Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity.

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Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others' facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition.

Detecting altered connectivity patterns in HIV associated neurocognitive impairment using mutual connectivity analysis

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Abidin, Anas Zainul; D'Souza, Adora M.; Nagarajan, Mahesh B.; Wismüller, Axel

2016-03-01

The use of functional Magnetic Resonance Imaging (fMRI) has provided interesting insights into our understanding of the brain. In clinical setups these scans have been used to detect and study changes in the brain network properties in various neurological disorders. A large percentage of subjects infected with HIV present cognitive deficits, which are known as HIV associated neurocognitive disorder (HAND). In this study we propose to use our novel technique named Mutual Connectivity Analysis (MCA) to detect differences in brain networks in subjects with and without HIV infection. Resting state functional MRI scans acquired from 10 subjects (5 HIV+ and 5 HIV-) were subject to standard preprocessing routines. Subsequently, the average time-series for each brain region of the Automated Anatomic Labeling (AAL) atlas are extracted and used with the MCA framework to obtain a graph characterizing the interactions between them. The network graphs obtained for different subjects are then compared using Network-Based Statistics (NBS), which is an approach to detect differences between graphs edges while controlling for the family-wise error rate when mass univariate testing is performed. Applying this approach on the graphs obtained yields a single network encompassing 42 nodes and 65 edges, which is significantly different between the two subject groups. Specifically connections to the regions in and around the basal ganglia are significantly decreased. Also some nodes corresponding to the posterior cingulate cortex are affected. These results are inline with our current understanding of pathophysiological mechanisms of HIV associated neurocognitive disease (HAND) and other HIV based fMRI connectivity studies. Hence, we illustrate the applicability of our novel approach with network-based statistics in a clinical case-control study to detect differences connectivity patterns.

A signaling network for patterning of neuronal connectivity in the Drosophila brain.

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Mohammed Srahna

2006-10-01

Full Text Available The precise number and pattern of axonal connections generated during brain development regulates animal behavior. Therefore, understanding how developmental signals interact to regulate axonal extension and retraction to achieve precise neuronal connectivity is a fundamental goal of neurobiology. We investigated this question in the developing adult brain of Drosophila and find that it is regulated by crosstalk between Wnt, fibroblast growth factor (FGF receptor, and Jun N-terminal kinase (JNK signaling, but independent of neuronal activity. The Rac1 GTPase integrates a Wnt-Frizzled-Disheveled axon-stabilizing signal and a Branchless (FGF-Breathless (FGF receptor axon-retracting signal to modulate JNK activity. JNK activity is necessary and sufficient for axon extension, whereas the antagonistic Wnt and FGF signals act to balance the extension and retraction required for the generation of the precise wiring pattern.

Potential risk for healthy siblings to develop schizophrenia: evidence from pattern classification with whole-brain connectivity.

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Liu, Meijie; Zeng, Ling-Li; Shen, Hui; Liu, Zhening; Hu, Dewen

2012-03-28

Recent resting-state functional connectivity MRI studies using group-level statistical analysis have demonstrated the inheritable characters of schizophrenia. The objective of the present study was to use pattern classification as a means to investigate schizophrenia inheritance based on the whole-brain resting-state functional connectivity at the individual subject level. One-against-one pattern classifications were made amongst three groups (i.e. patients diagnosed with schizophrenia, healthy siblings, and healthy controls after preprocessing), resulting in an 80.4% separation between patients with schizophrenia and healthy controls, a 77.6% separation between schizophrenia patients and their healthy siblings, and a 78.7% separation between healthy siblings and healthy controls, respectively. These results suggest that the healthy siblings of schizophrenia patients have an altered resting-state functional connectivity pattern compared with healthy controls. Thus, healthy siblings may have a potential higher risk for developing schizophrenia compared with the general population. Moreover, this pattern differed from that of schizophrenia patients and may contribute to the normal behavior exhibition of healthy siblings in daily life.

Optimizing electrical load pattern in Kuwait using grid connected photovoltaic systems

International Nuclear Information System (INIS)

Al-Hasan, A.Y.; Ghoneim, A.A.; Abdullah, A.H.

2004-01-01

Grid connected photovoltaic systems is one of the most promising applications of photovoltaic systems. These systems are employed in applications where utility service is already available. In this case, there is no need for battery storage because grid power may be used to supplement photovoltaic systems (PV) when the load exceeds available PV generation. The load receives electricity from both the photovoltaic array and the utility grid. In this system, the load is the total electrical energy consumption. The main objective of the present work is to optimize the electrical load pattern in Kuwait using grid connected PV systems. In this situation, the electric load demand can be satisfied from both the photovoltaic array and the utility grid. The performance of grid connected photovoltaic systems in the Kuwait climate has been evaluated. It was found that the peak load matches the maximum incident solar radiation in Kuwait, which would emphasize the role of using the PV station to minimize the electrical load demand. In addition, a significant reduction in peak load can be achieved with grid connected PV systems

Patterns of Bullying and Sexual Harassment: Connections with Parents and Teachers as Direct Protective Factors.

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Doty, Jennifer L; Gower, Amy L; Rudi, Jessie H; McMorris, Barbara J; Borowsky, Iris W

2017-11-01

Involvement in bullying and sexual harassment in adolescence is associated with a variety of internalizing, externalizing, and health-risk behaviors. Yet, the two behaviors are often studied independently. The current study examined how bullying and sexual harassment co-occur and whether social connections protected youth from risk patterns. The data for this study come from the 2013 Minnesota Student Survey (N = 121,311; 50% female, 74% White, 26% received free or reduced-price lunch; M age  = 14.9, SD = 1.3). Students reported on bullying and sexual harassment victimization and perpetration. Using latent class analysis, youth were classified into five patterns: High-Risk of All Forms of Victimization and Perpetration (7%), Relational and Cyberbullying Victimization (17%), Sexual Harassment Victimization and Perpetration (8%), Physical Bullying Perpetration (6%), and Low-Risk (62%). Compared to the low-risk class, the four other classes had lower levels of social connections, particularly with teachers and parents. Older youth (9th and 11th grade students) were at greater risk for the sexual harassment pattern, while younger youth (8th grade students) were at greater risk for bullying patterns. The results indicate that efforts to reduce bullying should also address sexual harassment and social connections with adults.

Connectivity, excitability and activity patterns in neuronal networks

International Nuclear Information System (INIS)

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

2014-01-01

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

Data Auditor: Analyzing Data Quality Using Pattern Tableaux

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Srivastava, Divesh

Monitoring databases maintain configuration and measurement tables about computer systems, such as networks and computing clusters, and serve important business functions, such as troubleshooting customer problems, analyzing equipment failures, planning system upgrades, etc. These databases are prone to many data quality issues: configuration tables may be incorrect due to data entry errors, while measurement tables may be affected by incorrect, missing, duplicate and delayed polls. We describe Data Auditor, a tool for analyzing data quality and exploring data semantics of monitoring databases. Given a user-supplied constraint, such as a boolean predicate expected to be satisfied by every tuple, a functional dependency, or an inclusion dependency, Data Auditor computes "pattern tableaux", which are concise summaries of subsets of the data that satisfy or fail the constraint. We discuss the architecture of Data Auditor, including the supported types of constraints and the tableau generation mechanism. We also show the utility of our approach on an operational network monitoring database.

Metabolic connectivity by interregional correlation analysis using statistical parametric mapping (SPM) and FDG brain PET; methodological development and patterns of metabolic connectivity in adults

International Nuclear Information System (INIS)

Lee, Dong Soo; Oh, Jungsu S.; Lee, Jae Sung; Lee, Myung Chul; Kang, Hyejin; Kim, Heejung; Park, Hyojin

2008-01-01

Regionally connected areas of the resting brain can be detected by fluorodeoxyglucose-positron emission tomography (FDG-PET). Voxel-wise metabolic connectivity was examined, and normative data were established by performing interregional correlation analysis on statistical parametric mapping of FDG-PET data. Characteristics of seed volumes of interest (VOIs) as functional brain units were represented by their locations, sizes, and the independent methods of their determination. Seed brain areas were identified as population-based gyral VOIs (n=70) or as population-based cytoarchitectonic Brodmann areas (BA; n=28). FDG uptakes in these areas were used as independent variables in a general linear model to search for voxels correlated with average seed VOI counts. Positive correlations were searched in entire brain areas. In normal adults, one third of gyral VOIs yielded correlations that were confined to themselves, but in the others, correlated voxels extended to adjacent areas and/or contralateral homologous regions. In tens of these latter areas with extensive connectivity, correlated voxels were found across midline, and asymmetry was observed in the patterns of connectivity of left and right homologous seed VOIs. Most of the available BAs yielded correlations reaching contralateral homologous regions and/or neighboring areas. Extents of metabolic connectivity were not found to be related to seed VOI size or to the methods used to define seed VOIs. These findings indicate that patterns of metabolic connectivity of functional brain units depend on their regional locations. We propose that interregional correlation analysis of FDG-PET data offers a means of examining voxel-wise regional metabolic connectivity of the resting human brain. (orig.)

Metabolic connectivity by interregional correlation analysis using statistical parametric mapping (SPM) and FDG brain PET; methodological development and patterns of metabolic connectivity in adults

Energy Technology Data Exchange (ETDEWEB)

Lee, Dong Soo; Oh, Jungsu S.; Lee, Jae Sung; Lee, Myung Chul [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Kang, Hyejin [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Seoul National University, Programs in Brain and Neuroscience, Seoul (Korea); Kim, Heejung; Park, Hyojin [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Seoul National University, Interdisciplinary Program in Cognitive Science, Seoul (Korea)

2008-09-15

Regionally connected areas of the resting brain can be detected by fluorodeoxyglucose-positron emission tomography (FDG-PET). Voxel-wise metabolic connectivity was examined, and normative data were established by performing interregional correlation analysis on statistical parametric mapping of FDG-PET data. Characteristics of seed volumes of interest (VOIs) as functional brain units were represented by their locations, sizes, and the independent methods of their determination. Seed brain areas were identified as population-based gyral VOIs (n=70) or as population-based cytoarchitectonic Brodmann areas (BA; n=28). FDG uptakes in these areas were used as independent variables in a general linear model to search for voxels correlated with average seed VOI counts. Positive correlations were searched in entire brain areas. In normal adults, one third of gyral VOIs yielded correlations that were confined to themselves, but in the others, correlated voxels extended to adjacent areas and/or contralateral homologous regions. In tens of these latter areas with extensive connectivity, correlated voxels were found across midline, and asymmetry was observed in the patterns of connectivity of left and right homologous seed VOIs. Most of the available BAs yielded correlations reaching contralateral homologous regions and/or neighboring areas. Extents of metabolic connectivity were not found to be related to seed VOI size or to the methods used to define seed VOIs. These findings indicate that patterns of metabolic connectivity of functional brain units depend on their regional locations. We propose that interregional correlation analysis of FDG-PET data offers a means of examining voxel-wise regional metabolic connectivity of the resting human brain. (orig.)

Diluted connectivity in pattern association networks facilitates the recall of information from the hippocampus to the neocortex.

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Rolls, Edmund T

2015-01-01

The recall of information stored in the hippocampus involves a series of corticocortical backprojections via the entorhinal cortex, parahippocampal gyrus, and one or more neocortical stages. Each stage is considered to be a pattern association network, with the retrieval cue at each stage the firing of neurons in the previous stage. The leading factor that determines the capacity of this multistage pattern association backprojection pathway is the number of connections onto any one neuron, which provides a quantitative basis for why there are as many backprojections between adjacent stages in the hierarchy as forward projections. The issue arises of why this multistage backprojection system uses diluted connectivity. One reason is that a multistage backprojection system with expansion of neuron numbers at each stage enables the hippocampus to address during recall the very large numbers of neocortical neurons, which would otherwise require hippocampal neurons to make very large numbers of synapses if they were directly onto neocortical neurons. The second reason is that as shown here, diluted connectivity in the backprojection pathways reduces the probability of more than one connection onto a receiving neuron in the backprojecting pathways, which otherwise reduces the capacity of the system, that is the number of memories that can be recalled from the hippocampus to the neocortex. For similar reasons, diluted connectivity is advantageous in pattern association networks in other brain systems such as the orbitofrontal cortex and amygdala; for related reasons, in autoassociation networks in, for example, the hippocampal CA3 and the neocortex; and for the different reason that diluted connectivity facilitates the operation of competitive networks in forward-connected cortical systems. © 2015 Elsevier B.V. All rights reserved.

Undifferentiated connective tissue disease and interstitial lung disease: Trying to define patterns.

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Alberti, María Laura; Paulin, Francisco; Toledo, Heidegger Mateos; Fernández, Martín Eduardo; Caro, Fabián Matías; Rojas-Serrano, Jorge; Mejía, Mayra Edith

To identify clinical or immunological features in patients with undifferentiated connective tissue disease (UCTD) associated interstitial lung disease (ILD), in order to group them and recognize different functional and high resolution computed tomography (HRCT) behavior. Retrospective cohort study. Patients meeting Kinder criteria for UCTD were included. We defined the following predictive variables: 'highly specific' connective tissue disease (CTD) manifestations (Raynaud's phenomenon, dry eyes or arthritis), high antinuclear antibody (ANA) titer (above 1: 320), and 'specific' ANA staining patterns (centromere, cytoplasmic and nucleolar patterns). We evaluated the following outcomes: change in the percentage of the predicted forced vital capacity (FVC%) during the follow-up period, and HRCT pattern. Sixty-six patients were included. Twenty-nine (43.94%) showed at least one 'highly specific' CTD manifestation, 16 (28.57%) had a 'specific' ANA staining pattern and 29 (43.94%) high ANA titer. Patients with 'highly specific' CTD manifestations were younger (mean [SD] 52 years [14.58] vs 62.08 years [9.46], P<.001), were more likely men (10.34% vs 48.65%, P<.001) and showed a smaller decline of the FVC% (median [interquartile range] 1% [-1 to 10] vs -6% [-16 to -4], P<.006). In the multivariate analysis, the presence of highly specific manifestations was associated with improvement in the FVC% (B coefficient of 13.25 [95% confidence interval, 2.41 to 24.09]). No association was observed in relation to the HRCT pattern. The presence of 'highly specific' CTD manifestations was associated with female sex, younger age and better functional behavior. These findings highlight the impact of the clinical features in the outcome of patients with UCTD ILD. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Reumatología y Colegio Mexicano de Reumatología. All rights reserved.

Patterns of brain structural connectivity differentiate normal weight from overweight subjects.

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Gupta, Arpana; Mayer, Emeran A; Sanmiguel, Claudia P; Van Horn, John D; Woodworth, Davis; Ellingson, Benjamin M; Fling, Connor; Love, Aubrey; Tillisch, Kirsten; Labus, Jennifer S

2015-01-01

Alterations in the hedonic component of ingestive behaviors have been implicated as a possible risk factor in the pathophysiology of overweight and obese individuals. Neuroimaging evidence from individuals with increasing body mass index suggests structural, functional, and neurochemical alterations in the extended reward network and associated networks. To apply a multivariate pattern analysis to distinguish normal weight and overweight subjects based on gray and white-matter measurements. Structural images (N = 120, overweight N = 63) and diffusion tensor images (DTI) (N = 60, overweight N = 30) were obtained from healthy control subjects. For the total sample the mean age for the overweight group (females = 32, males = 31) was 28.77 years (SD = 9.76) and for the normal weight group (females = 32, males = 25) was 27.13 years (SD = 9.62). Regional segmentation and parcellation of the brain images was performed using Freesurfer. Deterministic tractography was performed to measure the normalized fiber density between regions. A multivariate pattern analysis approach was used to examine whether brain measures can distinguish overweight from normal weight individuals. 1. White-matter classification: The classification algorithm, based on 2 signatures with 17 regional connections, achieved 97% accuracy in discriminating overweight individuals from normal weight individuals. For both brain signatures, greater connectivity as indexed by increased fiber density was observed in overweight compared to normal weight between the reward network regions and regions of the executive control, emotional arousal, and somatosensory networks. In contrast, the opposite pattern (decreased fiber density) was found between ventromedial prefrontal cortex and the anterior insula, and between thalamus and executive control network regions. 2. Gray-matter classification: The classification algorithm, based on 2 signatures with 42 morphological features, achieved 69

Patterns of brain structural connectivity differentiate normal weight from overweight subjects

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Gupta, Arpana; Mayer, Emeran A.; Sanmiguel, Claudia P.; Van Horn, John D.; Woodworth, Davis; Ellingson, Benjamin M.; Fling, Connor; Love, Aubrey; Tillisch, Kirsten; Labus, Jennifer S.

2015-01-01

Background Alterations in the hedonic component of ingestive behaviors have been implicated as a possible risk factor in the pathophysiology of overweight and obese individuals. Neuroimaging evidence from individuals with increasing body mass index suggests structural, functional, and neurochemical alterations in the extended reward network and associated networks. Aim To apply a multivariate pattern analysis to distinguish normal weight and overweight subjects based on gray and white-matter measurements. Methods Structural images (N = 120, overweight N = 63) and diffusion tensor images (DTI) (N = 60, overweight N = 30) were obtained from healthy control subjects. For the total sample the mean age for the overweight group (females = 32, males = 31) was 28.77 years (SD = 9.76) and for the normal weight group (females = 32, males = 25) was 27.13 years (SD = 9.62). Regional segmentation and parcellation of the brain images was performed using Freesurfer. Deterministic tractography was performed to measure the normalized fiber density between regions. A multivariate pattern analysis approach was used to examine whether brain measures can distinguish overweight from normal weight individuals. Results 1. White-matter classification: The classification algorithm, based on 2 signatures with 17 regional connections, achieved 97% accuracy in discriminating overweight individuals from normal weight individuals. For both brain signatures, greater connectivity as indexed by increased fiber density was observed in overweight compared to normal weight between the reward network regions and regions of the executive control, emotional arousal, and somatosensory networks. In contrast, the opposite pattern (decreased fiber density) was found between ventromedial prefrontal cortex and the anterior insula, and between thalamus and executive control network regions. 2. Gray-matter classification: The classification algorithm, based on 2 signatures with 42

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

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

2012-04-01

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

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

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Yan eTao

2015-11-01

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

Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy.

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Salis, Michele; Ager, Alan A; Alcasena, Fermin J; Arca, Bachisio; Finney, Mark A; Pellizzaro, Grazia; Spano, Donatella

2015-01-01

In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn probability, fire size, and flame length among time periods within the fire season, which starts in early June and ends in late September. Peak burn probability and flame length were observed in late July. We found that patterns of wildfire likelihood and intensity were mainly related to spatiotemporal variation in ignition locations, fuel moisture, and wind vectors. Our modeling approach allowed consideration of historical patterns of winds, ignition locations, and live and dead fuel moisture on fire exposure factors. The methodology proposed can be useful for analyzing potential wildfire risk and effects at landscape scale, evaluating historical changes and future trends in wildfire exposure, as well as for addressing and informing fuel management and risk mitigation issues.

Altered amygdalar resting-state connectivity in depression is explained by both genes and environment.

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Córdova-Palomera, Aldo; Tornador, Cristian; Falcón, Carles; Bargalló, Nuria; Nenadic, Igor; Deco, Gustavo; Fañanás, Lourdes

2015-10-01

Recent findings indicate that alterations of the amygdalar resting-state fMRI connectivity play an important role in the etiology of depression. While both depression and resting-state brain activity are shaped by genes and environment, the relative contribution of genetic and environmental factors mediating the relationship between amygdalar resting-state connectivity and depression remain largely unexplored. Likewise, novel neuroimaging research indicates that different mathematical representations of resting-state fMRI activity patterns are able to embed distinct information relevant to brain health and disease. The present study analyzed the influence of genes and environment on amygdalar resting-state fMRI connectivity, in relation to depression risk. High-resolution resting-state fMRI scans were analyzed to estimate functional connectivity patterns in a sample of 48 twins (24 monozygotic pairs) informative for depressive psychopathology (6 concordant, 8 discordant and 10 healthy control pairs). A graph-theoretical framework was employed to construct brain networks using two methods: (i) the conventional approach of filtered BOLD fMRI time-series and (ii) analytic components of this fMRI activity. Results using both methods indicate that depression risk is increased by environmental factors altering amygdalar connectivity. When analyzing the analytic components of the BOLD fMRI time-series, genetic factors altering the amygdala neural activity at rest show an important contribution to depression risk. Overall, these findings show that both genes and environment modify different patterns the amygdala resting-state connectivity to increase depression risk. The genetic relationship between amygdalar connectivity and depression may be better elicited by examining analytic components of the brain resting-state BOLD fMRI signals. © 2015 Wiley Periodicals, Inc.

Influence of Biological Factors on Connectivity Patterns for Concholepas concholepas (loco) in Chile.

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Garavelli, Lysel; Colas, François; Verley, Philippe; Kaplan, David Michael; Yannicelli, Beatriz; Lett, Christophe

2016-01-01

In marine benthic ecosystems, larval connectivity is a major process influencing the maintenance and distribution of invertebrate populations. Larval connectivity is a complex process to study as it is determined by several interacting factors. Here we use an individual-based, biophysical model, to disentangle the effects of such factors, namely larval vertical migration, larval growth, larval mortality, adults fecundity, and habitat availability, for the marine gastropod Concholepas concholepas (loco) in Chile. Lower transport success and higher dispersal distances are observed including larval vertical migration in the model. We find an overall decrease in larval transport success to settlement areas from northern to southern Chile. This spatial gradient results from the combination of current direction and intensity, seawater temperature, and available habitat. From our simulated connectivity patterns we then identify subpopulations of loco along the Chilean coast, which could serve as a basis for spatial management of this resource in the future.

Patterns in connectivity and retention of simulated Tanner crab (Chionoecetes bairdi) larvae in the eastern Bering Sea

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Richar, Jonathan I.; Kruse, Gordon H.; Curchitser, Enrique; Hermann, Albert J.

2015-11-01

The eastern Bering Sea (EBS) population of Tanner crab (Chionoecetes bairdi) has exhibited high variability in recruitment to the commercially exploited stock since the late 1970s. Concurrently, apparent shifts in crab distribution have also been observed. Larval advection patterns and associated local retention offer a potential mechanism for these observations. The Regional Ocean Modeling System (ROMS) was used to simulate larval Tanner crab advection patterns over 1978-2004 based on larval hatching sites inferred from the distributions of reproductive females sampled during annual National Marine Fisheries Service trawl surveys. Connectivity among EBS subregions was examined by comparing start and end float locations after 60 days of simulated drift. High levels of retention (>50% of floats) were observed in the majority of source subregions, and contributed significantly to the total number of endpoints in each region. Patterns in advection and resultant interregional connectivity were variable, with strongest sustained connectivity occurring along shelf, within individual domains. Increased settlement potential in the outer domain and southern middle domain after 1990 is consistent with an observed geographic shift in fishery productivity. Apparent reliance of Bristol Bay on local larval retention validates recent spatial fishery management to conserve this area as a subpopulation.

Storage of phase-coded patterns via STDP in fully-connected and sparse network: a study of the network capacity

Directory of Open Access Journals (Sweden)

Silvia Scarpetta

2010-08-01

Full Text Available We study the storage and retrieval of phase-coded patterns as stable dynamical attractors in recurrent neural networks, for both an analog and a integrate-and-fire spiking model. The synaptic strength is determined by a learning rule based on spike-time-dependent plasticity, with an asymmetric time window depending on the relative timing between pre- and post-synaptic activity. We store multiple patterns and study the network capacity. For the analog model, we find that the network capacity scales linearly with the network size, and that both capacity and the oscillation frequency of the retrieval state depend on the asymmetry of the learning time window. In addition to fully-connected networks, we study sparse networks, where each neuron is connected only to a small number $zll N$ of other neurons. Connections can be short range, between neighboring neurons placed on a regular lattice, or long range, between randomly chosen pairs of neurons. We find that a small fraction of long range connections is able to amplify the capacity of the network. This imply that a small-world-network topology is optimal, as a compromise between the cost of long range connections and the capacity increase. Also in the spiking integrate and fire model the crucial result of storing and retrieval of multiple phase-coded patterns is observed. The capacity of the fully-connected spiking network is investigated, together with the relation between oscillation frequency of retrieval state and window asymmetry.

l-Dopa responsiveness is associated with distinctive connectivity patterns in advanced Parkinson's disease.

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Akram, Harith; Wu, Chengyuan; Hyam, Jonathan; Foltynie, Thomas; Limousin, Patricia; De Vita, Enrico; Yousry, Tarek; Jahanshahi, Marjan; Hariz, Marwan; Behrens, Timothy; Ashburner, John; Zrinzo, Ludvic

2017-06-01

Neuronal loss and dopamine depletion alter motor signal processing between cortical motor areas, basal ganglia, and the thalamus, resulting in the motor manifestations of Parkinson's disease. Dopamine replacement therapy can reverse these manifestations with varying degrees of improvement. To evaluate functional connectivity in patients with advanced Parkinson's disease and changes in functional connectivity in relation to the degree of response to l-dopa, 19 patients with advanced Parkinson's disease underwent resting-state functional magnetic resonance imaging in the on-medication state. Scans were obtained on a 3-Tesla scanner in 3 × 3 × 2.5 mm 3 voxels. Seed-based bivariate regression analyses were carried out with atlas-defined basal ganglia regions as seeds, to explore relationships between functional connectivity and improvement in the motor section of the UPDRS-III following an l-dopa challenge. False discovery rate-corrected P was set at basal ganglia resting-state functional connectivity patterns associated with different degrees of l-dopa responsiveness in patients with advanced Parkinson's disease. l-Dopa exerts a graduated influence on remapping connectivity in distinct motor control networks, potentially explaining some of the variance in treatment response. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

More consistently altered connectivity patterns for cerebellum and medial temporal lobes than for amygdala and striatum in schizophrenia

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Henning ePeters

2016-02-01

Full Text Available Background: Brain architecture can be divided into a cortico-thalamic system and modulatory ‘subcortical-cerebellar’ systems containing key structures such as striatum, medial temporal lobes (MTLs, amygdala, and cerebellum. Subcortical-cerebellar systems are known to be altered in schizophrenia. In particular, intrinsic functional brain connectivity (iFC between these systems has been consistently demonstrated in patients. While altered connectivity is known for each subcortical-cerebellar system separately, it is unknown whether subcortical-cerebellar systems’ connectivity patterns with the cortico-thalamic system are comparably altered across systems, i.e., if separate subcortical-cerebellar systems’ connectivity patterns are consistent across patients. Methods: To investigate this question, 18 patients with schizophrenia (3 unmedicated, 15 medicated with atypical antipsychotics and 18 healthy controls were assessed by resting-state functional magnetic resonance imaging (fMRI. Independent component analysis of fMRI data revealed cortical intrinsic brain networks (NWs with time courses representing proxies for cortico-thalamic system activity. Subcortical-cerebellar systems’ activity was represented by fMRI-based time courses of selected regions-of-interest (ROIs (i.e., striatum, MTL, amygdala, cerebellum. Correlation analysis among ROI- and NWs-time courses yielded individual connectivity matrices (i.e. connectivity between NW and ROIs (allROIs-NW, separateROI-NW, only NWs (NWs-NWs, and only ROIs (allROIs-allROIs as main outcome measures, which were classified by support-vector-machine-based leave-one-out cross-validation. Differences in classification accuracy were statistically evaluated for consistency across subjects and systems. Results: Correlation matrices based on allROIs-NWs yielded 91% classification accuracy, which was significantly superior to allROIs-allROIs and NWs-NWs (56% and 74%, respectively. Considering separate

Assemblage patterns of fish functional groups relative to habitat connectivity and conditions in floodplain lakes

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Miyazono, S.; Aycock, J.N.; Miranda, L.E.; Tietjen, T.E.

2010-01-01

We evaluated the influences of habitat connectivity and local environmental factors on the distribution and abundance patterns of fish functional groups in 17 floodplain lakes in the Yazoo River Basin, USA. The results of univariate and multivariate analyses showed that species-environmental relationships varied with the functional groups. Species richness and assemblage structure of periodic strategists showed strong and positive correlations with habitat connectivity. Densities of most equilibrium and opportunistic strategists decreased with habitat connectivity. Densities of certain equilibrium and opportunistic strategists increased with turbidity. Forested wetlands around the lakes were positively related to the densities of periodic and equilibrium strategists. These results suggest that decreases in habitat connectivity, forested wetland buffers and water quality resulting from environmental manipulations may cause local extinction of certain fish taxa and accelerate the dominance of tolerant fishes in floodplain lakes. ?? 2010 John Wiley & Sons A/S.

Multi-Connection Pattern Analysis: Decoding the representational content of neural communication.

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Li, Yuanning; Richardson, Robert Mark; Ghuman, Avniel Singh

2017-11-15

The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions. Copyright © 2017 Elsevier Inc. All rights reserved.

Influence of Biological Factors on Connectivity Patterns for Concholepas concholepas (loco in Chile.

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Lysel Garavelli

Full Text Available In marine benthic ecosystems, larval connectivity is a major process influencing the maintenance and distribution of invertebrate populations. Larval connectivity is a complex process to study as it is determined by several interacting factors. Here we use an individual-based, biophysical model, to disentangle the effects of such factors, namely larval vertical migration, larval growth, larval mortality, adults fecundity, and habitat availability, for the marine gastropod Concholepas concholepas (loco in Chile. Lower transport success and higher dispersal distances are observed including larval vertical migration in the model. We find an overall decrease in larval transport success to settlement areas from northern to southern Chile. This spatial gradient results from the combination of current direction and intensity, seawater temperature, and available habitat. From our simulated connectivity patterns we then identify subpopulations of loco along the Chilean coast, which could serve as a basis for spatial management of this resource in the future.

Patterns of deep-sea genetic connectivity in the New Zealand region: implications for management of benthic ecosystems.

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Eleanor K Bors

Full Text Available Patterns of genetic connectivity are increasingly considered in the design of marine protected areas (MPAs in both shallow and deep water. In the New Zealand Exclusive Economic Zone (EEZ, deep-sea communities at upper bathyal depths (<2000 m are vulnerable to anthropogenic disturbance from fishing and potential mining operations. Currently, patterns of genetic connectivity among deep-sea populations throughout New Zealand's EEZ are not well understood. Using the mitochondrial Cytochrome Oxidase I and 16S rRNA genes as genetic markers, this study aimed to elucidate patterns of genetic connectivity among populations of two common benthic invertebrates with contrasting life history strategies. Populations of the squat lobster Munida gracilis and the polychaete Hyalinoecia longibranchiata were sampled from continental slope, seamount, and offshore rise habitats on the Chatham Rise, Hikurangi Margin, and Challenger Plateau. For the polychaete, significant population structure was detected among distinct populations on the Chatham Rise, the Hikurangi Margin, and the Challenger Plateau. Significant genetic differences existed between slope and seamount populations on the Hikurangi Margin, as did evidence of population differentiation between the northeast and southwest parts of the Chatham Rise. In contrast, no significant population structure was detected across the study area for the squat lobster. Patterns of genetic connectivity in Hyalinoecia longibranchiata are likely influenced by a number of factors including current regimes that operate on varying spatial and temporal scales to produce potential barriers to dispersal. The striking difference in population structure between species can be attributed to differences in life history strategies. The results of this study are discussed in the context of existing conservation areas that are intended to manage anthropogenic threats to deep-sea benthic communities in the New Zealand region.

Convergent and divergent functional connectivity patterns in patients with long-term left-sided and right-sided deafness.

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Zhang, Yanyang; Mao, Zhiqi; Feng, Shiyu; Wang, Wenxin; Zhang, Jun; Yu, Xinguang

2018-02-05

Cortical reorganization may be induced in long-term single-sided deafness (SD); however, the influence of the deafness side on the functional changes remains poorly understood. Here, we investigated whole-brain functional connectivity patterns in long-term SD patients. The normalized voxel-based functional connectivity strength (FCS) was determined using resting-state fMRI (rs-fMRI) in 17 left-sided deafness (LD) patients, 21 right-sided deafness (RD) patients and 21 healthy controls (HCs). Relative to the HCs, both the LD and RD patients exhibited a reduction in the FCS in the ipsilateral visual cortex. However, compared to that in the HCs, a significantly higher FCS was observed in some regions in the salience and default-mode networks in the RD patients, but this FCS alternation pattern was not observed in the LD patients. A direct comparison of the two patient groups revealed a significantly increased FCS in the supplemental motor area in the LD group. Altogether, the long-term SD groups with LD and RD exhibited convergent and divergent functional connectivity patterns in whole-brain networks, providing promising evidence that the functional changes in long-term SD are highly deafness-side-dependent. Copyright © 2017 Elsevier B.V. All rights reserved.

Regional homogeneity and functional connectivity patterns in major depressive disorder, cognitive vulnerability to depression and healthy subjects.

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Sun, Hui; Luo, Lizhu; Yuan, Xinru; Zhang, Lu; He, Yini; Yao, Shuqiao; Wang, Jiaojian; Xiao, Jing

2018-08-01

Cognitive vulnerability to depression (CVD) is a high risk for depressive disorder. Recent studies focus on individuals with CVD to determine the neural basis of major depressive disorder (MDD) neuropathology. However, whether CVD showed specific or similar brain functional activity and connectivity patterns, compared to MDD, remain largely unknown. Here, using resting-state functional magnetic resonance imaging in subjects with CVD, healthy controls (HC) and MDD, regional homogeneity (ReHo) and resting-state functional connectivity (R-FC) analyses were conducted to assess local synchronization and changes in functional connectivity patterns. Significant ReHo differences were found in right posterior lobe of cerebellum (PLC), left lingual gyrus (LG) and precuneus. Compared to HC, CVD subjects showed increased ReHo in the PLC, which was similar to the difference found between MDD and HC. Compared to MDD patients, CVD subjects showed decreased ReHo in PLC, LG, and precuneus. R-FC analyses found increased functional connections between LG and left inferior parietal lobule, posterior cingulate cortex, and dorsolateral prefrontal cortex in CVD compared to both HC and MDD. Moreover, Regional mean ReHo values were positively correlated with Center for Epidemiologic Studies Depression Scale scores. These analyses revealed that PLC and functional connections between LG and left inferior parietal lobule, posterior cingulate cortex, and dorsolateral prefrontal cortex may be a potential marker for CVD. Copyright © 2018 Elsevier B.V. All rights reserved.

Patterns and drivers for wetland connections in the Prairie Pothole Region, United States

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Vanderhoof, Melanie; Christensen, Jay R.; Alexander, Laurie C.

2017-01-01

Ecosystem function in rivers, lakes and coastal waters depends on the functioning of upstream aquatic ecosystems, necessitating an improved understanding of watershed-scale interactions including variable surface-water flows between wetlands and streams. As surface water in the Prairie Pothole Region expands in wet years, surface-water connections occur between many depressional wetlands and streams. Minimal research has explored the spatial patterns and drivers for the abundance of these connections, despite their potential to inform resource management and regulatory programs including the U.S. Clean Water Act. In this study, wetlands were identified that did not intersect the stream network, but were shown with Landsat images (1990–2011) to become merged with the stream network as surface water expanded. Wetlands were found to spill into or consolidate with other wetlands within both small (2–10 wetlands) and large (>100 wetlands) wetland clusters, eventually intersecting a stream channel, most often via a riparian wetland. These surface-water connections occurred over a wide range of wetland distances from streams (averaging 90–1400 m in different ecoregions). Differences in the spatial abundance of wetlands that show a variable surface-water connection to a stream were best explained by smaller wetland-to-wetland distances, greater wetland abundance, and maximum surface-water extent. This analysis demonstrated that wetland arrangement and surface water expansion are important mechanisms for depressional wetlands to connect to streams and provides a first step to understanding the frequency and abundance of these surface-water connections across the Prairie Pothole Region.

Functional connectivity changes detected with magnetoencephalography after mild traumatic brain injury

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Stavros I. Dimitriadis

2015-01-01

Full Text Available Mild traumatic brain injury (mTBI may affect normal cognition and behavior by disrupting the functional connectivity networks that mediate efficient communication among brain regions. In this study, we analyzed brain connectivity profiles from resting state Magnetoencephalographic (MEG recordings obtained from 31 mTBI patients and 55 normal controls. We used phase-locking value estimates to compute functional connectivity graphs to quantify frequency-specific couplings between sensors at various frequency bands. Overall, normal controls showed a dense network of strong local connections and a limited number of long-range connections that accounted for approximately 20% of all connections, whereas mTBI patients showed networks characterized by weak local connections and strong long-range connections that accounted for more than 60% of all connections. Comparison of the two distinct general patterns at different frequencies using a tensor representation for the connectivity graphs and tensor subspace analysis for optimal feature extraction showed that mTBI patients could be separated from normal controls with 100% classification accuracy in the alpha band. These encouraging findings support the hypothesis that MEG-based functional connectivity patterns may be used as biomarkers that can provide more accurate diagnoses, help guide treatment, and monitor effectiveness of intervention in mTBI.

Incongruent genetic connectivity patterns for VME indicator taxa: implications for the management of New Zealand's vulnerable marine ecosystems

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Clark, M. R.; Gardner, J.; Holland, L.; Zeng, C.; Hamilton, J. S.; Rowden, A. A.

2016-02-01

In the New Zealand region vulnerable marine ecosystems (VMEs) are at risk from commercial fishing activity and future seabed mining. Understanding connectivity among VMEs is important for the design of effective spatial management strategies, i.e. a network of protected areas. To date however, genetic connectivity in the New Zealand region has rarely been documented. As part of a project developing habitat suitability models and spatial management options for VMEs we used DNA sequence data and microsatellite genotyping to assess genetic connectivity for a range of VME indicator taxa, including the coral Desmophyllum dianthus, and the sponges Poecilastra laminaris and Penares palmatoclada. Overall, patterns of connectivity were inconsistent amonst taxa. Nonetheless, genetic data from each taxon were relevant to inform management at a variety of spatial scales. D. dianthus populations in the Kermadec volcanic arc and the Louisville Seamount Chain were indistinguishable, highlighting the importance of considering source-sink dynamics between populations beyond the EEZ in conservation planning. Poecilastra laminaris populations showed significant divergence across the Chatham Rise, in contrast to P. palmatoclada, which had a uniform haplotypic distribution. However, both sponge species exhibited the highest genetic diversity on the Chatham Rise, suggesting that this area is a genetic hotspot. The spatial heterogeneity of genetic patterns of structure suggest that inclusion of several taxa is necessary to facilitate understanding of regional connectivity patterns, variation in which may be attributed to alternate life history strategies, local hydrodynamic regimes, or in some cases, suboptimal sample sizes. Our findings provide important information for use by environmental managers, including summary maps of genetic diversity and barriers to gene flow, which will be used in spatial management decision-support tools.

Investigating univariate temporal patterns for intrinsic connectivity networks based on complexity and low-frequency oscillation: a test-retest reliability study.

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Wang, X; Jiao, Y; Tang, T; Wang, H; Lu, Z

2013-12-19

Intrinsic connectivity networks (ICNs) are composed of spatial components and time courses. The spatial components of ICNs were discovered with moderate-to-high reliability. So far as we know, few studies focused on the reliability of the temporal patterns for ICNs based their individual time courses. The goals of this study were twofold: to investigate the test-retest reliability of temporal patterns for ICNs, and to analyze these informative univariate metrics. Additionally, a correlation analysis was performed to enhance interpretability. Our study included three datasets: (a) short- and long-term scans, (b) multi-band echo-planar imaging (mEPI), and (c) eyes open or closed. Using dual regression, we obtained the time courses of ICNs for each subject. To produce temporal patterns for ICNs, we applied two categories of univariate metrics: network-wise complexity and network-wise low-frequency oscillation. Furthermore, we validated the test-retest reliability for each metric. The network-wise temporal patterns for most ICNs (especially for default mode network, DMN) exhibited moderate-to-high reliability and reproducibility under different scan conditions. Network-wise complexity for DMN exhibited fair reliability (ICC<0.5) based on eyes-closed sessions. Specially, our results supported that mEPI could be a useful method with high reliability and reproducibility. In addition, these temporal patterns were with physiological meanings, and certain temporal patterns were correlated to the node strength of the corresponding ICN. Overall, network-wise temporal patterns of ICNs were reliable and informative and could be complementary to spatial patterns of ICNs for further study. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Multivariate pattern analysis reveals anatomical connectivity differences between the left and right mesial temporal lobe epilepsy.

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Fang, Peng; An, Jie; Zeng, Ling-Li; Shen, Hui; Chen, Fanglin; Wang, Wensheng; Qiu, Shijun; Hu, Dewen

2015-01-01

Previous studies have demonstrated differences of clinical signs and functional brain network organizations between the left and right mesial temporal lobe epilepsy (mTLE), but the anatomical connectivity differences underlying functional variance between the left and right mTLE remain uncharacterized. We examined 43 (22 left, 21 right) mTLE patients with hippocampal sclerosis and 39 healthy controls using diffusion tensor imaging. After the whole-brain anatomical networks were constructed for each subject, multivariate pattern analysis was applied to classify the left mTLE from the right mTLE and extract the anatomical connectivity differences between the left and right mTLE patients. The classification results reveal 93.0% accuracy for the left mTLE versus the right mTLE, 93.4% accuracy for the left mTLE versus controls and 90.0% accuracy for the right mTLE versus controls. Compared with the right mTLE, the left mTLE exhibited a different connectivity pattern in the cortical-limbic network and cerebellum. The majority of the most discriminating anatomical connections were located within or across the cortical-limbic network and cerebellum, thereby indicating that these disease-related anatomical network alterations may give rise to a portion of the complex of emotional and memory deficit between the left and right mTLE. Moreover, the orbitofrontal gyrus, cingulate cortex, hippocampus and parahippocampal gyrus, which exhibit high discriminative power in classification, may play critical roles in the pathophysiology of mTLE. The current study demonstrated that anatomical connectivity differences between the left mTLE and the right mTLE may have the potential to serve as a neuroimaging biomarker to guide personalized diagnosis of the left and right mTLE.

Contrasting brain patterns of writing-related DTI parameters, fMRI connectivity, and DTI–fMRI connectivity correlations in children with and without dysgraphia or dyslexia

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Richards, T.L.; Grabowski, T.J.; Boord, P.; Yagle, K.; Askren, M.; Mestre, Z.; Robinson, P.; Welker, O.; Gulliford, D.; Nagy, W.; Berninger, V.

2015-01-01

Based on comprehensive testing and educational history, children in grades 4–9 (on average 12 years) were diagnosed with dysgraphia (persisting handwriting impairment) or dyslexia (persisting word spelling/reading impairment) or as typical writers and readers (controls). The dysgraphia group (n = 14) and dyslexia group (n = 17) were each compared to the control group (n = 9) and to each other in separate analyses. Four brain region seed points (left occipital temporal gyrus, supramarginal gyrus, precuneus, and inferior frontal gyrus) were used in these analyses which were shown in a metaanalysis to be related to written word production on four indicators of white matter integrity and fMRI functional connectivity for four tasks (self-guided mind wandering during resting state, writing letter that follows a visually displayed letter in alphabet, writing missing letter to create a correctly spelled real word, and planning for composing after scanning on topic specified by researcher). For those DTI indicators on which the dysgraphic group or dyslexic group differed from the control group (fractional anisotropy, relative anisotropy, axial diffusivity but not radial diffusivity), correlations were computed between the DTI parameter and fMRI functional connectivity for the two writing tasks (alphabet and spelling) by seed points. Analyses, controlled for multiple comparisons, showed that (a) the control group exhibited more white matter integrity than either the dysgraphic or dyslexic group; (b) the dysgraphic and dyslexic groups showed more functional connectivity than the control group but differed in patterns of functional connectivity for task and seed point; and (c) the dysgraphic and dyslexic groups showed different patterns of significant DTI–fMRI connectivity correlations for specific seed points and written language tasks. Thus, dysgraphia and dyslexia differ in white matter integrity, fMRI functional connectivity, and white matter–gray matter

Contrasting brain patterns of writing-related DTI parameters, fMRI connectivity, and DTI–fMRI connectivity correlations in children with and without dysgraphia or dyslexia

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T.L. Richards

2015-01-01

Full Text Available Based on comprehensive testing and educational history, children in grades 4–9 (on average 12 years were diagnosed with dysgraphia (persisting handwriting impairment or dyslexia (persisting word spelling/reading impairment or as typical writers and readers (controls. The dysgraphia group (n = 14 and dyslexia group (n = 17 were each compared to the control group (n = 9 and to each other in separate analyses. Four brain region seed points (left occipital temporal gyrus, supramarginal gyrus, precuneus, and inferior frontal gyrus were used in these analyses which were shown in a metaanalysis to be related to written word production on four indicators of white matter integrity and fMRI functional connectivity for four tasks (self-guided mind wandering during resting state, writing letter that follows a visually displayed letter in alphabet, writing missing letter to create a correctly spelled real word, and planning for composing after scanning on topic specified by researcher. For those DTI indicators on which the dysgraphic group or dyslexic group differed from the control group (fractional anisotropy, relative anisotropy, axial diffusivity but not radial diffusivity, correlations were computed between the DTI parameter and fMRI functional connectivity for the two writing tasks (alphabet and spelling by seed points. Analyses, controlled for multiple comparisons, showed that (a the control group exhibited more white matter integrity than either the dysgraphic or dyslexic group; (b the dysgraphic and dyslexic groups showed more functional connectivity than the control group but differed in patterns of functional connectivity for task and seed point; and (c the dysgraphic and dyslexic groups showed different patterns of significant DTI–fMRI connectivity correlations for specific seed points and written language tasks. Thus, dysgraphia and dyslexia differ in white matter integrity, fMRI functional connectivity, and white matter–gray matter

Cerebral functional connectivity and Mayer waves in mice: Phenomena and separability.

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Bumstead, Jonathan R; Bauer, Adam Q; Wright, Patrick W; Culver, Joseph P

2017-02-01

Resting-state functional connectivity is a growing neuroimaging approach that analyses the spatiotemporal structure of spontaneous brain activity, often using low-frequency (Mayer waves. Despite how close in frequency these phenomena exist, there is little research on how vasomotion and Mayer waves are related to or affect resting-state functional connectivity. In this study, we analyze spontaneous hemodynamic fluctuations over the mouse cortex using optical intrinsic signal imaging. We found spontaneous occurrence of oscillatory hemodynamics ∼0.2 Hz consistent with the properties of Mayer waves reported in the literature. Across a group of mice (n = 19), there was a large variability in the magnitude of Mayer waves. However, regardless of the magnitude of Mayer waves, functional connectivity patterns could be recovered from hemodynamic signals when filtered to the lower frequency band, 0.01-0.08 Hz. Our results demonstrate that both Mayer waves and resting-state functional connectivity patterns can co-exist simultaneously, and that they can be separated by applying bandpass filters.

Differential Resting-State Connectivity Patterns of the Right Anterior and Posterior Dorsolateral Prefrontal Cortices (DLPFC in Schizophrenia

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Natalia Chechko

2018-05-01

Full Text Available In schizophrenia (SCZ, dysfunction of the dorsolateral prefrontal cortex (DLPFC has been linked to the deficits in executive functions and attention. It has been suggested that, instead of considering the right DLPFC as a cohesive functional entity, it can be divided into two parts (anterior and posterior based on its whole-brain connectivity patterns. Given these two subregions' differential association with cognitive processes, we investigated the functional connectivity (FC profile of both subregions through resting-state data to determine whether they are differentially affected in SCZ. Resting-state magnetic resonance imaging (MRI scans were obtained from 120 patients and 172 healthy controls (HC at 6 different MRI sites. The results showed differential FC patterns for the anterior and posterior parts of the right executive control-related DLPFC in SCZ with the parietal, the temporal and the cerebellar regions, along with a convergent reduction of connectivity with the striatum and the occipital cortex. An increased psychopathology level was linked to a higher difference in posterior vs. anterior FC for the left IFG/anterior insula, regions involved in higher-order cognitive processes. In sum, the current analysis demonstrated that even between two neighboring clusters connectivity could be differentially disrupted in SCZ. Lacking the necessary anatomical specificity, such notions may in fact be detrimental to a proper understanding of SCZ pathophysiology.

Multivariate pattern analysis reveals anatomical connectivity differences between the left and right mesial temporal lobe epilepsy

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Peng Fang

2015-01-01

Full Text Available Previous studies have demonstrated differences of clinical signs and functional brain network organizations between the left and right mesial temporal lobe epilepsy (mTLE, but the anatomical connectivity differences underlying functional variance between the left and right mTLE remain uncharacterized. We examined 43 (22 left, 21 right mTLE patients with hippocampal sclerosis and 39 healthy controls using diffusion tensor imaging. After the whole-brain anatomical networks were constructed for each subject, multivariate pattern analysis was applied to classify the left mTLE from the right mTLE and extract the anatomical connectivity differences between the left and right mTLE patients. The classification results reveal 93.0% accuracy for the left mTLE versus the right mTLE, 93.4% accuracy for the left mTLE versus controls and 90.0% accuracy for the right mTLE versus controls. Compared with the right mTLE, the left mTLE exhibited a different connectivity pattern in the cortical-limbic network and cerebellum. The majority of the most discriminating anatomical connections were located within or across the cortical-limbic network and cerebellum, thereby indicating that these disease-related anatomical network alterations may give rise to a portion of the complex of emotional and memory deficit between the left and right mTLE. Moreover, the orbitofrontal gyrus, cingulate cortex, hippocampus and parahippocampal gyrus, which exhibit high discriminative power in classification, may play critical roles in the pathophysiology of mTLE. The current study demonstrated that anatomical connectivity differences between the left mTLE and the right mTLE may have the potential to serve as a neuroimaging biomarker to guide personalized diagnosis of the left and right mTLE.

Variability in connectivity patterns of fish with ontogenetic migrations: Modelling effects of abiotic and biotic factors

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Susanne Eva Tanner

2015-10-01

Full Text Available Connectivity is a critical property of marine fish populations as it drives population replenishment, determines colonization patterns and the resilience of populations to harvest. Understanding connectivity patterns is particularly important in species that present ontogenetic migrations and segregated habitat use during their life history, such as marine species with estuarine nursery areas. Albeit challenging, fish movement can be estimated and quantified using different methodologies depending on the life history stages of interest (e.g. biophysical modelling, otolith chemistry, genetic markers. Relative contributions from estuarine nursery areas to the adult coastal populations were determined using otolith elemental composition and maximum likelihood estimation for four commercially important species (Dicentrarchus labrax, Plathichtys flesus, Solea senegalensis and Solea solea and showed high interannual variability. Here, the effects of abiotic and biotic factors on the observed variability in connectivity rates and extent between estuarine juvenile and coastal adult subpopulations are investigated using generalized linear models (GLM and generalized mixed models (GMM. Abiotic factors impacting both larval and juvenile life history stages are included in the models (e.g. wind force and direction, NAO, water temperature while biotic factors relative to the estuarine residency of juvenile fish are evaluated (e.g. juvenile density, food availability. Factors contributing most to the observed variability in connectivity rates are singled out and compared among species. General trends are identified and results area discussed in the general context of identifying potential management frameworks applicable to different life stages and which may prove useful for ontogenetically migrating species.

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

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Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of

Modeling and analyzing stripe patterns in fish skin

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Zheng, Yibo; Zhang, Lei; Wang, Yuan; Liang, Ping; Kang, Junjian

2009-11-01

The formation mechanism of stripe patterns in the skin of tropical fishes has been investigated by a coupled two variable reaction diffusion model. Two types of spatial inhomogeneities have been introduced into a homogenous system. Several Turing modes pumped by the Turing instability give rise to a simple stripe pattern. It is found that the Turing mechanism can only determine the wavelength of stripe pattern. The orientation of stripe pattern is determined by the spatial inhomogeneity. Our numerical results suggest that it may be the most possible mechanism for the forming process of fish skin patterns.

Analyzing the association between functional connectivity of the brain and intellectual performance

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Pamplona, Gustavo S. P.; Santos Neto, Gérson S.; Rosset, Sara R. E.; Rogers, Baxter P.; Salmon, Carlos E. G.

2015-01-01

Measurements of functional connectivity support the hypothesis that the brain is composed of distinct networks with anatomically separated nodes but common functionality. A few studies have suggested that intellectual performance may be associated with greater functional connectivity in the fronto-parietal network and enhanced global efficiency. In this fMRI study, we performed an exploratory analysis of the relationship between the brain's functional connectivity and intelligence scores derived from the Portuguese language version of the Wechsler Adult Intelligence Scale (WAIS-III) in a sample of 29 people, born and raised in Brazil. We examined functional connectivity between 82 regions, including graph theoretic properties of the overall network. Some previous findings were extended to the Portuguese-speaking population, specifically the presence of small-world organization of the brain and relationships of intelligence with connectivity of frontal, pre-central, parietal, occipital, fusiform and supramarginal gyrus, and caudate nucleus. Verbal comprehension was associated with global network efficiency, a new finding. PMID:25713528

Analyzing the association between functional connectivity of the brain and intellectual performance

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Gustavo Santo Pedro Pamplona

2015-02-01

Full Text Available Measurements of functional connectivity support the hypothesis that the brain is composed of distinct networks with anatomically separated nodes but common functionality. A few studies have suggested that intellectual performance may be associated with greater functional connectivity in the fronto-parietal network and enhanced global efficiency. In this fMRI study, we performed an exploratory analysis of the relationship between the brain's functional connectivity and intelligence scores derived from the Portuguese language version of the Wechsler Adult Intelligence Scale (WAIS-III in a sample of 29 people, born and raised in Brazil. We examined functional connectivity between 82 regions, including graph theoretic properties of the overall network. Some previous findings were extended to the Portuguese-speaking population, specifically the presence of small-world organization of the brain and relationships of intelligence with connectivity of frontal, pre-central, parietal, occipital, fusiform and supramarginal gyrus and caudate nucleus. Verbal comprehension was associated with global network efficiency, a new finding.

VPA: an R tool for analyzing sequencing variants with user-specified frequency pattern

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Hu Qiang

2012-01-01

Full Text Available Abstract Background The massive amounts of genetic variant generated by the next generation sequencing systems demand the development of effective computational tools for variant prioritization. Findings VPA (Variant Pattern Analyzer is an R tool for prioritizing variants with specified frequency pattern from multiple study subjects in next-generation sequencing study. The tool starts from individual files of variant and sequence calls and extract variants with user-specified frequency pattern across the study subjects of interest. Several position level quality criteria can be incorporated into the variant extraction. It can be used in studies with matched pair design as well as studies with multiple groups of subjects. Conclusions VPA can be used as an automatic pipeline to prioritize variants for further functional exploration and hypothesis generation. The package is implemented in the R language and is freely available from http://vpa.r-forge.r-project.org.

Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study

NARCIS (Netherlands)

Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard Jack Anton; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F.

2014-01-01

The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state

Distributed patterns of occipito-parietal functional connectivity predict the precision of visual working memory.

