989 resultados para K-connectivity


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Objectives - The absence of pathophysiologically relevant diagnostic markers of bipolar disorder (BD) leads to its frequent misdiagnosis as unipolar depression (UD). We aimed to determine whether whole brain white matter connectivity differentiated BD from UD depression. Methods - We employed a three-way analysis of covariance, covarying for age, to examine whole brain fractional anisotropy (FA), and corresponding longitudinal and radial diffusivity, in currently depressed adults: 15 with BD-type I (mean age 36.3 years, SD 12.0 years), 16 with recurrent UD (mean age 32.3 years, SD 10.0 years), and 24 healthy control adults (HC) (mean age 29.5 years, SD 9.43 years). Depressed groups did not differ in depression severity, age of illness onset, and illness duration. Results - There was a main effect of group in left superior and inferior longitudinal fasciculi (SLF and ILF) (all F = 9.8; p = .05, corrected). Whole brain post hoc analyses (all t = 4.2; p = .05, corrected) revealed decreased FA in left SLF in BD, versus UD adults in inferior temporal cortex and, versus HC, in primary sensory cortex (associated with increased radial and decreased longitudinal diffusivity, respectively); and decreased FA in left ILF in UD adults versus HC. A main effect of group in right uncinate fasciculus (in orbitofrontal cortex) just failed to meet significance in all participants but was present in women. Post hoc analyses revealed decreased right uncinate fasciculus FA in all and in women, BD versus HC. Conclusions - White matter FA in left occipitotemporal and primary sensory regions supporting visuospatial and sensory processing differentiates BD from UD depression. Abnormally reduced FA in right fronto-temporal regions supporting mood regulation, might underlie predisposition to depression in BD. These measures might help differentiate pathophysiologic processes of BD versus UD depression.

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Although atypical social behaviour remains a key characterisation of ASD, the presence ofsensory and perceptual abnormalities has been given a more central role in recentclassification changes. An understanding of the origins of such aberrations could thus prove afruitful focus for ASD research. Early neurocognitive models of ASD suggested that thestudy of high frequency activity in the brain as a measure of cortical connectivity mightprovide the key to understanding the neural correlates of sensory and perceptual deviations inASD. As our review shows, the findings from subsequent research have been inconsistent,with a lack of agreement about the nature of any high frequency disturbances in ASD brains.Based on the application of new techniques using more sophisticated measures of brainsynchronisation, direction of information flow, and invoking the coupling between high andlow frequency bands, we propose a framework which could reconcile apparently conflictingfindings in this area and would be consistent both with emerging neurocognitive models ofautism and with the heterogeneity of the condition.

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The concept of a stock of fish as a management unit has been around for well over a hundred years, and this has formed the basis for fisheries science. Methods for delimiting stocks have advanced considerably over recent years, including genetic, telemetric, tagging, geochemical and phenotypic information. In parallel with these developments, concepts in population ecology such as meta-population dynamics and connectivity have advanced. The pragmatic view of stocks has always accepted some mixing during spawning, feeding and/or larval drift. Here we consider the mismatch between ecological connectivity of a matrix of populations typically focussed on demographic measurements, and genetic connectivity of populations that focus on genetic exchange detected using modern molecular approaches. We suggest that from an ecological-connectivity perspective populations can be delimited as management units if there is limited exchange during recruitment or via migration in most years. From a genetic-connectivity perspective such limited exchange can maintain panmixia. We use case-studies of species endangered by overexploitation and/or habitat degradation to show how current methods of stock delimitation can help in managing populations and in conservation.

