non-stationary properties of brain networks. Here, we introduce a novel graphical measure of dynamic connectivity, called time-varying eigenvector centrality (tv-EVC). In a sample 655 children and adolescents (7-15 years old) from the Brazilian "High Risk Cohort Study for Psychiatric Disorders" who were imaged using resting-state fMRI, we used this measure to investigate age effects in the temporal in control and default-mode networks (CN/DMN). Using support vector regression, we propose a network maturation index based on the temporal stability of tv-EVC. Moreover, we investigated whether the network maturation is associated with the overall presence of behavioral and emotional problems with the Child Behavior Checklist. As hypothesized, we found that the tv-EVC at each node of CN/DMN become more stable with increasing age (P < 0.001 for all nodes). In addition, the maturity index for this particular network is indeed associated with general psychopathology in children assessed by the total score of Child Behavior Checklist (P = 0.027). Moreover, immaturity of the network was mainly correlated with externalizing behavior dimensions. Taken together, these results suggest that changes in functional network dynamics during neurodevelopment may provide unique insights regarding pathophysiology.

  1. Synchronization of different chaotic systems via active radial basis functions sliding mode controller

    Institute of Scientific and Technical Information of China (English)

    Guo Hui-Jun; Yin You-Wei; Wang Hua-Min

    2008-01-01

    This paper presents a new method to synchronize different chaotic systems with disturbances via an active radial basis function (RBF) sliding controller.This method incorporates the advantages of active control,neural network and sliding mode control.The main part of the controller is given based on the output of the RBF neural networks and the weights of these single layer networks are tuned on-line based on the sliding mode reaching law.Only several radial basis functions are required for this controller which takes the sliding mode variable as the only input.The proposed controller can make the synchronization error converge to zero quickly and can overcome external disturbances.Analysis of the stability for the controller is carried out based on the Lyapunov stability theorem.Finally,five examples are given to illustrate the robustness and effectiveness of the proposed synchronization control strategy.

  2. Fast revelation of the motif mode for a yeast protein interaction network through intelligent agent-based distributed computing.

    Science.gov (United States)

    Lee, Wei-Po; Tzou, Wen-Shyong

    2010-09-01

    In the yeast protein-protein interaction network, motif mode, a collection of motifs of special combinations of protein nodes annotated by the molecular function terms of the Gene Ontology, has revealed differences in the conservation constraints within the same topology. In this study, by employing an intelligent agent-based distributed computing method, we are able to discover motif modes in a fast and adaptive manner. Moreover, by focusing on the highly evolutionarily conserved motif modes belonging to the same biological function, we find a large downshift in the distance between nodes belonging to the same motif mode compared with the whole, suggesting that nodes with the same motif mode tend to congregate in a network. Several motif modes with a high conservation of the motif constituents were revealed, but from a new perspective, including that with a three-node motif mode engaged in the protein fate and that with three four-node motif modes involved in the genome maintenance, cellular organization, and transcription. The network motif modes discovered from this method can be linked to the wealth of biological data which require further elucidation with regard to biological functions.

  3. A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice

    NARCIS (Netherlands)

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

    2013-01-01

    We propose a new stochastic actor-oriented model for the co-evolution of two-mode and one-mode networks. The model posits that activities of a set of actors, represented in the two-mode network, co-evolve with exchanges and interactions between the actors, as represented in the one-mode network. The

  4. Generalized multiscale radial basis function networks.

    Science.gov (United States)

    Billings, Stephen A; Wei, Hua-Liang; Balikhin, Michael A

    2007-12-01

    A novel modelling framework is proposed for constructing parsimonious and flexible multiscale radial basis function networks (RBF). Unlike a conventional standard single scale RBF network, where all the basis functions have a common kernel width, the new network structure adopts multiscale Gaussian functions as the bases, where each selected centre has multiple kernel widths, to provide more flexible representations with better generalization properties for general nonlinear dynamical systems. As a direct extension of the traditional single scale Gaussian networks, the new multiscale network is easy to implement and is quick to learn using standard learning algorithms. A k-means clustering algorithm and an improved orthogonal least squares (OLS) algorithm are used to determine the unknown parameters in the network model including the centres and widths of the basis functions, and the weights between the basis functions. It is demonstrated that the new network can lead to a parsimonious model with much better generalization property compared with the traditional single width RBF networks.

  5. Aberrant intra-salience network dynamic functional connectivity impairs large-scale network interactions in schizophrenia.

    Science.gov (United States)

    Wang, Xiangpeng; Zhang, Wenwen; Sun, Yujing; Hu, Min; Chen, Antao

    2016-12-01

    Aberrant functional interactions between several large-scale networks, especially the central executive network (CEN), the default mode network (DMN) and the salience network (SN), have been postulated as core pathophysiologic features of schizophrenia; however, the attributing factors of which remain unclear. The study employed resting-state fMRI with 77 participants (42 patients and 35 controls). We performed dynamic functional connectivity (DFC) and functional connectivity (FC) analyses to explore the connectivity patterns of these networks. Furthermore, we performed a structural equation model (SEM) analysis to explore the possible role of the SN in modulating network interactions. The results were as follows: (1) The inter-network connectivity showed decreased connectivity strength and increased time-varying instability in schizophrenia; (2) The SN manifested schizophrenic intra-network dysfunctions in both the FC and DFC patterns; (3) The connectivity properties of the SN were effective in discriminating controls from patients; (4) In patients, the dynamic intra-SN connectivity negatively predicted the inter-network FC, and this effect was mediated by intra-SN connectivity strength. These findings suggest that schizophrenia show systematic deficits in temporal stability of large-scale network connectivity. Furthermore, aberrant network interactions in schizophrenia could be attributed to instable intra-SN connectivity and the dysfunction of the SN may be an intrinsic biomarker of the disease. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. 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.

  7. Scale-Free Brain Functional Networks

    Science.gov (United States)

    Eguíluz, Victor M.; Chialvo, Dante R.; Cecchi, Guillermo A.; Baliki, Marwan; Apkarian, A. Vania

    2005-01-01

    Functional magnetic resonance imaging is used to extract functional networks connecting correlated human brain sites. Analysis of the resulting networks in different tasks shows that (a)the distribution of functional connections, and the probability of finding a link versus distance are both scale-free, (b)the characteristic path length is small and comparable with those of equivalent random networks, and (c)the clustering coefficient is orders of magnitude larger than those of equivalent random networks. All these properties, typical of scale-free small-world networks, reflect important functional information about brain states.

  8. Computational network design from functional specifications

    KAUST Repository

    Peng, Chi Han

    2016-07-11

    Connectivity and layout of underlying networks largely determine agent behavior and usage in many environments. For example, transportation networks determine the flow of traffic in a neighborhood, whereas building floorplans determine the flow of people in a workspace. Designing such networks from scratch is challenging as even local network changes can have large global effects. We investigate how to computationally create networks starting from only high-level functional specifications. Such specifications can be in the form of network density, travel time versus network length, traffic type, destination location, etc. We propose an integer programming-based approach that guarantees that the resultant networks are valid by fulfilling all the specified hard constraints and that they score favorably in terms of the objective function. We evaluate our algorithm in two different design settings, street layout and floorplans to demonstrate that diverse networks can emerge purely from high-level functional specifications.

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

    Science.gov (United States)

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

    2016-11-01

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

  10. The salience network is responsible for switching between the default mode network and the central executive network: replication from DCM.

    Science.gov (United States)

    Goulden, Nia; Khusnulina, Aygul; Davis, Nicholas J; Bracewell, Robert M; Bokde, Arun L; McNulty, Jonathan P; Mullins, Paul G

    2014-10-01

    With the advent of new analysis methods in neuroimaging that involve independent component analysis (ICA) and dynamic causal modelling (DCM), investigations have focused on measuring both the activity and connectivity of specific brain networks. In this study we combined DCM with spatial ICA to investigate network switching in the brain. Using time courses determined by ICA in our dynamic causal models, we focused on the dynamics of switching between the default mode network (DMN), the network which is active when the brain is not engaging in a specific task, and the central executive network (CEN), which is active when the brain is engaging in a task requiring attention. Previous work using Granger causality methods has shown that regions of the brain which respond to the degree of subjective salience of a stimulus, the salience network, are responsible for switching between the DMN and the CEN (Sridharan et al., 2008). In this work we apply DCM to ICA time courses representing these networks in resting state data. In order to test the repeatability of our work we applied this to two independent datasets. This work confirms that the salience network drives the switching between default mode and central executive networks and that our novel technique is repeatable.

  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. Network Physiology reveals relations between network topology and physiological function

    CERN Document Server

    Bashan, Amir; Kantelhardt, Jan W; Havlin, Shlomo; Ivanov, Plamen Ch; 10.1038/ncomms1705

    2012-01-01

    The human organism is an integrated network where complex physiologic systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown of the entire network. Identifying and quantifying dynamical networks of diverse systems with different types of interactions is a challenge. Here, we develop a framework to probe interactions among diverse systems, and we identify a physiologic network. We find that each physiologic state is characterized by a specific network structure, demonstrating a robust interplay between network topology and function. Across physiologic states the network undergoes topological transitions associated with fast reorganization of physiologic interactions on time scales of a few minutes, indicating high network flexibility in response to perturbations. The proposed system-wide integrative approach may facilitate the development of a new field, Network Physiology.

  13. A radial basis function sliding mode controller for chaotic Lorenz system

    Energy Technology Data Exchange (ETDEWEB)

    Guo Huijun [School of Electrical Engineering, Xi' an Jiaotong University, Xi' an 710049 (China)]. E-mail: realghj@yahoo.com.cn; Lin Suifang [Department of Automation, Xi' an University of Technology, Xi' an 710048 (China); Liu Junhua [School of Electrical Engineering, Xi' an Jiaotong University, Xi' an 710049 (China)

    2006-03-06

    This Letter presents a novel method to controlling Lorenz chaos via an adaptive radial basis function sliding mode controller. The proposed scheme combines the advantages of the adaptive control, neural network and sliding mode control strategies without precise system model information. It has on-line learning ability to deal with the parametric uncertainty and disturbance by adjusting the control parameters. A sliding mode controller is designed via the Lyapunov stability theory in order to guarantee the high quality of the controlled system. The simulation results show that this method is feasible and effective for chaos control, and the robustness to parametric changes and extern disturbance is provided.

  14. Functional brain network efficiency predicts intelligence.

    Science.gov (United States)

    Langer, Nicolas; Pedroni, Andreas; Gianotti, Lorena R R; Hänggi, Jürgen; Knoch, Daria; Jäncke, Lutz

    2012-06-01

    The neuronal causes of individual differences in mental abilities such as intelligence are complex and profoundly important. Understanding these abilities has the potential to facilitate their enhancement. The purpose of this study was to identify the functional brain network characteristics and their relation to psychometric intelligence. In particular, we examined whether the functional network exhibits efficient small-world network attributes (high clustering and short path length) and whether these small-world network parameters are associated with intellectual performance. High-density resting state electroencephalography (EEG) was recorded in 74 healthy subjects to analyze graph-theoretical functional network characteristics at an intracortical level. Ravens advanced progressive matrices were used to assess intelligence. We found that the clustering coefficient and path length of the functional network are strongly related to intelligence. Thus, the more intelligent the subjects are the more the functional brain network resembles a small-world network. We further identified the parietal cortex as a main hub of this resting state network as indicated by increased degree centrality that is associated with higher intelligence. Taken together, this is the first study that substantiates the neural efficiency hypothesis as well as the Parieto-Frontal Integration Theory (P-FIT) of intelligence in the context of functional brain network characteristics. These theories are currently the most established intelligence theories in neuroscience. Our findings revealed robust evidence of an efficiently organized resting state functional brain network for highly productive cognitions.

  15. Transition modes in Ising networks: an approximate theory for macromolecular recognition.

    Science.gov (United States)

    Keating, S; Di Cera, E

    1993-07-01

    For a statistical lattice, or Ising network, composed of N identical units existing in two possible states, 0 and 1, and interacting according to a given geometry, a set of values can be found for the mean free energy of the 0-->1 transition of a single unit. Each value defines a transition mode in an ensemble of nu N = 3N - 2N possible values and reflects the role played by intermediate states in shaping the energetics of the system as a whole. The distribution of transition modes has a number of intriguing properties. Some of them apply quite generally to any Ising network, regardless of its dimension, while others are specific for each interaction geometry and dimensional embedding and bear on fundamental aspects of analytical number theory. The landscape of transition modes encapsulates all of the important thermodynamic properties of the network. The free energy terms defining the partition function of the system can be derived from the modes by simple transformations. Classical mean-field expressions can be obtained from consideration of the properties of transition modes in a rather straightforward way. The results obtained in the analysis of the transition mode distributions have been used to develop an approximate treatment of the problem of macromolecular recognition. This phenomenon is modeled as a cooperative process that involves a number of recognition subsites across an interface generated by the binding of two macromolecular components. The distribution of allowed binding free energies for the system is shown to be a superposition of Gaussian terms with mean and variance determined a priori by the theory. Application to the analysis of the biologically interaction of thrombin with hirudin has provided some useful information on basic aspects of the interaction, such as the number of recognition subsites involved and the energy balance for binding and cooperative coupling among them. Our results agree quite well with information derived independently

  16. Mapping distributed brain function and networks with diffuse optical tomography

    Science.gov (United States)

    Eggebrecht, Adam T.; Ferradal, Silvina L.; Robichaux-Viehoever, Amy; Hassanpour, Mahlega S.; Dehghani, Hamid; Snyder, Abraham Z.; Hershey, Tamara; Culver, Joseph P.

    2014-06-01

    Mapping of human brain function has revolutionized systems neuroscience. However, traditional functional neuroimaging by positron emission tomography or functional magnetic resonance imaging cannot be used when applications require portability, or are contraindicated because of ionizing radiation (positron emission tomography) or implanted metal (functional magnetic resonance imaging). Optical neuroimaging offers a non-invasive alternative that is radiation free and compatible with implanted metal and electronic devices (for example, pacemakers). However, optical imaging technology has heretofore lacked the combination of spatial resolution and wide field of view sufficient to map distributed brain functions. Here, we present a high-density diffuse optical tomography imaging array that can map higher-order, distributed brain function. The system was tested by imaging four hierarchical language tasks and multiple resting-state networks including the dorsal attention and default mode networks. Finally, we imaged brain function in patients with Parkinson's disease and implanted deep brain stimulators that preclude functional magnetic resonance imaging.

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

    Science.gov (United States)

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

    2016-05-01

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

  18. Security technologies and protocols for Asynchronous Transfer Mode networks

    Energy Technology Data Exchange (ETDEWEB)

    Tarman, T.D.

    1996-06-01

    Asynchronous Transfer Mode (ATM) is a new data communications technology that promises to integrate voice, video, and data traffic into a common network infrastructure. In order to fully utilize ATM`s ability to transfer real-time data at high rates, applications will start to access the ATM layer directly. As a result of this trend, security mechanisms at the ATM layer will be required. A number of research programs are currently in progress which seek to better understand the unique issues associated with ATM security. This paper describes some of these issues, and the approaches taken by various organizations in the design of ATM layer security mechanisms. Efforts within the ATM Forum to address the user communities need for ATM security are also described.

  19. Low-mode averaging for baryon correlation functions

    CERN Document Server

    Giusti, Leonardo; Giusti, Leonardo; Necco, Silvia

    2005-01-01

    The low-mode averaging technique is a powerful tool for reducing large fluctuations in correlation functions due to low-mode eigenvalues of the Dirac operator. In this work we propose a generalization to baryons and test our method on two-point correlation functions of left-handed nucleons, computed with quenched Neuberger fermions on a lattice with extension L=1.5 fm. We show that the statistical fluctuations can be reduced and the baryon signal significantly improved.

  20. Nested Canalizing Functions and Their Networks

    CERN Document Server

    Kadelka, Claus; Adeyeye, John O; Laubenbacher, Reinhard

    2014-01-01

    The concept of a nested canalizing Boolean function has been studied over the last decade in the context of understanding the regulatory logic of molecular interaction networks, such as gene regulatory networks. Such networks are predominantly governed by nested canalizing functions. Derrida values are frequently used to analyze the robustness of a Boolean network to perturbations. This paper introduces closed formulas for the calculation of Derrida values of networks governed by Boolean nested canalizing functions, which previously required extensive simulations. Recently, the concept of nested canalizing functions has been generalized to include multistate functions, and a recursive formula has been derived for their number, as a function of the number of variables. This paper contains a detailed analysis of the class of nested canalizing functions over an arbitrary finite field. In addition, the concept of nested canalization is further generalized and closed formulas for the number of such generalized fun...

  1. Structure and function in flow networks

    CERN Document Server

    Rubido, Nicolás; Baptista, Murilo S

    2013-01-01

    This Letter presents a unified approach for the fundamental relationship between structure and function in flow networks by solving analytically the voltages in a resistor network, transforming the network structure to an effective all-to-all topology, and then measuring the resultant flows. Moreover, it defines a way to study the structural resilience of the graph and to detect possible communities.

  2. Understanding biological functions through molecular networks

    Institute of Scientific and Technical Information of China (English)

    Jing-Dong Jackie Han

    2008-01-01

    The completion of genome sequences and subsequent high-throughput mapping of molecular networks have allowed us to study biology from the network perspective. Experimental, statistical and mathematical modeling approaches have been employed to study the structure, function and dynamics of molecular networks, and begin to reveal important links of various network properties to the functions of the biological systems. In agreement with these functional links, evolutionary selection of a network is apparently based on the function, rather than directly on the structure of the network. Dynamic modularity is one of the prominent features of molecular networks. Taking advantage of such a feature may simplify network-based biological studies through construction of process-specific modular networks and provide functional and mechanistic insights linking genotypic variations to complex traits or diseases, which is likely to be a key approach in the next wave of understanding complex human diseases. With the development of ready-to-use network analysis and modeling tools the networks approaches will be infused into everyday biological research in the near future.

  3. ROBUST SLIDING MODE DECENTRALIZED CONTROL FOR A CLASS OF NONLINEAR INTERCONNECTED LARGE-SCALE SYSTEM WITH NEURAL NETWORKS

    Institute of Scientific and Technical Information of China (English)

    CHENMou; JIANGChang-sheng; CHENWen-hua

    2004-01-01

    A new decentralized robust control method is discussed for a class of nonlinear interconnected largescale system with unknown bounded disturbance and unknown nonlinear function term. A decentralized control law is proposed which combines the approximation method of neural network with sliding mode control. The decentralized controller consists of an equivalent controller and an adaptive sliding mode controller. The sliding mode controller is a robust controller used to reduce the track error of the control system. The neural networks are used to approximate the unknown nonlinear functions, meanwhile the approximation errors of the neural networks are applied to the weight value updated law to improve performance of the system. Finally, an example demonstrates the availability of the decentralized control method.

  4. Disconnection between the default mode network and medial temporal lobes in post-traumatic amnesia.

    Science.gov (United States)

    De Simoni, Sara; Grover, Patrick J; Jenkins, Peter O; Honeyfield, Lesley; Quest, Rebecca A; Ross, Ewan; Scott, Gregory; Wilson, Mark H; Majewska, Paulina; Waldman, Adam D; Patel, Maneesh C; Sharp, David J

    2016-12-01

    SEE BIGLER DOI101093/AWW277 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Post-traumatic amnesia is very common immediately after traumatic brain injury. It is characterized by a confused, agitated state and a pronounced inability to encode new memories and sustain attention. Clinically, post-traumatic amnesia is an important predictor of functional outcome. However, despite its prevalence and functional importance, the pathophysiology of post-traumatic amnesia is not understood. Memory processing relies on limbic structures such as the hippocampus, parahippocampus and parts of the cingulate cortex. These structures are connected within an intrinsic connectivity network, the default mode network. Interactions within the default mode network can be assessed using resting state functional magnetic resonance imaging, which can be acquired in confused patients unable to perform tasks in the scanner. Here we used this approach to test the hypothesis that the mnemonic symptoms of post-traumatic amnesia are caused by functional disconnection within the default mode network. We assessed whether the hippocampus and parahippocampus showed evidence of transient disconnection from cortical brain regions involved in memory processing. Nineteen patients with traumatic brain injury were classified into post-traumatic amnesia and traumatic brain injury control groups, based on their performance on a paired associates learning task. Cognitive function was also assessed with a detailed neuropsychological test battery. Functional interactions between brain regions were investigated using resting-state functional magnetic resonance imaging. Together with impairments in associative memory, patients in post-traumatic amnesia demonstrated impairments in information processing speed and spatial working memory. Patients in post-traumatic amnesia showed abnormal functional connectivity between the parahippocampal gyrus and posterior cingulate cortex. The strength of this functional

  5. Default Mode and Executive Networks Areas: Association with the Serial Order in Divergent Thinking

    National Research Council Canada - National Science Library

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

    2016-01-01

    .... Previous studies on creativity found an association between creativity and the brain regions in the prefrontal cortex, the anterior cingulate cortex, the default mode network and the executive network...

  6. 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.

  7. 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.

  8. Customised Mode Profiles Using Functional Materials

    CERN Document Server

    Gratus, Jonathan; Letizia, Rosa; Boyd, Taylor

    2016-01-01

    We show how to control the field profile on a sub-wavelength scale using a customised permittivity variation in a functional medium, thus avoiding the need to e.g. synthesize the shape from its Fourier harmonics. For applications such as beam dynamics, requiring field profile shaping in free space, we show that it is possible to achieve this despite using a slot in the medium.

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

    Science.gov (United States)

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

    2011-01-01

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

  10. Framework for Ethernet Network Functionality Testing

    Directory of Open Access Journals (Sweden)

    Mirza Aamir Mehmood

    2011-11-01

    Full Text Available Computer networks and telecommunication systems use a wide range of applications. Therefore, the power and complexity of computer networks are increasing every day which enhances the possibilities of the end user, but also makes harder the work of those who have to design, maintain and make a network efficient, optimized and secure. Ethernet functionality testing as a generic term used for checking connectivity, throughput and capability to transfer packets over the network. Especially in the packet-switch environment, Ethernet testing has become an essential part for deploying a reliable network. A platform and vendor independent framework is required to verify and test the functionality of the Ethernet network and to verify the functionality and performance of the TCP/IP stack. NetBurst is developed for Ethernet functionality testing

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

    Science.gov (United States)

    Huang, Daizheng; Wu, Zhihui

    2017-01-01

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

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

    Science.gov (United States)

    Huang, Daizheng; Wu, Zhihui

    2017-01-01

    Accurately predicting the trend of outpatient visits by mathematical modeling can help policy makers manage hospitals effectively, reasonably organize schedules for human resources and finances, and appropriately distribute hospital material resources. In this study, a hybrid method based on empirical mode decomposition and back-propagation artificial neural networks optimized by particle swarm optimization is developed to forecast outpatient visits on the basis of monthly numbers. The data outpatient visits are retrieved from January 2005 to December 2013 and first obtained as the original time series. Second, the original time series is decomposed into a finite and often small number of intrinsic mode functions by the empirical mode decomposition technique. Third, a three-layer back-propagation artificial neural network is constructed to forecast each intrinsic mode functions. To improve network performance and avoid falling into a local minimum, particle swarm optimization is employed to optimize the weights and thresholds of back-propagation artificial neural networks. Finally, the superposition of forecasting results of the intrinsic mode functions is regarded as the ultimate forecasting value. Simulation indicates that the proposed method attains a better performance index than the other four methods. PMID:28222194

  13. RBF networks with mixed radial basis functions

    NARCIS (Netherlands)

    Ciftcioglu, O.; Sariyildiz, I.S.

    2000-01-01

    After the introduction to neural network technology as multivariable function approximation, radial basis function (RBF) networks have been studied in many different aspects in recent years. From the theoretical viewpoint, approximation and uniqueness of the interpolation is studied and it has been

  14. Network architecture functional description and design

    Energy Technology Data Exchange (ETDEWEB)

    Stans, L.; Bencoe, M.; Brown, D.; Kelly, S.; Pierson, L.; Schaldach, C.

    1989-05-25

    This report provides a top level functional description and design for the development and implementation of the central network to support the next generation of SNL, Albuquerque supercomputer in a UNIX{reg sign} environment. It describes the network functions and provides an architecture and topology.

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

    Energy Technology Data Exchange (ETDEWEB)

    Zhao Xiaohu [Imaging Department of Tong Ji Hospital of Tong Ji University, Shanghai 200065 (China) and Bio-X lab, Department of Physics, Zhe Jiang University, Hangzhou 310027 (China)], E-mail: xhzhao999@263.net; Wang Peijun [Imaging Department of Tong Ji Hospital of Tong Ji University, Shanghai 200065 (China)], E-mail: tongjipjwang@vip.sina.com; Li Chunbo [Department of Psychiatry, Tong Ji Hospital of Tong Ji University, Shanghai 200065 (China)], E-mail: licb@mail.tongji.edu.cn; Hu Zhenghui [Department of Electrical and Engineering, Hong Kong University of Science and Technology, Hong Kong (China)], E-mail: eezhhu@ust.hk; Xi Qian [Imaging Department of Tong Ji Hospital of Tong Ji University, Shanghai 200065 (China)], E-mail: 96125007@sina.com.cn; Wu Wenyuan [Department of Psychiatry, Tong Ji Hospital of Tong Ji University, Shanghai 200065 (China)], E-mail: wuwy@mail.tongji.edu.cn; Tang Xiaowei [Bio-X lab, Department of Physics, Zhe Jiang University, Hangzhou 310027 (China)], E-mail: tangxw@zju.edu.cn

    2007-09-15

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

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

    Directory of Open Access Journals (Sweden)

    Yan eTao

    2015-11-01

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

  18. Hierarchical modularity in human brain functional networks

    CERN Document Server

    Meunier, D; Fornito, A; Ersche, K D; Bullmore, E T; 10.3389/neuro.11.037.2009

    2010-01-01

    The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at ...

  19. A Bayesian network model for predicting aquatic toxicity mode ...

    Science.gov (United States)

    The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity but MoA classification in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity mode of action using a recently published dataset containing over one thousand chemicals with MoA assignments for aquatic animal toxicity. Two dimensional theoretical chemical descriptors were generated for each chemical using the Toxicity Estimation Software Tool. The model was developed through augmented Markov blanket discovery from the data set with the MoA broad classifications as a target node. From cross validation, the overall precision for the model was 80.2% with a R2 of 0.959. The best precision was for the AChEI MoA (93.5%) where 257 chemicals out of 275 were correctly classified. Model precision was poorest for the reactivity MoA (48.5%) where 48 out of 99 reactive chemicals were correctly classified. Narcosis represented the largest class within the MoA dataset and had a precision and reliability of 80.0%, reflecting the global precision across all of the MoAs. False negatives for narcosis most often fell into electron transport inhibition, neurotoxicity or reactivity MoAs. False negatives for all other MoAs were most often narcosis. A probabilistic sensitivity analysis was undertaken for each MoA to examine the sensitivity to individual and multiple descriptor findings. The results show that the Markov blanket of a structurally

  20. Optical diagnosis of cervical cancer by intrinsic mode functions

    Science.gov (United States)

    Mukhopadhyay, Sabyasachi; Pratiher, Sawon; Pratiher, Souvik; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

    2017-03-01

    In this paper, we make use of the empirical mode decomposition (EMD) to discriminate the cervical cancer tissues from normal ones based on elastic scattering spectroscopy. The phase space has been reconstructed through decomposing the optical signal into a finite set of bandlimited signals known as intrinsic mode functions (IMFs). It has been shown that the area measure of the analytic IMFs provides a good discrimination performance. Simulation results validate the efficacy of the IMFs followed by SVM based classification.

  1. Multiprotocol label-switching network functional description

    Science.gov (United States)

    Owens, Kenneth R.; Kroculick, Joseph

    1999-11-01

    This paper integrates a functional transport and control layer network architecture for MPLS emphasizing Traffic Engineering concepts such as the specification and provisioning of end-to-end QoS service layer agreements. MPLS transport networks are provisioned considering administrator-defined policies on bandwidth allocation, security, and accounting techniques. The MPLS architecture consists of the transport and control layer networks. The transport layer network is concerned with configuration, packet forwarding, signaling, adaptation to higher layers, and support of higher layers. The control layer network is concerned with policy configuration, management, distribution, definitions, schemas, elements, settings, and enforcement.

  2. Mode and delay-dependent adaptive exponential synchronization in pth moment for stochastic delayed neural networks with Markovian switching.

    Science.gov (United States)

    Zhou, Wuneng; Tong, Dongbing; Gao, Yan; Ji, Chuan; Su, Hongye

    2012-04-01

    In this brief, the analysis problem of the mode and delay-dependent adaptive exponential synchronization in th moment is considered for stochastic delayed neural networks with Markovian switching. By utilizing a new nonnegative function and the -matrix approach, several sufficient conditions to ensure the mode and delay-dependent adaptive exponential synchronization in th moment for stochastic delayed neural networks are derived. Via the adaptive feedback control techniques, some suitable parameters update laws are found. To illustrate the effectiveness of the -matrix-based synchronization conditions derived in this brief, a numerical example is provided finally.

  3. Persistent Operational Synchrony within Brain Default-Mode Network and Self-Processing Operations in Healthy Subjects

    Science.gov (United States)

    Fingelkurts, Andrew A.; Fingelkurts, Alexander A.

    2011-01-01

    Based on the theoretical analysis of self-consciousness concepts, we hypothesized that the spatio-temporal pattern of functional connectivity within the default-mode network (DMN) should persist unchanged across a variety of different cognitive tasks or acts, thus being task-unrelated. This supposition is in contrast with current understanding…

  4. Simple models of human brain functional networks.

    Science.gov (United States)

    Vértes, Petra E; Alexander-Bloch, Aaron F; Gogtay, Nitin; Giedd, Jay N; Rapoport, Judith L; Bullmore, Edward T

    2012-04-10

    Human brain functional networks are embedded in anatomical space and have topological properties--small-worldness, modularity, fat-tailed degree distributions--that are comparable to many other complex networks. Although a sophisticated set of measures is available to describe the topology of brain networks, the selection pressures that drive their formation remain largely unknown. Here we consider generative models for the probability of a functional connection (an edge) between two cortical regions (nodes) separated by some Euclidean distance in anatomical space. In particular, we propose a model in which the embedded topology of brain networks emerges from two competing factors: a distance penalty based on the cost of maintaining long-range connections; and a topological term that favors links between regions sharing similar input. We show that, together, these two biologically plausible factors are sufficient to capture an impressive range of topological properties of functional brain networks. Model parameters estimated in one set of functional MRI (fMRI) data on normal volunteers provided a good fit to networks estimated in a second independent sample of fMRI data. Furthermore, slightly detuned model parameters also generated a reasonable simulation of the abnormal properties of brain functional networks in people with schizophrenia. We therefore anticipate that many aspects of brain network organization, in health and disease, may be parsimoniously explained by an economical clustering rule for the probability of functional connectivity between different brain areas.

  5. Network Assemblies in the Functional Brain

    Science.gov (United States)

    Sepulcre, Jorge; Sabuncu, Mert R.; Johnson, Keith A.

    2012-01-01

    Purpose of review This review focuses on recent advances in functional connectivity MRI and renewed interest in knowing the large-scale functional network assemblies in the brain. We also consider some methodological aspects of graph theoretical analysis. Recent findings Network science applied to neuroscience is quickly growing in recent years. The characterization of the functional connectomes in normal and pathological brain conditions is now a priority for researchers in the neuropsychiatric field and current findings have provided new insights regarding the pivotal role of network epicenters and specific configurations of the functional networks in the brain. Summary Functional connectivity and its analytical tools are providing organization of the functional brain that will be key for the understanding of pathologies in neurology. PMID:22766721

  6. Hybrid neural network fraction integral terminal sliding mode control of an Inchworm robot manipulator

    Science.gov (United States)

    Rahmani, Mehran; Ghanbari, Ahmad; Ettefagh, Mir Mohammad

    2016-12-01

    This paper proposes a control scheme based on the fraction integral terminal sliding mode control and adaptive neural network. It deals with the system model uncertainties and the disturbances to improve the control performance of the Inchworm robot manipulator. A fraction integral terminal sliding mode control applies to the Inchworm robot manipulator to obtain the initial stability. Also, an adaptive neural network is designed to approximate the system uncertainties and unknown disturbances to reduce chattering phenomena. The weight matrix of the proposed adaptive neural network can be updated online, according to the current state error information. The stability of the proposed control method is proved by Lyapunov theory. The performance of the adaptive neural network fraction integral terminal sliding mode control is compared with three other conventional controllers such as sliding mode control, integral terminal sliding mode control and fraction integral terminal sliding mode control. Simulation results show the effectiveness of the proposed control method.

  7. A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice

    OpenAIRE

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

    2013-01-01

    We propose a new stochastic actor-oriented model for the co-evolution of two-mode and one-mode networks. The model posits that activities of a set of actors, represented in the two-mode network, co-evolve with exchanges and interactions between the actors, as represented in the one-mode network. The model assumes that the actors, not the activities, have agency.

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

    Directory of Open Access Journals (Sweden)

    Yan-long Zhou

    2013-01-01

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

  9. 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.

  10. Mode-selective optical packet switching in mode-division multiplexing networks.

    Science.gov (United States)

    Diamantopoulos, N P; Hayashi, M; Yoshida, Y; Maruta, A; Maruyama, R; Kuwaki, N; Takenaga, K; Uemura, H; Matsuo, S; Kitayama, K

    2015-09-07

    A novel mode-selective optical packet switching, based on mode-multiplexers/demultiplexers and multi-port optical micro-electro-mechanical systems (MEMS) switches, has been proposed and experimentally demonstrated. The experimental demonstration was performed using the LP(01), LP(11a) and LP(11b) modes of a 30-km long mode-division multiplexed few-mode fiber link, utilizing 40 Gb/s, 16-QAM signals.

  11. Portraying the unique contribution of the default mode network to internally driven mnemonic processes.

    Science.gov (United States)

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

    2013-03-26

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

  12. Perturbed connectivity of the amygdala and its subregions with the central executive and default mode networks in chronic pain.

    Science.gov (United States)

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

    2016-09-01

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

  13. Sliding Modes for Anomaly Observation in TCP Networks: From Theory to Practice

    OpenAIRE

    Rahme, Sandy; Labit, Yann; Gouaisbaut, Frédéric; Floquet, Thierry

    2013-01-01

    International audience; Anomaly detection has been an active open problem in the networks community for several years. In this brief, we aim at detecting such abnormal signals by control theory techniques. Several classes of sliding mode observers are proposed for a fluid flow model of the transmission control protocol (TCP)/internet protocol network. Comparative simulations via network simulator NS-2 show the enhancement brought by a higher order sliding mode observer. The efficiency of this...