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Galeano Weber, Elena M; Hahn, Tim; Hilger, Kirsten; Fiebach, Christian J

2017-02-01

Limitations in visual working memory (WM) quality (i.e., WM precision) may depend on perceptual and attentional limitations during stimulus encoding, thereby affecting WM capacity. WM encoding relies on the interaction between sensory processing systems and fronto-parietal 'control' regions, and differences in the quality of this interaction are a plausible source of individual differences in WM capacity. Accordingly, we hypothesized that the coupling between perceptual and attentional systems affects the quality of WM encoding. We combined fMRI connectivity analysis with behavioral modeling by fitting a variable precision and fixed capacity model to the performance data obtained while participants performed a visual delayed continuous response WM task. We quantified functional connectivity during WM encoding between occipital and parietal brain regions activated during both perception and WM encoding, as determined using a conjunction of two independent experiments. The multivariate pattern of voxel-wise inter-areal functional connectivity significantly predicted WM performance, most specifically the mean of WM precision but not the individual number of items that could be stored in memory. In particular, higher occipito-parietal connectivity was associated with higher behavioral mean precision. These results are consistent with a network perspective of WM capacity, suggesting that the efficiency of information flow between perceptual and attentional neural systems is a critical determinant of limitations in WM quality. Copyright © 2016 Elsevier Inc. All rights reserved.

Capturing and analyzing wheelchair maneuvering patterns with mobile cloud computing.

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Fu, Jicheng; Hao, Wei; White, Travis; Yan, Yuqing; Jones, Maria; Jan, Yih-Kuen

2013-01-01

Power wheelchairs have been widely used to provide independent mobility to people with disabilities. Despite great advancements in power wheelchair technology, research shows that wheelchair related accidents occur frequently. To ensure safe maneuverability, capturing wheelchair maneuvering patterns is fundamental to enable other research, such as safe robotic assistance for wheelchair users. In this study, we propose to record, store, and analyze wheelchair maneuvering data by means of mobile cloud computing. Specifically, the accelerometer and gyroscope sensors in smart phones are used to record wheelchair maneuvering data in real-time. Then, the recorded data are periodically transmitted to the cloud for storage and analysis. The analyzed results are then made available to various types of users, such as mobile phone users, traditional desktop users, etc. The combination of mobile computing and cloud computing leverages the advantages of both techniques and extends the smart phone's capabilities of computing and data storage via the Internet. We performed a case study to implement the mobile cloud computing framework using Android smart phones and Google App Engine, a popular cloud computing platform. Experimental results demonstrated the feasibility of the proposed mobile cloud computing framework.

Deafferentation-Induced Plasticity of Visual Callosal Connections: Predicting Critical Periods and Analyzing Cortical Abnormalities Using Diffusion Tensor Imaging

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Jaime F. Olavarria

2012-01-01

Full Text Available Callosal connections form elaborate patterns that bear close association with striate and extrastriate visual areas. Although it is known that retinal input is required for normal callosal development, there is little information regarding the period during which the retina is critically needed and whether this period correlates with the same developmental stage across species. Here we review the timing of this critical period, identified in rodents and ferrets by the effects that timed enucleations have on mature callosal connections, and compare it to other developmental milestones in these species. Subsequently, we compare these events to diffusion tensor imaging (DTI measurements of water diffusion anisotropy within developing cerebral cortex. We observed that the relationship between the timing of the critical period and the DTI-characterized developmental trajectory is strikingly similar in rodents and ferrets, which opens the possibility of using cortical DTI trajectories for predicting the critical period in species, such as humans, in which this period likely occurs prenatally. Last, we discuss the potential of utilizing DTI to distinguish normal from abnormal cerebral cortical development, both within the context of aberrant connectivity induced by early retinal deafferentation, and more generally as a potential tool for detecting abnormalities associated with neurodevelopmental disorders.

Pattern-mixture models for analyzing normal outcome data with proxy respondents.

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Shardell, Michelle; Hicks, Gregory E; Miller, Ram R; Langenberg, Patricia; Magaziner, Jay

2010-06-30

Studies of older adults often involve interview questions regarding subjective constructs such as perceived disability. In some studies, when subjects are unable (e.g. due to cognitive impairment) or unwilling to respond to these questions, proxies (e.g. relatives or other care givers) are recruited to provide responses in place of the subject. Proxies are usually not approached to respond on behalf of subjects who respond for themselves; thus, for each subject, data from only one of the subject or proxy are available. Typically, proxy responses are simply substituted for missing subject responses, and standard complete-data analyses are performed. However, this approach may introduce measurement error and produce biased parameter estimates. In this paper, we propose using pattern-mixture models that relate non-identifiable parameters to identifiable parameters to analyze data with proxy respondents. We posit three interpretable pattern-mixture restrictions to be used with proxy data, and we propose estimation procedures using maximum likelihood and multiple imputation. The methods are applied to a cohort of elderly hip-fracture patients. (c) 2010 John Wiley & Sons, Ltd.

Directional patterns of cross frequency phase and amplitude coupling within the resting state mimic patterns of fMRI functional connectivity

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Weaver, Kurt E.; Wander, Jeremiah D.; Ko, Andrew L.; Casimo, Kaitlyn; Grabowski, Thomas J.; Ojemann, Jeffrey G.; Darvas, Felix

2016-01-01

Functional imaging investigations into the brain's resting state interactions have yielded a wealth of insight into the intrinsic and dynamic neural architecture supporting cognition and behavior. Electrophysiological studies however have highlighted the fact that synchrony across large-scale cortical systems is composed of spontaneous interactions occurring at timescales beyond the traditional resolution of fMRI, a feature that limits the capacity of fMRI to draw inference on the true directional relationship between network nodes. To approach the question of directionality in resting state signals, we recorded resting state functional MRI (rsfMRI) and electrocorticography (ECoG) from four human subjects undergoing invasive epilepsy monitoring. Using a seed-point based approach, we employed phase-amplitude coupling (PAC) and biPhase Locking Values (bPLV), two measures of cross-frequency coupling (CFC) to explore both outgoing and incoming connections between the seed and all non-seed, site electrodes. We observed robust PAC between a wide range of low-frequency phase and high frequency amplitude estimates. However, significant bPLV, a CFC measure of phase-phase synchrony, was only observed at specific narrow low and high frequency bandwidths. Furthermore, the spatial patterns of outgoing PAC connectivity were most closely associated with the rsfMRI connectivity maps. Our results support the hypothesis that PAC is relatively ubiquitous phenomenon serving as a mechanism for coordinating high-frequency amplitudes across distant neuronal assemblies even in absence of overt task structure. Additionally, we demonstrate that the spatial distribution of a seed-point rsfMRI sensorimotor network is strikingly similar to specific patterns of directional PAC. Specifically, the high frequency activities of distal patches of cortex owning membership in a rsfMRI sensorimotor network were most likely to be entrained to the phase of a low frequency rhythm engendered from the

Design patterns for instructional materials that foster proficiency at analyzing and interpreting complex geoscience data

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Kastens, K. A.; Krumhansl, R.

2016-12-01

The Next Generation Science Standards incorporate a stronger emphasis on having students work with data than did prior standards. This emphasis is most obvious in Practice 4: Analyzing and Interpreting Data, but also permeates performance expectations built on Practice 2 when students test models, Practice 6 when students construct explanations, and Practice 7 when student test claims with evidence. To support curriculum developers who wish to guide high school students towards more sophisticated engagement with complex data, we analyzed a well-regarded body of instructional materials designed for use in introductory college courses (http://serc.carleton.edu/integrate/teaching_materials/). Our analysis sought design patterns that can be reused for a variety of topics at the high school or college level. We found five such patterns, each of which was used in at least half of the modules analyzed. We describe each pattern, provide an example, and hypothesize a theory of action that could explain how the sequence of activities leverages known perceptual, cognitive and/or social processes to foster learning from and about data. In order from most to least frequent, the observed design patterns are as follows: In Data Puzzles, students respond to guiding questions about high-value snippets of data pre-selected and sequenced by the curriculum developer to lead to an Aha! inference. In Pooling Data to See the Big Picture, small groups analyze different instances of analogous phenomenon (e.g. different hurricanes, or different divergent plate boundaries) and pool their insights to extract the commonalities that constitute the essence of that phenomenon. In Make a Decision or Recommendation, students combine geoscience data with other factors (such as economic or environmental justice concerns) to make a decision or recommendation about a human or societal action. In Predict-Observe-Explain, students make a prediction about what the Earth will look like under conditions

Influence of urban form on landscape pattern and connectivity in metropolitan regions: a comparative case study of Phoenix, AZ, USA, and Izmir, Turkey.

Science.gov (United States)

Park, Sohyun; Hepcan, Çiğdem C; Hepcan, Şerif; Cook, Edward A

2014-10-01

Although ecological connectivity conservation in urban areas has recently been recognized as an important issue, less is known about its relationship to urban form and landscape pattern. This study investigates how urban morphology influences regional ecosystem pattern and landscape connectivity. Two metropolitan landscapes, Phoenix, AZ, USA, and Izmir, Turkey, were compared, both of which are fast-growing regions in their national context. A wide range of variables were considered for identifying natural and urban properties. The natural characteristics include typology of urban ecosystems, urban to natural cover ratio, dominant habitat type, urban biodiversity, landscape context, and connectivity conservation efforts. Urban parameters examine urban form, urban extent, urban cover proportion, growth rate, populations, urban gradient, major drivers of urbanization, urban density, and mode/approach of urban development. Twelve landscape metrics were measured and compared across the natural patches. Results show that there is little difference in landscape connectivity in the rural zones of Phoenix and Izmir, although Phoenix has slightly higher connectivity values. The connectivity variance in urbanized areas, however, is significantly dependent on the region. For example, Phoenix urban zones have substantially lower connectivity than either urban or suburban zones in Izmir. Findings demonstrate that small and compact urban settlements with more dense populations are more likely to conserve landscape connectivity compared to multiple-concentric but amalgamated urban form spreading all over the landscape (aka urban sprawl).

Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago.

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Xiaolu Zhou

Full Text Available The growing number of bike sharing systems (BSS in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities.

Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago.

Science.gov (United States)

Zhou, Xiaolu

2015-01-01

The growing number of bike sharing systems (BSS) in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities.

Preschool anxiety disorders predict different patterns of amygdala-prefrontal connectivity at school-age.

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Kimberly L H Carpenter

Full Text Available In this prospective, longitudinal study of young children, we examined whether a history of preschool generalized anxiety, separation anxiety, and/or social phobia is associated with amygdala-prefrontal dysregulation at school-age. As an exploratory analysis, we investigated whether distinct anxiety disorders differ in the patterns of this amygdala-prefrontal dysregulation.Participants were children taking part in a 5-year study of early childhood brain development and anxiety disorders. Preschool symptoms of generalized anxiety, separation anxiety, and social phobia were assessed with the Preschool Age Psychiatric Assessment (PAPA in the first wave of the study when the children were between 2 and 5 years old. The PAPA was repeated at age 6. We conducted functional MRIs when the children were 5.5 to 9.5 year old to assess neural responses to viewing of angry and fearful faces.A history of preschool social phobia predicted less school-age functional connectivity between the amygdala and the ventral prefrontal cortices to angry faces. Preschool generalized anxiety predicted less functional connectivity between the amygdala and dorsal prefrontal cortices in response to fearful faces. Finally, a history of preschool separation anxiety predicted less school-age functional connectivity between the amygdala and the ventral prefrontal cortices to angry faces and greater school-age functional connectivity between the amygdala and dorsal prefrontal cortices to angry faces.Our results suggest that there are enduring neurobiological effects associated with a history of preschool anxiety, which occur over-and-above the effect of subsequent emotional symptoms. Our results also provide preliminary evidence for the neurobiological differentiation of specific preschool anxiety disorders.

Dense neuron clustering explains connectivity statistics in cortical microcircuits.

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Vladimir V Klinshov

Full Text Available Local cortical circuits appear highly non-random, but the underlying connectivity rule remains elusive. Here, we analyze experimental data observed in layer 5 of rat neocortex and suggest a model for connectivity from which emerge essential observed non-random features of both wiring and weighting. These features include lognormal distributions of synaptic connection strength, anatomical clustering, and strong correlations between clustering and connection strength. Our model predicts that cortical microcircuits contain large groups of densely connected neurons which we call clusters. We show that such a cluster contains about one fifth of all excitatory neurons of a circuit which are very densely connected with stronger than average synapses. We demonstrate that such clustering plays an important role in the network dynamics, namely, it creates bistable neural spiking in small cortical circuits. Furthermore, introducing local clustering in large-scale networks leads to the emergence of various patterns of persistent local activity in an ongoing network activity. Thus, our results may bridge a gap between anatomical structure and persistent activity observed during working memory and other cognitive processes.

Algebraic connectivity of brain networks shows patterns of segregation leading to reduced network robustness in Alzheimer's disease

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Daianu, Madelaine; Jahanshad, Neda; Nir, Talia M.; Leonardo, Cassandra D.; Jack, Clifford R.; Weiner, Michael W.; Bernstein, Matthew A.; Thompson, Paul M.

2015-01-01

Measures of network topology and connectivity aid the understanding of network breakdown as the brain degenerates in Alzheimer's disease (AD). We analyzed 3-Tesla diffusion-weighted images from 202 patients scanned by the Alzheimer's Disease Neuroimaging Initiative – 50 healthy controls, 72 with early- and 38 with late-stage mild cognitive impairment (eMCI/lMCI) and 42 with AD. Using whole-brain tractography, we reconstructed structural connectivity networks representing connections between pairs of cortical regions. We examined, for the first time in this context, the network's Laplacian matrix and its Fiedler value, describing the network's algebraic connectivity, and the Fiedler vector, used to partition a graph. We assessed algebraic connectivity and four additional supporting metrics, revealing a decrease in network robustness and increasing disarray among nodes as dementia progressed. Network components became more disconnected and segregated, and their modularity increased. These measures are sensitive to diagnostic group differences, and may help understand the complex changes in AD. PMID:26640830

Development of new process network for gas chromatograph and analyzers connected with SCADA system and Digital Control Computers at Cernavoda NPP Unit 1

International Nuclear Information System (INIS)

Deneanu, Cornel; Popa Nemoiu, Dragos; Nica, Dana; Bucur, Cosmin

2007-01-01

The continuous monitoring of gas mixture concentrations (deuterium/ hydrogen/oxygen/nitrogen) accumulated in 'Moderator Cover Gas', 'Liquid Control Zone' and 'Heat Transport D 2 O Storage Tank Cover Gas', as well as the continuous monitoring of Heavy Water into Light Water concentration in 'Boilers Steam', 'Boilers Blown Down', 'Moderator heat exchangers', and 'Recirculated Water System', sensing any leaks of Cernavoda NPP U1 led to requirement of developing a new process network for gas chromatograph and analyzers connected to the SCADA system and Digital Control Computers of Cernavoda NPP Unit 1. In 2005 it was designed and implemented the process network for gas chromatograph which connected the gas chromatograph equipment to the SCADA system and Digital Control Computers of the Cernavoda NPP Unit 1. Later this process network for gas chromatograph has been extended to connect the AE13 and AE14 Fourier Transform Infrared (FTIR) analyzers with either. The Gas Chromatograph equipment measures with best accuracy the mixture gases (deuterium/ hydrogen/oxygen/nitrogen) concentration. The Fourier Transform Infrared (FTIR) AE13 and AE14 Analyzers measure the Heavy Water into Light Water concentration in Boilers Steam, Boilers BlownDown, Moderator heat exchangers, and Recirculated Water System, monitoring and signaling any leaks. The Gas Chromatograph equipment and Fourier Transform Infrared (FTIR) AE13 and AE14 Analyzers use the new OPC (Object Link Embedded for Process Control) technologies available in ABB's VistaNet network for interoperability with automation equipment. This new process network has interconnected the ABB chromatograph and Fourier Transform Infrared analyzers with plant Digital Control Computers using new technology. The result was an increased reliability and capability for inspection and improved system safety

Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study.

Science.gov (United States)

Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard J A; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F

2014-01-01

The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state fluctuations map to the well known architecture of the visual system. We investigated resting state connectivity at both a fine and large scale within and across visual areas V1, V2 and V3 in ten human subjects using a 7Tesla scanner. We found evidence for several coexisting and overlapping connectivity structures at different spatial scales. At the fine-scale level we found enhanced connectivity between the same topographic locations in the fieldmaps of V1, V2 and V3, enhanced connectivity to the contralateral functional homologue, and to a lesser extent enhanced connectivity between iso-eccentric locations within the same visual area. However, by far the largest proportion of the resting state fluctuations occurred within large-scale bilateral networks. These large-scale networks mapped to some extent onto the architecture of the visual system and could thereby obscure fine-scale connectivity. In fact, most of the fine-scale connectivity only became apparent after the large-scale network fluctuations were filtered from the timeseries. We conclude that fMRI resting state fluctuations in the visual cortex may in fact be a composite signal of different overlapping sources. Isolating the different sources could enhance correlations between BOLD and electrophysiological correlates of resting state activity. © 2013 Elsevier Inc. All rights reserved.

Schaffer collateral inputs to CA1 excitatory and inhibitory neurons follow different connectivity rules.

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Kwon, Osung; Feng, Linqing; Druckmann, Shaul; Kim, Jinhyun

2018-05-04

Neural circuits, governed by a complex interplay between excitatory and inhibitory neurons, are the substrate for information processing, and the organization of synaptic connectivity in neural network is an important determinant of circuit function. Here, we analyzed the fine structure of connectivity in hippocampal CA1 excitatory and inhibitory neurons innervated by Schaffer collaterals (SCs) using mGRASP in male mice. Our previous study revealed spatially structured synaptic connectivity between CA3-CA1 pyramidal cells (PCs). Surprisingly, parvalbumin-positive interneurons (PVs) showed a significantly more random pattern spatial structure. Notably, application of Peters' Rule for synapse prediction by random overlap between axons and dendrites enhanced structured connectivity in PCs, but, by contrast, made the connectivity pattern in PVs more random. In addition, PCs in a deep sublayer of striatum pyramidale appeared more highly structured than PCs in superficial layers, and little or no sublayer specificity was found in PVs. Our results show that CA1 excitatory PCs and inhibitory PVs innervated by the same SC inputs follow different connectivity rules. The different organizations of fine scale structured connectivity in hippocampal excitatory and inhibitory neurons provide important insights into the development and functions of neural networks. SIGNIFICANCE STATEMENT Understanding how neural circuits generate behavior is one of the central goals of neuroscience. An important component of this endeavor is the mapping of fine-scale connection patterns that underlie, and help us infer, signal processing in the brain. Here, using our recently developed synapse detection technology (mGRASP and neuTube), we provide detailed profiles of synaptic connectivity in excitatory (CA1 pyramidal) and inhibitory (CA1 parvalbumin-positive) neurons innervated by the same presynaptic inputs (CA3 Schaffer collaterals). Our results reveal that these two types of CA1 neurons follow

A deep convolutional neural network to analyze position averaged convergent beam electron diffraction patterns.

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Xu, W; LeBeau, J M

2018-05-01

We establish a series of deep convolutional neural networks to automatically analyze position averaged convergent beam electron diffraction patterns. The networks first calibrate the zero-order disk size, center position, and rotation without the need for pretreating the data. With the aligned data, additional networks then measure the sample thickness and tilt. The performance of the network is explored as a function of a variety of variables including thickness, tilt, and dose. A methodology to explore the response of the neural network to various pattern features is also presented. Processing patterns at a rate of  ∼ 0.1 s/pattern, the network is shown to be orders of magnitude faster than a brute force method while maintaining accuracy. The approach is thus suitable for automatically processing big, 4D STEM data. We also discuss the generality of the method to other materials/orientations as well as a hybrid approach that combines the features of the neural network with least squares fitting for even more robust analysis. The source code is available at https://github.com/subangstrom/DeepDiffraction. Copyright © 2018 Elsevier B.V. All rights reserved.

Prefrontal-limbic Functional Connectivity during Acquisition and Extinction of Conditioned Fear.

Science.gov (United States)

Barrett, Douglas W; Gonzalez-Lima, F

2018-04-15

This study is a new analysis to obtain novel metabolic data on the functional connectivity of prefrontal-limbic regions in Pavlovian fear acquisition and extinction of tone-footshock conditioning. Mice were analyzed with the fluorodeoxyglucose (FDG) autoradiographic method to metabolically map regional brain activity. New FDG data were sampled from the nuclei of the habenula and other regions implicated in aversive conditioning, such as infralimbic cortex, amygdala and periaqueductal gray regions. The activity patterns among these regions were inter-correlated during acquisition, extinction or pseudorandom training to develop a functional connectivity model. Two subdivisions of the habenular complex showed increased activity after acquisition relative to extinction, with the pseudorandom group intermediate between the other two groups. Significant acquisition activation effects were also found in centromedial amygdala, dorsomedial and ventrolateral periaqueductal gray. FDG uptake increases during extinction were found only in dorsal and ventral infralimbic cortex. The overall pattern of activity correlations between these regions revealed extensive but differential functional connectivity during acquisition and extinction training, with less functional connectivity found after pseudorandom training. Interestingly, habenula nuclei showed a distinct pattern of inter-correlations with amygdala nuclei during extinction. The functional connectivity model revealed changing interactions among infralimbic cortex, amygdala, habenula and periaqueductal gray regions through the stages of Pavlovian fear acquisition and extinction. This study provided new data on the contributions of the habenula to fear conditioning, and revealed previously unreported infralimbic-amygdala-habenula-periaqueductal gray interactions implicated in acquisition and extinction of conditioned fear. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

On Non-Universality of Solar-Terrestrial Connections

Science.gov (United States)

Pustilnik, Lev; Yom Din, Gregory

The discussion on the principal possibility of a causal chain from solar activity and space weather to the earth weather and agriculture price dynamics continues over 200 years from the first publication of Herschel (1801) up to the current time. We analyze main arguments of the two sides and show that the root of the critics of this possibility lies in the wide accepted conception of the universality of the solar-terrestrial connection (that can appear, for example, in daily and seasonal variations) what suggest that the effect can be observed in any historical period and in any region. We show that this expectation is not correct because of the solar-terrestrial connections generated by different sides of solar activity with different agents of solar magnetic dynamo process that have different and non-stable phase patterns. We remind that the realization of the causal chain “solar activity/space weather” - “earth weather” - “crops” -“market reaction” may have a place only in specific historical periods and in specific zones where and when the three necessary conditions hold true. This limitation leads to one of four possible scenarios of the market reaction. We show that the critical arguments used for rejecting a principal possibility of the causal connection “solar activity” - Earth agriculture markets” are based on neglecting the three necessary conditions for realization of this connection, and on analyzing periods and regions when and where the necessary conditions are not hold.

Mapping Dynamics of Inundation Patterns of Two Largest River-Connected Lakes in China: A Comparative Study

OpenAIRE

Guiping Wu; Yuanbo Liu

2016-01-01

Poyang Lake and Dongting Lake are the two largest freshwater lakes in China. The lakes are located approximately 300 km apart on the middle reaches of the Yangtze River and are differently connected through their respective tributary systems, which will lead to different river–lake water exchanges and discharges. Thus, differences in their morphological and hydrological conditions should induce individual lake spatio-temporal inundation patterns. Quantitative comparative analyses of the dynam...

A Method for Using Adjacency Matrices to Analyze the Connections Students Make within and between Concepts: The Case of Linear Algebra

Science.gov (United States)

Selinski, Natalie E.; Rasmussen, Chris; Wawro, Megan; Zandieh, Michelle

2014-01-01

The central goals of most introductory linear algebra courses are to develop students' proficiency with matrix techniques, to promote their understanding of key concepts, and to increase their ability to make connections between concepts. In this article, we present an innovative method using adjacency matrices to analyze students' interpretation…

Application of a clustering-remote sensing method in analyzing security patterns

Science.gov (United States)

López-Caloca, Alejandra; Martínez-Viveros, Elvia; Chapela-Castañares, José Ignacio

2009-04-01

In Mexican academic and government circles, research on criminal spatial behavior has been neglected. Only recently has there been an interest in criminal data geo-reference. However, more sophisticated spatial analyses models are needed to disclose spatial patterns of crime and pinpoint their changes overtime. The main use of these models lies in supporting policy making and strategic intelligence. In this paper we present a model for finding patterns associated with crime. It is based on a fuzzy logic algorithm which finds the best fit within cluster numbers and shapes of groupings. We describe the methodology for building the model and its validation. The model was applied to annual data for types of felonies from 2005 to 2006 in the Mexican city of Hermosillo. The results are visualized as a standard deviational ellipse computed for the points identified to be a "cluster". These areas indicate a high to low demand for public security, and they were cross-related to urban structure analyzed by SPOT images and statistical data such as population, poverty levels, urbanization, and available services. The fusion of the model results with other geospatial data allows detecting obstacles and opportunities for crime commission in specific high risk zones and guide police activities and criminal investigations.

Functional connectivity patterns reflect individual differences in conflict adaptation.

Science.gov (United States)

Wang, Xiangpeng; Wang, Ting; Chen, Zhencai; Hitchman, Glenn; Liu, Yijun; Chen, Antao

2015-04-01

Individuals differ in the ability to utilize previous conflict information to optimize current conflict resolution, which is termed the conflict adaptation effect. Previous studies have linked individual differences in conflict adaptation to distinct brain regions. However, the network-based neural mechanisms subserving the individual differences of the conflict adaptation effect have not been studied. The present study employed a psychophysiological interaction (PPI) analysis with a color-naming Stroop task to examine this issue. The main results were as follows: (1) the anterior cingulate cortex (ACC)-seeded PPI revealed the involvement of the salience network (SN) in conflict adaptation, while the posterior parietal cortex (PPC)-seeded PPI revealed the engagement of the central executive network (CEN). (2) Participants with high conflict adaptation effect showed higher intra-CEN connectivity and lower intra-SN connectivity; while those with low conflict adaptation effect showed higher intra-SN connectivity and lower intra-CEN connectivity. (3) The PPC-centered intra-CEN connectivity positively predicted the conflict adaptation effect; while the ACC-centered intra-SN connectivity had a negative correlation with this effect. In conclusion, our data demonstrated that conflict adaptation is likely supported by the CEN and the SN, providing a new perspective on studying individual differences in conflict adaptation on the basis of large-scale networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

FHR patterns that become significant in connection with ST waveform changes and metabolic acidosis at birth.

Science.gov (United States)

Rosén, Karl G; Norén, Håkan; Carlsson, Ann

2018-04-18

Recent developments have produced new CTG classification systems and the question is to what extent these may affect the model of FHR + ST interpretation? The two new systems (FIGO2015 and SSOG2017) classify FHR + ST events differently from the current CTG classification system used in the STAN interpretation algorithm (STAN2007). Identify the predominant FHR patterns in connection with ST events in cases of cord artery metabolic acidosis missed by the different CTG classification systems. Indicate to what extent STAN clinical guidelines could be modified enhancing the sensitivity. Provide a pathophysiological rationale. Forty-four cases with umbilical cord artery metabolic acidosis were retrieved from a European multicenter database. Significant FHR + ST events were evaluated post hoc in consensus by an expert panel. Eighteen cases were not identified as in need of intervention and regarded as negative in the sensitivity analysis. In 12 cases, ST changes occurred but the CTG was regarded as reassuring. Visual analysis of the FHR + ST tracings revealed specific FHR patterns: Conclusion: These findings indicate FHR + ST analysis may be undertaken regardless of CTG classification system provided there is a more physiologically oriented approach to FHR assessment in connection with an ST event.

River-floodplain Hydrologic Connectivity: Impact on Temporal and Spatial Floodplain Water Quality and Productivity Patterns

Science.gov (United States)

Gallo, E. L.; Ahearn, D.; Dahlgren, R. A.; Grosholz, E.

2003-12-01

Nutrient spiraling and cycling are critical processes for floodplain systems, but these have not been well studied in western North America. Floodplain production and function relies on the integrity of river-floodplain interactions, particularly during periods of hydrologic connectivity. The purpose of this study was to: (1) determine the importance of the timing and duration of river-floodplain hydrologic connectivity, (2) link flood event water quality to subsequent primary and secondary production, and (3) identify temporal and spatial patterns of floodplain production. The Cosumnes River watershed transports surface runoff and snowmelt from the Sierra Nevadas to the Sacramento-San Joaquin Delta. It is one of the few watersheds in California that has no major water diversions or impoundments; therefore the river responds to the natural watershed hydrology. The study site in southern Sacramento County is an unmanaged experimental floodplain, one of the few remaining floodplains in California. Weekly and flood-event water quality and macroinvertebrate sampling was conducted during the flood season from January through June in 2001 and 2002. Both water years were characterized by historically low river flows. On average, volatile suspended solids in the water column increased from 5 mg/l to 10 mg/l during early season periods of hydrologic connectivity (December - February), suggesting that during watershed flushing flood events, the river acts as a source of nutrients and organic matter to the floodplain. Following a flood event, invertebrate concentrations decreased on average from 26,000 individuals/m3 to 9,000 individuals/m3 for zooplankton and from 350 individuals/m2 to 65 individuals/m2 for benthic macro-invertebrate, suggesting a net dilution of invertebrates during flood events. Chlorophyll a (chl-a) levels were also diluted during flood events, on average from 25 ppb to 5 ppb. Zooplankton densities and chl-a levels quickly rose after flood events. On

Estimates of connectivity reveal non-equilibrium epiphyte occurrence patterns almost 180 years after habitat decline.

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Johansson, Victor; Snäll, Tord; Ranius, Thomas

2013-06-01

Habitat loss is a major cause of species decline and extinction. Immediately after habitat loss, species occurrences are not in equilibrium with the new landscape and more closely reflect the previous landscape structure. Species with slow colonisation-extinction dynamics may display long time-lags before reaching a new equilibrium. We investigated the importance of connectivity to current and historical dispersal sources with the aim of explaining the occurrence pattern of epiphytic lichens with different traits among 104 old oaks. We used oak survey data collected from 1830 and 2009 for a Swedish landscape where oak densities declined drastically shortly after 1830. We fitted a commonly used connectivity measure and estimated the confidence interval for the spatial scale parameter. Small differences in the spatial scale parameter resulted in large differences in model fit. Connectivity to trees in 1830 better explained the occurrence of three of the four species compared to the connectivity in 2009. The explanatory power of the historical landscape structure was highest for the species with traits that may result in a low colonisation rate--both a narrow niche (here few suitable trees) and large dispersal propagules. The results suggest that oak-dependent epiphytic lichens have not reached equilibrium with the spatial landscape structure 180 years after the drastic decline in habitat. For the long-term persistence of epiphytes associated with old trees, conservation efforts should focus on (1) protecting and restoring stands where specialised species with large dispersal propagules (i.e. with low colonisation rates) occur today and (2) promoting tree regeneration in their near vicinity.

Altered interhemispheric functional connectivity in patients with anisometropic and strabismic amblyopia: a resting-state fMRI study

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Liang, Minglong; Xie, Bing; Yin, Xuntao; Wang, Jian [Third Military Medical University, Department of Radiology, Southwest Hospital, 30 Gaotanyan Street, Shapingba District, Chongqing (China); Yang, Hong; Wang, Hao [Third Military Medical University, Ophthalmology Research Center, Southwest Eye Hospital/Southwest Hospital, Chongqing (China); Yu, Longhua [Third Military Medical University, Department of Radiology, Southwest Hospital, 30 Gaotanyan Street, Shapingba District, Chongqing (China); 401st Hospital of PLA, Department of Radiology, Qingdao (China); He, Sheng [University of Minnesota Twin Cities, Department of Psychology, Minneapolis, MN (United States)

2017-05-15

Altered brain functional connectivity has been reported in patients with amblyopia by recent neuroimaging studies. However, relatively little is known about the alterations in interhemispheric functional connectivity in amblyopia. The present study aimed to investigate the functional connectivity patterns between homotopic regions across hemispheres in patients with anisometropic and strabismic amblyopia under resting state. Nineteen monocular anisometropic amblyopia (AA), 18 strabismic amblyopia (SA), and 20 normal-sight controls (NC) were enrolled in this study. After a comprehensive ophthalmologic examination, resting-state fMRI scanning was performed in all participants. The pattern of the interhemispheric functional connectivity was measured with the voxel-mirrored homotopic connectivity (VMHC) approach. VMHC values differences within and between three groups were compared, and correlations between VMHC values and each the clinical variable were also analyzed. Altered VMHC was observed in AA and SA patients in lingual gyrus and fusiform gyrus compared with NC subjects. The altered VMHC of lingual gyrus showed a pattern of AA > SA > NC, while the altered VMHC of fusiform gyrus showed a pattern of AA > NC > SA. Moreover, the VMHC values of lingual gyrus were positively correlated with the stereoacuity both in AA and SA patients, and the VMHC values of fusiform gyrus were positively correlated with the amount of anisometropia just in AA patients. These findings suggest that interhemispheric functional coordination between several homotopic visual-related brain regions is impaired both in AA and SA patients under resting state and revealed the similarities and differences in interhemispheric functional connectivity between the anisometropic and strabismic amblyopia. (orig.)

Altered interhemispheric functional connectivity in patients with anisometropic and strabismic amblyopia: a resting-state fMRI study

International Nuclear Information System (INIS)

Liang, Minglong; Xie, Bing; Yin, Xuntao; Wang, Jian; Yang, Hong; Wang, Hao; Yu, Longhua; He, Sheng

2017-01-01

Altered brain functional connectivity has been reported in patients with amblyopia by recent neuroimaging studies. However, relatively little is known about the alterations in interhemispheric functional connectivity in amblyopia. The present study aimed to investigate the functional connectivity patterns between homotopic regions across hemispheres in patients with anisometropic and strabismic amblyopia under resting state. Nineteen monocular anisometropic amblyopia (AA), 18 strabismic amblyopia (SA), and 20 normal-sight controls (NC) were enrolled in this study. After a comprehensive ophthalmologic examination, resting-state fMRI scanning was performed in all participants. The pattern of the interhemispheric functional connectivity was measured with the voxel-mirrored homotopic connectivity (VMHC) approach. VMHC values differences within and between three groups were compared, and correlations between VMHC values and each the clinical variable were also analyzed. Altered VMHC was observed in AA and SA patients in lingual gyrus and fusiform gyrus compared with NC subjects. The altered VMHC of lingual gyrus showed a pattern of AA > SA > NC, while the altered VMHC of fusiform gyrus showed a pattern of AA > NC > SA. Moreover, the VMHC values of lingual gyrus were positively correlated with the stereoacuity both in AA and SA patients, and the VMHC values of fusiform gyrus were positively correlated with the amount of anisometropia just in AA patients. These findings suggest that interhemispheric functional coordination between several homotopic visual-related brain regions is impaired both in AA and SA patients under resting state and revealed the similarities and differences in interhemispheric functional connectivity between the anisometropic and strabismic amblyopia. (orig.)

Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

OpenAIRE

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

2016-01-01

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

Differential Patterns of Abnormal Activity and Connectivity in the Amygdala-Prefrontal Circuitry in Bipolar-I and Bipolar-NOS Youth

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Ladouceur, Cecile D.; Farchione, Tiffany; Diwadkar, Vaibhav; Pruitt, Patrick; Radwan, Jacqueline; Axelson, David A.; Birmaher, Boris; Phillips, Mary L.

2011-01-01

Objective: The functioning of neural systems supporting emotion processing and regulation in youth with bipolar disorder not otherwise specified (BP-NOS) remains poorly understood. We sought to examine patterns of activity and connectivity in youth with BP-NOS relative to youth with bipolar disorder type I (BP-I) and healthy controls (HC). Method:…

Connectivity and Dispersal Patterns of Protected Biogenic Reefs: Implications for the Conservation of Modiolus modiolus (L. in the Irish Sea.

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Kate Gormley

Full Text Available Biogenic reefs created by Modiolus modiolus (Linnaeus, 1758 (horse mussel reefs are marine habitats which support high levels of species biodiversity and provide valuable ecosystem services. Currently, M. modiolus reefs are listed as a threatened and/or declining species and habitat in all OSPAR regions and thus are highlighted as a conservation priority under the EU Marine Strategy Framework Directive (MSFD. Determining patterns of larval dispersal and genetic connectivity of remaining horse mussel populations can inform management efforts and is a critical component of effective marine spatial planning (MSP. Larval dispersal patterns and genetic structure were determined for several M. modiolus bed populations in the Irish Sea including those in Wales (North Pen Llŷn, Isle of Man (Point of Ayre and Northern Ireland (Ards Peninsula and Strangford Lough. Simulations of larval dispersal suggested extant connectivity between populations within the Irish Sea. Results from the genetic analysis carried out using newly developed microsatellite DNA markers were consistent with those of the biophysical model. Results indicated moderately significant differentiation between the Northern Ireland populations and those in the Isle of Man and Wales. Simulations of larval dispersal over a 30 day pelagic larval duration (PLD suggest that connectivity over a spatial scale of 150km is possible between some source and sink populations. However, it appears unlikely that larvae from Northern Ireland will connect directly with sites on the Llŷn or Isle of Man. It also appears unlikely that larvae from the Llŷn connect directly to any of the other sites. Taken together the data establishes a baseline for underpinning management and conservation of these important and threatened marine habitats in the southern part of the known range.

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

International Nuclear Information System (INIS)

Wang, Xun-Heng; Li, Lihua

2015-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-05-15

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

Process connectivity in a naturally prograding river delta

Science.gov (United States)

Sendrowski, Alicia; Passalacqua, Paola

2017-03-01

River deltas are lowland systems that can display high hydrological connectivity. This connectivity can be structural (morphological connections), functional (control of fluxes), and process connectivity (information flow from system drivers to sinks). In this work, we quantify hydrological process connectivity in Wax Lake Delta, coastal Louisiana, by analyzing couplings among external drivers (discharge, tides, and wind) and water levels recorded at five islands and one channel over summer 2014. We quantify process connections with information theory, a branch of mathematics concerned with the communication of information. We represent process connections as a network; variables serve as network nodes and couplings as network links describing the strength, direction, and time scale of information flow. Comparing process connections at long (105 days) and short (10 days) time scales, we show that tides exhibit daily synchronization with water level, with decreasing strength from downstream to upstream, and that tides transfer information as tides transition from spring to neap. Discharge synchronizes with water level and the time scale of its information transfer compares well to physical travel times through the system, computed with a hydrodynamic model. Information transfer and physical transport show similar spatial patterns, although information transfer time scales are larger than physical travel times. Wind events associated with water level setup lead to increased process connectivity with highly variable information transfer time scales. We discuss the information theory results in the context of the hydrologic behavior of the delta, the role of vegetation as a connector/disconnector on islands, and the applicability of process networks as tools for delta modeling results.

Population genomics meet Lagrangian simulations: Oceanographic patterns and long larval duration ensure connectivity among Paracentrotus lividus populations in the Adriatic and Ionian seas.

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Paterno, Marta; Schiavina, Marcello; Aglieri, Giorgio; Ben Souissi, Jamila; Boscari, Elisa; Casagrandi, Renato; Chassanite, Aurore; Chiantore, Mariachiara; Congiu, Leonardo; Guarnieri, Giuseppe; Kruschel, Claudia; Macic, Vesna; Marino, Ilaria A M; Papetti, Chiara; Patarnello, Tomaso; Zane, Lorenzo; Melià, Paco

2017-04-01

Connectivity between populations influences both their dynamics and the genetic structuring of species. In this study, we explored connectivity patterns of a marine species with long-distance dispersal, the edible common sea urchin Paracentrotus lividus , focusing mainly on the Adriatic-Ionian basins (Central Mediterranean). We applied a multidisciplinary approach integrating population genomics, based on 1,122 single nucleotide polymorphisms (SNPs) obtained from 2b-RAD in 275 samples, with Lagrangian simulations performed with a biophysical model of larval dispersal. We detected genetic homogeneity among eight population samples collected in the focal Adriatic-Ionian area, whereas weak but significant differentiation was found with respect to two samples from the Western Mediterranean (France and Tunisia). This result was not affected by the few putative outlier loci identified in our dataset. Lagrangian simulations found a significant potential for larval exchange among the eight Adriatic-Ionian locations, supporting the hypothesis of connectivity of P. lividus populations in this area. A peculiar pattern emerged from the comparison of our results with those obtained from published P. lividus cytochrome b (cytb) sequences, the latter revealing genetic differentiation in the same geographic area despite a smaller sample size and a lower power to detect differences. The comparison with studies conducted using nuclear markers on other species with similar pelagic larval durations in the same Adriatic-Ionian locations indicates species-specific differences in genetic connectivity patterns and warns against generalizing single-species results to the entire community of rocky shore habitats.

Network based approaches reveal clustering in protein point patterns

Science.gov (United States)

Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang

2014-03-01

Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.

Electroconvulsive therapy-induced brain functional connectivity predicts therapeutic efficacy in patients with schizophrenia: a multivariate pattern recognition study.

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Li, Peng; Jing, Ri-Xing; Zhao, Rong-Jiang; Ding, Zeng-Bo; Shi, Le; Sun, Hong-Qiang; Lin, Xiao; Fan, Teng-Teng; Dong, Wen-Tian; Fan, Yong; Lu, Lin

2017-05-11

REVEAL GOOD CANDIDATES FOR BRAIN STIMULATION: Connectivity patterns in the brain may help identify patients with schizophrenia most likely to benefit from electroconvulsive therapy. A team led by Lin Lu from Peking University, China, and Yong Fan from the University of Pennsylvania, USA, took functional magnetic resonance imaging (MRI) scans of 34 people with schizophrenia and 34 control individuals without mental illness. Those with schizophrenia were scanned before and after treatment; some received antipsychotics alone, others received medication plus electroconvulsive therapy. The researchers created organizational brain maps known as "intrinsic connectivity networks" for each individual, and showed that the neuroimaging pattern could discriminate between people with and without schizophrenia. For the schizophrenia patients, the connectivity networks taken prior to treatment also helped predict who would benefit from the brain-stimulation procedure. Such a biomarker could prove a useful diagnostic tool for clinicians.

Global imprint of historical connectivity on freshwater fish biodiversity.

Science.gov (United States)

Dias, Murilo S; Oberdorff, Thierry; Hugueny, Bernard; Leprieur, Fabien; Jézéquel, Céline; Cornu, Jean-François; Brosse, Sébastien; Grenouillet, Gael; Tedesco, Pablo A

2014-09-01

The relative importance of contemporary and historical processes is central for understanding biodiversity patterns. While several studies show that past conditions can partly explain the current biodiversity patterns, the role of history remains elusive. We reconstructed palaeo-drainage basins under lower sea level conditions (Last Glacial Maximum) to test whether the historical connectivity between basins left an imprint on the global patterns of freshwater fish biodiversity. After controlling for contemporary and past environmental conditions, we found that palaeo-connected basins displayed greater species richness but lower levels of endemism and beta diversity than did palaeo-disconnected basins. Palaeo-connected basins exhibited shallower distance decay of compositional similarity, suggesting that palaeo-river connections favoured the exchange of fish species. Finally, we found that a longer period of palaeo-connection resulted in lower levels of beta diversity. These findings reveal the first unambiguous results of the role played by history in explaining the global contemporary patterns of biodiversity. © 2014 John Wiley & Sons Ltd/CNRS.

Both Hypo-Connectivity and Hyper-Connectivity of the Insular Subregions Associated With Severity in Children With Autism Spectrum Disorders

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Jinping Xu

2018-04-01

Full Text Available Some studies identified hypo-connectivity, while others showed hyper-connectivity of the insula in the autism spectrum disorders (ASD. These contradictory findings leave open the question of whether and to what extent functional connectivity of the insula is altered and how functional connectivity of the insula is associated with the severity of ASD. A newly emerging insular atlas that comprises multiple functionally differentiated subregions provides a new framework to interpret the functional significance of insular findings and uncover the mechanisms underlying the severity of ASD. Using the new insular atlas, the present study aimed to investigate the distinct functional connectivity of the insular subregions and their associations with ASD severity in a cohort of 49 children with ASD and 33 typically developing (TD subjects. We found that compared with TD group, the ASD group showed different connectivity patterns in the left ventral agranular insula, right ventral dysgranular and granular insula, and dorsal dysgranular insula, characterized by significant hyper-connectivity and/or hypo-connectivity with special brain regions. Furthermore, both the hypo-connectivity and hyper-connectivity patterns of the insular subregions were significantly associated with the severity of ASD symptoms. Our research demonstrated distinct functional connectivity patterns of the insular subregions and emphasized the importance of the subdivisions within the insula to the potential impact of functional difference in children with ASD. Moreover, these results might help us to better understand the mechanisms underlying the symptoms in children with ASD and might elucidate potential biomarkers for clinical applications.

Aberrant orbitofrontal connectivity in marijuana smoking adolescents

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Melissa Patricia Lopez-Larson

2015-12-01

Discussion: Findings indicate atypical OFC functional connectivity patterns in attentional/executive, motor and reward networks in adolescents with heavy MJ use. These anomalies may be related to suboptimal decision making capacities and increased impulsivity. Results also suggest different OFC connectivity patterns may be present in adolescents with early onset of MJ use and high lifetime exposure to MJ.

Functional connectivity pattern during rest within the episodic memory network in association with episodic memory performance in bipolar disorder.

Science.gov (United States)

Oertel-Knöchel, Viola; Reinke, Britta; Matura, Silke; Prvulovic, David; Linden, David E J; van de Ven, Vincent

2015-02-28

In this study, we sought to examine the intrinsic functional organization of the episodic memory network during rest in bipolar disorder (BD). The previous work suggests that deficits in intrinsic functional connectivity may account for impaired memory performance. We hypothesized that regions involved in episodic memory processing would reveal aberrant functional connectivity in patients with bipolar disorder. We examined 21 patients with BD and 21 healthy matched controls who underwent functional magnetic resonance imaging (fMRI) during a resting condition. We did a seed-based functional connectivity analysis (SBA), using the regions of the episodic memory network that showed a significantly different activation pattern during task-related fMRI as seeds. The functional connectivity scores (FC) were further correlated with episodic memory task performance. Our results revealed decreased FC scores within frontal areas and between frontal and temporal/hippocampal/limbic regions in BD patients in comparison with controls. We observed higher FC in BD patients compared with controls between frontal and limbic regions. The decrease in fronto-frontal functional connectivity in BD patients showed a significant positive association with episodic memory performance. The association between task-independent dysfunctional frontal-limbic FC and episodic memory performance may be relevant for current pathophysiological models of the disease. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Contrasting patterns of connectivity among endemic and widespread fire coral species ( Millepora spp.) in the tropical Southwestern Atlantic

Science.gov (United States)

de Souza, Júlia N.; Nunes, Flávia L. D.; Zilberberg, Carla; Sanchez, Juan A.; Migotto, Alvaro E.; Hoeksema, Bert W.; Serrano, Xaymara M.; Baker, Andrew C.; Lindner, Alberto

2017-09-01

Fire corals are the only branching corals in the South Atlantic and provide an important ecological role as habitat-builders in the region. With three endemic species ( Millepora brazilensis, M. nitida and M. laboreli) and one amphi-Atlantic species ( M. alcicornis), fire coral diversity in the Brazilian Province rivals that of the Caribbean Province. Phylogenetic relationships and patterns of population genetic structure and diversity were investigated in all four fire coral species occurring in the Brazilian Province to understand patterns of speciation and biogeography in the genus. A total of 273 colonies from the four species were collected from 17 locations spanning their geographic ranges. Sequences from the 16S ribosomal DNA (rDNA) were used to evaluate phylogenetic relationships. Patterns in genetic diversity and connectivity were inferred by measures of molecular diversity, analyses of molecular variance, pairwise differentiation, and by spatial analyses of molecular variance. Morphometrics of the endemic species M. braziliensis and M. nitida were evaluated by discriminant function analysis; macro-morphological characters were not sufficient to distinguish the two species. Genetic analyses showed that, although they are closely related, each species forms a well-supported clade. Furthermore, the endemic species characterized a distinct biogeographic barrier: M. braziliensis is restricted to the north of the São Francisco River, whereas M. nitida occurs only to the south. Millepora laboreli is restricted to a single location and has low genetic diversity. In contrast, the amphi-Atlantic species M. alcicornis shows high genetic connectivity within the Brazilian Province, and within the Caribbean Province (including Bermuda), despite low levels of gene flow between these populations and across the tropical Atlantic. These patterns reflect the importance of the Amazon-Orinoco Plume and the Mid-Atlantic Barrier as biogeographic barriers, and suggest that

Analyzing animal movement patterns using potential functions

Science.gov (United States)

H. K. Preisler; A. A. Ager; M. J. Wisdom

2013-01-01

The advent of GPS technology has made it possible to study human-wildlife interactions on large landscapes and quantify behavioral responses to recreation and other anthropogenic disturbances at increasingly fine scales. Of particular interest are the potential impacts on habitat use patterns, energetics, and cascading impacts on fecundity and other life history traits...

Dynamic effective connectivity of inter-areal brain circuits.

Directory of Open Access Journals (Sweden)

Demian Battaglia

Full Text Available Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity, related to the elusive question "Which areas cause the present activity of which others?". Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early

Performance of Series Connected GaAs Photovoltaic Converters under Multimode Optical Fiber Illumination

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Tiqiang Shan

2014-01-01

Full Text Available In many military and industrial applications, GaAs photovoltaic (PV converters are connected in series in order to generate the required voltage compatible with most common electronics. Multimode optical fibers are usually used to carry high-intensity laser and illuminate the series connected GaAs PV converters in real time. However, multimode optical fiber illumination has a speckled intensity pattern. The series connected PV array is extremely sensitive to nonuniform illumination; its performance is limited severely by the converter that is illuminated the least. This paper quantifies the effects of multimode optical fiber illumination on the performance of series connected GaAs PV converters, analyzes the loss mechanisms due to speckles, and discusses the maximum illumination efficiency. In order to describe the illumination dependent behavior detailedly, modeling of the series connected PV array is accomplished based on the equivalent circuit for PV cells. Finally, a series of experiments are carried out to demonstrate the theory analysis.

An information theory framework for dynamic functional domain connectivity.

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Vergara, Victor M; Miller, Robyn; Calhoun, Vince

2017-06-01

Dynamic functional network connectivity (dFNC) analyzes time evolution of coherent activity in the brain. In this technique dynamic changes are considered for the whole brain. This paper proposes an information theory framework to measure information flowing among subsets of functional networks call functional domains. Our method aims at estimating bits of information contained and shared among domains. The succession of dynamic functional states is estimated at the domain level. Information quantity is based on the probabilities of observing each dynamic state. Mutual information measurement is then obtained from probabilities across domains. Thus, we named this value the cross domain mutual information (CDMI). Strong CDMIs were observed in relation to the subcortical domain. Domains related to sensorial input, motor control and cerebellum form another CDMI cluster. Information flow among other domains was seldom found. Other methods of dynamic connectivity focus on whole brain dFNC matrices. In the current framework, information theory is applied to states estimated from pairs of multi-network functional domains. In this context, we apply information theory to measure information flow across functional domains. Identified CDMI clusters point to known information pathways in the basal ganglia and also among areas of sensorial input, patterns found in static functional connectivity. In contrast, CDMI across brain areas of higher level cognitive processing follow a different pattern that indicates scarce information sharing. These findings show that employing information theory to formally measured information flow through brain domains reveals additional features of functional connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

An extended OpenSim knee model for analysis of strains of connective tissues.

Science.gov (United States)

Marieswaran, M; Sikidar, Arnab; Goel, Anu; Joshi, Deepak; Kalyanasundaram, Dinesh

2018-04-17

OpenSim musculoskeletal models provide an accurate simulation environment that eases limitations of in vivo and in vitro studies. In this work, a biomechanical knee model was formulated with femoral articular cartilages and menisci along with 25 connective tissue bundles representing ligaments and capsules. The strain patterns of the connective tissues in the presence of femoral articular cartilage and menisci in the OpenSim knee model was probed in a first of its kind study. The effect of knee flexion (0°-120°), knee rotation (- 40° to 30°) and knee adduction (- 15° to 15°) on the anterior cruciate, posterior cruciate, medial collateral, lateral collateral ligaments and other connective tissues were studied by passive simulation. Further, a new parameter for assessment of strain namely, the differential inter-bundle strain of the connective tissues were analyzed to provide new insights for injury kinematics. ACL, PCL, LCL and PL was observed to follow a parabolic strain pattern during flexion while MCL represented linear strain patterns. All connective tissues showed non-symmetric parabolic strain variation during rotation. During adduction, the strain variation was linear for the knee bundles except for FL, PFL and TL. Strains higher than 0.1 were observed in most of the bundles during lateral rotation followed by abduction, medial rotation and adduction. In the case of flexion, highest strains were observed in aACL and aPCL. A combination of strains at a flexion of 0° with medial rotation of 30° or a flexion of 80° with rotation of 30° are evaluated as rupture-prone kinematics.

On Identifying Useful Patterns to Analyze Products in Retail Transaction Databases

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Yun, Unil

Mining correlated patterns in large transaction databases is one of the essential tasks in data mining since a huge number of patterns are usually mined, but it is hard to find patterns with the correlation. The needed data analysis should be made according to the requirements of the particular real application. In previous mining approaches, patterns with the weak affinity are found even with a high minimum support. In this paper, we suggest weighted support affinity pattern mining in which a new measure, weighted support confidence (ws-confidence) is developed to identify correlated patterns with the weighted support affinity. To efficiently prune the weak affinity patterns, we prove that the ws-confidence measure satisfies the anti-monotone and cross weighted support properties which can be applied to eliminate patterns with dissimilar weighted support levels. Based on the two properties, we develop a weighted support affinity pattern mining algorithm (WSP). The weighted support affinity patterns can be useful to answer the comparative analysis queries such as finding itemsets containing items which give similar total selling expense levels with an acceptable error range α% and detecting item lists with similar levels of total profits. In addition, our performance study shows that WSP is efficient and scalable for mining weighted support affinity patterns.

Abnormal synchrony and effective connectivity in patients with schizophrenia and auditory hallucinations

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de la Iglesia-Vaya, Maria; Escartí, Maria José; Molina-Mateo, Jose; Martí-Bonmatí, Luis; Gadea, Marien; Castellanos, Francisco Xavier; Aguilar García-Iturrospe, Eduardo J.; Robles, Montserrat; Biswal, Bharat B.; Sanjuan, Julio

2014-01-01

Auditory hallucinations (AH) are the most frequent positive symptoms in patients with schizophrenia. Hallucinations have been related to emotional processing disturbances, altered functional connectivity and effective connectivity deficits. Previously, we observed that, compared to healthy controls, the limbic network responses of patients with auditory hallucinations differed when the subjects were listening to emotionally charged words. We aimed to compare the synchrony patterns and effective connectivity of task-related networks between schizophrenia patients with and without AH and healthy controls. Schizophrenia patients with AH (n = 27) and without AH (n = 14) were compared with healthy participants (n = 31). We examined functional connectivity by analyzing correlations and cross-correlations among previously detected independent component analysis time courses. Granger causality was used to infer the information flow direction in the brain regions. The results demonstrate that the patterns of cortico-cortical functional synchrony differentiated the patients with AH from the patients without AH and from the healthy participants. Additionally, Granger-causal relationships between the networks clearly differentiated the groups. In the patients with AH, the principal causal source was an occipital–cerebellar component, versus a temporal component in the patients without AH and the healthy controls. These data indicate that an anomalous process of neural connectivity exists when patients with AH process emotional auditory stimuli. Additionally, a central role is suggested for the cerebellum in processing emotional stimuli in patients with persistent AH. PMID:25379429

Application of frequent itemsets mining to analyze patterns of one-stop visits in Taiwan.