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The concept of a stock of fish as a management unit has been around for well over a hundred years, and this has formed the basis for fisheries science. Methods for delimiting stocks have advanced considerably over recent years, including genetic, telemetric, tagging, geochemical and phenotypic information. In parallel with these developments, concepts in population ecology such as meta-population dynamics and connectivity have advanced. The pragmatic view of stocks has always accepted some mixing during spawning, feeding and/or larval drift. Here we consider the mismatch between ecological connectivity of a matrix of populations typically focussed on demographic measurements, and genetic connectivity of populations that focus on genetic exchange detected using modern molecular approaches. We suggest that from an ecological-connectivity perspective populations can be delimited as management units if there is limited exchange during recruitment or via migration in most years. From a genetic-connectivity perspective such limited exchange can maintain panmixia. We use case-studies of species endangered by overexploitation and/or habitat degradation to show how current methods of stock delimitation can help in managing populations and in conservation.

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The organizational and architectural configuration of white matter pathways connecting brain regions has ramifications for all facets of the human condition, including manifestations of incipient neurodegeneration. Although diffusion tensor imaging (DTI) has been used extensively to visualize white matter connectivity, due to the widespread presence of crossing fibres, the lateral projections of the corpus callosum are not normally detected using this methodology. Detailed knowledge of the transcallosal connectivity of the human cortical motor network has therefore remained elusive. We employed constrained spherical deconvolution (CSD) tractography - an approach that is much less susceptible to the influence of crossing fibres, in order to derive complete in-vivo characterizations of white matter pathways connecting specific motor cortical regions to their counterparts and other loci in the opposite hemisphere. The revealed patterns of connectivity closely resemble those derived from anatomical tracing in primates. It was established that dorsal premotor cortex (PMd) and supplementary motor area (SMA) have extensive interhemispheric connectivity - exhibiting both dense homologous projections, and widespread structural relations with every other region in the contralateral motor network. Through this in-vivo portrayal, the importance of non-primary motor regions for interhemispheric communication is emphasized. Additionally, distinct connectivity profiles were detected for the anterior and posterior subdivisions of primary motor cortex. The present findings provide a comprehensive representation of transcallosal white matter projections in humans, and have the potential to inform the development of models and hypotheses relating structural and functional brain connectivity.

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We examine a non-cooperative model of network formation where players may stop functioning with a given probability. When this happens all the links associated with this player are no longer available in the network. In the model, players receive benefits from connecting directly and indirectly to other agents in the network through costly links. We identify conditions under which a Nash network will remain connected after the loss of k nodes by introducing the notion of k-Node Super Connectivity network. We identify similar conditions for efficient networks as well.

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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, 2016. © 2016 Wiley Periodicals, Inc.

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The Raman spectra at 77 K of the hydroxyl stretching of kaolinite were obtained along the three axes perpendicular to the crystal faces. Raman bands were observed at 3616, 3658 and 3677 cm−1 together with a distinct band observed at 3691 cm−1 and a broad profile between 3695 and 3715 cm−1. The band at 3616 cm−1 is assigned to the inner hydroxyl. The bands at 3658 and 3677 cm−1 are attributed to the out-of-phase vibrations of the inner surface hydroxyls. The Raman spectra of the in-phase vibrations of the inner-surface hydroxyl-stretching region are described in terms of transverse and longitudinal optic splitting. The band at 3691 cm−1 is assigned to the transverse optic and the broad profile to the longitudinal optic mode. This splitting remained even at liquid nitrogen temperature. The transverse optic vibration may be curve resolved into two or three bands, which are attributed to different types of hydroxyl groups in the kaolinite.

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We introduce K-tree in an information retrieval context. It is an efficient approximation of the k-means clustering algorithm. Unlike k-means it forms a hierarchy of clusters. It has been extended to address issues with sparse representations. We compare performance and quality to CLUTO using document collections. The K-tree has a low time complexity that is suitable for large document collections. This tree structure allows for efficient disk based implementations where space requirements exceed that of main memory.

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The K-Adv has been developed around the concept that it comprises an ICT enabling infrastructure that encompasses ICT hardware and software infrastructure facilities together with an enabling ICT support system; a leadership infrastructure support system that provides the vision for its implementation and the realisation capacity for the vision to be realised; and the necessary people infrastructure that includes the people capabilities and capacities supported by organisational processes that facilitates this resource to be mobilised.