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

    Science.gov (United States)

    Liu, Xiaosong; Shan, Zebiao; Li, Yuanchun

    2017-04-01

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

  15. Modeling one-mode projection of bipartite networks by tagging vertex information

    Science.gov (United States)

    Qiao, Jian; Meng, Ying-Ying; Chen, Hsinchun; Huang, Hong-Qiao; Li, Guo-Ying

    2016-09-01

    Traditional one-mode projection models are less informative than their original bipartite networks. Hence, using such models cannot control the projection's structure freely. We proposed a new method for modeling the one-mode projection of bipartite networks, which thoroughly breaks through the limitations of the available one-mode projecting methods by tagging the vertex information of bipartite networks in their one-mode projections. We designed a one-mode collaboration network model by using the method presented in this paper. The simulation results show that our model matches three real networks very well and outperforms the available collaboration network models significantly, which reflects the idea that our method is ideal for modeling one-mode projection models of bipartite graphs and that our one-mode collaboration network model captures the crucial mechanisms of the three real systems. Our study reveals that size growth, individual aging, random collaboration, preferential collaboration, transitivity collaboration and multi-round collaboration are the crucial mechanisms of collaboration networks, and the lack of some of the crucial mechanisms is the main reason that the other available models do not perform as well as ours.

  16. Industrial entrepreneurial network: Structural and functional analysis

    Science.gov (United States)

    Medvedeva, M. A.; Davletbaev, R. H.; Berg, D. B.; Nazarova, J. J.; Parusheva, S. S.

    2016-12-01

    Structure and functioning of two model industrial entrepreneurial networks are investigated in the present paper. One of these networks is forming when implementing an integrated project and consists of eight agents, which interact with each other and external environment. The other one is obtained from the municipal economy and is based on the set of the 12 real business entities. Analysis of the networks is carried out on the basis of the matrix of mutual payments aggregated over the certain time period. The matrix is created by the methods of experimental economics. Social Network Analysis (SNA) methods and instruments were used in the present research. The set of basic structural characteristics was investigated: set of quantitative parameters such as density, diameter, clustering coefficient, different kinds of centrality, and etc. They were compared with the random Bernoulli graphs of the corresponding size and density. Discovered variations of random and entrepreneurial networks structure are explained by the peculiarities of agents functioning in production network. Separately, were identified the closed exchange circuits (cyclically closed contours of graph) forming an autopoietic (self-replicating) network pattern. The purpose of the functional analysis was to identify the contribution of the autopoietic network pattern in its gross product. It was found that the magnitude of this contribution is more than 20%. Such value allows using of the complementary currency in order to stimulate economic activity of network agents.

  17. Intrinsic functional network organization in high-functioning adolescents with autism spectrum disorder

    Directory of Open Access Journals (Sweden)

    Elizabeth eRedcay

    2013-09-01

    Full Text Available Converging theories and data suggest that atypical patterns of functional and structural connectivity are a hallmark neurobiological feature of autism. However, empirical studies of functional connectivity, or, the correlation of MRI signal between brain regions, have largely been conducted during task performance and/or focused on group differences within one network (e.g., the default mode network. This narrow focus on task-based connectivity and single network analyses precludes investigation of whole-brain intrinsic network organization in autism. To assess whole-brain network properties in adolescents with autism, we collected resting-state functional connectivity MRI (rs-fcmri data from neurotypical adolescents (NT and adolescents with autism spectrum disorder (ASD. We used graph theory metrics on rs-fcmri data with 34 regions of interest (i.e., nodes that encompass 4 different functionally-defined networks: cingulo-opercular, cerebellar, fronto-parietal, and default mode (DMN (Fair et al., 2009. Contrary to our hypotheses, network analyses revealed minimal differences between groups with one exception. Betweenness centrality, which indicates the degree to which a seed (or node functions as a hub within and between networks was greater for participants with autism for the right lateral parietal region of the DMN. Follow-up seed-based analyses demonstrated greater functional connectivity in ASD than NT groups between the right lateral parietal seed and another region of the DMN, the anterior medial prefrontal cortex. Greater connectivity between these regions was related to lower ADOS scores (i.e. lower impairment in autism. These findings do not support current theories of underconnectivity in autism, but, rather, underscore the need for future studies to systematically examine factors that can influence patterns of intrinsic connectivity such as autism severity, age, and head motion.

  18. Integrating phosphorylation network with transcriptional network reveals novel functional relationships.

    Directory of Open Access Journals (Sweden)

    Lin Wang

    Full Text Available Phosphorylation and transcriptional regulation events are critical for cells to transmit and respond to signals. In spite of its importance, systems-level strategies that couple these two networks have yet to be presented. Here we introduce a novel approach that integrates the physical and functional aspects of phosphorylation network together with the transcription network in S.cerevisiae, and demonstrate that different network motifs are involved in these networks, which should be considered in interpreting and integrating large scale datasets. Based on this understanding, we introduce a HeRS score (hetero-regulatory similarity score to systematically characterize the functional relevance of kinase/phosphatase involvement with transcription factor, and present an algorithm that predicts hetero-regulatory modules. When extended to signaling network, this approach confirmed the structure and cross talk of MAPK pathways, inferred a novel functional transcription factor Sok2 in high osmolarity glycerol pathway, and explained the mechanism of reduced mating efficiency upon Fus3 deletion. This strategy is applicable to other organisms as large-scale datasets become available, providing a means to identify the functional relationships between kinases/phosphatases and transcription factors.

  19. Radial basis function networks and complexity regularization in function learning.

    Science.gov (United States)

    Krzyzak, A; Linder, T

    1998-01-01

    In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function network. Our approach differs from previous complexity regularization neural-network function learning schemes in that we operate with random covering numbers and l(1) metric entropy, making it possible to consider much broader families of activation functions, namely functions of bounded variation. Some constraints previously imposed on the network parameters are also eliminated this way. The network is trained by means of complexity regularization involving empirical risk minimization. Bounds on the expected risk in terms of the sample size are obtained for a large class of loss functions. Rates of convergence to the optimal loss are also derived.

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

    Science.gov (United States)

    Schmithorst, Vincent J; Plante, Elena; Holland, Scott

    2014-01-01

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

  1. A universal formula for network functions

    DEFF Research Database (Denmark)

    Skelboe, Stig

    1975-01-01

    A linear electrical network can be described in a convenient way by means of the node equations. This letter presents a universal formula which expresses any network function as the quotient of two determinants. The determinants belong to matrices derived from the indefinite nodal admittance...

  2. From networks of protein interactions to networks of functional dependencies

    Directory of Open Access Journals (Sweden)

    Luciani Davide

    2012-05-01

    Full Text Available Abstract Background As protein-protein interactions connect proteins that participate in either the same or different functions, networks of interacting and functionally annotated proteins can be converted into process graphs of inter-dependent function nodes (each node corresponding to interacting proteins with the same functional annotation. However, as proteins have multiple annotations, the process graph is non-redundant, if only proteins participating directly in a given function are included in the related function node. Results Reasoning that topological features (e.g., clusters of highly inter-connected proteins might help approaching structured and non-redundant understanding of molecular function, an algorithm was developed that prioritizes inclusion of proteins into the function nodes that best overlap protein clusters. Specifically, the algorithm identifies function nodes (and their mutual relations, based on the topological analysis of a protein interaction network, which can be related to various biological domains, such as cellular components (e.g., peroxisome and cellular bud or biological processes (e.g., cell budding of the model organism S. cerevisiae. Conclusions The method we have described allows converting a protein interaction network into a non-redundant process graph of inter-dependent function nodes. The examples we have described show that the resulting graph allows researchers to formulate testable hypotheses about dependencies among functions and the underlying mechanisms.

  3. Indirect photobiomodulation in functional networks

    Science.gov (United States)

    Liu, Timon Cheng-Yi; Zhu, Wei-Wei; Yang, Xiang-Bo

    2012-12-01

    Photobiomodulation (PBM) is a non-damaged modulation of laser irradiation or monochromatic light (LI) on a biosystem function. It depends on whether the function is in its function-specific homeostasis (FSH), a negative feedback response for the function to be performed perfectly. Many redundant pathways (RPs) maintain the same cellular function. The full activation of any of RPs can maintain a normal function in its FSH, but partial activation of all the RPs can only maintain a dysfunctional function far from its FSH. A PBM may self-adaptively modulate the activation of a partially activated RP of a normal function until it is fully activated and the normal function is then upgraded. This PBM is called indirect PBM (iPBM). The iPBM on cells such as tumor cells, myoblast cells and fibroblasts and other biosystems and their applications would be reviewed in this paper.

  4. A fuzzy neural network sliding mode controller for vibration suppression in robotically assisted minimally invasive surgery.

    Science.gov (United States)

    Sang, Hongqiang; Yang, Chenghao; Liu, Fen; Yun, Jintian; Jin, Guoguang

    2016-12-01

    It is very important for robotically assisted minimally invasive surgery to achieve a high-precision and smooth motion control. However, the surgical instrument tip will exhibit vibration caused by nonlinear friction and unmodeled dynamics, especially when the surgical robot system is attempting low-speed, fine motion. A fuzzy neural network sliding mode controller (FNNSMC) is proposed to suppress vibration of the surgical robotic system. Nonlinear friction and modeling uncertainties are compensated by a Stribeck model, a radial basis function (RBF) neural network and a fuzzy system, respectively. Simulations and experiments were performed on a 3 degree-of-freedom (DOF) minimally invasive surgical robot. The results demonstrate that the FNNSMC is effective and can suppress vibrations at the surgical instrument tip. The proposed FNNSMC can provide a robust performance and suppress the vibrations at the surgical instrument tip, which can enhance the quality and security of surgical procedures. Copyright © 2016 John Wiley & Sons, Ltd.

  5. Stability analysis of switched cellular neural networks: A mode-dependent average dwell time approach.

    Science.gov (United States)

    Huang, Chuangxia; Cao, Jie; Cao, Jinde

    2016-10-01

    This paper addresses the exponential stability of switched cellular neural networks by using the mode-dependent average dwell time (MDADT) approach. This method is quite different from the traditional average dwell time (ADT) method in permitting each subsystem to have its own average dwell time. Detailed investigations have been carried out for two cases. One is that all subsystems are stable and the other is that stable subsystems coexist with unstable subsystems. By employing Lyapunov functionals, linear matrix inequalities (LMIs), Jessen-type inequality, Wirtinger-based inequality, reciprocally convex approach, we derived some novel and less conservative conditions on exponential stability of the networks. Comparing to ADT, the proposed MDADT show that the minimal dwell time of each subsystem is smaller and the switched system stabilizes faster. The obtained results extend and improve some existing ones. Moreover, the validness and effectiveness of these results are demonstrated through numerical simulations.

  6. Steady-state and dynamic network modes for perceptual expectation.

    Science.gov (United States)

    Choi, Uk-Su; Sung, Yul-Wan; Ogawa, Seiji

    2017-01-12

    Perceptual expectation can attenuate repetition suppression, the stimulus-induced neuronal response generated by repeated stimulation, suggesting that repetition suppression is a top-down modulatory phenomenon. However, it is still unclear which high-level brain areas are involved and how they interact with low-level brain areas. Further, the temporal range over which perceptual expectation can effectively attenuate repetition suppression effects remains unclear. To elucidate the details of this top-down modulatory process, we used two short and long inter-stimulus intervals for a perceptual expectation paradigm of paired stimulation. We found that top-down modulation enhanced the response to the unexpected stimulus when repetition suppression was weak and that the effect disappeared at 1,000 ms prior to stimulus exposure. The high-level areas involved in this process included the left inferior frontal gyrus (IFG_L) and left parietal lobule (IPL_L). We also found two systems providing modulatory input to the right fusiform face area (FFA_R): one from IFG_L and the other from IPL_L. Most importantly, we identified two states of networks through which perceptual expectation modulates sensory responses: one is a dynamic state and the other is a steady state. Our results provide the first functional magnetic resonance imaging (fMRI) evidence of temporally nested networks in brain processing.

  7. A default mode of brain function in altered states of consciousness.

    Science.gov (United States)

    Guldenmund, P; Vanhaudenhuyse, A; Boly, M; Laureys, S; Soddu, A

    2012-01-01

    Using modern brain imaging techniques, new discoveries are being made concerning the spontaneous activity of the brain when it is devoid of attention-demanding tasks. Spatially separated patches of neuronal assemblies have been found to show synchronized oscillatory activity behavior and are said to be functionally connected. One of the most robust of these is the default mode network, which is associated with intrinsic processes like mind wandering and self-projection. Furthermore, activity in this network is anticorrelated with activity in a network that is linked to attention to external stimuli. The integrity of both networks is disturbed in altered states of consciousness, like sleep, general anesthesia and hypnosis. In coma and related disorders of consciousness, encompassing the vegetative state (unresponsive wakefulness syndrome) and minimally conscious state, default mode network integrity correlates with the level of remaining consciousness, offering the possibility of using this information for diagnostic and prognostic purposes. Functional brain imaging is currently being validated as a valuable addition to the standardized behavioral assessments that are already in use.

  8. Fuzzy Functional Dependencies and Bayesian Networks

    Institute of Scientific and Technical Information of China (English)

    LIU WeiYi(刘惟一); SONG Ning(宋宁)

    2003-01-01

    Bayesian networks have become a popular technique for representing and reasoning with probabilistic information. The fuzzy functional dependency is an important kind of data dependencies in relational databases with fuzzy values. The purpose of this paper is to set up a connection between these data dependencies and Bayesian networks. The connection is done through a set of methods that enable people to obtain the most information of independent conditions from fuzzy functional dependencies.

  9. Intrinsic neuronal properties switch the mode of information transmission in networks.

    Directory of Open Access Journals (Sweden)

    Julijana Gjorgjieva

    2014-12-01

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

  10. Intrinsic neuronal properties switch the mode of information transmission in networks.

    Science.gov (United States)

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

    2014-12-01

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

  11. 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.

  12. Identifying Functional Modules in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In this paper, we propose a new method that enables us to detect and describe the functional modules in complex networks. Using the proposed method, we can classify the nodes of networks into different modules according to their pattern of intra- and extra-module links. We use our method to analyze the modular structures of the ER random networks. We find that different modules of networks have different structure properties, such as the clustering coefficient. Moreover, at the same time, many nodes of networks participate different modules. Remarkably, we find that in the ER random networks, when the probability p is small, different modules or different roles of nodes can be identified by different regionsin the c-p parameter space.

  13. Investigating Default Mode and Sensorimotor Network Connectivity in Amyotrophic Lateral Sclerosis.

    Science.gov (United States)

    Chenji, Sneha; Jha, Shankar; Lee, Dawon; Brown, Matthew; Seres, Peter; Mah, Dennell; Kalra, Sanjay

    2016-01-01

    Amyotrophic lateral sclerosis (ALS) is a neurodegenerative condition characterized by degeneration of upper motor neurons (UMN) arising from the motor cortex in the brain and lower motor neurons (LMN) in the brainstem and spinal cord. Cerebral changes create differences in brain activity captured by functional magnetic resonance imaging (fMRI), including the spontaneous and simultaneous activity occurring between regions known as the resting state networks (RSNs). Progressive neurodegeneration as observed in ALS may lead to a disruption of RSNs which could provide insights into the disease process. Previous studies have reported conflicting findings of increased, decreased, or unaltered RSN functional connectivity in ALS and do not report the contribution of UMN changes to RSN connectivity. We aimed to bridge this gap by exploring two networks, the default mode network (DMN) and the sensorimotor network (SMN), in 21 ALS patients and 40 age-matched healthy volunteers. An UMN score dichotomized patients into UMN+ and UMN- groups. Subjects underwent resting state fMRI scan on a high field MRI operating at 4.7 tesla. The DMN and SMN changes between subject groups were compared. Correlations between connectivity and clinical measures such as the ALS Functional Rating Scale-Revised (ALSFRS-R), disease progression rate, symptom duration, UMN score and finger tapping were assessed. Significant group differences in resting state networks between patients and controls were absent, as was the dependence on degree of UMN burden. However, DMN connectivity was increased in patients with greater disability and faster progression rate, and SMN connectivity was reduced in those with greater motor impairment. These patterns of association are in line with literature supporting loss of inhibitory interneurons.

  14. Investigating Default Mode and Sensorimotor Network Connectivity in Amyotrophic Lateral Sclerosis.

    Directory of Open Access Journals (Sweden)

    Sneha Chenji

    Full Text Available Amyotrophic lateral sclerosis (ALS is a neurodegenerative condition characterized by degeneration of upper motor neurons (UMN arising from the motor cortex in the brain and lower motor neurons (LMN in the brainstem and spinal cord. Cerebral changes create differences in brain activity captured by functional magnetic resonance imaging (fMRI, including the spontaneous and simultaneous activity occurring between regions known as the resting state networks (RSNs. Progressive neurodegeneration as observed in ALS may lead to a disruption of RSNs which could provide insights into the disease process. Previous studies have reported conflicting findings of increased, decreased, or unaltered RSN functional connectivity in ALS and do not report the contribution of UMN changes to RSN connectivity. We aimed to bridge this gap by exploring two networks, the default mode network (DMN and the sensorimotor network (SMN, in 21 ALS patients and 40 age-matched healthy volunteers. An UMN score dichotomized patients into UMN+ and UMN- groups. Subjects underwent resting state fMRI scan on a high field MRI operating at 4.7 tesla. The DMN and SMN changes between subject groups were compared. Correlations between connectivity and clinical measures such as the ALS Functional Rating Scale-Revised (ALSFRS-R, disease progression rate, symptom duration, UMN score and finger tapping were assessed. Significant group differences in resting state networks between patients and controls were absent, as was the dependence on degree of UMN burden. However, DMN connectivity was increased in patients with greater disability and faster progression rate, and SMN connectivity was reduced in those with greater motor impairment. These patterns of association are in line with literature supporting loss of inhibitory interneurons.

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

    Science.gov (United States)

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

    2014-01-01

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

  16. Situating the default-mode network along a principal gradient of macroscale cortical organization.

    Science.gov (United States)

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

    2016-11-01

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

  17. 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.

  18. 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...

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

    Directory of Open Access Journals (Sweden)

    Vincent eSchmithorst

    2014-03-01

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

  20. Segregation between the parietal memory network and the default mode network: effects of spatial smoothing and model order in ICA.

    Science.gov (United States)

    Hu, Yang; Wang, Jijun; Li, Chunbo; Wang, Yin-Shan; Yang, Zhi; Zuo, Xi-Nian

    2016-01-01

    A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent fMRI studies. Though it is anatomically adjacent to and spatially overlaps with the default mode network (DMN), its function has been associated with memory processing, and it has been referred to as the parietal memory network (PMN). Independent component analysis (ICA) is the most common data-driven method used to extract PMN and DMN simultaneously. However, the effects of data preprocessing and parameter determination in ICA on PMN-DMN segregation are completely unknown. Here, we employ three typical algorithms of group ICA to assess how spatial smoothing and model order influence the degree of PMN-DMN segregation. Our findings indicate that PMN and DMN can only be stably separated using a combination of low-level spatial smoothing and high model order across the three ICA algorithms. We thus argue for more considerations on parametric settings for interpreting DMN data.

  1. 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.

  2. Dynamical patterns of calcium signaling in a functional model of neuron-astrocyte networks

    DEFF Research Database (Denmark)

    Postnov, D.E.; Koreshkov, R.N.; Brazhe, N.A.

    2009-01-01

    We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission...... in astrocytic-neuronal networks. We reproduce local and global dynamical patterns observed experimentally....

  3. Logistics Mode and Network Planning for Recycle of Crop Straw Resources

    Institute of Scientific and Technical Information of China (English)

    Lingyun; ZHOU; Weidong; GU; Qing; ZHANG

    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 comes up with construction and operation strategies of the straw logistics network from infrastructure,organization network,and information platform.

  4. Memory Systems, Processing Modes, and Components: Functional Neuroimaging Evidence

    Science.gov (United States)

    Cabeza, Roberto; Moscovitch, Morris

    2013-01-01

    In the 1980s and 1990s, there was a major theoretical debate in the memory domain regarding the multiple memory systems and processing modes frameworks. The components of processing framework argued for a middle ground: Instead of neatly divided memory systems or processing modes, this framework proposed the existence of numerous processing components that are recruited in different combinations by memory tasks and yield complex patterns of associations and dissociations. Because behavioral evidence was not sufficient to decide among these three frameworks, the debate was largely abandoned. However, functional neuroimaging evidence accumulated during the last two decades resolves the stalemate, because this evidence is more consistent with the components framework than with the other two frameworks. For example, functional neuroimaging evidence shows that brain regions attributed to one memory system can contribute to tasks associated with other memory systems and that brain regions attributed to the same processing mode (perceptual or conceptual) can be dissociated from each other. Functional neuroimaging evidence suggests that memory processes are supported by transient interactions between a few regions called process-specific alliances. These conceptual developments are an example of how functional neuroimaging can contribute to theoretical debates in cognitive psychology. PMID:24163702

  5. A two-mode planetary nebula luminosity function

    CERN Document Server

    Rodríguez-González, A; Esquivel, A; Raga, A C; Stasińska, G; Peña, M; Mayya, D

    2014-01-01

    We propose a new Planetary Nebula Luminosity Function (PNLF) that includes two populations in the distribution. Our PNLF is a direct extension of the canonical function proposed by Jacoby et al. (1987), in order to avoid problems related with the histogram construction, it is cast in terms of cumulative functions. We are interested in recovering the shape of the faint part of the PNLF in a consistent manner, for galaxies with and without a dip in their PN luminosity functions. The parameters for the two mode PNLF are obtained with a genetic algorithm, which obtains a best fit to the PNLF varying all of the parameters simultaneously in a broad parameter space. We explore a sample of 9 galaxies with various Hubble types and construct their PNLF. All of the irregular galaxies, except one, are found to be consistent with a two-mode population, while the situation is less clear for ellipticals and spirals.For the case of NGC\\, 6822, we show that the two-mode PNLF is consistent with previous studies of the star for...

  6. Functional brain networks in schizophrenia: a review

    Directory of Open Access Journals (Sweden)

    Vince D Calhoun

    2009-08-01

    Full Text Available Functional magnetic resonance imaging (fMRI has become a major technique for studying cognitive function and its disruption in mental illness, including schizophrenia. The major proportion of imaging studies focused primarily upon identifying regions which hemodynamic response amplitudes covary with particular stimuli and differentiate between patient and control groups. In addition to such amplitude based comparisons, one can estimate temporal correlations and compute maps of functional connectivity between regions which include the variance associated with event related responses as well as intrinsic fluctuations of hemodynamic activity. Functional connectivity maps can be computed by correlating all voxels with a seed region when a spatial prior is available. An alternative are multivariate decompositions such as independent component analysis (ICA which extract multiple components, each of which is a spatially distinct map of voxels with a common time course. Recent work has shown that these networks are pervasive in relaxed resting and during task performance and hence provide robust measures of intact and disturbed brain activity. This in turn bears the prospect of yielding biomarkers for schizophrenia, which can be described both in terms of disrupted local processing as well as altered global connectivity between large scale networks. In this review we will summarize functional connectivity measures with a focus upon work with ICA and discuss the meaning of intrinsic fluctuations. In addition, examples of how brain networks have been used for classification of disease will be shown. We present work with functional network connectivity, an approach that enables the evaluation of the interplay between multiple networks and how they are affected in disease. We conclude by discussing new variants of ICA for extracting maximally group discriminative networks from data. In summary, it is clear that identification of brain networks and their

  7. Agricultural Development Mode Transformation and Government Functions in Guizhou Province

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Based on the brief account of the connotation of transforming economic development pattern and government functions,the thesis will introduce the development status of agricultural economy in Guizhou Province:firstly,single agricultural industrial structure;secondly,large gap between urban and rural development;thirdly,low-level utilization of agricultural science and technology;fourthly,fierce contradiction between agricultural mode of production and ecological environment.Then it analyzes the basic requirements for government functions in transforming the development pattern of agricultural economy in Guizhou Province:the first one is the function to guide sustainable development and the structural adjustment of agricultural production;the second is the function to coordinate urban-rural development and equally supply basic public goods;the third is the function to input science and technology to serve agriculture;the fourth one is the dominant function to promote the harmonious development of man and nature as well as to reduce the number of peasants.In order to promote the transformation of agricultural development mode and maintain the sound and rapid economic development,some corresponding measures and suggestions are proposed from the perspective of government functions:firstly,promoting the optimization and upgrading of industrial structure;secondly,the government should take the lead in providing rural public goods;thirdly,strengthening the skills training and technological education of rural labor force;fourthly,reducing the number of farmers and retaining the farmers.

  8. 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.

  9. Representation of Functional Data in Neural Networks

    CERN Document Server

    Rossi, Fabrice; Conan-Guez, Brieuc; Verleysen, Michel

    2005-01-01

    Functional Data Analysis (FDA) is an extension of traditional data analysis to functional data, for example spectra, temporal series, spatio-temporal images, gesture recognition data, etc. Functional data are rarely known in practice; usually a regular or irregular sampling is known. For this reason, some processing is needed in order to benefit from the smooth character of functional data in the analysis methods. This paper shows how to extend the Radial-Basis Function Networks (RBFN) and Multi-Layer Perceptron (MLP) models to functional data inputs, in particular when the latter are known through lists of input-output pairs. Various possibilities for functional processing are discussed, including the projection on smooth bases, Functional Principal Component Analysis, functional centering and reduction, and the use of differential operators. It is shown how to incorporate these functional processing into the RBFN and MLP models. The functional approach is illustrated on a benchmark of spectrometric data ana...

  10. Histone chaperone networks shaping chromatin function

    DEFF Research Database (Denmark)

    Hammond, Colin; Strømme, Caroline Bianchi; Huang, Hongda

    2017-01-01

    and fate, which affects all chromosomal processes, including gene expression, chromosome segregation and genome replication and repair. Here, we review the distinct structural and functional properties of the expanding network of histone chaperones. We emphasize how chaperones cooperate in the histone...... chaperone network and via co-chaperone complexes to match histone supply with demand, thereby promoting proper nucleosome assembly and maintaining epigenetic information by recycling modified histones evicted from chromatin....

  11. Functional network inference of the suprachiasmatic nucleus.

    Science.gov (United States)

    Abel, John H; Meeker, Kirsten; Granados-Fuentes, Daniel; St John, Peter C; Wang, Thomas J; Bales, Benjamin B; Doyle, Francis J; Herzog, Erik D; Petzold, Linda R

    2016-04-19

    In the mammalian suprachiasmatic nucleus (SCN), noisy cellular oscillators communicate within a neuronal network to generate precise system-wide circadian rhythms. Although the intracellular genetic oscillator and intercellular biochemical coupling mechanisms have been examined previously, the network topology driving synchronization of the SCN has not been elucidated. This network has been particularly challenging to probe, due to its oscillatory components and slow coupling timescale. In this work, we investigated the SCN network at a single-cell resolution through a chemically induced desynchronization. We then inferred functional connections in the SCN by applying the maximal information coefficient statistic to bioluminescence reporter data from individual neurons while they resynchronized their circadian cycling. Our results demonstrate that the functional network of circadian cells associated with resynchronization has small-world characteristics, with a node degree distribution that is exponential. We show that hubs of this small-world network are preferentially located in the central SCN, with sparsely connected shells surrounding these cores. Finally, we used two computational models of circadian neurons to validate our predictions of network structure.

  12. Functional network inference of the suprachiasmatic nucleus

    Energy Technology Data Exchange (ETDEWEB)

    Abel, John H.; Meeker, Kirsten; Granados-Fuentes, Daniel; St. John, Peter C.; Wang, Thomas J.; Bales, Benjamin B.; Doyle, Francis J.; Herzog, Erik D.; Petzold, Linda R.

    2016-04-04

    In the mammalian suprachiasmatic nucleus (SCN), noisy cellular oscillators communicate within a neuronal network to generate precise system-wide circadian rhythms. Although the intracellular genetic oscillator and intercellular biochemical coupling mechanisms have been examined previously, the network topology driving synchronization of the SCN has not been elucidated. This network has been particularly challenging to probe, due to its oscillatory components and slow coupling timescale. In this work, we investigated the SCN network at a single-cell resolution through a chemically induced desynchronization. We then inferred functional connections in the SCN by applying the maximal information coefficient statistic to bioluminescence reporter data from individual neurons while they resynchronized their circadian cycling. Our results demonstrate that the functional network of circadian cells associated with resynchronization has small-world characteristics, with a node degree distribution that is exponential. We show that hubs of this small-world network are preferentially located in the central SCN, with sparsely connected shells surrounding these cores. Finally, we used two computational models of circadian neurons to validate our predictions of network structure.

  13. Energy-Efficient Next-Generation Passive Optical Networks Based on Sleep Mode and Heuristic Optimization

    Science.gov (United States)

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

    2015-05-01

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

  14. Exploring the psychosis functional connectome: aberrant intrinsic networks in schizophrenia and bipolar disorder

    Directory of Open Access Journals (Sweden)

    Vince D Calhoun

    2012-01-01

    Full Text Available Intrinsic functional brain networks (INs are regions showing temporal coherence with one another. These INs are present in the context of a task (as opposed to an undirected task such as rest, albeit modulated to a degree both spatially and temporally. Prominent networks include the default mode, attentional fronto-parietal, executive control, bilateral temporal lobe and motor networks. The characterization of INs has recently gained considerable momentum, however; most previous studies evaluate only a small subset of the intrinsic networks (e.g. default mode. In this paper we use independent component analysis to study INs decomposed from fMRI data collected in a large group of schizophrenia patients, healthy controls, and individuals with bipolar disorder, while performing an auditory oddball task. Schizophrenia and bipolar disorder share significant overlap in clinical symptoms, brain characteristics, and risk genes which motivates our goal of identifying whether functional imaging data can differentiate the two disorders. We tested for group differences in properties of all identified intrinsic networks including spatial maps, spectra, and functional network connectivity. A small set of default mode, temporal lobe, and frontal networks with default mode regions appearing to play a key role in all comparisons. Bipolar subjects showed more prominent changes in ventromedial and prefrontal default mode regions whereas schizophrenia patients showed changes in posterior default mode regions. Anti-correlations between left parietal areas and dorsolateral prefrontal cortical areas were different in bipolar and schizophrenia patients and amplitude was significantly different from healthy controls in both patient groups. Patients exhibited similar frequency behavior across multiple networks with decreased low frequency power. In summary, a comprehensive analysis of intrinsic networks reveals a key role for the default mode in both schizophrenia and

  15. 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.

  16. 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 t

  17. Changes of resting-state default-mode network functional connectivity in patients with unilateral sudden sensorineural hearing loss%单侧突发性感音神经性耳聋患者静息状态默认网络的变化

    Institute of Scientific and Technical Information of China (English)

    季慧; 黄志纯; 杨明; 朱新; 孟黎平; 李晶

    2012-01-01

    目的 探索单侧突发性感音神经性耳聋(SSNHL)患者静息状态默认网络的改变.方法 选取16例重度左侧突发性感音神经性耳聋患者(耳聋组)和16例健康志愿者(对照组)进行静息状态脑功能磁共振扫描,通过时程相关方法检测IMRI数据低频波动信号中以后扣带回为种子区的默认网络,并进行组间比较.结果 耳聋组较正常对照组脑功能连接增强的区域为右侧枕中回,耳聋组较正常对照组脑功能连接减弱的区域为右侧额中回.结论 SSNHL患者在静息状态下存在脑默认网络的功能连接异常.%To explore the changes of resting-state default-mode network functional connectivity in the patients with unilateral sudden sensorineural hearing loss(SSNHL). Methods The fMRI scanning in resting-state was performed in 16 severe left side SSNHL patients (group A) and 16 healthy volunteers with normal hearing( group B). The default-mode network based on seed region of posterior cingulated cortex was extracted from low frequency fluctuation signal in fMRI data using a temporal correlation method and compared between two groups. Results Compared with group B,the brain area with increased functional connectivity in group A was the right middle occipital gyrus, while the brain area with decreased functional connectivity was the right middle frontal gyrus. Conclusion The abnormal funtional connectivity of brain defanlt mode network happens to the SSNHL patients in resting state.

  18. Intrinsic functional network organization in high-functioning adolescents with autism spectrum disorder

    Science.gov (United States)

    Redcay, Elizabeth; Moran, Joseph M.; Mavros, Penelope L.; Tager-Flusberg, Helen; Gabrieli, John D. E.; Whitfield-Gabrieli, Susan

    2013-01-01

    Converging theories and data suggest that atypical patterns of functional and structural connectivity are a hallmark neurobiological feature of autism. However, empirical studies of functional connectivity, or, the correlation of MRI signal between brain regions, have largely been conducted during task performance and/or focused on group differences within one network [e.g., the default mode network (DMN)]. This narrow focus on task-based connectivity and single network analyses precludes investigation of whole-brain intrinsic network organization in autism. To assess whole-brain network properties in adolescents with autism, we collected resting-state functional connectivity MRI (rs-fcMRI) data from neurotypical (NT) adolescents and adolescents with autism spectrum disorder (ASD). We used graph theory metrics on rs-fcMRI data with 34 regions of interest (i.e., nodes) that encompass four different functionally defined networks: cingulo-opercular, cerebellar, fronto-parietal, and DMN (Fair etal., 2009). Contrary to our hypotheses, network analyses revealed minimal differences between groups with one exception. Betweenness centrality, which indicates the degree to which a seed (or node) functions as a hub within and between networks, was greater for participants with autism for the right lateral parietal (RLatP) region of the DMN. Follow-up seed-based analyses demonstrated greater functional connectivity in ASD than NT groups between the RLatP seed and another region of the DMN, the anterior medial prefrontal cortex. Greater connectivity between these regions was related to lower ADOS (Autism Diagnostic Observation Schedule) scores (i.e., lower impairment) in autism. These findings do not support current theories of underconnectivity in autism, but, rather, underscore the need for future studies to systematically examine factors that can influence patterns of intrinsic connectivity such as autism severity, age, and head motion. PMID:24062673

  19. Contacting mode operation of work function energy harvester

    Science.gov (United States)

    Varpula, A.; Laakso, S. J.; Havia, T.; Kyynäräinen, J.; Prunnila, M.

    2014-11-01

    The work function energy harvester (WFEH) is a variable capacitance vibration energy harvester where the charging of the capacitor electrodes is driven by the work function difference of the electrode materials. In this work, we investigate operation modes of the WFEH by utilizing a macroscopic parallel plate capacitor with Cu and Al electrodes and varying plate distance. We show that by charging the electrodes of the WFEH by letting the electrode plates touch during the operation a significant output power enhancement can be achieved in comparison to the case where the electrodes are charged and discharged only through a load resistor.