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Chun-Yi Tu

Full Text Available BACKGROUND: The free choice of health care facilities without limitations on frequency of visits within the National Health Insurance in Taiwan gives rise to not only a high number of annual ambulatory visits per capita but also a unique "one-stop shopping"phenomenon, which refers to a patient' visits to several specialties of the same healthcare facility in one day. The visits to multiple physicians would increase the potential risk of polypharmacy. The aim of this study was to analyze the frequency and patterns of one-stop visits in Taiwan. METHODOLOGY/PRINCIPAL FINDINGS: The claims datasets of 1 million nationally representative people within Taiwan's National Health Insurance in 2005 were used to calculate the number of patients with one-stop visits. The frequent itemsets mining was applied to compute the combination patterns of specialties in the one-stop visits. Among the total 13,682,469 ambulatory care visits in 2005, one-stop visits occurred 144,132 times and involved 296,822 visits (2.2% of all visits by 66,294 (6.6% persons. People tended to have this behavior with age and the percentage reached 27.5% (5,662 in 20,579 in the age group ≥80 years. In general, women were more likely to have one-stop visits than men (7.2% vs. 6.0%. Internal medicine plus ophthalmology was the most frequent combination with a visited frequency of 3,552 times (2.5%, followed by cardiology plus neurology with 3,183 times (2.2%. The most frequent three-specialty combination, cardiology plus neurology and gastroenterology, occurred only 111 times. CONCLUSIONS/SIGNIFICANCE: Without the novel computational technique, it would be hardly possible to analyze the extremely diverse combination patterns of specialties in one-stop visits. The results of the study could provide useful information either for the hospital manager to set up integrated services or for the policymaker to rebuild the health care system.

Reconsidering connectivity in the sub-Antarctic.

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Moon, Katherine L; Chown, Steven L; Fraser, Ceridwen I

2017-11-01

Extreme and remote environments provide useful settings to test ideas about the ecological and evolutionary drivers of biological diversity. In the sub-Antarctic, isolation by geographic, geological and glaciological processes has long been thought to underpin patterns in the region's terrestrial and marine diversity. Molecular studies using increasingly high-resolution data are, however, challenging this perspective, demonstrating that many taxa disperse among distant sub-Antarctic landmasses. Here, we reconsider connectivity in the sub-Antarctic region, identifying which taxa are relatively isolated, which are well connected, and the scales across which this connectivity occurs in both terrestrial and marine systems. Although many organisms show evidence of occasional long-distance, trans-oceanic dispersal, these events are often insufficient to maintain gene flow across the region. Species that do show evidence of connectivity across large distances include both active dispersers and more sedentary species. Overall, connectivity patterns in the sub-Antarctic at intra- and inter-island scales are highly complex, influenced by life-history traits and local dynamics such as relative dispersal capacity and propagule pressure, natal philopatry, feeding associations, the extent of human exploitation, past climate cycles, contemporary climate, and physical barriers to movement. An increasing use of molecular data - particularly genomic data sets that can reveal fine-scale patterns - and more effective international collaboration and communication that facilitates integration of data from across the sub-Antarctic, are providing fresh insights into the processes driving patterns of diversity in the region. These insights offer a platform for assessing the ways in which changing dispersal mechanisms, such as through increasing human activity and changes to wind and ocean circulation, may alter sub-Antarctic biodiversity patterns in the future. © 2017 Cambridge

Optimization of the kernel functions in a probabilistic neural network analyzing the local pattern distribution.

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Galleske, I; Castellanos, J

2002-05-01

This article proposes a procedure for the automatic determination of the elements of the covariance matrix of the gaussian kernel function of probabilistic neural networks. Two matrices, a rotation matrix and a matrix of variances, can be calculated by analyzing the local environment of each training pattern. The combination of them will form the covariance matrix of each training pattern. This automation has two advantages: First, it will free the neural network designer from indicating the complete covariance matrix, and second, it will result in a network with better generalization ability than the original model. A variation of the famous two-spiral problem and real-world examples from the UCI Machine Learning Repository will show a classification rate not only better than the original probabilistic neural network but also that this model can outperform other well-known classification techniques.

Differences in interregional brain connectivity in children with unilateral hearing loss.

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Jung, Matthew E; Colletta, Miranda; Coalson, Rebecca; Schlaggar, Bradley L; Lieu, Judith E C

2017-11-01

To identify functional network architecture differences in the brains of children with unilateral hearing loss (UHL) using resting-state functional-connectivity magnetic resonance imaging (rs-fcMRI). Prospective observational study. Children (7 to 17 years of age) with severe to profound hearing loss in one ear, along with their normal hearing (NH) siblings, were recruited and imaged using rs-fcMRI. Eleven children had right UHL; nine had left UHL; and 13 had normal hearing. Forty-one brain regions of interest culled from established brain networks such as the default mode (DMN); cingulo-opercular (CON); and frontoparietal networks (FPN); as well as regions for language, phonological, and visual processing, were analyzed using regionwise correlations and conjunction analysis to determine differences in functional connectivity between the UHL and normal hearing children. When compared to the NH group, children with UHL showed increased connectivity patterns between multiple networks, such as between the CON and visual processing centers. However, there were decreased, as well as aberrant connectivity patterns with the coactivation of the DMN and FPN, a relationship that usually is negatively correlated. Children with UHL demonstrate multiple functional connectivity differences between brain networks involved with executive function, cognition, and language comprehension that may represent adaptive as well as maladaptive changes. These findings suggest that possible interventions or habilitation, beyond amplification, might be able to affect some children's requirement for additional help at school. 3b. Laryngoscope, 127:2636-2645, 2017. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

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Liu, Jin; Liao, Xuhong; Xia, Mingrui; He, Yong

2018-02-01

The human brain is a large, interacting dynamic network, and its architecture of coupling among brain regions varies across time (termed the "chronnectome"). However, very little is known about whether and how the dynamic properties of the chronnectome can characterize individual uniqueness, such as identifying individuals as a "fingerprint" of the brain. Here, we employed multiband resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 105) and a sliding time-window dynamic network analysis approach to systematically examine individual time-varying properties of the chronnectome. We revealed stable and remarkable individual variability in three dynamic characteristics of brain connectivity (i.e., strength, stability, and variability), which was mainly distributed in three higher order cognitive systems (i.e., default mode, dorsal attention, and fronto-parietal) and in two primary systems (i.e., visual and sensorimotor). Intriguingly, the spatial patterns of these dynamic characteristics of brain connectivity could successfully identify individuals with high accuracy and could further significantly predict individual higher cognitive performance (e.g., fluid intelligence and executive function), which was primarily contributed by the higher order cognitive systems. Together, our findings highlight that the chronnectome captures inherent functional dynamics of individual brain networks and provides implications for individualized characterization of health and disease. © 2017 Wiley Periodicals, Inc.

Connectivity Measures in EEG Microstructural Sleep Elements.

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Sakellariou, Dimitris; Koupparis, Andreas M; Kokkinos, Vasileios; Koutroumanidis, Michalis; Kostopoulos, George K

2016-01-01

During Non-Rapid Eye Movement sleep (NREM) the brain is relatively disconnected from the environment, while connectedness between brain areas is also decreased. Evidence indicates, that these dynamic connectivity changes are delivered by microstructural elements of sleep: short periods of environmental stimuli evaluation followed by sleep promoting procedures. The connectivity patterns of the latter, among other aspects of sleep microstructure, are still to be fully elucidated. We suggest here a methodology for the assessment and investigation of the connectivity patterns of EEG microstructural elements, such as sleep spindles. The methodology combines techniques in the preprocessing, estimation, error assessing and visualization of results levels in order to allow the detailed examination of the connectivity aspects (levels and directionality of information flow) over frequency and time with notable resolution, while dealing with the volume conduction and EEG reference assessment. The high temporal and frequency resolution of the methodology will allow the association between the microelements and the dynamically forming networks that characterize them, and consequently possibly reveal aspects of the EEG microstructure. The proposed methodology is initially tested on artificially generated signals for proof of concept and subsequently applied to real EEG recordings via a custom built MATLAB-based tool developed for such studies. Preliminary results from 843 fast sleep spindles recorded in whole night sleep of 5 healthy volunteers indicate a prevailing pattern of interactions between centroparietal and frontal regions. We demonstrate hereby, an opening to our knowledge attempt to estimate the scalp EEG connectivity that characterizes fast sleep spindles via an "EEG-element connectivity" methodology we propose. The application of the latter, via a computational tool we developed suggests it is able to investigate the connectivity patterns related to the occurrence

Analyzing and Predicting Micro-Location Patterns of Software Firms

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Jan Kinne

2017-12-01

Full Text Available While the effects of non-geographic aggregation on statistical inference are well studied in economics, research on the effects of geographic aggregation on regression analysis is rather scarce. This knowledge gap, together with the use of aggregated spatial units in previous firm location studies, results in a lack of understanding of firm location determinants at the microgeographic level. Suitable data for microgeographic location analysis has become available only recently through the emergence of Volunteered Geographic Information (VGI, especially the OpenStreetMap (OSM project, and the increasing availability of official (open geodata. In this paper, we use a comprehensive dataset of three million street-level geocoded firm observations to explore the location pattern of software firms in an Exploratory Spatial Data Analysis (ESDA. Based on the ESDA results, we develop a software firm location prediction model using Poisson regression and OSM data. Our findings offer novel insights into the mode of operation of the Modifiable Areal Unit Problem (MAUP in the context of a microgeographic location analysis: We find that non-aggregated data can be used to detect information on location determinants, which are superimposed when aggregated spatial units are analyzed, and that some findings of previous firm location studies are not robust at the microgeographic level. However, we also conclude that the lack of high-resolution geodata on socio-economic population characteristics causes systematic prediction errors, especially in cities with diverse and segregated populations.

Measurements of brain microstructure and connectivity with diffusion MRI

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Ching-Po Lin

2011-12-01

Full Text Available By probing direction-dependent diffusivity of water molecules, diffusion MRI has shown its capability to reflect the microstructural tissue status and to estimate the neural orientation and pathways in the living brain. This approach has supplied novel insights into in-vivo human brain connections. By detecting the connection patterns, anatomical architecture and structural integrity between cortical regions or subcortical nuclei in the living human brain can be easily identified. It thus opens a new window on brain connectivity studies and disease processes. During the past years, there is a growing interest in exploring the connectivity patterns of the human brain. Specifically, the utilities of noninvasive neuroimaging data and graph theoretical analysis have provided important insights into the anatomical connections and topological pattern of human brain structural networks in vivo. Here, we review the progress of this important technique and the recent methodological and application studies utilizing graph theoretical approaches on brain structural networks with structural MRI and diffusion MRI.

What happens in an estuary doesn't stay there: patterns of biotic connectivity resulting from long term ecological research

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Mather, Martha E.; Finn, John T.; Kennedy, Christina G.; Deegan, Linda A.; Smith, Joseph M.

2013-01-01

The paucity of data on migratory connections and an incomplete understanding of how mobile organisms use geographically separate areas have been obstacles to understanding coastal dynamics. Research on acoustically tagged striped bass (Morone saxatilis) at the Plum Island Ecosystems (PIE) Long Term Ecological Research site, Massachusetts, documents intriguing patterns of biotic connectivity (i.e., long-distance migration between geographically distinct areas). First, the striped bass tagged at PIE migrated southward along the coast using different routes. Second, these tagged fish exhibited strong fidelity and specificity to PIE. For example, across multiple years, tagged striped bass resided in PIE waters for an average of 1.5-2.5 months per year (means: 51-72 days; range 2-122 days), left this estuary in fall, then returned in subsequent years. Third, this specificity and fidelity connected PIE to other locations. The fish exported nutrients and energy to at least three other coastal locations through biomass added as growth. These results demonstrate that what happens in an individual estuary can affect other estuaries. Striped bass that use tightly connected routes to feed in specific estuaries should have greater across-system impacts than fish that are equally likely to go anywhere. Consequently, variations in when, where, and how fish migrate can alter across-estuary impacts.

Group-ICA model order highlights patterns of functional brain connectivity

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Ahmed eAbou Elseoud

2011-06-01

Full Text Available Resting-state networks (RSNs can be reliably and reproducibly detected using independent component analysis (ICA at both individual subject and group levels. Altering ICA dimensionality (model order estimation can have a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Recent evidence from several neuroimaging studies suggests that the human brain has a modular hierarchical organization which resembles the hierarchy depicted by different ICA model orders. We hypothesized that functional connectivity between-group differences measured with ICA might be affected by model order selection. We investigated differences in functional connectivity using so-called dual-regression as a function of ICA model order in a group of unmedicated seasonal affective disorder (SAD patients compared to normal healthy controls. The results showed that the detected disease-related differences in functional connectivity alter as a function of ICA model order. The volume of between-group differences altered significantly as a function of ICA model order reaching maximum at model order 70 (which seems to be an optimal point that conveys the largest between-group difference then stabilized afterwards. Our results show that fine-grained RSNs enable better detection of detailed disease-related functional connectivity changes. However, high model orders show an increased risk of false positives that needs to be overcome. Our findings suggest that multilevel ICA exploration of functional connectivity enables optimization of sensitivity to brain disorders.

Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

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

2016-01-01

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

On the relevance of sophisticated structural annotations for disulfide connectivity pattern prediction.

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Julien Becker

Full Text Available Disulfide bridges strongly constrain the native structure of many proteins and predicting their formation is therefore a key sub-problem of protein structure and function inference. Most recently proposed approaches for this prediction problem adopt the following pipeline: first they enrich the primary sequence with structural annotations, second they apply a binary classifier to each candidate pair of cysteines to predict disulfide bonding probabilities and finally, they use a maximum weight graph matching algorithm to derive the predicted disulfide connectivity pattern of a protein. In this paper, we adopt this three step pipeline and propose an extensive study of the relevance of various structural annotations and feature encodings. In particular, we consider five kinds of structural annotations, among which three are novel in the context of disulfide bridge prediction. So as to be usable by machine learning algorithms, these annotations must be encoded into features. For this purpose, we propose four different feature encodings based on local windows and on different kinds of histograms. The combination of structural annotations with these possible encodings leads to a large number of possible feature functions. In order to identify a minimal subset of relevant feature functions among those, we propose an efficient and interpretable feature function selection scheme, designed so as to avoid any form of overfitting. We apply this scheme on top of three supervised learning algorithms: k-nearest neighbors, support vector machines and extremely randomized trees. Our results indicate that the use of only the PSSM (position-specific scoring matrix together with the CSP (cysteine separation profile are sufficient to construct a high performance disulfide pattern predictor and that extremely randomized trees reach a disulfide pattern prediction accuracy of [Formula: see text] on the benchmark dataset SPX[Formula: see text], which corresponds to

Characterizing synchrony patterns across cognitive task stages of associative recognition memory.

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Portoles, Oscar; Borst, Jelmer P; van Vugt, Marieke K

2017-12-28

Numerous studies seek to understand the role of oscillatory synchronization in cognition. This problem is particularly challenging in the context of complex cognitive behavior, which consists of a sequence of processing steps with uncertain duration. In this study, we analyzed oscillatory connectivity measures in time windows that previous computational models had associated with a specific sequence of processing steps in an associative memory recognition task (visual encoding, familiarity, memory retrieval, decision making, and motor response). The timing of these processing steps was estimated on a single-trial basis with a novel hidden semi-Markov model multivariate pattern analysis (HSMM-MVPA) method. We show that different processing stages are associated with specific patterns of oscillatory connectivity. Visual encoding is characterized by a dense network connecting frontal, posterior, and temporal areas as well as frontal and occipital phase locking in the 4-9 Hz theta band. Familiarity is associated with frontal phase locking in the 9-14 Hz alpha band. Decision making is associated with frontal and temporo-central interhemispheric connections in the alpha band. During decision making, a second network in the theta band that connects left-temporal, central, and occipital areas bears similarity to the neural signature for preparing a motor response. A similar theta band network is also present during the motor response, with additionally alpha band connectivity between right-temporal and posterior areas. This demonstrates that the processing stages discovered with the HSMM-MVPA method are indeed linked to distinct synchronization patterns, leading to a closer understanding of the functional role of oscillations in cognition. © 2017 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Intranasal oxytocin modulates neural functional connectivity during human social interaction.

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Rilling, James K; Chen, Xiangchuan; Chen, Xu; Haroon, Ebrahim

2018-02-10

Oxytocin (OT) modulates social behavior in primates and many other vertebrate species. Studies in non-primate animals have demonstrated that, in addition to influencing activity within individual brain areas, OT influences functional connectivity across networks of areas involved in social behavior. Previously, we used fMRI to image brain function in human subjects during a dyadic social interaction task following administration of either intranasal oxytocin (INOT) or placebo, and analyzed the data with a standard general linear model. Here, we conduct an extensive re-analysis of these data to explore how OT modulates functional connectivity across a neural network that animal studies implicate in social behavior. OT induced widespread increases in functional connectivity in response to positive social interactions among men and widespread decreases in functional connectivity in response to negative social interactions among women. Nucleus basalis of Meynert, an important regulator of selective attention and motivation with a particularly high density of OT receptors, had the largest number of OT-modulated connections. Regions known to receive mesolimbic dopamine projections such as the nucleus accumbens and lateral septum were also hubs for OT effects on functional connectivity. Our results suggest that the neural mechanism by which OT influences primate social cognition may include changes in patterns of activity across neural networks that regulate social behavior in other animals. © 2018 Wiley Periodicals, Inc.

Multivariate pattern dependence.

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Stefano Anzellotti

2017-11-01

Full Text Available When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analysis. In the present article, we introduce and apply multivariate pattern dependence (MVPD: a technique to study the statistical dependence between brain regions in humans in terms of the multivariate relations between their patterns of responses. MVPD characterizes the responses in each brain region as trajectories in region-specific multidimensional spaces, and models the multivariate relationship between these trajectories. We applied MVPD to the posterior superior temporal sulcus (pSTS and to the fusiform face area (FFA, using a searchlight approach to reveal interactions between these seed regions and the rest of the brain. Across two different experiments, MVPD identified significant statistical dependence not detected by standard functional connectivity. Additionally, MVPD outperformed univariate connectivity in its ability to explain independent variance in the responses of individual voxels. In the end, MVPD uncovered different connectivity profiles associated with different representational subspaces of FFA: the first principal component of FFA shows differential connectivity with occipital and parietal regions implicated in the processing of low-level properties of faces, while the second and third components show differential connectivity with anterior temporal regions implicated in the processing of invariant representations of face identity.

Aberrant patterns of local and long-range functional connectivity densities in schizophrenia.

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Liu, Chuanxin; Zhang, Wei; Chen, Guangdong; Tian, Hongjun; Li, Jie; Qu, Hongru; Cheng, Langlang; Zhu, Jingjing; Zhuo, Chuanjun

2017-07-18

Schizophrenia is a disorder of brain dysconnectivity, and both the connection strength and connection number are disrupted in patients with schizophrenia. The functional connectivity density (FCD) can reflect alterations in the connection number. Alterations in the global FCD (gFCD) in schizophrenia were previously demonstrated; however, alterations in two other indices of the pathological characteristics of the brain, local FCD (lFCD) and long-range FCD (lrFCD), have not been revealed. To investigate lFCD and lrFCD alterations in patients with schizophrenia, 95 patients and 93 matched healthy controls were examined using structural and resting-state functional magnetic resonance imaging scanning. lFCD and lrFCD were measured using FCD mapping, and differences were identified using a two-sample t-test in a voxel-wise manner, with age and gender considered to increase variability. Multiple comparisons were performed using a false discovery rate method with a corrected threshold of Pschizophrenia is a disorder of brain dysconnectivity, particularly affecting the local functional connectivity network, and support the hypothesis that schizophrenia is associated with a widespread cortical functional connectivity/activity deficit, with hyper- and/or hypo-connectivity/activity coexisting in some cortical or subcortical regions.

Measures for brain connectivity analysis: nodes centrality and their invariant patterns

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da Silva, Laysa Mayra Uchôa; Baltazar, Carlos Arruda; Silva, Camila Aquemi; Ribeiro, Mauricio Watanabe; de Aratanha, Maria Adelia Albano; Deolindo, Camila Sardeto; Rodrigues, Abner Cardoso; Machado, Birajara Soares

2017-07-01

The high dynamical complexity of the brain is related to its small-world topology, which enable both segregated and integrated information processing capabilities. Several measures of connectivity estimation have already been employed to characterize functional brain networks from multivariate electrophysiological data. However, understanding the properties of each measure that lead to a better description of the real topology and capture the complex phenomena present in the brain remains challenging. In this work we compared four nonlinear connectivity measures and show that each method characterizes distinct features of brain interactions. The results suggest an invariance of global network parameters from different behavioral states and that more complete description may be reached considering local features, independently of the connectivity measure employed. Our findings also point to future perspectives in connectivity studies that combine distinct and complementary dependence measures in assembling higher dimensions manifolds.

Synthesis of compact patterns for NMR relaxation decay in intelligent "electronic tongue" for analyzing heavy oil composition

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Lapshenkov, E. M.; Volkov, V. Y.; Kulagin, V. P.

2018-05-01

The article is devoted to the problem of pattern creation of the NMR sensor signal for subsequent recognition by the artificial neural network in the intelligent device "the electronic tongue". The specific problem of removing redundant data from the spin-spin relaxation signal pattern that is used as a source of information in analyzing the composition of oil and petroleum products is considered. The method is proposed that makes it possible to remove redundant data of the relaxation decay pattern but without introducing additional distortion. This method is based on combining some relaxation decay curve intervals that increment below the noise level such that the increment of the combined intervals is above the noise level. In this case, the relaxation decay curve samples that are located inside the combined intervals are removed from the pattern. This method was tested on the heavy-oil NMR signal patterns that were created by using the Carr-Purcell-Meibum-Gill (CPMG) sequence for recording the relaxation process. Parameters of CPMG sequence are: 100 μs - time interval between 180° pulses, 0.4s - duration of measurement. As a result, it was revealed that the proposed method allowed one to reduce the number of samples 15 times (from 4000 to 270), and the maximum detected root mean square error (RMS error) equals 0.00239 (equivalent to signal-to-noise ratio 418).

Empirical validation of directed functional connectivity.

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Mill, Ravi D; Bagic, Anto; Bostan, Andreea; Schneider, Walter; Cole, Michael W

2017-02-01

Mapping directions of influence in the human brain connectome represents the next phase in understanding its functional architecture. However, a host of methodological uncertainties have impeded the application of directed connectivity methods, which have primarily been validated via "ground truth" connectivity patterns embedded in simulated functional MRI (fMRI) and magneto-/electro-encephalography (MEG/EEG) datasets. Such simulations rely on many generative assumptions, and we hence utilized a different strategy involving empirical data in which a ground truth directed connectivity pattern could be anticipated with confidence. Specifically, we exploited the established "sensory reactivation" effect in episodic memory, in which retrieval of sensory information reactivates regions involved in perceiving that sensory modality. Subjects performed a paired associate task in separate fMRI and MEG sessions, in which a ground truth reversal in directed connectivity between auditory and visual sensory regions was instantiated across task conditions. This directed connectivity reversal was successfully recovered across different algorithms, including Granger causality and Bayes network (IMAGES) approaches, and across fMRI ("raw" and deconvolved) and source-modeled MEG. These results extend simulation studies of directed connectivity, and offer practical guidelines for the use of such methods in clarifying causal mechanisms of neural processing. Copyright © 2016 Elsevier Inc. All rights reserved.

Topography of Striate-Extrastriate Connections in Neonatally Enucleated Rats

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Robyn J. Laing

2013-01-01

Full Text Available It is known that retinal input is necessary for the normal development of striate cortex and its corticocortical connections, but there is little information on the role that retinal input plays in the development of retinotopically organized connections between V1 and surrounding visual areas. In nearly all lateral extrastriate areas, the anatomical and physiological representation of the nasotemporal axis of the visual field mirrors the representation of this axis in V1. To determine whether the mediolateral topography of striate-extrastriate projections is preserved in neonatally enucleated rats, we analyzed the patterns of projections resulting from tracer injections placed at different sites along the mediolateral axis of V1. We found that the correlation between the distance from injection sites to the lateral border of V1 and the distance of the labeling patterns in area 18a was strong in controls and much weaker in enucleates. Data from pairs of injections in the same animal revealed that the separation of area 18a projection fields for a given separation of injection sites was more variable in enucleated than in control rats. Our analysis of single and double tracer injections suggests that neonatal bilateral enucleation weakens, but not completely abolishes, the mediolateral topography in area 18a.

Wideband energy harvesting based on mixed connection of piezoelectric oscillators

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Wu, P. H.; Chen, Y. J.; Li, B. Y.; Shu, Y. C.

2017-09-01

An approach for wideband energy harvesting together with power enhancement is proposed by integrating multiple piezoelectric oscillators with mixed parallel-series connection. This gives rise to the feasibility of shifting the operation frequency band to the dominant frequency domain of ambient excitations. There are two types of connection patterns discussed here: the p-type (s-type) is the parallel (series) connection of all sets of oscillators where some of them may be connected in series (parallel). In addition, the standard interface circuit used for electric rectification is adopted here. The analytic estimates of output power are derived and explicitly expressed in terms of different matrix formulations for these two connection patterns. They are subsequently validated and are found in good agreement with numerical simulations and experimental observations. Finally, the experimental results from the mixed connection of 4 piezoelectric oscillators show that the peak power of each array is about 3.4 times higher than that generated by a single piezoelectric oscillator. In addition, the bandwidth of the array capable of switching connection patterns is around 2.8 times wider than that based on a single array configuration. Hence, the effective bandwidth is enlarged without the loss of peak power.

Brain-Wide Analysis of Functional Connectivity in First-Episode and Chronic Stages of Schizophrenia.

Science.gov (United States)

Li, Tao; Wang, Qiang; Zhang, Jie; Rolls, Edmund T; Yang, Wei; Palaniyappan, Lena; Zhang, Lu; Cheng, Wei; Yao, Ye; Liu, Zhaowen; Gong, Xiaohong; Luo, Qiang; Tang, Yanqing; Crow, Timothy J; Broome, Matthew R; Xu, Ke; Li, Chunbo; Wang, Jijun; Liu, Zhening; Lu, Guangming; Wang, Fei; Feng, Jianfeng

2017-03-01

Published reports of functional abnormalities in schizophrenia remain divergent due to lack of staging point-of-view and whole-brain analysis. To identify key functional-connectivity differences of first-episode (FE) and chronic patients from controls using resting-state functional MRI, and determine changes that are specifically associated with disease onset, a clinical staging model is adopted. We analyze functional-connectivity differences in prodromal, FE (mostly drug naïve), and chronic patients from their matched controls from 6 independent datasets involving a total of 789 participants (343 patients). Brain-wide functional-connectivity analysis was performed in different datasets and the results from the datasets of the same stage were then integrated by meta-analysis, with Bonferroni correction for multiple comparisons. Prodromal patients differed from controls in their pattern of functional-connectivity involving the inferior frontal gyri (Broca's area). In FE patients, 90% of the functional-connectivity changes involved the frontal lobes, mostly the inferior frontal gyrus including Broca's area, and these changes were correlated with delusions/blunted affect. For chronic patients, functional-connectivity differences extended to wider areas of the brain, including reduced thalamo-frontal connectivity, and increased thalamo-temporal and thalamo-sensorimoter connectivity that were correlated with the positive, negative, and general symptoms, respectively. Thalamic changes became prominent at the chronic stage. These results provide evidence for distinct patterns of functional-dysconnectivity across FE and chronic stages of schizophrenia. Importantly, abnormalities in the frontal language networks appear early, at the time of disease onset. The identification of stage-specific pathological processes may help to understand the disease course of schizophrenia and identify neurobiological markers crucial for early diagnosis. © The Author 2016. Published by

Organization of Anti-Phase Synchronization Pattern in Neural Networks: What are the Key Factors?

Science.gov (United States)

Li, Dong; Zhou, Changsong

2011-01-01

Anti-phase oscillation has been widely observed in cortical neural network. Elucidating the mechanism underlying the organization of anti-phase pattern is of significance for better understanding more complicated pattern formations in brain networks. In dynamical systems theory, the organization of anti-phase oscillation pattern has usually been considered to relate to time delay in coupling. This is consistent to conduction delays in real neural networks in the brain due to finite propagation velocity of action potentials. However, other structural factors in cortical neural network, such as modular organization (connection density) and the coupling types (excitatory or inhibitory), could also play an important role. In this work, we investigate the anti-phase oscillation pattern organized on a two-module network of either neuronal cell model or neural mass model, and analyze the impact of the conduction delay times, the connection densities, and coupling types. Our results show that delay times and coupling types can play key roles in this organization. The connection densities may have an influence on the stability if an anti-phase pattern exists due to the other factors. Furthermore, we show that anti-phase synchronization of slow oscillations can be achieved with small delay times if there is interaction between slow and fast oscillations. These results are significant for further understanding more realistic spatiotemporal dynamics of cortico-cortical communications. PMID:22232576

Looking for hotspots of marine metacommunity connectivity: a methodological framework

Science.gov (United States)

Melià, Paco; Schiavina, Marcello; Rossetto, Marisa; Gatto, Marino; Fraschetti, Simonetta; Casagrandi, Renato

2016-03-01

Seascape connectivity critically affects the spatiotemporal dynamics of marine metacommunities. Understanding how connectivity patterns emerge from physically and biologically-mediated interactions is therefore crucial to conserve marine ecosystem functions and biodiversity. Here, we develop a set of biophysical models to explore connectivity in assemblages of species belonging to a typical Mediterranean community (Posidonia oceanica meadows) and characterized by different dispersing traits. We propose a novel methodological framework to synthesize species-specific results into a set of community connectivity metrics and show that spatiotemporal variation in magnitude and direction of the connections, as well as interspecific differences in dispersing traits, are key factors structuring community connectivity. We eventually demonstrate how these metrics can be used to characterize the functional role of each marine area in determining patterns of community connectivity at the basin level and to support marine conservation planning.

Phase synchronization in train connection timetables

Energy Technology Data Exchange (ETDEWEB)

Fretter, Christoph; Mueller-Hannemann, Matthias [Martin Luther Universitaet, Halle-Wittenberg (Germany); Krumov, Lachezar; Weihe, Karsten [TU Darmstadt (Germany); Huett, Marc-Thorsten [Jacobs University, Bremen (Germany)

2010-07-01

Train connection timetables are an important research topic in algorithmics. Finding optimal or near-optimal timetables under the subsidiary conditions of minimizing travel times and other criteria is an important contribution to the functioning of public transportation. In addition to efficiency (given, e.g. by minimal average travel times), the robustness of the timetable, i.e. a minimization of delay propagation, is an important criterion. Here we study the balance of efficiency and robustness in train connection timetables from the perspective of synchronization, exploiting the fact that a major part of the trains run nearly periodically. We find that synchronization is highest at intermediate-sized stations. We argue that this synchronization perspectives opens a new avenue towards an understanding of train connection timetables by representing them as spatiotemporal phase patterns. Robustness and efficiency can then be viewed as properties of this phase pattern.

Changes of functional connectivity in the left frontoparietal network following aphasic stroke

Directory of Open Access Journals (Sweden)

Dan eZhu

2014-05-01

Full Text Available Language is an essential higher cognitive function supported by large-scale brain networks. In this study, we investigated functional connectivity changes in the left frontoparietal network (LFPN, a language-cognition related brain network in aphasic patients. We enrolled thirteen aphasic patients who had undergone a stroke in the left hemisphere and age-, gender-, educational level-matched controls and analyzed the data by integrating independent component analysis (ICA with a network connectivity analysis method. Resting state functional magnetic resonance imaging (fMRI and clinical evaluation of language function were assessed at two stages: one and two months after stroke onset. We found reduced functional connectivity between the LFPN and the right middle frontal cortex, medial frontal cortex and right inferior frontal cortex in aphasic patients as compared to controls. Correlation analysis showed that stronger functional connectivity between the LFPN and the right middle frontal cortex and medial frontal cortex coincided with more preserved language comprehension ability after stroke. Network connectivity analysis showed reduced LFPN connectivity as indicated by the mean network connectivity index of key regions in the LFPN of aphasic patients. The decreased LFPN connectivity in stroke patients was significantly associated with the impairment of language function in their comprehension ability. We also found significant association between recovery of comprehension ability and the mean changes in intrinsic LFPN connectivity. Our findings suggest that brain lesions may influence language comprehension by altering functional connectivity between regions and that the patterns of abnormal functional connectivity may contribute to the recovery of language deficits.

Food web complexity and stability across habitat connectivity gradients.

Science.gov (United States)

LeCraw, Robin M; Kratina, Pavel; Srivastava, Diane S

2014-12-01

The effects of habitat connectivity on food webs have been studied both empirically and theoretically, yet the question of whether empirical results support theoretical predictions for any food web metric other than species richness has received little attention. Our synthesis brings together theory and empirical evidence for how habitat connectivity affects both food web stability and complexity. Food web stability is often predicted to be greatest at intermediate levels of connectivity, representing a compromise between the stabilizing effects of dispersal via rescue effects and prey switching, and the destabilizing effects of dispersal via regional synchronization of population dynamics. Empirical studies of food web stability generally support both this pattern and underlying mechanisms. Food chain length has been predicted to have both increasing and unimodal relationships with connectivity as a result of predators being constrained by the patch occupancy of their prey. Although both patterns have been documented empirically, the underlying mechanisms may differ from those predicted by models. In terms of other measures of food web complexity, habitat connectivity has been empirically found to generally increase link density but either reduce or have no effect on connectance, whereas a unimodal relationship is expected. In general, there is growing concordance between empirical patterns and theoretical predictions for some effects of habitat connectivity on food webs, but many predictions remain to be tested over a full connectivity gradient, and empirical metrics of complexity are rarely modeled. Closing these gaps will allow a deeper understanding of how natural and anthropogenic changes in connectivity can affect real food webs.

Resting-state functional connectivity of orthographic networks in acquired dysgraphia

Directory of Open Access Journals (Sweden)

Gali Ellenblum

2015-05-01

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

Stimulus-Elicited Connectivity Influences Resting-State Connectivity Years Later in Human Development: A Prospective Study.

Science.gov (United States)

Gabard-Durnam, Laurel Joy; Gee, Dylan Grace; Goff, Bonnie; Flannery, Jessica; Telzer, Eva; Humphreys, Kathryn Leigh; Lumian, Daniel Stephen; Fareri, Dominic Stephen; Caldera, Christina; Tottenham, Nim

2016-04-27

Although the functional architecture of the brain is indexed by resting-state connectivity networks, little is currently known about the mechanisms through which these networks assemble into stable mature patterns. The current study posits and tests the long-term phasic molding hypothesis that resting-state networks are gradually shaped by recurring stimulus-elicited connectivity across development by examining how both stimulus-elicited and resting-state functional connections of the human brain emerge over development at the systems level. Using a sequential design following 4- to 18-year-olds over a 2 year period, we examined the predictive associations between stimulus-elicited and resting-state connectivity in amygdala-cortical circuitry as an exemplar case (given this network's protracted development across these ages). Age-related changes in amygdala functional connectivity converged on the same regions of medial prefrontal cortex (mPFC) and inferior frontal gyrus when elicited by emotional stimuli and when measured at rest. Consistent with the long-term phasic molding hypothesis, prospective analyses for both connections showed that the magnitude of an individual's stimulus-elicited connectivity unidirectionally predicted resting-state functional connectivity 2 years later. For the amygdala-mPFC connection, only stimulus-elicited connectivity during childhood and the transition to adolescence shaped future resting-state connectivity, consistent with a sensitive period ending with adolescence for the amygdala-mPFC circuit. Together, these findings suggest that resting-state functional architecture may arise from phasic patterns of functional connectivity elicited by environmental stimuli over the course of development on the order of years. A fundamental issue in understanding the ontogeny of brain function is how resting-state (intrinsic) functional networks emerge and relate to stimulus-elicited functional connectivity. Here, we posit and test the long

Mapping functional connectivity

Science.gov (United States)

Peter Vogt; Joseph R. Ferrari; Todd R. Lookingbill; Robert H. Gardner; Kurt H. Riitters; Katarzyna Ostapowicz

2009-01-01

An objective and reliable assessment of wildlife movement is important in theoretical and applied ecology. The identification and mapping of landscape elements that may enhance functional connectivity is usually a subjective process based on visual interpretations of species movement patterns. New methods based on mathematical morphology provide a generic, flexible,...

Single-trial effective brain connectivity patterns enhance discriminability of mental imagery tasks

Science.gov (United States)

Rathee, Dheeraj; Cecotti, Hubert; Prasad, Girijesh

2017-10-01

Objective. The majority of the current approaches of connectivity based brain-computer interface (BCI) systems focus on distinguishing between different motor imagery (MI) tasks. Brain regions associated with MI are anatomically close to each other, hence these BCI systems suffer from low performances. Our objective is to introduce single-trial connectivity feature based BCI system for cognition imagery (CI) based tasks wherein the associated brain regions are located relatively far away as compared to those for MI. Approach. We implemented time-domain partial Granger causality (PGC) for the estimation of the connectivity features in a BCI setting. The proposed hypothesis has been verified with two publically available datasets involving MI and CI tasks. Main results. The results support the conclusion that connectivity based features can provide a better performance than a classical signal processing framework based on bandpass features coupled with spatial filtering for CI tasks, including word generation, subtraction, and spatial navigation. These results show for the first time that connectivity features can provide a reliable performance for imagery-based BCI system. Significance. We show that single-trial connectivity features for mixed imagery tasks (i.e. combination of CI and MI) can outperform the features obtained by current state-of-the-art method and hence can be successfully applied for BCI applications.

Modelling water and sediment connectivity patterns in a semi-arid landscape

International Nuclear Information System (INIS)

Cammeraat, L. H.; Beek, L. P. H. van; Dooms, T.

2009-01-01

Desertification is a major threat in SE Spain and mitigation strategies are required to reduce the adverse effect of water-induced erosion on soil production potential. Severity of soil erosion depends on local runoff response and the connectivity of pathways of water and sediment at different spatial scales. We investigated the connectivity between sources and sinks on semi-natural slopes by means of a semi-distributed model that delineated Hydrological response Units (HRUs) on the basis of physiographic characteristics. The model was calibrated with information at the plot, hill slope and sub-catchment scale covering the period 1995-2008 and validated against larger events that connected the semi-natural sub-catchment with the underlying cultivated slopes. (Author) 12 refs.

Modelling water and sediment connectivity patterns in a semi-arid landscape

Energy Technology Data Exchange (ETDEWEB)

Cammeraat, L. H.; Beek, L. P. H. van; Dooms, T.

2009-07-01

Desertification is a major threat in SE Spain and mitigation strategies are required to reduce the adverse effect of water-induced erosion on soil production potential. Severity of soil erosion depends on local runoff response and the connectivity of pathways of water and sediment at different spatial scales. We investigated the connectivity between sources and sinks on semi-natural slopes by means of a semi-distributed model that delineated Hydrological response Units (HRUs) on the basis of physiographic characteristics. The model was calibrated with information at the plot, hill slope and sub-catchment scale covering the period 1995-2008 and validated against larger events that connected the semi-natural sub-catchment with the underlying cultivated slopes. (Author) 12 refs.

Structural Connectivity Asymmetry in the Neonatal Brain

OpenAIRE

Ratnarajah, Nagulan; Rifkin-Graboi, Anne; Fortier, Marielle V.; Chong, Yap Seng; Kwek, Kenneth; Saw, Seang-Mei; Godfrey, Keith M; Gluckman, Peter D.; Meaney, Michael J.; Qiu, Anqi

2013-01-01

Asymmetry of the neonatal brain is not yet understood at the level of structural connectivity. We utilized DTI deterministic tractography and structural network analysis based on graph theory to determine the pattern of structural connectivity asymmetry in 124 normal neonates. We tracted white matter axonal pathways characterizing interregional connections among brain regions and inferred asymmetry in left and right anatomical network properties. Our findings revealed that in neonates, small-...

Fish utilisation of wetland nurseries with complex hydrological connectivity.

Directory of Open Access Journals (Sweden)

Ben Davis

Full Text Available The physical and faunal characteristics of coastal wetlands are driven by dynamics of hydrological connectivity to adjacent habitats. Wetlands on estuary floodplains are particularly dynamic, driven by a complex interplay of tidal marine connections and seasonal freshwater flooding, often with unknown consequences for fish using these habitats. To understand the patterns and subsequent processes driving fish assemblage structure in such wetlands, we examined the nature and diversity of temporal utilisation patterns at a species or genus level over three annual cycles in a tropical Australian estuarine wetland system. Four general patterns of utilisation were apparent based on CPUE and size-structure dynamics: (i classic nursery utlisation (use by recently settled recruits for their first year (ii interrupted peristence (iii delayed recruitment (iv facultative wetland residence. Despite the small self-recruiting 'facultative wetland resident' group, wetland occupancy seems largely driven by connectivity to the subtidal estuary channel. Variable connection regimes (i.e. frequency and timing of connections within and between different wetland units (e.g. individual pools, lagoons, swamps will therefore interact with the diversity of species recruitment schedules to generate variable wetland assemblages in time and space. In addition, the assemblage structure is heavily modified by freshwater flow, through simultaneously curtailing persistence of the 'interrupted persistence' group, establishing connectivity for freshwater spawned members of both the 'facultative wetland resident' and 'delayed recruitment group', and apparently mediating use of intermediate nursery habitats for marine-spawned members of the 'delayed recruitment' group. The diversity of utilisation pattern and the complexity of associated drivers means assemblage compositions, and therefore ecosystem functioning, is likely to vary among years depending on variations in hydrological

Sensing coral reef connectivity pathways from space

KAUST Repository

Raitsos, Dionysios E.; Brewin, Robert J. W.; Zhan, Peng; Dreano, Denis; Pradhan, Yaswant; Nanninga, Gerrit B.; Hoteit, Ibrahim

2017-01-01

Coral reefs rely on inter-habitat connectivity to maintain gene flow, biodiversity and ecosystem resilience. Coral reef communities of the Red Sea exhibit remarkable genetic homogeneity across most of the Arabian Peninsula coastline, with a genetic break towards the southern part of the basin. While previous studies have attributed these patterns to environmental heterogeneity, we hypothesize that they may also emerge as a result of dynamic circulation flow; yet, such linkages remain undemonstrated. Here, we integrate satellite-derived biophysical observations, particle dispersion model simulations, genetic population data and ship-borne in situ profiles to assess reef connectivity in the Red Sea. We simulated long-term (>20 yrs.) connectivity patterns driven by remotely-sensed sea surface height and evaluated results against estimates of genetic distance among populations of anemonefish, Amphiprion bicinctus, along the eastern Red Sea coastline. Predicted connectivity was remarkably consistent with genetic population data, demonstrating that circulation features (eddies, surface currents) formulate physical pathways for gene flow. The southern basin has lower physical connectivity than elsewhere, agreeing with known genetic structure of coral reef organisms. The central Red Sea provides key source regions, meriting conservation priority. Our analysis demonstrates a cost-effective tool to estimate biophysical connectivity remotely, supporting coastal management in data-limited regions.

Sensing coral reef connectivity pathways from space

KAUST Repository

Raitsos, Dionysios E.

2017-08-18

Coral reefs rely on inter-habitat connectivity to maintain gene flow, biodiversity and ecosystem resilience. Coral reef communities of the Red Sea exhibit remarkable genetic homogeneity across most of the Arabian Peninsula coastline, with a genetic break towards the southern part of the basin. While previous studies have attributed these patterns to environmental heterogeneity, we hypothesize that they may also emerge as a result of dynamic circulation flow; yet, such linkages remain undemonstrated. Here, we integrate satellite-derived biophysical observations, particle dispersion model simulations, genetic population data and ship-borne in situ profiles to assess reef connectivity in the Red Sea. We simulated long-term (>20 yrs.) connectivity patterns driven by remotely-sensed sea surface height and evaluated results against estimates of genetic distance among populations of anemonefish, Amphiprion bicinctus, along the eastern Red Sea coastline. Predicted connectivity was remarkably consistent with genetic population data, demonstrating that circulation features (eddies, surface currents) formulate physical pathways for gene flow. The southern basin has lower physical connectivity than elsewhere, agreeing with known genetic structure of coral reef organisms. The central Red Sea provides key source regions, meriting conservation priority. Our analysis demonstrates a cost-effective tool to estimate biophysical connectivity remotely, supporting coastal management in data-limited regions.

Analyzing a problem-solution pattern in the transcription of a conversation: suggestions for the ELF classroom

Directory of Open Access Journals (Sweden)

Navas Brenes, César A.

2005-12-01

Full Text Available This paper analyzes a problem-solution pattern shown in the transcription of a conversation. This analysis is based on a conversation that has been elicited from three native speakers of English. These speakers were given a topic that dealt with the problem of children being constantly exposed to violent video games. As a result, the writer recorded an oral text that contains several elements related to a problem-solution pattern such as the main issue, opinions, personal examples, possible solutions, and the evaluation of these solutions. The writer analyzed this pattern in terms of discourse analysis using idea units from the transcription. Moreover, the writer will point out how appropriate this transcription is for preparing teaching tasks for the EFL classroom. Este artículo analiza el patrón estructural de la solución de un problema evidente en la transcripción de una conversación. El análisis esta basado en un diálogo obtenido de tres hablantes nativos de la lengua inglesa. El autor suministró a dichas personas un tema relacionado con el problema de la exposición de niños al contenido violento de los juegos de video. Como resultado, el escritor obtuvo una grabación del texto oral que contiene varios elementos relacionados con el patrón estructural de la solución de un problema. Algunos de estos elementos son el problema principal, opiniones, ejemplos personales, soluciones viables al problema, y la evaluación de dichas soluciones. El autor analizó algunas líneas de la transcripción con la ayuda de algunos conceptos relacionados con el análisis del discurso. Cabe destacar que el uso de tales trascripciones es muy apropiado en la preparación de actividades para una clase de inglés como lengua extranjera.

Brain connectivity measures: computation and comparison

Directory of Open Access Journals (Sweden)

Jovanović Aleksandar

2013-12-01

Full Text Available In this article computation and comparison of causality measures which are used in determination of brain connectivity patterns is investigated. Main analyzed examples included published computation and comparisons of Directed Transfer Function ‐ DTF and Partial Directed Coherence ‐ PDC. It proved that serious methodology mistakes were involved in measure computations and comparisons. It is shown that the neighborhood of zero is of accented importance in such evaluations and that the issues of semantic stability have to be treated with more attention. Published results on the relationship of these two important measures are partly unstable with small changes of zero threshold and pictures of involved brain structures deduced from the cited articles have to be corrected. Analysis of the operators involved in evaluation and comparisons is given with suggestions for their improvement and complementary additional actions.

A review of variables of urban street connectivity for spatial connection

International Nuclear Information System (INIS)

Mohamad, W S N W; Said, I

2014-01-01

Several studies on street connectivity in cities and towns have been modeled on topology, morphology, technology and psychology of people living in the urban environment. Street connectivity means the connection of streets that offers people alternative routes. However, there emerge difficulties to determine the suitable variables and analysis to be chosen in defining the accurate result for studies street connectivity. The aim of this paper is to identify variables of street connectivity by applying GIS and Space Syntax. This paper reviews the variables of street connectivity from 15 past articles done in 1990s to early 2000s from journals of nine disciplines on Environment and Behavior, Planning and Design, Computers, Environment and Urban Systems, Applied Earth Observation and Geo-information, Environment and Planning, Physica A: Statistical Mechanics and its Applications, Environmental Psychology, Social Science and Medicine and Building and Environment. From the review, there are four variables found for street connectivity: link (streets-streets, street-nodes or node-streets, nodes-nodes), accessibility, least-angle, and centrality. Space syntax and GIS are suitable tools to analyze the four variables relating to systematic street systems for pedestrians. This review implies that planners of the street systems, in the aspect of street connectivity in cities and towns, should consider these four variables

A review of variables of urban street connectivity for spatial connection

Science.gov (United States)

Mohamad, W. S. N. W.; Said, I.

2014-02-01

Several studies on street connectivity in cities and towns have been modeled on topology, morphology, technology and psychology of people living in the urban environment. Street connectivity means the connection of streets that offers people alternative routes. However, there emerge difficulties to determine the suitable variables and analysis to be chosen in defining the accurate result for studies street connectivity. The aim of this paper is to identify variables of street connectivity by applying GIS and Space Syntax. This paper reviews the variables of street connectivity from 15 past articles done in 1990s to early 2000s from journals of nine disciplines on Environment and Behavior, Planning and Design, Computers, Environment and Urban Systems, Applied Earth Observation and Geo-information, Environment and Planning, Physica A: Statistical Mechanics and its Applications, Environmental Psychology, Social Science and Medicine and Building and Environment. From the review, there are four variables found for street connectivity: link (streets-streets, street-nodes or node-streets, nodes-nodes), accessibility, least-angle, and centrality. Space syntax and GIS are suitable tools to analyze the four variables relating to systematic street systems for pedestrians. This review implies that planners of the street systems, in the aspect of street connectivity in cities and towns, should consider these four variables.

Acoustic Pattern Recognition on Android Devices

DEFF Research Database (Denmark)

Møller, Maiken Bjerg; Gaarsdal, Jesper; Steen, Kim Arild

2013-01-01

an Android application developed for acoustic pattern recognition of bird species. The acoustic data is recorded using a built-in microphone, and pattern recognition is performed on the device, requiring no network connection. The algorithm is implemented in C++ as a native Android module and the Open......CV library is used for signal processing. We conclude that the approach presented here is a viable solution to pattern recognition problems. Since it requires no network connection, it shows promise in fields such as wildlife research....

A Tensor Statistical Model for Quantifying Dynamic Functional Connectivity.

Science.gov (United States)

Zhu, Yingying; Zhu, Xiaofeng; Kim, Minjeong; Yan, Jin; Wu, Guorong

2017-06-01

Functional connectivity (FC) has been widely investigated in many imaging-based neuroscience and clinical studies. Since functional Magnetic Resonance Image (MRI) signal is just an indirect reflection of brain activity, it is difficult to accurately quantify the FC strength only based on signal correlation. To address this limitation, we propose a learning-based tensor model to derive high sensitivity and specificity connectome biomarkers at the individual level from resting-state fMRI images. First, we propose a learning-based approach to estimate the intrinsic functional connectivity. In addition to the low level region-to-region signal correlation, latent module-to-module connection is also estimated and used to provide high level heuristics for measuring connectivity strength. Furthermore, sparsity constraint is employed to automatically remove the spurious connections, thus alleviating the issue of searching for optimal threshold. Second, we integrate our learning-based approach with the sliding-window technique to further reveal the dynamics of functional connectivity. Specifically, we stack the functional connectivity matrix within each sliding window and form a 3D tensor where the third dimension denotes for time. Then we obtain dynamic functional connectivity (dFC) for each individual subject by simultaneously estimating the within-sliding-window functional connectivity and characterizing the across-sliding-window temporal dynamics. Third, in order to enhance the robustness of the connectome patterns extracted from dFC, we extend the individual-based 3D tensors to a population-based 4D tensor (with the fourth dimension stands for the training subjects) and learn the statistics of connectome patterns via 4D tensor analysis. Since our 4D tensor model jointly (1) optimizes dFC for each training subject and (2) captures the principle connectome patterns, our statistical model gains more statistical power of representing new subject than current state

Fibroblastic connective tissue nevus: a rare cutaneous lesion analyzed in a series of 25 cases.

Science.gov (United States)

de Feraudy, Sébastien; Fletcher, Christopher D M

2012-10-01

Fibroblastic connective tissue nevus (FCTN) represents a rare and distinct benign cutaneous mesenchymal lesion of fibroblastic/myofibroblastic lineage, which broadens the spectrum of lesions presently recognized as connective tissue nevus. A series of 25 cases of FCTN has been analyzed to further characterize the clinicopathologic spectrum and immunohistochemical features of this entity. Sixteen patients were female (64%) and 9 were male (36%), with age at presentation ranging from 1.5 months to 58 years (median, 10 y). Most patients presented with a solitary, slowly growing, painless plaque-like or nodular skin lesion. Eleven cases (44%) arose on the trunk, 9 (36%) on the head and neck, and 5 (20%) on the limbs. The lesion was present for a median duration of 11.5 months (mean, 13.2 mo). Grossly, the lesions were tan-brown to tan-white, smooth, and firm. Their size ranged from 0.3 to 2.0 cm in greatest dimension (mean size, 0.67 cm; median, 0.6 cm). All tumors showed poor circumscription and were situated primarily in the reticular deep dermis, extending into the superficial subcutis in 13 cases (52%). The lesion was associated with papillomatous epidermis in 17 cases (70%) and the presence of adipose tissue in the reticular dermis in 14 cases (60.9%). All tumors were composed of a proliferation of bland intradermal fibroblastic/myofibroblastic cells with indistinct palely eosinophilic cytoplasm and tapering nuclei, with no significant cytologic atypia or pleomorphism, arranged in short-intersecting fascicles and entrapping appendages. No mitoses were identified. Immunostains showed positivity for CD34 in 20 of 23 cases (87%) and weak focal positivity for smooth muscle actin in 9 of 19 cases (47%). No case stained positively for desmin or S100 protein. Clinical follow-up was obtained for 14 patients (median duration, 4 y). No tumor recurred locally, even when surgical excision was incomplete. No lesion metastasized. FCTN occurs most commonly as a plaque on the

Functional and effective whole brain connectivity using magnetoencephalography to identify monozygotic twin pairs

NARCIS (Netherlands)

Demuru, M.; Gouw, A.; Hillebrand, A.; Stam, C J; van Dijk, B W; Scheltens, P.; Tijms, B.M.; Konijnenberg, E.; ten Kate-Booij, M.J.; den Braber, A; Smit, D J A; Boomsma, D I; Visser, P J

2017-01-01

Resting-state functional connectivity patterns are highly stable over time within subjects. This suggests that such 'functional fingerprints' may have strong genetic component. We investigated whether the functional (FC) or effective (EC) connectivity patterns of one monozygotic twin could be used

Atmospheric Circulation Patterns over East Asia and Their Connection with Summer Precipitation and Surface Air Temperature in Eastern China during 1961-2013

Science.gov (United States)

Li, Shuping; Hou, Wei; Feng, Guolin

2018-04-01

Based on the NCEP/NCAR reanalysis data and Chinese observational data during 1961-2013, atmospheric circulation patterns over East Asia in summer and their connection with precipitation and surface air temperature in eastern China as well as associated external forcing are investigated. Three patterns of the atmospheric circulation are identified, all with quasi-barotropic structures: (1) the East Asia/Pacific (EAP) pattern, (2) the Baikal Lake/Okhotsk Sea (BLOS) pattern, and (3) the eastern China/northern Okhotsk Sea (ECNOS) pattern. The positive EAP pattern significantly increases precipitation over the Yangtze River valley and favors cooling north of the Yangtze River and warming south of the Yangtze River in summer. The warm sea surface temperature anomalies over the tropical Indian Ocean suppress convection over the northwestern subtropical Pacific through the Ekman divergence induced by a Kelvin wave and excite the EAP pattern. The positive BLOS pattern is associated with below-average precipitation south of the Yangtze River and robust cooling over northeastern China. This pattern is triggered by anomalous spring sea ice concentration in the northern Barents Sea. The anomalous sea ice concentration contributes to a Rossby wave activity flux originating from the Greenland Sea, which propagates eastward to North Pacific. The positive ECNOS pattern leads to below-average precipitation and significant warming over northeastern China in summer. The reduced soil moisture associated with the earlier spring snowmelt enhances surface warming over Mongolia and northeastern China and the later spring snowmelt leads to surface cooling over Far East in summer, both of which are responsible for the formation of the ECNOS pattern.

Is Reading Instruction Evidence-Based? Analyzing Teaching Practices Using T-Patterns.

Science.gov (United States)

Suárez, Natalia; Sánchez, Carmen R; Jiménez, Juan E; Anguera, M Teresa

2018-01-01

The main goal of this study was to analyze whether primary teachers use evidence-based reading instruction for primary-grade readers. The study sample consisted of six teachers whose teaching was recorded. The observation instrument used was developed ad hoc for this study. The recording instrument used was Match Vision Studio. The data analysis was performed using SAS, GT version 2.0 E, and THEME. The results indicated that the teaching practices used most frequently and for the longest duration were: feedback (i.e., correcting the student when reading); fluency (i.e., individual and group reading, both out loud and silently, with and without intonation); literal or inference comprehension exercises (i.e., summarizing, asking questions); and use of educational resources (i.e., stories, songs, poems). Later, we conducted analyses of T-Patterns that showed the sequence of instruction in detail. We can conclude that practices used by the majority of teachers were based on the recommendations of the National Reading Panel (NRP). Only one teacher followed best practices. The same was the case for instructional time spent on the five essential components of reading, with the exception of teacher E., who dedicated 70.31% of class time implementing best practices. Teaching practices (i.e., learners' activities) designed and implemented to exercise and master alphabetic knowledge and phonological awareness skills were used less frequently in the classroom.

Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback.

Science.gov (United States)

Ramot, Michal; Kimmich, Sara; Gonzalez-Castillo, Javier; Roopchansingh, Vinai; Popal, Haroon; White, Emily; Gotts, Stephen J; Martin, Alex

2017-09-16

The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants' awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns.

Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback

Science.gov (United States)

Kimmich, Sara; Gonzalez-Castillo, Javier; Roopchansingh, Vinai; Popal, Haroon; White, Emily; Gotts, Stephen J; Martin, Alex

2017-01-01

The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants’ awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns. PMID:28917059

Organization of anti-phase synchronization pattern in neural networks: what are the key factors?

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Dong eLi

2011-12-01

Full Text Available Anti-phase oscillation has been widely observed in cortical neuralnetwork. Elucidating the mechanism underlying the organization ofanti-phase pattern is of significance for better understanding morecomplicated pattern formations in brain networks. In dynamicalsystems theory, the organization of anti-phase oscillation patternhas usually been considered to relate to time-delay in coupling.This is consistent to conduction delays in real neural networks inthe brain due to finite propagation velocity of action potentials.However, other structural factors in cortical neural network, suchas modular organization (connection density and the coupling types(excitatory or inhibitory, could also play an important role. Inthis work, we investigate the anti-phase oscillation patternorganized on a two-module network of either neuronal cell model orneural mass model, and analyze the impact of the conduction delaytimes, the connection densities, and coupling types. Our resultsshow that delay times and coupling types can play key roles in thisorganization. The connection densities may have an influence on thestability if an anti-phase pattern exists due to the other factors.Furthermore, we show that anti-phase synchronization of slowoscillations can be achieved with small delay times if there isinteraction between slow and fast oscillations. These results aresignificant for further understanding more realistic spatiotemporaldynamics of cortico-cortical communications.

Modeling Structural Brain Connectivity

DEFF Research Database (Denmark)

Ambrosen, Karen Marie Sandø

The human brain consists of a gigantic complex network of interconnected neurons. Together all these connections determine who we are, how we react and how we interpret the world. Knowledge about how the brain is connected can further our understanding of the brain’s structural organization, help...... improve diagnosis, and potentially allow better treatment of a wide range of neurological disorders. Tractography based on diffusion magnetic resonance imaging is a unique tool to estimate this “structural connectivity” of the brain non-invasively and in vivo. During the last decade, brain connectivity...... has increasingly been analyzed using graph theoretic measures adopted from network science and this characterization of the brain’s structural connectivity has been shown to be useful for the classification of populations, such as healthy and diseased subjects. The structural connectivity of the brain...

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

Science.gov (United States)

Djurfeldt, Mikael

2012-07-01

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

Topologically convergent and divergent functional connectivity patterns in unmedicated unipolar depression and bipolar disorder.

Science.gov (United States)

Wang, Y; Wang, J; Jia, Y; Zhong, S; Zhong, M; Sun, Y; Niu, M; Zhao, L; Zhao, L; Pan, J; Huang, L; Huang, R

2017-07-04

Bipolar disorder (BD), particularly BD II, is frequently misdiagnosed as unipolar depression (UD), leading to inappropriate treatment and poor clinical outcomes. Although depressive symptoms may be expressed similarly in UD and BD, the similarities and differences in the architecture of brain functional networks between the two disorders are still unknown. In this study, we hypothesized that UD and BD II patients would show convergent and divergent patterns of disrupted topological organization of the functional connectome, especially in the default mode network (DMN) and the limbic network. Brain resting-state functional magnetic resonance imaging (fMRI) data were acquired from 32 UD-unmedicated patients, 31 unmedicated BD II patients (current episode depressed) and 43 healthy subjects. Using graph theory, we systematically studied the topological organization of their whole-brain functional networks at the following three levels: whole brain, modularity and node. First, both the UD and BD II patients showed increased characteristic path length and decreased global efficiency compared with the controls. Second, both the UD and BD II patients showed disrupted intramodular connectivity within the DMN and limbic system network. Third, decreased nodal characteristics (nodal strength and nodal efficiency) were found predominantly in brain regions in the DMN, limbic network and cerebellum of both the UD and BD II patients, whereas differences between the UD and BD II patients in the nodal characteristics were also observed in the precuneus and temporal pole. Convergent deficits in the topological organization of the whole brain, DMN and limbic networks may reflect overlapping pathophysiological processes in unipolar and bipolar depression. Our discovery of divergent regional connectivity that supports emotion processing could help to identify biomarkers that will aid in differentiating these disorders.

Mechanisms of Left-Right Coordination in Mammalian Locomotor Pattern Generation Circuits: A Mathematical Modeling View

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Talpalar, Adolfo E.; Rybak, Ilya A.

2015-01-01

The locomotor gait in limbed animals is defined by the left-right leg coordination and locomotor speed. Coordination between left and right neural activities in the spinal cord controlling left and right legs is provided by commissural interneurons (CINs). Several CIN types have been genetically identified, including the excitatory V3 and excitatory and inhibitory V0 types. Recent studies demonstrated that genetic elimination of all V0 CINs caused switching from a normal left-right alternating activity to a left-right synchronized “hopping” pattern. Furthermore, ablation of only the inhibitory V0 CINs (V0D subtype) resulted in a lack of left-right alternation at low locomotor frequencies and retaining this alternation at high frequencies, whereas selective ablation of the excitatory V0 neurons (V0V subtype) maintained the left–right alternation at low frequencies and switched to a hopping pattern at high frequencies. To analyze these findings, we developed a simplified mathematical model of neural circuits consisting of four pacemaker neurons representing left and right, flexor and extensor rhythm-generating centers interacting via commissural pathways representing V3, V0D, and V0V CINs. The locomotor frequency was controlled by a parameter defining the excitation of neurons and commissural pathways mimicking the effects of N-methyl-D-aspartate on locomotor frequency in isolated rodent spinal cord preparations. The model demonstrated a typical left-right alternating pattern under control conditions, switching to a hopping activity at any frequency after removing both V0 connections, a synchronized pattern at low frequencies with alternation at high frequencies after removing only V0D connections, and an alternating pattern at low frequencies with hopping at high frequencies after removing only V0V connections. We used bifurcation theory and fast-slow decomposition methods to analyze network behavior in the above regimes and transitions between them. The model

Analyzing Social Media Networks with NodeXL Insights from a Connected World

CERN Document Server

Hansen, Derek; Smith, Marc A

2010-01-01

Businesses, entrepreneurs, individuals, and government agencies alike are looking to social network analysis (SNA) tools for insight into trends, connections, and fluctuations in social media. Microsoft's NodeXL is a free, open-source SNA plug-in for use with Excel. It provides instant graphical representation of relationships of complex networked data. But it goes further than other SNA tools -- NodeXL was developed by a multidisciplinary team of experts that bring together information studies, computer science, sociology, human-computer interaction, and over 20 years of visual analytic theor

Jubilite: A 4-,8-connected Cubic Structural Pattern in Space Group Pm3

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Eduardo A. Castro

2005-05-01

Full Text Available Abstract: In the course of investigating structural modifications of the 3-,4-connected net known as the Pt3O4 structure-type (waserite, a novel 4-,8-connected structure-type was discovered. This lattice is generated by replacing the 3-connected trigonal planar vertices of the Pt3O4 structure-type with 4-connected tetrahedral vertices, to achieve a structure which possesses a generic empirical formula of JK6L8. In such a topological modification, the four 3-fold axes of the parent cubic, Pm3n, Pt3O4 structure-type are retained. Thus the 4-connected tetrahedral vertices are oriented so as to preserve cubic symmetry in the resulting Pm3, JK6L8 (jubilite lattice. The unit cell contains a single 8-connected cubecentered vertex, six 4-connected distorted square planar vertices and eight 4-connected distorted tetrahedral vertices. It is a Wellsean structure with a Wells point symbol given by (4166484(42826(43838 and a Schläfli symbol of (53/4, 4.2667. This latter index reveals a decrease in the lattice’s polygonality and concomitant increase in the connectivity through the transformation from waserite to jubilite. The topology of the parent waserite lattice (Pt3O4 corresponds to that of the Catalan structures with the Wells point symbol (843(834, which has the Schläfli symbol (8, 3.4285. Finally, it can be seen that a sequence of structure-types starting with waserite (Pt3O4 and moving to jubilite (JK6L8 and finally to fluorite (CaF2 represents a continuous crystallographic structural transformation in which the symmetry and topology undergo concomitant changes from one structure-type (waserite to the other structure-types. The topology of the fluorite lattice, represented by the Wells point symbol (424(462, and the Schläfli symbol (4, 51/3, indicates a discontinuous topological transformation from the intermediate jubilite lattice; like the discontinuous topological transformation from Pt3O4 to JK6L8; in which the

How multi segmental patterns deviate in spastic diplegia from typical developed.

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Zago, Matteo; Sforza, Chiarella; Bona, Alessia; Cimolin, Veronica; Costici, Pier Francesco; Condoluci, Claudia; Galli, Manuela

2017-10-01

The relationship between gait features and coordination in children with Cerebral Palsy is not sufficiently analyzed yet. Principal Component Analysis can help in understanding motion patterns decomposing movement into its fundamental components (Principal Movements). This study aims at quantitatively characterizing the functional connections between multi-joint gait patterns in Cerebral Palsy. 65 children with spastic diplegia aged 10.6 (SD 3.7) years participated in standardized gait analysis trials; 31 typically developing adolescents aged 13.6 (4.4) years were also tested. To determine if posture affects gait patterns, patients were split into Crouch and knee Hyperextension group according to knee flexion angle at standing. 3D coordinates of hips, knees, ankles, metatarsal joints, pelvis and shoulders were submitted to Principal Component Analysis. Four Principal Movements accounted for 99% of global variance; components 1-3 explained major sagittal patterns, components 4-5 referred to movements on frontal plane and component 6 to additional movement refinements. Dimensionality was higher in patients than in controls (p<0.01), and the Crouch group significantly differed from controls in the application of components 1 and 4-6 (p<0.05), while the knee Hyperextension group in components 1-2 and 5 (p<0.05). Compensatory strategies of children with Cerebral Palsy (interactions between main and secondary movement patterns), were objectively determined. Principal Movements can reduce the effort in interpreting gait reports, providing an immediate and quantitative picture of the connections between movement components. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating time-dependent connectivity in marine systems

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Defne, Zafer; Ganju, Neil K.; Aretxabaleta, Alfredo

2016-01-01

Hydrodynamic connectivity describes the sources and destinations of water parcels within a domain over a given time. When combined with biological models, it can be a powerful concept to explain the patterns of constituent dispersal within marine ecosystems. However, providing connectivity metrics for a given domain is a three-dimensional problem: two dimensions in space to define the sources and destinations and a time dimension to evaluate connectivity at varying temporal scales. If the time scale of interest is not predefined, then a general approach is required to describe connectivity over different time scales. For this purpose, we have introduced the concept of a “retention clock” that highlights the change in connectivity through time. Using the example of connectivity between protected areas within Barnegat Bay, New Jersey, we show that a retention clock matrix is an informative tool for multitemporal analysis of connectivity.

Analyzing crack development pattern of masonry structure in seismic oscillation by digital photography

Science.gov (United States)

Zhang, Guojian; Yu, Chengxin; Ding, Xinhua

2018-01-01

In this study, digital photography is used to monitor the instantaneous deformation of a masonry wall in seismic oscillation. In order to obtain higher measurement accuracy, the image matching-time baseline parallax method (IM-TBPM) is used to correct errors caused by the change of intrinsic and extrinsic parameters of digital cameras. Results show that the average errors of control point C5 are 0.79mm, 0.44mm and 0.96mm in X, Z and comprehensive direction, respectively. The average errors of control point C6 are 0.49mm, 0.44mm and 0.71mm in X, Z and comprehensive direction, respectively. These suggest that IM-TBPM can meet the accuracy requirements of instantaneous deformation monitoring. In seismic oscillation the middle to lower of the masonry wall develops cracks firstly. Then the shear failure occurs on the middle of masonry wall. This study provides technical basis for analyzing the crack development pattern of masonry structure in seismic oscillation and have significant implications for improved construction of masonry structures in earthquake prone areas.

Inference from correlated patterns: a unified theory for perceptron learning and linear vector channels

Energy Technology Data Exchange (ETDEWEB)

Kabashima, Y [Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama 226-8502 (Japan)], E-mail: kaba@dis.titech.ac.jp

2008-01-15

A framework to analyze inference performance in densely connected single-layer feed-forward networks is developed for situations where a given data set is composed of correlated patterns. The framework is based on the assumption that the left and right singular value bases of the given pattern matrix are generated independently and uniformly from Haar measures. This assumption makes it possible to characterize the objective system by a single function of two variables which is determined by the eigenvalue spectrum of the cross-correlation matrix of the pattern matrix. Links to existing methods for analysis of perceptron learning and Gaussian linear vector channels and an application to a simple but nontrivial problem are also shown.

Inference from correlated patterns: a unified theory for perceptron learning and linear vector channels

International Nuclear Information System (INIS)

Kabashima, Y

2008-01-01

A framework to analyze inference performance in densely connected single-layer feed-forward networks is developed for situations where a given data set is composed of correlated patterns. The framework is based on the assumption that the left and right singular value bases of the given pattern matrix are generated independently and uniformly from Haar measures. This assumption makes it possible to characterize the objective system by a single function of two variables which is determined by the eigenvalue spectrum of the cross-correlation matrix of the pattern matrix. Links to existing methods for analysis of perceptron learning and Gaussian linear vector channels and an application to a simple but nontrivial problem are also shown

Inference from correlated patterns: a unified theory for perceptron learning and linear vector channels

Science.gov (United States)

Kabashima, Y.

2008-01-01

A framework to analyze inference performance in densely connected single-layer feed-forward networks is developed for situations where a given data set is composed of correlated patterns. The framework is based on the assumption that the left and right singular value bases of the given pattern matrix are generated independently and uniformly from Haar measures. This assumption makes it possible to characterize the objective system by a single function of two variables which is determined by the eigenvalue spectrum of the cross-correlation matrix of the pattern matrix. Links to existing methods for analysis of perceptron learning and Gaussian linear vector channels and an application to a simple but nontrivial problem are also shown.

Persistence of self-recruitment and patterns of larval connectivity in a marine protected area network

KAUST Repository

Berumen, Michael L.

2012-02-01

The use of marine protected area (MPA) networks to sustain fisheries and conserve biodiversity is predicated on two critical yet rarely tested assumptions. Individual MPAs must produce sufficient larvae that settle within that reserve\\'s boundaries to maintain local populations while simultaneously supplying larvae to other MPA nodes in the network that might otherwise suffer local extinction. Here, we use genetic parentage analysis to demonstrate that patterns of self-recruitment of two reef fishes (Amphiprion percula and Chaetodon vagabundus) in an MPA in Kimbe Bay, Papua New Guinea, were remarkably consistent over several years. However, dispersal from this reserve to two other nodes in an MPA network varied between species and through time. The stability of our estimates of self-recruitment suggests that even small MPAs may be self-sustaining. However, our results caution against applying optimization strategies to MPA network design without accounting for variable connectivity among species and over time. 2012 The Authors.

Is Reading Instruction Evidence-Based? Analyzing Teaching Practices Using T-Patterns

Directory of Open Access Journals (Sweden)

Natalia Suárez

2018-02-01

Full Text Available The main goal of this study was to analyze whether primary teachers use evidence-based reading instruction for primary-grade readers. The study sample consisted of six teachers whose teaching was recorded. The observation instrument used was developed ad hoc for this study. The recording instrument used was Match Vision Studio. The data analysis was performed using SAS, GT version 2.0 E, and THEME. The results indicated that the teaching practices used most frequently and for the longest duration were: feedback (i.e., correcting the student when reading; fluency (i.e., individual and group reading, both out loud and silently, with and without intonation; literal or inference comprehension exercises (i.e., summarizing, asking questions; and use of educational resources (i.e., stories, songs, poems. Later, we conducted analyses of T-Patterns that showed the sequence of instruction in detail. We can conclude that <50% of the teaching practices used by the majority of teachers were based on the recommendations of the National Reading Panel (NRP. Only one teacher followed best practices. The same was the case for instructional time spent on the five essential components of reading, with the exception of teacher E., who dedicated 70.31% of class time implementing best practices. Teaching practices (i.e., learners' activities designed and implemented to exercise and master alphabetic knowledge and phonological awareness skills were used less frequently in the classroom.

Conditionals and inferential connections: A hypothetical inferential theory.

Science.gov (United States)

Douven, Igor; Elqayam, Shira; Singmann, Henrik; van Wijnbergen-Huitink, Janneke

2018-03-01

Intuition suggests that for a conditional to be evaluated as true, there must be some kind of connection between its component clauses. In this paper, we formulate and test a new psychological theory to account for this intuition. We combined previous semantic and psychological theorizing to propose that the key to the intuition is a relevance-driven, satisficing-bounded inferential connection between antecedent and consequent. To test our theory, we created a novel experimental paradigm in which participants were presented with a soritical series of objects, notably colored patches (Experiments 1 and 4) and spheres (Experiment 2), or both (Experiment 3), and were asked to evaluate related conditionals embodying non-causal inferential connections (such as "If patch number 5 is blue, then so is patch number 4"). All four experiments displayed a unique response pattern, in which (largely determinate) responses were sensitive to parameters determining inference strength, as well as to consequent position in the series, in a way analogous to belief bias. Experiment 3 showed that this guaranteed relevance can be suppressed, with participants reverting to the defective conditional. Experiment 4 showed that this pattern can be partly explained by a measure of inference strength. This pattern supports our theory's "principle of relevant inference" and "principle of bounded inference," highlighting the dual processing characteristics of the inferential connection. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Clinical applicability of quantitative nailfold capillaroscopy in differential diagnosis of connective tissue diseases with Raynaud's phenomenon.

Science.gov (United States)

Wu, Po-Chang; Huang, Min-Nung; Kuo, Yu-Min; Hsieh, Song-Chou; Yu, Chia-Li

2013-08-01

Nailfold capillaroscopy is a useful tool to distinguish primary from secondary Raynaud's phenomenon (RP) by examining the morphology of nailfold capillaries but its role in disease diagnosis is not clearly established. The purpose of this study was to evaluate the roles of quantitative nailfold capillaroscopy in differential diagnosis of connective tissue diseases (CTDs) with RP. The data between the year 2005 and 2009 were retrieved from the nailfold capillaroscopic database of National Taiwan University Hospital (NTUH). Only the data from the patients with RP were analyzed. The criteria for interpretation of capillaroscopic findings were predefined. The final diagnoses of the patients were based on the American College of Rheumatology classification criteria for individual diseases, independent of nailfold capillaroscopic findings. The sensitivity and the specificity of each capillaroscopic pattern to the diseases were determined. The data from a total of 67 patients were qualified for the current study. We found the sensitivity and specificity of scleroderma pattern for systemic sclerosis (SSc) were 89.47% and 80%, and the specificity of the early, active, and late scleroderma patterns for SSc reached 87.5%, 97.5%, and 95%, respectively. The sensitivity/specificity of systemic lupus erythematosus (SLE) pattern for SLE and polymyositis/dermatomyositis (PM/DM) pattern for PM/DM were 33.33%/95.45% and 60%/96.3%, respectively. The sensitivity/specificity of mixed connective tissue disease (MCTD) pattern for MCTD were 20%/100%. The nailfold capillaroscopic (NC) patterns may be useful in the differential diagnosis of CTDs with RP. The NC patterns for SSc and PM/DM are both sensitive and specific to the diseases, while the SLE and MCTD patterns exhibit high specificity but relatively low sensitivity. Copyright © 2012. Published by Elsevier B.V.

Mathematical Modeling of Column-Base Connections under Monotonic Loading

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Gholamreza Abdollahzadeh

2014-12-01

Full Text Available Some considerable damage to steel structures during the Hyogo-ken Nanbu Earthquake occurred. Among them, many exposed-type column bases failed in several consistent patterns, such as brittle base plate fracture, excessive bolt elongation, unexpected early bolt failure, and inferior construction work, etc. The lessons from these phenomena led to the need for improved understanding of column base behavior. Joint behavior must be modeled when analyzing semi-rigid frames, which is associated with a mathematical model of the moment–rotation curve. The most accurate model uses continuous nonlinear functions. This article presents three areas of steel joint research: (1 analysis methods of semi-rigid joints; (2 prediction methods for the mechanical behavior of joints; (3 mathematical representations of the moment–rotation curve. In the current study, a new exponential model to depict the moment–rotation relationship of column base connection is proposed. The proposed nonlinear model represents an approach to the prediction of M–θ curves, taking into account the possible failure modes and the deformation characteristics of the connection elements. The new model has three physical parameters, along with two curve-fitted factors. These physical parameters are generated from dimensional details of the connection, as well as the material properties. The M–θ curves obtained by the model are compared with published connection tests and 3D FEM research. The proposed mathematical model adequately comes close to characterizing M–θ behavior through the full range of loading/rotations. As a result, modeling of column base connections using the proposed mathematical model can give crucial beforehand information, and overcome the disadvantages of time consuming workmanship and cost of experimental studies.

A word-count approach to analyze linguistic patterns in the reflective writings of medical students

Directory of Open Access Journals (Sweden)

Chi-Wei Lin

2016-02-01

Full Text Available Background: Teaching reflection and administering reflective writing assignments to students are widely practiced and discussed in medical education and health professional education. However, little is known about how medical students use language to construct their narratives. Exploring students’ linguistic patterns in their reflective writings can facilitate understanding the scope and facets of their reflections and their representational or communication approaches to share their experiences. Moreover, research findings regarding gender differences in language use are inconsistent. Therefore, we attempted to examine how females and males differ in their use of words in reflective writing within our research circumstance to detect the unique and gender-specific approaches to learning and their applications. Methods: We analyzed the linguistic profiles of psychological process categories in the reflective writings of medical students and examined the difference in word usage between male and female medical students. During the first year of a clinical rotation, 60 fifth-year medical students wrote reflective narratives regarding pediatric patients and the psychosocial challenges faced by the patients and their family members. The narratives were analyzed using the Chinese version of Linguistic Inquiry and Word Count (CLIWC, a text analysis software program. Multivariate procedures were applied for statistical analysis. Results: Cognitive words were most pervasive, averaging 22.16%, whereas perceptual words (2.86% were least pervasive. Female students used more words related to positive emotions and sadness than did male students. The male students exceeded the female students only in the space category. The major limitation of this study is that CLIWC cannot directly acquire contextual text meanings; therefore, depending on the research topic, further qualitative study of the given texts might be necessary. Conclusions: To enhance students�

Dopamine-Related Disruption of Functional Topography of Striatal Connections in Unmedicated Patients With Schizophrenia.

Science.gov (United States)

Horga, Guillermo; Cassidy, Clifford M; Xu, Xiaoyan; Moore, Holly; Slifstein, Mark; Van Snellenberg, Jared X; Abi-Dargham, Anissa

2016-08-01

Despite the well-established role of striatal dopamine in psychosis, current views generally agree that cortical dysfunction is likely necessary for the emergence of psychotic symptoms. The topographic organization of striatal-cortical connections is central to gating and integration of higher-order information, so a disruption of such topography via dysregulated dopamine could lead to cortical dysfunction in schizophrenia. However, this hypothesis remains to be tested using multivariate methods ascertaining the global pattern of striatal connectivity and without the confounding effects of antidopaminergic medication. To examine whether the pattern of brain connectivity across striatal subregions is abnormal in unmedicated patients with schizophrenia and whether this abnormality relates to psychotic symptoms and extrastriatal dopaminergic transmission. In this multimodal, case-control study, we obtained resting-state functional magnetic resonance imaging data from 18 unmedicated patients with schizophrenia and 24 matched healthy controls from the New York State Psychiatric Institute. A subset of these (12 and 17, respectively) underwent positron emission tomography with the dopamine D2 receptor radiotracer carbon 11-labeled FLB457 before and after amphetamine administration. Data were acquired between June 16, 2011, and February 25, 2014. Data analysis was performed from September 1, 2014, to January 11, 2016. Group differences in the striatal connectivity pattern (assessed via multivariable logistic regression) across striatal subregions, the association between the multivariate striatal connectivity pattern and extrastriatal baseline D2 receptor binding potential and its change after amphetamine administration, and the association between the multivariate connectivity pattern and the severity of positive symptoms evaluated with the Positive and Negative Syndrome Scale. Of the patients with schizophrenia (mean [SEM] age, 35.6 [11.8] years), 9 (50%) were male and 9

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

Science.gov (United States)

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

Science.gov (United States)

Li, Xiang; Lim, Chulwoo; Li, Kaiming; Guo, Lei; Liu, Tianming

2013-01-01

Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) have been widely used to study structural and functional brain connectivity in recent years. A common assumption used in many previous functional brain connectivity studies is the temporal stationarity. However, accumulating literature evidence has suggested that functional brain connectivity is under temporal dynamic changes in different time scales. In this paper, a novel and intuitive approach is proposed to model and detect dynamic changes of functional brain states based on multimodal fMRI/DTI data. The basic idea is that functional connectivity patterns of all fiber-connected cortical voxels are concatenated into a descriptive functional feature vector to represent the brain’s state, and the temporal change points of brain states are decided by detecting the abrupt changes of the functional vector patterns via the sliding window approach. Our extensive experimental results have shown that meaningful brain state change points can be detected in task-based fMRI/DTI, resting state fMRI/DTI, and natural stimulus fMRI/DTI data sets. Particularly, the detected change points of functional brain states in task-based fMRI corresponded well to the external stimulus paradigm administered to the participating subjects, thus partially validating the proposed brain state change detection approach. The work in this paper provides novel perspective on the dynamic behaviors of functional brain connectivity and offers a starting point for future elucidation of the complex patterns of functional brain interactions and dynamics. PMID:22941508

Increased functional connectivity strength of right inferior temporal gyrus in first-episode, drug-naive somatization disorder.

Science.gov (United States)

Su, Qinji; Yao, Dapeng; Jiang, Muliang; Liu, Feng; Jiang, Jiajing; Xu, Chunxing; Dai, Yi; Yu, Miaoyu; Long, Liling; Li, Hongzheng; Liu, Jianrong; Zhang, Zhikun; Zhang, Jian; Xiao, Changqing; Guo, Wenbin

2015-01-01

Evidence of brain structural and functional alterations have been implicated in patients with somatization disorder (SD). However, little is known about brain functional connectivity in SD. In the present study, resting-state functional magnetic resonance imaging (fMRI) and graph theory were used to obtain a comprehensive view of whole-brain functional connectivity and to investigate the changes of voxel-wise functional networks in patients with SD. Twenty-five first-episode, medication-naive patients with SD and 28 age-, sex- and education-matched healthy controls (HCs) underwent resting-state fMRI. The graph theory approach was employed to analyze the data. Compared to the HCs, patients with SD showed significantly increased functional connectivity strength in the right inferior temporal gyrus (ITG). There is a significant positive correlation between the z-values of the cluster in the right ITG and Hamilton Anxiety Scale scores. Our findings indicate that there is a disruption of the functional connectivity pattern in the right ITG in first-episode, treatment-naive patients with SD, which bears clinical significance. © The Royal Australian and New Zealand College of Psychiatrists 2014.

Surveying and analyzing injection responses for patterns with horizontal wells

Energy Technology Data Exchange (ETDEWEB)

Fedenczuk, L.; Hoffman, K.

1998-12-31

A novel method for visualizing injection responses in patterns that include horizontal and/or vertical wells is described. Understanding fluid communication between the horizontal well and the surrounding injectors is essential to estimating the effectiveness of the waterflood. Armed with the understanding of responses, injection patterns can be optimized, production rates can be increased and more efficient oil recovery can be achieved. In this study the time lags of correlations and a new parameter, the waterflood response type is introduced. The response type is based on the oil and total fluid responses. In addition spider diagrams are introduced to help visualizing the correlations, time lags and response types. Integration of the results with geology, petrophysics and completion techniques can help to find the cause and effect rules in waterflood fields. 6 refs., 10 figs.

Probabilistic Tractography Recovers a Rostrocaudal Trajectory of Connectivity Variability in the Human Insular Cortex

Science.gov (United States)

Cerliani, Leonardo; Thomas, Rajat M; Jbabdi, Saad; Siero, Jeroen CW; Nanetti, Luca; Crippa, Alessandro; Gazzola, Valeria; D'Arceuil, Helen; Keysers, Christian

2012-01-01

The insular cortex of macaques has a wide spectrum of anatomical connections whose distribution is related to its heterogeneous cytoarchitecture. Although there is evidence of a similar cytoarchitectural arrangement in humans, the anatomical connectivity of the insula in the human brain has not yet been investigated in vivo. In the present work, we used in vivo probabilistic white-matter tractography and Laplacian eigenmaps (LE) to study the variation of connectivity patterns across insular territories in humans. In each subject and hemisphere, we recovered a rostrocaudal trajectory of connectivity variation ranging from the anterior dorsal and ventral insula to the dorsal caudal part of the long insular gyri. LE suggested that regional transitions among tractography patterns in the insula occur more gradually than in other brain regions. In particular, the change in tractography patterns was more gradual in the insula than in the medial premotor region, where a sharp transition between different tractography patterns was found. The recovered trajectory of connectivity variation in the insula suggests a relation between connectivity and cytoarchitecture in humans resembling that previously found in macaques: tractography seeds from the anterior insula were mainly found in limbic and paralimbic regions and in anterior parts of the inferior frontal gyrus, while seeds from caudal insular territories mostly reached parietal and posterior temporal cortices. Regions in the putative dysgranular insula displayed more heterogeneous connectivity patterns, with regional differences related to the proximity with either putative granular or agranular regions. Hum Brain Mapp 33:2005–2034, 2012. © 2011 Wiley Periodicals, Inc. PMID:21761507

Progressively Disrupted Brain Functional Connectivity Network in Subcortical Ischemic Vascular Cognitive Impairment Patients.

Science.gov (United States)

Sang, Linqiong; Chen, Lin; Wang, Li; Zhang, Jingna; Zhang, Ye; Li, Pengyue; Li, Chuanming; Qiu, Mingguo

2018-01-01

Cognitive impairment caused by subcortical ischemic vascular disease (SIVD) has been elucidated by many neuroimaging studies. However, little is known regarding the changes in brain functional connectivity networks in relation to the severity of cognitive impairment in SIVD. In the present study, 20 subcortical ischemic vascular cognitive impairment no dementia patients (SIVCIND) and 20 dementia patients (SIVaD) were enrolled; additionally, 19 normal controls were recruited. Each participant underwent a resting-state functional MRI scan. Whole-brain functional networks were analyzed with graph theory and network-based statistics (NBS) to study the functional organization of networks and find alterations in functional connectivity among brain regions. After adjustments for age, gender, and duration of formal education, there were significant group differences for two network functional organization indices, global efficiency and local efficiency, which decreased (NC > SIVCIND > SIVaD) as cognitive impairment worsened. Between-group differences in functional connectivity (NBS corrected, p  impairment worsened, with an increased number of decreased connections between brain regions. We also observed more reductions in nodal efficiency in the prefrontal and temporal cortices for SIVaD than for SIVCIND. These findings indicated a progressively disrupted pattern of the brain functional connectivity network with increased cognitive impairment and showed promise for the development of reliable biomarkers of network metric changes related to cognitive impairment caused by SIVD.

Balancing Health Information Exchange and Privacy Governance from a Patient-Centred Connected Health and Telehealth Perspective.

Science.gov (United States)

Kuziemsky, Craig E; Gogia, Shashi B; Househ, Mowafa; Petersen, Carolyn; Basu, Arindam

2018-04-22

 Connected healthcare is an essential part of patient-centred care delivery. Technology such as telehealth is a critical part of connected healthcare. However, exchanging health information brings the risk of privacy issues. To better manage privacy risks we first need to understand the different patterns of patient-centred care in order to tailor solutions to address privacy risks.  Drawing upon published literature, we develop a business model to enable patient-centred care via telehealth. The model identifies three patient-centred connected health patterns. We then use the patterns to analyse potential privacy risks and possible solutions from different types of telehealth delivery.  Connected healthcare raises the risk of unwarranted access to health data and related invasion of privacy. However, the risk and extent of privacy issues differ according to the pattern of patient-centred care delivery and the type of particular challenge as they enable the highest degree of connectivity and thus the greatest potential for privacy breaches.  Privacy issues are a major concern in telehealth systems and patients, providers, and administrators need to be aware of these privacy issues and have guidance on how to manage them. This paper integrates patient-centred connected health care, telehealth, and privacy risks to provide an understanding of how risks vary across different patterns of patient-centred connected health and different types of telehealth delivery. Georg Thieme Verlag KG Stuttgart.

Lobular patterns of cerebellar resting-state connectivity in adults with Autism Spectrum Disorder.

Science.gov (United States)

Olivito, Giusy; Lupo, Michela; Laghi, Fiorenzo; Clausi, Silvia; Baiocco, Roberto; Cercignani, Mara; Bozzali, Marco; Leggio, Maria

2018-03-01

Autism spectrum disorder is a neurodevelopmental disorder characterized by core deficits in social functioning. Core autistics traits refer to poor social and imagination skills, poor attention-switching/strong focus of attention, exceptional attention to detail, as expressed by the autism-spectrum quotient. Over the years, the importance of the cerebellum in the aetiology of autism spectrum disorder has been acknowledged. Neuroimaging studies have provided a strong support to this view, showing both structural and functional connectivity alterations to affect the cerebellum in autism spectrum disorder. According to the underconnectivity theory, disrupted connectivity within cerebello-cerebral networks has been specifically implicated in the aetiology of autism spectrum disorder. However, inconsistent results have been generated across studies. In this study, an integrated approach has been used in a selected population of adults with autism spectrum disorder to analyse both cerebellar morphometry and functional connectivity. In individuals with autism spectrum disorder, a decreased cerebellar grey matter volume affected the right Crus II, a region showing extensive connections with cerebral areas related to social functions. This grey matter reduction correlates with the degree of autistic traits as measured by autism-spectrum quotient. Interestingly, altered functional connectivity was found between the reduced cerebellar Crus II and contralateral cerebral regions, such as frontal and temporal areas. Overall, the present data suggest that adults with autism spectrum disorder present with specific cerebellar structural alterations that may affect functional connectivity within cerebello-cerebral modules relevant to social processing and account for core autistics traits. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Patterns of effective connectivity during memory encoding and retrieval differ between patients with mild cognitive impairment and healthy older adults.

Science.gov (United States)

Hampstead, B M; Khoshnoodi, M; Yan, W; Deshpande, G; Sathian, K

2016-01-01

Previous research has shown that there is considerable overlap in the neural networks mediating successful memory encoding and retrieval. However, little is known about how the relevant human brain regions interact during these distinct phases of memory or how such interactions are affected by memory deficits that characterize mild cognitive impairment (MCI), a condition that often precedes dementia due to Alzheimer's disease. Here we employed multivariate Granger causality analysis using autoregressive modeling of inferred neuronal time series obtained by deconvolving the hemodynamic response function from measured blood oxygenation level-dependent (BOLD) time series data, in order to examine the effective connectivity between brain regions during successful encoding and/or retrieval of object location associations in MCI patients and comparable healthy older adults. During encoding, healthy older adults demonstrated a left hemisphere dominant pattern where the inferior frontal junction, anterior intraparietal sulcus (likely involving the parietal eye fields), and posterior cingulate cortex drove activation in most left hemisphere regions and virtually every right hemisphere region tested. These regions are part of a frontoparietal network that mediates top-down cognitive control and is implicated in successful memory formation. In contrast, in the MCI patients, the right frontal eye field drove activation in every left hemisphere region examined, suggesting reliance on more basic visual search processes. Retrieval in the healthy older adults was primarily driven by the right hippocampus with lesser contributions of the right anterior thalamic nuclei and right inferior frontal sulcus, consistent with theoretical models holding the hippocampus as critical for the successful retrieval of memories. The pattern differed in MCI patients, in whom the right inferior frontal junction and right anterior thalamus drove successful memory retrieval, reflecting the

Calibration-measurement unit for the automation of vector network analyzer measurements

Directory of Open Access Journals (Sweden)

I. Rolfes

2008-05-01

Full Text Available With the availability of multi-port vector network analyzers, the need for automated, calibrated measurement facilities increases. In this contribution, a calibration-measurement unit is presented which realizes a repeatable automated calibration of the measurement setup as well as a user-friendly measurement of the device under test (DUT. In difference to commercially available calibration units, which are connected to the ports of the vector network analyzer preceding a measurement and which are then removed so that the DUT can be connected, the presented calibration-measurement unit is permanently connected to the ports of the VNA for the calibration as well as for the measurement of the DUT. This helps to simplify the calibrated measurement of complex scattering parameters. Moreover, a full integration of the calibration unit into the analyzer setup becomes possible. The calibration-measurement unit is based on a multiport switch setup of e.g. electromechanical relays. Under the assumption of symmetry of a switch, on the one hand the unit realizes the connection of calibration standards like one-port reflection standards and two-port through connections between different ports and on the other hand it enables the connection of the DUT. The calibration-measurement unit is applicable for two-port VNAs as well as for multiport VNAs. For the calibration of the unit, methods with completely known calibration standards like SOLT (short, open, load, through as well as self-calibration procedures like TMR or TLR can be applied.

A central pattern generator producing alternative outputs: pattern, strength, and dynamics of premotor synaptic input to leech heart motor neurons.

Science.gov (United States)

Norris, Brian J; Weaver, Adam L; Wenning, Angela; García, Paul S; Calabrese, Ronald L

2007-11-01

The central pattern generator (CPG) for heartbeat in medicinal leeches consists of seven identified pairs of segmental heart interneurons and one unidentified pair. Four of the identified pairs and the unidentified pair of interneurons make inhibitory synaptic connections with segmental heart motor neurons. The CPG produces a side-to-side asymmetric pattern of intersegmental coordination among ipsilateral premotor interneurons corresponding to a similarly asymmetric fictive motor pattern in heart motor neurons, and asymmetric constriction pattern of the two tubular hearts, synchronous and peristaltic. Using extracellular recordings from premotor interneurons and voltage-clamp recordings of ipsilateral segmental motor neurons in 69 isolated nerve cords, we assessed the strength and dynamics of premotor inhibitory synaptic output onto the entire ensemble of heart motor neurons and the associated conduction delays in both coordination modes. We conclude that premotor interneurons establish a stereotypical pattern of intersegmental synaptic connectivity, strengths, and dynamics that is invariant across coordination modes, despite wide variations among preparations. These data coupled with a previous description of the temporal pattern of premotor interneuron activity and relative phasing of motor neuron activity in the two coordination modes enable a direct assessment of how premotor interneurons through their temporal pattern of activity and their spatial pattern of synaptic connectivity, strengths, and dynamics coordinate segmental motor neurons into a functional pattern of activity.

Home-range use patterns and movements of the Siberian flying squirrel in urban forests: Effects of habitat composition and connectivity.

Science.gov (United States)

Mäkeläinen, Sanna; de Knegt, Henrik J; Ovaskainen, Otso; Hanski, Ilpo K

2016-01-01

Urbanization causes modification, fragmentation and loss of native habitats. Such landscape changes threaten many arboreal and gliding mammals by limiting their movements through treeless parts of a landscape and by making the landscape surrounding suitable habitat patches more inhospitable. Here, we investigate the effects of landscape structure and habitat availability on the home-range use and movement patterns of the Siberian flying squirrel (Pteromys volans) at different spatial and temporal scales. We followed radio-tagged individuals in a partly urbanized study area in Eastern Finland, and analysed how landscape composition and connectivity affected the length and speed of movement bursts, distances moved during one night, and habitat and nest-site use. The presence of urban habitat on movement paths increased both movement lengths and speed whereas nightly distances travelled by males decreased with increasing amount of urban habitat within the home range. The probability of switching from the present nest site to another nest site decreased with increasing distance among the nest sites, but whether the nest sites were connected or unconnected by forests did not have a clear effect on nest switching. Flying squirrels preferred to use mature forests for their movements at night. Our results suggest that the proximity to urban habitats modifies animal movements, possibly because animals try to avoid such habitats by moving faster through them. Urbanization at the scale of an entire home range can restrict their movements. Thus, maintaining a large enough amount of mature forests around inhabited landscape fragments will help protect forest specialists in urban landscapes. The effect of forested connections remains unclear, highlighting the difficulty of measuring and preserving connectivity in a species-specific way.

Close encounters: Analyzing how social similarity and propinquity contribute to strong network connections.

OpenAIRE

Reagans, Ray Eugene

2010-01-01

Models of network formation emphasize the importance of social similarity and propinquity in producing strong interpersonal connections. The positive effect each factor can have on tie strength has been documented across a number of studies, and yet we know surprisingly very little about how the two factors combine to produce strong ties. Being in close proximity could either amplify or dampen the positive effect that social similarity can have on tie strength. Data on tie strength among teac...

Using Petri nets for modeling enterprise integration patterns

NARCIS (Netherlands)

Fahland, D.; Gierds, C.

2012-01-01

Enterprise Integration Patterns are a collection of widely used patterns for integrating enterprise applications and business processes. These patterns informally represent typical design decisions for connecting enterprise applications. For the set of patterns collected by Hohpe and Woolf in

Evolutionary plasticity of habenular asymmetry with a conserved efferent connectivity pattern.

Directory of Open Access Journals (Sweden)

Aldo Villalón

Full Text Available The vertebrate habenulae (Hb is an evolutionary conserved dorsal diencephalic nuclear complex that relays information from limbic and striatal forebrain regions to the ventral midbrain. One key feature of this bilateral nucleus is the presence of left-right differences in size, cytoarchitecture, connectivity, neurochemistry and/or gene expression. In teleosts, habenular asymmetry has been associated with preferential innervation of left-right habenular efferents into dorso-ventral domains of the midbrain interpeduncular nucleus (IPN. However, the degree of conservation of this trait and its relation to the structural asymmetries of the Hb are currently unknown. To address these questions, we performed the first systematic comparative analysis of structural and connectional asymmetries of the Hb in teleosts. We found striking inter-species variability in the overall shape and cytoarchitecture of the Hb, and in the frequency, strength and to a lesser degree, laterality of habenular volume at the population level. Directional asymmetry of the Hb was either to the left in D. rerio, E. bicolor, O. latipes, P. reticulata, B. splendens, or to the right in F. gardneri females. In contrast, asymmetry was absent in P. scalare and F. gardneri males at the population level, although in these species the Hb displayed volumetric asymmetries at the individual level. Inter-species variability was more pronounced across orders than within a single order, and coexisted with an overall conserved laterotopic representation of left-right habenular efferents into dorso-ventral domains of the IPN. These results suggest that the circuit design involving the Hb of teleosts promotes structural flexibility depending on developmental, cognitive and/or behavioural pressures, without affecting the main midbrain connectivity output, thus unveiling a key conserved role of this connectivity trait in the function of the circuit. We propose that ontogenic plasticity in habenular

Increased precuneus connectivity during propofol sedation.

Science.gov (United States)

Liu, Xiaolin; Li, Shi-Jiang; Hudetz, Anthony G

2014-02-21

Using functional magnetic resonance imaging in human participants, we show that sedation by propofol to the point of lost overt responsiveness during the performance of an auditory verbal memory task unexpectedly increases functional connectivity of the precuneus with cortical regions, particularly the dorsal prefrontal and visual cortices. After recovery of consciousness, functional connectivity returns to a pattern similar to that observed during the wakeful baseline. In the context of a recent proposal that highlights the uncoupling of consciousness, connectedness, and responsiveness in general anesthesia, the increased precuneus functional connectivity under propofol sedation may reflect disconnected endogenous mentation or dreaming that continues at a reduced level of metabolic activity. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Latent and Abnormal Functional Connectivity Circuits in Autism Spectrum Disorder.

Science.gov (United States)

Chen, Shuo; Xing, Yishi; Kang, Jian

2017-01-01

Autism spectrum disorder (ASD) is associated with disrupted brain networks. Neuroimaging techniques provide noninvasive methods of investigating abnormal connectivity patterns in ASD. In the present study, we compare functional connectivity networks in people with ASD with those in typical controls, using neuroimaging data from the Autism Brain Imaging Data Exchange (ABIDE) project. Specifically, we focus on the characteristics of intrinsic functional connectivity based on data collected by resting-state functional magnetic resonance imaging (rs-fMRI). Our aim was to identify disrupted brain connectivity patterns across all networks, instead of in individual edges, by using advanced statistical methods. Unlike many brain connectome studies, in which networks are prespecified before the edge connectivity in each network is compared between clinical groups, we detected the latent differentially expressed networks automatically. Our network-level analysis identified abnormal connectome networks that (i) included a high proportion of edges that were differentially expressed between people with ASD and typical controls; and (ii) showed highly-organized graph topology. These findings provide new insight into the study of the underlying neuropsychiatric mechanism of ASD.

Scale of habitat connectivity and colonization in fragmented nuthatch populations

NARCIS (Netherlands)

Langevelde, van F.

2000-01-01

Studies of effects of landscape pattern on population dynamics should consider the spatial scale at which habitat connectivity varies relative to the spatial scale of the species' behavioral response. In this paper, I investigate the relationship between the degree of connectivity of wooded patches

Emission spectrometric isotope analyzer

International Nuclear Information System (INIS)

Mauersberger, K.; Meier, G.; Nitschke, W.; Rose, W.; Schmidt, G.; Rahm, N.; Andrae, G.; Krieg, D.; Kuefner, W.; Tamme, G.; Wichlacz, D.

1982-01-01

An emission spectrometric isotope analyzer has been designed for determining relative abundances of stable isotopes in gaseous samples in discharge tubes, in liquid samples, and in flowing gaseous samples. It consists of a high-frequency generator, a device for defined positioning of discharge tubes, a grating monochromator with oscillating slit and signal converter, signal generator, window discriminator, AND connection, read-out display, oscillograph, gas dosing device and chemical conversion system with carrier gas source and vacuum pump

Functional and effective whole brain connectivity using magnetoencephalography to identify monozygotic twin pairs.

Science.gov (United States)

Demuru, M; Gouw, A A; Hillebrand, A; Stam, C J; van Dijk, B W; Scheltens, P; Tijms, B M; Konijnenberg, E; Ten Kate, M; den Braber, A; Smit, D J A; Boomsma, D I; Visser, P J

2017-08-29

Resting-state functional connectivity patterns are highly stable over time within subjects. This suggests that such 'functional fingerprints' may have strong genetic component. We investigated whether the functional (FC) or effective (EC) connectivity patterns of one monozygotic twin could be used to identify the co-twin among a larger sample and determined the overlap in functional fingerprints within monozygotic (MZ) twin pairs using resting state magnetoencephalography (MEG). We included 32 cognitively normal MZ twin pairs from the Netherlands Twin Register who participate in the EMIF-AD preclinAD study (average age 68 years). Combining EC information across multiple frequency bands we obtained an identification rate over 75%. Since MZ twin pairs are genetically identical these results suggest a high genetic contribution to MEG-based EC patterns, leading to large similarities in brain connectivity patterns between two individuals even after 60 years of life or more.

Intervessel connectivity and relationship with patterns of lateral water exchange within and between xylem sectors in seven xeric shrubs from the great Sahara desert.

Science.gov (United States)

Halis, Youcef; Mayouf, Rabah; Benhaddya, Mohamed Lamine; Belhamra, Mohamed

2013-03-01

The main objective of this study was to evaluate the role of intervessel contacts in determining the patterns of hydraulic integration both within and between xylem sectors. The degree of intervessel contacts and the lateral exchange capability within and between sectors were examined and correlated in different xeric shrubs. A dye injection method was used to detect the connections between vessels; an apoplastic dye was sucked through a known number of vessels and its distribution in the xylem network was followed. Hydraulic techniques were used to measure axial and tangential conductivity both within and between xylem sectors. The intra- and inter-sector integration indexes were then determined as the ratio of tangential to axial conductance. Species differed significantly in the degree of intervessel contacts, intra- and inter-sector integration index. In all cases, hydraulic integration was observed to be higher within sector than between sectors. From the correlation analyses, the intervessel contacts showed a very weak relationship with inter-sector integration index and a strong positive relationship with intra-sector integration index. Results suggested that (1) the factors affecting patterns of lateral flow within xylem sectors might be relatively different from those between sectors. (2) The degree of intervessel contacts was a major determinant of hydraulic integration within the same xylem sector. (3) Intervessel connectivity alone was a poor predictor of hydraulic integration between different sectors, implying a significant contribution of other anatomical, physiological and environmental factors in determining the patterns of integrated-sectored transport within woody stems.

Extraversion modulates functional connectivity hubs of resting-state brain networks.

Science.gov (United States)

Pang, Yajing; Cui, Qian; Duan, Xujun; Chen, Heng; Zeng, Ling; Zhang, Zhiqiang; Lu, Guangming; Chen, Huafu

2017-09-01

Personality dimension extraversion describes individual differences in social behaviour and socio-emotional functioning. The intrinsic functional connectivity patterns of the brain are reportedly associated with extraversion. However, whether or not extraversion is associated with functional hubs warrants clarification. Functional hubs are involved in the rapid integration of neural processing, and their dysfunction contributes to the development of neuropsychiatric disorders. In this study, we employed the functional connectivity density (FCD) method for the first time to distinguish the energy-efficient hubs associated with extraversion. The resting-state functional magnetic resonance imaging data of 71 healthy subjects were used in the analysis. Short-range FCD was positively correlated with extraversion in the left cuneus, revealing a link between the local functional activity of this region and extraversion in risk-taking. Long-range FCD was negatively correlated with extraversion in the right superior frontal gyrus and the inferior frontal gyrus. Seed-based resting-state functional connectivity (RSFC) analyses revealed that a decreased long-range FCD in individuals with high extraversion scores showed a low long-range functional connectivity pattern between the medial and dorsolateral prefrontal cortex, middle temporal gyrus, and anterior cingulate cortex. This result suggests that decreased RSFC patterns are responsible for self-esteem, self-evaluation, and inhibitory behaviour system that account for the modulation and shaping of extraversion. Overall, our results emphasize specific brain hubs, and reveal long-range functional connections in relation to extraversion, thereby providing a neurobiological basis of extraversion. © 2015 The British Psychological Society.

Resting-state network disruption and APOE genotype in Alzheimer's disease: a lagged functional connectivity study.

Directory of Open Access Journals (Sweden)

Leonides Canuet

Full Text Available BACKGROUND: The apolipoprotein E epsilon 4 (APOE-4 is associated with a genetic vulnerability to Alzheimer's disease (AD and with AD-related abnormalities in cortical rhythms. However, it is unclear whether APOE-4 is linked to a specific pattern of intrinsic functional disintegration of the brain after the development of the disease or during its different stages. This study aimed at identifying spatial patterns and effects of APOE genotype on resting-state oscillations and functional connectivity in patients with AD, using a physiological connectivity index called "lagged phase synchronization". METHODOLOGY/PRINCIPAL FINDINGS: Resting EEG was recorded during awake, eyes-closed state in 125 patients with AD and 60 elderly controls. Source current density and functional connectivity were determined using eLORETA. Patients with AD exhibited reduced parieto-occipital alpha oscillations compared with controls, and those carrying the APOE-4 allele had reduced alpha activity in the left inferior parietal and temporo-occipital cortex relative to noncarriers. There was a decreased alpha2 connectivity pattern in AD, involving the left temporal and bilateral parietal cortex. Several brain regions exhibited increased lagged phase synchronization in low frequencies, specifically in the theta band, across and within hemispheres, where temporal lobe connections were particularly compromised. Areas with abnormal theta connectivity correlated with cognitive scores. In patients with early AD, we found an APOE-4-related decrease in interhemispheric alpha connectivity in frontal and parieto-temporal regions. CONCLUSIONS/SIGNIFICANCE: In addition to regional cortical dysfunction, as indicated by abnormal alpha oscillations, there are patterns of functional network disruption affecting theta and alpha bands in AD that associate with the level of cognitive disturbance or with the APOE genotype. These functional patterns of nonlinear connectivity may potentially

Granular patterns

CERN Document Server

Aranson, Igor S

2009-01-01

This title presents a review of experiments and novel theoretical concepts needed to understand the mechanisms of pattern formation in granular materials. An effort is made to connect concepts and ideas developed in granular physics with new emergent fields, especially in biology, such as cytoskeleton dynamics.

Zebrafish Expression Ontology of Gene Sets (ZEOGS): A Tool to Analyze Enrichment of Zebrafish Anatomical Terms in Large Gene Sets

Science.gov (United States)

Marsico, Annalisa

2013-01-01

Abstract The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene

Zebrafish Expression Ontology of Gene Sets (ZEOGS): a tool to analyze enrichment of zebrafish anatomical terms in large gene sets.

Science.gov (United States)

Prykhozhij, Sergey V; Marsico, Annalisa; Meijsing, Sebastiaan H

2013-09-01

The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene expression

The Chess and Mathematics Connection: More than Just a Game

Science.gov (United States)

Berkman, Robert M.

2004-01-01

This article describes connections between chess and mathematics, including examples of activities that connect chess with set theory, patterns, algebra, geometry, combinatorics, and Pascal's triangle. The author observes that competitive games play a dual purpose in advancing the work of mathematics educators: to reinforce a specific skill and to…

Utilizing Geographic Information Systems (GIS) to analyze geographic and demographic patterns related to forensic case recovery locations in Florida.

Science.gov (United States)

Kolpan, Katharine E; Warren, Michael

2017-12-01

This paper highlights how Geographic Information Systems (GIS) can be utilized to analyze biases and patterns related to physical and cultural geography in Florida. Using case recovery locations from the C. Addison Pound Human Identification Laboratory (CAPHIL), results indicate that the majority of CAPHIL cases are recovered from urban areas with medium to low population density and low rates of crime. The results also suggest that more accurate record keeping methods would enhance the data. Copyright © 2017 Elsevier B.V. All rights reserved.