  20. USB Dual-Mode Function IP Core Development

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    This paper describes the specification and implement of a Universal Serial Bus (USB) dual-mode function IP core used for embedded system. Controlled by micro controller/CPU, the novel IP core can function as a USB host controller or USB peripheral controller. When configured as a USB host controller, it supports all USB 1.1 transaction types; supports automatic preamble insertion, and automatic SOF generation and transmission. Otherwise, when it is configured as a USB device by a microprocessor, it operates as a USB peripheral controller compliant with USB2.0 specification.

  1. Default mode network disturbances in restless legs syndrome/Willis-Ekbom disease.

    Science.gov (United States)

    Ku, Jeonghun; Lee, Yeong Seon; Chang, HyukWon; Earley, Christopher J; Allen, Richard P; Cho, Yong Won

    2016-07-01

    The unusual sensations of restless legs syndrome/Willis-Ekbom disease (RLS/WED) are induced by rest or a low arousal state with a circadian variation in the threshold for induction. It has been suggested that the emergence of RLS/WED symptoms relates to abnormal brain functions dealing with internally generated stimuli. The purpose of this study was to investigate the changes in the default mode network (DMN) in RLS/WED subjects. Sixteen drug-naïve, idiopathic, RLS/WED subjects, and 16 age-matched and gender-matched healthy subjects were scanned in an asymptomatic resting state. A comparison of the DMN was conducted between the two groups. Resting state functional magnetic resonance imaging (MRI), Korean versions of the International RLS scale, and other sleep questionnaires were used. The results showed reductions in the DMN connectivity in the left posterior cingulate cortex, the right orbito-frontal gyrus, the left precuneus, and the right subcallosal gyrus of the RLS/WED subjects. The DMN connectivity was increased in sensory-motor-associated circuits, which included the right superior parietal lobule, the right supplementary motor area, and the left thalamus. In addition, the connectivity between the DMN and thalamus was negatively correlated with that in the orbito-frontal gyrus and the subcallosal gyrus in the subjects. The results showed disturbances of the DMN in RLS/WED subjects that influence the thalamic relay sensory-motor-associated circuit. These findings may underscore the fact that RLS/WED subjects have disturbances in default mode network functions involving internal stimuli in the resting state. This may be related to compensatory changes to maintain resting. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Altered resting state connectivity of the default mode network in alexithymia

    NARCIS (Netherlands)

    Liemburg, Edith J.; Swart, Marte; Bruggeman, Richard; Kortekaas, Rudie; Knegtering, Henderikus; Curcic-Blake, Branislava; Aleman, Andre

    Alexithymia is a trait characterized by a diminished capacity to describe and distinguish emotions and to fantasize; it is associated with reduced introspection and problems in emotion processing. The default mode network (DMN) is a network of brain areas that is normally active during rest and

  3. Modes of governance of new service development for mobile networks. A life cycle perspective

    NARCIS (Netherlands)

    J.C.M. van den Ende (Jan)

    2002-01-01

    textabstractThis paper focuses on governance modes for service development of mobile telephone networks (GSM, WAP, GPRS, UMTS). 'Services' refer to services embodying a specific content. The paper shows that the phase of the life cycle of the network and the service affects the choice of governance

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

    Science.gov (United States)

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

    2016-05-01

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

  5. 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.

  6. Assessing Two-Mode Semantic Network Story Representations Using a False Memory Paradigm

    OpenAIRE

    Corman, Steven R.; Ball, B. Hunter; Talboom, Kimberly M.; GENE A. BREWER

    2013-01-01

    This paper describes a novel method of representing semantic networks of stories (and other text) as a two-mode graph. This method has some advantages over traditional one-mode semantic networks, but has the potential drawback (shared with n-gram text networks) that it contains paths that are not present in the text. An empirical study was devised using a false memory paradigm to determine whether these induced paths are remembered as being true of a set of stories. Results indicate that part...

  7. Generalization performance of radial basis function networks.

    Science.gov (United States)

    Lei, Yunwen; Ding, Lixin; Zhang, Wensheng

    2015-03-01

    This paper studies the generalization performance of radial basis function (RBF) networks using local Rademacher complexities. We propose a general result on controlling local Rademacher complexities with the L1 -metric capacity. We then apply this result to estimate the RBF networks' complexities, based on which a novel estimation error bound is obtained. An effective approximation error bound is also derived by carefully investigating the Hölder continuity of the lp loss function's derivative. Furthermore, it is demonstrated that the RBF network minimizing an appropriately constructed structural risk admits a significantly better learning rate when compared with the existing results. An empirical study is also performed to justify the application of our structural risk in model selection.

  8. Schizophrenia classification using functional network features

    Science.gov (United States)

    Rish, Irina; Cecchi, Guillermo A.; Heuton, Kyle

    2012-03-01

    This paper focuses on discovering statistical biomarkers (features) that are predictive of schizophrenia, with a particular focus on topological properties of fMRI functional networks. We consider several network properties, such as node (voxel) strength, clustering coefficients, local efficiency, as well as just a subset of pairwise correlations. While all types of features demonstrate highly significant statistical differences in several brain areas, and close to 80% classification accuracy, the most remarkable results of 93% accuracy are achieved by using a small subset of only a dozen of most-informative (lowest p-value) correlation features. Our results suggest that voxel-level correlations and functional network features derived from them are highly informative about schizophrenia and can be used as statistical biomarkers for the disease.

  9. Distributed Function Calculation over Noisy Networks

    Directory of Open Access Journals (Sweden)

    Zhidun Zeng

    2016-01-01

    Full Text Available Considering any connected network with unknown initial states for all nodes, the nearest-neighbor rule is utilized for each node to update its own state at every discrete-time step. Distributed function calculation problem is defined for one node to compute some function of the initial values of all the nodes based on its own observations. In this paper, taking into account uncertainties in the network and observations, an algorithm is proposed to compute and explicitly characterize the value of the function in question when the number of successive observations is large enough. While the number of successive observations is not large enough, we provide an approach to obtain the tightest possible bounds on such function by using linear programing optimization techniques. Simulations are provided to demonstrate the theoretical results.

  10. Functional Localization of Genetic Network Programming

    Science.gov (United States)

    Eto, Shinji; Hirasawa, Kotaro; Hu, Jinglu

    According to the knowledge of brain science, it is suggested that there exists cerebral functional localization, which means that a specific part of the cerebrum is activated depending on various kinds of information human receives. The aim of this paper is to build an artificial model to realize functional localization based on Genetic Network Programming (GNP), a new evolutionary computation method recently developed. GNP has a directed graph structure suitable for realizing functional localization. We studied the basic characteristics of the proposed system by making GNP work in a functionally localized way.

  11. Default Mode Network Activity Predicts Early Memory Decline in Healthy Young Adults Aged 18-31.

    Science.gov (United States)

    Nelson, Steven M; Savalia, Neil K; Fishell, Andrew K; Gilmore, Adrian W; Zou, Fan; Balota, David A; McDermott, Kathleen B

    2016-08-01

    Functional magnetic resonance imaging (fMRI) research conducted in healthy young adults is typically done with the assumption that this sample is largely homogeneous. However, studies from cognitive psychology suggest that long-term memory and attentional control begin to diminish in the third decade of life. Here, 100 participants between the ages of 18 and 31 learned Lithuanian translations of English words in an individual differences study using fMRI. Long-term memory ability was operationalized for each participant by deriving a memory score from 3 convergent measures. Age of participant predicted memory score in this cohort. In addition, degree of deactivation during initial encoding in a set of regions occurring largely in the default mode network (DMN) predicted both age and memory score. The current study demonstrates that early memory decline may partially be accounted for by failure to modulate activity in the DMN.

  12. 2型糖尿病患者大脑默认模式网络功能及灰质体积改变的功能MRI研究%Aberrant function connectivity and grey matter volume within default mode network in patients with type 2 diabetes mellitus by functional MRI

    Institute of Scientific and Technical Information of China (English)

    王晓阳; 李辉; 林丹丹; 付丽媛; 林钱森; 陈锦华; 陈自谦

    2016-01-01

    目的 采用独立成分分析法(ICA)和基于体素的形态测量学(VBM)方法,研究2型糖尿病(T2DM)患者大脑默认模式网络(DMN)功能及其灰质体积的改变.方法 2014年5月至2015年1月收集29例T2DM患者(T2DM组)及年龄、性别相匹配的33名健康志愿者(对照组),利用蒙特利尔认知评估(MoCA)及简易精神状态检查量表(MMSE)进行认知评分,然后行脑部静息态fMRI及3DT1WI结构像扫描.利用ICA法处理静息态功能成像数据,分离提取DMN,并利用VBM法得到DMN各脑区的灰质体积.采用双样本t检验对两组DMN的功能网络及灰质体积进行比较,并将差异区的功能连接值(FC)与灰质体积、病程进行Pearson相关分析.结果 T2DM组患者较对照组DMN的功能连接减低脑区主要为右侧前扣带回和内侧前额叶皮层(体素数目为121,t=-3.81,P<0.05),两组灰质体积差异无统计学意义,并且差异区的功能网络参与度值与灰质体积无相关性,与糖尿病病程也无相关性.结论 T2DM患者大脑DMN的功能连接先于其灰质体积发生变化,提示DMN可能成为一种监测T2DM患者认知损害相关脑部改变的方法.%Objective To explore early aberrant change of the function and grey matter volume within default-mode network in patients with type 2 diabetes mellitus (T2DM) by Independent component analysis and voxel-based morphometry.Methods Twenty-nine T2DM patients and thirty-three healthy control subjects were recruited in this study between May 2014 and January 2015,and the demographic and clinical data (fasting plasma glucose and HbA1c level) were obtained.General cognition was assessed by MMSE and MoCA in all subjects.Resting-state fMRI and T1-weighted imaging were performed in all subjects.Then the z-maps of default-mode network were obtained from Resting-state fMRI by independent component analysis,and the grey matter volumes were extracted by VBM.Finally,two-sample t-test was performed in the function and grey

  13. Developing Functional Networks of Frontier Capital Markets

    Science.gov (United States)

    2011-10-01

    capital. As Stiglitz and Gallegati (2011) note, “Some network designs may be good at absorbing small shocks, when there can be systemic failure when...functions in innovative ways. 3 Stiglitz , Joseph E. and Mauro Gallegati, “Heterogeneous Interacting Agent Models for Understanding Monetary

  14. Deep networks for motor control functions

    Directory of Open Access Journals (Sweden)

    Max eBerniker

    2015-03-01

    Full Text Available The motor system generates time-varying commands to move our limbs and body. Conventional descriptions of motor control and learning rely on dynamical representations of our body’s state (forward and inverse models, and control policies that must be integrated forward to generate feedforward time-varying commands; thus these are representations across space, but not time. Here we examine a new approach that directly represents both time-varying commands and the resulting state trajectories with a function; a representation across space and time. Since the output of this function includes time, it necessarily requires more parameters than a typical dynamical model. To avoid the problems of local minima these extra parameters introduce, we exploit recent advances in machine learning to build our function using a stacked autoencoder, or deep network. With initial and target states as inputs, this deep network can be trained to output an accurate temporal profile of the optimal command and state trajectory for a point-to-point reach of a nonlinear limb model, even when influenced by varying force fields. In a manner that mirrors motor babble, the network can also teach itself to learn through trial and error. Lastly, we demonstrate how this network can learn to optimize a cost objective. This functional approach to motor control is a sharp departure from the standard dynamical approach, and may offer new insights into the neural implementation of motor control.

  15. Altered functional brain networks in Prader-Willi syndrome.

    Science.gov (United States)

    Zhang, Yi; Zhao, Heng; Qiu, Siyou; Tian, Jie; Wen, Xiaotong; Miller, Jennifer L; von Deneen, Karen M; Zhou, Zhenyu; Gold, Mark S; Liu, Yijun

    2013-06-01

    Prader-Willi syndrome (PWS) is a genetic imprinting disorder characterized mainly by hyperphagia and early childhood obesity. Previous functional neuroimaging studies used visual stimuli to examine abnormal activities in the eating-related neural circuitry of patients with PWS. It was found that patients with PWS exhibited both excessive hunger and hyperphagia consistently, even in situations without any food stimulation. In the present study, we employed resting-state functional MRI techniques to investigate abnormal brain networks related to eating disorders in children with PWS. First, we applied amplitude of low-frequency fluctuation analysis to define the regions of interest that showed significant alterations in resting-state brain activity levels in patients compared with their sibling control group. We then applied a functional connectivity (FC) analysis to these regions of interest in order to characterize interactions among the brain regions. Our results demonstrated that patients with PWS showed decreased FC strength in the medial prefrontal cortex (MPFC)/inferior parietal lobe (IPL), MPFC/precuneus, IPL/precuneus and IPL/hippocampus in the default mode network; decreased FC strength in the pre-/postcentral gyri and dorsolateral prefrontal cortex (DLPFC)/orbitofrontal cortex (OFC) in the motor sensory network and prefrontal cortex network, respectively; and increased FC strength in the anterior cingulate cortex/insula, ventrolateral prefrontal cortex (VLPFC)/OFC and DLPFC/VLPFC in the core network and prefrontal cortex network, respectively. These findings indicate that there are FC alterations among the brain regions implicated in eating as well as rewarding, even during the resting state, which may provide further evidence supporting the use of PWS as a model to study obesity and to provide information on potential neural targets for the medical treatment of overeating.

  16. Large-Scale Functional Brain Network Reorganization During Taoist Meditation.

    Science.gov (United States)

    Jao, Tun; Li, Chia-Wei; Vértes, Petra E; Wu, Changwei Wesley; Achard, Sophie; Hsieh, Chao-Hsien; Liou, Chien-Hui; Chen, Jyh-Horng; Bullmore, Edward T

    2016-02-01

    Meditation induces a distinct and reversible mental state that provides insights into brain correlates of consciousness. We explored brain network changes related to meditation by graph theoretical analysis of resting-state functional magnetic resonance imaging data. Eighteen Taoist meditators with varying levels of expertise were scanned using a within-subjects counterbalanced design during resting and meditation states. State-related differences in network topology were measured globally and at the level of individual nodes and edges. Although measures of global network topology, such as small-worldness, were unchanged, meditation was characterized by an extensive and expertise-dependent reorganization of the hubs (highly connected nodes) and edges (functional connections). Areas of sensory cortex, especially the bilateral primary visual and auditory cortices, and the bilateral temporopolar areas, which had the highest degree (or connectivity) during the resting state, showed the biggest decrease during meditation. Conversely, bilateral thalamus and components of the default mode network, mainly the bilateral precuneus and posterior cingulate cortex, had low degree in the resting state but increased degree during meditation. Additionally, these changes in nodal degree were accompanied by reorganization of anatomical orientation of the edges. During meditation, long-distance longitudinal (antero-posterior) edges increased proportionally, whereas orthogonal long-distance transverse (right-left) edges connecting bilaterally homologous cortices decreased. Our findings suggest that transient changes in consciousness associated with meditation introduce convergent changes in the topological and spatial properties of brain functional networks, and the anatomical pattern of integration might be as important as the global level of integration when considering the network basis for human consciousness.

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

    Directory of Open Access Journals (Sweden)

    Wei-Che Lin

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

  18. Disrupted Resting-State Default Mode Network in Betel Quid-Dependent Individuals

    Science.gov (United States)

    Zhu, Xueling; Zhu, Qiuling; Jiang, Canhua; Shen, Huaizhen; Wang, Furong; Liao, Weihua; Yuan, Fulai

    2017-01-01

    Recent studies have shown that substance dependence (addiction) is accompanied with altered activity patterns of the default mode network (DMN). However, the neural correlates of the resting-state DMN and betel quid dependence (BQD)-related physiopathological characteristics still remain unclear. Resting-state functional magnetic resonance imaging images were obtained from 26 BQD individuals and 28 matched healthy control subjects. Group independent component analysis was performed to analyze the resting state images into spatially independent components. Gray matter volume was examined as covariate with voxel-based morphometry to rule out its effect on the functional results. The severity of BQD was assessed by the BQD Scale (BQDS). We observed decreased functional connectivity in anterior part of the DMN including ventral medial prefrontal cortex, orbital MPFC (OMPFC)/anterior cingulate cortex (ACC). Furthermore, the functional connectivity within the OMPFC/ACC in BQD individuals was negatively correlated with BQDS (p = 0.01, r = -0.49). We reported decreased functional connectivity within anterior part of the DMN in BQD individuals, which provides new evidence for the role of the DMN in the pathophysiology of BQD. PMID:28194128

  19. Development of deactivation of the default-mode network during episodic memory formation

    Science.gov (United States)

    Chai, Xiaoqian J.; Ofen, Noa; Gabrieli, John D. E.; Whitfield-Gabrieli, Susan

    2014-01-01

    Task-induced deactivation of the default-mode network (DMN) has been associated in adults with successful episodic memory formation, possibly as a mechanism to focus allocation of mental resources for successful encoding of external stimuli. We investigated developmental changes of deactivation of the DMN (posterior cingulate, medial prefrontal, and bilateral lateral parietal cortices) during episodic memory formation in children, adolescents, and young adults (ages 8–24), who studied scenes during functional magnetic resonance imaging (fMRI). Recognition memory improved with age. We defined DMN regions of interest from a different sample of participants with the same age range, using resting-state fMRI. In adults, there was greater deactivation of the DMN for scenes that were later remembered than scenes that were later forgotten. In children, deactivation of the default-network did not differ reliably between scenes that were later remembered or forgotten. Adolescents exhibited a pattern of activation intermediate to that of children and adults. The hippocampal region, often considered part of the DMN, showed a functional dissociation with the rest of the DMN by exhibiting increased activation for later remembered than later forgotten scene that was similar across age groups. These findings suggest that development of memory ability from childhood through adulthood may involve increased deactivation of the neocortical DMN during learning. PMID:24064072

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

    Directory of Open Access Journals (Sweden)

    Felicity eCallard

    2014-08-01

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

  1. Task modulates functional connectivity networks in free viewing behavior.

    Science.gov (United States)

    Seidkhani, Hossein; Nikolaev, Andrey R; Meghanathan, Radha Nila; Pezeshk, Hamid; Masoudi-Nejad, Ali; van Leeuwen, Cees

    2017-08-03

    In free visual exploration, eye-movement is immediately followed by dynamic reconfiguration of brain functional connectivity. We studied the task-dependency of this process in a combined visual search-change detection experiment. Participants viewed two (nearly) same displays in succession. First time they had to find and remember multiple targets among distractors, so the ongoing task involved memory encoding. Second time they had to determine if a target had changed in orientation, so the ongoing task involved memory retrieval. From multichannel EEG recorded during 200 ms intervals time-locked to fixation onsets, we estimated the functional connectivity using a weighted phase lag index at the frequencies of theta, alpha, and beta bands, and derived global and local measures of the functional connectivity graphs. We found differences between both memory task conditions for several network measures, such as mean path length, radius, diameter, closeness and eccentricity, mainly in the alpha band. Both the local and the global measures indicated that encoding involved a more segregated mode of operation than retrieval. These differences arose immediately after fixation onset and persisted for the entire duration of the lambda complex, an evoked potential commonly associated with early visual perception. We concluded that encoding and retrieval differentially shape network configurations involved in early visual perception, affecting the way the visual input is processed at each fixation. These findings demonstrate that task requirements dynamically control the functional connectivity networks involved in early visual perception. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Functional optimization of the arterial network

    CERN Document Server

    Mauroy, Benjamin

    2014-01-01

    We build an evolutionary scenario that explains how some crucial physiological constraints in the arterial network of mammals - i.e. hematocrit, vessels diameters and arterial pressure drops - could have been selected by evolution. We propose that the arterial network evolved while being constrained by its function as an organ. To support this hypothesis, we focus our study on one of the main function of blood network: oxygen supply to the organs. We consider an idealized organ with a given oxygen need and we optimize blood network geometry and hematocrit with the constraint that it must fulfill the organ oxygen need. Our model accounts for the non-Newtonian behavior of blood, its maintenance cost and F\\aa hr\\ae us effects (decrease in average concentration of red blood cells as the vessel diameters decrease). We show that the mean shear rates (relative velocities of fluid layers) in the tree vessels follow a scaling law related to the multi-scale property of the tree network, and we show that this scaling la...

  3. Engineering functionality gradients by dip coating process in acceleration mode.

    Science.gov (United States)

    Faustini, Marco; Ceratti, Davide R; Louis, Benjamin; Boudot, Mickael; Albouy, Pierre-Antoine; Boissière, Cédric; Grosso, David

    2014-10-08

    In this work, unique functional devices exhibiting controlled gradients of properties are fabricated by dip-coating process in acceleration mode. Through this new approach, thin films with "on-demand" thickness graded profiles at the submillimeter scale are prepared in an easy and versatile way, compatible for large-scale production. The technique is adapted to several relevant materials, including sol-gel dense and mesoporous metal oxides, block copolymers, metal-organic framework colloids, and commercial photoresists. In the first part of the Article, an investigation on the effect of the dip coating speed variation on the thickness profiles is reported together with the critical roles played by the evaporation rate and by the viscosity on the fluid draining-induced film formation. In the second part, dip-coating in acceleration mode is used to induce controlled variation of functionalities by playing on structural, chemical, or dimensional variations in nano- and microsystems. In order to demonstrate the full potentiality and versatility of the technique, original graded functional devices are made including optical interferometry mirrors with bidirectional gradients, one-dimensional photonic crystals with a stop-band gradient, graded microfluidic channels, and wetting gradient to induce droplet motion.

  4. Transition mode long period grating biosensor with functional multilayer coatings.

    Science.gov (United States)

    Pilla, Pierluigi; Malachovská, Viera; Borriello, Anna; Buosciolo, Antonietta; Giordano, Michele; Ambrosio, Luigi; Cutolo, Antonello; Cusano, Andrea

    2011-01-17

    We report our latest research results concerning the development of a platform for label-free biosensing based on overlayered Long Period Gratings (LPGs) working in transition mode. The main novelty of this work lies in a multilayer design that allows to decouple the problem of an efficient surface functionalization from that of the tuning in transition region of the cladding modes. An innovative solvent/nonsolvent strategy for the dip-coating technique was developed in order to deposit on the LPG multiple layers of transparent polymers. In particular, a primary coating of atactic polystyrene was used as high refractive index layer to tune the working point of the device in the so-called transition region. In this way, state-of-the-art-competitive sensitivity to surrounding medium refractive index changes was achieved. An extremely thin secondary functional layer of poly(methyl methacrylate-co-methacrylic acid) was deposited onto the primary coating by means of an original identification of selective solvents. This approach allowed to obtain desired functional groups (carboxyls) on the surface of the device for a stable covalent attachment of bioreceptors and minimal perturbation of the optical design. Standard 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide / N-hydrosuccinimide (EDC / NHS) coupling chemistry was used to link streptavidin on the surface of the coated LPG. Highly sensitive real-time monitoring of multiple affinity assays between streptavidin and biotinylated bovine serum albumin was performed by following the shift of the LPGs attenuation bands.

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

    Science.gov (United States)

    Doucet, Gaelle Eve; Skidmore, Christopher; Evans, James; Sharan, Ashwini; Sperling, Michael R; Pustina, Dorian; Tracy, Joseph I

    2014-01-01

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

  6. Exocytosis and endocytosis: modes, functions, and coupling mechanisms.

    Science.gov (United States)

    Wu, Ling-Gang; Hamid, Edaeni; Shin, Wonchul; Chiang, Hsueh-Cheng

    2014-01-01

    Vesicle exocytosis releases content to mediate many biological events, including synaptic transmission essential for brain functions. Following exocytosis, endocytosis is initiated to retrieve exocytosed vesicles within seconds to minutes. Decades of studies in secretory cells reveal three exocytosis modes coupled to three endocytosis modes: (a) full-collapse fusion, in which vesicles collapse into the plasma membrane, followed by classical endocytosis involving membrane invagination and vesicle reformation; (b) kiss-and-run, in which the fusion pore opens and closes; and (c) compound exocytosis, which involves exocytosis of giant vesicles formed via vesicle-vesicle fusion, followed by bulk endocytosis that retrieves giant vesicles. Here we review these exo- and endocytosis modes and their roles in regulating quantal size and synaptic strength, generating synaptic plasticity, maintaining exocytosis, and clearing release sites for vesicle replenishment. Furthermore, we highlight recent progress in understanding how vesicle endocytosis is initiated and is thus coupled to exocytosis. The emerging model is that calcium influx via voltage-dependent calcium channels at the calcium microdomain triggers endocytosis and controls endocytosis rate; calmodulin and synaptotagmin are the calcium sensors; and the exocytosis machinery, including SNARE proteins (synaptobrevin, SNAP25, and syntaxin), is needed to coinitiate endocytosis, likely to control the amount of endocytosis.

  7. Whispering Gallery Mode Resonator with Orthogonally Reconfigurable Filter Function

    Science.gov (United States)

    Maleki, Lute; Matsko, Andrey; Strekalov, Dmitry; Savchenkov, Anatoliy

    2008-01-01

    An optical resonator has been developed with reconfigurable filter function that has resonant lines that can be shifted precisely and independently from each other, creating any desirable combination of resonant lines. This is achieved by changing the axial distribution of the effective refractive index of the resonator, which shifts the resonant frequency of particular optical modes, leaving all the rest unchanged. A reconfigurable optical filter is part of the remote chemical detector proposed for the Mars mission (Planetary Instrument Definition and Development Program PIDDP), but it is also useful for photonic communications devices.

  8. Coarse grained normal mode analysis vs. refined Gaussian Network Model for protein residue-level structural fluctuations.

    Science.gov (United States)

    Park, Jun-Koo; Jernigan, Robert; Wu, Zhijun

    2013-01-01

    We investigate several approaches to coarse grained normal mode analysis on protein residual-level structural fluctuations by choosing different ways of representing the residues and the forces among them. Single-atom representations using the backbone atoms C(α), C, N, and C(β) are considered. Combinations of some of these atoms are also tested. The force constants between the representative atoms are extracted from the Hessian matrix of the energy function and served as the force constants between the corresponding residues. The residue mean-square-fluctuations and their correlations with the experimental B-factors are calculated for a large set of proteins. The results are compared with all-atom normal mode analysis and the residue-level Gaussian Network Model. The coarse-grained methods perform more efficiently than all-atom normal mode analysis, while their B-factor correlations are also higher. Their B-factor correlations are comparable with those estimated by the Gaussian Network Model and in many cases better. The extracted force constants are surveyed for different pairs of residues with different numbers of separation residues in sequence. The statistical averages are used to build a refined Gaussian Network Model, which is able to predict residue-level structural fluctuations significantly better than the conventional Gaussian Network Model in many test cases.

  9. Functional model of biological neural networks.

    Science.gov (United States)

    Lo, James Ting-Ho

    2010-12-01

    A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.

  10. Studying the default mode and its mindfulness-induced changes using EEG functional connectivity

    OpenAIRE

    2013-01-01

    The default mode network (DMN) has been largely studied by imaging, but not yet by neurodynamics, using electroencephalography (EEG) functional connectivity (FC). mindfulness meditation (MM), a receptive, non-elaborative training is theorized to lower DMN activity. We explored: (i) the usefulness of EEG-FC for investigating the DMN and (ii) the MM-induced EEG-FC effects. To this end, three MM groups were compared with controls, employing EEG-FC (–MPC, mean phase coherence). Our results show t...

  11. NEURAL NETWORK MODELING IN PROBLEMS OF PREDICTION MODES OF ELECTRICAL GRIDS

    Directory of Open Access Journals (Sweden)

    A.N. Moroz

    2016-03-01

    Full Text Available Purpose. Form a neuro-fuzzy network based on temperature monitoring of overhead transmission line for the prediction modes of the electrical network. Methodology. To predict the load capacity of the overhead line architecture provides the use of neuro-fuzzy network based on temperature monitoring of overhead line. The proposed neuro-fuzzy network has a four-layer architecture with direct transmission of information. To create a full mesh network architecture based on hybrid neural elements with power estimation accuracy of the following two stages of the procedure: - in the first stage a core network (without power estimation accuracy is generated; - in the second stage architecture and network parameters are fixed obtained during the first stage, and it is added to the block estimation accuracy, the input signals which are all input, internal and output signals of the core network, as well as additional input signals. Results. Formed neuro-fuzzy network based on temperature monitoring of overhead line. Originality. A distinctive feature of the proposed network is the ability to process information specified in the different scales of measurement, and high performance for prediction modes mains. Practical value. The monitoring system will become a tool parameter is measuring the temperature of the wire, which will, based on a retrospective analysis of the accumulated information on the parameters to predict the thermal resistance of the HV line and as a result carry out the calculation of load capacity in real time.

  12. Global network analysis of drug tolerance, mode of action and virulence in methicillin-resistant S. aureus

    Directory of Open Access Journals (Sweden)

    Shirran Sally

    2011-05-01

    Full Text Available Abstract Background Staphylococcus aureus is a major human pathogen and strains resistant to existing treatments continue to emerge. Development of novel treatments is therefore important. Antimicrobial peptides represent a source of potential novel antibiotics to combat resistant bacteria such as Methicillin-Resistant Staphylococcus aureus (MRSA. A promising antimicrobial peptide is ranalexin, which has potent activity against Gram-positive bacteria, and particularly S. aureus. Understanding mode of action is a key component of drug discovery and network biology approaches enable a global, integrated view of microbial physiology, including mechanisms of antibiotic killing. We developed a systems-wide functional association network approach to integrate proteome and transcriptome profiles, enabling study of drug resistance and mode of action. Results The functional association network was constructed by Bayesian logistic regression, providing a framework for identification of antimicrobial peptide (ranalexin response modules from S. aureus MRSA-252 transcriptome and proteome profiling. These signatures of ranalexin treatment revealed multiple killing mechanisms, including cell wall activity. Cell wall effects were supported by gene disruption and osmotic fragility experiments. Furthermore, twenty-two novel virulence factors were inferred, while the VraRS two-component system and PhoU-mediated persister formation were implicated in MRSA tolerance to cationic antimicrobial peptides. Conclusions This work demonstrates a powerful integrative approach to study drug resistance and mode of action. Our findings are informative to the development of novel therapeutic strategies against Staphylococcus aureus and particularly MRSA.

  13. Altered functional and structural connectivity networks in psychogenic non-epileptic seizures.

    Directory of Open Access Journals (Sweden)

    Ju-Rong Ding

    Full Text Available Psychogenic non-epileptic seizures (PNES are paroxysmal behaviors that resemble epileptic seizures but lack abnormal electrical activity. Recent studies suggest aberrant functional connectivity involving specific brain regions in PNES. Little is known, however, about alterations of topological organization of whole-brain functional and structural connectivity networks in PNES. We constructed functional connectivity networks from resting-state functional MRI signal correlations and structural connectivity networks from diffusion tensor imaging tractography in 17 PNES patients and 20 healthy controls. Graph theoretical analysis was employed to compute network properties. Moreover, we investigated the relationship between functional and structural connectivity networks. We found that PNES patients exhibited altered small-worldness in both functional and structural networks and shifted towards a more regular (lattice-like organization, which could serve as a potential imaging biomarker for PNES. In addition, many regional characteristics were altered in structural connectivity network, involving attention, sensorimotor, subcortical and default-mode networks. These regions with altered nodal characteristics likely reflect disease-specific pathophysiology in PNES. Importantly, the coupling strength of functional-structural connectivity was decreased and exhibited high sensitivity and specificity to differentiate PNES patients from healthy controls, suggesting that the decoupling strength of functional-structural connectivity might be an important characteristic reflecting the mechanisms of PNES. This is the first study to explore the altered topological organization in PNES combining functional and structural connectivity networks, providing a new way to understand the pathophysiological mechanisms of PNES.

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

    KAUST Repository

    Ali, Konpal S.

    2015-06-08

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

  15. A novel fairness control mode for Resilient Packet Ring (RPR) network

    Science.gov (United States)

    Yong, Wang; Fu, Songnian; Wu, Chongqing; Zhang, Liren; Shum, P.

    2005-11-01

    Resilient Packet Ring (RPR), defined by the IEEE 802.17 working group, is a new solution to metropolitan area network. RPR adopts the packet-based dual ring structure so that it can provide the protection capability similar to the SDH as well as dynamic bandwidth allocation. The design of fairness control mechanism to allocate the bandwidth is a key problem for RPR. Currently, two different modes of fairness algorithm have been proposed in the RPR standard, the aggressive mode (AM) and the conservative mode (CM). However, there are several limitations for these modes, such as the amount of the bandwidth allocated oscillates permanently under unbalanced traffic scenarios. In this paper, we propose a novel fairness control mode. The simulation experiment shows the range of traffic oscillation controlled by our mode is significantly damped compared to current RPR algorithm.

  16. Effects of model-based physiological noise correction on default mode network anti-correlations and correlations.

    Science.gov (United States)

    Chang, Catie; Glover, Gary H

    2009-10-01

    Previous studies have reported that the spontaneous, resting-state time course of the default-mode network is negatively correlated with that of the "task-positive network", a collection of regions commonly recruited in demanding cognitive tasks. However, all studies of negative correlations between the default-mode and task-positive networks have employed some form of normalization or regression of the whole-brain average signal ("global signal"); these processing steps alter the time series of voxels in an uninterpretable manner as well as introduce spurious negative correlations. Thus, the extent of negative correlations with the default mode network without global signal removal has not been well characterized, and it is has recently been hypothesized that the apparent negative correlations in many of the task-positive regions could be artifactually induced by global signal pre-processing. The present study aimed to examine negative and positive correlations with the default-mode network when model-based corrections for respiratory and cardiac noise are applied in lieu of global signal removal. Physiological noise correction consisted of (1) removal of time-locked cardiac and respiratory artifacts using RETROICOR (Glover, G.H., Li, T.Q., Ress, D., 2000. Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn. Reson. Med. 44, 162-167), and (2) removal of low-frequency respiratory and heart rate variations by convolving these waveforms with pre-determined transfer functions (Birn et al., 2008; Chang et al., 2009) and projecting the resulting two signals out of the data. It is demonstrated that negative correlations between the default-mode network and regions of the task-positive network are present in the majority of individual subjects both with and without physiological noise correction. Physiological noise correction increased the spatial extent and magnitude of negative correlations, yielding negative

  17. Spatiotemporal chaos synchronization of an uncertain network based on sliding mode control

    Institute of Scientific and Technical Information of China (English)

    Lü Ling; Yu Miao; Wei Lin-Ling; Zhang Meng; Li Yu-Shan

    2012-01-01

    The sliding mode control method is used to study spatiotemporal chaos synchronization of an uncertain network.The method is extended from synchronization between two chaotic systems to the synchronization of complex network composed of N spatiotemporal chaotic systems.The sliding surface of the network and the control input are designed.Furthermore,the effectiveness of the method is analysed based on the stability theory. The Burgers equation with spatiotemporal chaos behavior is taken as an example to simulate the experiment.It is found that the synchronization performance of the network is very stable.

  18. Effects of exercise on resting-state default mode and salience network activity in overweight/obese adults.

    Science.gov (United States)

    McFadden, Kristina L; Cornier, Marc-Andre; Melanson, Edward L; Bechtell, Jamie L; Tregellas, Jason R

    2013-10-23

    Despite the common use of exercise as a weight-loss strategy, little is known about its neuronal effects, and how these may be related to cognitive changes that impact food intake. The current study assessed the effects of a 6-month exercise intervention on intrinsic activity in the default mode network (DMN), a functionally connected network of brain regions including posterior cingulate cortex, cuneus/precuneus, medial prefrontal cortex, medial temporal lobe, and inferior parietal cortices, and salience network, which includes the anterior cingulate cortex and insula. Resting-state functional MRI data were acquired in 12 overweight/obese individuals. The intervention was associated with a reduction in DMN activity in the precuneus (P=0.003, family-wise error-corrected), which was associated with greater fat mass loss (P=0.013) as well as reduced perceived hunger (Three Factor Eating Questionnaire, P=0.024) and hunger ratings in response to a meal (P=0.013). No changes were observed in the salience network in response to the exercise intervention. The association between DMN change and both fat mass loss and reduction of hunger ratings suggests that DMN function may be involved in the regulation of food intake behaviors. Given previous reports of DMN overactivity in overweight/obese individuals, the present findings may indicate an exercise-related 'normalization' of network function.

  19. The default mode network and EEG regional spectral power: a simultaneous fMRI-EEG study.

    Science.gov (United States)

    Neuner, Irene; Arrubla, Jorge; Werner, Cornelius J; Hitz, Konrad; Boers, Frank; Kawohl, Wolfram; Shah, N Jon

    2014-01-01

    Electroencephalography (EEG) frequencies have been linked to specific functions as an "electrophysiological signature" of a function. A combination of oscillatory rhythms has also been described for specific functions, with or without predominance of one specific frequency-band. In a simultaneous fMRI-EEG study at 3 T we studied the relationship between the default mode network (DMN) and the power of EEG frequency bands. As a methodological approach, we applied Multivariate Exploratory Linear Optimized Decomposition into Independent Components (MELODIC) and dual regression analysis for fMRI resting state data. EEG power for the alpha, beta, delta and theta-bands were extracted from the structures forming the DMN in a region-of-interest approach by applying Low Resolution Electromagnetic Tomography (LORETA). A strong link between the spontaneous BOLD response of the left parahippocampal gyrus and the delta-band extracted from the anterior cingulate cortex was found. A positive correlation between the beta-1 frequency power extracted from the posterior cingulate cortex (PCC) and the spontaneous BOLD response of the right supplementary motor cortex was also established. The beta-2 frequency power extracted from the PCC and the precuneus showed a positive correlation with the BOLD response of the right frontal cortex. Our results support the notion of beta-band activity governing the "status quo" in cognitive and motor setup. The highly significant correlation found between the delta power within the DMN and the parahippocampal gyrus is in line with the association of delta frequencies with memory processes. We assumed "ongoing activity" during "resting state" in bringing events from the past to the mind, in which the parahippocampal gyrus is a relevant structure. Our data demonstrate that spontaneous BOLD fluctuations within the DMN are associated with different EEG-bands and strengthen the conclusion that this network is characterized by a specific

  20. The default mode network and EEG regional spectral power: a simultaneous fMRI-EEG study.

    Directory of Open Access Journals (Sweden)

    Irene Neuner

    Full Text Available Electroencephalography (EEG frequencies have been linked to specific functions as an "electrophysiological signature" of a function. A combination of oscillatory rhythms has also been described for specific functions, with or without predominance of one specific frequency-band. In a simultaneous fMRI-EEG study at 3 T we studied the relationship between the default mode network (DMN and the power of EEG frequency bands. As a methodological approach, we applied Multivariate Exploratory Linear Optimized Decomposition into Independent Components (MELODIC and dual regression analysis for fMRI resting state data. EEG power for the alpha, beta, delta and theta-bands were extracted from the structures forming the DMN in a region-of-interest approach by applying Low Resolution Electromagnetic Tomography (LORETA. A strong link between the spontaneous BOLD response of the left parahippocampal gyrus and the delta-band extracted from the anterior cingulate cortex was found. A positive correlation between the beta-1 frequency power extracted from the posterior cingulate cortex (PCC and the spontaneous BOLD response of the right supplementary motor cortex was also established. The beta-2 frequency power extracted from the PCC and the precuneus showed a positive correlation with the BOLD response of the right frontal cortex. Our results support the notion of beta-band activity governing the "status quo" in cognitive and motor setup. The highly significant correlation found between the delta power within the DMN and the parahippocampal gyrus is in line with the association of delta frequencies with memory processes. We assumed "ongoing activity" during "resting state" in bringing events from the past to the mind, in which the parahippocampal gyrus is a relevant structure. Our data demonstrate that spontaneous BOLD fluctuations within the DMN are associated with different EEG-bands and strengthen the conclusion that this network is characterized by a specific

  1. Function Analyses of Geographic Information System on Rural Distribution Network

    Institute of Scientific and Technical Information of China (English)

    FANG Junlong; FAN Yongcun; ZHANG Chunmei; GU Shumin

    2006-01-01

    With the actuality and characteristic and requirement of rural power enterprise distribution network management, this article introduced the function of geographic information system on the framework of distribution network, in order to develop rural distribution network.

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

    Science.gov (United States)

    Fei, Juntao; Lu, Cheng

    2017-03-06

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

  3. Dynamic network participation of functional connectivity hubs assessed by resting-state fMRI

    Directory of Open Access Journals (Sweden)

    Alexander eSchaefer

    2014-05-01

    Full Text Available Network studies of large-scale brain connectivity have demonstrated that highly connected areas, or ‘hubs’, are a key feature of human functional and structural brain organization. We use resting-state functional MRI data and connectivity clustering to identify multi network hubs and show that while hubs can belong to multiple networks their degree of integration into these different networks varies dynamically over time. In addition, we found that these network dynamics were inversely related to positive self-generated thoughts reported by individuals and were further decreased with older age. Moreover, the left caudate varied its degree of participation between a default mode subnetwork and a limbic network. This variation was predictive of individual differences in the reports of past-related thoughts. These results support an association between ongoing thought processes and network dynamics and offer a new approach to investigate the brain dynamics underlying mental experience.

  4. Encoding and retrieval along the long axis of the hippocampus and their relationships with dorsal attention and default mode networks: The HERNET model.

    Science.gov (United States)

    Kim, Hongkeun

    2015-04-01

    The encoding of sensory input is intertwined with external attention, whereas retrieval is intrinsically related to internal attention. This study proposes a model in which the encoding of sensory input involves mainly the anterior hippocampus and the external attention network, whereas retrieval, the posterior hippocampus and the internal attention network. This model is referred to as the HERNET (hippocampal encoding/retrieval and network) model. Functional neuroimaging studies have identified two intrinsic large-scale networks closely associated with external and internal attention, respectively. The dorsal attention network activates during any externally oriented mental activity, whereas the default mode network shows increased activity during internally oriented mental activity. Therefore, the HERNET model may predict the activation of the anterior hippocampus and the dorsal attention network during the encoding and activation of the posterior hippocampus and the default mode network during retrieval. To test this prediction, this study provides a meta-analysis of three memory-imaging paradigms: subsequent memory, laboratory-based recollection, and autobiographical memory retrieval. The meta-analysis included 167 individual studies and 2,856 participants. The results provide support for the HERNET model and suggest that the anterior-posterior gradient of encoding and retrieval includes amygdala regions. More broadly, humans continuously oscillate between external and internal attention and thus between encoding and retrieval processes. These oscillations may involve repetitive and spontaneous activity switching between the anterior hippocampus/dorsal attention network and the posterior hippocampus/default mode network.

  5. Arithmetic functions in torus and tree networks

    Science.gov (United States)

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

    2007-12-25

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

  6. Two different modes of oscillation in a gene transcription regulatory network with interlinked positive and negative feedback loops

    Science.gov (United States)

    Karmakar, Rajesh

    2016-12-01

    We study the oscillatory behavior of a gene regulatory network with interlinked positive and negative feedback loop. The frequency and amplitude are two important properties of oscillation. The studied network produces two different modes of oscillation. In one mode (mode-I), frequency of oscillation remains constant over a wide range of amplitude and in the other mode (mode-II) the amplitude of oscillation remains constant over a wide range of frequency. Our study reproduces both features of oscillations in a single gene regulatory network and shows that the negative plus positive feedback loops in gene regulatory network offer additional advantage. We identified the key parameters/variables responsible for different modes of oscillation. The network is flexible in switching between different modes by choosing appropriately the required parameters/variables.

  7. Single mode phonon energy transmission in functionalized carbon nanotubes.

    Science.gov (United States)

    Lee, Jonghoon; Varshney, Vikas; Roy, Ajit K; Farmer, Barry L

    2011-09-14

    Although the carbon nanotube (CNT) features superior thermal properties in its pristine form, the chemical functionalization often required for many applications of CNT inevitably degrades the structural integrity and affects the transport of energy carriers. In this article, the effect of the side wall functionalization on the phonon energy transmission along the symmetry axis of CNT is studied using the phonon wave packet method. Three different functional groups are studied: methyl (-CH(3)), vinyl (-C(2)H(3)), and carboxyl (-COOH). We find that, near Γ point of the Brillouin zone, acoustic phonons show ideal transmission, while the transmission of the optical phonons is strongly suppressed. A positive correlation between the energy transmission coefficient and the phonon group velocity is observed for both acoustic and optical phonon modes. On comparing the transmission due to functional groups with equivalent point mass defects on CNT, we find that the chemistry of the functional group, rather than its molecular mass, has a dominant role in determining phonon scattering, hence the transmission, at the defect sites.

  8. Diagnostic classification of intrinsic functional connectivity highlights somatosensory, default mode, and visual regions in autism.

    Science.gov (United States)

    Chen, Colleen P; Keown, Christopher L; Jahedi, Afrooz; Nair, Aarti; Pflieger, Mark E; Bailey, Barbara A; Müller, Ralph-Axel

    2015-01-01

    Despite consensus on the neurological nature of autism spectrum disorders (ASD), brain biomarkers remain unknown and diagnosis continues to be based on behavioral criteria. Growing evidence suggests that brain abnormalities in ASD occur at the level of interconnected networks; however, previous attempts using functional connectivity data for diagnostic classification have reached only moderate accuracy. We selected 252 low-motion resting-state functional MRI (rs-fMRI) scans from the Autism Brain Imaging Data Exchange (ABIDE) including typically developing (TD) and ASD participants (n = 126 each), matched for age, non-verbal IQ, and head motion. A matrix of functional connectivities between 220 functionally defined regions of interest was used for diagnostic classification, implementing several machine learning tools. While support vector machines in combination with particle swarm optimization and recursive feature elimination performed modestly (with accuracies for validation datasets ensemble learning method. Among the 100 most informative features (connectivities), for which this peak accuracy was achieved, participation of somatosensory, default mode, visual, and subcortical regions stood out. Whereas some of these findings were expected, given previous findings of default mode abnormalities and atypical visual functioning in ASD, the prominent role of somatosensory regions was remarkable. The finding of peak accuracy for 100 interregional functional connectivities further suggests that brain biomarkers of ASD may be regionally complex and distributed, rather than localized.

  9. Diagnostic classification of intrinsic functional connectivity highlights somatosensory, default mode, and visual regions in autism

    Directory of Open Access Journals (Sweden)

    Colleen P. Chen

    2015-01-01

    Full Text Available Despite consensus on the neurological nature of autism spectrum disorders (ASD, brain biomarkers remain unknown and diagnosis continues to be based on behavioral criteria. Growing evidence suggests that brain abnormalities in ASD occur at the level of interconnected networks; however, previous attempts using functional connectivity data for diagnostic classification have reached only moderate accuracy. We selected 252 low-motion resting-state functional MRI (rs-fMRI scans from the Autism Brain Imaging Data Exchange (ABIDE including typically developing (TD and ASD participants (n = 126 each, matched for age, non-verbal IQ, and head motion. A matrix of functional connectivities between 220 functionally defined regions of interest was used for diagnostic classification, implementing several machine learning tools. While support vector machines in combination with particle swarm optimization and recursive feature elimination performed modestly (with accuracies for validation datasets <70%, diagnostic classification reached a high accuracy of 91% with random forest (RF, a nonparametric ensemble learning method. Among the 100 most informative features (connectivities, for which this peak accuracy was achieved, participation of somatosensory, default mode, visual, and subcortical regions stood out. Whereas some of these findings were expected, given previous findings of default mode abnormalities and atypical visual functioning in ASD, the prominent role of somatosensory regions was remarkable. The finding of peak accuracy for 100 interregional functional connectivities further suggests that brain biomarkers of ASD may be regionally complex and distributed, rather than localized.

  10. 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.

  11. A Clustering Ensemble approach based on the similarities in 2-mode social networks

    Institute of Scientific and Technical Information of China (English)

    SU Bao-ping; ZHANG Meng-jie

    2014-01-01

    For a particular clustering problems, selecting the best clustering method is a challenging problem.Research suggests that integrate the multiple clustering can improve the accuracy of clustering ensemble greatly. A new clustering ensemble approach based on the similarities in 2-mode networks is proposed in this paper. First of all, the data object and the initial clustering clusters transform into 2-mode networks, then using the similarities in 2-mode networks to calculate the similarity between different clusters iteratively to refine the adjacency matrix , K-means algorithm is finally used to get the final clustering, then obtain the final clustering results.The method effectively use the similarity between different clusters, example shows the feasibility of this method.

  12. TDMA-based dual-mode communication for mobile wireless sensor networks.

    Science.gov (United States)

    Mehta, Ankur; Kerkez, Branko; Glaser, Steven D; Pister, Kristofer S J

    2012-11-22

    Small highly mobile robots, and in particular micro air vehicles (MAVs), are well suited to the task of exploring unknown indoor environments such as buildings and caves. Such a task imposes a number of requirements on the underlying communication infrastructure, with differing goals during various stages of the mission. This work addresses those requirements with a hybrid communications infrastructure consisting of a stationary mesh network along with the mobile nodes. The combined network operates in two independent modes, coupling a highly efficient, low duty cycle, low throughput mode for routing and persistent sensing with a burst mode for high data rate communication. By strategically distributing available frequency channels between the mobile agents and the stationary nodes, the overall network provides reliable long-term communication paths while maximizing data throughput when needed.

  13. TDMA-Based Dual-Mode Communication for Mobile Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ankur Mehta

    2012-11-01

    Full Text Available Small highly mobile robots, and in particular micro air vehicles (MAVs, are well suited to the task of exploring unknown indoor environments such as buildings and caves. Such a task imposes a number of requirements on the underlying communication infrastructure, with differing goals during various stages of the mission. This work addresses those requirements with a hybrid communications infrastructure consisting of a stationary mesh network along with the mobile nodes. The combined network operates in two independent modes, coupling a highly efficient, low duty cycle, low throughput mode for routing and persistent sensing with a burst mode for high data rate communication. By strategically distributing available frequency channels between the mobile agents and the stationary nodes, the overall network provides reliable long-term communication paths while maximizing data throughput when needed.

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

    Directory of Open Access Journals (Sweden)

    Gaelle Eve Doucet

    2014-03-01

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

  15. Coded Network Function Virtualization: Fault Tolerance via In-Network Coding

    DEFF Research Database (Denmark)

    Al-Shuwaili, A.; Simone, O.; Kliewer, J.

    2016-01-01

    Network function virtualization (NFV) prescribes the instantiation of network functions on general-purpose network devices, such as servers and switches. While yielding a more flexible and cost-effective network architecture, NFV is potentially limited by the fact that commercial off-the-shelf ha......Network function virtualization (NFV) prescribes the instantiation of network functions on general-purpose network devices, such as servers and switches. While yielding a more flexible and cost-effective network architecture, NFV is potentially limited by the fact that commercial off...

  16. Empirical mode decomposition and neural networks on FPGA for fault diagnosis in induction motors.

    Science.gov (United States)

    Camarena-Martinez, David; Valtierra-Rodriguez, Martin; Garcia-Perez, Arturo; Osornio-Rios, Roque Alfredo; Romero-Troncoso, Rene de Jesus

    2014-01-01

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

  17. Decreased default-mode network homogeneity in unaffected siblings of schizophrenia patients at rest.

    Science.gov (United States)

    Guo, Wenbin; Liu, Feng; Yao, Dapeng; Jiang, Jiajing; Su, Qinji; Zhang, Zhikun; Zhang, Jian; Yu, Liuyu; Zhai, Jinguo; Xiao, Changqing

    2014-12-30

    The dysconnectivity hypothesis proposes that abnormal resting state connectivity within the default-mode network (DMN) plays a key role in schizophrenia. Little is known, however, about alterations of the network homogeneity (NH) of the DMN in unaffected siblings of patients with schizophrenia. Unaffected siblings have unique advantages as subjects of neuroimaging studies independent of the clinical and treatment issues that complicate studies of the patients themselves. In the present study, we investigated NH of the DMN in unaffected siblings of schizophrenia. Participants comprised 46 unaffected siblings of schizophrenia patients and 50 age-, sex-, and education-matched healthy controls who underwent resting state functional magnetic resonance imaging (fMRI). Automated NH and group independent component analysis (ICA) approaches were used to analyze the data. Compared with healthy controls, the unaffected siblings of schizophrenia patients showed decreased DMN homogeneity in the left precuneus. No significantly increased DMN homogeneity was found in the sibling group relative to the control group. Our results suggest that there is decreased NH of the DMN in unaffected siblings of schizophrenia patients and indicate that the alternative perspective of examining the DMN NH in patients׳ siblings may improve understanding of the nature of schizophrenia.

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

    Directory of Open Access Journals (Sweden)

    David Camarena-Martinez

    2014-01-01

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

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

    Science.gov (United States)

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

    2015-11-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Fernanda Palhano-Fontes

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

  2. Discrete-Time Sliding Mode Control for Uncertain Networked System Subject to Time Delay

    Directory of Open Access Journals (Sweden)

    Saulo C. Garcia

    2015-01-01

    Full Text Available We deal with uncertain systems with networked sliding mode control, subject to time delay. To minimize the degenerative effects of the time delay, a simpler format of state predictor is proposed in the control law. Some ultimate bounded stability analyses and stabilization conditions are provided for the uncertain time delay system with proposed discrete-time sliding mode control strategy. A numerical example is presented to corroborate the analyses.

  3. 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.

  4. Synchronous activation within the default mode network correlates with perceived social support.

    Science.gov (United States)

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

    2014-10-01

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

  5. A Squeezed Artificial Neural Network for the Symbolic Network Reliability Functions of Binary-State Networks.

    Science.gov (United States)

    Yeh, Wei-Chang

    2016-08-18

    Network reliability is an important index to the provision of useful information for decision support in the modern world. There is always a need to calculate symbolic network reliability functions (SNRFs) due to dynamic and rapid changes in network parameters. In this brief, the proposed squeezed artificial neural network (SqANN) approach uses the Monte Carlo simulation to estimate the corresponding reliability of a given designed matrix from the Box-Behnken design, and then the Taguchi method is implemented to find the appropriate number of neurons and activation functions of the hidden layer and the output layer in ANN to evaluate SNRFs. According to the experimental results of the benchmark networks, the comparison appears to support the superiority of the proposed SqANN method over the traditional ANN-based approach with at least 16.6% improvement in the median absolute deviation in the cost of extra 2 s on average for all experiments.

  6. Terminal Sliding Mode-Based Consensus Tracking Control for Networked Uncertain Mechanical Systems on Digraphs.

    Science.gov (United States)

    Chen, Gang; Song, Yongduan; Guan, Yanfeng

    2016-12-29

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

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

    Science.gov (United States)

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

    2012-12-10

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

  8. Supporting IP dense mode multicast routing protocols in WDM all-optical networks

    Science.gov (United States)

    Salvador, Marcos R.; Heemstra de Groot, Sonia; Dey, Diptish

    2000-09-01

    Recent developments in all-optical networking and wavelength division multiplexing technologies allow for the support of optical multicasting, a missing feature towards the optical Internet. In this paper we propose a protocol to construct source-rooted WDM multicast trees. The protocol works under dense mode multicasting routing IP protocols and supports network nodes with different degrees of light splitting, wavelength conversion, and add/drop capabilities.

  9. Advanced Functionalities for Highly Reliable Optical Networks

    DEFF Research Database (Denmark)

    An, Yi

    This thesis covers two research topics concerning optical solutions for networks e.g. avionic systems. One is to identify the applications for silicon photonic devices for cost-effective solutions in short-range optical networks. The other one is to realise advanced functionalities in order to in......) using two exclusive OR (XOR) gates realised by four-wave mixing (FWM) in semiconductor optical amplifiers (SOAs) is experimentally demonstrated and very low (~ 1 dB) total operation penalty is achieved....... to increase the availability of highly reliable optical networks. A cost-effective transmitter based on a directly modulated laser (DML) using a silicon micro-ring resonator (MRR) to enhance its modulation speed is proposed, analysed and experimentally demonstrated. A modulation speed enhancement from 10 Gbit...... interconnects and network-on-chips. A novel concept of all-optical protection switching scheme is proposed, where fault detection and protection trigger are all implemented in the optical domain. This scheme can provide ultra-fast establishment of the protection path resulting in a minimum loss of data...

  10. Pairing Nambu-Goldstone modes within nuclear density functional theory

    CERN Document Server

    Hinohara, Nobuo

    2016-01-01

    We show that the Nambu-Goldstone formalism of the broken gauge symmetry in the presence of the $T=1$ pairing condensate offers a quantitative description of the binding energy differences of open-shell superfluid nuclei. We conclude that the pairing rotational moments of inertia are excellent pairing indicators, which are free from ambiguities attributed to odd-mass systems. We offer a new, unified interpretation of the binding-energy differences traditionally viewed in the shell model picture as signatures of the valence nucleon properties. We present the first systematic analysis of the off-diagonal pairing rotational moments of inertia, and demonstrate the mixing of the neutron and proton pairing rotational modes in the ground states of even-even nuclei. Finally, we discuss the importance of mass measurements of neutron-rich nuclei for constraining the pairing energy density functional.

  11. Relationship between the anterior forebrain mesocircuit and the default mode network in the structural bases of disorders of consciousness

    Directory of Open Access Journals (Sweden)

    Nicholas D. Lant

    2016-01-01

    Full Text Available The specific neural bases of disorders of consciousness (DOC are still not well understood. Some studies have suggested that functional and structural impairments in the default mode network may play a role in explaining these disorders. In contrast, others have proposed that dysfunctions in the anterior forebrain mesocircuit involving striatum, globus pallidus, and thalamus may be the main underlying mechanism. Here, we provide the first report of structural integrity of fiber tracts connecting the nodes of the mesocircuit and the default mode network in 8 patients with DOC. We found evidence of significant damage to subcortico-cortical and cortico-cortical fibers, which were more severe in vegetative state patients and correlated with clinical severity as determined by Coma Recovery Scale—Revised (CRS-R scores. In contrast, fiber tracts interconnecting subcortical nodes were not significantly impaired. Lastly, we found significant damage in all fiber tracts connecting the precuneus with cortical and subcortical areas. Our results suggest a strong relationship between the default mode network – and most importantly the precuneus – and the anterior forebrain mesocircuit in the neural basis of the DOC.

  12. Complex network perspective on structure and function of Staphylococcus aureus metabolic network

    Indian Academy of Sciences (India)

    L Ying; D W Ding

    2013-02-01

    With remarkable advances in reconstruction of genome-scale metabolic networks, uncovering complex network structure and function from these networks is becoming one of the most important topics in system biology. This work aims at studying the structure and function of Staphylococcus aureus (S. aureus) metabolic network by complex network methods. We first generated a metabolite graph from the recently reconstructed high-quality S. aureus metabolic network model. Then, based on `bow tie' structure character, we explain and discuss the global structure of S. aureus metabolic network. The functional significance, global structural properties, modularity and centrality analysis of giant strong component in S. aureus metabolic networks are studied.

  13. Allocating resources between network nodes for providing a network node function

    NARCIS (Netherlands)

    Strijkers, R.J.; Meulenhoff, P.J.

    2014-01-01

    The invention provides a method wherein a first network node advertises available resources that a second network node may use to offload network node functions transparently to the first network node. Examples of the first network node are a client device (e.g. PC, notebook, tablet, smart phone), a

  14. Implementing the sine transform of fermionic modes as a tensor network

    Science.gov (United States)

    Epple, Hannes; Fries, Pascal; Hinrichsen, Haye

    2017-09-01

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

  15. The role of the default mode network in component processes underlying the wandering mind.

    Science.gov (United States)

    Poerio, Giulia L; Sormaz, Mladen; Wang, Hao-Ting; Margulies, Daniel; Jefferies, Elizabeth; Smallwood, Jonathan

    2017-03-21

    Experiences such as mind-wandering illustrate that cognition is not always tethered to events in the here-and-now. Although converging evidence emphasises the default mode network (DMN) in mind-wandering, its precise contribution remains unclear. The DMN comprises cortical regions that are maximally distant from primary sensory and motor cortex, a topological location that may support the stimulus-independence of mind-wandering. The DMN is functionally heterogeneous, comprising regions engaged by memory, social cognition, and planning; processes relevant to mind-wandering content. Our study examined the relationships between: (i) individual differences in resting-state DMN connectivity, (ii) performance on memory, social, and planning tasks and (iii) variability in spontaneous thought, to investigate whether the DMN is critical to mind-wandering because it supports stimulus-independent cognition, memory retrieval, or both. Individual variation in task performance modulated the functional organisation of the DMN: poor external engagement was linked to stronger coupling between medial and dorsal subsystems, while decoupling of the core from the cerebellum predicted reports of detailed memory retrieval. Both patterns predicted off-task future thoughts. Consistent with predictions from component process accounts of mind-wandering, our study suggests a two-fold involvement of the DMN: (i) it supports experiences that are unrelated to the environment through strong coupling between its sub-systems; (ii) it allows memory representations to form the basis of conscious experience. © The Author (2017). Published by Oxford University Press.

  16. Serotonergic modulation of resting state default mode network connectivity in healthy women.

    Science.gov (United States)

    Helmbold, K; Zvyagintsev, M; Dahmen, B; Biskup, C S; Bubenzer-Busch, S; Gaber, T J; Klasen, M; Eisert, A; Konrad, K; Habel, U; Herpertz-Dahlmann, B; Zepf, F D

    2016-04-01

    The default mode network (DMN) plays a central role in intrinsic thought processes. Altered DMN connectivity has been linked to diminished cerebral serotonin synthesis. Diminished brain serotonin synthesis is further associated with a lack of impulse control and various psychiatric disorders. Here, we investigated the serotonergic modulation of intrinsic functional connectivity (FC) within the DMN in healthy adult females, controlling for the menstrual cycle phase. Eighteen healthy women in the follicular phase (aged 20-31 years) participated in a double-blind controlled cross-over study of serotonin depletion. Acute tryptophan depletion (ATD) and a balanced amino acid load (BAL), used as the control condition, were applied on two separate days of assessment. Neural resting state data using functional magnetic resonance imaging (fMRI) and individual trait impulsivity scores were obtained. ATD compared with BAL significantly reduced FC with the DMN in the precuneus (associated with self-referential thinking) and enhanced FC with the DMN in the frontal cortex (associated with cognitive reasoning). Connectivity differences with the DMN between BAL and ATD in the precentral gyrus were significantly correlated with the magnitude of serotonin depletion. Right medial frontal gyrus and left superior frontal gyrus connectivity differences with the DMN were inversely correlated with trait impulsivity. These findings partially deviate from previous findings obtained in males and underline the importance of gender-specific studies and controlling for menstrual cycle to further elucidate the mechanism of ATD-induced changes within intrinsic thought processes.

  17. Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging.

    Science.gov (United States)

    Robinson, Jennifer L; Baxi, Madhura; Katz, Jeffrey S; Waggoner, Paul; Beyers, Ronald; Morrison, Edward; Salibi, Nouha; Denney, Thomas S; Vodyanoy, Vitaly; Deshpande, Gopikrishna

    2016-11-25

    Diffusion tensor imaging (DTI) provides us an insight into the micro-architecture of white-matter tracts in the brain. This method has proved promising in understanding and investigating the neuronal tracts and structural connectivity between the brain regions in primates as well as rodents. The close evolutionary relationship between canines and humans may have spawned a unique bond in regard to social cognition rendering them useful as an animal model in translational research. In this study, we acquired diffusion data from anaesthetized dogs and created a DTI-based atlas for a canine model which could be used to investigate various white matter diseases. We illustrate the application of this atlas by calculating DTI tractography based structural connectivity between the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) regions of the default mode network (DMN) in dogs. White matter connectivity was investigated to provide structural basis for the functional dissociation observed between the anterior and posterior parts of DMN. A comparison of the integrity of long range structural connections (such as in the DMN) between dogs and humans is likely to provide us with new perspectives on the neural basis of the evolution of cognitive functions.

  18. Dynamics of learning near singularities in radial basis function networks.

    Science.gov (United States)

    Wei, Haikun; Amari, Shun-Ichi

    2008-09-01

    The radial basis function (RBF) networks are one of the most widely used models for function approximation in the regression problem. In the learning paradigm, the best approximation is recursively or iteratively searched for based on observed data (teacher signals). One encounters difficulties in such a process when two component basis functions become identical, or when the magnitude of one component becomes null. In this case, the number of the components reduces by one, and then the reduced component recovers as the learning process proceeds further, provided such a component is necessary for the best approximation. Strange behaviors, especially the plateau phenomena, have been observed in dynamics of learning when such reduction occurs. There exist singularities in the space of parameters, and the above reduction takes place at the singular regions. This paper focuses on a detailed analysis of the dynamical behaviors of learning near the overlap and elimination singularities in RBF networks, based on the averaged learning equation that is applicable to both on-line and batch mode learning. We analyze the stability on the overlap singularity by solving the eigenvalues of the Hessian explicitly. Based on the stability analysis, we plot the analytical dynamic vector fields near the singularity, which are then compared to those real trajectories obtained by a numeric method. We also confirm the existence of the plateaus in both batch and on-line learning by simulation.

  19. Realistic Energy Saving Potential of Sleep Mode for Existing and Future Mobile Networks

    DEFF Research Database (Denmark)

    Micallef, Gilbert; Saker, Louai; Elayoubi, Salah Eddine

    2012-01-01

    going through a number of different alternatives of the feature, this is applied to different network topologies, macro-only based networks, and a set of heterogeneous networks that employ the use of small cells in traffic hotspots. Results obtained through detailed case studies show that sleep mode can......This paper presents an extensive overview on an energy saving feature referred to as ‘site sleep mode’, designed for existing and future mobile broadband networks. In addition to providing a detailed understanding of the main concept, the paper also provides various studies and results to highlight...... reduce the average daily energy consumption of a network by around 30%. This can be achieved while maintaining a predefined level of performance, used as a measure of comparing different scenarios....

  20. Realistic Energy Saving Potential of Sleep Mode for Existing and Future Mobile Networks

    DEFF Research Database (Denmark)

    Micallef, Gilbert; Saker, Louai; Elayoubi, Salah Eddine;

    2012-01-01

    This paper presents an extensive overview on an energy saving feature referred to as ‘site sleep mode’, designed for existing and future mobile broadband networks. In addition to providing a detailed understanding of the main concept, the paper also provides various studies and results to highlight...... going through a number of different alternatives of the feature, this is applied to different network topologies, macro-only based networks, and a set of heterogeneous networks that employ the use of small cells in traffic hotspots. Results obtained through detailed case studies show that sleep mode can...... reduce the average daily energy consumption of a network by around 30%. This can be achieved while maintaining a predefined level of performance, used as a measure of comparing different scenarios....

  1. Density functional and neural network analysis

    DEFF Research Database (Denmark)

    Jalkanen, K. J.; Bohr, Henrik

    1997-01-01

    Density functional theory (DFT) calculations have been carried out for hydrated L-alanine, L-alanyl-L-alanine and N-acetyl L-alanine N'-methylamide and examined with respect to the effect of water on the structure, the vibrational frequencies, vibrational absorption (VA) and vibrational circular...... dichroism (VCD) intensities. The large changes due to hydration on the structures, relative stability of conformers, and in the VA and VCD spectra observed experimentally are reproduced by the DFT calculations. Furthermore a neural network was constructed for reproducing the inverse scattering data (infer...

  2. Modulation of the default-mode network and the attentional network by self-referential processes in patients with disorder of consciousness.

    Science.gov (United States)

    Mäki-Marttunen, Verónica; Castro, Mariana; Olmos, Lisandro; Leiguarda, Ramón; Villarreal, Mirta

    2016-02-01

    Disorders of consciousness (DOC) are related to an altered capacity of the brain to successfully integrate and segregate information. Alterations in brain functional networks structure have been found in fMRI studies, which could account for the incapability of the brain to efficiently manage internally and externally generated information. Here we assess the modulation of neural activity in areas of the networks related to active introspective or extrospective processing in 9 patients with DOC and 17 controls using fMRI. In addition, we assess the functional connectivity between those areas in resting state. Patients were experimentally studied in an early phase after the event of brain injury (3±1 months after the event) and subsequently in a second session 4±1 months after the first session. The results showed that the concerted modulation of the default mode network (DMN) and attentional network (AN) in response to the active involvement in the task improved with the level of consciousness, reflecting an integral recovery of the brain in its ability to be engaged in cognitive processes. In addition, functional connectivity decreased between the DMN and AN with recovery. Our results help to further understand the neural underpins of the disorders of consciousness.

  3. Contribution of hidden modes to nonlinear epidemic dynamics in urban human proximity networks

    CERN Document Server

    Fujiwara, Naoya; Iwayama, Koji; Aihara, Kazuyuki

    2015-01-01

    Recently developed techniques to acquire high-quality human mobility data allow large-scale simulations of the spread of infectious diseases with high spatial and temporal resolution.Analysis of such data has revealed the oversimplification of existing theoretical frameworks to infer the final epidemic size or influential nodes from the network topology. Here we propose a spectral decomposition-based framework for the quantitative analysis of epidemic processes on realistic networks of human proximity derived from urban mobility data. Common wisdom suggests that modes with larger eigenvalues contribute more to the epidemic dynamics. However, we show that hidden dominant structures, namely modes with smaller eigenvalues but a greater contribution to the epidemic dynamics, exist in the proximity network. This framework provides a basic understanding of the relationship between urban human motion and epidemic dynamics, and will contribute to strategic mitigation policy decisions.