Histopathology of lung disease in the connective tissue diseases.

Science.gov (United States)

Vivero, Marina; Padera, Robert F

2015-05-01

The pathologic correlates of interstitial lung disease (ILD) secondary to connective tissue disease (CTD) comprise a diverse group of histologic patterns. Lung biopsies in patients with CTD-associated ILD tend to demonstrate simultaneous involvement of multiple anatomic compartments of the lung. Certain histologic patterns tend to predominate in each defined CTD, and it is possible in many cases to confirm connective tissue-associated lung disease and guide patient management using surgical lung biopsy. This article will cover the pulmonary pathologies seen in rheumatoid arthritis, systemic sclerosis, myositis, systemic lupus erythematosus, Sjögren syndrome, and mixed CTD. Copyright © 2015 Elsevier Inc. All rights reserved.

Analyzing Unsaturated Flow Patterns in Fractured Rock Using an Integrated Modeling Approach

International Nuclear Information System (INIS)

Y.S. Wu; G. Lu; K. Zhang; L. Pan; G.S. Bodvarsson

2006-01-01

Characterizing percolation patterns in unsaturated fractured rock has posed a greater challenge to modeling investigations than comparable saturated zone studies, because of the heterogeneous nature of unsaturated media and the great number of variables impacting unsaturated flow. This paper presents an integrated modeling methodology for quantitatively characterizing percolation patterns in the unsaturated zone of Yucca Mountain, Nevada, a proposed underground repository site for storing high-level radioactive waste. The modeling approach integrates a wide variety of moisture, pneumatic, thermal, and isotopic geochemical field data into a comprehensive three-dimensional numerical model for modeling analyses. It takes into account the coupled processes of fluid and heat flow and chemical isotopic transport in Yucca Mountain's highly heterogeneous, unsaturated fractured tuffs. Modeling results are examined against different types of field-measured data and then used to evaluate different hydrogeological conceptualizations and their results of flow patterns in the unsaturated zone. In particular, this model provides a much clearer understanding of percolation patterns and flow behavior through the unsaturated zone, both crucial issues in assessing repository performance. The integrated approach for quantifying Yucca Mountain's flow system is demonstrated to provide a practical modeling tool for characterizing flow and transport processes in complex subsurface systems

When is connectivity important? A case study of the spatial pattern of sudden oak death

Science.gov (United States)

A. Ellis; T. Vaclavik; R.K. Meentemeyer

2010-01-01

Although connectivity has been examined from many different angles and in many ecological disciplines, few studies have tested in which systems and under what conditions connectivity is important in determining ecological dynamics. Identifying general rules governing when connectivity is important is crucial not only for basic ecology, but also for our ability to...

Global imprint of historical connectivity on freshwater fish biodiversity

OpenAIRE

Dias, M. S.; Oberdorff, Thierry; Hugueny, Bernard; Leprieur, F.; Jézéquel, Céline; Cornu, Jean-François; Brosse, S.; Grenouillet, G.; Tedesco, Pablo

2014-01-01

The relative importance of contemporary and historical processes is central for understanding biodiversity patterns. While several studies show that past conditions can partly explain the current biodiversity patterns, the role of history remains elusive. We reconstructed palaeo-drainage basins under lower sea level conditions (Last Glacial Maximum) to test whether the historical connectivity between basins left an imprint on the global patterns of freshwater fish biodiversity. After controll...

State-Dependent Differences in Functional Connectivity in Young Children With Autism Spectrum Disorder

Directory of Open Access Journals (Sweden)

Ashura W. Buckley

2015-12-01

Interpretation: Functional connectivity is distinctly different in children with autism compared to samples with typical development and developmental delay without autism. Differences in connectivity in autism are state and region related. In this study, children with autism were characterized by a dynamically evolving pattern of altered connectivity.

An adopter-centric approach to analyze the diffusion patterns of innovative residential heating systems in Sweden

International Nuclear Information System (INIS)

Mahapatra, Krushna; Gustavsson, Leif

2008-01-01

Innovation and diffusion of renewable energy technologies play a major role in mitigation of climate change. In Sweden replacing electric and oil heating systems with innovative heating systems such as district heating, heat pumps and wood pellet boilers in detached homes is a significant mitigation option. Using an adopter-centric approach, we analyzed the influence of investment subsidy on conversion of resistance heaters and oil boilers, and the variation in diffusion pattern of district heating, heat pumps and pellet boilers in Swedish detached homes. Results from questionnaire surveys of 1500 randomly selected homeowners in September 2004 and January 2007 showed that more than 80% of the respondents did not intend to install a new heating system. Hence, about 37% of the homeowners still have electric and oil heating systems. The government investment subsidy was important for conversion from a resistance heater, but not from an oil boiler. This is because homeowners currently replacing their oil boilers are the laggards, while those replacing resistance heaters are the 'early adopters'. Economic aspects and functional reliability were the most important factors for the homeowners when considering a new heating system. There is a variation in the perceived advantages associated with each of the innovative heating systems and therefore, the diffusion patterns of such systems vary. Installers and interpersonal sources were the most important communication channels for information on heating systems

An adopter-centric approach to analyze the diffusion patterns of innovative residential heating systems in Sweden

Energy Technology Data Exchange (ETDEWEB)

Mahapatra, Krushna; Gustavsson, Leif [Ecotechnology, Mid Sweden University, 831 25 Oestersund (Sweden)

2008-02-15

Innovation and diffusion of renewable energy technologies play a major role in mitigation of climate change. In Sweden replacing electric and oil heating systems with innovative heating systems such as district heating, heat pumps and wood pellet boilers in detached homes is a significant mitigation option. Using an adopter-centric approach, we analyzed the influence of investment subsidy on conversion of resistance heaters and oil boilers, and the variation in diffusion pattern of district heating, heat pumps and pellet boilers in Swedish detached homes. Results from questionnaire surveys of 1500 randomly selected homeowners in September 2004 and January 2007 showed that more than 80% of the respondents did not intend to install a new heating system. Hence, about 37% of the homeowners still have electric and oil heating systems. The government investment subsidy was important for conversion from a resistance heater, but not from an oil boiler. This is because homeowners currently replacing their oil boilers are the laggards, while those replacing resistance heaters are the 'early adopters'. Economic aspects and functional reliability were the most important factors for the homeowners when considering a new heating system. There is a variation in the perceived advantages associated with each of the innovative heating systems and therefore, the diffusion patterns of such systems vary. Installers and interpersonal sources were the most important communication channels for information on heating systems. (author)

Connected versus Mainstreamed. Politicized or de-politicized?

Directory of Open Access Journals (Sweden)

Iria Puyosa

2012-02-01

Full Text Available In our research line about changes in the Venezuelans' political culture in the context of the information society, we are progressing on the characterization of the mass media and the Internet usage dynamics. The model hypothesize the existence of four political culture types, 1 citizens integrated by personal or familial bonds; 2 citizens integrated by ideology ; 3 citizens instrumentally rational ; and 4 citizens socially rational. The current study focuses on the usage of mass media and Internet in relationship with political views. Data come from a survey conducted using a telephone database to collect responses from a representative sample of the Venezuelan registered for vote population. Data was analyzed using the 2-step cluster analysis technique. Results are consistent with the hypothesis of the four political culture types, on regard as mass media and the Internet usage patterns. Cases grouped into four clusters defined by Internet connection and politics information preferences.

Heteroassociative storage of hippocampal pattern sequences in the CA3 subregion

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Raphael Y. de Camargo

2018-01-01

Full Text Available Background Recent research suggests that the CA3 subregion of the hippocampus has properties of both autoassociative network, due to its ability to complete partial cues, tolerate noise, and store associations between memories, and heteroassociative one, due to its ability to store and retrieve sequences of patterns. Although there are several computational models of the CA3 as an autoassociative network, more detailed evaluations of its heteroassociative properties are missing. Methods We developed a model of the CA3 subregion containing 10,000 integrate-and-fire neurons with both recurrent excitatory and inhibitory connections, and which exhibits coupled oscillations in the gamma and theta ranges. We stored thousands of pattern sequences using a heteroassociative learning rule with competitive synaptic scaling. Results We showed that a purely heteroassociative network model can (i retrieve pattern sequences from partial cues with external noise and incomplete connectivity, (ii achieve homeostasis regarding the number of connections per neuron when many patterns are stored when using synaptic scaling, (iii continuously update the set of retrievable patterns, guaranteeing that the last stored patterns can be retrieved and older ones can be forgotten. Discussion Heteroassociative networks with synaptic scaling rules seem sufficient to achieve many desirable features regarding connectivity homeostasis, pattern sequence retrieval, noise tolerance and updating of the set of retrievable patterns.

Influence of biological factors on connectivity patterns for Concholepas concholepas (loco) in Chile

OpenAIRE

Garavelli, L.; Colas, F.; Verley, Philippe; Kaplan, David; Yannicelli, B.; Lett, Christophe

2016-01-01

International audience; In marine benthic ecosystems, larval connectivity is a major process influencing the maintenance and distribution of invertebrate populations. Larval connectivity is a complex process to study as it is determined by several interacting factors. Here we use an individual-based, biophysical model, to disentangle the effects of such factors, namely larval vertical migration , larval growth, larval mortality, adults fecundity, and habitat availability, for the marine gastr...

EXPERIMENTAL STUDY AND PERFORMANCE OF SOLAR ENERGY SYSTEM WITH GRID CONNECTED POWER SUPPLY

OpenAIRE

Pradeep Bharti; Dr. A.K.Sharma

2017-01-01

In this paper , we are analyzed about the solar power with grid connection using of various component such as PV Cells battery inverter, and grid power connection , in this way we are connected the grid power and solar power , after that finally we are analyzed the power quality of output with the help of various devices.

Structural Connectivity of the Developing Human Amygdala

Science.gov (United States)

Saygin, Zeynep M.; Osher, David E.; Koldewyn, Kami; Martin, Rebecca E.; Finn, Amy; Saxe, Rebecca; Gabrieli, John D.E.; Sheridan, Margaret

2015-01-01

A large corpus of research suggests that there are changes in the manner and degree to which the amygdala supports cognitive and emotional function across development. One possible basis for these developmental differences could be the maturation of amygdalar connections with the rest of the brain. Recent functional connectivity studies support this conclusion, but the structural connectivity of the developing amygdala and its different nuclei remains largely unstudied. We examined age related changes in the DWI connectivity fingerprints of the amygdala to the rest of the brain in 166 individuals of ages 5-30. We also developed a model to predict age based on individual-subject amygdala connectivity, and identified the connections that were most predictive of age. Finally, we segmented the amygdala into its four main nucleus groups, and examined the developmental changes in connectivity for each nucleus. We observed that with age, amygdalar connectivity becomes increasingly sparse and localized. Age related changes were largely localized to the subregions of the amygdala that are implicated in social inference and contextual memory (the basal and lateral nuclei). The central nucleus’ connectivity also showed differences with age but these differences affected fewer target regions than the basal and lateral nuclei. The medial nucleus did not exhibit any age related changes. These findings demonstrate increasing specificity in the connectivity patterns of amygdalar nuclei across age. PMID:25875758

Connectivity to the surface determines diversity patterns in subsurface aquifers of the Fennoscandian shield.

Science.gov (United States)

Hubalek, Valerie; Wu, Xiaofen; Eiler, Alexander; Buck, Moritz; Heim, Christine; Dopson, Mark; Bertilsson, Stefan; Ionescu, Danny

2016-10-01

Little research has been conducted on microbial diversity deep under the Earth's surface. In this study, the microbial communities of three deep terrestrial subsurface aquifers were investigated. Temporal community data over 6 years revealed that the phylogenetic structure and community dynamics were highly dependent on the degree of isolation from the earth surface biomes. The microbial community at the shallow site was the most dynamic and was dominated by the sulfur-oxidizing genera Sulfurovum or Sulfurimonas at all-time points. The microbial community in the meteoric water filled intermediate aquifer (water turnover approximately every 5 years) was less variable and was dominated by candidate phylum OD1. Metagenomic analysis of this water demonstrated the occurrence of key genes for nitrogen and carbon fixation, sulfate reduction, sulfide oxidation and fermentation. The deepest water mass (5000 year old waters) had the lowest taxon richness and surprisingly contained Cyanobacteria. The high relative abundance of phylogenetic groups associated with nitrogen and sulfur cycling, as well as fermentation implied that these processes were important in these systems. We conclude that the microbial community patterns appear to be shaped by the availability of energy and nutrient sources via connectivity to the surface or from deep geological processes.

Independent working place on the base of the DVK-2M computer and UNO-4096 analyzer

International Nuclear Information System (INIS)

Zajtsev, M.Yu.; Balandin, A.F.

1987-01-01

Independent working place on the base of the DVK-2M microcomputer and UNO-4096-90 analyzer, designated for investigations of the field of reactor and protection physics is described. Two ways of the analyzer connection with the DVK-2M microcomputer are suggested : by means of CAMAC system or direct connection of UNO-analyzer with the DVK-2M processor

Quantifying indices of short- and long-range white matter connectivity at each cortical vertex.

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Maria Carmela Padula

Full Text Available Several neurodevelopmental diseases are characterized by impairments in cortical morphology along with altered white matter connectivity. However, the relationship between these two measures is not yet clear. In this study, we propose a novel methodology to compute and display metrics of white matter connectivity at each cortical point. After co-registering the extremities of the tractography streamlines with the cortical surface, we computed two measures of connectivity at each cortical vertex: the mean tracts' length, and the proportion of short- and long-range connections. The proposed measures were tested in a clinical sample of 62 patients with 22q11.2 deletion syndrome (22q11DS and 57 typically developing individuals. Using these novel measures, we achieved a fine-grained visualization of the white matter connectivity patterns at each vertex of the cortical surface. We observed an intriguing pattern of both increased and decreased short- and long-range connectivity in 22q11DS, that provides novel information about the nature and topology of white matter alterations in the syndrome. We argue that the method presented in this study opens avenues for additional analyses of the relationship between cortical properties and patterns of underlying structural connectivity, which will help clarifying the intrinsic mechanisms that lead to altered brain structure in neurodevelopmental disorders.

Globalization, Mobility and Air Connectivity Analysis: a Tool for Interdisciplinary Practice

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Juan Antonio Córdoba Ordóñez

2012-10-01

Full Text Available This paper explores the interconnected relationship between Geography and Social Anthropology in the study of social and spatial phenomena. It argues that the informed and combined use of quantitative and qualitative research techniques, like air connectivity analysis and ethnographic fieldwork, are fundamental in the understanding of socioeconomic globalization processes, and particularly in those characterized by mobility. The study of air mobility in Mexico highlights the existence of multi-scalar and multi-functional patterns of relations that are vital to explain the situated dynamics of the social and territorial relations that have followed the country’s adoption of neoliberal policies. And specifically, to analyze processes as regional adjustments, labour migration, tourism, development and underdevelopment, spatial fixation, as well as homogenization and cultural hybridization.

Attractor neural networks with resource-efficient synaptic connectivity

Science.gov (United States)

Pehlevan, Cengiz; Sengupta, Anirvan

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

Altered Functional Connectivity of Insular Subregions in Alzheimer’s Disease

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Xingyun Liu

2018-04-01

Full Text Available Recent researches have demonstrated that the insula is the crucial hub of the human brain networks and most vulnerable region of Alzheimer’s disease (AD. However, little is known about the changes of functional connectivity of insular subregions in the AD patients. In this study, we collected resting-state functional magnetic resonance imaging (fMRI data including 32 AD patients and 38 healthy controls (HCs. By defining three subregions of insula, we mapped whole-brain resting-state functional connectivity (RSFC and identified several distinct RSFC patterns of the insular subregions: For positive connectivity, three cognitive-related RSFC patterns were identified within insula that suggest anterior-to-posterior functional subdivisions: (1 an dorsal anterior zone of the insula that exhibits RSFC with executive control network (ECN; (2 a ventral anterior zone of insula, exhibits functional connectivity with the salience network (SN; (3 a posterior zone along the insula exhibits functional connectivity with the sensorimotor network (SMN. In addition, we found significant negative connectivities between the each insular subregion and several special default mode network (DMN regions. Compared with controls, the AD patients demonstrated distinct disruption of positive RSFCs in the different network (ECN and SMN, suggesting the impairment of the functional integrity. There were no differences of the positive RSFCs in the SN between the two groups. On the other hand, several DMN regions showed increased negative RSFCs to the sub-region of insula in the AD patients, indicating compensatory plasticity. Furthermore, these abnormal insular subregions RSFCs are closely correlated with cognitive performances in the AD patients. Our findings suggested that different insular subregions presented distinct RSFC patterns with various functional networks, which are differently affected in the AD patients.

Discriminative analysis of Parkinson's disease based on whole-brain functional connectivity.

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Yongbin Chen

Full Text Available Recently, there has been an increasing emphasis on applications of pattern recognition and neuroimaging techniques in the effective and accurate diagnosis of psychiatric or neurological disorders. In the present study, we investigated the whole-brain resting-state functional connectivity patterns of Parkinson's disease (PD, which are expected to provide additional information for the clinical diagnosis and treatment of this disease. First, we computed the functional connectivity between each pair of 116 regions of interest derived from a prior atlas. The most discriminative features based on Kendall tau correlation coefficient were then selected. A support vector machine classifier was employed to classify 21 PD patients with 26 demographically matched healthy controls. This method achieved a classification accuracy of 93.62% using leave-one-out cross-validation, with a sensitivity of 90.47% and a specificity of 96.15%. The majority of the most discriminative functional connections were located within or across the default mode, cingulo-opercular and frontal-parietal networks and the cerebellum. These disease-related resting-state network alterations might play important roles in the pathophysiology of this disease. Our results suggest that analyses of whole-brain resting-state functional connectivity patterns have the potential to improve the clinical diagnosis and treatment evaluation of PD.

Modelling fast spreading patterns of airborne infectious diseases using complex networks

Science.gov (United States)

Brenner, Frank; Marwan, Norbert; Hoffmann, Peter

2017-04-01

The pandemics of SARS (2002/2003) and H1N1 (2009) have impressively shown the potential of epidemic outbreaks of infectious diseases in a world that is strongly connected. Global air travelling established an easy and fast opportunity for pathogens to migrate globally in only a few days. This made epidemiological prediction harder. By understanding this complex development and its link to climate change we can suggest actions to control a part of global human health affairs. In this study we combine the following data components to simulate the outbreak of an airborne infectious disease that is directly transmitted from human to human: em{Global Air Traffic Network (from openflights.org) with information on airports, airport location, direct flight connection, airplane type} em{Global population dataset (from SEDAC, NASA)} em{Susceptible-Infected-Recovered (SIR) compartmental model to simulate disease spreading in the vicinity of airports. A modified Susceptible-Exposed-Infected-Recovered (SEIR) model to analyze the impact of the incubation period.} em{WATCH-Forcing-Data-ERA-Interim (WFDEI) climate data: temperature, specific humidity, surface air pressure, and water vapor pressure} These elements are implemented into a complex network. Nodes inside the network represent airports. Each single node is equipped with its own SIR/SEIR compartmental model with node specific attributes. Edges between those nodes represent direct flight connections that allow infected individuals to move between linked nodes. Therefore the interaction of the set of unique SIR models creates the model dynamics we will analyze. To better figure out the influence on climate change on disease spreading patterns, we focus on Influenza-like-Illnesses (ILI). The transmission rate of ILI has a dependency on climate parameters like humidity and temperature. Even small changes of environmental variables can trigger significant differences in the global outbreak behavior. Apart from the direct

Bipolar Cell-Photoreceptor Connectivity in the Zebrafish (Danio rerio) Retina

Science.gov (United States)

Li, Yong N.; Tsujimura, Taro; Kawamura, Shoji; Dowling, John E.

2013-01-01

Bipolar cells convey luminance, spatial and color information from photoreceptors to amacrine and ganglion cells. We studied the photoreceptor connectivity of 321 bipolar cells in the adult zebrafish retina. 1,1'-Dioctadecyl-3,3,3',3'-tetramethylindocarbocyanine perchlorate (DiI) was inserted into whole-mounted transgenic zebrafish retinas to label bipolar cells. The photoreceptors that connect to these DiI-labeled cells were identified by transgenic fluorescence or their positions relative to the fluorescent cones, as cones are arranged in a highly-ordered mosaic: rows of alternating blue- (B) and ultraviolet-sensitive (UV) single cones alternate with rows of red- (R) and green-sensitive (G) double cones. Rod terminals intersperse among cone terminals. As many as 18 connectivity subtypes were observed, 9 of which – G, GBUV, RG, RGB, RGBUV, RGRod, RGBRod, RGBUVRod and RRod bipolar cells – accounted for 96% of the population. Based on their axon terminal stratification, these bipolar cells could be further sub-divided into ON, OFF, and ON-OFF cells. The dendritic spread size, soma depth and size, and photoreceptor connections of the 308 bipolar cells within the 9 common connectivity subtypes were determined, and their dendritic tree morphologies and axonal stratification patterns compared. We found that bipolar cells with the same axonal stratification patterns could have heterogeneous photoreceptor connectivity whereas bipolar cells with the same dendritic tree morphology usually had the same photoreceptor connectivity, although their axons might stratify on different levels. PMID:22907678

Functional magnetic resonance imaging in disorders of consciousness: preliminary results of an innovative analysis of brain connectivity.

Science.gov (United States)

De Pasquale, Francesco; Caravasso, Chiara Falletta; Péran, Patrice; Catani, Sheila; Tuovinen, Noora; Sabatini, Umberto; Formisano, Rita

2015-01-01

The aim of this preliminary study was to present a new approach for connectivity analysis in patients with severe acquired brain injury (ABI) that overcomes some of the difficulties created by anatomical abnormalities due to the brain injury. Using a data-driven approach, resting-state structural MRI (sMRI) and functional MRI (fMRI) data from three severe ABI patients - two with disorders of consciousness (DOC) and one who had recovered consciousness (non-DOC) - were integrated and analyzed. Parameters extracted from the distribution of the connectivity values, such as mean, standard deviation and skeweness, were considered. The distribution parameters estimated seem to provide an accurate multivariate classification of the considered cases that can be summarized as follows: connectivity in the severe ABI patients with DOC was on average lower than in the severe ABI non-DOC patient and healthy subjects. The dispersion of connectivity values of the severe ABI patients, non-DOC and DOC, was comparable, however the shape of the distribution was different in the non-DOC patient. Eventually, seed-based connectivity maps of the default mode Functional magnetic resonance imaging in disorders of consciousness: preliminary results of an innovative analysis of brain connectivity network show a pattern of increasing disruption of this network from the healthy subjects to non-DOC and DOC patients. Consistent results are obtained using an ICA-based approach..

Analyzing the Facebook Friendship Graph

OpenAIRE

Catanese, Salvatore; De Meo, Pasquale; Ferrara, Emilio; Fiumara, Giacomo

2010-01-01

Online Social Networks (OSN) during last years acquired a huge and increasing popularity as one of the most important emerging Web phenomena, deeply modifying the behavior of users and contributing to build a solid substrate of connections and relationships among people using the Web. In this preliminary work paper, our purpose is to analyze Facebook, considering a significant sample of data reflecting relationships among subscribed users. Our goal is to extract, from this platform, relevant ...

Analyzing the multilevel structure of the European airport network

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Oriol Lordan

2017-04-01

Full Text Available The multilayered structure of the European airport network (EAN, composed of connections and flights between European cities, is analyzed through the k-core decomposition of the connections network. This decomposition allows to identify the core, bridge and periphery layers of the EAN. The core layer includes the best-connected cities, which include important business air traffic destinations. The periphery layer includes cities with lesser connections, which serve low populated areas where air travel is an economic alternative. The remaining cities form the bridge of the EAN, including important leisure travel origins and destinations. The multilayered structure of the EAN affects network robustness, as the EAN is more robust to isolation of nodes of the core, than to the isolation of a combination of core and bridge nodes.

CMS Connect

Science.gov (United States)

Balcas, J.; Bockelman, B.; Gardner, R., Jr.; Hurtado Anampa, K.; Jayatilaka, B.; Aftab Khan, F.; Lannon, K.; Larson, K.; Letts, J.; Marra Da Silva, J.; Mascheroni, M.; Mason, D.; Perez-Calero Yzquierdo, A.; Tiradani, A.

2017-10-01

The CMS experiment collects and analyzes large amounts of data coming from high energy particle collisions produced by the Large Hadron Collider (LHC) at CERN. This involves a huge amount of real and simulated data processing that needs to be handled in batch-oriented platforms. The CMS Global Pool of computing resources provide +100K dedicated CPU cores and another 50K to 100K CPU cores from opportunistic resources for these kind of tasks and even though production and event processing analysis workflows are already managed by existing tools, there is still a lack of support to submit final stage condor-like analysis jobs familiar to Tier-3 or local Computing Facilities users into these distributed resources in an integrated (with other CMS services) and friendly way. CMS Connect is a set of computing tools and services designed to augment existing services in the CMS Physics community focusing on these kind of condor analysis jobs. It is based on the CI-Connect platform developed by the Open Science Grid and uses the CMS GlideInWMS infrastructure to transparently plug CMS global grid resources into a virtual pool accessed via a single submission machine. This paper describes the specific developments and deployment of CMS Connect beyond the CI-Connect platform in order to integrate the service with CMS specific needs, including specific Site submission, accounting of jobs and automated reporting to standard CMS monitoring resources in an effortless way to their users.

Analyzing stakeholders' workshop dialogue for evidence of social learning

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Amanda L. Bentley Brymer

2018-03-01

Full Text Available After much debate and synthesis, social learning scholarship is entering an era of empirical research. Given the range across individual-, network-, and systems-level perspectives and scales, clear documentation of social learning processes is critical for making claims about social learning outcomes and their impacts. Past studies have relied on participant recall and concept maps to document perceptions of social learning process and outcome. Using an individual-centric perspective and importing ideas from communication and psychology on question-answer learning through conversational agents, we contribute an expanded conceptual framework and qualitative analytical strategy for assessing stakeholder dialogue for evidence of social learning. We observed stakeholder dialogue across five workshops coordinated for the Bruneau-Owyhee Sage-Grouse Habitat Project (BOSH in Owyhee County, Idaho, USA. Participants' dialogue was audio recorded, transcribed, and analyzed for cross-case patterns. Deductive and inductive coding techniques were applied to illuminate cognitive, relational, and epistemic dimensions of learning and topics of learning. A key finding supports our inclusion of the epistemic dimension and highlights a need for future research: although some participants articulated epistemic positions, they did not challenge each other to share sources or justify factual claims. These findings align with previous research suggesting that, in addition to considering diversity and representation (who is at the table, we should pay more attention to how participants talk, perhaps prompting specific patterns of speech as we endeavor to draw causal connections between social learning processes and outcomes.

How restructuring river connectivity changes freshwater fish biodiversity and biogeography

Science.gov (United States)

Lynch, Heather L.; Grant, Evan H. Campbell; Muneepeerakul, Rachata; Arunachalam, Muthukumarasamy; Rodriguez-Iturbe, Ignacio; Fagan, William F.

2011-01-01

Interbasin water transfer projects, in which river connectivity is restructured via man-made canals, are an increasingly popular solution to address the spatial mismatch between supply and demand of fresh water. However, the ecological consequences of such restructuring remain largely unexplored, and there are no general theoretical guidelines from which to derive these expectations. River systems provide excellent opportunities to explore how network connectivity shapes habitat occupancy, community dynamics, and biogeographic patterns. We apply a neutral model (which assumes competitive equivalence among species within a stochastic framework) to an empirically derived river network to explore how proposed changes in network connectivity may impact patterns of freshwater fish biodiversity. Without predicting the responses of individual extant species, we find the addition of canals connecting hydrologically isolated river basins facilitates the spread of common species and increases average local species richness without changing the total species richness of the system. These impacts are sensitive to the parameters controlling the spatial scale of fish dispersal, with increased dispersal affording more opportunities for biotic restructuring at the community and landscape scales. Connections between isolated basins have a much larger effect on local species richness than those connecting reaches within a river basin, even when those within-basin reaches are far apart. As a result, interbasin canal projects have the potential for long-term impacts to continental-scale riverine communities.

Predicting clinical symptoms of attention deficit hyperactivity disorder based on temporal patterns between and within intrinsic connectivity networks.

Science.gov (United States)

Wang, Xun-Heng; Jiao, Yun; Li, Lihua

2017-10-24

Attention deficit hyperactivity disorder (ADHD) is a common brain disorder with high prevalence in school-age children. Previously developed machine learning-based methods have discriminated patients with ADHD from normal controls by providing label information of the disease for individuals. Inattention and impulsivity are the two most significant clinical symptoms of ADHD. However, predicting clinical symptoms (i.e., inattention and impulsivity) is a challenging task based on neuroimaging data. The goal of this study is twofold: to build predictive models for clinical symptoms of ADHD based on resting-state fMRI and to mine brain networks for predictive patterns of inattention and impulsivity. To achieve this goal, a cohort of 74 boys with ADHD and a cohort of 69 age-matched normal controls were recruited from the ADHD-200 Consortium. Both structural and resting-state fMRI images were obtained for each participant. Temporal patterns between and within intrinsic connectivity networks (ICNs) were applied as raw features in the predictive models. Specifically, sample entropy was taken asan intra-ICN feature, and phase synchronization (PS) was used asan inter-ICN feature. The predictive models were based on the least absolute shrinkage and selectionator operator (LASSO) algorithm. The performance of the predictive model for inattention is r=0.79 (p<10 -8 ), and the performance of the predictive model for impulsivity is r=0.48 (p<10 -8 ). The ICN-related predictive patterns may provide valuable information for investigating the brain network mechanisms of ADHD. In summary, the predictive models for clinical symptoms could be beneficial for personalizing ADHD medications. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Passivity Enhancement in RES Based Power Plant with Paralleled Grid-Connected Inverters

DEFF Research Database (Denmark)

Bai, Haofeng; Wang, Xiongfei; Blaabjerg, Frede

2016-01-01

Harmonic instability is threatening the operation of power plants with multiple grid connected converters in parallel. To analyze and improve the stability of the grid connected converters, the passivity of the output admittance converters is first analyzed in this paper. It is shown that the non-passivity...

How do dispersal costs and habitat selection influence realized population connectivity?

Science.gov (United States)

Burgess, Scott C; Treml, Eric A; Marshall, Dustin J

2012-06-01

Despite the importance of dispersal for population connectivity, dispersal is often costly to the individual. A major impediment to understanding connectivity has been a lack of data combining the movement of individuals and their survival to reproduction in the new habitat (realized connectivity). Although mortality often occurs during dispersal (an immediate cost), in many organisms costs are paid after dispersal (deferred costs). It is unclear how such deferred costs influence the mismatch between dispersal and realized connectivity. Through a series of experiments in the field and laboratory, we estimated both direct and indirect deferred costs in a marine bryozoan (Bugula neritina). We then used the empirical data to parameterize a theoretical model in order to formalize predictions about how dispersal costs influence realized connectivity. Individuals were more likely to colonize poor-quality habitat after prolonged dispersal durations. Individuals that colonized poor-quality habitat performed poorly after colonization because of some property of the habitat (an indirect deferred cost) rather than from prolonged dispersal per se (a direct deferred cost). Our theoretical model predicted that indirect deferred costs could result in nonlinear mismatches between spatial patterns of potential and realized connectivity. The deferred costs of dispersal are likely to be crucial for determining how well patterns of dispersal reflect realized connectivity. Ignoring these deferred costs could lead to inaccurate predictions of spatial population dynamics.

Connecting the dots: Illusory pattern perception predicts belief in conspiracies and the supernatural.

Science.gov (United States)

van Prooijen, Jan-Willem; Douglas, Karen M; De Inocencio, Clara

2018-04-01

A common assumption is that belief in conspiracy theories and supernatural phenomena are grounded in illusory pattern perception. In the present research we systematically tested this assumption. Study 1 revealed that such irrational beliefs are related to perceiving patterns in randomly generated coin toss outcomes. In Study 2, pattern search instructions exerted an indirect effect on irrational beliefs through pattern perception. Study 3 revealed that perceiving patterns in chaotic but not in structured paintings predicted irrational beliefs. In Study 4, we found that agreement with texts supporting paranormal phenomena or conspiracy theories predicted pattern perception. In Study 5, we manipulated belief in a specific conspiracy theory. This manipulation influenced the extent to which people perceive patterns in world events, which in turn predicted unrelated irrational beliefs. We conclude that illusory pattern perception is a central cognitive mechanism accounting for conspiracy theories and supernatural beliefs.

Connecting the dots: Illusory pattern perception predicts belief in conspiracies and the supernatural

Science.gov (United States)

Douglas, Karen M.; De Inocencio, Clara

2017-01-01

Abstract A common assumption is that belief in conspiracy theories and supernatural phenomena are grounded in illusory pattern perception. In the present research we systematically tested this assumption. Study 1 revealed that such irrational beliefs are related to perceiving patterns in randomly generated coin toss outcomes. In Study 2, pattern search instructions exerted an indirect effect on irrational beliefs through pattern perception. Study 3 revealed that perceiving patterns in chaotic but not in structured paintings predicted irrational beliefs. In Study 4, we found that agreement with texts supporting paranormal phenomena or conspiracy theories predicted pattern perception. In Study 5, we manipulated belief in a specific conspiracy theory. This manipulation influenced the extent to which people perceive patterns in world events, which in turn predicted unrelated irrational beliefs. We conclude that illusory pattern perception is a central cognitive mechanism accounting for conspiracy theories and supernatural beliefs. PMID:29695889

Axial displacement of external and internal implant-abutment connection evaluated by linear mixed model analysis.

Science.gov (United States)

Seol, Hyon-Woo; Heo, Seong-Joo; Koak, Jai-Young; Kim, Seong-Kyun; Kim, Shin-Koo

2015-01-01

To analyze the axial displacement of external and internal implant-abutment connection after cyclic loading. Three groups of external abutments (Ext group), an internal tapered one-piece-type abutment (Int-1 group), and an internal tapered two-piece-type abutment (Int-2 group) were prepared. Cyclic loading was applied to implant-abutment assemblies at 150 N with a frequency of 3 Hz. The amount of axial displacement, the Periotest values (PTVs), and the removal torque values(RTVs) were measured. Both a repeated measures analysis of variance and pattern analysis based on the linear mixed model were used for statistical analysis. Scanning electron microscopy (SEM) was used to evaluate the surface of the implant-abutment connection. The mean axial displacements after 1,000,000 cycles were 0.6 μm in the Ext group, 3.7 μm in the Int-1 group, and 9.0 μm in the Int-2 group. Pattern analysis revealed a breakpoint at 171 cycles. The Ext group showed no declining pattern, and the Int-1 group showed no declining pattern after the breakpoint (171 cycles). However, the Int-2 group experienced continuous axial displacement. After cyclic loading, the PTV decreased in the Int-2 group, and the RTV decreased in all groups. SEM imaging revealed surface wear in all groups. Axial displacement and surface wear occurred in all groups. The PTVs remained stable, but the RTVs decreased after cyclic loading. Based on linear mixed model analysis, the Ext and Int-1 groups' axial displacements plateaued after little cyclic loading. The Int-2 group's rate of axial displacement slowed after 100,000 cycles.

Connecting Leadership and Learning: Do Versatile Learners make Connective Leaders?

OpenAIRE

Jill L. Robinson

2016-01-01

Recent failures in leadership, suggest that creating better-quality leadership development programs is critical. In moving from theory to practice, this paper examined the relationship between learning style and leadership style which may enable us to move away from one-size-fits-all leadership development programs. Utilizing Kolb’s Experiential Learning Model and Connective Leadership theory, approximately 3600 college students were analyzed to discover whether versatility in learning styles...

Connecting leadership and learning: Do versatile learners make connective leaders?

OpenAIRE

Robinson, Jill L.

2016-01-01

Recent failures in leadership, suggest that creating better-quality leadership development programs is critical. In moving from theory to practice, this paper examined the relationship between learning style and leadership style which may enable us to move away from one-size-fits-all leadership development programs. Utilizing Kolb’s Experiential Learning Model and Connective Leadership theory, approximately 3600 college students were analyzed to discover whether versatility in learning styles...

Connecting Leadership and Learning: Do Versatile Learners make Connective Leaders?

OpenAIRE

Jill L. Robinson

2016-01-01

Abstract Recent failures in leadership, suggest that creating better-quality leadership development programs is critical. In moving from theory to practice, this paper examined the relationship between learning style and leadership style which may enable us to move away from one-size-fits-all leadership development programs. Utilizing Kolb’s Experiential Learning Model and Connective Leadership theory, approximately 3600 college students were analyzed to discover whether versatility in le...

Forced phase-locked states and information retrieval in a two-layer network of oscillatory neurons with directional connectivity

International Nuclear Information System (INIS)

Kazantsev, Victor; Pimashkin, Alexey

2007-01-01

We propose two-layer architecture of associative memory oscillatory network with directional interlayer connectivity. The network is capable to store information in the form of phase-locked (in-phase and antiphase) oscillatory patterns. The first (input) layer takes an input pattern to be recognized and their units are unidirectionally connected with all units of the second (control) layer. The connection strengths are weighted using the Hebbian rule. The output (retrieved) patterns appear as forced-phase locked states of the control layer. The conditions are found and analytically expressed for pattern retrieval in response on incoming stimulus. It is shown that the system is capable to recover patterns with a certain level of distortions or noises in their profiles. The architecture is implemented with the Kuramoto phase model and using synaptically coupled neural oscillators with spikes. It is found that the spiking model is capable to retrieve patterns using the spiking phase that translates memorized patterns into the spiking phase shifts at different time scales

Comparing Structural Brain Connectivity by the Infinite Relational Model

DEFF Research Database (Denmark)

Ambrosen, Karen Marie Sandø; Herlau, Tue; Dyrby, Tim

2013-01-01

The growing focus in neuroimaging on analyzing brain connectivity calls for powerful and reliable statistical modeling tools. We examine the Infinite Relational Model (IRM) as a tool to identify and compare structure in brain connectivity graphs by contrasting its performance on graphs from...

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

Science.gov (United States)

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

2014-01-01

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

Patterns of patterns of synchronization: Noise induced attractor switching in rings of coupled nonlinear oscillators

Energy Technology Data Exchange (ETDEWEB)

Emenheiser, Jeffrey [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Physics, University of California, Davis, California 95616 (United States); Chapman, Airlie; Mesbahi, Mehran [William E. Boeing Department of Aeronautics and Astronautics, University of Washington, Seattle, Washington 98195 (United States); Pósfai, Márton [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Computer Science, University of California, Davis, California 95616 (United States); Crutchfield, James P. [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Physics, University of California, Davis, California 95616 (United States); Department of Computer Science, University of California, Davis, California 95616 (United States); Santa Fe Institute, Santa Fe, New Mexico 87501 (United States); D' Souza, Raissa M. [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Computer Science, University of California, Davis, California 95616 (United States); Santa Fe Institute, Santa Fe, New Mexico 87501 (United States); Department of Mechanical and Aerospace Engineering, University of California, Davis, California 95616 (United States)

2016-09-15

Following the long-lived qualitative-dynamics tradition of explaining behavior in complex systems via the architecture of their attractors and basins, we investigate the patterns of switching between distinct trajectories in a network of synchronized oscillators. Our system, consisting of nonlinear amplitude-phase oscillators arranged in a ring topology with reactive nearest-neighbor coupling, is simple and connects directly to experimental realizations. We seek to understand how the multiple stable synchronized states connect to each other in state space by applying Gaussian white noise to each of the oscillators' phases. To do this, we first analytically identify a set of locally stable limit cycles at any given coupling strength. For each of these attracting states, we analyze the effect of weak noise via the covariance matrix of deviations around those attractors. We then explore the noise-induced attractor switching behavior via numerical investigations. For a ring of three oscillators, we find that an attractor-switching event is always accompanied by the crossing of two adjacent oscillators' phases. For larger numbers of oscillators, we find that the distribution of times required to stochastically leave a given state falls off exponentially, and we build an attractor switching network out of the destination states as a coarse-grained description of the high-dimensional attractor-basin architecture.

Age Differences in the Intrinsic Functional Connectivity of Default Network Subsystems

Directory of Open Access Journals (Sweden)

Karen eCampbell

2013-11-01

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

THE DEVELOPMENT OF STREET PATTERNS IN ISRAELI CITIES

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Itzhak OMER

2015-12-01

Full Text Available Street patterns of Israeli cities were investigated by comparing three time periods of urban development: (I the late 19th century until the establishment of the state of Israel in 1948; (II 1948 until the 1980s; and (III the late 1980s until the present. These time periods are related respectively to the pre-modern, modern and late-modern urban planning approach. Representative urban street networks were examined in selected cities by means of morphological analysis of typical street pattern properties: curvature, fragmentation, connectivity, continuity and differentiation. The study results reveal significant differences between the street patterns of the three examined periods in the development of cities in Israel. The results show clearly the gradual trends in the intensification of curvature, fragmentation, complexity and hierarchical organization of street networks as well as the weakening of the network's internal and external connectivity. The implications of these changes on connectivity and spatial integration are discussed with respect to planning approaches.

THE DEVELOPMENT OF STREET PATTERNS IN ISRAELI CITIES

Directory of Open Access Journals (Sweden)

Itzhak OMER

2016-07-01

Full Text Available Street patterns of Israeli cities were investigated by comparing three time periods of urban development: (I the late 19th century until the establishment of the state of Israel in 1948; (II 1948 until the 1980s; and (III the late 1980s until the present. These time periods are related respectively to the pre-modern, modern and late-modern urban planning approach. Representative urban street networks were examined in selected cities by means of morphological analysis of typical street pattern properties: curvature, fragmentation, connectivity, continuity and differentiation. The study results reveal significant differences between the street patterns of the three examined periods in the development of cities in Israel. The results show clearly the gradual trends in the intensification of curvature, fragmentation, complexity and hierarchical organization of street networks as well as the weakening of the network's internal and external connectivity. The implications of these changes on connectivity and spatial integration are discussed with respect to planning approaches.

Consensus clustering approach to group brain connectivity matrices

Directory of Open Access Journals (Sweden)

Javier Rasero

2017-10-01

Full Text Available A novel approach rooted on the notion of consensus clustering, a strategy developed for community detection in complex networks, is proposed to cope with the heterogeneity that characterizes connectivity matrices in health and disease. The method can be summarized as follows: (a define, for each node, a distance matrix for the set of subjects by comparing the connectivity pattern of that node in all pairs of subjects; (b cluster the distance matrix for each node; (c build the consensus network from the corresponding partitions; and (d extract groups of subjects by finding the communities of the consensus network thus obtained. Different from the previous implementations of consensus clustering, we thus propose to use the consensus strategy to combine the information arising from the connectivity patterns of each node. The proposed approach may be seen either as an exploratory technique or as an unsupervised pretraining step to help the subsequent construction of a supervised classifier. Applications on a toy model and two real datasets show the effectiveness of the proposed methodology, which represents heterogeneity of a set of subjects in terms of a weighted network, the consensus matrix.

Estuary-ocean connectivity: fast physics, slow biology.

Science.gov (United States)

Raimonet, Mélanie; Cloern, James E

2017-06-01

Estuaries are connected to both land and ocean so their physical, chemical, and biological dynamics are influenced by climate patterns over watersheds and ocean basins. We explored climate-driven oceanic variability as a source of estuarine variability by comparing monthly time series of temperature and chlorophyll-a inside San Francisco Bay with those in adjacent shelf waters of the California Current System (CCS) that are strongly responsive to wind-driven upwelling. Monthly temperature fluctuations inside and outside the Bay were synchronous, but their correlations weakened with distance from the ocean. These results illustrate how variability of coastal water temperature (and associated properties such as nitrate and oxygen) propagates into estuaries through fast water exchanges that dissipate along the estuary. Unexpectedly, there was no correlation between monthly chlorophyll-a variability inside and outside the Bay. However, at the annual scale Bay chlorophyll-a was significantly correlated with the Spring Transition Index (STI) that sets biological production supporting fish recruitment in the CCS. Wind forcing of the CCS shifted in the late 1990s when the STI advanced 40 days. This shift was followed, with lags of 1-3 years, by 3- to 19-fold increased abundances of five ocean-produced demersal fish and crustaceans and 2.5-fold increase of summer chlorophyll-a in the Bay. These changes reflect a slow biological process of estuary-ocean connectivity operating through the immigration of fish and crustaceans that prey on bivalves, reduce their grazing pressure, and allow phytoplankton biomass to build. We identified clear signals of climate-mediated oceanic variability in this estuary and discovered that the response patterns vary with the process of connectivity and the timescale of ocean variability. This result has important implications for managing nutrient inputs to estuaries connected to upwelling systems, and for assessing their responses to changing

Aberrant Neural Connectivity during Emotional Processing Associated with Posttraumatic Stress.

Science.gov (United States)

Sadeh, Naomi; Spielberg, Jeffrey M; Warren, Stacie L; Miller, Gregory A; Heller, Wendy

2014-11-01

Given the complexity of the brain, characterizing relations among distributed brain regions is likely essential to describing the neural instantiation of posttraumatic stress symptoms. This study examined patterns of functional connectivity among key brain regions implicated in the pathophysiology of posttraumatic stress disorder (PTSD) in 35 trauma-exposed adults using an emotion-word Stroop task. PTSD symptom severity (particularly hyperarousal symptoms) moderated amygdala-mPFC coupling during the processing of unpleasant words, and this moderation correlated positively with reported real-world impairment and amygdala reactivity. Reexperiencing severity moderated hippocampus-insula coupling during pleasant and unpleasant words. Results provide evidence that PTSD symptoms differentially moderate functional coupling during emotional interference and underscore the importance of examining network connectivity in research on PTSD. They suggest that hyperarousal is associated with negative mPFC-amygdala coupling and that reexperiencing is associated with altered insula-hippocampus function, patterns of connectivity that may represent separable indicators of dysfunctional inhibitory control during affective processing.

Disruption of an Evolutionarily Novel Synaptic Expression Pattern in Autism.

Directory of Open Access Journals (Sweden)

Xiling Liu

2016-09-01

Full Text Available Cognitive defects in autism spectrum disorder (ASD include socialization and communication: key behavioral capacities that separate humans from other species. Here, we analyze gene expression in the prefrontal cortex of 63 autism patients and control individuals, as well as 62 chimpanzees and macaques, from natal to adult age. We show that among all aberrant expression changes seen in ASD brains, a single aberrant expression pattern overrepresented in genes involved synaptic-related pathways is enriched in nucleotide variants linked to autism. Furthermore, only this pattern contains an excess of developmental expression features unique to humans, thus resulting in the disruption of human-specific developmental programs in autism. Several members of the early growth response (EGR transcription factor family can be implicated in regulation of this aberrant developmental change. Our study draws a connection between the genetic risk architecture of autism and molecular features of cortical development unique to humans.

Disruption of an Evolutionarily Novel Synaptic Expression Pattern in Autism

Science.gov (United States)

Jiang, Xi; Hu, Haiyang; Guijarro, Patricia; Mitchell, Amanda; Ely, John J.; Sherwood, Chet C.; Hof, Patrick R.; Qiu, Zilong; Pääbo, Svante; Akbarian, Schahram; Khaitovich, Philipp

2016-01-01

Cognitive defects in autism spectrum disorder (ASD) include socialization and communication: key behavioral capacities that separate humans from other species. Here, we analyze gene expression in the prefrontal cortex of 63 autism patients and control individuals, as well as 62 chimpanzees and macaques, from natal to adult age. We show that among all aberrant expression changes seen in ASD brains, a single aberrant expression pattern overrepresented in genes involved synaptic-related pathways is enriched in nucleotide variants linked to autism. Furthermore, only this pattern contains an excess of developmental expression features unique to humans, thus resulting in the disruption of human-specific developmental programs in autism. Several members of the early growth response (EGR) transcription factor family can be implicated in regulation of this aberrant developmental change. Our study draws a connection between the genetic risk architecture of autism and molecular features of cortical development unique to humans. PMID:27685936

Hydrodynamic modeling of hydrologic surface connectivity within a coastal river-floodplain system

Science.gov (United States)

Castillo, C. R.; Guneralp, I.

2017-12-01

Hydrologic surface connectivity (HSC) within river-floodplain environments is a useful indicator of the overall health of riparian habitats because it allows connections amongst components/landforms of the riverine landscape system to be quantified. Overbank flows have traditionally been the focus for analyses concerned with river-floodplain connectivity, but recent works have identified the large significance from sub-bankfull streamflows. Through the use of morphometric analysis and a digital elevation model that is relative to the river water surface, we previously determined that >50% of the floodplain for Mission River on the Coastal Bend of Texas becomes connected to the river at streamflows well-below bankfull conditions. Guided by streamflow records, field-based inundation data, and morphometric analysis; we develop a two-dimensional hydrodynamic model for lower portions of Mission River Floodplain system. This model not only allows us to analyze connections induced by surface water inundation, but also other aspects of the hydrologic connectivity concept such as exchanges of sediment and energy between the river and its floodplain. We also aggregate hydrodynamic model outputs to an object/landform level in order to analyze HSC and associated attributes using measures from graph/network theory. Combining physically-based hydrodynamic models with object-based and graph theoretical analyses allow river-floodplain connectivity to be quantified in a consistent manner with measures/indicators commonly used in landscape analysis. Analyzes similar to ours build towards the establishment of a formal framework for analyzing river-floodplain interaction that will ultimately serve to inform the management of riverine/floodplain environments.

How does farmer connectivity influence livestock genetic structure?

DEFF Research Database (Denmark)

Berthouly, C; Do, Duy Ngoc; Thévenon, S

2009-01-01

Assessing how genes flow across populations is a key component of conservation genetics. Gene flow in a natural population depends on ecological traits and the local environment, whereas for a livestock population, gene flow is driven by human activities. Spatial organization, relationships between...... farmers and their husbandry practices will define the farmer's network and so determine farmer connectivity. It is thus assumed that farmer connectivity will affect the genetic structure of their livestock. To test this hypothesis, goats reared by four different ethnic groups in a Vietnamese province were......, ethnicity and husbandry practices. In this study, we clearly linked the livestock genetic pattern to farmer connectivity and showed the importance of taking into account spatial information in genetic studies....

How Analysts Cognitively “Connect the Dots”

Energy Technology Data Exchange (ETDEWEB)

Bradel, Lauren; Self, Jessica S.; Endert, Alexander; Hossain, Shahriar M.; North, Chris; Ramakrishnan, Naren

2013-06-04

As analysts attempt to make sense of a collection of documents, such as intelligence analysis reports, they may wish to “connect the dots” between pieces of information that may initially seem unrelated. This process of synthesizing information between information requires users to make connections between pairs of documents, creating a conceptual story. We conducted a user study to analyze the process by which users connect pairs of documents and how they spatially arrange information. Users created conceptual stories that connected the dots using organizational strategies that ranged in complexity. We propose taxonomies for cognitive connections and physical structures used when trying to “connect the dots” between two documents. We compared the user-created stories with a data-mining algorithm that constructs chains of documents using co-occurrence metrics. Using the insight gained into the storytelling process, we offer design considerations for the existing data mining algorithm and corresponding tools to combine the power of data mining and the complex cognitive processing of analysts.

Is functional brain connectivity atypical in autism? A systematic review of EEG and MEG studies.

Directory of Open Access Journals (Sweden)

Christian O'Reilly

Full Text Available Although it is well recognized that autism is associated with altered patterns of over- and under-connectivity, specifics are still a matter of debate. Little has been done so far to synthesize available literature using whole-brain electroencephalography (EEG and magnetoencephalography (MEG recordings.1 To systematically review the literature on EEG/MEG functional and effective connectivity in autism spectrum disorder (ASD, 2 to synthesize and critically appraise findings related with the hypothesis that ASD is characterized by long-range underconnectivity and local overconnectivity, and 3 to provide, based on the literature, an analysis of tentative factors that are likely to mediate association between ASD and atypical connectivity (e.g., development, topography, lateralization.Literature reviews were done using PubMed and PsychInfo databases. Abstracts were screened, and only relevant articles were analyzed based on the objectives of this paper. Special attention was paid to the methodological characteristics that could have created variability in outcomes reported between studies.Our synthesis provides relatively strong support for long-range underconnectivity in ASD, whereas the status of local connectivity remains unclear. This observation was also mirrored by a similar relationship with lower frequencies being often associated with underconnectivity and higher frequencies being associated with both under- and over-connectivity. Putting together these observations, we propose that ASD is characterized by a general trend toward an under-expression of lower-band wide-spread integrative processes compensated by more focal, higher-frequency, locally specialized, and segregated processes. Further investigation is, however, needed to corroborate the conclusion and its generalizability across different tasks. Of note, abnormal lateralization in ASD, specifically an elevated left-over-right EEG and MEG functional connectivity ratio, has been also

Patterns of brain structural connectivity differentiate normal weight from overweight subjects

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Arpana Gupta

2015-01-01

Conclusions: 1. An increased BMI (i.e., overweight subjects is associated with distinct changes in gray-matter and fiber density of the brain. 2. Classification algorithms based on white-matter connectivity involving regions of the reward and associated networks can identify specific targets for mechanistic studies and future drug development aimed at abnormal ingestive behavior and in overweight/obesity.

Slowly evolving connectivity in recurrent neural networks: I. The extreme dilution regime

International Nuclear Information System (INIS)

Wemmenhove, B; Skantzos, N S; Coolen, A C C

2004-01-01

We study extremely diluted spin models of neural networks in which the connectivity evolves in time, although adiabatically slowly compared to the neurons, according to stochastic equations which on average aim to reduce frustration. The (fast) neurons and (slow) connectivity variables equilibrate separately, but at different temperatures. Our model is exactly solvable in equilibrium. We obtain phase diagrams upon making the condensed ansatz (i.e. recall of one pattern). These show that, as the connectivity temperature is lowered, the volume of the retrieval phase diverges and the fraction of mis-aligned spins is reduced. Still one always retains a region in the retrieval phase where recall states other than the one corresponding to the 'condensed' pattern are locally stable, so the associative memory character of our model is preserved

Repetitive tactile stimulation changes resting-state functional connectivity – implications for treatment of sensorimotor decline

Directory of Open Access Journals (Sweden)

Frank eFreyer

2012-05-01

Full Text Available Neurological disorders and physiological aging can lead to a decline of perceptual abilities. In contrast to the conventional therapeutic approach that comprises intensive training and practicing, passive repetitive sensory stimulation (RSS has recently gained increasing attention as an alternative to countervail the sensory decline by improving perceptual abilities without the need of active participation. A particularly effective type of high-frequency RSS, utilizing Hebbian learning principles, improves perceptual acuity as well as sensorimotor functions and has been successfully applied to treat chronic stroke patients and elderly subjects. High-frequency RSS has been shown to induce plastic changes of somatosensory cortex such as representational map reorganization, but its impact on the brain’s ongoing network activity and resting-state functional connectivity has not been investigated so far. Here, we applied high-frequency RSS in healthy human subjects and analyzed resting state Electroencephalography (EEG functional connectivity patterns before and after RSS by means of imaginary coherency (ImCoh, a frequency-specific connectivity measure which is known to reduce overestimation biases due to volume conduction and common reference. Thirty minutes of passive high-frequency RSS lead to significant ImCoh-changes of the resting state mu-rhythm in the individual upper alpha frequency band within distributed sensory and motor cortical areas. These stimulation induced distributed functional connectivity changes likely underlie the previously observed improvement in sensorimotor integration.