  4. Modes of interaction between individuals dominate the topologies of real world networks.

    Directory of Open Access Journals (Sweden)

    Insuk Lee

    Full Text Available We find that the topologies of real world networks, such as those formed within human societies, by the Internet, or among cellular proteins, are dominated by the mode of the interactions considered among the individuals. Specifically, a major dichotomy in previously studied networks arises from modeling networks in terms of pairwise versus group tasks. The former often intrinsically give rise to scale-free, disassortative, hierarchical networks, whereas the latter often give rise to single- or broad-scale, assortative, nonhierarchical networks. These dependencies explain contrasting observations among previous topological analyses of real world complex systems. We also observe this trend in systems with natural hierarchies, in which alternate representations of the same networks, but which capture different levels of the hierarchy, manifest these signature topological differences. For example, in both the Internet and cellular proteomes, networks of lower-level system components (routers within domains or proteins within biological processes are assortative and nonhierarchical, whereas networks of upper-level system components (internet domains or biological processes are disassortative and hierarchical. Our results demonstrate that network topologies of complex systems must be interpreted in light of their hierarchical natures and interaction types.

  5. Modes of interaction between individuals dominate the topologies of real world networks.

    Science.gov (United States)

    Lee, Insuk; Kim, Eiru; Marcotte, Edward M

    2015-01-01

    We find that the topologies of real world networks, such as those formed within human societies, by the Internet, or among cellular proteins, are dominated by the mode of the interactions considered among the individuals. Specifically, a major dichotomy in previously studied networks arises from modeling networks in terms of pairwise versus group tasks. The former often intrinsically give rise to scale-free, disassortative, hierarchical networks, whereas the latter often give rise to single- or broad-scale, assortative, nonhierarchical networks. These dependencies explain contrasting observations among previous topological analyses of real world complex systems. We also observe this trend in systems with natural hierarchies, in which alternate representations of the same networks, but which capture different levels of the hierarchy, manifest these signature topological differences. For example, in both the Internet and cellular proteomes, networks of lower-level system components (routers within domains or proteins within biological processes) are assortative and nonhierarchical, whereas networks of upper-level system components (internet domains or biological processes) are disassortative and hierarchical. Our results demonstrate that network topologies of complex systems must be interpreted in light of their hierarchical natures and interaction types.

  6. Network physiology reveals relations between network topology and physiological function

    OpenAIRE

    Bashan, Amir; Bartsch, Ronny P.; Kantelhardt, Jan W.; Havlin, Shlomo; Ivanov, Plamen Ch.

    2012-01-01

    The human organism is an integrated network where complex physiological systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown of the entire network. Identifying and quantifying dynamical networks of diverse systems with different types of interactions is a challenge. Here we develop a framework to probe interactions among diverse systems, and we identify a physiological network. We find that each physiological state is...

  7. Computer network defense through radial wave functions

    Science.gov (United States)

    Malloy, Ian J.

    The purpose of this research is to synthesize basic and fundamental findings in quantum computing, as applied to the attack and defense of conventional computer networks. The concept focuses on uses of radio waves as a shield for, and attack against traditional computers. A logic bomb is analogous to a landmine in a computer network, and if one was to implement it as non-trivial mitigation, it will aid computer network defense. As has been seen in kinetic warfare, the use of landmines has been devastating to geopolitical regions in that they are severely difficult for a civilian to avoid triggering given the unknown position of a landmine. Thus, the importance of understanding a logic bomb is relevant and has corollaries to quantum mechanics as well. The research synthesizes quantum logic phase shifts in certain respects using the Dynamic Data Exchange protocol in software written for this work, as well as a C-NOT gate applied to a virtual quantum circuit environment by implementing a Quantum Fourier Transform. The research focus applies the principles of coherence and entanglement from quantum physics, the concept of expert systems in artificial intelligence, principles of prime number based cryptography with trapdoor functions, and modeling radio wave propagation against an event from unknown parameters. This comes as a program relying on the artificial intelligence concept of an expert system in conjunction with trigger events for a trapdoor function relying on infinite recursion, as well as system mechanics for elliptic curve cryptography along orbital angular momenta. Here trapdoor both denotes the form of cipher, as well as the implied relationship to logic bombs.

  8. Modeling dynamic functional information flows on large-scale brain networks.

    Science.gov (United States)

    Lv, Peili; Guo, Lei; Hu, Xintao; Li, Xiang; Jin, Changfeng; Han, Junwei; Li, Lingjiang; Liu, Tianming

    2013-01-01

    Growing evidence from the functional neuroimaging field suggests that human brain functions are realized via dynamic functional interactions on large-scale structural networks. Even in resting state, functional brain networks exhibit remarkable temporal dynamics. However, it has been rarely explored to computationally model such dynamic functional information flows on large-scale brain networks. In this paper, we present a novel computational framework to explore this problem using multimodal resting state fMRI (R-fMRI) and diffusion tensor imaging (DTI) data. Basically, recent literature reports including our own studies have demonstrated that the resting state brain networks dynamically undergo a set of distinct brain states. Within each quasi-stable state, functional information flows from one set of structural brain nodes to other sets of nodes, which is analogous to the message package routing on the Internet from the source node to the destination. Therefore, based on the large-scale structural brain networks constructed from DTI data, we employ a dynamic programming strategy to infer functional information transition routines on structural networks, based on which hub routers that most frequently participate in these routines are identified. It is interesting that a majority of those hub routers are located within the default mode network (DMN), revealing a possible mechanism of the critical functional hub roles played by the DMN in resting state. Also, application of this framework on a post trauma stress disorder (PTSD) dataset demonstrated interesting difference in hub router distributions between PTSD patients and healthy controls.

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

    Science.gov (United States)

    Etxaniz, Josu; Aranguren, Gerardo

    2017-04-30

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

  10. Default Mode Network Connectivity Encodes Clinical Pain: An Arterial Spin Labeling Study

    Science.gov (United States)

    Loggia, Marco L.; Kim, Jieun; Gollub, Randy L.; Vangel, Mark G.; Kirsch, Irving; Kong, Jian; Wasan, Ajay D.; Napadow, Vitaly

    2012-01-01

    Neuroimaging studies have suggested the presence of alterations in the anatomo-functional properties of the brain of patients with chronic pain. However, investigation of the brain circuitry supporting the perception of clinical pain presents significant challenges, particularly when using traditional neuroimaging approaches. While potential neuroimaging markers for clinical pain have included resting brain connectivity, these cross-sectional studies have not examined sensitivity to within-subject exacerbation of pain. We used the dual regression probabilistic Independent Component Analysis approach to investigate resting-state connectivity on Arterial Spin Labeling (ASL) data. Brain connectivity was compared between patients with chronic low back pain (cLBP) and healthy controls, before and after the performance of maneuvers aimed at exacerbating clinical pain levels in the patients. Our analyses identified multiple resting state networks, including the Default Mode Network (DMN). At baseline, patients demonstrated stronger DMN connectivity to the pregenual anterior cingulate cortex (pgACC), left inferior parietal lobule and right insula (rINS). Patients’ baseline clinical pain correlated positively with connectivity strength between the DMN and right insula (DMN-rINS). The performance of calibrated physical maneuvers induced changes in pain, which were paralleled by changes in DMN-rINS connectivity. Maneuvers also disrupted the DMN-pgACC connectivity, which at baseline was anti-correlated with pain. Finally, baseline DMN connectivity predicted maneuver-induced changes in both pain and DMN-rINS connectivity. Our results support the use of ASL to evaluate clinical pain, and the use of resting DMN connectivity as a potential neuroimaging biomarker for chronic pain perception. PMID:23111164

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

    Directory of Open Access Journals (Sweden)

    Mao Chizu

    2016-01-01

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

  12. 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.

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

    Science.gov (United States)

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

    2009-02-01

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

  14. The default mode network as a biomarker for monitoring the therapeutic effects of meditation.

    Science.gov (United States)

    Simon, Rozalyn; Engström, Maria

    2015-01-01

    The default mode network (DMN) is a group of anatomically separate regions in the brain found to have synchronized patterns of activation in functional magnetic resonance imaging (fMRI). Mentation associated with the DMN includes processes such as mind wandering, autobiographical memory, self-reflective thought, envisioning the future, and considering the perspective of others. Abnormalities in the DMN have been linked to symptom severity in a variety of mental disorders indicating that the DMN could be used as a biomarker for diagnosis. These correlations have also led to the use of DMN modulation as a biomarker for assessing pharmacological treatments. Concurrent research investigating the neural correlates of meditation, have associated DMN modulation with practice. Furthermore, meditative practice is increasingly understood to have a beneficial role in the treatment of mental disorders. Therefore we propose the use of DMN measures as a biomarker for monitoring the therapeutic effects of meditation practices in mental disorders. Recent findings support this perspective, and indicate the utility of DMN monitoring in understanding and developing meditative treatments for these debilitating conditions.

  15. The default mode network as a biomarker for monitoring the therapeutic effects of meditation

    Directory of Open Access Journals (Sweden)

    Rozalyn eSimon

    2015-06-01

    Full Text Available The default mode network (DMN is a group of anatomically separate regions in the brain found to have synchronized patterns of activation in functional magnetic resonance imaging (fMRI. Mentation associated with the DMN includes processes such as mind wandering, autobiographical memory, self-reflective thought, envisioning the future, and considering the perspective of others. Abnormalities in the DMN have been linked to symptom severity in a variety of mental disorders indicating that the DMN could be used as a biomarker for diagnosis. These correlations have also led to the use of DMN modulation as a biomarker for assessing pharmacological treatments. Concurrent research investigating the neurocorrelates of meditation have associated DMN modulation with practice. Furthermore, meditative practice is increasingly understood to have a beneficial role in the treatment of mental disorders. Therefore we propose the use of DMN measures as a biomarker for monitoring the therapeutic effects of meditation practices in mental disorders. Recent findings support this perspective, and indicate the utility of DMN monitoring in understanding and developing meditative treatments for these debilitating conditions.

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

    Directory of Open Access Journals (Sweden)

    Belinda ePletzer

    2015-04-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  18. Sleep disturbance in mild cognitive impairment is associated with alterations in the brain's default mode network.

    Science.gov (United States)

    McKinnon, Andrew C; Lagopoulos, Jim; Terpening, Zoe; Grunstein, Ron; Hickie, Ian B; Batchelor, Jennifer; Lewis, Simon J G; Duffy, Shantel; Shine, James M; Naismith, Sharon L

    2016-06-01

    This study aimed to identify default mode network (DMN) functional connectivity deficits in patients with mild cognitive impairment (MCI) and sleep disturbance, relative to those with MCI and no sleep disturbance. A control group was included to aid in identifying DMN changes specific to MCI. A cross-sectional, single-center study was performed at the Brain and Mind Research Centre in Sydney, Australia. Participants (95 adults over the age of 65: 38 controls and 57 meeting criteria for MCI) underwent resting-state functional MRI along with comprehensive neuropsychological, medical, and psychiatric assessment. Self-report data were collected including sleep quality assessment via the Pittsburgh Sleep Quality Index. A total score of greater than 5 on the Pittsburgh Sleep Quality Index was used to signify the presence of significant sleep disturbance, as per commonly used methodology. Using this criterion, 53% (n = 30) of our MCI group were classified as sleep-disturbed. Whereas the total group of MCI subjects and controls demonstrated no significant differences, sleep-disturbed MCIs demonstrated increased connectivity between temporal and parietal regions, and decreased connectivity between the prefrontal cortex and the temporoparietal junction relative to sleep-disturbed controls. Relative to those MCIs without sleep disturbance, sleep-disturbed MCI participants demonstrated significantly diminished DMN connectivity between temporal and parietal regions, a finding that was particularly pronounced in amnestic MCI. Sleep disturbance in MCI is associated with distinct alterations in DMN functional connectivity in brain regions underpinning salient memory and sleep systems. Future studies may build on these results via experimental manipulation and objective measurement of sleep. (PsycINFO Database Record

  19. A NOVEL INTRUSION DETECTION MODE BASED ON UNDERSTANDABLE NEURAL NETWORK TREES

    Institute of Scientific and Technical Information of China (English)

    Xu Qinzhen; Yang Luxi; Zhao Qiangfu; He Zhenya

    2006-01-01

    Several data mining techniques such as Hidden Markov Model (HMM), artificial neural network,statistical techniques and expert systems are used to model network packets in the field of intrusion detection.In this paper a novel intrusion detection mode based on understandable Neural Network Tree (NNTree) is presented. NNTree is a modular neural network with the overall structure being a Decision Tree (DT), and each non-terminal node being an Expert Neural Network (ENN). One crucial advantage of using NNTrees is that they keep the non-symbolic model ENN's capability of learning in changing environments. Another potential advantage of using NNTrees is that they are actually "gray boxes" as they can be interpreted easily ifthe number of inputs for each ENN is limited. We showed through experiments that the trained NNTree achieved a simple ENN at each non-terminal node as well as a satisfying recognition rate of the network packets dataset.We also compared the performance with that of a three-layer backpropagation neural network. Experimental results indicated that the NNTree based intrusion detection model achieved better performance than the neural network based intrusion detection model.

  20. Altered resting-state functional connectivity in cortical networks in psychopathy.

    Science.gov (United States)

    Philippi, Carissa L; Pujara, Maia S; Motzkin, Julian C; Newman, Joseph; Kiehl, Kent A; Koenigs, Michael

    2015-04-15

    Psychopathy is a personality disorder characterized by callous antisocial behavior and criminal recidivism. Here we examine whether psychopathy is associated with alterations in functional connectivity in three large-scale cortical networks. Using fMRI in 142 adult male prison inmates, we computed resting-state functional connectivity using seeds from the default mode network, frontoparietal network, and cingulo-opercular network. To determine the specificity of our findings to these cortical networks, we also calculated functional connectivity using seeds from two comparison primary sensory networks: visual and auditory networks. Regression analyses related network connectivity to overall psychopathy scores and to subscores for the "factors" and "facets" of psychopathy: Factor 1, interpersonal/affective traits; Factor 2, lifestyle/antisocial traits; Facet 1, interpersonal; Facet 2, affective; Facet 3, lifestyle; Facet 4, antisocial. Overall psychopathy severity was associated with reduced functional connectivity between lateral parietal cortex and dorsal anterior cingulate cortex. The two factor scores exhibited contrasting relationships with functional connectivity: Factor 1 scores were associated with reduced functional connectivity in the three cortical networks, whereas Factor 2 scores were associated with heightened connectivity in the same networks. This dissociation was evident particularly in the functional connectivity between anterior insula and dorsal anterior cingulate cortex. The facet scores also demonstrated distinct patterns of connectivity. We found no associations between psychopathy scores and functional connectivity within visual or auditory networks. These findings provide novel evidence on the neural correlates of psychopathy and suggest that connectivity between cortical association hubs, such as the dorsal anterior cingulate cortex, may be a neurobiological marker of the disorder.

  1. 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

  2. A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice.

    Science.gov (United States)

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

    2013-05-01

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

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

    Science.gov (United States)

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

    2017-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Britta Klagge

    2012-01-01

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

  5. Learning discriminative functional network features of schizophrenia

    Science.gov (United States)

    Gheiratmand, Mina; Rish, Irina; Cecchi, Guillermo; Brown, Matthew; Greiner, Russell; Bashivan, Pouya; Polosecki, Pablo; Dursun, Serdar

    2017-03-01

    Associating schizophrenia with disrupted functional connectivity is a central idea in schizophrenia research. However, identifying neuroimaging-based features that can serve as reliable "statistical biomarkers" of the disease remains a challenging open problem. We argue that generalization accuracy and stability of candidate features ("biomarkers") must be used as additional criteria on top of standard significance tests in order to discover more robust biomarkers. Generalization accuracy refers to the utility of biomarkers for making predictions about individuals, for example discriminating between patients and controls, in novel datasets. Feature stability refers to the reproducibility of the candidate features across different datasets. Here, we extracted functional connectivity network features from fMRI data at both high-resolution (voxel-level) and a spatially down-sampled lower-resolution ("supervoxel" level). At the supervoxel level, we used whole-brain network links, while at the voxel level, due to the intractably large number of features, we sampled a subset of them. We compared statistical significance, stability and discriminative utility of both feature types in a multi-site fMRI dataset, composed of schizophrenia patients and healthy controls. For both feature types, a considerable fraction of features showed significant differences between the two groups. Also, both feature types were similarly stable across multiple data subsets. However, the whole-brain supervoxel functional connectivity features showed a higher cross-validation classification accuracy of 78.7% vs. 72.4% for the voxel-level features. Cross-site variability and heterogeneity in the patient samples in the multi-site FBIRN dataset made the task more challenging compared to single-site studies. The use of the above methodology in combination with the fully data-driven approach using the whole brain information have the potential to shed light on "biomarker discovery" in schizophrenia.

  6. On stabilization of stochastic Cohen-Grossberg neural networks with mode-dependent mixed time-delays and Markovian switching.

    Science.gov (United States)

    Zheng, Cheng-De; Shan, Qi-He; Zhang, Huaguang; Wang, Zhanshan

    2013-05-01

    The globally exponential stabilization problem is investigated for a general class of stochastic Cohen-Grossberg neural networks with both Markovian jumping parameters and mixed mode-dependent time-delays. The mixed time-delays consist of both discrete and distributed delays. This paper aims to design a memoryless state feedback controller such that the closed-loop system is stochastically exponentially stable in the mean square sense. By introducing a new Lyapunov-Krasovskii functional that accounts for the mode-dependent mixed delays, stochastic analysis is conducted in order to derive delay-dependent criteria for the exponential stabilization problem. Three numerical examples are carried out to demonstrate the feasibility of our delay-dependent stabilization criteria.

  7. Manifold learning on brain functional networks in aging.

    Science.gov (United States)

    Qiu, Anqi; Lee, Annie; Tan, Mingzhen; Chung, Moo K

    2015-02-01

    We propose a new analysis framework to utilize the full information of brain functional networks for computing the mean of a set of brain functional networks and embedding brain functional networks into a low-dimensional space in which traditional regression and classification analyses can be easily employed. For this, we first represent the brain functional network by a symmetric positive matrix computed using sparse inverse covariance estimation. We then impose a Log-Euclidean Riemannian manifold structure on brain functional networks whose norm gives a convenient and practical way to define a mean. Finally, based on the fact that the computation of linear operations can be done in the tangent space of this Riemannian manifold, we adopt Locally Linear Embedding (LLE) to the Log-Euclidean Riemannian manifold space in order to embed the brain functional networks into a low-dimensional space. We show that the integration of the Log-Euclidean manifold with LLE provides more efficient and succinct representation of the functional network and facilitates regression analysis, such as ridge regression, on the brain functional network to more accurately predict age when compared to that of the Euclidean space of functional networks with LLE. Interestingly, using the Log-Euclidean analysis framework, we demonstrate the integration and segregation of cortical-subcortical networks as well as among the salience, executive, and emotional networks across lifespan.

  8. Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging.

    Science.gov (United States)

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

    2016-05-01

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

  9. Joint Mode Selection and Resource Allocation for Cellular Controlled Short-Range Communication in OFDMA Networks

    Science.gov (United States)

    Deng, Hui; Tao, Xiaoming; Ge, Ning; Lu, Jianhua

    This letter studies cellular controlled short-range communication in OFDMA networks. The network needs to decide when to allow direct communication between a closely located device-to-device (D2D) pair instead of conveying data from one device to the other via the base station and when not to, in addition to subchannel and power allocation. Our goal is to maximize the total network throughput while guaranteeing the rate requirements of all users. For that purpose, we formulate an optimization problem subject to subchannel and power constraints. A scheme which combines a joint mode selection and subchannel allocation algorithm based on equal power allocation with a power reallocation scheme is proposed. Simulation results show that our proposed scheme can improve the network throughput and outage probability compared with other schemes.

  10. 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.

  11. DevOps for network function virtualisation: an architectural approach

    OpenAIRE

    Karl, H.; Draexler, S.; Peuster, M; Galis, A.; Bredel, M.; RAMOS, A.; Martrat, J.; Siddiqui, M S; Van Rossem, S.; Tavernier, W; Xilouris, G.

    2016-01-01

    The Service Programming and Orchestration for Virtualised Software Networks (SONATA) project targets both the flexible programmability of software networks and the optimisation of their deployments by means of integrating Development and Operations in order to accelerate industry adoption of software networks and reduce time-to-market for networked services. SONATA supports network function chaining and orchestration, making service platforms modular and easier to customise to the needs of di...

  12. Improving the Network Structure can lead to Functional Failures

    CERN Document Server

    Pade, Jan Philipp

    2014-01-01

    In many real-world networks the ability to synchronize is a key property for its performance. Examples include power-grid, sensor, and neuron networks as well as consensus formation. Recent work on undirected networks with diffusive interaction revealed that improvements in the network connectivity such as making the network more connected and homogeneous enhances synchronization. However, real-world networks have directed and weighted connections. In such directed networks, understanding the impact of structural changes on the network performance remains a major challenge. Here, we show that improving the structure of a directed network can lead to a failure in the network function. For instance, introducing new links to reduce the minimum distance between nodes can lead to instabilities in the synchronized motion. This counter-intuitive effect only occurs in directed networks. Our results allow to identify the dynamical importance of a link and thereby have a major impact on the design and control of direct...

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

    Directory of Open Access Journals (Sweden)

    M. Udin Harun Al Rasyid

    2013-12-01

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

  14. Constructive feedforward neural networks using hermite polynomial activation functions.

    Science.gov (United States)

    Ma, Liying; Khorasani, K

    2005-07-01

    In this paper, a constructive one-hidden-layer network is introduced where each hidden unit employs a polynomial function for its activation function that is different from other units. Specifically, both a structure level as well as a function level adaptation methodologies are utilized in constructing the network. The functional level adaptation scheme ensures that the "growing" or constructive network has different activation functions for each neuron such that the network may be able to capture the underlying input-output map more effectively. The activation functions considered consist of orthonormal Hermite polynomials. It is shown through extensive simulations that the proposed network yields improved performance when compared to networks having identical sigmoidal activation functions.

  15. Measuring the Wigner Functions of Two-Mode Cavity Fields and Testing the Bell's Inequalities

    Institute of Scientific and Technical Information of China (English)

    张智明

    2004-01-01

    We propose a scheme for measuring the Wigner function of a two-mode cavity field. The scheme bases on the interaction between the two-mode cavity field and three-level atoms. We find a simple relation between the Wigner function and the atomic population. One can obtain the Wigner function by measuring the atomic population with a micromaser-like experiment and doing a numerical integral. By using the two-mode Wigner function one can obtain the Clauser-Horne combination and test the Bell's inequalities. We test our equations with a two-mode entanglement state and the results are rather good.

  16. Decentralized adaptive neural network sliding mode position/force control of constrained reconfigurable manipulators

    Institute of Scientific and Technical Information of China (English)

    李元春; 丁贵彬; 赵博

    2016-01-01

    A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooperation, the proposed decentralized position/force control scheme can be applied to series constrained reconfigurable manipulators. By multiplying each row of Jacobian matrix in the dynamics by contact force vector, the converted joint torque is obtained. Furthermore, using desired information of other joints instead of their actual values, the dynamics can be represented as a set of interconnected subsystems by model decomposition technique. An adaptive neural network controller is introduced to approximate the unknown dynamics of subsystem. The interconnection and the whole error term are removed by employing an adaptive sliding mode term. And then, the Lyapunov stability theory guarantees the stability of the closed-loop system. Finally, two reconfigurable manipulators with different configurations are employed to show the effectiveness of the proposed decentralized position/force control scheme.

  17. The shareholding similarity of the shareholders of the worldwide listed energy companies based on a two-mode primitive network and a one-mode derivative holding-based network

    Science.gov (United States)

    Li, Huajiao; Fang, Wei; An, Haizhong; Yan, LiLi

    2014-12-01

    Two-mode and multi-mode networks represent new directions of simulating a complex network that can simulate the relationships among the entities more precisely. In this paper, we constructed two different levels of networks: one is the two-mode primitive networks of the energy listed companies and their shareholders on the basis of the two-mode method of complex theory, and the other is the derivative one-mode holding-based network based on the equivalence network theory. We calculated two different topological characteristics of the two networks, that is, the out-degree of the actor nodes of the two-mode network (9003 nodes) and the weights of the edges of the one-mode network (619,766 edges), and we analyzed the distribution features of both of the two topological characteristics. In this paper, we define both the weighted and un-weighted Shareholding Similarity Coefficient, and using the data of the worldwide listed energy companies and their shareholders as empirical study subjects, we calculated and compared both the weighted and un-weighted shareholding similarity coefficient of the worldwide listed energy companies. The result of the analysis indicates that (1) both the out-degree of the actor nodes of the two-mode network and the weights of the edges of the one-mode network follow a power-law distribution; (2) there are significant differences between the weighted and un-weighted shareholding similarity coefficient of the worldwide listed energy companies, and the weighted shareholding similarity coefficient is of greater regularity than the un-weighted one; (3) there are a vast majority of shareholders who hold stock in only one or a few of the listed energy companies; and (4) the shareholders hold stock in the same listed energy companies when the value of the un-weighted shareholding similarity coefficient is between 0.4 and 0.8. The study will be a helpful tool to analyze the relationships of the nodes of the one-mode network, which is constructed based

  18. Progressive Bidirectional Age-Related Changes in Default Mode Network Effective Connectivity across Six Decades.

    Science.gov (United States)

    Li, Karl; Laird, Angela R; Price, Larry R; McKay, D Reese; Blangero, John; Glahn, David C; Fox, Peter T

    2016-01-01

    The default mode network (DMN) is a set of regions that is tonically engaged during the resting state and exhibits task-related deactivation that is readily reproducible across a wide range of paradigms and modalities. The DMN has been implicated in numerous disorders of cognition and, in particular, in disorders exhibiting age-related cognitive decline. Despite these observations, investigations of the DMN in normal aging are scant. Here, we used blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) acquired during rest to investigate age-related changes in functional connectivity of the DMN in 120 healthy normal volunteers comprising six, 20-subject, decade cohorts (from 20-29 to 70-79). Structural equation modeling (SEM) was used to assess age-related changes in inter-regional connectivity within the DMN. SEM was applied both using a previously published, meta-analytically derived, node-and-edge model, and using exploratory modeling searching for connections that optimized model fit improvement. Although the two models were highly similar (only 3 of 13 paths differed), the sample demonstrated significantly better fit with the exploratory model. For this reason, the exploratory model was used to assess age-related changes across the decade cohorts. Progressive, highly significant changes in path weights were found in 8 (of 13) paths: four rising, and four falling (most changes were significant by the third or fourth decade). In all cases, rising paths and falling paths projected in pairs onto the same nodes, suggesting compensatory increases associated with age-related decreases. This study demonstrates that age-related changes in DMN physiology (inter-regional connectivity) are bidirectional, progressive, of early onset and part of normal aging.

  19. Probabilistic atlases of default mode, executive control and salience network white matter tracts: an fMRI-guided diffusion tensor imaging and tractography study.

    Science.gov (United States)

    Figley, Teresa D; Bhullar, Navdeep; Courtney, Susan M; Figley, Chase R

    2015-01-01

    Diffusion tensor imaging (DTI) is a powerful MRI technique that can be used to estimate both the microstructural integrity and the trajectories of white matter pathways throughout the central nervous system. This fiber tracking (aka, "tractography") approach is often carried out using anatomically-defined seed points to identify white matter tracts that pass through one or more structures, but can also be performed using functionally-defined regions of interest (ROIs) that have been determined using functional MRI (fMRI) or other methods. In this study, we performed fMRI-guided DTI tractography between all of the previously defined nodes within each of six common resting-state brain networks, including the: dorsal Default Mode Network (dDMN), ventral Default Mode Network (vDMN), left Executive Control Network (lECN), right Executive Control Network (rECN), anterior Salience Network (aSN), and posterior Salience Network (pSN). By normalizing the data from 32 healthy control subjects to a standard template-using high-dimensional, non-linear warping methods-we were able to create probabilistic white matter atlases for each tract in stereotaxic coordinates. By investigating all 198 ROI-to-ROI combinations within the aforementioned resting-state networks (for a total of 6336 independent DTI tractography analyses), the resulting probabilistic atlases represent a comprehensive cohort of functionally-defined white matter regions that can be used in future brain imaging studies to: (1) ascribe DTI or other white matter changes to particular functional brain networks, and (2) compliment resting state fMRI or other functional connectivity analyses.

  20. Using neural networks to predict the functionality of reconfigurable nano-material networks

    NARCIS (Netherlands)

    Greff, Klaus; Damme, van Ruud; Koutnik, Jan; Broersma, Hajo; Mikhal, Julia; Lawrence, Celestine; Wiel, van der Wilfred; Schmidhuber, Jürgen

    2017-01-01

    This paper demonstrates how neural networks can be applied to model and predict the functional behaviour of disordered nano-particle and nano-tube networks. In recently published experimental work, nano-particle and nano-tube networks show promising functionality for future reconfigurable devices, w

  1. INFERRING FUNCTIONAL NETWORK-BASED SIGNATURES VIA STRUCTURALLY-WEIGHTED LASSO MODEL.

    Science.gov (United States)

    Zhu, Dajiang; Shen, Dinggang; Liu, Tianming

    2013-01-01

    Most current research approaches for functional/effective connectivity analysis focus on pair-wise connectivity and cannot deal with network-scale functional interactions. In this paper, we propose a structurally-weighted LASSO (SW-LASSO) regression model to represent the functional interaction among multiple regions of interests (ROIs) based on resting state fMRI (R-fMRI) data. The structural connectivity constraints derived from diffusion tenor imaging (DTI) data will guide the selection of the weights which adjust the penalty levels of different coefficients corresponding to different ROIs. Using the Default Mode Network (DMN) as a test-bed, our results indicate that the learned SW-LASSO has good capability of differentiating Mild Cognitive Impairment (MCI) subjects from their normal controls and has promising potential to characterize the brain functions among different condition, thus serving as the functional network-based signature.

  2. Energy-aware wireless networked control using radio-mode management

    OpenAIRE

    Cardoso De Castro, Nicolas; Canudas De Wit, Carlos; Garin, Federica

    2012-01-01

    International audience; Energy efficiency is one of the main issues in wireless Networked Control Systems. The control community has already shown large interest in the topics of intermittent control and event-based control, allowing to turn off the radio of the nodes, which is the main energy consumer, on longer time intervals than in the periodic case. While the existing literature only addresses policies using two radio-modes (Tx - Transmitting, and Sleep), this paper considers intermediat...

  3. Functional alignment of regulatory networks: a study of temperate phages.

    Directory of Open Access Journals (Sweden)

    Ala Trusina

    2005-12-01

    Full Text Available The relationship between the design and functionality of molecular networks is now a key issue in biology. Comparison of regulatory networks performing similar tasks can provide insights into how network architecture is constrained by the functions it directs. Here, we discuss methods of network comparison based on network architecture and signaling logic. Introducing local and global signaling scores for the difference between two networks, we quantify similarities between evolutionarily closely and distantly related bacteriophages. Despite the large evolutionary separation between phage lambda and 186, their networks are found to be similar when difference is measured in terms of global signaling. We finally discuss how network alignment can be used to pinpoint protein similarities viewed from the network perspective.

  4. Integral Sliding Mode Fault-Tolerant Control for Uncertain Linear Systems Over Networks With Signals Quantization.

    Science.gov (United States)

    Hao, Li-Ying; Park, Ju H; Ye, Dan

    2016-06-13

    In this paper, a new robust fault-tolerant compensation control method for uncertain linear systems over networks is proposed, where only quantized signals are assumed to be available. This approach is based on the integral sliding mode (ISM) method where two kinds of integral sliding surfaces are constructed. One is the continuous-state-dependent surface with the aim of sliding mode stability analysis and the other is the quantization-state-dependent surface, which is used for ISM controller design. A scheme that combines the adaptive ISM controller and quantization parameter adjustment strategy is then proposed. Through utilizing H∞ control analytical technique, once the system is in the sliding mode, the nature of performing disturbance attenuation and fault tolerance from the initial time can be found without requiring any fault information. Finally, the effectiveness of our proposed ISM control fault-tolerant schemes against quantization errors is demonstrated in the simulation.

  5. Projective synchronization of nonidentical fractional-order neural networks based on sliding mode controller.

    Science.gov (United States)

    Ding, Zhixia; Shen, Yi

    2016-04-01

    This paper investigates global projective synchronization of nonidentical fractional-order neural networks (FNNs) based on sliding mode control technique. We firstly construct a fractional-order integral sliding surface. Then, according to the sliding mode control theory, we design a sliding mode controller to guarantee the occurrence of the sliding motion. Based on fractional Lyapunov direct methods, system trajectories are driven to the proposed sliding surface and remain on it evermore, and some novel criteria are obtained to realize global projective synchronization of nonidentical FNNs. As the special cases, some sufficient conditions are given to ensure projective synchronization of identical FNNs, complete synchronization of nonidentical FNNs and anti-synchronization of nonidentical FNNs. Finally, one numerical example is given to demonstrate the effectiveness of the obtained results.

  6. Resting state functional MRI reveals abnormal network connectivity in orthostatic tremor.

    Science.gov (United States)

    Benito-León, Julián; Louis, Elan D; Manzanedo, Eva; Hernández-Tamames, Juan Antonio; Álvarez-Linera, Juan; Molina-Arjona, José Antonio; Matarazzo, Michele; Romero, Juan Pablo; Domínguez-González, Cristina; Domingo-Santos, Ángela; Sánchez-Ferro, Álvaro

    2016-07-01

    Very little is known about the pathogenesis of orthostatic tremor (OT). We have observed that OT patients might have deficits in specific aspects of neuropsychological function, particularly those thought to rely on the integrity of the prefrontal cortex, which suggests a possible involvement of frontocerebellar circuits. We examined whether resting-state functional magnetic resonance imaging (fMRI) might provide further insights into the pathogenesis on OT. Resting-state fMRI data in 13 OT patients (11 women and 2 men) and 13 matched healthy controls were analyzed using independent component analysis, in combination with a "dual-regression" technique, to identify group differences in several resting-state networks (RSNs). All participants also underwent neuropsychological testing during the same session. Relative to healthy controls, OT patients showed increased connectivity in RSNs involved in cognitive processes (default mode network [DMN] and frontoparietal networks), and decreased connectivity in the cerebellum and sensorimotor networks. Changes in network integrity were associated not only with duration (DMN and medial visual network), but also with cognitive function. Moreover, in at least 2 networks (DMN and medial visual network), increased connectivity was associated with worse performance on different cognitive domains (attention, executive function, visuospatial ability, visual memory, and language). In this exploratory study, we observed selective impairments of RSNs in OT patients. This and other future resting-state fMRI studies might provide a novel method to understand the pathophysiological mechanisms of motor and nonmotor features of OT.