Hyponymy Patterns in Romanian

Directory of Open Access Journals (Sweden)

Verginica Barbu Mititelu

2011-10-01

Full Text Available Hyponymy is a lexical-semantic relation that has been studied in Romanian linguistics only occasionally and almost exclusively in connection to other relations. However, for computational engineers it offers a very effective way of organizing the lexical material useful in many applications involving Natural Language Processing. In this paper we present two methods of identifying Romanian hyponymy patterns, their results and evaluation; we also envisage the applicability of these patterns and future work

Population Connectivity Measures of Fishery-Targeted Coral Reef Species to Inform Marine Reserve Network Design in Fiji.

Science.gov (United States)

Eastwood, Erin K; López, Elora H; Drew, Joshua A

2016-01-25

Coral reef fish serve as food sources to coastal communities worldwide, yet are vulnerable to mounting anthropogenic pressures like overfishing and climate change. Marine reserve networks have become important tools for mitigating these pressures, and one of the most critical factors in determining their spatial design is the degree of connectivity among different populations of species prioritized for protection. To help inform the spatial design of an expanded reserve network in Fiji, we used rapidly evolving mitochondrial genes to investigate connectivity patterns of three coral reef species targeted by fisheries in Fiji: Epinephelus merra (Serranidae), Halichoeres trimaculatus (Labridae), and Holothuria atra (Holothuriidae). The two fish species, E. merra and Ha. trimaculatus, exhibited low genetic structuring and high amounts of gene flow, whereas the sea cucumber Ho. atra displayed high genetic partitioning and predominantly westward gene flow. The idiosyncratic patterns observed among these species indicate that patterns of connectivity in Fiji are likely determined by a combination of oceanographic and ecological characteristics. Our data indicate that in the cases of species with high connectivity, other factors such as representation or political availability may dictate where reserves are placed. In low connectivity species, ensuring upstream and downstream connections is critical.

Topologically convergent and divergent structural connectivity patterns between patients with remitted geriatric depression and amnestic mild cognitive impairment.

Science.gov (United States)

Bai, Feng; Shu, Ni; Yuan, Yonggui; Shi, Yongmei; Yu, Hui; Wu, Di; Wang, Jinhui; Xia, Mingrui; He, Yong; Zhang, Zhijun

2012-03-21

Alzheimer's disease (AD) can be conceptualized as a disconnection syndrome. Both remitted geriatric depression (RGD) and amnestic mild cognitive impairment (aMCI) are associated with a high risk for developing AD. However, little is known about the similarities and differences in the topological patterns of white matter (WM) structural networks between RGD and aMCI. In this study, diffusion tensor imaging and deterministic tractography were used to map the human WM networks of 35 RGD patients, 38 aMCI patients, and 30 healthy subjects. Furthermore, graph theoretical methods were applied to investigate the alterations in the global and regional properties of the WM network in these patients. First, both the RGD and aMCI patients showed abnormal global topology in their WM networks (i.e., reduced network strength, reduced global efficiency, and increased absolute path length) compared with the controls, and there were no significant differences in these global network properties between the patient groups. Second, similar deficits of the regional and connectivity characteristics in the WM networks were primarily found in the frontal brain regions of RGD and aMCI patients compared with the controls, while a different nodal efficiency of the posterior cingulate cortex and several prefrontal brain regions were also observed between the patient groups. Together, our study provides direct evidence for the association of a great majority of convergent and a minority of divergent connectivity of WM structural networks between RGD and aMCI patients, which may lead to increasing attention in defining a population at risk of AD.

Sex-related differences in amygdala functional connectivity during resting conditions.

Science.gov (United States)

Kilpatrick, L A; Zald, D H; Pardo, J V; Cahill, L F

2006-04-01

Recent neuroimaging studies have established a sex-related hemispheric lateralization of amygdala involvement in memory for emotionally arousing material. Here, we examine the possibility that sex-related differences in amygdala involvement in memory for emotional material develop from differential patterns of amygdala functional connectivity evident in the resting brain. Seed voxel partial least square analyses of regional cerebral blood flow data revealed significant sex-related differences in amygdala functional connectivity during resting conditions. The right amygdala was associated with greater functional connectivity in men than in women. In contrast, the left amygdala was associated with greater functional connectivity in women than in men. Furthermore, the regions displaying stronger functional connectivity with the right amygdala in males (sensorimotor cortex, striatum, pulvinar) differed from those displaying stronger functional connectivity with the left amygdala in females (subgenual cortex, hypothalamus). These differences in functional connectivity at rest may link to sex-related differences in medical and psychiatric disorders.

The Functional Organization and Cortical Connections of Motor Cortex in Squirrels

Science.gov (United States)

Cooke, Dylan F.; Padberg, Jeffrey; Zahner, Tony

2012-01-01

Despite extraordinary diversity in the rodent order, studies of motor cortex have been limited to only 2 species, rats and mice. Here, we examine the topographic organization of motor cortex in the Eastern gray squirrel (Sciurus carolinensis) and cortical connections of motor cortex in the California ground squirrel (Spermophilus beecheyi). We distinguish a primary motor area, M1, based on intracortical microstimulation (ICMS), myeloarchitecture, and patterns of connectivity. A sensorimotor area between M1 and the primary somatosensory area, S1, was also distinguished based on connections, functional organization, and myeloarchitecture. We term this field 3a based on similarities with area 3a in nonrodent mammals. Movements are evoked with ICMS in both M1 and 3a in a roughly somatotopic pattern. Connections of 3a and M1 are distinct and suggest the presence of a third far rostral field, termed “F,” possibly involved in motor processing based on its connections. We hypothesize that 3a is homologous to the dysgranular zone (DZ) in S1 of rats and mice. Our results demonstrate that squirrels have both similar and unique features of M1 organization compared with those described in rats and mice, and that changes in 3a/DZ borders appear to have occurred in both lineages. PMID:22021916

Connectivity diagnostics in the Mediterranean obtained from Lagrangian Flow Networks; global patterns, sensitivity and robustness

Science.gov (United States)

Monroy, Pedro; Rossi, Vincent; Ser-Giacomi, Enrico; López, Cristóbal; Hernández-García, Emilio

2017-04-01

Lagrangian Flow Network (LFN) is a modeling framework in which geographical sub-areas of the ocean are represented as nodes in a network and are interconnected by links representing the transport of water, substances or propagules (eggs and larvae) by currents. Here we compute for the surface of the whole Mediterranean basin four connectivity metrics derived from LFN that measure retention and exchange processes, thus providing a systematic characterization of propagule dispersal driven by the ocean circulation. Then we assess the sensitivity and robustness of the results with respect to the most relevant parameters: the density of released particles, the node size (spatial-scales of discretization), the Pelagic Larval Duration (PLD) and the modality of spawning. We find a threshold for the number of particles per node that guarantees reliable values for most of the metrics examined, independently of node size. For our setup, this threshold is 100 particles per node. We also find that the size of network nodes has a non-trivial influence on the spatial variability of both exchange and retention metrics. Although the spatio-temporal fluctuations of the circulation affect larval transport in a complex and unpredictable manner, our analyses evidence how specific biological parametrization impact the robustness of connectivity diagnostics. Connectivity estimates for long PLDs are more robust against biological uncertainties (PLD and spawning date) than for short PLDs. Furthermore, our model suggests that for mass-spawners that release propagules over short periods (≃ 2 to 10 days), daily release must be simulated to properly consider connectivity fluctuations. In contrast, average connectivity estimates for species that spawn repeatedly over longer duration (a few weeks to a few months) remain robust even using longer periodicity (5 to 10 days). Our results give a global view of the surface connectivity of the Mediterranean Sea and have implications for the design of

Cerebro-cerebellar resting state functional connectivity in children and adolescents with autism spectrum disorder

Science.gov (United States)

Khan, Amanda J.; Nair, Aarti; Keown, Christopher L.; Datko, Michael C.; Lincoln, Alan J.; Müller, Ralph-Axel

2017-01-01

Background The cerebellum plays important roles in both sensorimotor and supramodal cognitive functions. Cellular, volumetric, and functional abnormalities of the cerebellum have been found in autism spectrum disorders (ASD), but no comprehensive investigation of cerebro-cerebellar connectivity in ASD is available. Methods We used resting-state functional connectivity MRI in 56 children and adolescents (28 ASD, 28 typically developing [TD]) aged 8–17 years. Partial and total correlation analyses were performed for unilateral regions of interest (ROIs), distinguished in two broad domains as sensorimotor (premotor/primary motor, somatosensory, superior temporal, occipital) and supramodal (prefrontal, posterior parietal, and inferior and middle temporal). Results There were three main findings: (i) Total correlation analyses showed predominant cerebro-cerebellar functional overconnectivity in the ASD group; (ii) partial correlation analyses that emphasized domain-specificity (sensorimotor vs. supramodal) indicated a pattern of robustly increased connectivity in the ASD group (compared to the TD group) for sensorimotor ROIs, but predominantly reduced connectivity for supramodal ROIs; (iii) this atypical pattern of connectivity was supported by significantly increased non-canonical connections (between sensorimotor cerebral and supramodal cerebellar ROIs, and vice versa) in the ASD group. Conclusions Our findings indicate that sensorimotor intrinsic functional connectivity is atypically increased in ASD, at the expense of connectivity supporting cerebellar participation in supramodal cognition. PMID:25959247

Polyhedral patterns

KAUST Repository

Jiang, Caigui

2015-10-27

We study the design and optimization of polyhedral patterns, which are patterns of planar polygonal faces on freeform surfaces. Working with polyhedral patterns is desirable in architectural geometry and industrial design. However, the classical tiling patterns on the plane must take on various shapes in order to faithfully and feasibly approximate curved surfaces. We define and analyze the deformations these tiles must undertake to account for curvature, and discover the symmetries that remain invariant under such deformations. We propose a novel method to regularize polyhedral patterns while maintaining these symmetries into a plethora of aesthetic and feasible patterns.

Directional connectivity in hydrology and ecology

Science.gov (United States)

Larsen, Laurel G.; Choi, Jungyill; Nungesser, Martha K.; Harvey, Judson W.

2012-01-01

subtle differences in the physical-biological feedbacks driving pattern formation. Case-study application of the DCI to the Everglades in south Florida revealed that loss of directional hydrologic connectivity occurs more rapidly and is a more sensitive indicator of declining ecosystem function than other metrics (e.g., habitat area) used previously. Here and elsewhere, directional connectivity can provide insight into landscape drivers and processes, act as an early-warning indicator of environmental degradation, and serve as a planning tool or performance measure for conservation and restoration efforts.

Directional connectivity in hydrology and ecology.

Science.gov (United States)

Larsen, Laurel G; Choi, Jungyill; Nungesser, Martha K; Harvey, Judson W

2012-12-01

subtle differences in the physical-biological feedbacks driving pattern formation. Case-study application of the DCI to the Everglades in south Florida revealed that loss of directional hydrologic connectivity occurs more rapidly and is a more sensitive indicator of declining ecosystem function than other metrics (e.g., habitat area) used previously. Here and elsewhere, directional connectivity can provide insight into landscape drivers and processes, act as an early-warning indicator of environmental degradation, and serve as a planning tool or performance measure for conservation and restoration efforts.

State-Dependent Changes of Connectivity Patterns and Functional Brain Network Topology in Autism Spectrum Disorder

Science.gov (United States)

Barttfeld, Pablo; Wicker, Bruno; Cukier, Sebastian; Navarta, Silvana; Lew, Sergio; Leiguarda, Ramon; Sigman, Mariano

2012-01-01

Anatomical and functional brain studies have converged to the hypothesis that autism spectrum disorders (ASD) are associated with atypical connectivity. Using a modified resting-state paradigm to drive subjects' attention, we provide evidence of a very marked interaction between ASD brain functional connectivity and cognitive state. We show that…

Conservation patterns of HIV-1 RT connection and RNase H domains: identification of new mutations in NRTI-treated patients.

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André F A Santos

Full Text Available BACKGROUND: Although extensive HIV drug resistance information is available for the first 400 amino acids of its reverse transcriptase, the impact of antiretroviral treatment in C-terminal domains of Pol (thumb, connection and RNase H is poorly understood. METHODS AND FINDINGS: We wanted to characterize conserved regions in RT C-terminal domains among HIV-1 group M subtypes and CRF. Additionally, we wished to identify NRTI-related mutations in HIV-1 RT C-terminal domains. We sequenced 118 RNase H domains from clinical viral isolates in Brazil, and analyzed 510 thumb and connection domain and 450 RNase H domain sequences collected from public HIV sequence databases, together with their treatment status and histories. Drug-naïve and NRTI-treated datasets were compared for intra- and inter-group conservation, and differences were determined using Fisher's exact tests. One third of RT C-terminal residues were found to be conserved among group M variants. Three mutations were found exclusively in NRTI-treated isolates. Nine mutations in the connection and 6 mutations in the RNase H were associated with NRTI treatment in subtype B. Some of them lay in or close to amino acid residues which contact nucleic acid or near the RNase H active site. Several of the residues pointed out herein have been recently associated to NRTI exposure or increase drug resistance to NRTI. CONCLUSIONS: This is the first comprehensive genotypic analysis of a large sequence dataset that describes NRTI-related mutations in HIV-1 RT C-terminal domains in vivo. The findings into the conservation of RT C-terminal domains may pave the way to more rational drug design initiatives targeting those regions.

Effects of Early and Late Bilingualism on Resting-State Functional Connectivity.

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Berken, Jonathan A; Chai, Xiaoqian; Chen, Jen-Kai; Gracco, Vincent L; Klein, Denise

2016-01-27

Of current interest is how variations in early language experience shape patterns of functional connectivity in the human brain. In the present study, we compared simultaneous (two languages from birth) and sequential (second language learned after age 5 years) bilinguals using a seed-based resting-state MRI approach. We focused on the inferior frontal gyrus (IFG) as our ROI, as recent studies have demonstrated both neurofunctional and neurostructural changes related to age of second language acquisition in bilinguals in this cortical area. Stronger functional connectivity was observed for simultaneous bilinguals between the left and right IFG, as well as between the inferior frontal gyrus and brain areas involved in language control, including the dorsolateral prefrontal cortex, inferior parietal lobule, and cerebellum. Functional connectivity between the left IFG and the right IFG and right inferior parietal lobule was also significantly correlated with age of acquisition for sequential bilinguals; the earlier the second language was acquired, the stronger was the functional connectivity. In addition, greater functional connectivity between homologous regions of the inferior frontal gyrus was associated with reduced neural activation in the left IFG during speech production. The increased connectivity at rest and reduced neural activation during task performance suggests enhanced neural efficiency in this important brain area involved in both speech production and domain-general cognitive processing. Together, our findings highlight how the brain's intrinsic functional patterns are influenced by the developmental timeline in which second language acquisition occurs. Of current interest is how early life experience leaves its footprint on brain structure and function. In this regard, bilingualism provides an optimal way to determine the effects of the timing of language learning because a second language can be learned from birth or later in life. We used resting

Brain Connectivity and Visual Attention

Science.gov (United States)

Parks, Emily L.

2013-01-01

Abstract Emerging hypotheses suggest that efficient cognitive functioning requires the integration of separate, but interconnected cortical networks in the brain. Although task-related measures of brain activity suggest that a frontoparietal network is associated with the control of attention, little is known regarding how components within this distributed network act together or with other networks to achieve various attentional functions. This review considers both functional and structural studies of brain connectivity, as complemented by behavioral and task-related neuroimaging data. These studies show converging results: The frontal and parietal cortical regions are active together, over time, and identifiable frontoparietal networks are active in relation to specific task demands. However, the spontaneous, low-frequency fluctuations of brain activity that occur in the resting state, without specific task demands, also exhibit patterns of connectivity that closely resemble the task-related, frontoparietal attention networks. Both task-related and resting-state networks exhibit consistent relations to behavioral measures of attention. Further, anatomical structure, particularly white matter pathways as defined by diffusion tensor imaging, places constraints on intrinsic functional connectivity. Lastly, connectivity analyses applied to investigate cognitive differences across individuals in both healthy and diseased states suggest that disconnection of attentional networks is linked to deficits in cognitive functioning, and in extreme cases, to disorders of attention. Thus, comprehensive theories of visual attention and their clinical translation depend on the continued integration of behavioral, task-related neuroimaging, and brain connectivity measures. PMID:23597177

X-ray chemical analyzer for field applications

International Nuclear Information System (INIS)

Gamba, O.O.M.

1977-01-01

A self-supporting portable field multichannel x-ray chemical analyzer system is claimed. It comprises a lightweight, flexibly connected, remotely locatable, radioisotope-excited sensing probe utilizing a cryogenically-cooled solid state semi-conductor crystal detector for fast in situ non-destructive, qualitative and quantitative analysis of elements in solid, powder, liquid or slurried form, utilizing an x-ray energy dispersive spectrometry technique

Using the "K[subscript 5]Connected Cognition Diagram" to Analyze Teachers' Communication and Understanding of Regions in Three-Dimensional Space

Science.gov (United States)

Moore-Russo, Deborah; Viglietti, Janine M.

2012-01-01

This paper reports on a study that introduces and applies the "K[subscript 5]Connected Cognition Diagram" as a lens to explore video data showing teachers' interactions related to the partitioning of regions by axes in a three-dimensional geometric space. The study considers "semiotic bundles" (Arzarello, 2006), introduces "semiotic connections,"…

NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity.

Science.gov (United States)

Al-Awami, Ali K; Beyer, Johanna; Strobelt, Hendrik; Kasthuri, Narayanan; Lichtman, Jeff W; Pfister, Hanspeter; Hadwiger, Markus

2014-12-01

We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity

KAUST Repository

Al-Awami, Ali K.; Beyer, Johanna; Strobelt, Hendrik; Kasthuri, Narayanan; Lichtman, Jeff W.; Pfister, Hanspeter; Hadwiger, Markus

2014-01-01

We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity

KAUST Repository

Al-Awami, Ali K.

2014-12-31

We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

Subregions of the human superior frontal gyrus and their connections.

Science.gov (United States)

Li, Wei; Qin, Wen; Liu, Huaigui; Fan, Lingzhong; Wang, Jiaojian; Jiang, Tianzi; Yu, Chunshui

2013-09-01

The superior frontal gyrus (SFG) is located at the superior part of the prefrontal cortex and is involved in a variety of functions, suggesting the existence of functional subregions. However, parcellation schemes of the human SFG and the connection patterns of each subregion remain unclear. We firstly parcellated the human SFG into the anteromedial (SFGam), dorsolateral (SFGdl), and posterior (SFGp) subregions based on diffusion tensor tractography. The SFGam was anatomically connected with the anterior and mid-cingulate cortices, which are critical nodes of the cognitive control network and the default mode network (DMN). The SFGdl was connected with the middle and inferior frontal gyri, which are involved in the cognitive execution network. The SFGp was connected with the precentral gyrus, caudate, thalamus, and frontal operculum, which are nodes of the motor control network. Resting-state functional connectivity analysis further revealed that the SFGam was mainly correlated with the cognitive control network and the DMN; the SFGdl was correlated with the cognitive execution network and the DMN; and the SFGp was correlated with the sensorimotor-related brain regions. The SFGam and SFGdl were further parcellated into three and two subclusters that are well corresponding to Brodmann areas. These findings suggest that the human SFG consists of multiple dissociable subregions that have distinct connection patterns and that these subregions are involved in different functional networks and serve different functions. These results may improve our understanding on the functional complexity of the SFG and provide us an approach to investigate the SFG at the subregional level. Copyright © 2013 Elsevier Inc. All rights reserved.

Linking DMN connectivity to episodic memory capacity: What can we learn from patients with medial temporal lobe damage?

Directory of Open Access Journals (Sweden)

Cornelia McCormick

2014-01-01

Full Text Available Computational models predict that focal damage to the Default Mode Network (DMN causes widespread decreases and increases of functional DMN connectivity. How such alterations impact functioning in a specific cognitive domain such as episodic memory remains relatively unexplored. Here, we show in patients with unilateral medial temporal lobe epilepsy (mTLE that focal structural damage leads indeed to specific patterns of DMN functional connectivity alterations, specifically decreased connectivity between both medial temporal lobes (MTLs and the posterior part of the DMN and increased intrahemispheric anterior–posterior connectivity. Importantly, these patterns were associated with better and worse episodic memory capacity, respectively. These distinct patterns, shown here for the first time, suggest that a close dialogue between both MTLs and the posterior components of the DMN is required to fully express the extensive repertoire of episodic memory abilities.

[Pulmonary involvement in connective tissue disease].

Science.gov (United States)

Bartosiewicz, Małgorzata

2016-01-01

The connective tissue diseases are a variable group of autoimmune mediated disorders characterized by multiorgan damage. Pulmonary complications are common, usually occur after the onset of joint symptoms, but can also be initially presenting complaint. The respiratory system may be involved in all its component: airways, vessels, parenchyma, pleura and respiratory muscles. Lung involvement is an increasing cause of morbidity and mortality in the connective tissue diseases. Clinical course is highly variable - can range from mild to rapidly progressive, some processes are reversible, while others are irreversible. Thus, the identification of reversible disease , and separately progressive disease, are important clinical issues. The frequency, clinical presentation, prognosis and responce to therapy are different, depending on the pattern of involvement as well as on specyfic diagnostic method used to identify it. High- resolution computed tompography plays an important role in identifying patients with respiratory involvement. Pulmonary function tests are a sensitive tool detecting interstitial lung disease. In this article, pulmonary lung involvement accompanying most frequently apperaing connective tissue diseases - rheumatoid arthritis, systemic sclerosis, lupus erythematosus, polymyositis/dermatomyositis, Sjögrens syndrome and mixed connective tissue disaese are reviewed.

Longitudinal connectome-based predictive modeling for REM sleep behavior disorder from structural brain connectivity

Science.gov (United States)

Giancardo, Luca; Ellmore, Timothy M.; Suescun, Jessika; Ocasio, Laura; Kamali, Arash; Riascos-Castaneda, Roy; Schiess, Mya C.

2018-02-01

Methods to identify neuroplasticity patterns in human brains are of the utmost importance in understanding and potentially treating neurodegenerative diseases. Parkinson disease (PD) research will greatly benefit and advance from the discovery of biomarkers to quantify brain changes in the early stages of the disease, a prodromal period when subjects show no obvious clinical symptoms. Diffusion tensor imaging (DTI) allows for an in-vivo estimation of the structural connectome inside the brain and may serve to quantify the degenerative process before the appearance of clinical symptoms. In this work, we introduce a novel strategy to compute longitudinal structural connectomes in the context of a whole-brain data-driven pipeline. In these initial tests, we show that our predictive models are able to distinguish controls from asymptomatic subjects at high risk of developing PD (REM sleep behavior disorder, RBD) with an area under the receiving operating characteristic curve of 0.90 (pParkinson's Progression Markers Initiative. By analyzing the brain connections most relevant for the predictive ability of the best performing model, we find connections that are biologically relevant to the disease.

Effects of Auxiliary-Source Connection in Multichip Power Module

DEFF Research Database (Denmark)

Li, Helong; Munk-Nielsen, Stig; Wang, Xiongfei

2017-01-01

the power loop and the gate loop like how the Kelvin-source connection does, owing to their involvement in the loop of the power source current. Three effects of the auxiliary-source connections are then analyzed, which are 1) the common source stray inductance reduction, 2) the transient drain......Auxiliary-source bond wires and connections are widely used in power modules with paralleled MOSFETs or IGBTs. This paper investigates the operation mechanism of the auxiliary-source connections in multichip power modules. It reveals that the auxiliary-source connections cannot fully decouple......-source current imbalance mitigation, and 3) the influence on the steady-state current distribution. Lastly, simulations and experimental results validate the theoretical analysis....

Effect of Kanji and Kana reading on cerebral blood flow patterns measured by PET

International Nuclear Information System (INIS)

Kiyosawa, Motohiro; Itoh, Masatoshi; Nakagawa, Youichi; Kobayashi, Naoki; Tamai, Makoto.

1995-01-01

To investigate the respective functions of pathways in processing visual information from different types of symbols, by positron emission tomography (PET) we examined the effect on cerebral blood flow (CBF) of reading the Japanese morphogram (kanji) versus the syllabogram (kana). Nine Japanese men were presented with three visual conditions in random order 2 minutes before the scan: eyes open controls, kanji morphogram reading, and kana syllabogram reading. Three words written in kanji or kana were shown, and subjects were instructed to read them silently and to identify the word unrelated logically to the other two. The reading and analyzing tasks activated wide areas of vision-related cortices. The comparison of the kanji and kana readings showed higher metabolism, with the former only in the posterior part of the primary visual cortex. Most of the CBF increases were common for both stimuli, although the patterns of these increases differed slightly. The correlation matrix of CBF change in the left hemisphere showed a ventral connection in kanji reading and a dorsal connection in kana reading. Our results suggest there is a functional differentiation in the brain between patterned and sequential perception when reading Japanese morphograms and syllabograms. (author)

Fuel analyzer; Analisador de combustiveis

Energy Technology Data Exchange (ETDEWEB)

Cozzolino, Roberval [RS Motors, Indaiatuba, SP (Brazil)

2008-07-01

The current technology 'COMBUSTIMETRO' aims to examine the fuel through performance of the engine, as the role of the fuel is to produce energy for the combustion engine in the form of which is directly proportional to the quality and type of fuel. The 'COMBUSTIMETRO' has an engine that always keeps the same entry of air, fuel and fixed point of ignition. His operation is monitored by sensors (Sonda Lambda, RPM and Gases Analyzer) connected to a processor that performs calculations and records the information, generate reports and graphs. (author)

Specialization Patterns

DEFF Research Database (Denmark)

Schultz, Ulrik Pagh; Lawall, Julia Laetitia; Consel, Charles

2000-01-01

Design patterns offer many advantages for software development, but can introduce inefficiency into the final program. Program specialization can eliminate such overheads, but is most effective when targeted by the user to specific bottlenecks. Consequently, we propose that these concepts...... are complementary. Program specialization can optimize programs written using design patterns, and design patterns provide information about the program structure that can guide specialization. Concretely, we propose specialization patterns, which describe how to apply program specialization to optimize uses...... of design patterns. In this paper, we analyze the specialization opportunities provided by specific uses of design patterns. Based on the analysis of each design pattern, we define the associated specialization pattern. These specialization opportunities can be declared using the specialization classes...

A high performance P(VDF-TrFE) nanogenerator with self-connected and vertically integrated fibers by patterned EHD pulling

Science.gov (United States)

Chen, Xiaoliang; Tian, Hongmiao; Li, Xiangming; Shao, Jinyou; Ding, Yucheng; An, Ningli; Zhou, Yaopei

2015-07-01

Piezoelectricity based energy harvesting from mechanical vibrations has attracted extensive attention for its potential application in powering wireless mobile electronics recently. Here, a patterned electrohydrodynamic (EHD) pulling technology was proposed to fabricate a new self-connected, piezoelectric fiber array vertically integrated P(VDF-TrFE) nanogenerator, with a molecular poling orientation fully aligned to the principal excitation for maximized conversion and a well-bridged electrode pair for efficient charge collection. The nanogenerator is fabricated in a novel way by applying a voltage across an electrode pair sandwiching an air gap and an array of shallow micropillars, during which the EHD force tends to pull the micropillars upward, generating a microfiber array finally in robust contact with the upper electrode. Such a thermoplastic and EHD deformation of the microfibers, featured simultaneously by an electric field and by a microfiber elongation dominantly vertical to the electrode, leads to a poling orientation of P(VDF-TrFE) well coincident with the principal strain for the generator excited by a force normal to the electrodes. The as-prepared piezoelectric device exhibits an enhanced output voltage up to 4.0 V and a current of 2.6 μA, therefore the piezoelectric voltage was enhanced to 5.4 times that from the bulk film. Under periodic mechanical impact, electric signals are repeatedly generated from the device and used to power a seven-segment indicator, RBGY colored light-emitting diodes, and a large-scale liquid crystal display screen. These results not only provide a tool for fabricating 3D piezoelectric polymers but offer a new type of self-connected nanogenerator for the next generation of self-powered electronics.Piezoelectricity based energy harvesting from mechanical vibrations has attracted extensive attention for its potential application in powering wireless mobile electronics recently. Here, a patterned electrohydrodynamic (EHD

Successful reconstruction of a physiological circuit with known connectivity from spiking activity alone.

Directory of Open Access Journals (Sweden)

Felipe Gerhard

Full Text Available Identifying the structure and dynamics of synaptic interactions between neurons is the first step to understanding neural network dynamics. The presence of synaptic connections is traditionally inferred through the use of targeted stimulation and paired recordings or by post-hoc histology. More recently, causal network inference algorithms have been proposed to deduce connectivity directly from electrophysiological signals, such as extracellularly recorded spiking activity. Usually, these algorithms have not been validated on a neurophysiological data set for which the actual circuitry is known. Recent work has shown that traditional network inference algorithms based on linear models typically fail to identify the correct coupling of a small central pattern generating circuit in the stomatogastric ganglion of the crab Cancer borealis. In this work, we show that point process models of observed spike trains can guide inference of relative connectivity estimates that match the known physiological connectivity of the central pattern generator up to a choice of threshold. We elucidate the necessary steps to derive faithful connectivity estimates from a model that incorporates the spike train nature of the data. We then apply the model to measure changes in the effective connectivity pattern in response to two pharmacological interventions, which affect both intrinsic neural dynamics and synaptic transmission. Our results provide the first successful application of a network inference algorithm to a circuit for which the actual physiological synapses between neurons are known. The point process methodology presented here generalizes well to larger networks and can describe the statistics of neural populations. In general we show that advanced statistical models allow for the characterization of effective network structure, deciphering underlying network dynamics and estimating information-processing capabilities.

Nevos de tejido conectivo Connective tissue nevi

Directory of Open Access Journals (Sweden)

RE Achenbach

Full Text Available Comunicamos dos casos de nevo del tejido conectivo, el primero con patrón histológico mixto y el segundo con predominio de alteraciones en las fibras elásticas. No se constataron síndromes ni patología sistémica asociada. Un caso presentó disposición linear y un nevo acrómico asociado.Two cases of connective tissue nevi are reported, one of them with a mixed histopatologic pattern and one with elastin fibers diminished. None of the patients had systemic involvement or associated syndromes. The mixed connective tissue nevi type showed a linear distribution and has associated an acromic nevi.

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

Directory of Open Access Journals (Sweden)

Youjun Li

2017-08-01

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

Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis.

Science.gov (United States)

Ponsoda, Vicente; Martínez, Kenia; Pineda-Pardo, José A; Abad, Francisco J; Olea, Julio; Román, Francisco J; Barbey, Aron K; Colom, Roberto

2017-02-01

Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Functional hierarchy underlies preferential connectivity disturbances in schizophrenia.

Science.gov (United States)

Yang, Genevieve J; Murray, John D; Wang, Xiao-Jing; Glahn, David C; Pearlson, Godfrey D; Repovs, Grega; Krystal, John H; Anticevic, Alan

2016-01-12

Schizophrenia may involve an elevated excitation/inhibition (E/I) ratio in cortical microcircuits. It remains unknown how this regulatory disturbance maps onto neuroimaging findings. To address this issue, we implemented E/I perturbations within a neural model of large-scale functional connectivity, which predicted hyperconnectivity following E/I elevation. To test predictions, we examined resting-state functional MRI in 161 schizophrenia patients and 164 healthy subjects. As predicted, patients exhibited elevated functional connectivity that correlated with symptom levels, and was most prominent in association cortices, such as the fronto-parietal control network. This pattern was absent in patients with bipolar disorder (n = 73). To account for the pattern observed in schizophrenia, we integrated neurobiologically plausible, hierarchical differences in association vs. sensory recurrent neuronal dynamics into our model. This in silico architecture revealed preferential vulnerability of association networks to E/I imbalance, which we verified empirically. Reported effects implicate widespread microcircuit E/I imbalance as a parsimonious mechanism for emergent inhomogeneous dysconnectivity in schizophrenia.

Examining Neuronal Connectivity and Its Role in Learning and Memory

Science.gov (United States)

Gala, Rohan

Learning and long-term memory formation are accompanied with changes in the patterns and weights of synaptic connections in the underlying neuronal network. However, the fundamental rules that drive connectivity changes, and the precise structure-function relationships within neuronal networks remain elusive. Technological improvements over the last few decades have enabled the observation of large but specific subsets of neurons and their connections in unprecedented detail. Devising robust and automated computational methods is critical to distill information from ever-increasing volumes of raw experimental data. Moreover, statistical models and theoretical frameworks are required to interpret the data and assemble evidence into understanding of brain function. In this thesis, I first describe computational methods to reconstruct connectivity based on light microscopy imaging experiments. Next, I use these methods to quantify structural changes in connectivity based on in vivo time-lapse imaging experiments. Finally, I present a theoretical model of associative learning that can explain many stereotypical features of experimentally observed connectivity.

No Reef Is an Island: Integrating Coral Reef Connectivity Data into the Design of Regional-Scale Marine Protected Area Networks.

Science.gov (United States)

Schill, Steven R; Raber, George T; Roberts, Jason J; Treml, Eric A; Brenner, Jorge; Halpin, Patrick N

2015-01-01

We integrated coral reef connectivity data for the Caribbean and Gulf of Mexico into a conservation decision-making framework for designing a regional scale marine protected area (MPA) network that provides insight into ecological and political contexts. We used an ocean circulation model and regional coral reef data to simulate eight spawning events from 2008-2011, applying a maximum 30-day pelagic larval duration and 20% mortality rate. Coral larval dispersal patterns were analyzed between coral reefs across jurisdictional marine zones to identify spatial relationships between larval sources and destinations within countries and territories across the region. We applied our results in Marxan, a conservation planning software tool, to identify a regional coral reef MPA network design that meets conservation goals, minimizes underlying threats, and maintains coral reef connectivity. Our results suggest that approximately 77% of coral reefs identified as having a high regional connectivity value are not included in the existing MPA network. This research is unique because we quantify and report coral larval connectivity data by marine ecoregions and Exclusive Economic Zones (EZZ) and use this information to identify gaps in the current Caribbean-wide MPA network by integrating asymmetric connectivity information in Marxan to design a regional MPA network that includes important reef network connections. The identification of important reef connectivity metrics guides the selection of priority conservation areas and supports resilience at the whole system level into the future.

No Reef Is an Island: Integrating Coral Reef Connectivity Data into the Design of Regional-Scale Marine Protected Area Networks.

Directory of Open Access Journals (Sweden)

Steven R Schill

Full Text Available We integrated coral reef connectivity data for the Caribbean and Gulf of Mexico into a conservation decision-making framework for designing a regional scale marine protected area (MPA network that provides insight into ecological and political contexts. We used an ocean circulation model and regional coral reef data to simulate eight spawning events from 2008-2011, applying a maximum 30-day pelagic larval duration and 20% mortality rate. Coral larval dispersal patterns were analyzed between coral reefs across jurisdictional marine zones to identify spatial relationships between larval sources and destinations within countries and territories across the region. We applied our results in Marxan, a conservation planning software tool, to identify a regional coral reef MPA network design that meets conservation goals, minimizes underlying threats, and maintains coral reef connectivity. Our results suggest that approximately 77% of coral reefs identified as having a high regional connectivity value are not included in the existing MPA network. This research is unique because we quantify and report coral larval connectivity data by marine ecoregions and Exclusive Economic Zones (EZZ and use this information to identify gaps in the current Caribbean-wide MPA network by integrating asymmetric connectivity information in Marxan to design a regional MPA network that includes important reef network connections. The identification of important reef connectivity metrics guides the selection of priority conservation areas and supports resilience at the whole system level into the future.

Connectivity dynamics in typical development and its relationship to autistic traits and autism spectrum disorder.

Science.gov (United States)

Rashid, Barnaly; Blanken, Laura M E; Muetzel, Ryan L; Miller, Robyn; Damaraju, Eswar; Arbabshirani, Mohammad R; Erhardt, Erik B; Verhulst, Frank C; van der Lugt, Aad; Jaddoe, Vincent W V; Tiemeier, Henning; White, Tonya; Calhoun, Vince

2018-03-30

Recent advances in neuroimaging techniques have provided significant insights into developmental trajectories of human brain function. Characterizations of typical neurodevelopment provide a framework for understanding altered neurodevelopment, including differences in brain function related to developmental disorders and psychopathology. Historically, most functional connectivity studies of typical and atypical development operate under the assumption that connectivity remains static over time. We hypothesized that relaxing stationarity assumptions would reveal novel features of both typical brain development related to children on the autism spectrum. We employed a "chronnectomic" (recurring, time-varying patterns of connectivity) approach to evaluate transient states of connectivity using resting-state functional MRI in a population-based sample of 774 6- to 10-year-old children. Dynamic connectivity was evaluated using a sliding-window approach, and revealed four transient states. Internetwork connectivity increased with age in modularized dynamic states, illustrating an important pattern of connectivity in the developing brain. Furthermore, we demonstrated that higher levels of autistic traits and ASD diagnosis were associated with longer dwell times in a globally disconnected state. These results provide a roadmap to the chronnectomic organization of the developing brain and suggest that characteristics of functional brain connectivity are related to children on the autism spectrum. © 2018 Wiley Periodicals, Inc.

Transcranial magnetic stimulation and connectivity mapping: tools for studying the neural bases of brain disorders.

Science.gov (United States)

Hampson, M; Hoffman, R E

2010-01-01

There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS) provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through long-range connections to other brain areas. Thus, by identifying distal regions activated during TMS, researchers can infer connectivity patterns in the healthy human brain and can examine how those patterns may be disrupted in patients with different brain disorders. Conversely, connectivity maps derived using neuroimaging methods can identify components of a dysfunctional network. Nodes in this dysfunctional network accessible as targets for TMS by virtue of their proximity to the scalp may then permit TMS-induced alterations of components of the network not directly accessible to TMS via propagated effects. Thus TMS can provide a portal for accessing and altering neural dynamics in networks that are widely distributed anatomically. Finally, when long-term modulation of network dynamics is induced by trains of repetitive TMS, changes in functional connectivity patterns can be studied in parallel with changes in patient symptoms. These correlational data can elucidate neural mechanisms underlying illness and recovery. In this review, we focus on the application of these approaches to the study of psychiatric and neurological illnesses.

Transcranial magnetic stimulation and connectivity mapping: tools for studying the neural bases of brain disorders.

Directory of Open Access Journals (Sweden)

Michelle Hampson

2010-08-01

Full Text Available There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through long-range connections to other brain areas. Thus, by identifying distal regions activated during TMS, researchers can infer connectivity patterns in the healthy human brain and can examine how those patterns may be disrupted in patients with different brain disorders. Conversely, connectivity maps derived using neuroimaging methods can identify components of a dysfunctional network. Nodes in this dysfunctional network accessible as targets for TMS by virtue of their proximity to the scalp may then permit TMS-induced alterations of components of the network not directly accessible to TMS via propagated effects. Thus TMS can provide a portal for accessing and altering neural dynamics in networks that are widely distributed anatomically. Finally, when long-term modulation of network dynamics is induced by trains of repetitive TMS, changes in functional connectivity patterns can be studied in parallel with changes in patient symptoms. These correlational data can elucidate neural mechanisms underlying illness and recovery. In this review, we focus on the application of these approaches to the study of psychiatric and neurological illnesses.

Toxicity and Detoxification Effects of Herbal Caowu via Ultra Performance Liquid Chromatography/Mass Spectrometry Metabolomics Analyzed using Pattern Recognition Method

Science.gov (United States)

Yan, Yan; Zhang, Aihua; Dong, Hui; Yan, Guangli; Sun, Hui; Wu, Xiuhong; Han, Ying; Wang, Xijun

2017-01-01

Background: Caowu (Radix Aconiti kusnezoffii, CW), the root of Aconitum kusnezoffii Reichb., has widely used clinically in rheumatic arthritis, painful joints, and tumors for thousands of years. However, the toxicity of heart and central nervous system induced by CW still limited the application. Materials and Methods: Metabolomics was performed to identify the sensitive and reliable biomarkers and to characterize the phenotypically biochemical perturbations and potential mechanisms of CW-induced toxicity, and the detoxification by combinatorial intervention of CW with Gancao (Radix Glycyrrhizae) (CG), Baishao (Radix Paeoniae Alba) (CB), and Renshen (Radix Ginseng) (CR) was also analyzed by pattern recognition methods. Results: As a result, the metabolites were characterized and responsible for pentose and glucuronate interconversions, tryptophan metabolism, amino sugar and nucleotide sugar metabolism, taurine and hypotaurine metabolism, fructose and mannose metabolism, and starch and sucrose metabolism, six networks of which were the same to the metabolic pathways of Chuanwu (Radix Aconiti, CHW) group. The ascorbate and aldarate metabolism was also characterized by CW group. The urinary metabolomics also revealed CW-induced serious toxicity to heart and liver. Thirteen significant metabolites were identified and had validated as phenotypic toxicity biomarkers of CW, five biomarkers of which were commonly owned in Aconitum. The changes of toxicity metabolites obtained from combinatorial intervention of CG, CB, and CR also were analyzed to investigate the regulation degree of toxicity biomarkers adjusted by different combinatorial interventions at 6th month. Conclusion: Metabolomics analyses coupled with pattern recognition methods in the evaluation of drug toxicity and finding detoxification methods were highlighted in this work. SUMMARY Metabolomics was performed to characterize the biochemical potential mechanisms of Caowu toxicityThirteen significant metabolites

Network structure shapes spontaneous functional connectivity dynamics.

Science.gov (United States)

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

2015-04-08

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

Changes in Soil Quality and Hydrological Connectivity Caused by the Abandonment of Terraces in a Mediterranean Burned Catchment

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Aleix Calsamiglia

2017-09-01

Full Text Available Wildfires and agricultural activities are relevant factors affecting soil quality, hydrological cycle and sedimentary dynamics. Land abandonment leads to afforestation, which increases fire risk and land degradation. However, no studies have yet evaluated the effect of combining the two factors, which occur frequently in Mediterranean ecosystems. This study assessed the changes in soil quality caused by the abandonment of terraces in two microcatchments (<2.5 ha affected distinctly by wildfires (once and twice burned and in an unburned control microcatchment by analyzing soil quality parameters, biochemical indices and spatial patterns of hydrological and sediment connectivity. Soil samples were collected in thirty-six plots (25 m2 representing terraced and non-terraced areas within these microcatchments. Unburned non-terraced plots had higher organic matter content and higher microbiological and enzymatic activities than other plots. Plots in abandoned terraces had lower soil quality indices, regardless of the fire effect. Land abandonment induced changes in the spatial patterns of hydrological connectivity, leading to concentrated runoff, enhanced erosion and soil degradation. Fire also negatively affected soil quality in both terraced and non-terraced plots. However, microbiological communities had different positive post-fire recovery strategies (growth and activity, depending on the previous soil conditions and land uses, which is indicative of the resilience of Mediterranean soil ecosystems.

Implications of tristability in pattern-forming ecosystems

Science.gov (United States)

Zelnik, Yuval R.; Gandhi, Punit; Knobloch, Edgar; Meron, Ehud

2018-03-01

Many ecosystems show both self-organized spatial patterns and multistability of possible states. The combination of these two phenomena in different forms has a significant impact on the behavior of ecosystems in changing environments. One notable case is connected to tristability of two distinct uniform states together with patterned states, which has recently been found in model studies of dryland ecosystems. Using a simple model, we determine the extent of tristability in parameter space, explore its effects on the system dynamics, and consider its implications for state transitions or regime shifts. We analyze the bifurcation structure of model solutions that describe uniform states, periodic patterns, and hybrid states between the former two. We map out the parameter space where these states exist, and note how the different states interact with each other. We further focus on two special implications with ecological significance, breakdown of the snaking range and complex fronts. We find that the organization of the hybrid states within a homoclinic snaking structure breaks down as it meets a Maxwell point where simple fronts are stationary. We also discover a new series of complex fronts between the uniform states, each with its own velocity. We conclude with a brief discussion of the significance of these findings for the dynamics of regime shifts and their potential control.

Rural transformations in the context of changing rural-urban connections

DEFF Research Database (Denmark)

Birch-Thomsen, Torben; Ørtenblad, Sinne Borby; Msese, Lukelo

, the infrastructure, including road systems and means of communication, has in general increased and improved. This development has among a number of other things caused changing patterns of mobility. These changes are highly interrelated and connected to changing rural-urban linkages, which include flows of people......, capital, resources, agricultural commodities, goods, services, technology and information, between rural and urban locations. We emphasize that the rural-urban connections go beyond the spatial dichotomy and that the linkages often occur in a dynamic rural-urban continuum. Influenced by these changes......, this paper sets out to elucidate patterns and dynamics of rural transformation in Tanzania in the context of changing rural-urban linkages by presenting data from a particularly dynamic region; namely Njombe Region in the Southern Highlands of Tanzania. Based on fieldwork conducted during 2014 and 2015...

The adversative connectives aber and but in conversational corpora.

Science.gov (United States)

Gülzow, Insa; Bartlitz, Victoria; Kuehnast, Milena; Golcher, Felix; Bittner, Dagmar

2018-03-09

We analyzed the conversational corpora of two German and two English children to investigate how the different use types of the adversative connectives aber and but influence the probability of monologically versus dialogically constructed utterances in the first year of use. Our findings show that children produce adversative connectives mainly in dialogic structures for illocutionary and theme-management purposes, but that the use types of adversative connectives lead to a different distribution of monologic and dialogic clause combinations. The results suggest that monologic and dialogic realizations as a function of text type must be considered when describing the developmental trajectory of the different use types of adversative connectives.

The necessity of connection structures in neural models of variable binding.

Science.gov (United States)

van der Velde, Frank; de Kamps, Marc

2015-08-01

In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1-11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other ('connectivity based') type uses dedicated connections structures to achieve novel variable binding. Feldman argued that label (synchrony) based models are the only possible candidates to handle novel variable binding, whereas connectivity based models lack the flexibility required for that. We argue and illustrate that Feldman's analysis is incorrect. Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior. We will show that the label (synchrony) based models analyzed by Feldman are in fact examples of connectivity based models. Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference. Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain. We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures.

KEEFEKTIFAN MODEL CONNECTED DAN INTEGRATED DALAM PEMBELAJARAN IPS SMP DI KOTA YOGYAKARTA

OpenAIRE

Idrus idrus

2011-01-01

This research aimed to: (1) analyze the differences in social studies learning achievement between the students using connected and integrated models and those using conventional model; and (2) analyze the hierarchy of the effect of the learning models  among the connected, integrated, and conventional. This experimental research employed a matching post-test comparison group design. The population of this research was National Standardized Schools of Junior Secondary Schools in Yogya...

Patterns and persistence of larval retention and connectivity in a marine fish metapopulation

KAUST Repository

Saenz Agudelo, Pablo; Jones, Geoffrey P.; Thorrold, Simon R.; Planes, Serge

2012-01-01

Connectivity, the demographic linking of local populations through the dispersal of individuals, is one of the most poorly understood processes in population dynamics, yet has profound implications for conservation and harvest strategies. For marine

Edge parameters from an energy analyzer and particle transport on TEXT-U

International Nuclear Information System (INIS)

Crockett, D.B.; Phillips, P.E.; Craven, W.A.; Rowan, W.L.; Wootton, A.J.; Wan, A.S.; Yang, T.F.

1994-01-01

The energy distributions of ions and electrons in the scrape-off layer of TEXT are measured with a bi-directional Retarding Field Analyzer (RFA). The probe provides simultaneous measurements parallel and anti-parallel to the plasma current. Large asymmetries in this direction in the flux and temperature that were found with the RFA appear largely due to differences in the connection lengths L c . The measurements from the analyzer are compared with the results of a simple edge model to infer the edge particle diffusion coefficient. While the measurements are consistent with the model for longer connection lengths (∼ 10 meters in TEXT-U), the agreement deteriorates for L c less than two meters

The phase interrogation method for optical fiber sensor by analyzing the fork interference pattern

Science.gov (United States)

Lv, Riqing; Qiu, Liqiang; Hu, Haifeng; Meng, Lu; Zhang, Yong

2018-02-01

The phase interrogation method for optical fiber sensor is proposed based on the fork interference pattern between the orbital angular momentum beam and plane wave. The variation of interference pattern with phase difference between the two light beams is investigated to realize the phase interrogation. By employing principal component analysis method, the features of the interference pattern can be extracted. Moreover, the experimental system is designed to verify the theoretical analysis, as well as feasibility of phase interrogation. In this work, the Mach-Zehnder interferometer was employed to convert the strain applied on sensing fiber to the phase difference between the reference and measuring paths. This interrogation method is also applicable for the measurements of other physical parameters, which can produce the phase delay in optical fiber. The performance of the system can be further improved by employing highlysensitive materials and fiber structures.

Chagas disease, migration and community settlement patterns in Arequipa, Peru.

Directory of Open Access Journals (Sweden)

Angela M Bayer

2009-12-01

Full Text Available Chagas disease is one of the most important neglected tropical diseases in the Americas. Vectorborne transmission of Chagas disease has been historically rare in urban settings. However, in marginal communities near the city of Arequipa, Peru, urban transmission cycles have become established. We examined the history of migration and settlement patterns in these communities, and their connections to Chagas disease transmission.This was a qualitative study that employed focus group discussions and in-depth interviews. Five focus groups and 50 in-depth interviews were carried out with 94 community members from three shantytowns and two traditional towns near Arequipa, Peru. Focus groups utilized participatory methodologies to explore the community's mobility patterns and the historical and current presence of triatomine vectors. In-depth interviews based on event history calendars explored participants' migration patterns and experience with Chagas disease and vectors. Focus group data were analyzed using participatory analysis methodologies, and interview data were coded and analyzed using a grounded theory approach. Entomologic data were provided by an ongoing vector control campaign. We found that migrants to shantytowns in Arequipa were unlikely to have brought triatomines to the city upon arrival. Frequent seasonal moves, however, took shantytown residents to valleys surrounding Arequipa where vectors are prevalent. In addition, the pattern of settlement of shantytowns and the practice of raising domestic animals by residents creates a favorable environment for vector proliferation and dispersal. Finally, we uncovered a phenomenon of population loss and replacement by low-income migrants in one traditional town, which created the human settlement pattern of a new shantytown within this traditional community.The pattern of human migration is therefore an important underlying determinant of Chagas disease risk in and around Arequipa. Frequent

The Strategy of Micro-Network for Research on Network Connections

OpenAIRE

MladenKralj, -; LilijanaZupan, -

2013-01-01

This paper emphasizes mainly on the grid-connected control strategy of the micro-grid during the grid-connected process. The typical configuration of the micro-grid is presented. The power flow in the micro-grid is analyzed based on the characteristic curve of frequency-power, and the method of the best connection point selection is given. In consideration of the harmonics, disturbances and time delay, the gridconnected control strategy is proposed. The micro-grid is simulated by the simulati...

Crosstalk performance of integrated optical cross-connects

NARCIS (Netherlands)

Herben, C.G.P.; Leijtens, X.J.M.; Maat, D.H.P.; Blok, H.; Smit, M.K.

1999-01-01

Crosstalk performance of monolithically integrated multiwavelength optical cross-connects (OXC's) depends strongly on their architecture. In this paper, a semiquantitative analysis of crosstalk in 11 different architectures is presented. Two architectures are analyzed numerically in more detail and

An autoradiographic analysis of the cortical connections of the pallidal and cerebellar zones within the feline motor thalamus

International Nuclear Information System (INIS)

Wensel, J.P.

1989-01-01

The feline motor thalamus relays both basal ganglia and cerebellar inputs to the motor cortex. This complex is classically subdivided into three nuclei: the ventroanterior nucleus (VA), the ventrolateral nucleus (VL), and the ventromedial nucleus (VM). Poor correlation between recognized patterns of cortical and subcortical connectivity and traditional boundaries used to distinguish these nuclei complicate the elucidation of the role they play in the elaboration of motor behavior. The recent demonstration of complementarity for the pallidothalamic and dentatothalamic projections to the motor thalamus of the cat provided the foundation for a revision of these nuclear borders to reflect differences in subcortical connectivity. Using a revised topography, this study analyzed the afferent and efferent connections of the feline VA and VL through the application of both anterograde and retrograde tracing techniques. The extent of the cerebellothalamic projection, as revealed by the bidirectional transport of WGA-HRP, was used to demarcate the boundary between VA and VL. Injections of tritiated amino acids into VA and VL allowed for the autoradiographic tracing of their cortical projections. Autoradiography was also used to demonstrate the distributions of corticothalamic projections from selected pericruciate and posterior parietal subfields to the motor thalamus

Sensitivity of marine protected area network connectivity to atmospheric variability.

Science.gov (United States)

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

2016-11-01

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

Connective Tissue Disorders and Cardiovascular Complications: The indomitable role of Transforming Growth Factor-beta signaling

Science.gov (United States)

Wheeler, Jason B.; Ikonomidis, John S.; Jones, Jeffrey A.

2015-01-01

Marfan Syndrome (MFS) and Loeys-Dietz Syndrome (LDS) represent heritable connective tissue disorders that cosegregate with a similar pattern of cardiovascular defects (thoracic aortic aneurysm, mitral valve prolapse/regurgitation, and aortic dilatation with regurgitation). This pattern of cardiovascular defects appears to be expressed along a spectrum of severity in many heritable connective tissue disorders and raises suspicion of a relationship between the normal development of connective tissues and the cardiovascular system. Given the evidence of increased transforming growth factor-beta (TGF-β) signaling in MFS and LDS, this signaling pathway may represent the common link in this relationship. To further explore this hypothetical link, this chapter will review the TGF-β signaling pathway, heritable connective tissue syndromes related to TGF-β receptor (TGFBR) mutations, and discuss the pathogenic contribution of TGF-β to these syndromes with a primary focus on the cardiovascular system. PMID:24443024

Effect of Pore Size and Pore Connectivity on Unidirectional Capillary Penetration Kinetics in 3-D Porous Media using Direct Numerical Simulation

Science.gov (United States)

Fu, An; Palakurthi, Nikhil; Konangi, Santosh; Comer, Ken; Jog, Milind

2017-11-01

The physics of capillary flow is used widely in multiple fields. Lucas-Washburn equation is developed by using a single pore-sized capillary tube with continuous pore connection. Although this equation has been extended to describe the penetration kinetics into porous medium, multiple studies have indicated L-W does not accurately predict flow patterns in real porous media. In this study, the penetration kinetics including the effect of pore size and pore connectivity will be closely examined since they are expected to be the key factors effecting the penetration process. The Liquid wicking process is studied from a converging and diverging capillary tube to the complex virtual 3-D porous structures with Direct Numerical Simulation (DNS) using the Volume-Of-Fluid (VOF) method within the OpenFOAM CFD Solver. Additionally Porous Medium properties such as Permeability (k) , Tortuosity (τ) will be also analyzed.

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

Science.gov (United States)

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

2017-12-01

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

Cerebro-cerebellar Resting-State Functional Connectivity in Children and Adolescents with Autism Spectrum Disorder.