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

    Science.gov (United States)

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

    2015-02-09

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

  8. Models of neural networks with fuzzy activation functions

    Science.gov (United States)

    Nguyen, A. T.; Korikov, A. M.

    2017-02-01

    This paper investigates the application of a new form of neuron activation functions that are based on the fuzzy membership functions derived from the theory of fuzzy systems. On the basis of the results regarding neuron models with fuzzy activation functions, we created the models of fuzzy-neural networks. These fuzzy-neural network models differ from conventional networks that employ the fuzzy inference systems using the methods of neural networks. While conventional fuzzy-neural networks belong to the first type, fuzzy-neural networks proposed here are defined as the second-type models. The simulation results show that the proposed second-type model can successfully solve the problem of the property prediction for time – dependent signals. Neural networks with fuzzy impulse activation functions can be widely applied in many fields of science, technology and mechanical engineering to solve the problems of classification, prediction, approximation, etc.

  9. Analysis of neural networks through base functions

    NARCIS (Netherlands)

    van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.

    Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more

  10. Analysis of Neural Networks through Base Functions

    NARCIS (Netherlands)

    Zwaag, van der B.J.; Slump, C.H.; Spaanenburg, L.

    2002-01-01

    Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more

  11. Nonequilibrium functional bosonization of quantum wire networks

    Energy Technology Data Exchange (ETDEWEB)

    Ngo Dinh, Stephane, E-mail: stephane.ngodinh@kit.edu [Institut fuer Theorie der Kondensierten Materie, Karlsruhe Institute of Technology, 76128 Karlsruhe (Germany); DFG Center for Functional Nanostructures, Karlsruhe Institute of Technology, 76128 Karlsruhe (Germany); Bagrets, Dmitry A. [Institut fuer Theoretische Physik, Universitaet zu Koeln, Zuelpicher Str. 77, 50937 Koeln (Germany); Mirlin, Alexander D. [Institut fuer Theorie der Kondensierten Materie, Karlsruhe Institute of Technology, 76128 Karlsruhe (Germany); Institut fuer Nanotechnologie, Karlsruhe Institute of Technology, 76021 Karlsruhe (Germany); DFG Center for Functional Nanostructures, Karlsruhe Institute of Technology, 76128 Karlsruhe (Germany); Petersburg Nuclear Physics Institute, 188300 St. Petersburg (Russian Federation)

    2012-11-15

    We develop a general approach to nonequilibrium nanostructures formed by one-dimensional channels coupled by tunnel junctions and/or by impurity scattering. The formalism is based on nonequilibrium version of functional bosonization. A central role in this approach is played by the Keldysh action that has a form reminiscent of the theory of full counting statistics. To proceed with evaluation of physical observables, we assume the weak-tunneling regime and develop a real-time instanton method. A detailed exposition of the formalism is supplemented by two important applications: (i) tunneling into a biased Luttinger liquid with an impurity, and (ii) quantum Hall Fabry-Perot interferometry. - Highlights: Black-Right-Pointing-Pointer A nonequilibrium functional bosonization framework for quantum wire networks is developed Black-Right-Pointing-Pointer For the study of observables in the weak tunneling regime a real-time instanton method is elaborated. Black-Right-Pointing-Pointer We consider tunneling into a biased Luttinger liquid with an impurity. Black-Right-Pointing-Pointer We analyze electronic Fabry-Perot interferometers in the integer quantum Hall regime.

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

    Directory of Open Access Journals (Sweden)

    Inês R Violante

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

  13. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-03-27

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

  15. A Functional Complexity Framework for the Analysis of Telecommunication Networks

    CERN Document Server

    Dzaferagic, Merim; Macaluso, Irene; Marchetti, Nicola

    2016-01-01

    The rapid evolution of network services demands new paradigms for studying and designing networks. In order to understand the underlying mechanisms that provide network functions, we propose a framework which enables the functional analysis of telecommunication networks. This framework allows us to isolate and analyse a network function as a complex system. We propose functional topologies to visualise the relationships between system entities and enable the systematic study of interactions between them. We also define a complexity metric $C_F$ (functional complexity) which quantifies the variety of structural patterns and roles of nodes in the topology. This complexity metric provides a wholly new approach to study the operation of telecommunication networks. We study the relationship between $C_F$ and different graph structures by analysing graph theory metrics in order to recognize complex organisations. $C_F$ is equal to zero for both a full mesh topology and a disconnected topology. We show that complexi...

  16. Functional atrial undersensing associated with switching to a tracking mode of pacing.

    Science.gov (United States)

    Barold, S Serge; Van Heuverswyn, Frederic; Timmers, Liesbeth; Stroobandt, Roland X

    2012-10-01

    We have previously demonstrated that contemporary St. Jude devices (pacemakers and implantable cardioverter-defibrillators [ICDs]; St. Jude Medical, Sylmar, CA, USA) are designed to generate an extended postventricular atrial refractory period (PVARP) of 475 ms at the termination of conventional automatic mode switching (AMS) in response to atrial tachyarrhythmias . This response may cause functional atrial undersensing . A similar PVARP response unrelated to conventional AMS was found in four St. Jude devices (three ICDs and one pacemaker) whenever a nontracking pacing mode switched to a tracking DDD(R) mode. PVARP extension and functional atrial undersensing were observed when the VOO, VVI, and the DDI(R) modes (unrelated to conventional AMS) switched to the DDD(R) mode . In one patient the switch from the OOO mode (in the programmed noise reversion mode) to the DDD mode occurred after cessation of electromagnetic interference disturbing the ventricular channel. In this case PVARP extension was seen only in the corresponding markers because no P waves occurred coincidentally with the extended PVARP. The PVARP extension caused by a mode switch to the tracking function was designed to prevent sensing of a retrograde P wave on the first cycle of the reestablished tracking mode. The observed functional atrial undersensing is a normal manifestation of device function and must not be misinterpreted as a true atrial undersensing problem.

  17. 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.

  18. Driving and driven architectures of directed small-world human brain functional networks.

    Directory of Open Access Journals (Sweden)

    Chaogan Yan

    Full Text Available Recently, increasing attention has been focused on the investigation of the human brain connectome that describes the patterns of structural and functional connectivity networks of the human brain. Many studies of the human connectome have demonstrated that the brain network follows a small-world topology with an intrinsically cohesive modular structure and includes several network hubs in the medial parietal regions. However, most of these studies have only focused on undirected connections between regions in which the directions of information flow are not taken into account. How the brain regions causally influence each other and how the directed network of human brain is topologically organized remain largely unknown. Here, we applied linear multivariate Granger causality analysis (GCA and graph theoretical approaches to a resting-state functional MRI dataset with a large cohort of young healthy participants (n = 86 to explore connectivity patterns of the population-based whole-brain functional directed network. This directed brain network exhibited prominent small-world properties, which obviously improved previous results of functional MRI studies showing weak small-world properties in the directed brain networks in terms of a kernel-based GCA and individual analysis. This brain network also showed significant modular structures associated with 5 well known subsystems: fronto-parietal, visual, paralimbic/limbic, subcortical and primary systems. Importantly, we identified several driving hubs predominantly located in the components of the attentional network (e.g., the inferior frontal gyrus, supplementary motor area, insula and fusiform gyrus and several driven hubs predominantly located in the components of the default mode network (e.g., the precuneus, posterior cingulate gyrus, medial prefrontal cortex and inferior parietal lobule. Further split-half analyses indicated that our results were highly reproducible between two

  19. Discovering functional interaction patterns in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Can Tolga

    2008-06-01

    Full Text Available Abstract Background In recent years, a considerable amount of research effort has been directed to the analysis of biological networks with the availability of genome-scale networks of genes and/or proteins of an increasing number of organisms. A protein-protein interaction (PPI network is a particular biological network which represents physical interactions between pairs of proteins of an organism. Major research on PPI networks has focused on understanding the topological organization of PPI networks, evolution of PPI networks and identification of conserved subnetworks across different species, discovery of modules of interaction, use of PPI networks for functional annotation of uncharacterized proteins, and improvement of the accuracy of currently available networks. Results In this article, we map known functional annotations of proteins onto a PPI network in order to identify frequently occurring interaction patterns in the functional space. We propose a new frequent pattern identification technique, PPISpan, adapted specifically for PPI networks from a well-known frequent subgraph identification method, gSpan. Existing module discovery techniques either look for specific clique-like highly interacting protein clusters or linear paths of interaction. However, our goal is different; instead of single clusters or pathways, we look for recurring functional interaction patterns in arbitrary topologies. We have applied PPISpan on PPI networks of Saccharomyces cerevisiae and identified a number of frequently occurring functional interaction patterns. Conclusion With the help of PPISpan, recurring functional interaction patterns in an organism's PPI network can be identified. Such an analysis offers a new perspective on the modular organization of PPI networks. The complete list of identified functional interaction patterns is available at http://bioserver.ceng.metu.edu.tr/PPISpan/.

  20. Structure-function clustering in multiplex brain networks

    Science.gov (United States)

    Crofts, J. J.; Forrester, M.; O'Dea, R. D.

    2016-10-01

    A key question in neuroscience is to understand how a rich functional repertoire of brain activity arises within relatively static networks of structurally connected neural populations: elucidating the subtle interactions between evoked “functional connectivity” and the underlying “structural connectivity” has the potential to address this. These structural-functional networks (and neural networks more generally) are more naturally described using a multilayer or multiplex network approach, in favour of standard single-layer network analyses that are more typically applied to such systems. In this letter, we address such issues by exploring important structure-function relations in the Macaque cortical network by modelling it as a duplex network that comprises an anatomical layer, describing the known (macro-scale) network topology of the Macaque monkey, and a functional layer derived from simulated neural activity. We investigate and characterize correlations between structural and functional layers, as system parameters controlling simulated neural activity are varied, by employing recently described multiplex network measures. Moreover, we propose a novel measure of multiplex structure-function clustering which allows us to investigate the emergence of functional connections that are distinct from the underlying cortical structure, and to highlight the dependence of multiplex structure on the neural dynamical regime.

  1. Epileptic seizure classification in EEG signals using second-order difference plot of intrinsic mode functions.

    Science.gov (United States)

    Pachori, Ram Bilas; Patidar, Shivnarayan

    2014-02-01

    Epilepsy is a neurological disorder which is characterized by transient and unexpected electrical disturbance of the brain. The electroencephalogram (EEG) is a commonly used signal for detection of epileptic seizures. This paper presents a new method for classification of ictal and seizure-free EEG signals. The proposed method is based on the empirical mode decomposition (EMD) and the second-order difference plot (SODP). The EMD method decomposes an EEG signal into a set of symmetric and band-limited signals termed as intrinsic mode functions (IMFs). The SODP of IMFs provides elliptical structure. The 95% confidence ellipse area measured from the SODP of IMFs has been used as a feature in order to discriminate seizure-free EEG signals from the epileptic seizure EEG signals. The feature space obtained from the ellipse area parameters of two IMFs has been used for classification of ictal and seizure-free EEG signals using the artificial neural network (ANN) classifier. It has been shown that the feature space formed using ellipse area parameters of first and second IMFs has given good classification performance. Experimental results on EEG database available by the University of Bonn, Germany, are included to illustrate the effectiveness of the proposed method.

  2. Unit 1002: The Modes and Functions of Discourse.

    Science.gov (United States)

    Minnesota Univ., Minneapolis. Center for Curriculum Development in English.

    The purpose of this 10th-grade unit on language is to pose, for students, basic and tentative questions about the rhetorical uses of language. Examples are provided which designate the modes of language: Daniel Fogarty's story of rhetoric to show language which informs; materials from Northrop Frye to show language which inquires; a John F.…

  3. The influence of rest period instructions on the default mode network

    Directory of Open Access Journals (Sweden)

    Christopher eBenjamin

    2010-12-01

    Full Text Available The default mode network (DMN refers to regional brain activity that is greater during rest periods than during attention-demanding tasks and many studies have reported DMN alterations in patient populations. It has also been shown that the DMN is suppressed by scanner background noise (SBN, which is the noise produced by functional magnetic resonance imaging (fMRI. However, it is unclear whether different approaches to rest in the noisy MR environment can alter the DMN and constitute a confound in studies investigating the DMN in particular patient populations (e.g., individuals with schizophrenia, Alzheimer’s disease. We examined twenty-seven healthy adult volunteers who completed an fMRI experiment with 3 different instructions for rest: (1 relax and be still, (2 attend to SBN, or (3 ignore SBN. Region of interest (ROI analyses were performed to determine the influence of rest period instructions on core regions of the DMN and DMN regions previously reported to be altered in patients with or at risk for Alzheimer’s disease or schizophrenia. The dorsal medial prefrontal cortex (dmPFC exhibited greater activity when specific resting instructions were given (i.e. attend to or ignore SBN compared to when non-specific resting instructions were given. Condition-related differences in connectivity were also observed between regions of the dmPFC and inferior parietal/posterior superior temporal cortex. We conclude that rest period instructions and SBN levels should be carefully considered for fMRI studies on the DMN, especially studies on clinical populations and groups that may have different approaches to rest, such as first-time research participants and children.

  4. The Influence of Rest Period Instructions on the Default Mode Network

    Science.gov (United States)

    Benjamin, Christopher; Lieberman, Daniel A.; Chang, Maria; Ofen, Noa; Whitfield-Gabrieli, Sue; Gabrieli, John D. E.; Gaab, Nadine

    2010-01-01

    The default mode network (DMN) refers to regional brain activity that is greater during rest periods than during attention-demanding tasks; many studies have reported DMN alterations in patient populations. It has also been shown that the DMN is suppressed by scanner background noise (SBN), which is the noise produced by functional magnetic resonance imaging (fMRI). However, it is unclear whether different approaches to “rest” in the noisy MR environment can alter the DMN and constitute a confound in studies investigating the DMN in particular patient populations (e.g., individuals with schizophrenia, Alzheimer's disease). We examined 27 healthy adult volunteers who completed an fMRI experiment with three different instructions for rest: (1) relax and be still, (2) attend to SBN, or (3) ignore SBN. Region of interest analyses were performed to determine the influence of rest period instructions on core regions of the DMN and DMN regions previously reported to be altered in patients with or at risk for Alzheimer's disease or schizophrenia. The dorsal medial prefrontal cortex (dmPFC) exhibited greater activity when specific resting instructions were given (i.e., attend to or ignore SBN) compared to when non-specific resting instructions were given. Condition-related differences in connectivity were also observed between regions of the dmPFC and inferior parietal/posterior superior temporal cortex. We conclude that rest period instructions and SBN levels should be carefully considered for fMRI studies on the DMN, especially studies on clinical populations and groups that may have different approaches to rest, such as first-time research participants and children. PMID:21151779

  5. Deficits in episodic memory retrieval reveal impaired default mode network connectivity in amnestic mild cognitive impairment

    Directory of Open Access Journals (Sweden)

    Cameron J. Dunn

    2014-01-01

    Full Text Available Amnestic mild cognitive impairment (aMCI is believed to represent a transitional stage between normal healthy ageing and the development of dementia. In particular, aMCI patients have been shown to have higher annual transition rates to Alzheimer's Disease (AD than individuals without cognitive impairment. Despite intensifying interest investigating the neuroanatomical basis of this transition, there remain a number of questions regarding the pathophysiological process underlying aMCI itself. A number of recent studies in aMCI have shown specific impairments in connectivity within the default mode network (DMN, which is a group of regions strongly related to episodic memory capacities. However to date, no study has investigated the integrity of the DMN between patients with aMCI and those with a non-amnestic pattern of MCI (naMCI, who have cognitive impairment, but intact memory storage systems. In this study, we contrasted the DMN connectivity in 24 aMCI and 33 naMCI patients using seed-based resting state fMRI. The two groups showed no statistical difference in their DMN intra-connectivity. However when connectivity was analysed according to performance on measures of episodic memory retrieval, the two groups were separable, with aMCI patients demonstrating impaired functional connectivity between the hippocampal formation and the posterior cingulate cortex. We provide evidence that this lack of connectivity is driven by impaired communication from the posterior cingulate hub and does not simply represent hippocampal atrophy, suggesting that posterior cingulate degeneration is the driving force behind impaired DMN connectivity in aMCI.

  6. Deficits in episodic memory retrieval reveal impaired default mode network connectivity in amnestic mild cognitive impairment

    Science.gov (United States)

    Dunn, Cameron J.; Duffy, Shantel L; Hickie, Ian B; Lagopoulos, Jim; Lewis, Simon J.G.; Naismith, Sharon L.; Shine, James M.

    2014-01-01

    Amnestic mild cognitive impairment (aMCI) is believed to represent a transitional stage between normal healthy ageing and the development of dementia. In particular, aMCI patients have been shown to have higher annual transition rates to Alzheimer's Disease (AD) than individuals without cognitive impairment. Despite intensifying interest investigating the neuroanatomical basis of this transition, there remain a number of questions regarding the pathophysiological process underlying aMCI itself. A number of recent studies in aMCI have shown specific impairments in connectivity within the default mode network (DMN), which is a group of regions strongly related to episodic memory capacities. However to date, no study has investigated the integrity of the DMN between patients with aMCI and those with a non-amnestic pattern of MCI (naMCI), who have cognitive impairment, but intact memory storage systems. In this study, we contrasted the DMN connectivity in 24 aMCI and 33 naMCI patients using seed-based resting state fMRI. The two groups showed no statistical difference in their DMN intra-connectivity. However when connectivity was analysed according to performance on measures of episodic memory retrieval, the two groups were separable, with aMCI patients demonstrating impaired functional connectivity between the hippocampal formation and the posterior cingulate cortex. We provide evidence that this lack of connectivity is driven by impaired communication from the posterior cingulate hub and does not simply represent hippocampal atrophy, suggesting that posterior cingulate degeneration is the driving force behind impaired DMN connectivity in aMCI. PMID:24634833

  7. Decreased regional activity of default-mode network in unaffected siblings of schizophrenia patients at rest.

    Science.gov (United States)

    Guo, Wenbin; Su, Qinji; Yao, Dapeng; Jiang, Jiajing; Zhang, Jian; Zhang, Zhikun; Yu, Liuyu; Zhai, Jinguo; Xiao, Changqing

    2014-04-01

    Dysconnectivity hypothesis posits that abnormal resting-state connectivity within the default-mode network (DMN) acts as a key role in schizophrenia. However, little is known about the regional alterations of the DMN in unaffected siblings of schizophrenia patients. Unaffected siblings have a unique advantage in neuroimaging studies independent of clinical and treatment issues that complicate studies on patients themselves. In the present study, we used fractional amplitude of low-frequency fluctuation (fALFF) to investigate regional alterations of the DMN in unaffected siblings of schizophrenia patients at rest. Forty-six unaffected siblings of schizophrenia patients and 50 age-, sex-, and education-matched healthy controls underwent a resting-state functional magnetic resonance imaging (fMRI). The fALFF and independent component analysis (ICA) approaches were used to analyze the data. The unaffected siblings of schizophrenia patients had lower fALFF than the controls in the left inferior temporal gyrus (ITG). No significantly increased fALFF was found in any brain regions in the siblings compared to that in the controls. Further receiver operating characteristic (ROC) curve and support vector machine (SVM) analyses showed that the fALFF values of the left ITG could be utilized to separate the siblings from the controls. Our results first suggest that there is decreased regional activity of the DMN in unaffected siblings of schizophrenia patients, and provide a clue that decreased regional activity of the left ITG could be applied as a candidate biomarker to identify the siblings from the controls.

  8. Epileptic discharges affect the default mode network--FMRI and intracerebral EEG evidence.

    Directory of Open Access Journals (Sweden)

    Firas Fahoum

    Full Text Available Functional neuroimaging studies of epilepsy patients often show, at the time of epileptic activity, deactivation in default mode network (DMN regions, which is hypothesized to reflect altered consciousness. We aimed to study the metabolic and electrophysiological correlates of these changes in the DMN regions. We studied six epilepsy patients that underwent scalp EEG-fMRI and later stereotaxic intracerebral EEG (SEEG sampling regions of DMN (posterior cingulate cortex, Pre-cuneus, inferior parietal lobule, medial prefrontal cortex and dorsolateral frontal cortex as well as non-DMN regions. SEEG recordings were subject to frequency analyses comparing sections with interictal epileptic discharges (IED to IED-free baselines in the IED-generating region, DMN and non-DMN regions. EEG-fMRI and SEEG were obtained at rest. During IEDs, EEG-fMRI demonstrated deactivation in various DMN nodes in 5 of 6 patients, most frequently the pre-cuneus and inferior parietal lobule, and less frequently the other DMN nodes. SEEG analyses demonstrated decrease in gamma power (50-150 Hz, and increase in the power of lower frequencies (<30 Hz at times of IEDs, in at least one DMN node in all patients. These changes were not apparent in the non-DMN regions. We demonstrate that, at the time of IEDs, DMN regions decrease their metabolic demand and undergo an EEG change consisting of decreased gamma and increased lower frequencies. These findings, specific to DMN regions, confirm in a pathological condition a direct relationship between DMN BOLD activity and EEG activity. They indicate that epileptic activity affects the DMN, and therefore may momentarily reduce the consciousness level and cognitive reserve.

  9. Dopamine transporters in striatum correlate with deactivation in the default mode network during visuospatial attention.

    Directory of Open Access Journals (Sweden)

    Dardo Tomasi

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

  10. Dopamine Transporters in Striatum Correlated with Deactivation in the Default Mode Network during Visuospatial Attention

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-06-01

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

  11. 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.

  12. Spreadsheets In Function Of Optimisation Of Logistics Network

    OpenAIRE

    Drago Pupavac; Mimo Draskovic

    2007-01-01

    This scientific paper discusses how estimated spreadsheets functions in logistics networks optimisation. The suggested working hypothesis for efficacy of estimated spreadsheets in designing logistics networks is proved and a practical example. In this way the given model can be applied to all logistics networks of similar problem capacity. Logistics network model confronting estimated spreadsheets present a real world at a level needed for understanding the problem of optimisation of logistic...

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

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

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

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

    Science.gov (United States)

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

    2010-12-01

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

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

    Science.gov (United States)

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

    2016-05-01

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

  16. Enhancing the functional content of eukaryotic protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Gaurav Pandey

    Full Text Available Protein interaction networks are a promising type of data for studying complex biological systems. However, despite the rich information embedded in these networks, these networks face important data quality challenges of noise and incompleteness that adversely affect the results obtained from their analysis. Here, we apply a robust measure of local network structure called common neighborhood similarity (CNS to address these challenges. Although several CNS measures have been proposed in the literature, an understanding of their relative efficacies for the analysis of interaction networks has been lacking. We follow the framework of graph transformation to convert the given interaction network into a transformed network corresponding to a variety of CNS measures evaluated. The effectiveness of each measure is then estimated by comparing the quality of protein function predictions obtained from its corresponding transformed network with those from the original network. Using a large set of human and fly protein interactions, and a set of over 100 GO terms for both, we find that several of the transformed networks produce more accurate predictions than those obtained from the original network. In particular, the HC.cont measure and other continuous CNS measures perform well this task, especially for large networks. Further investigation reveals that the two major factors contributing to this improvement are the abilities of CNS measures to prune out noisy edges and enhance functional coherence in the transformed networks.

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

    Directory of Open Access Journals (Sweden)

    Xiang Hongyu

    2015-09-01

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

  18. Impaired default network functional connectivity in autosomal dominant Alzheimer disease

    Science.gov (United States)

    Chhatwal, Jasmeer P.; Schultz, Aaron P.; Johnson, Keith; Benzinger, Tammie L.S.; Jack, Clifford; Ances, Beau M.; Sullivan, Caroline A.; Salloway, Stephen P.; Ringman, John M.; Koeppe, Robert A.; Marcus, Daniel S.; Thompson, Paul; Saykin, Andrew J.; Correia, Stephen; Schofield, Peter R.; Rowe, Christopher C.; Fox, Nick C.; Brickman, Adam M.; Mayeux, Richard; McDade, Eric; Bateman, Randall; Fagan, Anne M.; Goate, Allison M.; Xiong, Chengjie; Buckles, Virginia D.; Morris, John C.

    2013-01-01

    Objective: To investigate default mode network (DMN) functional connectivity MRI (fcMRI) in a large cross-sectional cohort of subjects from families harboring pathogenic presenilin-1 (PSEN1), presenilin-2 (PSEN2), and amyloid precursor protein (APP) mutations participating in the Dominantly Inherited Alzheimer Network. Methods: Eighty-three mutation carriers and 37 asymptomatic noncarriers from the same families underwent fMRI during resting state at 8 centers in the United States, United Kingdom, and Australia. Using group-independent component analysis, fcMRI was compared using mutation status and Clinical Dementia Rating to stratify groups, and related to each participant's estimated years from expected symptom onset (eYO). Results: We observed significantly decreased DMN fcMRI in mutation carriers with increasing Clinical Dementia Rating, most evident in the precuneus/posterior cingulate and parietal cortices (p < 0.001). Comparison of asymptomatic mutation carriers with noncarriers demonstrated decreased fcMRI in the precuneus/posterior cingulate (p = 0.014) and right parietal cortex (p = 0.0016). We observed a significant interaction between mutation carrier status and eYO, with decreases in DMN fcMRI observed as mutation carriers approached and surpassed their eYO. Conclusion: Functional disruption of the DMN occurs early in the course of autosomal dominant Alzheimer disease, beginning before clinically evident symptoms, and worsening with increased impairment. These findings suggest that DMN fcMRI may prove useful as a biomarker across a wide spectrum of disease, and support the feasibility of DMN fcMRI as a secondary endpoint in upcoming multicenter clinical trials in Alzheimer disease. PMID:23884042

  19. Current-mode implementation of processing modules in ART-based neural networks

    Science.gov (United States)

    Lopez-Alcantud, Jose-Alejandro; Hauer, Hans; Diaz-Madrid, Jose-Angel; Ruiz-Merino, Ramon

    2003-04-01

    This paper describes implementation of neural network processing layers using basic current-mode operating modules. The research work has been focused on the implementation of neural networks based on the Adaptive Resonance Theory, developed by S. Grossberg and G.A. Carpenter. The ART-based neural network whose operating modules have been choosen for development is the one called MART, proposed by F. Delgado, because of its complex architecture, auto--adaptive self-learning process, able to discard unmeaningful cathegories. Our presentation starts introducing the behaviour of MART with an analysis of its structure. The development described by this research work is focused on the monochannel block included in the main signal processing part of the MART neural network. The description of the computing algorithm of the layers inside a monochannel block are also provided in order to show what operational current-mode modules are needed (multiplier, divider, square-rooter, adder, substractor, absolute value, maximum and minimum evaluator...). Descriptions at schematic and layout levels of all the processing layers are given. All of them have been designed using AMS 0.35 micron technology with a supply voltage of 3.3 volts. The modules are designed to deal with input currents in the range of 20 to 50 microamps, showing a lineal behaviour and an output error of less than 10%, which is good enough for neural signal processing systems. The maximum frecuency of operation is around 200 kHz. Simulation results are included to show that the operation performed by the hardware designed matches the behaviour described by the MART neural network. For testing purposes we show the design of a monochannel block hardware implementation restricted to five inputs and three cathegories.

  20. Catching Functional Modes and Structural Communication in Dbl Family Rho Guanine Nucleotide Exchange Factors.

    Science.gov (United States)

    Raimondi, Francesco; Felline, Angelo; Fanelli, Francesca

    2015-09-28

    Computational approaches such as Principal Component Analysis (PCA) and Elastic Network Model-Normal Mode Analysis (ENM-NMA) are proving to be of great value in investigating relevant biological problems linked to slow motions with no demand in computer power. In this study, these approaches have been coupled to the graph theory-based Protein Structure Network (PSN) analysis to dissect functional dynamics and structural communication in the Dbl family of Rho Guanine Nucleotide Exchange Factors (RhoGEFs). They are multidomain proteins whose common structural feature is a DH-PH tandem domain deputed to the GEF activity that makes them play a central role in cell and cancer biology. While their common GEF action is accomplished by the DH domain, their regulatory mechanisms are highly variegate and depend on the PH and the additional domains as well as on interacting proteins. Major evolutionary-driven deformations as inferred from PCA concern the α6 helix of DH that dictates the orientation of the PH domain. Such deformations seem to depend on the mechanisms adopted by the GEF to prevent Rho binding, i.e. functional specialization linked to autoinhibition. In line with PCA, ENM-NMA indicates α6 and the linked PH domain as the portions of the tandem domain holding almost the totality of intrinsic and functional dynamics, with the α6/β1 junction acting as a hinge point for the collective motions of PH. In contrast, the DH domain holds a static scaffolding and hub behavior, with structural communication playing a central role in the regulatory actions by other domains/proteins. Possible allosteric communication pathways involving essentially DH were indeed found in those RhoGEFs acting as effectors of small or heterotrimeric RasGTPases. The employed methodology is suitable for deciphering structure/dynamics relationships in large sets of homologous or analogous proteins.

  1. Cognitive rehabilitation of working memory in juvenile multiple sclerosis-effects on cognitive functioning, functional MRI and network related connectivity.

    Science.gov (United States)

    Hubacher, Martina; DeLuca, John; Weber, Peter; Steinlin, Maja; Kappos, Ludwig; Opwis, Klaus; Penner, Iris-Katharina

    2015-01-01

    To assess possible effects of working memory (WM) training on cognitive functionality, functional MRI and brain connectivity in patients with juvenile MS. Cognitive status, fMRI and inter-network connectivity were assessed in 5 cases with juvenile MS aged between 12 and 18 years. Afterwards they received a computerized WM training for four weeks. Primary cognitive outcome measures were WM (visual and verbal) and alertness. Activation patterns related to WM were assessed during fMRI using an N-Back task with increasing difficulty. Inter-network connectivity analyses were focused on fronto-parietal (left and right), default-mode (dorsal and ventral) and the anterior salience network. Cognitive functioning, fMRI and inter-network connectivity were reassessed directly after the training and again nine months following training. Response to treatment was seen in two patients. These patients showed increased performance in WM and alertness after the training. These behavioural changes were accompanied by increased WM network activation and systematic changes in inter-network connectivity. The remaining participants were non-responders to treatment. Effects on cognitive performance were maintained up to nine months after training, whereas effects observed by fMRI disappeared. Responders revealed training effects on all applied outcome measures. Disease activity and general intelligence may be factors associated with response to treatment.

  2. Infection Functions for Virus Propagation in Computer Networks: An Empirical Study

    Institute of Scientific and Technical Information of China (English)

    YUAN Hua; WU Junjie; CHEN Guoqing

    2009-01-01

    There has been an increasing amount of interest in modeling virus propagation in recent years. However, the group-based infection mechanism of computer viruses is not well understood and the selec-tion of infection function in virus propagation modeling has not been well studied. This paper describes a point-to-group (P2G) infection mode to describe" virus propagation in networks with information sharing groups. Simulations compare the constant infection and I-type infection functions with the new E-type infec-lion function in the small-world-network environment. The simulation results show that the E-type infection function shows supedor performances to that of the traditional I-type infection function in modeling the P2G virus infection mechanism and the Ⅰ-type infection function shows better performance in modeling the ran-dom infection mechanism.

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

    Directory of Open Access Journals (Sweden)

    Susanne Kunkel

    2017-06-01

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

  4. 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 works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain's functioning at resting state.

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

    Science.gov (United States)

    The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity but MoA classification in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity mode of action using a recently published dataset contain...

  6. Radial basis function network design for chaotic time series prediction

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Chang Yong; Kim, Taek Soo; Park, Sang Hui [Yonsei University, Seoul (Korea, Republic of); Choi, Yoon Ho [Kyonggi University, Suwon (Korea, Republic of)

    1996-04-01

    In this paper, radial basis function networks with two hidden layers, which employ the K-means clustering method and the hierarchical training, are proposed for improving the short-term predictability of chaotic time series. Furthermore the recursive training method of radial basis function network using the recursive modified Gram-Schmidt algorithm is proposed for the purpose. In addition, the radial basis function networks trained by the proposed training methods are compared with the X.D. He A Lapedes`s model and the radial basis function network by non-recursive training method. Through this comparison, an improved radial basis function network for predicting chaotic time series is presented. (author). 17 refs., 8 figs., 3 tabs.

  7. 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.

  8. A new optimal sliding mode controller design using scalar sign function.

    Science.gov (United States)

    Singla, Mithun; Shieh, Leang-San; Song, Gangbing; Xie, Linbo; Zhang, Yongpeng

    2014-03-01

    This paper presents a new optimal sliding mode controller using the scalar sign function method. A smooth, continuous-time scalar sign function is used to replace the discontinuous switching function in the design of a sliding mode controller. The proposed sliding mode controller is designed using an optimal Linear Quadratic Regulator (LQR) approach. The sliding surface of the system is designed using stable eigenvectors and the scalar sign function. Controller simulations are compared with another existing optimal sliding mode controller. To test the effectiveness of the proposed controller, the controller is implemented on an aluminum beam with piezoceramic sensor and actuator for vibration control. This paper includes the control design and stability analysis of the new optimal sliding mode controller, followed by simulation and experimental results. The simulation and experimental results show that the proposed approach is very effective.

  9. Rational design of functional and tunable oscillating enzymatic networks

    Science.gov (United States)

    Semenov, Sergey N.; Wong, Albert S. Y.; van der Made, R. Martijn; Postma, Sjoerd G. J.; Groen, Joost; van Roekel, Hendrik W. H.; de Greef, Tom F. A.; Huck, Wilhelm T. S.

    2015-02-01

    Life is sustained by complex systems operating far from equilibrium and consisting of a multitude of enzymatic reaction networks. The operating principles of biology's regulatory networks are known, but the in vitro assembly of out-of-equilibrium enzymatic reaction networks has proved challenging, limiting the development of synthetic systems showing autonomous behaviour. Here, we present a strategy for the rational design of programmable functional reaction networks that exhibit dynamic behaviour. We demonstrate that a network built around autoactivation and delayed negative feedback of the enzyme trypsin is capable of producing sustained oscillating concentrations of active trypsin for over 65 h. Other functions, such as amplification, analog-to-digital conversion and periodic control over equilibrium systems, are obtained by linking multiple network modules in microfluidic flow reactors. The methodology developed here provides a general framework to construct dissipative, tunable and robust (bio)chemical reaction networks.

  10. The posterior medial cortex in urologic chronic pelvic pain syndrome: detachment from default mode network-a resting-state study from the MAPP Research Network.