Science.gov (United States)

Khan, Amanda J; Nair, Aarti; Keown, Christopher L; Datko, Michael C; Lincoln, Alan J; Müller, Ralph-Axel

2015-11-01

The cerebellum plays important roles in sensori-motor and supramodal cognitive functions. Cellular, volumetric, and functional abnormalities of the cerebellum have been found in autism spectrum disorders (ASD), but no comprehensive investigation of cerebro-cerebellar connectivity in ASD is available. We used resting-state functional connectivity magnetic resonance imaging in 56 children and adolescents (28 subjects with ASD, 28 typically developing subjects) 8-17 years old. Partial and total correlation analyses were performed for unilateral regions of interest (ROIs), distinguished in two broad domains as sensori-motor (premotor/primary motor, somatosensory, superior temporal, and occipital) and supramodal (prefrontal, posterior parietal, and inferior and middle temporal). There were three main findings: 1) Total correlation analyses showed predominant cerebro-cerebellar functional overconnectivity in the ASD group; 2) partial correlation analyses that emphasized domain specificity (sensori-motor vs. supramodal) indicated a pattern of robustly increased connectivity in the ASD group (compared with the typically developing group) for sensori-motor ROIs but predominantly reduced connectivity for supramodal ROIs; and 3) this atypical pattern of connectivity was supported by significantly increased noncanonical connections (between sensori-motor cerebral and supramodal cerebellar ROIs and vice versa) in the ASD group. Our findings indicate that sensori-motor intrinsic functional connectivity is atypically increased in ASD, at the expense of connectivity supporting cerebellar participation in supramodal cognition. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Vertical and horizontal genetic connectivity in Chromis verater, an endemic damselfish found on shallow and mesophotic reefs in the Hawaiian Archipelago and adjacent Johnston Atoll.

Science.gov (United States)

Tenggardjaja, Kimberly A; Bowen, Brian W; Bernardi, Giacomo

2014-01-01

Understanding vertical and horizontal connectivity is a major priority in research on mesophotic coral ecosystems (30-150 m). However, horizontal connectivity has been the focus of few studies, and data on vertical connectivity are limited to sessile benthic mesophotic organisms. Here we present patterns of vertical and horizontal connectivity in the Hawaiian Islands-Johnston Atoll endemic threespot damselfish, Chromis verater, based on 319 shallow specimens and 153 deep specimens. The mtDNA markers cytochrome b and control region were sequenced to analyze genetic structure: 1) between shallow (shallow and mesophotic populations. There was no significant genetic differentiation by depth, indicating high levels of vertical connectivity between shallow and deep aggregates of C. verater. Consequently, shallow and deep samples were combined by location for analyses of horizontal connectivity. We detected low but significant population structure across the Hawaiian Archipelago (overall cytochrome b: ΦST = 0.009, P = 0.020; control region: ΦST = 0.012, P = 0.009) and a larger break between the archipelago and Johnston Atoll (cytochrome b: ΦST = 0.068, P deep reefs may constitute a population reservoir for species depleted in shallow reef habitats. These findings represent the first connectivity study on a mobile organism that spans shallow and mesophotic depths and provide a reference point for future connectivity studies on mesophotic fishes.

Multivariate Heteroscedasticity Models for Functional Brain Connectivity

Directory of Open Access Journals (Sweden)

Christof Seiler

2017-12-01

Full Text Available Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI. We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.

Complex Pattern Formation from Current-Driven Dynamics of Single-Layer Homoepitaxial Islands on Crystalline Conducting Substrates

Science.gov (United States)

Kumar, Ashish; Dasgupta, Dwaipayan; Maroudas, Dimitrios

2017-07-01

We report a systematic study of complex pattern formation resulting from the driven dynamics of single-layer homoepitaxial islands on surfaces of face-centered-cubic (fcc) crystalline conducting substrates under the action of an externally applied electric field. The analysis is based on an experimentally validated nonlinear model of mass transport via island edge atomic diffusion, which also accounts for edge diffusional anisotropy. We analyze the morphological stability and simulate the field-driven evolution of rounded islands for an electric field oriented along the fast edge diffusion direction. For larger-than-critical island sizes on {110 } and {100 } fcc substrates, we show that multiple necking instabilities generate complex island patterns, including not-simply-connected void-containing islands mediated by sequences of breakup and coalescence events and distributed symmetrically with respect to the electric field direction. We analyze the dependence of the formed patterns on the original island size and on the duration of application of the external field. Starting from a single large rounded island, we characterize the evolution of the number of daughter islands and their average size and uniformity. The evolution of the average island size follows a universal power-law scaling relation, and the evolution of the total edge length of the islands in the complex pattern follows Kolmogorov-Johnson-Mehl-Avrami kinetics. Our study makes a strong case for the use of electric fields, as precisely controlled macroscopic forcing, toward surface patterning involving complex nanoscale features.

Accelerated Distributed Dual Averaging Over Evolving Networks of Growing Connectivity

Science.gov (United States)

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

2018-04-01

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

Face processing pattern under top-down perception: a functional MRI study

Science.gov (United States)

Li, Jun; Liang, Jimin; Tian, Jie; Liu, Jiangang; Zhao, Jizheng; Zhang, Hui; Shi, Guangming

2009-02-01

Although top-down perceptual process plays an important role in face processing, its neural substrate is still puzzling because the top-down stream is extracted difficultly from the activation pattern associated with contamination caused by bottom-up face perception input. In the present study, a novel paradigm of instructing participants to detect faces from pure noise images is employed, which could efficiently eliminate the interference of bottom-up face perception in topdown face processing. Analyzing the map of functional connectivity with right FFA analyzed by conventional Pearson's correlation, a possible face processing pattern induced by top-down perception can be obtained. Apart from the brain areas of bilateral fusiform gyrus (FG), left inferior occipital gyrus (IOG) and left superior temporal sulcus (STS), which are consistent with a core system in the distributed cortical network for face perception, activation induced by top-down face processing is also found in these regions that include the anterior cingulate gyrus (ACC), right oribitofrontal cortex (OFC), left precuneus, right parahippocampal cortex, left dorsolateral prefrontal cortex (DLPFC), right frontal pole, bilateral premotor cortex, left inferior parietal cortex and bilateral thalamus. The results indicate that making-decision, attention, episodic memory retrieving and contextual associative processing network cooperate with general face processing regions to process face information under top-down perception.

Broad-scale sampling of primary freshwater fish populations reveals the role of intrinsic traits, inter-basin connectivity, drainage area and latitude on shaping contemporary patterns of genetic diversity

Directory of Open Access Journals (Sweden)

Carla Sousa-Santos

2016-02-01

Full Text Available Background. Worldwide predictions suggest that up to 75% of the freshwater fish species occurring in rivers with reduced discharge could be extinct by 2070 due to the combined effect of climate change and water abstraction. The Mediterranean region is considered to be a hotspot of freshwater fish diversity but also one of the regions where the effects of climate change will be more severe. Iberian cyprinids are currently highly endangered, with over 68% of the species raising some level of conservation concern. Methods. During the FISHATLAS project, the Portuguese hydrographical network was extensively covered (all the 34 river basins and 47 sub-basins in order to contribute with valuable data on the genetic diversity distribution patterns of native cyprinid species. A total of 188 populations belonging to 16 cyprinid species of Squalius, Luciobarbus, Achondrostoma, Iberochondrostoma, Anaecypris and Pseudochondrostoma were characterized, for a total of 3,678 cytochrome b gene sequences. Results. When the genetic diversity of these populations was mapped, it highlighted differences among populations from the same species and between species with identical distribution areas. Factors shaping the contemporary patterns of genetic diversity were explored and the results revealed the role of latitude, inter-basin connectivity, migratory behaviour, species maximum size, species range and other species intrinsic traits in determining the genetic diversity of sampled populations. Contrastingly, drainage area and hydrological regime (permanent vs. temporary seem to have no significant effect on genetic diversity. Species intrinsic traits, maximum size attained, inter-basin connectivity and latitude explained over 30% of the haplotype diversity variance and, generally, the levels of diversity were significantly higher for smaller sized species, from connected and southerly river basins. Discussion. Targeting multiple co-distributed species of primary

Evaluating the role of reentrant output-to-input feedback in simultaneous pattern processing

Energy Technology Data Exchange (ETDEWEB)

Achler, Tsvi [Los Alamos National Laboratory

2010-01-01

Simultaneous Pattern Processing (SPP) is defined as the ability to identify simultaneous-intermixed patterns without isolating them individually (e.g. without separating each pattern in space and processing it individually). Enhanced SPP ability is beneficial for many real-life applications such as scene understanding, separating simultaneous voices, and identifying odorant or taste mixes. The first part of this work identifies how SPP scenarios are problematic to models which train synaptic connections or implement lateral inhibition and quantifies how subtle difficulties lead to complex combinatorial issues. The second part of this work proposes and tests an algorithm motivated by Ubiquitous re-entrant 'output to input' connections found throughout sensory processing regions of the brain. Through these connections the model proposes a dynamic gain mechanism that can provide functionality normally achieved through variable synaptic connections. The re-entrant structure combined with enhanced perfonnance suggests the brain may utilize this configuration for SPP flexibility.

Formal truncations of connected kernel equations

International Nuclear Information System (INIS)

Dixon, R.M.

1977-01-01

The Connected Kernel Equations (CKE) of Alt, Grassberger and Sandhas (AGS); Kouri, Levin and Tobocman (KLT); and Bencze, Redish and Sloan (BRS) are compared against reaction theory criteria after formal channel space and/or operator truncations have been introduced. The Channel Coupling Class concept is used to study the structure of these CKE's. The related wave function formalism of Sandhas, of L'Huillier, Redish and Tandy and of Kouri, Krueger and Levin are also presented. New N-body connected kernel equations which are generalizations of the Lovelace three-body equations are derived. A method for systematically constructing fewer body models from the N-body BRS and generalized Lovelace (GL) equations is developed. The formally truncated AGS, BRS, KLT and GL equations are analyzed by employing the criteria of reciprocity and two-cluster unitarity. Reciprocity considerations suggest that formal truncations of BRS, KLT and GL equations can lead to reciprocity-violating results. This study suggests that atomic problems should employ three-cluster connected truncations and that the two-cluster connected truncations should be a useful starting point for nuclear systems

Age-Related Changes in BOLD Activation Pattern in Phonemic Fluency Paradigm: An Investigation of Activation, Functional Connectivity and Psychophysiological Interactions.

Science.gov (United States)

La, Christian; Garcia-Ramos, Camille; Nair, Veena A; Meier, Timothy B; Farrar-Edwards, Dorothy; Birn, Rasmus; Meyerand, Mary E; Prabhakaran, Vivek

2016-01-01

Healthy aging is associated with decline of cognitive functions. However, even before those declines become noticeable, the neural architecture underlying those mechanisms has undergone considerable restructuring and reorganization. During performance of a cognitive task, not only have the task-relevant networks demonstrated reorganization with aging, which occurs primarily by recruitment of additional areas to preserve performance, but the task-irrelevant network of the "default-mode" network (DMN), which is normally deactivated during task performance, has also consistently shown reduction of this deactivation with aging. Here, we revisited those age-related changes in task-relevant (i.e., language system) and task-irrelevant (i.e., DMN) systems with a language production paradigm in terms of task-induced activation/deactivation, functional connectivity, and context-dependent correlations between the two systems. Our task fMRI data demonstrated a late increase in cortical recruitment in terms of extent of activation, only observable in our older healthy adult group, when compared to the younger healthy adult group, with recruitment of the contralateral hemisphere, but also other regions from the network previously underutilized. Our middle-aged individuals, when compared to the younger healthy adult group, presented lower levels of activation intensity and connectivity strength, with no recruitment of additional regions, possibly reflecting an initial, uncompensated, network decline. In contrast, the DMN presented a gradual decrease in deactivation intensity and deactivation extent (i.e., low in the middle-aged, and lower in the old) and similar gradual reduction of functional connectivity within the network, with no compensation. The patterns of age-related changes in the task-relevant system and DMN are incongruent with the previously suggested notion of anti-correlation of the two systems. The context-dependent correlation by psycho-physiological interaction

Automatic writer identification using connected-component contours and edge-based features of uppercase western script

NARCIS (Netherlands)

Schomaker, L; Bulacu, M

In this paper, a new technique for offline writer identification is presented, using connected-component contours (COCOCOs or CO(3)s) in uppercase handwritten samples. In our model, the writer is considered to be characterized by a stochastic pattern generator, producing a family of connected

Neural activation patterns and connectivity in visual attention during Number and Non-number processing: An ERP study using the Ishihara pseudoisochromatic plates.

Science.gov (United States)

Al-Marri, Faraj; Reza, Faruque; Begum, Tahamina; Hitam, Wan Hazabbah Wan; Jin, Goh Khean; Xiang, Jing

2017-10-25

Visual cognitive function is important to build up executive function in daily life. Perception of visual Number form (e.g., Arabic digit) and numerosity (magnitude of the Number) is of interest to cognitive neuroscientists. Neural correlates and the functional measurement of Number representations are complex occurrences when their semantic categories are assimilated with other concepts of shape and colour. Colour perception can be processed further to modulate visual cognition. The Ishihara pseudoisochromatic plates are one of the best and most common screening tools for basic red-green colour vision testing. However, there is a lack of study of visual cognitive function assessment using these pseudoisochromatic plates. We recruited 25 healthy normal trichromat volunteers and extended these studies using a 128-sensor net to record event-related EEG. Subjects were asked to respond by pressing Numbered buttons when they saw the Number and Non-number plates of the Ishihara colour vision test. Amplitudes and latencies of N100 and P300 event related potential (ERP) components were analysed from 19 electrode sites in the international 10-20 system. A brain topographic map, cortical activation patterns and Granger causation (effective connectivity) were analysed from 128 electrode sites. No major significant differences between N100 ERP components in either stimulus indicate early selective attention processing was similar for Number and Non-number plate stimuli, but Non-number plate stimuli evoked significantly higher amplitudes, longer latencies of the P300 ERP component with a slower reaction time compared to Number plate stimuli imply the allocation of attentional load was more in Non-number plate processing. A different pattern of asymmetric scalp voltage map was noticed for P300 components with a higher intensity in the left hemisphere for Number plate tasks and higher intensity in the right hemisphere for Non-number plate tasks. Asymmetric cortical activation

Harmonic Interaction Analysis in Grid Connected Converter using Harmonic State Space (HSS) Modeling

DEFF Research Database (Denmark)

Kwon, Jun Bum; Wang, Xiongfei; Bak, Claus Leth

2015-01-01

-model, are introduced to analyze these problems. However, it is found that Linear Time Invariant (LTI) base model analysis makes it difficult to analyze these phenomenon because of time varying system operation trajectories, varying output impedance seen by grid connected systems and neglected switching component......An increasing number of power electronics based Distributed Generation (DG) systems and loads generate coupled harmonic as well as non-characteristic harmonic with each other. Several methods like impedance based analysis, which is derived from conventional small signal- and average...... during the modeling process. This paper investigates grid connected converter by means of Harmonic State Space (HSS) small signal model, which is modeled from Linear Time varying Periodically (LTP) system. Further, a grid connected converter harmonic matrix is investigated to analyze the harmonic...

ICN_Atlas: Automated description and quantification of functional MRI activation patterns in the framework of intrinsic connectivity networks.

Science.gov (United States)

Kozák, Lajos R; van Graan, Louis André; Chaudhary, Umair J; Szabó, Ádám György; Lemieux, Louis

2017-12-01

Generally, the interpretation of functional MRI (fMRI) activation maps continues to rely on assessing their relationship to anatomical structures, mostly in a qualitative and often subjective way. Recently, the existence of persistent and stable brain networks of functional nature has been revealed; in particular these so-called intrinsic connectivity networks (ICNs) appear to link patterns of resting state and task-related state connectivity. These networks provide an opportunity of functionally-derived description and interpretation of fMRI maps, that may be especially important in cases where the maps are predominantly task-unrelated, such as studies of spontaneous brain activity e.g. in the case of seizure-related fMRI maps in epilepsy patients or sleep states. Here we present a new toolbox (ICN_Atlas) aimed at facilitating the interpretation of fMRI data in the context of ICN. More specifically, the new methodology was designed to describe fMRI maps in function-oriented, objective and quantitative way using a set of 15 metrics conceived to quantify the degree of 'engagement' of ICNs for any given fMRI-derived statistical map of interest. We demonstrate that the proposed framework provides a highly reliable quantification of fMRI activation maps using a publicly available longitudinal (test-retest) resting-state fMRI dataset. The utility of the ICN_Atlas is also illustrated on a parametric task-modulation fMRI dataset, and on a dataset of a patient who had repeated seizures during resting-state fMRI, confirmed on simultaneously recorded EEG. The proposed ICN_Atlas toolbox is freely available for download at http://icnatlas.com and at http://www.nitrc.org for researchers to use in their fMRI investigations. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Association Between Brain Activation and Functional Connectivity.

Science.gov (United States)

Tomasi, Dardo; Volkow, Nora D

2018-04-13

The origin of the "resting-state" brain activity recorded with functional magnetic resonance imaging (fMRI) is still uncertain. Here we provide evidence for the neurovascular origins of the amplitude of the low-frequency fluctuations (ALFF) and the local functional connectivity density (lFCD) by comparing them with task-induced blood-oxygen level dependent (BOLD) responses, which are considered a proxy for neuronal activation. Using fMRI data for 2 different tasks (Relational and Social) collected by the Human Connectome Project in 426 healthy adults, we show that ALFF and lFCD have linear associations with the BOLD response. This association was significantly attenuated by a novel task signal regression (TSR) procedure, indicating that task performance enhances lFCD and ALFF in activated regions. We also show that lFCD predicts BOLD activation patterns, as was recently shown for other functional connectivity metrics, which corroborates that resting functional connectivity architecture impacts brain activation responses. Thus, our findings indicate a common source for BOLD responses, ALFF and lFCD, which is consistent with the neurovascular origin of local hemodynamic synchrony presumably reflecting coordinated fluctuations in neuronal activity. This study also supports the development of task-evoked functional connectivity density mapping.

Analysis of changes in farm pond network connectivity in the peri-urban landscape of the Taoyuan area, Taiwan.

Science.gov (United States)

Huang, Shu-Li; Lee, Ying-Chieh; Budd, William W; Yang, Min-Chia

2012-04-01

The farm pond system for irrigation is the most prominent feature in the Taoyuan area, Taiwan, giving the region a unique landscape and hydrological character. Although this area had more than 3,290 ponds in the 1970s, fewer than 1,800 now remain. This study analyzes changes in irrigation farm ponds and the canal network landscape in the Taoyuan area. The spatial and temporal changes to ponds and the canal network on the Taoyuan plain were examined graphically for each spatial unit (2,765 m × 2,525 m) using aerial photographs for 1979 and 2005. Landscape metrics were calculated to analyze landscape change associated with increased urbanization. Landscape indices of connectivity and circuitry were utilized to describe changes in the configuration of ponds and canal networks. The total length of canals and total number of ponds in the study area decreased significantly during 1979-2005. The average values of connectivity indices (γ- and α-index) also decreased during 1979-2005, reflecting degradation of canal networks due to urban sprawl. A multivariate technique was applied to portion the study area into three zones according to changes to land cover, ponds, and canal networks. The effects of urban sprawl on the spatial pattern of ponds and canal networks are discussed.

Connectivity and dynamics of neuronal networks as defined by the shape of individual neurons

International Nuclear Information System (INIS)

Ahnert, Sebastian E; A N Travencolo, Bruno; Costa, Luciano da Fontoura

2009-01-01

Biological neuronal networks constitute a special class of dynamical systems, as they are formed by individual geometrical components, namely the neurons. In the existing literature, relatively little attention has been given to the influence of neuron shape on the overall connectivity and dynamics of the emerging networks. The current work addresses this issue by considering simplified neuronal shapes consisting of circular regions (soma/axons) with spokes (dendrites). Networks are grown by placing these patterns randomly in the two-dimensional (2D) plane and establishing connections whenever a piece of dendrite falls inside an axon. Several topological and dynamical properties of the resulting graph are measured, including the degree distribution, clustering coefficients, symmetry of connections, size of the largest connected component, as well as three hierarchical measurements of the local topology. By varying the number of processes of the individual basic patterns, we can quantify relationships between the individual neuronal shape and the topological and dynamical features of the networks. Integrate-and-fire dynamics on these networks is also investigated with respect to transient activation from a source node, indicating that long-range connections play an important role in the propagation of avalanches.

Research on Basis and Method of Fujian-Taiwan Cultural Creative Industry Connection

Directory of Open Access Journals (Sweden)

Li Hao

2016-01-01

Full Text Available deepening Fujian-Taiwan cultural creative industry connection cooperation is of great importance to close Fujian-Taiwan relationship, forge new economic growth points, optimize and adjust industrial structure. In this paper, the opportunities, potential, basis and conditions for Fujian-Taiwan cultural creative industry connection cooperation are analyzed, and countermeasures and suggestions to deepen the connection cooperation are proposed.

KEEFEKTIFAN MODEL CONNECTED DAN INTEGRATED DALAM PEMBELAJARAN IPS SMP DI KOTA YOGYAKARTA

Directory of Open Access Journals (Sweden)

Idrus idrus

2011-01-01

Full Text Available This research aimed to: (1 analyze the differences in social studies learning achievement between the students using connected and integrated models and those using conventional model; and (2 analyze the hierarchy of the effect of the learning models  among the connected, integrated, and conventional. This experimental research employed a matching post-test comparison group design. The population of this research was National Standardized Schools of Junior Secondary Schools in Yogyakarta. The technique used for sample drawing was multistage sampling. In this research, the independent variable was the learning model which consisted of three categories: integrated, connected, and conventional models. The dependent variable was the mean score of students’ learning achievement in social studies subject. Data collection was done by means of an achievement test. Instrument validation was done by discriminating power and difficulty index, while the reliability was calculated by KR-20. The pre-requisite  test included normality and homogeneity tests. The normality test used Kolmogorov-Smirnov and the homogeneity test used Levene Test. Data were analyzed in one way anova analysis and continued with Scheffe comparison test on the significance level of 0.05. The results of the experiment show that there are  significant difference among the students’ learning achievement who used integrated, connected, and conventional models. The continued test using Scheffe ensured that the integrated model was more effective than the connected and conventional models, while the connected model was more effective in improving the students’ learning achievement in social studies subject compared with the conventional model. Therefore, the hierarchy of the effect of the learning models is first the integrated model followed by connected and conventional models. Key words: Connected, Integrated Models, Social Studies Learning

Connecting the dots : Illusory pattern perception predicts belief in conspiracies and the supernatural

NARCIS (Netherlands)

van Prooijen, Jan Willem; Douglas, Karen M.; De Inocencio, Clara

A common assumption is that belief in conspiracy theories and supernatural phenomena are grounded in illusory pattern perception. In the present research we systematically tested this assumption. Study 1 revealed that such irrational beliefs are related to perceiving patterns in randomly generated

Modelling biomechanics of bark patterning in grasstrees.

Science.gov (United States)

Dale, Holly; Runions, Adam; Hobill, David; Prusinkiewicz, Przemyslaw

2014-09-01

Bark patterns are a visually important characteristic of trees, typically attributed to fractures occurring during secondary growth of the trunk and branches. An understanding of bark pattern formation has been hampered by insufficient information regarding the biomechanical properties of bark and the corresponding difficulties in faithfully modelling bark fractures using continuum mechanics. This study focuses on the genus Xanthorrhoea (grasstrees), which have an unusual bark-like structure composed of distinct leaf bases connected by sticky resin. Due to its discrete character, this structure is well suited for computational studies. A dynamic computational model of grasstree development was created. The model captures both the phyllotactic pattern of leaf bases during primary growth and the changes in the trunk's width during secondary growth. A biomechanical representation based on a system of masses connected by springs is used for the surface of the trunk, permitting the emergence of fractures during secondary growth to be simulated. The resulting fracture patterns were analysed statistically and compared with images of real trees. The model reproduces key features of grasstree bark patterns, including their variability, spanning elongated and reticulate forms. The patterns produced by the model have the same statistical character as those seen in real trees. The model was able to support the general hypothesis that the patterns observed in the grasstree bark-like layer may be explained in terms of mechanical fractures driven by secondary growth. Although the generality of the results is limited by the unusual structure of grasstree bark, it supports the hypothesis that bark pattern formation is primarily a biomechanical phenomenon.

YANA – a software tool for analyzing flux modes, gene-expression and enzyme activities

Directory of Open Access Journals (Sweden)

Engels Bernd

2005-06-01

Full Text Available Abstract Background A number of algorithms for steady state analysis of metabolic networks have been developed over the years. Of these, Elementary Mode Analysis (EMA has proven especially useful. Despite its low user-friendliness, METATOOL as a reliable high-performance implementation of the algorithm has been the instrument of choice up to now. As reported here, the analysis of metabolic networks has been improved by an editor and analyzer of metabolic flux modes. Analysis routines for expression levels and the most central, well connected metabolites and their metabolic connections are of particular interest. Results YANA features a platform-independent, dedicated toolbox for metabolic networks with a graphical user interface to calculate (integrating METATOOL, edit (including support for the SBML format, visualize, centralize, and compare elementary flux modes. Further, YANA calculates expected flux distributions for a given Elementary Mode (EM activity pattern and vice versa. Moreover, a dissection algorithm, a centralization algorithm, and an average diameter routine can be used to simplify and analyze complex networks. Proteomics or gene expression data give a rough indication of some individual enzyme activities, whereas the complete flux distribution in the network is often not known. As such data are noisy, YANA features a fast evolutionary algorithm (EA for the prediction of EM activities with minimum error, including alerts for inconsistent experimental data. We offer the possibility to include further known constraints (e.g. growth constraints in the EA calculation process. The redox metabolism around glutathione reductase serves as an illustration example. All software and documentation are available for download at http://yana.bioapps.biozentrum.uni-wuerzburg.de. Conclusion A graphical toolbox and an editor for METATOOL as well as a series of additional routines for metabolic network analyses constitute a new user

Method of measuring misalignment of welded threaded connections

Energy Technology Data Exchange (ETDEWEB)

Kasatkin, V I

1981-01-01

A method is presented for measuring misalignment of welded connections by special attachment, superposed indicator. Requirements are analyzed for welding the threaded sleeves established by specifications. It is shown that measurement of the slack only in one section on the selected base is insufficient for monitoring the geometry of the connected pipe parts. It is suggested that in order to evaluate the misalignment the concept of total slack be used and formulas are derived to define it.

Fill and spill drives runoff connectivity over frozen ground

Science.gov (United States)

Coles, A. E.; McDonnell, J. J.

2018-03-01

Snowmelt-runoff processes on frozen ground are poorly understood at the hillslope scale. This is especially true for hillslopes on the northern Great Plains of North America where long periods of snow-covered frozen ground with very shallow slopes mask any spatial patterns and process controls on connectivity and hillslope runoff generation. This study examines a 4.66 ha (46,600 m2) hillslope on the northern Great Plains during the 2014 spring snowmelt season to explore hillslope runoff processes. Specifically, we explore the spatial patterns of runoff production source areas and examine how surface topography and patterns of snow cover, snow water equivalent, soil water content, and thawed layer depth - which we measured on a 10 m grid across our 46,600 m2 hillslope - affect melt water partitioning and runoff connectivity. A key question was whether or not the controls on connectivity are consistent with the fill and spill mechanism found in rain-dominated and unfrozen soil domains. The contrast between the slow infiltration rates into frozen soil and the relatively fast rates of snowmelt delivery to the soil surface resulted in water accumulation in small depressions under the snowpack. Consequently, infiltration was minimal over the 12 day melt period. Instead, nested filling of micro- and meso-depressions was followed by macro-scale, whole-slope spilling. This spilling occurred when large patches of ponded water exceeded the storage capacity behind downslope micro barriers in the surface topography, and flows from them coalesced to drive a rapid increase in runoff at the hillslope outlet. These observations of ponded water and flowpaths followed mapable fill and spill locations based on 2 m resolution digital topographic analysis. Interestingly, while surface topography is relatively unimportant under unfrozen conditions at our site because of low relief and high infiltrability, surface topography shows episodically critical importance for connectivity and

Transient Aspects of Wave Propagation Connected with Spatial Coherence

Directory of Open Access Journals (Sweden)

Ezzat G. Bakhoum

2013-01-01

Full Text Available This study presents transient aspects of light wave propagation connected with spatial coherence. It is shown that reflection and refraction phenomena involve spatial patterns which are created within a certain transient time interval. After this transient time interval, these patterns act like a memory, determining the wave vector for subsequent sets of reflected/refracted waves. The validity of this model is based on intuitive aspects regarding phase conservation of energy for waves reflected/refracted by multiple centers in a certain material medium.

Intrinsic connectivity networks within cerebellum and beyond in eating disorders.

Science.gov (United States)

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

2013-10-01

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

Characteristics of flow in turbine-condenser connections

International Nuclear Information System (INIS)

Yasugahira, Norio; Sato, Takeshi; Mukai, Yasuteru; Otake, Katsumoto; Miyai, Masahiko

1981-01-01

It is important to save energy in thermal and nuclear power plants, and Hitachi Ltd. has exerted efforts on this subject. The performance of condensers depends largely on the condition of steam flow into the tube nests, and is affected by the state of steam flow in the connecting parts between LP turbines and the condensers. It is desirable to give turbines low exhaust pressure by minimizing the resistance of the obstacles in the diffuser paths and increasing the restoration of static pressure. But in the connecting parts, feed water heaters, bleeding pipes and stiffeners are placed, and if these re arranged inadequately, the performance of condensers and the efficiency of turbines are lowered by pressure loss. In this study, the flow in the connecting parts was reproduced with models, and the detailed state of internal flow was grasped. Also the influence of the form of the connecting parts, feed water heaters and bleeding pipes on pressure loss was examined, and the measures to reduce the pressure loss were sought. The cases of the connecting parts containing one feed water heater and four feed water heaters were examined. The experimental setup, the structure of the tested models, and the test results are reported. The velocity distribution and flow pattern of the internal flow were obtained, and the arrangement of feed water heaters which reduces pressure loss was clarified. (Kako, I.)

The Dissociative Subtype of Posttraumatic Stress Disorder: Unique Resting-State Functional Connectivity of Basolateral and Centromedial Amygdala Complexes.

Science.gov (United States)

Nicholson, Andrew A; Densmore, Maria; Frewen, Paul A; Théberge, Jean; Neufeld, Richard Wj; McKinnon, Margaret C; Lanius, Ruth A

2015-09-01

Previous studies point towards differential connectivity patterns among basolateral (BLA) and centromedial (CMA) amygdala regions in patients with posttraumatic stress disorder (PTSD) as compared with controls. Here we describe the first study to compare directly connectivity patterns of the BLA and CMA complexes between PTSD patients with and without the dissociative subtype (PTSD+DS and PTSD-DS, respectively). Amygdala connectivity to regulatory prefrontal regions and parietal regions involved in consciousness and proprioception were expected to differ between these two groups based on differential limbic regulation and behavioral symptoms. PTSD patients (n=49) with (n=13) and without (n=36) the dissociative subtype and age-matched healthy controls (n=40) underwent resting-state fMRI. Bilateral BLA and CMA connectivity patterns were compared using a seed-based approach via SPM Anatomy Toolbox. Among patients with PTSD, the PTSD+DS group exhibited greater amygdala functional connectivity to prefrontal regions involved in emotion regulation (bilateral BLA and left CMA to the middle frontal gyrus and bilateral CMA to the medial frontal gyrus) as compared with the PTSD-DS group. In addition, the PTSD+DS group showed greater amygdala connectivity to regions involved in consciousness, awareness, and proprioception-implicated in depersonalization and derealization (left BLA to superior parietal lobe and cerebellar culmen; left CMA to dorsal posterior cingulate and precuneus). Differences in amygdala complex connectivity to specific brain regions parallel the unique symptom profiles of the PTSD subgroups and point towards unique biological markers of the dissociative subtype of PTSD.

A new automatic analyzer for uranium determination

International Nuclear Information System (INIS)

Xia Buyun; Zhu Yaokun; Wang Bin; Cong Peiyan; Zhang Lan

1992-08-01

An intellectual automatic analyzer for uranium based on the principle of flow injection analysis (FIA) has been developed. It can directly determine the uranium solution in range of 0.02 to 500 mg/L without any pre-process. A chromatographic column with extractant, in which the trace uranium is concentrated and separated, has special ability to enrich uranium, is connected to the manifold of the analyzer. The analyzer is suited for trace uranium determination in varies samples. The 2-(5-bromo-2-pyridylazo)-5-diethyl-aminophenol (Br-PADAP) is used as color reagent. Uranium is determined in aqueous solution by adding cation surfactant, cetyl-pyridinium bromide (PCB). The rate of analysis is 30 to 90 samples per hour. The relative standard deviation of determination is 1% ∼ 2%. The analyzer has been used in factories and laboratory, and the results are satisfied. The determination range can easily be changed by using a multi-function auto-injection valve that changes the injection volume of the sample and channels. So, it could adopt varies FIA operation modes to meet the needs of FIA determination for other substance. The analyzer has universal functions

Successful group psychotherapy of depression in adolescents alters fronto-limbic resting-state connectivity.

Science.gov (United States)

Straub, J; Metzger, C D; Plener, P L; Koelch, M G; Groen, G; Abler, B

2017-02-01

Current resting state imaging findings support suggestions that the neural signature of depression and therefore also its therapy should be conceptualized as a network disorder rather than a dysfunction of specific brain regions. In this study, we compared neural connectivity of adolescent patients with depression (PAT) and matched healthy controls (HC) and analysed pre-to-post changes of seed-based network connectivities in PAT after participation in a cognitive behavioral group psychotherapy (CBT). 38 adolescents (30 female; 19 patients; 13-18 years) underwent an eyes-closed resting-state scan. PAT were scanned before (pre) and after (post) five sessions of CBT. Resting-state functional connectivity was analysed in a seed-based approach for right-sided amygdala and subgenual anterior cingulate cortex (sgACC). Symptom severity was assessed using the Beck Depression Inventory Revision (BDI-II). Prior to group CBT, between groups amygdala and sgACC connectivity with regions of the default mode network was stronger in the patients group relative to controls. Within the PAT group, a similar pattern significantly decreased after successful CBT. Conversely, seed-based connectivity with affective regions and regions processing cognition and salient stimuli was stronger in HC relative to PAT before CBT. Within the PAT group, a similar pattern changed with CBT. Changes in connectivity correlated with the significant pre-to-post symptom improvement, and pre-treatment amygdala connectivity predicted treatment response in depressed adolescents. Sample size and missing long-term follow-up limit the interpretability. Successful group psychotherapy of depression in adolescents involved connectivity changes in resting state networks to that of healthy controls. Copyright © 2016 Elsevier B.V. All rights reserved.

Darwinism for the Genomic Age: Connecting Mutation to Diversification.

Science.gov (United States)

Hua, Xia; Bromham, Lindell

2017-01-01

A growing body of evidence suggests that rates of diversification of biological lineages are correlated with differences in genome-wide mutation rate. Given that most research into differential patterns of diversification rate have focused on species traits or ecological parameters, a connection to the biochemical processes of genome change is an unexpected observation. While the empirical evidence for a significant association between mutation rate and diversification rate is mounting, there has been less effort in explaining the factors that mediate this connection between genetic change and species richness. Here we draw together empirical studies and theoretical concepts that may help to build links in the explanatory chain that connects mutation to diversification. First we consider the way that mutation rates vary between species. We then explore how differences in mutation rates have flow-through effects to the rate at which populations acquire substitutions, which in turn influences the speed at which populations become reproductively isolated from each other due to the acquisition of genomic incompatibilities. Since diversification rate is commonly measured from phylogenetic analyses, we propose a conceptual approach for relating events of reproductive isolation to bifurcations on molecular phylogenies. As we examine each of these relationships, we consider theoretical models that might shine a light on the observed association between rate of molecular evolution and diversification rate, and critically evaluate the empirical evidence for these links, focusing on phylogenetic comparative studies. Finally, we ask whether we are getting closer to a real understanding of the way that the processes of molecular evolution connect to the observable patterns of diversification.

Island connections: Icelandic spatiality in the wake of worldly linkages

Directory of Open Access Journals (Sweden)

David Bjarnason

2010-11-01

Full Text Available The notions and materiality of connections, through electronic networks as well as modes of mobility, play an ever-increasing role in how we define, understand, engage and experience the world we live in and the islands we live on. This article presents an account of Icelandic encounters with technologies of telecommunication and explores how electronic connections have participated in formulating a particularly connected, island spatiality. It is argued that an island can be regarded as a kind of connected laboratory suitable for studying how associations form around technologies of connections, which can be traced through various actors. For this purpose, the historical genealogy of connections and telecommunication in Iceland is analyzed, as well as more contemporary ideas and representations of mobile phone usage and network connectivity. It is maintained that connections have fundamentally altered the spatiality as well as representations of Iceland. While still an island in a geographical sense, and in that manner remote and isolated, the social space of the island now denies such connotations in many respects, valorizing the connectivity of Iceland and its people.

Influence of Connection Placement to the Behavior of Precast Concrete Exterior Beam-Column Joint

OpenAIRE

Elly Tjahjono; Heru Purnomo

2010-01-01

This paper presents an experimental study on the influence of connection placement to the behaviour of exterior beamcolumn joint of precast concrete structure under semi cyclic loading. Four half-scale beam-column specimens were investigated. Three beam-columns were jointed through connection that are placed in beam-column joint region and the forth is connected at the plastic hinge potensial region of the beam. Crack patterns, strength, stiffness and ductility of the test specimens have been...

Altered Insula Connectivity under MDMA.

Science.gov (United States)

Walpola, Ishan C; Nest, Timothy; Roseman, Leor; Erritzoe, David; Feilding, Amanda; Nutt, David J; Carhart-Harris, Robin L

2017-10-01

Recent work with noninvasive human brain imaging has started to investigate the effects of 3,4-methylenedioxymethamphetamine (MDMA) on large-scale patterns of brain activity. MDMA, a potent monoamine-releaser with particularly pronounced serotonin- releasing properties, has unique subjective effects that include: marked positive mood, pleasant/unusual bodily sensations and pro-social, empathic feelings. However, the neurobiological basis for these effects is not properly understood, and the present analysis sought to address this knowledge gap. To do this, we administered MDMA-HCl (100 mg p.o.) and, separately, placebo (ascorbic acid) in a randomized, double-blind, repeated-measures design with twenty-five healthy volunteers undergoing fMRI scanning. We then employed a measure of global resting-state functional brain connectivity and follow-up seed-to-voxel analysis to the fMRI data we acquired. Results revealed decreased right insula/salience network functional connectivity under MDMA. Furthermore, these decreases in right insula/salience network connectivity correlated with baseline trait anxiety and acute experiences of altered bodily sensations under MDMA. The present findings highlight insular disintegration (ie, compromised salience network membership) as a neurobiological signature of the MDMA experience, and relate this brain effect to trait anxiety and acutely altered bodily sensations-both of which are known to be associated with insular functioning.

Rapid change of field line connectivity and reconnection in stochastic magnetic fields

International Nuclear Information System (INIS)

Huang, Yi-Min; Bhattacharjee, A.; Boozer, Allen H.

2014-01-01

Magnetic fields without a direction of continuous symmetry have the generic feature that neighboring field lines exponentiate away from each other and become stochastic, and hence the ideal constraint of preserving magnetic field line connectivity becomes exponentially sensitive to small deviations from ideal Ohm's law. The idea of breaking field line connectivity by stochasticity as a mechanism for fast reconnection is tested with numerical simulations based on reduced magnetohydrodynamics equations with a strong guide field line-tied to two perfectly conducting end plates. Starting from an ideally stable force-free equilibrium, the system is allowed to undergo resistive relaxation. Two distinct phases are found in the process of resistive relaxation. During the quasi-static phase, rapid change of field line connectivity and strong induced flow are found in regions of high field line exponentiation. However, although the field line connectivity of individual field lines can change rapidly, the overall pattern of field line mapping appears to deform gradually. From this perspective, field line exponentiation appears to cause enhanced diffusion rather than reconnection. In some cases, resistive quasi-static evolution can cause the ideally stable initial equilibrium to cross a stability threshold, leading to formation of intense current filaments and rapid change of field line mapping into a qualitatively different pattern. It is in this onset phase that the change of field line connectivity is more appropriately designated as magnetic reconnection. Our results show that rapid change of field line connectivity appears to be a necessary, but not a sufficient condition for fast reconnection.

[Selection of distance thresholds of urban forest landscape connectivity in Shenyang City].

Science.gov (United States)

Liu, Chang-fu; Zhou, Bin; He, Xing-yuan; Chen, Wei

2010-10-01

By using the QuickBird remote sensing image interpretation data of urban forests in Shenyang City in 2006, and with the help of geographical information system, this paper analyzed the landscape patches of the urban forests in the area inside the third ring-road of Shenyang. Based on the habitat availability and the dispersal potential of animal and plant species, 8 distance thresholds (50, 100, 200, 400, 600, 800, 1000, and 1200 m) were selected to compute the integral index of connectivity, probability of connectivity, and important value of the landscape patches, and the computed values were used for analyzing and screening the distance thresholds of urban forest landscape connectivity in the City. The results showed that the appropriate distance thresholds of the urban forest landscape connectivity in Shenyang City in 2006 ranged from 100 to 400 m, with 200 m being most appropriate. It was suggested that the distance thresholds should be increased or decreased according to the performability of urban forest landscape connectivity and the different demands for landscape levels.

On optical detection of densely labeled synapses in neuropil and mapping connectivity with combinatorially multiplexed fluorescent synaptic markers.

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Yuriy Mishchenko

Full Text Available We propose a new method for mapping neural connectivity optically, by utilizing Cre/Lox system Brainbow to tag synapses of different neurons with random mixtures of different fluorophores, such as GFP, YFP, etc., and then detecting patterns of fluorophores at different synapses using light microscopy (LM. Such patterns will immediately report the pre- and post-synaptic cells at each synaptic connection, without tracing neural projections from individual synapses to corresponding cell bodies. We simulate fluorescence from a population of densely labeled synapses in a block of hippocampal neuropil, completely reconstructed from electron microscopy data, and show that high-end LM is able to detect such patterns with over 95% accuracy. We conclude, therefore, that with the described approach neural connectivity in macroscopically large neural circuits can be mapped with great accuracy, in scalable manner, using fast optical tools, and straightforward image processing. Relying on an electron microscopy dataset, we also derive and explicitly enumerate the conditions that should be met to allow synaptic connectivity studies with high-resolution optical tools.

Developmental Changes in Brain Network Hub Connectivity in Late Adolescence.

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Baker, Simon T E; Lubman, Dan I; Yücel, Murat; Allen, Nicholas B; Whittle, Sarah; Fulcher, Ben D; Zalesky, Andrew; Fornito, Alex

2015-06-17

The human brain undergoes substantial development throughout adolescence and into early adulthood. This maturational process is thought to include the refinement of connectivity between putative connectivity hub regions of the brain, which collectively form a dense core that enhances the functional integration of anatomically distributed, and functionally specialized, neural systems. Here, we used longitudinal diffusion magnetic resonance imaging to characterize changes in connectivity between 80 cortical and subcortical anatomical regions over a 2 year period in 31 adolescents between the ages of 15 and 19 years. Connectome-wide analysis indicated that only a small subset of connections showed evidence of statistically significant developmental change over the study period, with 8% and 6% of connections demonstrating decreased and increased structural connectivity, respectively. Nonetheless, these connections linked 93% and 90% of the 80 regions, respectively, pointing to a selective, yet anatomically distributed pattern of developmental changes that involves most of the brain. Hub regions showed a distinct tendency to be highly connected to each other, indicating robust "rich-club" organization. Moreover, connectivity between hubs was disproportionately influenced by development, such that connectivity between subcortical hubs decreased over time, whereas frontal-subcortical and frontal-parietal hub-hub connectivity increased over time. These findings suggest that late adolescence is characterized by selective, yet significant remodeling of hub-hub connectivity, with the topological organization of hubs shifting emphasis from subcortical hubs in favor of an increasingly prominent role for frontal hub regions. Copyright © 2015 the authors 0270-6474/15/359078-10$15.00/0.

Recommendation Systems for Geoscience Data Portals Built by Analyzing Usage Patterns

Science.gov (United States)

Crosby, C.; Nandigam, V.; Baru, C.

2009-04-01

Since its launch five years ago, the National Science Foundation-funded GEON Project (www.geongrid.org) has been providing access to a variety of geoscience data sets such as geologic maps and other geographic information system (GIS)-oriented data, paleontologic databases, gravity and magnetics data and LiDAR topography via its online portal interface. In addition to data, the GEON Portal also provides web-based tools and other resources that enable users to process and interact with data. Examples of these tools include functions to dynamically map and integrate GIS data, compute synthetic seismograms, and to produce custom digital elevation models (DEMs) with user defined parameters such as resolution. The GEON portal built on the Gridsphere-portal framework allows us to capture user interaction with the system. In addition to the site access statistics captured by tools like Google Analystics which capture hits per unit time, search key words, operating systems, browsers, and referring sites, we also record additional statistics such as which data sets are being downloaded and in what formats, processing parameters, and navigation pathways through the portal. With over four years of data now available from the GEON Portal, this record of usage is a rich resource for exploring how earth scientists discover and utilize online data sets. Furthermore, we propose that this data could ultimately be harnessed to optimize the way users interact with the data portal, design intelligent processing and data management systems, and to make recommendations on algorithm settings and other available relevant data. The paradigm of integrating popular and commonly used patterns to make recommendations to a user is well established in the world of e-commerce where users receive suggestions on books, music and other products that they may find interesting based on their website browsing and purchasing history, as well as the patterns of fellow users who have made similar

Systematic analysis of stability patterns in plant primary metabolism.

Directory of Open Access Journals (Sweden)

Dorothee Girbig

Full Text Available Metabolic networks are characterized by complex interactions and regulatory mechanisms between many individual components. These interactions determine whether a steady state is stable to perturbations. Structural kinetic modeling (SKM is a framework to analyze the stability of metabolic steady states that allows the study of the system Jacobian without requiring detailed knowledge about individual rate equations. Stability criteria can be derived by generating a large number of structural kinetic models (SK-models with randomly sampled parameter sets and evaluating the resulting Jacobian matrices. Until now, SKM experiments applied univariate tests to detect the network components with the largest influence on stability. In this work, we present an extended SKM approach relying on supervised machine learning to detect patterns of enzyme-metabolite interactions that act together in an orchestrated manner to ensure stability. We demonstrate its application on a detailed SK-model of the Calvin-Benson cycle and connected pathways. The identified stability patterns are highly complex reflecting that changes in dynamic properties depend on concerted interactions between several network components. In total, we find more patterns that reliably ensure stability than patterns ensuring instability. This shows that the design of this system is strongly targeted towards maintaining stability. We also investigate the effect of allosteric regulators revealing that the tendency to stability is significantly increased by including experimentally determined regulatory mechanisms that have not yet been integrated into existing kinetic models.

Heterotic reduction of Courant algebroid connections and Einstein–Hilbert actions

Energy Technology Data Exchange (ETDEWEB)

Jurčo, Branislav, E-mail: jurco@karlin.mff.cuni.cz [Mathematical Institute, Faculty of Mathematics and Physics, Charles University, Prague 186 75 (Czech Republic); Vysoký, Jan, E-mail: vysoky@math.cas.cz [Institute of Mathematics of the Czech Academy of Sciences, Žitná 25, Prague 115 67 (Czech Republic); Mathematical Sciences Institute, Australian National University, Acton ACT 2601 (Australia)

2016-08-15

We discuss Levi-Civita connections on Courant algebroids. We define an appropriate generalization of the curvature tensor and compute the corresponding scalar curvatures in the exact and heterotic case, leading to generalized (bosonic) Einstein–Hilbert type of actions known from supergravity. In particular, we carefully analyze the process of the reduction for the generalized metric, connection, curvature tensor and the scalar curvature.

Heterotic reduction of Courant algebroid connections and Einstein–Hilbert actions

International Nuclear Information System (INIS)

Jurčo, Branislav; Vysoký, Jan

2016-01-01

We discuss Levi-Civita connections on Courant algebroids. We define an appropriate generalization of the curvature tensor and compute the corresponding scalar curvatures in the exact and heterotic case, leading to generalized (bosonic) Einstein–Hilbert type of actions known from supergravity. In particular, we carefully analyze the process of the reduction for the generalized metric, connection, curvature tensor and the scalar curvature.

ANALYZING THE RELATIONSHIP BETWEEN MOVIES AND TV COMMERCIALS TYPES

Directory of Open Access Journals (Sweden)

Frank Van Der Valk

2017-09-01

Full Text Available The aim of this paper is to shed some light on whether there is any connection between the types of movies broadcasted on TV and types of commercials or not. A total of 20 different movies of Polish channels have been recorded and visually analyzed including the contents of the commercials broadcasted before, after and, during them. The different types of movies examined include comedies of manners, romantic comedies, thrillers, action movies, dramas, crimes, science-fiction and adventures. The research results show that there is a relationship between the types of movies broadcasted and the commercials before, during and after them. This connection is based on the needs and consuming behavior of each movie’s viewers.

Experimental study on the connection property of full-scale composite member

Science.gov (United States)

Panpan, Cao; Qing, Sun

2018-01-01

The excellent properties of composite result in its increasingly application in electric power construction, however there are less experimental studies on full-scale composite member connection property. Full-scale experiments of the connection property between E-glass fiber/epoxy reinforced polymer member and steel casing in practical engineering have been conducted. Based on the axial compression test of the designed specimens, the failure process and failure characteristics were observed, the load-displacement curves and strain distribution of the specimens were obtained. The finite element analysis was used to get the tensile connection strength of the component. The connection property of the components was analyzed to provide basis of the casing connection of GFRP application in practical engineering.

The connection between cellular mechanoregulation and tissue patterns during bone healing.

Science.gov (United States)

Repp, Felix; Vetter, Andreas; Duda, Georg N; Weinkamer, Richard

2015-09-01

The formation of different tissues in the callus during secondary bone healing is at least partly influenced by mechanical stimuli. We use computer simulations to test the consequences of different hypotheses of the mechanoregulation at the cellular level on the patterns of tissues formed during healing. The computational study is based on an experiment on sheep, where after a tibial osteotomy, histological sections were harvested at different time points. In the simulations, we used a recently proposed basic phenomenological model, which allows ossification to occur either via endochondral or intramembranous ossification, but tries otherwise to employ a minimal number of simulation parameters. The model was extended to consider also the possibility of bone resorption and consequently allowing a description of the full healing progression till the restoration of the cortex. Specifically, we investigated how three changes in the mechanoregulation influence the resulting tissue patterns: (1) a time delay between stimulation of the cell and the formation of the tissue, (2) a variable mechanosensitivity of the cells, and (3) an independence of long time intervals of the soft tissue maturation from the mechanical stimulus. For all three scenarios, our simulations do not show qualitative differences in the time development of the tissue patterns. Largest differences were observed in the intermediate phases of healing in the amount and location of the cartilage. Interestingly, the course of healing was virtually unaltered in case of scenario (3) where tissue maturation proceeded independent of mechanical stimulation.

The decrease in silicon concentration of the connective tissues with age in rats is a marker of connective tissue turnover.

Science.gov (United States)

Jugdaohsingh, Ravin; Watson, Abigail I E; Pedro, Liliana D; Powell, Jonathan J

2015-06-01

Silicon may be important for bone and connective tissue health. Higher concentrations of silicon are suggested to be associated with bone and the connective tissues, compared with the non-connective soft tissues. Moreover, in connective tissues it has been suggested that silicon levels may decrease with age based upon analyses of human aorta. These claims, however, have not been tested under controlled conditions. Here connective and non-connective tissues were collected and analysed for silicon levels from female Sprague-Dawley rats of different ages (namely, 3, 5, 8, 12, 26 and 43 weeks; n=8-10 per age group), all maintained on the same feed source and drinking water, and kept in the same environment from weaning to adulthood. Tissues (696 samples) were digested in nitric acid and analysed by inductively coupled plasma optical emission spectrometry for total silicon content. Fasting serum samples were also collected, diluted and analysed for silicon. Higher concentrations of silicon (up to 50-fold) were found associated with bone and the connective tissues compared with the non-connective tissues. Although total silicon content increased with age in all tissues, the highest connective tissue silicon concentrations (up to 9.98 μg/g wet weight) were found in young weanling rats, decreasing thereafter with age (by 2-6 fold). Fasting serum silicon concentrations reflected the pattern of connective tissue silicon concentrations and, both measures, when compared to collagen data from a prior experiment in Sprague-Dawley rats, mirrored type I collagen turnover with age. Our findings confirm the link between silicon and connective tissues and would imply that young growing rats have proportionally higher requirements for dietary silicon than mature adults, for bone and connective tissue development, although this was not formally investigated here. However, estimation of total body silicon content suggested that actual Si requirements may be substantially lower than

The decrease in silicon concentration of the connective tissues with age in rats is a marker of connective tissue turnover☆

Science.gov (United States)

Jugdaohsingh, Ravin; Watson, Abigail I.E.; Pedro, Liliana D.; Powell, Jonathan J.

2015-01-01

Silicon may be important for bone and connective tissue health. Higher concentrations of silicon are suggested to be associated with bone and the connective tissues, compared with the non-connective soft tissues. Moreover, in connective tissues it has been suggested that silicon levels may decrease with age based upon analyses of human aorta. These claims, however, have not been tested under controlled conditions. Here connective and non-connective tissues were collected and analysed for silicon levels from female Sprague–Dawley rats of different ages (namely, 3, 5, 8, 12, 26 and 43 weeks; n = 8–10 per age group), all maintained on the same feed source and drinking water, and kept in the same environment from weaning to adulthood. Tissues (696 samples) were digested in nitric acid and analysed by inductively coupled plasma optical emission spectrometry for total silicon content. Fasting serum samples were also collected, diluted and analysed for silicon. Higher concentrations of silicon (up to 50-fold) were found associated with bone and the connective tissues compared with the non-connective tissues. Although total silicon content increased with age in all tissues, the highest connective tissue silicon concentrations (up to 9.98 μg/g wet weight) were found in young weanling rats, decreasing thereafter with age (by 2–6 fold). Fasting serum silicon concentrations reflected the pattern of connective tissue silicon concentrations and, both measures, when compared to collagen data from a prior experiment in Sprague–Dawley rats, mirrored type I collagen turnover with age. Our findings confirm the link between silicon and connective tissues and would imply that young growing rats have proportionally higher requirements for dietary silicon than mature adults, for bone and connective tissue development, although this was not formally investigated here. However, estimation of total body silicon content suggested that actual Si requirements may be substantially

Connecting Network Properties of Rapidly Disseminating Epizoonotics

Science.gov (United States)

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

2012-01-01

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

Neural mechanism of activity spread in the cat motor cortex and its relation to the intrinsic connectivity

DEFF Research Database (Denmark)

Capaday, Charles; van Vreeswijk, Carl; Ethier, Christian

2011-01-01

NON TECHNICAL SUMMARY{NBSP}: The motor cortex (MCx) is an important brain region that initiates and controls voluntary movements. Neurons in MCx are anatomically connected by recurrent (feedback) networks. This connectivity pattern allows neurons to communicate reciprocally with each other potent...

Disrupted resting-state functional connectivity in minimally treated chronic schizophrenia.