    Science.gov (United States)

    Martucci, Katherine T; Shirer, William R; Bagarinao, Epifanio; Johnson, Kevin A; Farmer, Melissa A; Labus, Jennifer S; Apkarian, A Vania; Deutsch, Georg; Harris, Richard E; Mayer, Emeran A; Clauw, Daniel J; Greicius, Michael D; Mackey, Sean C

    2015-09-01

    Altered resting-state (RS) brain activity, as a measure of functional connectivity (FC), is commonly observed in chronic pain. Identifying a reliable signature pattern of altered RS activity for chronic pain could provide strong mechanistic insights and serve as a highly beneficial neuroimaging-based diagnostic tool. We collected and analyzed RS functional magnetic resonance imaging data from female patients with urologic chronic pelvic pain syndrome (N = 45) and matched healthy participants (N = 45) as part of an NIDDK-funded multicenter project (www.mappnetwork.org). Using dual regression and seed-based analyses, we observed significantly decreased FC of the default mode network to 2 regions in the posterior medial cortex (PMC): the posterior cingulate cortex (PCC) and the left precuneus (threshold-free cluster enhancement, family-wise error corrected P pain, sensory, motor, and emotion regulation processes (eg, insular cortex, dorsolateral prefrontal cortex, thalamus, globus pallidus, putamen, amygdala, hippocampus). The left precuneus demonstrated decreased FC to several regions of pain processing, reward, and higher executive functioning within the prefrontal (orbitofrontal, anterior cingulate, ventromedial prefrontal) and parietal cortices (angular gyrus, superior and inferior parietal lobules). The altered PMC connectivity was associated with several phenotype measures, including pain and urologic symptom intensity, depression, anxiety, quality of relationships, and self-esteem levels in patients. Collectively, these findings indicate that in patients with urologic chronic pelvic pain syndrome, regions of the PMC are detached from the default mode network, whereas neurological processes of self-referential thought and introspection may be joined to pain and emotion regulatory processes.

  11. Hierarchical organization of brain functional network during visual task

    CERN Document Server

    Zhuo, Zhao; Fu, Zhong-Qian; Zhang, Jie

    2011-01-01

    In this paper, the brain functional networks derived from high-resolution synchronous EEG time series during visual task are generated by calculating the phase synchronization among the time series. The hierarchical modular organizations of these networks are systematically investigated by the fast Girvan-Newman algorithm. At the same time, the spatially adjacent electrodes (corresponding to EEG channels) are clustered into functional groups based on anatomical parcellation of brain cortex, and this clustering information are compared to that of the functional network. The results show that the modular architectures of brain functional network are in coincidence with that from the anatomical structures over different levels of hierarchy, which suggests that population of neurons performing the same function excite and inhibit in identical rhythms. The structure-function relationship further reveals that the correlations among EEG time series in the same functional group are much stronger than those in differe...

  12. Bidirectional Control of Generalized Epilepsy Networks via Rapid Real-Time Switching of Firing Mode.

    Science.gov (United States)

    Sorokin, Jordan M; Davidson, Thomas J; Frechette, Eric; Abramian, Armen M; Deisseroth, Karl; Huguenard, John R; Paz, Jeanne T

    2017-01-04

    Thalamic relay neurons have well-characterized dual firing modes: bursting and tonic spiking. Studies in brain slices have led to a model in which rhythmic synchronized spiking (phasic firing) in a population of relay neurons leads to hyper-synchronous oscillatory cortico-thalamo-cortical rhythms that result in absence seizures. This model suggests that blocking thalamocortical phasic firing would treat absence seizures. However, recent in vivo studies in anesthetized animals have questioned this simple model. Here we resolve this issue by developing a real-time, mode-switching approach to drive thalamocortical neurons into or out of a phasic firing mode in two freely behaving genetic rodent models of absence epilepsy. Toggling between phasic and tonic firing in thalamocortical neurons launched and aborted absence seizures, respectively. Thus, a synchronous thalamocortical phasic firing state is required for absence seizures, and switching to tonic firing rapidly halts absences. This approach should be useful for modulating other networks that have mode-dependent behaviors.

  13. Emotion-Induced Topological Changes in Functional Brain Networks.

    Science.gov (United States)

    Park, Chang-Hyun; Lee, Hae-Kook; Kweon, Yong-Sil; Lee, Chung Tai; Kim, Ki-Tae; Kim, Young-Joo; Lee, Kyoung-Uk

    2016-01-01

    In facial expression perception, a distributed network is activated according to stimulus context. We proposed that an interaction between brain activation and stimulus context in response to facial expressions could signify a pattern of interactivity across the whole brain network beyond the face processing network. Functional magnetic resonance imaging data were acquired for 19 young healthy subjects who were exposed to either emotionally neutral or negative facial expressions. We constructed group-wise functional brain networks for 12 face processing areas [bilateral inferior occipital gyri (IOG), fusiform gyri (FG), superior temporal sulci (STS), amygdalae (AMG), inferior frontal gyri (IFG), and orbitofrontal cortices (OFC)] and for 73 whole brain areas, based on partial correlation of mean activation across subjects. We compared the topological properties of the networks with respect to functional distance-based measures, global and local efficiency, between the two types of face stimulus. In both face processing and whole brain networks, global efficiency was lower and local efficiency was higher for negative faces relative to neutral faces, indicating that network topology differed according to stimulus context. Particularly in the face processing network, emotion-induced changes in network topology were attributable to interactions between core (bilateral IOG, FG, and STS) and extended (bilateral AMG, IFG, and OFC) systems. These results suggest that changes in brain activation patterns in response to emotional face stimuli could be revealed as changes in the topological properties of functional brain networks for the whole brain as well as for face processing areas.

  14. Unveiling protein functions through the dynamics of the interaction network.

    Directory of Open Access Journals (Sweden)

    Irene Sendiña-Nadal

    Full Text Available Protein interaction networks have become a tool to study biological processes, either for predicting molecular functions or for designing proper new drugs to regulate the main biological interactions. Furthermore, such networks are known to be organized in sub-networks of proteins contributing to the same cellular function. However, the protein function prediction is not accurate and each protein has traditionally been assigned to only one function by the network formalism. By considering the network of the physical interactions between proteins of the yeast together with a manual and single functional classification scheme, we introduce a method able to reveal important information on protein function, at both micro- and macro-scale. In particular, the inspection of the properties of oscillatory dynamics on top of the protein interaction network leads to the identification of misclassification problems in protein function assignments, as well as to unveil correct identification of protein functions. We also demonstrate that our approach can give a network representation of the meta-organization of biological processes by unraveling the interactions between different functional classes.

  15. Deactivation of the default mode network as a marker of impaired consciousness: an fMRI study.

    Directory of Open Access Journals (Sweden)

    Julia Sophia Crone

    Full Text Available Diagnosis of patients with a disorder of consciousness is very challenging. Previous studies investigating resting state networks demonstrate that 2 main features of the so-called default mode network (DMN, metabolism and functional connectivity, are impaired in patients with a disorder of consciousness. However, task-induced deactivation--a third main feature of the DMN--has not been explored in a group of patients. Deactivation of the DMN is supposed to reflect interruptions of introspective processes. Seventeen patients with unresponsive wakefulness syndrome (UWS, former vegetative state, 8 patients in minimally conscious state (MCS, and 25 healthy controls were investigated with functional magnetic resonance imaging during a passive sentence listening task. Results show that deactivation in medial regions is reduced in MCS and absent in UWS patients compared to healthy controls. Moreover, behavioral scores assessing the level of consciousness correlate with deactivation in patients. On single-subject level, all control subjects but only 2 patients in MCS and 6 with UWS exposed deactivation. Interestingly, all patients who deactivated during speech processing (except for one showed activation in left frontal regions which are associated with conscious processing. Our results indicate that deactivation of the DMN can be associated with the level of consciousness by selecting those who are able to interrupt ongoing introspective processes. In consequence, deactivation of the DMN may function as a marker of consciousness.

  16. Shaped by the Past: The Default Mode Network Supports Cognition that Is Independent of Immediate Perceptual Input.

    Science.gov (United States)

    Konishi, Mahiko; McLaren, Donald George; Engen, Haakon; Smallwood, Jonathan

    2015-01-01

    Although many different accounts of the functions of the default mode network (DMN) have been proposed, few can adequately account for the spectrum of different cognitive functions that utilize this network. The current study used functional magnetic resonance imaging (fMRI) to explore the hypothesis that the role of the DMN in higher order cognition is to allow cognition to be shaped by information from stored representations rather than information in the immediate environment. Using a novel task paradigm, we observed increased BOLD activity in regions of the medial prefrontal cortex and posterior cingulate cortex when individuals made decisions on the location of shapes from the prior trial and decreased BOLD activity when individuals made decisions on the location of shapes on the current trial. These data are inconsistent with views of the DMN as a task-negative system or one that is sensitive only to stimuli with strong personal or emotional ties. Instead the involvement of the DMN when people make decisions about where a shape was, rather than where it is now, supports the hypothesis that the core hubs of the DMN allow cognition to be guided by information other than the immediate perceptual input. We propose that a variety of different forms of higher order thought (such as imagining the future or considering the perspective of another person) engage the DMN because these more complex introspective forms of higher order thought all depend on the capacity for cognition to be shaped by representations that are not present in the external environment.

  17. Musical Creativity "Revealed" in Brain Structure: Interplay between Motor, Default Mode, and Limbic Networks.

    Science.gov (United States)

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

    2016-02-18

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

  18. Dimensionality reduction in conic section function neural network

    Indian Academy of Sciences (India)

    Tulay Yildirim; Lale Ozyilmaz

    2002-12-01

    This paper details how dimensionality can be reduced in conic section function neural networks (CSFNN). This is particularly important for hardware implementation of networks. One of the main problems to be solved when considering the hardware design is the high connectivity requirement. If the effect that each of the network inputs has on the network output after training a neural network is known, then some inputs can be removed from the network. Consequently, the dimensionality of the network, and hence, the connectivity and the training time can be reduced. Sensitivity analysis, which extracts the cause and effect relationship between the inputs and outputs of the network, has been proposed as a method to achieve this and is investigated for Iris plant, thyroid disease and ionosphere databases. Simulations demonstrate the validity of the method used.

  19. Current-mode analog nonlinear function synthesizer structures

    CERN Document Server

    Popa, Cosmin Radu

    2013-01-01

    This book is dedicated to the analysis and design of analog CMOS nonlinear function synthesizer structures, based on original superior-order approximation functions. A variety of analog function synthesizer structures are discussed, based on accurate approximation functions.  Readers will be enabled to implement numerous circuit functions with applications in analog signal processing, including exponential, Gaussian or hyperbolic functions. Generalizing the methods for obtaining these particular functions, the author analyzes superior-order approximation functions, which represent the core for developing CMOS analog nonlinear function synthesizers.   ·         Describes novel methods for generating a multitude of circuit functions, based on superior-order improved accuracy approximation functions; ·         Presents techniques for analog function synthesizers that can be applied easily to a wide variety of analog signal processing circuits; ·         Enables the design of analog s...

  20. Dynamic network participation of functional connectivity hubs assessed by resting-state fMRI

    Science.gov (United States)

    Schaefer, Alexander; Margulies, Daniel S.; Lohmann, Gabriele; Gorgolewski, Krzysztof J.; Smallwood, Jonathan; Kiebel, Stefan J.; Villringer, Arno

    2014-01-01

    Network studies of large-scale brain connectivity have demonstrated that highly connected areas, or “hubs,” are a key feature of human functional and structural brain organization. We use resting-state functional MRI data and connectivity clustering to identify multi-network hubs and show that while hubs can belong to multiple networks their degree of integration into these different networks varies dynamically over time. The extent of the network variation was related to the connectedness of the hub. In addition, we found that these network dynamics were inversely related to positive self-generated thoughts reported by individuals and were further decreased with older age. Moreover, the left caudate varied its degree of participation between a default mode subnetwork and a limbic network. This variation was predictive of individual differences in the reports of past-related thoughts. These results support an association between ongoing thought processes and network dynamics and offer a new approach to investigate the brain dynamics underlying mental experience. PMID:24860458

  1. Mapping multiplex hubs in human functional brain networks

    Directory of Open Access Journals (Sweden)

    Alex Arenas

    2016-07-01

    Full Text Available Typical brain networks consist of many peripheral regions and a few highly centralones, i.e. hubs, playing key functional roles in cerebral inter-regional interactions. Studieshave shown that networks, obtained from the analysis of specific frequency components ofbrain activity, present peculiar architectures with unique profiles of region centrality. However,the identification of hubs in networks built from different frequency bands simultaneouslyis still a challenging problem, remaining largely unexplored. Here we identify eachfrequency component with one layer of a multiplex network and face this challenge by exploitingthe recent advances in the analysis of multiplex topologies. First, we show that eachfrequency band carries unique topological information, fundamental to accurately modelbrain functional networks. We then demonstrate that hubs in the multiplex network, in generaldifferent from those ones obtained after discarding or aggregating the measured signalsas usual, provide a more accurate map of brain’s most important functional regions, allowingto distinguish between healthy and schizophrenic populations better than conventionalnetwork approaches.

  2. Controlling the electrical conductive network formation of polymer nanocomposites via polymer functionalization.

    Science.gov (United States)

    Gao, Yangyang; Wu, Youping; Liu, Jun; Zhang, Liqun

    2016-12-06

    By adopting coarse-grained molecular dynamics simulations, the effect of polymer functionalization on the relationship between the microstructure and the electric percolation probability of nanorod filled polymer nanocomposites has been investigated. At a low chain functionalization degree, the nanorods in the polymer matrix form isolated aggregates with a local order structure. At a moderate chain functionalization degree, the local order structure of the nanorod aggregate is gradually broken up. Meanwhile, excessive functionalization chain beads can connect the isolated aggregates together, which leads to the maximum size of nanorod aggregation. At a high chain functionalization degree, it forms a single nanorod structure in the matrix. As a result, the highest percolation probability of the materials appears at the moderate chain functionalization degree, which is attributed to the formation of the tightly connected nanorod network by analyzing the main cluster. In addition, this optimum chain functionalization degree exists at two chain functionalization modes (random and diblock). Lastly, under the tensile field, even though the contact distance between nanorods nearly remains unchanged, the topological structure of the percolation network is broken down. While under the shear field, the contact distance between nanorods increases and the topological structure of the percolation network is broken down, which leads to a decrease in the percolation probability. In total, the topological structure of the percolation network dominates the percolation probability, which is not a necessary connection with the contact distance between nanorods. In summary, this work presents further understanding of the electric conductive properties of nanorod-filled nanocomposites with functionalized polymers.

  3. Mode S Beacon System: Functional Description. Revision D

    Science.gov (United States)

    1986-08-29

    by setting up a message text on some input device and pushing an appropriate "send" button . The presence of this message causes the DR code of every...NADIN IfEEC PRFEWK L 11T 1 PWACO$I OT! WAV! AfhCC L I PEFOMAC NOTE: TRACN = Terminl Radar AprNoahonrlacit = r .QLVVIfi CntolCete N~~~~flIN~ ~ ~ CLT...and indicators are retained, including: 4096 code selector Ident button ATCRBS reply indicator Power switch *Each Mode S transponder must be able to

  4. Performance Analysis of QoS in PMP Mode WiMax Networks

    CERN Document Server

    kamboj, Maninder Singh

    2010-01-01

    IEEE 802.16 standard supports two different topologies: point to multipoint (PMP) and Mesh. In this paper, a QoS mechanism for point to multipoint of IEEE 802.16 and BS scheduler for PMP Mode is proposed. This paper also describes quality of service over WiMAX networks. Average WiMAX delay, Average WiMAX load and Average WiMAX throughput at base station is analyzed and compared by applying different scheduler at Base station and at fixed nodes.

  5. Neural Dysregulation in Posttraumatic Stress Disorder: Evidence for Disrupted Equilibrium between Salience and Default Mode Brain Networks

    Science.gov (United States)

    Sripada, Rebecca K.; King, Anthony P.; Welsh, Robert C.; Garfinkel, Sarah N.; Wang, Xin; Sripada, Chandra S.; Liberzon, Israel

    2012-01-01

    Objective Convergent neuroimaging and neuropsychological research demonstrates disrupted attention and heightened threat sensitivity in PTSD. This might be linked to aberrations in large-scale networks subserving detection of salient stimuli, i.e. the salience network (SN), and stimulus-independent, internally-focused thought, i.e. the default mode network (DMN). Methods Resting state brain activity was measured in returning veterans who served in Iraq or Afghanistan with (n=15) and without PTSD (n=15) and in healthy community controls (n=15). Correlation coefficients were calculated between the time course of seed regions in key SN and DMN regions (posterior cingulate, ventromedial prefrontal cortex, and bilateral anterior insula) and all other voxels of the brain. Results Compared to control groups, PTSD participants showed reduced functional connectivity within DMN (between DMN seeds and other DMN regions), including rostral ACC/vmPFC (Z=3.31; p=.005, corrected) and hippocampus (Z=2.58; p=.005), and increased connectivity within SN (between insula seeds and other SN regions), including amygdala (Z=3.03; p=.01, corrected). PTSD participants also demonstrated increased cross-network connectivity. DMN seeds exhibited elevated connectivity with SN regions, including insula (Z=3.06; p=.03, corrected), putamen, and supplementary motor area (Z=4.14; Z=4.08; p<.001), and SN seeds exhibited elevated connectivity with DMN regions, including hippocampus (Z=3.10; p=.048, corrected). Conclusions During resting state scanning, PTSD participants showed reduced coupling within DMN, greater coupling within SN, and increased coupling between DMN and SN. Our findings suggest a relative dominance of threat-sensitive circuitry in PTSD, even in task-free conditions. Disequilibrium between large-scale networks subserving salience detection versus internally focused thought may be associated with PTSD pathophysiology. PMID:23115342

  6. Short-term antidepressant administration reduces default mode and task-positive network connectivity in healthy individuals during rest

    NARCIS (Netherlands)

    van Wingen, Guido A; Tendolkar, Indira; Urner, Maren; van Marle, Hein J; Denys, D.; Verkes, Robbert-Jan; Fernández, Guillén

    2014-01-01

    Resting-state studies in depressed patients have revealed increased connectivity within the default mode network (DMN) and task-positive network (TPN). This has been associated with heightened rumination, which is the tendency to repetitively think about symptoms of distress. Here, we performed a ph

  7. Short-term antidepressant administration reduces default mode and task-positive network connectivity in healthy individuals during rest

    NARCIS (Netherlands)

    Wingen, G.A. van; Tendolkar, I.; Urner, M.; Marle, H.J.F. van; Denys, D.; Verkes, R.J.; Fernandez, G.S.E.

    2013-01-01

    Resting-state studies in depressed patients have revealed increased connectivity within the default mode network (DMN) and task-positive network (TPN). This has been associated with heightened rumination, which is the tendency to repetitively think about symptoms of distress. Here, we performed a ph

  8. Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia.

    Science.gov (United States)

    Meda, Shashwath A; Ruaño, Gualberto; Windemuth, Andreas; O'Neil, Kasey; Berwise, Clifton; Dunn, Sabra M; Boccaccio, Leah E; Narayanan, Balaji; Kocherla, Mohan; Sprooten, Emma; Keshavan, Matcheri S; Tamminga, Carol A; Sweeney, John A; Clementz, Brett A; Calhoun, Vince D; Pearlson, Godfrey D

    2014-05-13

    The brain's default mode network (DMN) is highly heritable and is compromised in a variety of psychiatric disorders. However, genetic control over the DMN in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is largely unknown. Study subjects (n = 1,305) underwent a resting-state functional MRI scan and were analyzed by a two-stage approach. The initial analysis used independent component analysis (ICA) in 324 healthy controls, 296 SZ probands, 300 PBP probands, 179 unaffected first-degree relatives of SZ probands (SZREL), and 206 unaffected first-degree relatives of PBP probands to identify DMNs and to test their biomarker and/or endophenotype status. A subset of controls and probands (n = 549) then was subjected to a parallel ICA (para-ICA) to identify imaging-genetic relationships. ICA identified three DMNs. Hypo-connectivity was observed in both patient groups in all DMNs. Similar patterns observed in SZREL were restricted to only one network. DMN connectivity also correlated with several symptom measures. Para-ICA identified five sub-DMNs that were significantly associated with five different genetic networks. Several top-ranking SNPs across these networks belonged to previously identified, well-known psychosis/mood disorder genes. Global enrichment analyses revealed processes including NMDA-related long-term potentiation, PKA, immune response signaling, axon guidance, and synaptogenesis that significantly influenced DMN modulation in psychoses. In summary, we observed both unique and shared impairments in functional connectivity across the SZ and PBP cohorts; these impairments were selectively familial only for SZREL. Genes regulating specific neurodevelopment/transmission processes primarily mediated DMN disconnectivity. The study thus identifies biological pathways related to a widely researched quantitative trait that might suggest novel, targeted drug treatments for these diseases.

  9. Discovering and Analyzing Network Function and Structure

    Science.gov (United States)

    2015-07-08

    that the numerical linear algebra community has been seeking for a long time: sparse approximate inverses. To explain these, I recall that the classical...accelerate the computation. Our presently best algorithm computes the matrices L and U and applies them to solve a linear system in parallel time O(log6 n...imization, comes from Zhu, Ghahramani and Lafferty [ZGL+03], and only applies to undirected networks. Formally, one is given a network with vertex set

  10. Using Radial-basis Function Network for CLV

    Institute of Scientific and Technical Information of China (English)

    李纯青; 郑建国

    2002-01-01

    Analysis and comparing with three existing and popularly used forcasting customer lifetime value (CLV) methods, which are the Dwyer method, customer event-method and fitting method, and using performances of the existent artificial neural network, we apply the Radial-basis Function(RBF) network to forecast the CLV, the RBF network can approach the objective function partially. To every input/output pairs, it only needs adjust the weight a little and learn quickly which is very important to the forecast precision. Simulation and experimental results on the customers' data of a company in Shaanxi Province reveal the effectiveness and feasibility of the RBF network.

  11. Neural networks for function approximation in nonlinear control

    Science.gov (United States)

    Linse, Dennis J.; Stengel, Robert F.

    1990-01-01

    Two neural network architectures are compared with a classical spline interpolation technique for the approximation of functions useful in a nonlinear control system. A standard back-propagation feedforward neural network and a cerebellar model articulation controller (CMAC) neural network are presented, and their results are compared with a B-spline interpolation procedure that is updated using recursive least-squares parameter identification. Each method is able to accurately represent a one-dimensional test function. Tradeoffs between size requirements, speed of operation, and speed of learning indicate that neural networks may be practical for identification and adaptation in a nonlinear control environment.

  12. Electro-acupuncture at different acupoints modulating the relative specific brain functional network

    Science.gov (United States)

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

    2010-11-01

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

  13. Functional brain networks: great expectations, hard times and the big leap forward.

    Science.gov (United States)

    Papo, David; Zanin, Massimiliano; Pineda-Pardo, José Angel; Boccaletti, Stefano; Buldú, Javier M

    2014-10-05

    Many physical and biological systems can be studied using complex network theory, a new statistical physics understanding of graph theory. The recent application of complex network theory to the study of functional brain networks has generated great enthusiasm as it allows addressing hitherto non-standard issues in the field, such as efficiency of brain functioning or vulnerability to damage. However, in spite of its high degree of generality, the theory was originally designed to describe systems profoundly different from the brain. We discuss some important caveats in the wholesale application of existing tools and concepts to a field they were not originally designed to describe. At the same time, we argue that complex network theory has not yet been taken full advantage of, as many of its important aspects are yet to make their appearance in the neuroscience literature. Finally, we propose that, rather than simply borrowing from an existing theory, functional neural networks can inspire a fundamental reformulation of complex network theory, to account for its exquisitely complex functioning mode.

  14. Resting state functional network disruptions in a kainic acid model of temporal lobe epilepsy

    Directory of Open Access Journals (Sweden)

    Ravnoor Singh Gill

    2017-01-01

    Full Text Available We studied the graph topological properties of brain networks derived from resting-state functional magnetic resonance imaging in a kainic acid induced model of temporal lobe epilepsy (TLE in rats. Functional connectivity was determined by temporal correlation of the resting-state Blood Oxygen Level Dependent (BOLD signals between two brain regions during 1.5% and 2% isoflurane, and analyzed as networks in epileptic and control rats. Graph theoretical analysis revealed a significant increase in functional connectivity between brain areas in epileptic than control rats, and the connected brain areas could be categorized as a limbic network and a default mode network (DMN. The limbic network includes the hippocampus, amygdala, piriform cortex, nucleus accumbens, and mediodorsal thalamus, whereas DMN involves the medial prefrontal cortex, anterior and posterior cingulate cortex, auditory and temporal association cortex, and posterior parietal cortex. The TLE model manifested a higher clustering coefficient, increased global and local efficiency, and increased small-worldness as compared to controls, despite having a similar characteristic path length. These results suggest extensive disruptions in the functional brain networks, which may be the basis of altered cognitive, emotional and psychiatric symptoms in TLE.

  15. Dynamic reorganization of brain functional networks during cognition.

    Science.gov (United States)

    Bola, Michał; Sabel, Bernhard A

    2015-07-01

    How does cognition emerge from neural dynamics? The dominant hypothesis states that interactions among distributed brain regions through phase synchronization give basis for cognitive processing. Such phase-synchronized networks are transient and dynamic, established on the timescale of milliseconds in order to perform specific cognitive operations. But unlike resting-state networks, the complex organization of transient cognitive networks is typically not characterized within the graph theory framework. Thus, it is not known whether cognitive processing merely changes the strength of functional connections or, conversely, requires qualitatively new topological arrangements of functional networks. To address this question, we recorded high-density EEG while subjects performed a visual discrimination task. We conducted an event-related network analysis (ERNA) where source-space weighted functional networks were characterized with graph measures. ERNA revealed rapid, transient, and frequency-specific reorganization of the network's topology during cognition. Specifically, cognitive networks were characterized by strong clustering, low modularity, and strong interactions between hub-nodes. Our findings suggest that dense and clustered connectivity between the hub nodes belonging to different modules is the "network fingerprint" of cognition. Such reorganization patterns might facilitate global integration of information and provide a substrate for a "global workspace" necessary for cognition and consciousness to occur. Thus, characterizing topology of the event-related networks opens new vistas to interpret cognitive dynamics in the broader conceptual framework of graph theory. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. Time-perception network and default mode network are associated with temporal prediction in a periodic motion task

    Directory of Open Access Journals (Sweden)

    Fabiana Mesquita Carvalho

    2016-06-01

    Full Text Available The updating of prospective internal models is necessary to accurately predict future observations. Uncertainty-driven internal model updating has been studied using a variety of perceptual paradigms, and have revealed engagement of frontal and parietal areas. In a distinct literature, studies on temporal expectations have also characterized a time-perception network, which relies on temporal orienting of attention. However, the updating of prospective internal models is highly dependent on temporal attention, since temporal attention must be reoriented according to the current environmental demands. In this study we used fMRI to evaluate to what extend the continuous manipulation of temporal prediction would recruit update-related areas and the time-perception network areas. We developed an exogenous temporal task that combines rhythm cueing and time-to-contact principles to generate implicit temporal expectation. Two patterns of motion were created: periodic (simple harmonic oscillation and non-periodic (harmonic oscillation with variable acceleration. We found that non-periodic motion engaged the exogenous temporal orienting network, which includes the ventral premotor and inferior parietal cortices, and the cerebellum, as well as the presupplementary motor area, which has previously been implicated in internal model updating, and the motion-sensitive area MT+. Interestingly, we found a right-hemisphere preponderance suggesting the engagement of explicit timing mechanisms. We also show that the periodic motion condition, when compared to the non-periodic motion, activated a particular subset of the default-mode network (DMN midline areas, including the left dorsomedial prefrontal cortex, anterior cingulate cortex, and bilateral posterior cingulate cortex/precuneus. It suggests that the DMN plays a role in processing contextually expected information and supports recent evidence that the DMN may reflect the validation of prospective internal

  17. Changes in brain functional network connectivity after stroke

    Institute of Scientific and Technical Information of China (English)

    Wei Li; Yapeng Li; Wenzhen Zhu; Xi Chen

    2014-01-01

    Studies have shown that functional network connection models can be used to study brain net-work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their ifrst ever stroke. Using independent component analysis, six spatially independent components highly correlat-ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our ifndings suggest that functional network connectivity in stroke patients is more complex than that in hea-lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.

  18. Discursive Modes and Their Pedagogical Functions in Model-Based Inquiry (MBI) Classrooms

    Science.gov (United States)

    Campbell, Todd; Oh, Phil Seok; Neilson, Drew

    2012-01-01

    This research investigated the emergent discursive modes and their pedagogical functions found in model-based inquiry (MBI) science classrooms. A sample of four high school physics classrooms was video-recorded and analysed using a newly established discourse mode analysis framework. Qualitative methods were employed to identify the most salient…

  19. An Adaptive Sliding Mode Tracking Controller Using BP Neural Networks for a Class of Large-scale Nonlinear Systems

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A new type controller, BP neural-networks-based sliding mode controller is developed for a class of large-scale nonlinear systems with unknown bounds of high-order interconnections in this paper. It is shown that decentralized BP neural networks are used to adaptively learn the uncertainty bounds of interconnected subsystems in the Lyapunov sense, and the outputs of the decentralized BP neural networks are then used as the parameters of the sliding mode controller to compensate for the effects of subsystems uncertainties. Using this scheme, not only strong robustness with respect to uncertainty dynamics and nonlinearities can be obtained, but also the output tracking error between the actual output of each subsystem and the corresponding desired reference output can asymptotically converge to zero. A simulation example is presented to support the validity of the proposed BP neural-networks-based sliding mode controller.

  20. 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.

    2017-01-01

    Naturalistic environments have been demonstrated to promote relaxation and wellbeing. We assess opposing theoretical accounts for these effects through investigation of autonomic arousal and alterations of activation and functional connectivity within the default mode network (DMN) of the brain while participants listened to sounds from artificial and natural environments. We found no evidence for increased DMN activity in the naturalistic compared to artificial or control condition, however, seed based functional connectivity showed a shift from anterior to posterior midline functional coupling in the naturalistic condition. These changes were accompanied by an increase in peak high frequency heart rate variability, indicating an increase in parasympathetic activity in the naturalistic condition in line with the Stress Recovery Theory of nature exposure. Changes in heart rate and the peak high frequency were correlated with baseline functional connectivity within the DMN and baseline parasympathetic tone respectively, highlighting the importance of individual neural and autonomic differences in the response to nature exposure. Our findings may help explain reported health benefits of exposure to natural environments, through identification of alterations to autonomic activity and functional coupling within the DMN when listening to naturalistic sounds. PMID:28345604

  1. Robust fuzzy neural network sliding mode control scheme for IPMSM drives

    Science.gov (United States)

    Leu, V. Q.; Mwasilu, F.; Choi, H. H.; Lee, J.; Jung, J. W.

    2014-07-01

    This article proposes a robust fuzzy neural network sliding mode control (FNNSMC) law for interior permanent magnet synchronous motor (IPMSM) drives. The proposed control strategy not only guarantees accurate and fast command speed tracking but also it ensures the robustness to system uncertainties and sudden speed and load changes. The proposed speed controller encompasses three control terms: a decoupling control term which compensates for nonlinear coupling factors using nominal parameters, a fuzzy neural network (FNN) control term which approximates the ideal control components and a sliding mode control (SMC) term which is proposed to compensate for the errors of that approximation. Next, an online FNN training methodology, which is developed using the Lyapunov stability theorem and the gradient descent method, is proposed to enhance the learning capability of the FNN. Moreover, the maximum torque per ampere (MTPA) control is incorporated to maximise the torque generation in the constant torque region and increase the efficiency of the IPMSM drives. To verify the effectiveness of the proposed robust FNNSMC, simulations and experiments are performed by using MATLAB/Simulink platform and a TI TMS320F28335 DSP on a prototype IPMSM drive setup, respectively. Finally, the simulated and experimental results indicate that the proposed design scheme can achieve much better control performances (e.g. more rapid transient response and smaller steady-state error) when compared to the conventional SMC method, especially in the case that there exist system uncertainties.

  2. Implementations of artificial neural networks using current-mode pulse width modulation technique.

    Science.gov (United States)

    El-Masry, E I; Yang, H K; Yakout, M A

    1997-01-01

    The use of a current-mode pulse width modulation (CM-PWM) technique to implement analog artificial neural networks (ANNs) is presented. This technique can be used to efficiently implement the weighted summation operation (WSO) that are required in the realization of a general ANN. The sigmoidal transformation is inherently performed by the nonlinear transconductance amplifier, which is a key component in the current integrator used in the realization of WSO. The CM-PWM implementation results in a minimum silicon area, and therefore is suitable for very large scale neural systems. Other pronounced features of the CM-PWM implementation are its easy programmability, electronically adjustable gains of neurons, and modular structures. In this paper, all the current-mode CMOS circuits (building blocks) required for the realization of CM-PWM ANNs are presented and simulated. Four modules for modular design of ANNs are introduced. Also, it is shown that the CM-PWM technique is an efficient method for implementing discrete-time cellular neural networks (DT-CNNs). Two application examples are given: a winner-take-all circuit and a connected component detector.

  3. 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.

  4. Identification of significant intrinsic mode functions for the diagnosis of induction motor fault.

    Science.gov (United States)

    Cho, Sangjin; Shahriar, Md Rifat; Chong, Uipil

    2014-08-01

    For the analysis of non-stationary signals generated by a non-linear process like fault of an induction motor, empirical mode decomposition (EMD) is the best choice as it decomposes the signal into its natural oscillatory modes known as intrinsic mode functions (IMFs). However, some of these oscillatory modes obtained from a fault signal are not significant as they do not bear any fault signature and can cause misclassification of the fault instance. To solve this issue, a novel IMF selection algorithm is proposed in this work.

  5. 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.

  6. Layered neural networks with non-monotonic transfer functions

    Science.gov (United States)

    Katayama, Katsuki; Sakata, Yasuo; Horiguchi, Tsuyoshi

    2003-01-01

    We investigate storage capacity and generalization ability for two types of fully connected layered neural networks with non-monotonic transfer functions; random patterns are embedded into the networks by a Hebbian learning rule. One of them is a layered network in which a non-monotonic transfer function of even layers is different from that of odd layers. The other is a layered network with intra-layer connections, in which the non-monotonic transfer function of inter-layer is different from that of intra-layer, and inter-layered neurons and intra-layered neurons are updated alternately. We derive recursion relations for order parameters for those layered networks by the signal-to-noise ratio method. We clarify that the storage capacity and the generalization ability for those layered networks are enhanced in comparison with those with a conventional monotonic transfer function when non-monotonicity of the transfer functions is selected optimally. We also point out that some chaotic behavior appears in the order parameters for the layered networks when non-monotonicity of the transfer functions increases.