Science.gov (United States)

Wang, Xijin; Xia, Mingrui; Lai, Yunyao; Dai, Zhengjia; Cao, Qingjiu; Cheng, Zhang; Han, Xue; Yang, Lei; Yuan, Yanbo; Zhang, Yong; Li, Keqing; Ma, Hong; Shi, Chuan; Hong, Nan; Szeszko, Philip; Yu, Xin; He, Yong

2014-07-01

The pathophysiology of chronic schizophrenia may reflect long term brain changes related to the disorder. The effect of chronicity on intrinsic functional connectivity patterns in schizophrenia without the potentially confounding effect of antipsychotic medications, however, remains largely unknown. We collected resting-state fMRI data in 21 minimally treated chronic schizophrenia patients and 20 healthy controls. We computed regional functional connectivity strength for each voxel in the brain, and further divided regional functional connectivity strength into short-range regional functional connectivity strength and long-range regional functional connectivity strength. General linear models were used to detect between-group differences in these regional functional connectivity strength metrics and to further systematically investigate the relationship between these differences and clinical/behavioral variables in the patients. Compared to healthy controls, the minimally treated chronic schizophrenia patients showed an overall reduced regional functional connectivity strength especially in bilateral sensorimotor cortex, right lateral prefrontal cortex, left insula and right lingual gyrus, and these regional functional connectivity strength decreases mainly resulted from disruption of short-range regional functional connectivity strength. The minimally treated chronic schizophrenia patients also showed reduced long-range regional functional connectivity strength in the bilateral posterior cingulate cortex/precuneus, and increased long-range regional functional connectivity strength in the right lateral prefrontal cortex and lingual gyrus. Notably, disrupted short-range regional functional connectivity strength mainly correlated with duration of illness and negative symptoms, whereas disrupted long-range regional functional connectivity strength correlated with neurocognitive performance. All of the results were corrected using Monte-Carlo simulation. This

Functional connectivity and structural covariance between regions of interest can be measured more accurately using multivariate distance correlation.

Science.gov (United States)

Geerligs, Linda; Cam-Can; Henson, Richard N

2016-07-15

Studies of brain-wide functional connectivity or structural covariance typically use measures like the Pearson correlation coefficient, applied to data that have been averaged across voxels within regions of interest (ROIs). However, averaging across voxels may result in biased connectivity estimates when there is inhomogeneity within those ROIs, e.g., sub-regions that exhibit different patterns of functional connectivity or structural covariance. Here, we propose a new measure based on "distance correlation"; a test of multivariate dependence of high dimensional vectors, which allows for both linear and non-linear dependencies. We used simulations to show how distance correlation out-performs Pearson correlation in the face of inhomogeneous ROIs. To evaluate this new measure on real data, we use resting-state fMRI scans and T1 structural scans from 2 sessions on each of 214 participants from the Cambridge Centre for Ageing & Neuroscience (Cam-CAN) project. Pearson correlation and distance correlation showed similar average connectivity patterns, for both functional connectivity and structural covariance. Nevertheless, distance correlation was shown to be 1) more reliable across sessions, 2) more similar across participants, and 3) more robust to different sets of ROIs. Moreover, we found that the similarity between functional connectivity and structural covariance estimates was higher for distance correlation compared to Pearson correlation. We also explored the relative effects of different preprocessing options and motion artefacts on functional connectivity. Because distance correlation is easy to implement and fast to compute, it is a promising alternative to Pearson correlations for investigating ROI-based brain-wide connectivity patterns, for functional as well as structural data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Altered patterns of directed connectivity within the reading network of dyslexic children and their relation to reading dysfluency

Directory of Open Access Journals (Sweden)

Gojko Žarić

2017-02-01

Full Text Available Reading is a complex cognitive skill subserved by a distributed network of visual and language-related regions. Disruptions of connectivity within this network have been associated with developmental dyslexia but their relation to individual differences in the severity of reading problems remains unclear. Here we investigate whether dysfunctional connectivity scales with the level of reading dysfluency by examining EEG recordings during visual word and false font processing in 9-year-old typically reading children (TR and two groups of dyslexic children: severely dysfluent (SDD and moderately dysfluent (MDD dyslexics. Results indicated weaker occipital to inferior-temporal connectivity for words in both dyslexic groups relative to TRs. Furthermore, SDDs exhibited stronger connectivity from left central to right inferior-temporal and occipital sites for words relative to TRs, and for false fonts relative to both MDDs and TRs. Importantly, reading fluency was positively related with forward and negatively with backward connectivity. Our results suggest disrupted visual processing of words in both dyslexic groups, together with a compensatory recruitment of right posterior brain regions especially in the SDDs during word and false font processing. Functional connectivity in the brain’s reading network may thus depend on the level of reading dysfluency beyond group differences between dyslexic and typical readers.

Structural connectivity asymmetry in the neonatal brain.

Science.gov (United States)

Ratnarajah, Nagulan; Rifkin-Graboi, Anne; Fortier, Marielle V; Chong, Yap Seng; Kwek, Kenneth; Saw, Seang-Mei; Godfrey, Keith M; Gluckman, Peter D; Meaney, Michael J; Qiu, Anqi

2013-07-15

Asymmetry of the neonatal brain is not yet understood at the level of structural connectivity. We utilized DTI deterministic tractography and structural network analysis based on graph theory to determine the pattern of structural connectivity asymmetry in 124 normal neonates. We tracted white matter axonal pathways characterizing interregional connections among brain regions and inferred asymmetry in left and right anatomical network properties. Our findings revealed that in neonates, small-world characteristics were exhibited, but did not differ between the two hemispheres, suggesting that neighboring brain regions connect tightly with each other, and that one region is only a few paths away from any other region within each hemisphere. Moreover, the neonatal brain showed greater structural efficiency in the left hemisphere than that in the right. In neonates, brain regions involved in motor, language, and memory functions play crucial roles in efficient communication in the left hemisphere, while brain regions involved in emotional processes play crucial roles in efficient communication in the right hemisphere. These findings suggest that even at birth, the topology of each cerebral hemisphere is organized in an efficient and compact manner that maps onto asymmetric functional specializations seen in adults, implying lateralized brain functions in infancy. Copyright © 2013 Elsevier Inc. All rights reserved.

Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models

KAUST Repository

Ting, Chee-Ming; Ombao, Hernando; Samdin, S. Balqis; Salleh, Sh-Hussain

2017-01-01

successfully identifies modular organization in resting-state networks in consistency with other studies. It further reveals changes in brain states with variations across subjects and distinct large-scale directed connectivity patterns across states.

A study to analyze the different patterns of quid usage among subjects with chewer′s mucosa

Directory of Open Access Journals (Sweden)

Saba Khan

2012-01-01

Full Text Available Aim: Betel chewer′s mucosa, although not considered as a potentially malignant lesion, has been suggested to be a precursor of oral submucous fibrosis (OSMF. Thus a study was undertaken to asses various quid chewing patterns in patients with chewer′s mucosa and to evaluate possible association between chewer′s mucosa and a particular quid usage patter. Materials and methods: The study was done on 150 subjects clinically diagnosed of having chewers mucosa lesion. After complete oral examination, a detailed habit history was taken through preformed questionnaire. The data obtained was analyzed using Chi-square test. Results: Among the 150 subjects males to female ratio was 8:2- Majority of the subjects were within the age group of 20 to 30 years and chewed a combination of betel leaf, arecanut, tobacco, lime- Majority of the subjects of chewer′s mucosa used the quid for a duration of 1 to 5 years, a frequency of three to five quid per day. Conclusion: In the present study, chewers mucosa was seen in majority of the subjects who used the quid for a duration of 1 to 5 years, a frequency of three to five quid per day and chewed the quid containing betel leaf, arecanut, tobacco, lime as its constituents.

Learning from correlated patterns by simple perceptrons

Energy Technology Data Exchange (ETDEWEB)

Shinzato, Takashi; Kabashima, Yoshiyuki [Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama 226-8502 (Japan)], E-mail: shinzato@sp.dis.titech.ac.jp, E-mail: kaba@dis.titech.ac.jp

2009-01-09

Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance.

Learning from correlated patterns by simple perceptrons

Science.gov (United States)

Shinzato, Takashi; Kabashima, Yoshiyuki

2009-01-01

Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance.

Learning from correlated patterns by simple perceptrons

International Nuclear Information System (INIS)

Shinzato, Takashi; Kabashima, Yoshiyuki

2009-01-01

Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance

Stable isotopes in barnacles as a tool to understand green sea turtle (Chelonia mydas) regional movement patterns

Science.gov (United States)

Detjen, M.; Sterling, E.; Gómez, A.

2015-12-01

Sea turtles are migratory animals that travel long distances between their feeding and breeding grounds. Traditional methods for researching sea turtle migratory behavior have important disadvantages, and the development of alternatives would enhance our ability to monitor and manage these globally endangered species. Here we report on the isotope signatures in green sea-turtle (Chelonia mydas) barnacles (Platylepas sp.) and discuss their potential relevance as tools with which to study green sea turtle migration and habitat use patterns. We analyzed oxygen (δ18O) and carbon (δ13C) isotope ratios in barnacle calcite layers from specimens collected from green turtles captured at the Palmyra Atoll National Wildlife Refuge (PANWR) in the central Pacific. Carbon isotopes were not informative in this study. However, the oxygen isotope results suggest likely regional movement patterns when mapped onto a predictive oxygen isotope map of the Pacific. Barnacle proxies could therefore complement other methods in understanding regional movement patterns, informing more effective conservation policy that takes into account connectivity between populations.

Outbreak patterns of the novel avian influenza (H7N9)

Science.gov (United States)

Pan, Ya-Nan; Lou, Jing-Jing; Han, Xiao-Pu

2014-05-01

The attack of novel avian influenza (H7N9) in East China caused a serious health crisis and public panic. In this paper, we empirically analyze the onset patterns of human cases of the novel avian influenza and observe several spatial and temporal properties that are similar to other infectious diseases. More specifically, using the empirical analysis and modeling studies, we find that the spatio-temporal network that connects the cities with human cases along the order of outbreak timing emerges two-regime-power-law edge-length distribution, indicating the picture that several islands with higher and heterogeneous risk straggle in East China. The proposed method is applicable to the analysis of the spreading situation in the early stage of disease outbreak using quite limited dataset.

Does resting-state connectivity reflect depressive rumination? A tale of two analyses.

Science.gov (United States)

Berman, Marc G; Misic, Bratislav; Buschkuehl, Martin; Kross, Ethan; Deldin, Patricia J; Peltier, Scott; Churchill, Nathan W; Jaeggi, Susanne M; Vakorin, Vasily; McIntosh, Anthony R; Jonides, John

2014-12-01

Major Depressive Disorder (MDD) is characterized by rumination. Prior research suggests that resting-state brain activation reflects rumination when depressed individuals are not task engaged. However, no study has directly tested this. Here we investigated whether resting-state epochs differ from induced ruminative states for healthy and depressed individuals. Most previous research on resting-state networks comes from seed-based analyses with the posterior cingulate cortex (PCC). By contrast, we examined resting state connectivity by using the complete multivariate connectivity profile (i.e., connections across all brain nodes) and by comparing these results to seeded analyses. We find that unconstrained resting-state intervals differ from active rumination states in strength of connectivity and that overall connectivity was higher for healthy vs. depressed individuals. Relationships between connectivity and subjective mood (i.e., behavior) were strongly observed during induced rumination epochs. Furthermore, connectivity patterns that related to subjective mood were strikingly different for MDD and healthy control (HC) groups suggesting different mood regulation mechanisms. Copyright © 2014 Elsevier Inc. All rights reserved.

Passivity Enhancement in Renewable Energy Source Based Power Plant With Paralleled Grid-Connected VSIs

DEFF Research Database (Denmark)

Bai, Haofeng; Wang, Xiongfei; Blaabjerg, Frede

2017-01-01

Harmonic instability is threatening the operation of renewable energy based power plants where multiple gridconnected VSIs are connected in parallel. To analyze and improve the stability of the grid-connected VSIs, the real part of the output admittance of the VSIs is first investigated......-connected VSIs can improve the stability of the renewable power plant....

Performance Evaluation of Moment Connections of Moment Resisting Frames Against Progressive Collapse

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M. Mahmoudi

2017-02-01

Full Text Available When a primary structural element fails due to sudden load such as explosion, the building undergoes progressive collapse. The method for design of moment connections during progressive collapse is different to seismic design of moment connections. Because in this case, the axial force on the connections makes it behave differently. The purpose of this paper is to evaluate the performance of a variety of moment connections in preventing progressive collapse in steel moment frames. To achieve this goal, three prequalified moment connections (BSEEP, BFP and WUP-W were designed according seismic codes. These moment connections were analyzed numerically using ABAQUS software for progressive collapse. The results show that the BFP connection (bolted flange plate has capacity much more than other connections because of the use of plates at the junction of beam-column.

Spatial assessment of landscape ecological connectivity in different urban gradient.

Science.gov (United States)

Park, Sohyun

2015-07-01

Urbanization has resulted in remnant natural patches within cities that often have no connectivity among themselves and to natural reserves outside the urban area. Protecting ecological connectivity in fragmented urban areas is becoming crucial in maintaining urban biodiversity and securing critical habitat levels and configurations under continual development pressures. Nevertheless, few studies have been undertaken for urban landscapes. This study aims to assess ecological connectivity for a group of species that represent the urban desert landscape in the Phoenix metropolitan area and to compare the connectivity values along the different urban gradient. A GIS-based landscape connectivity model which relies upon ecological connectivity index (ECI) was developed and applied to this region. A GIS-based concentric buffering technique was employed to delineate conceptual boundaries for urban, suburban, and rural zones. The research findings demonstrated that urban habitats and potential habitat patches would be significantly influenced by future urban development. Particularly, the largest loss of higher connectivity would likely to be anticipated in the "in-between areas" where urban, suburban, and rural zones overlap one another. The connectivity maps would be useful to provide spatial identification regarding connectivity patterns and vulnerability for urban and suburban activities in this area. This study provides planners and landscape architects with a spatial guidance to minimize ecological fragmentation, which ultimately leads to urban landscape sustainability. This study suggests that conventional planning practices which disregard the ecological processes in urban landscapes need to integrate landscape ecology into planning and design strategies.

Altered intrinsic and extrinsic connectivity in schizophrenia.

Science.gov (United States)

Zhou, Yuan; Zeidman, Peter; Wu, Shihao; Razi, Adeel; Chen, Cheng; Yang, Liuqing; Zou, Jilin; Wang, Gaohua; Wang, Huiling; Friston, Karl J

2018-01-01

Schizophrenia is a disorder characterized by functional dysconnectivity among distributed brain regions. However, it is unclear how causal influences among large-scale brain networks are disrupted in schizophrenia. In this study, we used dynamic causal modeling (DCM) to assess the hypothesis that there is aberrant directed (effective) connectivity within and between three key large-scale brain networks (the dorsal attention network, the salience network and the default mode network) in schizophrenia during a working memory task. Functional MRI data during an n-back task from 40 patients with schizophrenia and 62 healthy controls were analyzed. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes, we found that intrinsic (within-region) and extrinsic (between-region) effective connectivity involving prefrontal regions were abnormal in schizophrenia. Specifically, in patients (i) inhibitory self-connections in prefrontal regions of the dorsal attention network were decreased across task conditions; (ii) extrinsic connectivity between regions of the default mode network was increased; specifically, from posterior cingulate cortex to the medial prefrontal cortex; (iii) between-network extrinsic connections involving the prefrontal cortex were altered; (iv) connections within networks and between networks were correlated with the severity of clinical symptoms and impaired cognition beyond working memory. In short, this study revealed the predominance of reduced synaptic efficacy of prefrontal efferents and afferents in the pathophysiology of schizophrenia.

A low power Multi-Channel Analyzer

International Nuclear Information System (INIS)

Anderson, G.A.; Brackenbush, L.W.

1993-06-01

The instrumentation used in nuclear spectroscopy is generally large, is not portable, and requires a lot of power. Key components of these counting systems are the computer and the Multi-Channel Analyzer (MCA). To assist in performing measurements requiring portable systems, a small, very low power MCA has been developed at Pacific Northwest Laboratory (PNL). This MCA is interfaced with a Hewlett Packard palm top computer for portable applications. The MCA can also be connected to an IBM/PC for data storage and analysis. In addition, a real-time time display mode allows the user to view the spectra as they are collected

Neutral Evolution and Dispersal Limitation Produce Biogeographic Patterns in Microcystis aeruginosa Populations of Lake Systems.

Science.gov (United States)

Shirani, Sahar; Hellweger, Ferdi L

2017-08-01

Molecular observations reveal substantial biogeographic patterns of cyanobacteria within systems of connected lakes. An important question is the relative role of environmental selection and neutral processes in the biogeography of these systems. Here, we quantify the effect of genetic drift and dispersal limitation by simulating individual cyanobacteria cells using an agent-based model (ABM). In the model, cells grow (divide), die, and migrate between lakes. Each cell has a full genome that is subject to neutral mutation (i.e., the growth rate is independent of the genome). The model is verified by simulating simplified lake systems, for which theoretical solutions are available. Then, it is used to simulate the biogeography of the cyanobacterium Microcystis aeruginosa in a number of real systems, including the Great Lakes, Klamath River, Yahara River, and Chattahoochee River. Model output is analyzed using standard bioinformatics tools (BLAST, MAFFT). The emergent patterns of nucleotide divergence between lakes are dynamic, including gradual increases due to accumulation of mutations and abrupt changes due to population takeovers by migrant cells (coalescence events). The model predicted nucleotide divergence is heterogeneous within systems, and for weakly connected lakes, it can be substantial. For example, Lakes Superior and Michigan are predicted to have an average genomic nucleotide divergence of 8200 bp or 0.14%. The divergence between more strongly connected lakes is much lower. Our results provide a quantitative baseline for future biogeography studies. They show that dispersal limitation can be an important factor in microbe biogeography, which is contrary to the common belief, and could affect how a system responds to environmental change.

The Connection between Beauty and Morality in Kant's aesthetics

Directory of Open Access Journals (Sweden)

Ali salmani

2015-09-01

Full Text Available Abstract At first glance it seems that Kant distinguishes beauty from morality because while analyzing the matter of beauty according to quality, he explicitly separates pleasure of beauty from pleasure of agreeable and pleasure of good; and believes that the pleasure of the beauty is neither to satisfy our physical desires nor to achieve a moral purpose. On the other hand, Kant speaks of a connection between beauty and morality in some sections of his critique of judgment. This essay intends to study the mentioned sections and clarifies how one can distinguish beauty from morality and simultaneously believes in the connection between beauty and morality. Following this, we are going to discuss why Kant deems such a connection necessary. Examining this matter, we will find out that morality and aesthetics can be indirectly related to each other. Kant's most major concern with regard to the connection between beauty and morality is the connection between feelings and foredoom.

Low-frequency connectivity is associated with mild traumatic brain injury

Directory of Open Access Journals (Sweden)

B.T. Dunkley

2015-01-01

Full Text Available Mild traumatic brain injury (mTBI occurs from a closed-head impact. Often referred to as concussion, about 20% of cases complain of secondary psychological sequelae, such as disorders of attention and memory. Known as post-concussive symptoms (PCS, these problems can severely disrupt the patient's quality of life. Changes in local spectral power, particularly low-frequency amplitude increases and/or peak alpha slowing have been reported in mTBI, but large-scale connectivity metrics based on inter-regional amplitude correlations relevant for integration and segregation in functional brain networks, and their association with disorders in cognition and behaviour, remain relatively unexplored. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in a group with mTBI (n = 20, and a control group (n = 21. We observed a trend for atypical slow-wave power changes in subcortical, temporal and parietal regions in mTBI, as well as significant long-range increases in amplitude envelope correlations among deep-source, temporal, and frontal regions in the delta, theta, and alpha bands. Subsequently, we conducted an exploratory analysis of patterns of connectivity most associated with variability in secondary symptoms of mTBI, including inattention, anxiety, and depression. Differential patterns of altered resting state neurophysiological network connectivity were found across frequency bands. This indicated that multiple network and frequency specific alterations in large scale brain connectivity may contribute to overlapping cognitive sequelae in mTBI. In conclusion, we show that local spectral power content can be supplemented with measures of correlations in amplitude to define general networks that are atypical in mTBI, and suggest that certain cognitive difficulties are mediated by disturbances in a variety of alterations in network interactions which are differentially

Human brain networks in physiological aging: a graph theoretical analysis of cortical connectivity from EEG data.

Science.gov (United States)

Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria

2014-01-01

Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.

A series connection architecture for large-area organic photovoltaic modules with a 7.5% module efficiency.

Science.gov (United States)

Hong, Soonil; Kang, Hongkyu; Kim, Geunjin; Lee, Seongyu; Kim, Seok; Lee, Jong-Hoon; Lee, Jinho; Yi, Minjin; Kim, Junghwan; Back, Hyungcheol; Kim, Jae-Ryoung; Lee, Kwanghee

2016-01-05

The fabrication of organic photovoltaic modules via printing techniques has been the greatest challenge for their commercial manufacture. Current module architecture, which is based on a monolithic geometry consisting of serially interconnecting stripe-patterned subcells with finite widths, requires highly sophisticated patterning processes that significantly increase the complexity of printing production lines and cause serious reductions in module efficiency due to so-called aperture loss in series connection regions. Herein we demonstrate an innovative module structure that can simultaneously reduce both patterning processes and aperture loss. By using a charge recombination feature that occurs at contacts between electron- and hole-transport layers, we devise a series connection method that facilitates module fabrication without patterning the charge transport layers. With the successive deposition of component layers using slot-die and doctor-blade printing techniques, we achieve a high module efficiency reaching 7.5% with area of 4.15 cm(2).

Political connections, media monitoring and long-term loans

Institute of Scientific and Technical Information of China (English)

Deming; Yang; Zhengfei; Lu; Danglun; Luo

2014-01-01

We analyze data on Chinese non-state-listed firms and find that it is easier for firms with political connections to obtain long-term loans with extended debt maturities than it is for firms without political connections. Our investigation indicates that this phenomenon is significantly less common with increased media monitoring. Houston et al.(2011) find strong evidence that the state ownership of media is associated with higher levels of bank corruption in China, but our study shows that, to a certain extent, media monitoring can curb corruption.

Political connections, media monitoring and long-term loans

Directory of Open Access Journals (Sweden)

Deming Yang

2014-09-01

Full Text Available We analyze data on Chinese non-state-listed firms and find that it is easier for firms with political connections to obtain long-term loans with extended debt maturities than it is for firms without political connections. Our investigation indicates that this phenomenon is significantly less common with increased media monitoring. Houston et al. (2011 find strong evidence that the state ownership of media is associated with higher levels of bank corruption in China, but our study shows that, to a certain extent, media monitoring can curb corruption.

Vowel Patterns in Developmental Apraxia of Speech: Three Longitudinal Case Studies

Science.gov (United States)

Davis, Barbara L.; Jacks, Adam; Marquardt, Thomas P.

2005-01-01

Vowel inventories and error patterns for three children with suspected developmental apraxia of speech (DAS) were analysed over a 3-year period using phonetic transcriptions of connected speech samples. The children demonstrated complete English vowel inventories except for rhotics. However, accuracy of vowel targets in connected speech did not…

Numerical Study on the Behaviour of Reduced Beam Section Presence in Rectangular Concrete Filled Tubes Connection

Science.gov (United States)

Amalia, A. R.; Suswanto, B.; Kristijanto, H.; Irawan, D.

2018-01-01

This paper discusses about the behaviour of two types of RCFT column connections with steel beams due to cyclic loads using software based on finite element method ABAQUS 6.14. This comparison involves modelling RCFT connections with rigid connection that do not allow any deformation and rotation in the joint. There are two types of model to be compared: BB and BRBS which include RCFT connections to ordinary beam without RBS (BB) and to Reduce Beam Section Beam (BRBS). The models behaviour can be discussed in this study are stress value, von misses stress pattern and rotational degree of each model. From the von misses stress pattern value, it found that the highest regions of stress occurs in vicinity of beam flange near column face for connection without RBS (BB). For earthquake resistant building, that behaviour needs to be avoided because sudden collapse often happen in that joint connection. Moreover, the connection with the presence of RBS (BRBS), the highest regions of stress occurs in reduced beam section of the beam, it means that the failure might be happen as proposed plan. The ultimate force that can be restrained by BB model (402 kN) is higher than BRBS model (257,18 kN) because of reducing of flange area. BRBS model has higher rotation angle (0,057 rad) than BB model (0,045 rad). The analysis results also observed that cyclic performances of the moment connection with RBS (BRBS) were more ductile than the connection with ordinary beam (BB).

Connectivity-based parcellation of the human orbitofrontal cortex.

Science.gov (United States)

Kahnt, Thorsten; Chang, Luke J; Park, Soyoung Q; Heinzle, Jakob; Haynes, John-Dylan

2012-05-02

The primate orbitofrontal cortex (OFC) is involved in reward processing, learning, and decision making. Research in monkeys has shown that this region is densely connected with higher sensory, limbic, and subcortical regions. Moreover, a parcellation of the monkey OFC into two subdivisions has been suggested based on its intrinsic anatomical connections. However, in humans, little is known about any functional subdivisions of the OFC except for a rather coarse medial/lateral distinction. Here, we used resting-state fMRI in combination with unsupervised clustering techniques to investigate whether OFC subdivisions can be revealed based on their functional connectivity profiles with other brain regions. Examination of different cluster solutions provided support for a parcellation into two parts as observed in monkeys, but it also highlighted a much finer hierarchical clustering of the orbital surface. Specifically, we identified (1) a medial, (2) a posterior-central, (3) a central, and (4-6) three lateral clusters spanning the anterior-posterior gradient. Consistent with animal tracing studies, these OFC clusters were connected to other cortical regions such as prefrontal, temporal, and parietal cortices but also subcortical areas in the striatum and the midbrain. These connectivity patterns provide important implications for identifying specific functional roles of OFC subdivisions for reward processing, learning, and decision making. Moreover, this parcellation schema can provide guidance to report results in future studies.

Electricity transmission pricing: Tracing based point-of-connection tariff

International Nuclear Information System (INIS)

Abhyankar, A.R.; Khaparde, S.A.

2009-01-01

Point-of-connection (POC) scheme of transmission pricing in decentralized markets charges the participants a single rate per MW depending on their point-of-connection. Use of grossly aggregated postage stamp rates as POC charges fails to provide appropriate price signals. The POC tariff based on distribution of network sunk costs by employing conventional tracing assures recovery of sunk costs based on extent of use of network by participants. However, the POC tariff by this method does not accommodate economically efficient price signals which correspond to marginal costs. On the other hand, the POC tariff, if made proportional to marginal costs alone, fails to account for sunk costs and extent of use of network. This paper overcomes these lacunae by combining the above stated desired objectives under the recently proposed optimal tracing framework. Since real power tracing problem is amenable to multiple solutions, it is formulated as linearly constrained optimization problem. By employing this methodology, consideration of extent of network use and sunk cost recovery are guaranteed, while objective function is designed such that the spatial pattern of price signals closely follows the pattern of scaled locational marginal prices. The methodology is tested on IEEE 30 bus system, wherein average power flow pattern is established by running various simulation states on congested and un-congested network conditions. (author)

Reduced beta band connectivity during number estimation in autism

Directory of Open Access Journals (Sweden)

Katrin A. Bangel

2014-01-01

Full Text Available Recent evidence suggests that disruption of integrative processes in sensation and perception may play a critical role in cognitive and behavioural atypicalities characteristic of ASD. In line with this, ASD is associated with altered structural and functional brain connectivity and atypical patterns of inter-regional communication which have been proposed to contribute to cognitive difficulties prevalent in this group. The present MEG study used atlas-guided source space analysis of inter-regional phase synchronization in ASD participants, as well as matched typically developing controls, during a dot number estimation task. This task included stimuli with globally integrated forms (animal shapes as well as randomly-shaped stimuli which lacked a coherent global pattern. Early task-dependent increases in inter-regional phase synchrony in theta, alpha and beta frequency bands were observed. Reduced long-range beta-band phase synchronization was found in participants with ASD at 70–145 ms during presentation of globally coherent dot patterns. This early reduction in task-dependent inter-regional connectivity encompassed numerous areas including occipital, parietal, temporal, and frontal lobe regions. These results provide the first evidence for inter-regional phase synchronization during numerosity estimation, as well as its alteration in ASD, and suggest that problems with communication among brain areas may contribute to difficulties with integrative processes relevant to extraction of meaningful ‘Gestalt’ features in this population.

Influence of Connection Placement to the Behavior of Precast Concrete Exterior Beam-Column Joint

Directory of Open Access Journals (Sweden)

Elly Tjahjono

2010-10-01

Full Text Available This paper presents an experimental study on the influence of connection placement to the behaviour of exterior beamcolumn joint of precast concrete structure under semi cyclic loading. Four half-scale beam-column specimens were investigated. Three beam-columns were jointed through connection that are placed in beam-column joint region and the forth is connected at the plastic hinge potensial region of the beam. Crack patterns, strength, stiffness and ductility of the test specimens have been evaluated. The test result indicated that all beam-column specimens show good ductility behavior.

Comparison of Marginal Bone Loss Between Implants with Internal and External Connections: A Systematic Review.

Science.gov (United States)

Palacios-Garzón, Natalia; Mauri-Obradors, Elisabeth; Roselló-LLabrés, Xavier; Estrugo-Devesa, Albert; Jané-Salas, Enric; López-López, José

The objective of this systematic review was to compare the loss of marginal bone between implants with internal and external connections by analyzing results reported in studies published after 2010. A literature search in MEDLINE with the keywords "dental implant connections, external internal implant connection, bone loss implant designs, internal and external connection implant studies in humans" was conducted. Clinical trials on human beings, comparing both connections and published in English, from 2010 to 2016 were selected. Their methodologic quality was assessed using the Jadad scale. From the initial search, 415 articles were obtained; 32 were chosen as potentially relevant based on their titles and abstracts. Among them, only 10 finally met the inclusion criteria. A total of 1,523 patients with 3,965 implants were analyzed. Six out of 10 studies observed that internal connections showed significantly less bone loss compared with external connections. The remaining four articles did not find statistically significant differences between the two connections. According to this systematic review and considering its limitation due to the degree of heterogeneity between the included studies, both internal and external connections present high survival rates. To assess whether marginal bone loss differs significantly between the two connections, more homogenous clinical studies are needed with identical implant characteristics, larger samples, and longer follow-up periods. Studies included in this review and characterized by long-term follow-ups showed that the external connection is a reliable connection on a long-term basis.

Patterns of Knowledge Construction

Science.gov (United States)

Chang, Bo

2018-01-01

The purpose of this study was to identify knowledge construction patterns in a local learning community. Observation, documents, and semistructured interviews were employed to collect data. Twenty learners were interviewed. Data were analyzed inductively using the constant comparative method. Five major patterns--radiation, circulation,…

Humanly space objects-Perception and connection with the observer

Science.gov (United States)

Balint, Tibor S.; Hall, Ashley

2015-05-01

Expanding humanity into space is an inevitable step in our quest to explore our world. Yet space exploration is costly, and the awaiting environment challenges us with extreme cold, heat, vacuum and radiation, unlike anything encountered on Earth. Thus, the few pioneers who experience it needed to be well protected throughout their spaceflight. The resulting isolation heightens the senses and increases the desire to make humanly connections with any other perceived manifestation of life. Such connections may occur via sensory inputs, namely vision, touch, sound, smell, and taste. This then follows the process of sensing, interpreting, and recognizing familiar patterns, or learning from new experiences. The desire to connect could even transfer to observed objects, if their movements and characteristics trigger the appropriate desires from the observer. When ordered in a familiar way, for example visual stimuli from lights and movements of an object, it may create a perceived real bond with an observer, and evoke the feeling of surprise when the expected behavior changes to something no longer predictable or recognizable. These behavior patterns can be designed into an object and performed autonomously in front of an observer, in our case an astronaut. The experience may introduce multiple responses, including communication, connection, empathy, order, and disorder. While emotions are clearly evoked in the observer and may seem one sided, in effect the object itself provides a decoupled bond, connectivity and communication between the observer and the artist-designer of the object. In this paper we will discuss examples from the field of arts and other domains, including robotics, where human perception through object interaction was explored, and investigate the starting point for new innovative design concepts and future prototype designs, that extend these experiences beyond the boundaries of Earth, while taking advantage of remoteness and the zero gravity

Connectivity of the hippocampus and Broca's area during acquisition of a novel grammar.

Science.gov (United States)

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

2018-01-15

Following Opitz and Friederici (2003) suggesting interactions of the hippocampal system and the prefrontal cortex as the neural mechanism underlying novel grammar learning, the present fMRI study investigated functional connectivity of bilateral BA 44/45 and the hippocampus during an artificial grammar learning (AGL) task. Our results, contrary to the previously reported interactions, demonstrated parallel (but separate) contributions of both regions, each with their own interactions, to the process of novel grammar acquisition. The functional connectivity pattern of Broca's area pointed to the importance of coherent activity of left frontal areas around the core language processing region for successful grammar learning. Furthermore, connectivity patterns of left and right hippocampi (predominantly with occipital areas) were found to be a strong predictor of high performance on the task. Finally, increasing functional connectivity over time of both left and right BA 44/45 with the right posterior cingulate cortex and the right temporo-parietal areas points to the importance of multimodal and attentional processes supporting novel grammar acquisition. Moreover, it highlights the right-hemispheric involvement in initial stages of L2 learning. These latter interactions were found to operate irrespective of the task performance, making them an obligatory mechanism accompanying novel grammar learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Hydrological connectivity for riverine fish: measurement challenges and research opportunities

Science.gov (United States)

Fullerton, A.H.; Burnett, K.M.; Steel, E.A.; Flitcroft, R.L.; Pess, G.R.; Feist, B.E.; Torgersen, Christian E.; Miller, D.J.; Sanderson, B.L.

2010-01-01

) incorporating network structure and river discharge into analyses; (ii) increasing explicit consideration of temporal complexity and fish behaviour in the scope of analyses; and (iii) parsing degrees of human and natural influences on connectivity and defining acceptable alterations. Multiscale analyses are most likely to identify dominant patterns of connections and disconnections, and the appropriate scale at which to focus conservation activities.

Quantifying Riverscape Connectivity with Graph Theory

Science.gov (United States)

Carbonneau, P.; Milledge, D.; Sinha, R.; Tandon, S. K.

2013-12-01

connectivity structure of the Gangetic riverscape with fluvial remote sensing. Our study reach extends from the heavily dammed headwaters of the Bhagirathi, Mandakini and Alaknanda rivers which form the source of the Ganga to Allahabad ~900 km downstream on the main stem. We use Landsat-8 imagery as the baseline dataset. Channel width along the Ganga (i.e. Ganges) is often several kilometres. Therefore, the pan-sharpened 15m pixels of Landsat-8 are in fact capable of resolving inner channel features for over 80% of the channel length thus allowing a riverscape approach to be adopted. We examine the following connectivity metrics: size distribution of connected components, betweeness centrality and the integrated index of connectivity. A geographic perspective is added by mapping local (25 km-scale) values for these metrics in order to examine spatial patterns of connectivity. This approach allows us to map impacts of dam construction and has the potential to inform policy decisions in the area as well as open-up new avenues of investigation.

Behavior of Reinforced Hybrid Concrete Corbel-Column Connection with Vertical Construction Joint

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Ammar Yasir Ali

2017-03-01

Full Text Available In this paper, shear behavior of reinforced hybrid concrete connection of corbel-column is experimentally investigated. Nine homogenous and hybrid concrete corbel-column connections subjected to vertical applied loads were constructed and tested within two test groups (A, B. The experimental program included the effect of several variables such as type of hybrid concrete;high strength concrete (HSC or steel fiber reinforced concrete (SFRC, monolithic casting of hybrid concrete connection, and presence of construction joint at the interface of corbel-column. Experimental results showed significant effects of concrete hybridization on the structural behavior of connection specimens such as: ultimate strength, cracking loads, cracking patterns, and failure modes. Hybridization process in group (A included hybrid connection of corbel-column with HSC or SFRC corbel instated of NSC. This process led to increase the capacity of connection by (26%, 38% and shear cracking loads by (20%, 120% respectively. Moreover, connections of hybrid concrete corbels cast monolithically improved the shear capacity of corbels by (19%, 42% for HSC or SFRC respectively. In group (B, presence of construction joint at connection region reduced the shear capacity of connectionsby (10% to 22% and cracking loads by (23%-62% compared with connections cast monolithically.

OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis.

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Koush, Yury; Ashburner, John; Prilepin, Evgeny; Sladky, Ronald; Zeidman, Peter; Bibikov, Sergei; Scharnowski, Frank; Nikonorov, Artem; De Ville, Dimitri Van

2017-08-01

Neurofeedback based on real-time functional magnetic resonance imaging (rt-fMRI) is a novel and rapidly developing research field. It allows for training of voluntary control over localized brain activity and connectivity and has demonstrated promising clinical applications. Because of the rapid technical developments of MRI techniques and the availability of high-performance computing, new methodological advances in rt-fMRI neurofeedback become possible. Here we outline the core components of a novel open-source neurofeedback framework, termed Open NeuroFeedback Training (OpenNFT), which efficiently integrates these new developments. This framework is implemented using Python and Matlab source code to allow for diverse functionality, high modularity, and rapid extendibility of the software depending on the user's needs. In addition, it provides an easy interface to the functionality of Statistical Parametric Mapping (SPM) that is also open-source and one of the most widely used fMRI data analysis software. We demonstrate the functionality of our new framework by describing case studies that include neurofeedback protocols based on brain activity levels, effective connectivity models, and pattern classification approaches. This open-source initiative provides a suitable framework to actively engage in the development of novel neurofeedback approaches, so that local methodological developments can be easily made accessible to a wider range of users. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Path connectivity based spectral defragmentation in flexible bandwidth networks.

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

2013-01-28

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

Integrated analysis and visualization of group differences in structural and functional brain connectivity: Applications in typical ageing and schizophrenia

NARCIS (Netherlands)

C.D. Langen (Carolyn); T.J.H. White (Tonya); M.A. Ikram (Arfan); M.W. Vernooij (Meike); W.J. Niessen (Wiro)

2015-01-01

textabstractStructural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uniand bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of

Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity : Applications in Typical Ageing and Schizophrenia

NARCIS (Netherlands)

Langen, C.D.; White, T.; Ikram, M.A.; Vernooij, M.W.; Niessen, W.J.

2015-01-01

Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of

Three dysconnectivity patterns in treatment-resistant schizophrenia patients and their unaffected siblings.

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Wang, Jicai; Cao, Hongbao; Liao, Yanhui; Liu, Weiqing; Tan, Liwen; Tang, Yanqing; Chen, Jindong; Xu, Xiufeng; Li, Haijun; Luo, Chunrong; Liu, Chunyu; Ries Merikangas, Kathleen; Calhoun, Vince; Tang, Jinsong; Shugart, Yin Yao; Chen, Xiaogang

2015-01-01

Among individuals diagnosed with schizophrenia, approximately 20%-33% are recognized as treatment-resistant schizophrenia (TRS) patients. These TRS patients suffer more severely from the disease but struggle to benefit from existing antipsychotic treatments. A few recent studies suggested that schizophrenia may be caused by impaired synaptic plasticity that manifests as functional dysconnectivity in the brain, however, few of those studies focused on the functional connectivity changes in the brains of TRS groups. In this study, we compared the whole brain connectivity variations in TRS patients, their unaffected siblings, and healthy controls. Connectivity network features between and within the 116 automated anatomical labeling (AAL) brain regions were calculated and compared using maps created with three contrasts: patient vs. control, patient vs. sibling, and sibling vs. To evaluate the predictive power of the selected features, we performed a multivariate classification approach. We also evaluated the influence of six important clinical measures (e.g. age, education level) on the connectivity features. This study identified abnormal significant connectivity changes of three patterns in TRS patients and their unaffected siblings: 1) 69 patient-specific connectivity (PCN); 2) 102 shared connectivity (SCN); and 3) 457 unshared connectivity (UCN). While the first two patterns were widely reported by previous non-TRS specific studies, we were among the first to report widespread significant connectivity differences between TRS patient groups and their healthy sibling groups. Observations of this study may provide new insights for the understanding of the neurophysiological mechanisms of TRS.

Thermodynamics of complexity and pattern manipulation

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Garner, Andrew J. P.; Thompson, Jayne; Vedral, Vlatko; Gu, Mile

2017-04-01

Many organisms capitalize on their ability to predict the environment to maximize available free energy and reinvest this energy to create new complex structures. This functionality relies on the manipulation of patterns—temporally ordered sequences of data. Here, we propose a framework to describe pattern manipulators—devices that convert thermodynamic work to patterns or vice versa—and use them to build a "pattern engine" that facilitates a thermodynamic cycle of pattern creation and consumption. We show that the least heat dissipation is achieved by the provably simplest devices, the ones that exhibit desired operational behavior while maintaining the least internal memory. We derive the ultimate limits of this heat dissipation and show that it is generally nonzero and connected with the pattern's intrinsic crypticity—a complexity theoretic quantity that captures the puzzling difference between the amount of information the pattern's past behavior reveals about its future and the amount one needs to communicate about this past to optimally predict the future.

Social network models predict movement and connectivity in ecological landscapes

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

2011-01-01

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

Social network models predict movement and connectivity in ecological landscapes.

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

2011-11-29

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

On Data Transfers Over Wide-Area Dedicated Connections

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Rao, Nageswara S. [ORNL; Liu, Qiang [ORNL

2018-01-01

Dedicated wide-area network connections are employed in big data and high-performance computing scenarios, since the absence of cross-traffic promises to make it easier to analyze and optimize data transfers over them. However, nonlinear transport dynamics and end-system complexity due to multi-core hosts and distributed file systems make these tasks surprisingly challenging. We present an overview of methods to analyze memory and disk file transfers using extensive measurements over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory transfers, we derive performance profiles of TCP and UDT throughput as a function of RTT, which show concave regions in contrast to entirely convex regions predicted by previous models. These highly desirable concave regions can be expanded by utilizing large buffers and more parallel flows. We also present Poincar´e maps and Lyapunov exponents of TCP and UDT throughputtraces that indicate complex throughput dynamics. For disk file transfers, we show that throughput can be optimized using a combination of parallel I/O and network threads under direct I/O mode. Our initial throughput measurements of Lustre filesystems mounted over long-haul connections using LNet routers show convex profiles indicative of I/O limits.

Analyzing Local Spatio-Temporal Patterns of Police Calls-for-Service Using Bayesian Integrated Nested Laplace Approximation

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Hui Luan

2016-09-01

Full Text Available This research investigates spatio-temporal patterns of police calls-for-service in the Region of Waterloo, Canada, at a fine spatial and temporal resolution. Modeling was implemented via Bayesian Integrated Nested Laplace Approximation (INLA. Temporal patterns for two-hour time periods, spatial patterns at the small-area scale, and space-time interaction (i.e., unusual departures from overall spatial and temporal patterns were estimated. Temporally, calls-for-service were found to be lowest in the early morning (02:00–03:59 and highest in the evening (20:00–21:59, while high levels of calls-for-service were spatially located in central business areas and in areas characterized by major roadways, universities, and shopping centres. Space-time interaction was observed to be geographically dispersed during daytime hours but concentrated in central business areas during evening hours. Interpreted through the routine activity theory, results are discussed with respect to law enforcement resource demand and allocation, and the advantages of modeling spatio-temporal datasets with Bayesian INLA methods are highlighted.

Mapping the changed hubs and corresponding functional connectivity in idiopathic restless legs syndrome.

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Liu, Chunyan; Wang, Jiaojian; Hou, Yue; Qi, Zhigang; Wang, Li; Zhan, Shuqin; Wang, Rong; Wang, Yuping

2018-05-01

The hubs of the brain network play a key role in integrating and transferring information between different functional modules. However, whether the changed pattern in functional network hubs contributes to the onset of leg discomfort symptoms in restless legs syndrome (RLS) patients remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory methods, we investigated whether alterations of hubs can be detected in RLS. First, we constructed the whole-brain voxelwise functional connectivity and calculated a functional connectivity strength (FCS) map in each of 16 drug-naive idiopathic RLS patients and 26 gender- and age-matched healthy control (HC) subjects. Next, a two-sample t test was applied to compare the FCS maps between HC and RLS patients, and to identify significant changes in FCS in RLS patients. To further elucidate the corresponding changes in the functional connectivity patterns of the aberrant hubs in RLS patients, whole-brain resting-state functional connectivity analyses for the hub areas were performed. The hub analysis revealed decreased FCS in the cuneus, fusiform gyrus, paracentral lobe, and precuneus, and increased FCS in the superior frontal gyrus and thalamus in idiopathic drug-naive RLS patients. Subsequent functional connectivity analyses revealed decreased functional connectivity in sensorimotor and visual processing networks and increased functional connectivity in the affective cognitive network and cerebellar-thalamic circuit. Furthermore, the mean FCS value in the superior frontal gyrus was significantly correlated with Hamilton Anxiety Rating Scale scores in RLS patients, and the mean FCS value in the fusiform gyrus was significantly correlated with Hamilton Depression Rating Scale scores. These findings may provide novel insight into the pathophysiology of RLS. Copyright © 2018 Elsevier B.V. All rights reserved.

CoverageAnalyzer (CAn: A Tool for Inspection of Modification Signatures in RNA Sequencing Profiles

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Ralf Hauenschild

2016-11-01

Full Text Available Combination of reverse transcription (RT and deep sequencing has emerged as a powerful instrument for the detection of RNA modifications, a field that has seen a recent surge in activity because of its importance in gene regulation. Recent studies yielded high-resolution RT signatures of modified ribonucleotides relying on both sequence-dependent mismatch patterns and reverse transcription arrests. Common alignment viewers lack specialized functionality, such as filtering, tailored visualization, image export and differential analysis. Consequently, the community will profit from a platform seamlessly connecting detailed visual inspection of RT signatures and automated screening for modification candidates. CoverageAnalyzer (CAn was developed in response to the demand for a powerful inspection tool. It is freely available for all three main operating systems. With SAM file format as standard input, CAn is an intuitive and user-friendly tool that is generally applicable to the large community of biomedical users, starting from simple visualization of RNA sequencing (RNA-Seq data, up to sophisticated modification analysis with significance-based modification candidate calling.

Synchrony, waves and ripple in spatially coupled Kuramoto oscillators with Mexican hat connectivity.

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Heitmann, Stewart; Ermentrout, G Bard

2015-06-01

Spatiotemporal waves of synchronized activity are known to arise in oscillatory neural networks with lateral inhibitory coupling. How such patterns respond to dynamic changes in coupling strength is largely unexplored. The present study uses analysis and simulation to investigate the evolution of wave patterns when the strength of lateral inhibition is varied dynamically. Neural synchronization was modeled by a spatial ring of Kuramoto oscillators with Mexican hat lateral coupling. Broad bands of coexisting stable wave solutions were observed at all levels of inhibition. The stability of these waves was formally analyzed in both the infinite ring and the finite ring. The broad range of multi-stability predicted hysteresis in transitions between neighboring wave solutions when inhibition is slowly varied. Numerical simulation confirmed the predicted transitions when inhibition was ramped down from a high initial value. However, non-wave solutions emerged from the uniform solution when inhibition was ramped upward from zero. These solutions correspond to spatially periodic deviations of phase that we call ripple states. Numerical continuation showed that stable ripple states emerge from synchrony via a supercritical pitchfork bifurcation. The normal form of this bifurcation was derived analytically, and its predictions compared against the numerical results. Ripple states were also found to bifurcate from wave solutions, but these were locally unstable. Simulation also confirmed the existence of hysteresis and ripple states in two spatial dimensions. Our findings show that spatial synchronization patterns can remain structurally stable despite substantial changes in network connectivity.

Age-Related Difference in Functional Brain Connectivity of Mastication

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Lin, Chia-shu; Wu, Ching-yi; Wu, Shih-yun; Lin, Hsiao-Han; Cheng, Dong-hui; Lo, Wen-liang

2017-01-01

The age-related decline in motor function is associated with changes in intrinsic brain signatures. Here, we investigated the functional connectivity (FC) associated with masticatory performance, a clinical index evaluating general masticatory function. Twenty-six older adults (OA) and 26 younger (YA) healthy adults were recruited and assessed using the masticatory performance index (MPI) and resting-state functional magnetic resonance imaging (rs-fMRI). We analyzed the rs-fMRI FC network related to mastication, which was constructed based on 12 bilateral mastication-related brain regions according to the literature. For the OA and the YA group, we identified the mastication-related hubs, i.e., the nodes for which the degree centrality (DC) was positively correlated with the MPI. For each pair of nodes, we identified the inter-nodal link for which the FC was positively correlated with the MPI. The network analysis revealed that, in the YA group, the FC between the sensorimotor cortex, the thalamus (THA) and the cerebellum was positively correlated with the MPI. Consistently, the cerebellum nodes were defined as the mastication-related hubs. In contrast, in the OA group, we found a sparser connection within the sensorimotor regions and cerebellum and a denser connection across distributed regions, including the FC between the superior parietal lobe (SPL), the anterior insula (aINS) and the dorsal anterior cingulate cortex (dACC). Compared to the YA group, the network of the OA group also comprised more mastication-related hubs, which were spatially distributed outside the sensorimotor regions, including the right SPL, the right aINS, and the bilateral dACC. In general, the findings supported the hypothesis that in OA, higher masticatory performance is associated with a widespread pattern of mastication-related hubs. Such a widespread engagement of multiple brain regions associated with the MPI may reflect an increased demand in sensorimotor integration, attentional

Using Multi-Temporal Remote Sensing Data to Analyze the Spatio-Temporal Patterns of Dry Season Rice Production in Bangladesh

Science.gov (United States)

Shew, A. M.; Ghosh, A.

2017-10-01

Remote sensing in the optical domain is widely used in agricultural monitoring; however, such initiatives pose a challenge for developing countries due to a lack of high quality in situ information. Our proposed methodology could help developing countries bridge this gap by demonstrating the potential to quantify patterns of dry season rice production in Bangladesh. To analyze approximately 90,000 km2 of cultivated land in Bangladesh at 30 m spatial resolution, we used two decades of remote sensing data from the Landsat archive and Google Earth Engine (GEE), a cloud-based geospatial data analysis platform built on Google infrastructure and capable of processing petabyte-scale remote sensing data. We reconstructed the seasonal patterns of vegetation indices (VIs) for each pixel using a harmonic time series (HTS) model, which minimizes the effects of missing observations and noise. Next, we combined the seasonality information of VIs with our knowledge of rice cultivation systems in Bangladesh to delineate rice areas in the dry season, which are predominantly hybrid and High Yielding Varieties (HYV). Based on historical Landsat imagery, the harmonic time series of vegetation indices (HTS-VIs) model estimated 4.605 million ha, 3.519 million ha, and 4.021 million ha of rice production for Bangladesh in 2005, 2010, and 2015 respectively. Fine spatial scale information on HYV rice over the last 20 years will greatly improve our understanding of double-cropped rice systems, current status of production, and potential for HYV rice adoption in Bangladesh during the dry season.

Monitoring, analyzing and simulating of spatial-temporal changes of landscape pattern over mining area

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Liu, Pei; Han, Ruimei; Wang, Shuangting

2014-11-01

According to the merits of remotely sensed data in depicting regional land cover and Land changes, multi- objective information processing is employed to remote sensing images to analyze and simulate land cover in mining areas. In this paper, multi-temporal remotely sensed data were selected to monitor the pattern, distri- bution and trend of LUCC and predict its impacts on ecological environment and human settlement in mining area. The monitor, analysis and simulation of LUCC in this coal mining areas are divided into five steps. The are information integration of optical and SAR data, LULC types extraction with SVM classifier, LULC trends simulation with CA Markov model, landscape temporal changes monitoring and analysis with confusion matrixes and landscape indices. The results demonstrate that the improved data fusion algorithm could make full use of information extracted from optical and SAR data; SVM classifier has an efficient and stable ability to obtain land cover maps, which could provide a good basis for both land cover change analysis and trend simulation; CA Markov model is able to predict LULC trends with good performance, and it is an effective way to integrate remotely sensed data with spatial-temporal model for analysis of land use / cover change and corresponding environmental impacts in mining area. Confusion matrixes are combined with landscape indices to evaluation and analysis show that, there was a sustained downward trend in agricultural land and bare land, but a continues growth trend tendency in water body, forest and other lands, and building area showing a wave like change, first increased and then decreased; mining landscape has undergone a from small to large and large to small process of fragmentation, agricultural land is the strongest influenced landscape type in this area, and human activities are the primary cause, so the problem should be pay more attentions by government and other organizations.

Using circuit theory to model connectivity in ecology, evolution, and conservation.

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McRae, Brad H; Dickson, Brett G; Keitt, Timothy H; Shah, Viral B

2008-10-01

Connectivity among populations and habitats is important for a wide range of ecological processes. Understanding, preserving, and restoring connectivity in complex landscapes requires connectivity models and metrics that are reliable, efficient, and process based. We introduce a new class of ecological connectivity models based in electrical circuit theory. Although they have been applied in other disciplines, circuit-theoretic connectivity models are new to ecology. They offer distinct advantages over common analytic connectivity models, including a theoretical basis in random walk theory and an ability to evaluate contributions of multiple dispersal pathways. Resistance, current, and voltage calculated across graphs or raster grids can be related to ecological processes (such as individual movement and gene flow) that occur across large population networks or landscapes. Efficient algorithms can quickly solve networks with millions of nodes, or landscapes with millions of raster cells. Here we review basic circuit theory, discuss relationships between circuit and random walk theories, and describe applications in ecology, evolution, and conservation. We provide examples of how circuit models can be used to predict movement patterns and fates of random walkers in complex landscapes and to identify important habitat patches and movement corridors for conservation planning.

The effects of habitat connectivity and regional heterogeneity on artificial pond metacommunities.

Science.gov (United States)

Pedruski, Michael T; Arnott, Shelley E

2011-05-01

Habitat connectivity and regional heterogeneity represent two factors likely to affect biodiversity across different spatial scales. We performed a 3 × 2 factorial design experiment to investigate the effects of connectivity, heterogeneity, and their interaction on artificial pond communities of freshwater invertebrates at the local (α), among-community (β), and regional (γ) scales. Despite expectations that the effects of connectivity would depend on levels of regional heterogeneity, no significant interactions were found for any diversity index investigated at any spatial scale. While observed responses of biodiversity to connectivity and heterogeneity depended to some extent on the diversity index and spatial partitioning formula used, the general pattern shows that these factors largely act at the β scale, as opposed to the α or γ scales. We conclude that the major role of connectivity in aquatic invertebrate communities is to act as a homogenizing force with relatively little effect on diversity at the α or γ levels. Conversely, heterogeneity acts as a force maintaining differences between communities.

What Hold us Together? Analyzing Biotech Field Formation

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Jackeline Amantino de Andrade

2011-03-01

Full Text Available This article proposes to analyze the formation of biotechnological field bringing actor-network theory’s lens as contribution. Based on conclusions of studies developed by Walter Powell and colleagues it was held a research to analyze the diversity of institutional relations that are active by hemophilia therapies, the principle of generalized symmetry adopted for actor-network theory is highlight to identify how socio-technical associations are assembled. Besides the interorganizational relations, research’s findings indicate the scientific and technological contents have a significant mediating role to create and sustain those connections of knowledge. So, it is emphasized the need of a boarder theoretical discussion to enlarge explanations about the dynamics of organizational fields as well as innovation processes.