  7. The Efficiency of a Small-World Functional Brain Network

    Institute of Scientific and Technical Information of China (English)

    ZHAO Qing-Bai; ZHANG Xiao-Fei; SUI Dan-Ni; ZHOU Zhi-Jin; CHEN Qi-Cai; TANG Yi-Yuan

    2012-01-01

    We investigate whether the small-world topology of a functional brain network means high information processing efficiency by calculating the correlation between the small-world measures of a functional brain network and behavioral reaction during an imagery task.Functional brain networks are constructed by multichannel eventrelated potential data,in which the electrodes are the nodes and the functional connectivities between them are the edges.The results show that the correlation between small-world measures and reaction time is task-specific,such that in global imagery,there is a positive correlation between the clustering coefficient and reaction time,while in local imagery the average path length is positively correlated with the reaction time.This suggests that the efficiency of a functional brain network is task-dependent.%We investigate whether the small-world topology of a functional brain network means high information processing efficiency by calculating the correlation between the small-world measures of a functional brain network and behavioral reaction during an imagery task. Functional brain networks are constructed by multichannel event-related potential data, in which the electrodes are the nodes and the functional connectivities between them are the edges. The results show that the correlation between small-world measures and reaction time is task-specific, such that in global imagery, there is a positive correlation between the clustering coefficient and reaction time, while in local imagery the average path length is positively correlated with the reaction time. This suggests that the efficiency of a functional brain network is task-dependent.

  8. Spatio-temporal filtering for determination of common mode error in regional GNSS networks

    Science.gov (United States)

    Bogusz, Janusz; Gruszczynski, Maciej; Figurski, Mariusz; Klos, Anna

    2015-04-01

    The spatial correlation between different stations for individual components in the regional GNSS networks seems to be significant. The mismodelling in satellite orbits, the Earth orientation parameters (EOP), largescale atmospheric effects or satellite antenna phase centre corrections can all cause the regionally correlated errors. This kind of GPS time series errors are referred to as common mode errors (CMEs). They are usually estimated with the regional spatial filtering, such as the "stacking". In this paper, we show the stacking approach for the set of ASG-EUPOS permanent stations, assuming that spatial distribution of the CME is uniform over the whole region of Poland (more than 600 km extent). The ASG-EUPOS is a multifunctional precise positioning system based on the reference network designed for Poland. We used a 5- year span time series (2008-2012) of daily solutions in the ITRF2008 from Bernese 5.0 processed by the Military University of Technology EPN Local Analysis Centre (MUT LAC). At the beginning of our analyses concerning spatial dependencies, the correlation coefficients between each pair of the stations in the GNSS network were calculated. This analysis shows that spatio-temporal behaviour of the GPS-derived time series is not purely random, but there is the evident uniform spatial response. In order to quantify the influence of filtering using CME, the norms L1 and L2 were determined. The values of these norms were calculated for the North, East and Up components twice: before performing the filtration and after stacking. The observed reduction of the L1 and L2 norms was up to 30% depending on the dimension of the network. However, the question how to define an optimal size of CME-analysed subnetwork remains unanswered in this research, due to the fact that our network is not extended enough.

  9. On the classification enhancement of radial basis function networks

    NARCIS (Netherlands)

    Ciftcioglu, O.; Durmisevic, S.; Sariyildiz, I.S.

    2001-01-01

    Artificial neural networks are powerfultools for analysing information expressed as data sets, which contain complex nonlinear relationships to be identified and classified. In particular radial basis function (RBF) neural networks have outstanding features for this. However, due to far reaching imp

  10. Functional expansion representations of artificial neural networks

    Science.gov (United States)

    Gray, W. Steven

    1992-01-01

    In the past few years, significant interest has developed in using artificial neural networks to model and control nonlinear dynamical systems. While there exists many proposed schemes for accomplishing this and a wealth of supporting empirical results, most approaches to date tend to be ad hoc in nature and rely mainly on heuristic justifications. The purpose of this project was to further develop some analytical tools for representing nonlinear discrete-time input-output systems, which when applied to neural networks would give insight on architecture selection, pruning strategies, and learning algorithms. A long term goal is to determine in what sense, if any, a neural network can be used as a universal approximator for nonliner input-output maps with memory (i.e., realized by a dynamical system). This property is well known for the case of static or memoryless input-output maps. The general architecture under consideration in this project was a single-input, single-output recurrent feedforward network.

  11. Whole-brain functional networks in cognitively normal, mild cognitive impairment, and Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Eun Hyun Seo

    Full Text Available The conceptual significance of understanding functional brain alterations and cognitive deficits associated with Alzheimer's disease (AD process has been widely established. However, the whole-brain functional networks of AD and its prodromal stage, mild cognitive impairment (MCI, are not well clarified yet. In this study, we compared the characteristics of the whole-brain functional networks among cognitively normal (CN, MCI, and AD individuals by applying graph theoretical analyses to [(18F] fluorodeoxyglucose positron emission tomography (FDG-PET data. Ninety-four CN elderly, 183 with MCI, and 216 with AD underwent clinical evaluation and FDG-PET scan. The overall small-world property as seen in the CN whole-brain network was preserved in MCI and AD. In contrast, individual parameters of the network were altered with the following patterns of changes: local clustering of networks was lower in both MCI and AD compared to CN, while path length was not different among the three groups. Then, MCI had a lower level of local clustering than AD. Subgroup analyses for AD also revealed that very mild AD had lower local clustering and shorter path length compared to mild AD. Regarding the local properties of the whole-brain networks, MCI and AD had significantly decreased normalized betweenness centrality in several hubs regionally associated with the default mode network compared to CN. Our results suggest that the functional integration in whole-brain network progressively declines due to the AD process. On the other hand, functional relatedness between neighboring brain regions may not gradually decrease, but be the most severely altered in MCI stage and gradually re-increase in clinical AD stages.

  12. Constructing analytically mode functions of inflation with trans-Planckian physics

    CERN Document Server

    Zhu, Tao; Cleaver, Gerald; Kirsten, Klaus; Sheng, Qin

    2013-01-01

    We present a technique, {\\em the uniform asymptotic approximation}, to construct analytically solutions of the mode functions of inflation with trans-Planckian physics, in which the dispersion relations are nonlinear and have various turning points (zeros). Each turning point can be a single, double or higher multiple zero. Error bounds are constructed explicitly. It is shown that the analytical solutions describe the exact evolution of the mode function extremely well even only to the first-order approximations.

  13. A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks.

    Science.gov (United States)

    Sridharan, Devarajan; Levitin, Daniel J; Menon, Vinod

    2008-08-26

    Cognitively demanding tasks that evoke activation in the brain's central-executive network (CEN) have been consistently shown to evoke decreased activation (deactivation) in the default-mode network (DMN). The neural mechanisms underlying this switch between activation and deactivation of large-scale brain networks remain completely unknown. Here, we use functional magnetic resonance imaging (fMRI) to investigate the mechanisms underlying switching of brain networks in three different experiments. We first examined this switching process in an auditory event segmentation task. We observed significant activation of the CEN and deactivation of the DMN, along with activation of a third network comprising the right fronto-insular cortex (rFIC) and anterior cingulate cortex (ACC), when participants perceived salient auditory event boundaries. Using chronometric techniques and Granger causality analysis, we show that the rFIC-ACC network, and the rFIC, in particular, plays a critical and causal role in switching between the CEN and the DMN. We replicated this causal connectivity pattern in two additional experiments: (i) a visual attention "oddball" task and (ii) a task-free resting state. These results indicate that the rFIC is likely to play a major role in switching between distinct brain networks across task paradigms and stimulus modalities. Our findings have important implications for a unified view of network mechanisms underlying both exogenous and endogenous cognitive control.

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

    Science.gov (United States)

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

    2017-08-01

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

  15. Magnetoencephalographic alpha band connectivity reveals differential Default Mode Network interactions during focused attention and open monitoring meditation

    Directory of Open Access Journals (Sweden)

    Laura eMarzetti

    2014-10-01

    Full Text Available 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 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 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 posterior cingulate cortex with left medial prefrontal cortex 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 and DMN networks. Our results support the idea that the interplay between the DMN and the fronto-parietal network in the alpha band is crucial for the transition from resting state to different meditative states.

  16. 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.

  17. Statistical Network Analysis for Functional MRI: Mean Networks and Group Comparisons.

    Directory of Open Access Journals (Sweden)

    Cedric E Ginestet

    2014-05-01

    Full Text Available Comparing networks in neuroscience is hard, because the topological properties of a given network are necessarily dependent on the number of edges of that network. This problem arises in the analysis of both weighted and unweighted networks. The term density is often used in this context, in order to refer to the mean edge weight of a weighted network, or to the number of edges in an unweighted one. Comparing families of networks is therefore statistically difficult because differences in topology are necessarily associated with differences in density. In this review paper, we consider this problem from two different perspectives, which include (i the construction of summary networks, such as how to compute and visualize the mean network from a sample of network-valued data points; and (ii how to test for topological differences, when two families of networks also exhibit significant differences in density. In the first instance, we show that the issue of summarizing a family of networks can be conducted by either adopting a mass-univariate approach, which produces a statistical parametric network (SPN, or by directly computing the mean network, provided that a metric has been specified on the space of all networks with a given number of nodes. In the second part of this review, we then highlight the inherent problems associated with the comparison of topological functions of families of networks that differ in density. In particular, we show that a wide range of topological summaries, such as global efficiency and network modularity are highly sensitive to differences in density. Moreover, these problems are not restricted to unweighted metrics, as we demonstrate that the same issues remain present when considering the weighted versions of these metrics. We conclude by encouraging caution, when reporting such statistical comparisons, and by emphasizing the importance of constructing summary networks.

  18. Joint Modelling of Structural and Functional Brain Networks

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther; Herlau, Tue; Mørup, Morten

    Functional and structural magnetic resonance imaging have become the most important noninvasive windows to the human brain. A major challenge in the analysis of brain networks is to establish the similarities and dissimilarities between functional and structural connectivity. We formulate a non...... significant structures that are consistently shared across subjects and data splits. This provides an unsupervised approach for modeling of structure-function relations in the brain and provides a general framework for multimodal integration.......-parametric Bayesian network model which allows for joint modelling and integration of multiple networks. We demonstrate the model’s ability to detect vertices that share structure across networks jointly in functional MRI (fMRI) and diffusion MRI (dMRI) data. Using two fMRI and dMRI scans per subject, we establish...

  19. Universal approximation by radial basis function networks of Delsarte translates.

    Science.gov (United States)

    Arteaga, Cristian; Marrero, Isabel

    2013-10-01

    We prove that, under certain mild conditions on the kernel function (or activation function), the family of radial basis function neural networks obtained by replacing the usual translation with the Delsarte one, and taking the same smoothing factor in all kernel nodes, has the universal approximation property.

  20. Decreased mental time travel to the past correlates with default-mode network disintegration under lysergic acid diethylamide.

    Science.gov (United States)

    Speth, Jana; Speth, Clemens; Kaelen, Mendel; Schloerscheidt, Astrid M; Feilding, Amanda; Nutt, David J; Carhart-Harris, Robin L

    2016-04-01

    This paper reports on the effects of LSD on mental time travel during spontaneous mentation. Twenty healthy volunteers participated in a placebo-controlled crossover study, incorporating intravenous administration of LSD (75 μg) and placebo (saline) prior to functional magnetic resonance imaging (fMRI). Six independent, blind judges analysed mentation reports acquired during structured interviews performed shortly after the functional magnetic resonance imaging (fMRI) scans (approximately 2.5 h post-administration). Within each report, specific linguistic references to mental spaces for the past, present and future were identified. Results revealed significantly fewer mental spaces for the past under LSD and this effect correlated with the general intensity of the drug's subjective effects. No differences in the number of mental spaces for the present or future were observed. Consistent with the previously proposed role of the default-mode network (DMN) in autobiographical memory recollection and ruminative thought, decreased resting-state functional connectivity (RSFC) within the DMN correlated with decreased mental time travel to the past. These results are discussed in relation to potential therapeutic applications of LSD and related psychedelics, e.g. in the treatment of depression, for which excessive reflection on one's past, likely mediated by DMN functioning, is symptomatic.

  1. Functional Reorganizations of Brain Network in Prelingually Deaf Adolescents

    OpenAIRE

    Wenjing Li; Jianhong Li; Jieqiong Wang; Peng Zhou; Zhenchang Wang; Junfang Xian; Huiguang He

    2016-01-01

    Previous neuroimaging studies suggested structural or functional brain reorganizations occurred in prelingually deaf subjects. However, little is known about the reorganizations of brain network architectures in prelingually deaf adolescents. The present study aims to investigate alterations of whole-brain functional network using resting-state fMRI and graph theory analysis. We recruited 16 prelingually deaf adolescents (10~18 years) and 16 normal controls matched in age and gender. Brain ne...

  2. Nodal centrality of functional network in the differentiation of schizophrenia.

    Science.gov (United States)

    Cheng, Hu; Newman, Sharlene; Goñi, Joaquín; Kent, Jerillyn S; Howell, Josselyn; Bolbecker, Amanda; Puce, Aina; O'Donnell, Brian F; Hetrick, William P

    2015-10-01

    A disturbance in the integration of information during mental processing has been implicated in schizophrenia, possibly due to faulty communication within and between brain regions. Graph theoretic measures allow quantification of functional brain networks. Functional networks are derived from correlations between time courses of brain regions. Group differences between SZ and control groups have been reported for functional network properties, but the potential of such measures to classify individual cases has been little explored. We tested whether the network measure of betweenness centrality could classify persons with schizophrenia and normal controls. Functional networks were constructed for 19 schizophrenic patients and 29 non-psychiatric controls based on resting state functional MRI scans. The betweenness centrality of each node, or fraction of shortest-paths that pass through it, was calculated in order to characterize the centrality of the different regions. The nodes with high betweenness centrality agreed well with hub nodes reported in previous studies of structural and functional networks. Using a linear support vector machine algorithm, the schizophrenia group was differentiated from non-psychiatric controls using the ten nodes with the highest betweenness centrality. The classification accuracy was around 80%, and stable against connectivity thresholding. Better performance was achieved when using the ranks as feature space as opposed to the actual values of betweenness centrality. Overall, our findings suggest that changes in functional hubs are associated with schizophrenia, reflecting a variation of the underlying functional network and neuronal communications. In addition, a specific network property, betweenness centrality, can classify persons with SZ with a high level of accuracy.

  3. Language networks in children: Evidence from functional MRI studies

    OpenAIRE

    2009-01-01

    We review functional MRI and other neuroimaging studies of language skills in children from infancy to adulthood. These studies show developmental changes in the networks of brain regions supporting language, which can be affected by brain injuries or neurological disorders. Particular aspects of language rely on networks that lateralize to the dominant hemisphere; others rely on bilateral or non-dominant mechanisms. Multiple fMRI tasks for pediatric patients characterize functional brain reo...

  4. Studying the default mode and its mindfulness-induced changes using EEG functional connectivity.

    Science.gov (United States)

    Berkovich-Ohana, Aviva; Glicksohn, Joseph; Goldstein, Abraham

    2014-10-01

    The default mode network (DMN) has been largely studied by imaging, but not yet by neurodynamics, using electroencephalography (EEG) functional connectivity (FC). mindfulness meditation (MM), a receptive, non-elaborative training is theorized to lower DMN activity. We explored: (i) the usefulness of EEG-FC for investigating the DMN and (ii) the MM-induced EEG-FC effects. To this end, three MM groups were compared with controls, employing EEG-FC (-MPC, mean phase coherence). Our results show that: (i) DMN activity was identified as reduced overall inter-hemispheric gamma MPC during the transition from resting state to a time production task and (ii) MM-induced a state increase in alpha MPC as well as a trait decrease in EEG-FC. The MM-induced EEG-FC decrease was irrespective of expertise or band. Specifically, there was a relative reduction in right theta MPC, and left alpha and gamma MPC. The left gamma MPC was negatively correlated with MM expertise, possibly related to lower internal verbalization. The trait lower gamma MPC supports the notion of MM-induced reduction in DMN activity, related with self-reference and mind-wandering. This report emphasizes the possibility of studying the DMN using EEG-FC as well as the importance of studying meditation in relation to it.

  5. Computing black hole partition functions from quasinormal modes

    CERN Document Server

    Arnold, Peter; Vaman, Diana

    2016-01-01

    We propose a method of computing one-loop determinants in black hole spacetimes (with emphasis on asymptotically anti-de Sitter black holes) that may be used for numerics when completely-analytic results are unattainable. The method utilizes the expression for one-loop determinants in terms of quasinormal frequencies determined by Denef, Hartnoll and Sachdev in [1]. A necessary ingredient is a refined regularization scheme to regulate the contributions of individual fixed-momentum sectors to the partition function. To this end, we formulate an effective two-dimensional problem in which a natural refinement of standard heat kernel techniques can be used to account for contributions to the partition function at fixed momentum. We test our method in a concrete case by reproducing the scalar one-loop determinant in the BTZ black hole background. We then discuss the application of such techniques to more complicated spacetimes.

  6. Greater default-mode network abnormalities compared to high order visual processing systems in amnestic mild cognitive impairment: an integrated multi-modal MRI study.

    Science.gov (United States)

    Sala-Llonch, Roser; Bosch, Beatriz; Arenaza-Urquijo, Eider M; Rami, Lorena; Bargalló, Núria; Junqué, Carme; Molinuevo, José-Luis; Bartrés-Faz, David

    2010-01-01

    We conducted an integrated multi-modal magnetic resonance imaging (MRI) study based on functional MRI (fMRI) data during a complex but cognitively preserved visual task in 15 amnestic mild cognitive impairment (a-MCI) patients and 15 Healthy Elders (HE). Independent Component Analysis of fMRI data identified a functional network containing an Activation Task Related Pattern (ATRP), including regions of the dorsal and ventral visual stream, and a Deactivation Task Related Pattern network (DTRP), with high spatial correspondence with the default-mode network (DMN). Gray matter (GM) volumes of the underlying ATRP and DTRP cortical areas were measured, and probabilistic tractography (based on diffusion MRI) identified fiber pathways within each functional network. For the ATRP network, a-MCI patients exhibited increased fMRI responses in inferior-ventral visual areas, possibly reflecting compensatory activations for more compromised dorsal regions. However, no significant GM or white matter group differences were observed within the ATRP network. For the DTRP/DMN, a-MCI showed deactivation deficits and reduced GM volumes in the posterior cingulate/precuneus, excessive deactivations in the inferior parietal lobe, and less fiber tract integrity in the cingulate bundles. Task performance correlated with DTRP-functionality in the HE group. Besides allowing the identification of functional reorganizations in the cortical network directly processing the task-stimuli, these findings highlight the importance of conducting integrated multi-modal MRI studies in MCI based on spared cognitive domains in order to identify functional abnormalities in critical areas of the DMN and their precise anatomical substrates. These latter findings may reflect early neuroimaging biomarkers in dementia.

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

    Directory of Open Access Journals (Sweden)

    Petro D. Lezhniuk

    2017-06-01

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

  8. Creativity and the default network: A functional connectivity analysis of the creative brain at rest.

    Science.gov (United States)

    Beaty, Roger E; Benedek, Mathias; Wilkins, Robin W; Jauk, Emanuel; Fink, Andreas; Silvia, Paul J; Hodges, Donald A; Koschutnig, Karl; Neubauer, Aljoscha C

    2014-11-01

    The present research used resting-state functional magnetic resonance imaging (fMRI) to examine whether the ability to generate creative ideas corresponds to differences in the intrinsic organization of functional networks in the brain. We examined the functional connectivity between regions commonly implicated in neuroimaging studies of divergent thinking, including the inferior prefrontal cortex and the core hubs of the default network. Participants were prescreened on a battery of divergent thinking tests and assigned to high- and low-creative groups based on task performance. Seed-based functional connectivity analysis revealed greater connectivity between the left inferior frontal gyrus (IFG) and the entire default mode network in the high-creative group. The right IFG also showed greater functional connectivity with bilateral inferior parietal cortex and the left dorsolateral prefrontal cortex in the high-creative group. The results suggest that the ability to generate creative ideas is characterized by increased functional connectivity between the inferior prefrontal cortex and the default network, pointing to a greater cooperation between brain regions associated with cognitive control and low-level imaginative processes. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. Creativity and the default network: A functional connectivity analysis of the creative brain at rest☆

    Science.gov (United States)

    Beaty, Roger E.; Benedek, Mathias; Wilkins, Robin W.; Jauk, Emanuel; Fink, Andreas; Silvia, Paul J.; Hodges, Donald A.; Koschutnig, Karl; Neubauer, Aljoscha C.

    2014-01-01

    The present research used resting-state functional magnetic resonance imaging (fMRI) to examine whether the ability to generate creative ideas corresponds to differences in the intrinsic organization of functional networks in the brain. We examined the functional connectivity between regions commonly implicated in neuroimaging studies of divergent thinking, including the inferior prefrontal cortex and the core hubs of the default network. Participants were prescreened on a battery of divergent thinking tests and assigned to high- and low-creative groups based on task performance. Seed-based functional connectivity analysis revealed greater connectivity between the left inferior frontal gyrus (IFG) and the entire default mode network in the high-creative group. The right IFG also showed greater functional connectivity with bilateral inferior parietal cortex and the left dorsolateral prefrontal cortex in the high-creative group. The results suggest that the ability to generate creative ideas is characterized by increased functional connectivity between the inferior prefrontal cortex and the default network, pointing to a greater cooperation between brain regions associated with cognitive control and low-level imaginative processes. PMID:25245940

  10. Does sleep restore the topology of functional brain networks?

    Science.gov (United States)

    Koenis, Maria M G; Romeijn, Nico; Piantoni, Giovanni; Verweij, Ilse; Van der Werf, Ysbrand D; Van Someren, Eus J W; Stam, Cornelis J

    2013-02-01

    Previous studies have shown that healthy anatomical as well as functional brain networks have small-world properties and become less optimal with brain disease. During sleep, the functional brain network becomes more small-world-like. Here we test the hypothesis that the functional brain network during wakefulness becomes less optimal after sleep deprivation (SD). Electroencephalography (EEG) was recorded five times a day after a night of SD and after a night of normal sleep in eight young healthy subjects, both during eyes-closed and eyes-open resting state. Overall synchronization was determined with the synchronization likelihood (SL) and the phase lag index (PLI). From these coupling strength matrices the normalized clustering coefficient C (a measurement of local clustering) and path length L (a measurement of global integration) were computed. Both measures were normalized by dividing them by their corresponding C-s and L-s values of random control networks. SD reduced alpha band C/C-s and L/L-s and theta band C/C-s during eyes-closed resting state. In contrast, SD increased gamma-band C/C-s and L/L-s during eyes-open resting state. Functional relevance of these changes in network properties was suggested by their association with sleep deprivation-induced performance deficits on a sustained attention simple reaction time task. The findings indicate that SD results in a more random network of alpha-coupling and a more ordered network of gamma-coupling. The present study shows that SD induces frequency-specific changes in the functional network topology of the brain, supporting the idea that sleep plays a role in the maintenance of an optimal functional network. Copyright © 2011 Wiley Periodicals, Inc.

  11. A Statistical Method to Distinguish Functional Brain Networks

    Science.gov (United States)

    Fujita, André; Vidal, Maciel C.; Takahashi, Daniel Y.

    2017-01-01

    One major problem in neuroscience is the comparison of functional brain networks of different populations, e.g., distinguishing the networks of controls and patients. Traditional algorithms are based on search for isomorphism between networks, assuming that they are deterministic. However, biological networks present randomness that cannot be well modeled by those algorithms. For instance, functional brain networks of distinct subjects of the same population can be different due to individual characteristics. Moreover, networks of subjects from different populations can be generated through the same stochastic process. Thus, a better hypothesis is that networks are generated by random processes. In this case, subjects from the same group are samples from the same random process, whereas subjects from different groups are generated by distinct processes. Using this idea, we developed a statistical test called ANOGVA to test whether two or more populations of graphs are generated by the same random graph model. Our simulations' results demonstrate that we can precisely control the rate of false positives and that the test is powerful to discriminate random graphs generated by different models and parameters. The method also showed to be robust for unbalanced data. As an example, we applied ANOGVA to an fMRI dataset composed of controls and patients diagnosed with autism or Asperger. ANOGVA identified the cerebellar functional sub-network as statistically different between controls and autism (p < 0.001). PMID:28261045

  12. Probing the statistical properties of CMB $B$-mode polarization through Minkowski Functionals

    CERN Document Server

    Zhao, W

    2015-01-01

    The detection of the magnetic type $B$-mode polarization is the main goal of future cosmic microwave background (CMB) experiments. In the standard model, the $B$-mode map is a strongly non-gaussian field due to the lensed component. Besides the two-point correlation function, the other statistics are also very important to dig the information of the polarization map. In this paper, we employ the Minkowski functionals to study the morphological properties of the lensed $B$-mode maps. We find that the deviations from Gaussianity are very significant for both full and partial-sky surveys. As an application of the analysis, we investigate the morphological imprints of the foreground residuals in the $B$-mode map. We find that even for very tiny foreground residuals, the effects on the map can be detected by the Minkowski functional analysis. Therefore, it provides a complementary way to investigate the foreground contaminations in the CMB studies.

  13. Probing the statistical properties of CMB B-mode polarization through Minkowski functionals

    Science.gov (United States)

    Santos, Larissa; Wang, Kai; Zhao, Wen

    2016-07-01

    The detection of the magnetic type B-mode polarization is the main goal of future cosmic microwave background (CMB) experiments. In the standard model, the B-mode map is a strong non-gaussian field due to the CMB lensing component. Besides the two-point correlation function, the other statistics are also very important to dig the information of the polarization map. In this paper, we employ the Minkowski functionals to study the morphological properties of the lensed B-mode maps. We find that the deviations from Gaussianity are very significant for both full and partial-sky surveys. As an application of the analysis, we investigate the morphological imprints of the foreground residuals in the B-mode map. We find that even for very tiny foreground residuals, the effects on the map can be detected by the Minkowski functional analysis. Therefore, it provides a complementary way to investigate the foreground contaminations in the CMB studies.

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

    Science.gov (United States)

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

    2017-01-01

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

  15. Intelligent nonsingular terminal sliding-mode control using MIMO Elman neural network for piezo-flexural nanopositioning stage.

    Science.gov (United States)

    Lin, Faa-Jeng; Lee, Shih-Yang; Chou, Po-Huan

    2012-12-01

    The objective of this study is to develop an intelligent nonsingular terminal sliding-mode control (INTSMC) system using an Elman neural network (ENN) for the threedimensional motion control of a piezo-flexural nanopositioning stage (PFNS). First, the dynamic model of the PFNS is derived in detail. Then, to achieve robust, accurate trajectory-tracking performance, a nonsingular terminal sliding-mode control (NTSMC) system is proposed for the tracking of the reference contours. The steady-state response of the control system can be improved effectively because of the addition of the nonsingularity in the NTSMC. Moreover, to relax the requirements of the bounds and discard the switching function in NTSMC, an INTSMC system using a multi-input-multioutput (MIMO) ENN estimator is proposed to improve the control performance and robustness of the PFNS. The ENN estimator is proposed to estimate the hysteresis phenomenon and lumped uncertainty, including the system parameters and external disturbance of the PFNS online. Furthermore, the adaptive learning algorithms for the training of the parameters of the ENN online are derived using the Lyapunov stability theorem. In addition, two robust compensators are proposed to confront the minimum reconstructed errors in INTSMC. Finally, some experimental results for the tracking of various contours are given to demonstrate the validity of the proposed INTSMC system for PFNS.

  16. A Cutting Pattern Recognition Method for Shearers Based on Improved Ensemble Empirical Mode Decomposition and a Probabilistic Neural Network

    Directory of Open Access Journals (Sweden)

    Jing Xu

    2015-10-01

    Full Text Available In order to guarantee the stable operation of shearers and promote construction of an automatic coal mining working face, an online cutting pattern recognition method with high accuracy and speed based on Improved Ensemble Empirical Mode Decomposition (IEEMD and Probabilistic Neural Network (PNN is proposed. An industrial microphone is installed on the shearer and the cutting sound is collected as the recognition criterion to overcome the disadvantages of giant size, contact measurement and low identification rate of traditional detectors. To avoid end-point effects and get rid of undesirable intrinsic mode function (IMF components in the initial signal, IEEMD is conducted on the sound. The end-point continuation based on the practical storage data is performed first to overcome the end-point effect. Next the average correlation coefficient, which is calculated by the correlation of the first IMF with others, is introduced to select essential IMFs. Then the energy and standard deviation of the reminder IMFs are extracted as features and PNN is applied to classify the cutting patterns. Finally, a simulation example, with an accuracy of 92.67%, and an industrial application prove the efficiency and correctness of the proposed method.

  17. Density-dependence of functional spiking networks in vitro

    Energy Technology Data Exchange (ETDEWEB)

    Ham, Michael I [Los Alamos National Laboratory; Gintautuas, Vadas [Los Alamos National Laboratory; Rodriguez, Marko A [Los Alamos National Laboratory; Bettencourt, Luis M A [Los Alamos National Laboratory; Bennett, Ryan [UNIV OF NORTH TEXAS; Santa Maria, Cara L [UNIV OF NORTH TEXAS

    2008-01-01

    During development, the mammalian brain differentiates into specialized regions with unique functional abilities. While many factors contribute to this functional specialization, we explore the effect neuronal density can have on neuronal interactions. Two types of networks, dense (50,000 neurons and glia support cells) and sparse (12,000 neurons and glia support cells), are studied. A competitive first response model is applied to construct activation graphs that represent pairwise neuronal interactions. By observing the evolution of these graphs during development in vitro we observe that dense networks form activation connections earlier than sparse networks, and that link-!llltropy analysis of the resulting dense activation graphs reveals that balanced directional connections dominate. Information theoretic measures reveal in addition that early functional information interactions (of order 3) are synergetic in both dense and sparse networks. However, during development in vitro, such interactions become redundant in dense, but not sparse networks. Large values of activation graph link-entropy correlate strongly with redundant ensembles observed in the dense networks. Results demonstrate differences between dense and sparse networks in terms of informational groups, pairwise relationships, and activation graphs. These differences suggest that variations in cell density may result in different functional specialization of nervous system tissue also in vivo.

  18. A framework for interpreting functional networks in schizophrenia

    Directory of Open Access Journals (Sweden)

    Peter eWilliamson

    2012-06-01

    Full Text Available Some promising genetic correlates of schizophrenia have emerged in recent years but none explain more than a small fraction of cases. The challenge of our time is to characterize the neuronal networks underlying schizophrenia and other neuropsychiatric illnesses. It has been proposed that schizophrenia arises from a uniquely human brain network associated with directed effort including the dorsal anterior and posterior cingulate cortex, auditory cortex, and hippocampus and while mood disorders arise from a different brain network associated with emotional encoding including the ventral anterior cingulate cortex, orbital frontal cortex, and amygdala. Both interact with a representation network including the frontal and temporal poles and the fronto-insular cortex, allowing the representation of the thoughts, feelings and actions of self and others. This paper reviews recent morphological and functional literature in light of the proposed networks underlying these disorders. It is suggested that there is considerable support for the involvement of the directed effort network in schizophrenia from studies of brain structure with voxel-based morphometry (VBM and diffusion tensor imaging (DTI. While early studies of resting brain networks are inconclusive, functional magnetic resonance imaging imaging (fMRI studies of task-related networks clearly implicate these regions. In keeping with the model, functional deficits in regions associated with directed effort and self-monitoring are associated with structural anomalies in action-related regions in schizophrenic patients. VBM, DTI, fMRI studies of mood disordered patients support the involvement of a different network associated with emotional encoding. The distinction between disorders is enhanced by combining structural and functional data. It is concluded that brain networks associated with directed effort are particularly vulnerable to failure in the human brain leading to the symptoms of

  19. Computer Experiment on Characteristic Modes of Excitation in a Random Neural Network on the McCulloch-Pitts Model

    Science.gov (United States)

    Satoh, Kazuhiro

    1989-08-01

    Numerical studies are made out the behavior of a random neural network in which each neuron is coupled to a certain number of randomly chosen neurons. Such a random-net serves as a simple model for an elemental sub-network of the cortex. Neurons are regarded as binary decision elements, and they synchronously update their values in discrete time steps according to a deterministic equation (the McCulloch-Pitts model). It is found that each random-net containing one hundred neurons has only a few kinds of characteristic modes of excitation. Periods of these modes are usually less than ten steps when the number of connections per neuron is two to five. For the random-net containing one thousand neurons, an excited mode is practically aperiodic. When the refractory period is introduced, however, a nearly periodic oscillation takes place in the activity of the network.

  20. A methodology for the structural and functional analysis of signaling and regulatory networks

    Directory of Open Access Journals (Sweden)

    Simeoni Luca

    2006-02-01

    Full Text Available Abstract Background Structural analysis of cellular interaction networks contributes to a deeper understanding of network-wide interdependencies, causal relationships, and basic functional capabilities. While the structural analysis of metabolic networks is a well-established field, similar methodologies have been scarcely developed and applied to signaling and regulatory networks. Results We propose formalisms and methods, relying on adapted and partially newly introduced approaches, which facilitate a structural analysis of signaling and regulatory networks with focus on functional aspects. We use two different formalisms to represent and analyze interaction networks: interaction graphs and (logical interaction hypergraphs. We show that, in interaction graphs, the determination of feedback cycles and of all the signaling paths between any pair of species is equivalent to the computation of elementary modes known from metabolic networks. Knowledge on the set of signaling paths and feedback loops facilitates the computation of intervention strategies and the classification of compounds into activators, inhibitors, ambivalent factors, and non-affecting factors with respect to a certain species. In some cases, qualitative effects induced by perturbations can be unambiguously predicted from the network scheme. Interaction graphs however, are not able to capture AND relationships which do frequently occur in interaction networks. The consequent logical concatenation of all the arcs pointing into a species leads to Boolean networks. For a Boolean representation of cellular interaction networks we propose a formalism based on logical (or signed interaction hypergraphs, which facilitates in particular a logical steady state analysis (LSSA. LSSA enables studies on the logical processing of signals and the identification of optimal intervention points (targets in cellular networks. LSSA also reveals network regions whose parametrization and initial

  1. Patterns of brain activity supporting autobiographical memory, prospection, and theory of mind, and their relationship to the default mode network.

    Science.gov (United States)

    Spreng, R Nathan; Grady, Cheryl L

    2010-06-01

    The ability to rise above the present environment and reflect upon the past, the future, and the minds of others is a fundamentally defining human feature. It has been proposed that these three self-referential processes involve a highly interconnected core set of brain structures known as the default mode network (DMN). The DMN appears to be active when individuals are engaged in stimulus-independent thought. This network is a likely candidate for supporting multiple processes, but this idea has