1000 resultados para Vol spatial


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Elderly individuals display a rapid age-related increase in intraindividual variability (IIV) of their performances. This phenomenon could reflect subtle changes in frontal lobe integrity. However, structural studies in this field are still missing. To address this issue, we computed an IIV index for a simple reaction time (RT) task and performed magnetic resonance imaging (MRI) including voxel based morphometry (VBM) and the tract based spatial statistics (TBSS) analysis of diffusion tensor imaging (DTI) in 61 adults aged from 22 to 88 years. The age-related IIV increase was associated with decreased fractional anisotropy (FA) as well as increased radial (RD) and mean (MD) diffusion in the main white matter (WM) fiber tracts. In contrast, axial diffusion (AD) and grey matter (GM) densities did not show any significant correlation with IIV. In multivariate models, only FA has an age-independent effect on IIV. These results revealed that WM but not GM changes partly mediated the age-related increase of IIV. They also revealed that the association between WM and IIV could not be only attributed to the damage of frontal lobe circuits but concerned the majority of interhemispheric and intrahemispheric corticocortical connections.

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This study was designed to assess sex-related differences in the selection of an appropriate strategy when facing novelty. A simple visuo-spatial task was used to investigate exploratory behavior as a specific response to novelty. The exploration task was followed by a visual discrimination task, and the responses were analyzed using signal detection theory. During exploration women selected a local searching strategy in which the metric distance between what is already known and what is unknown was reduced, whereas men adopted a global strategy based on an approximately uniform distribution of choices. Women's exploratory behavior gives rise to a notion of a secure base warranting a sense of safety while men's behavior does not appear to be influenced by risk. This sex-related difference was interpreted as a difference in beliefs concerning the likelihood of uncertain events influencing risk evaluation. Keywords: exploration, spontaneous strategies, sex differences, decision-making.

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Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presenceonly evaluators to usual presence/absence measures. We use a reliable, diverse, presence/absence dataset of 114 plant species to test how common presence/absence indices (Kappa, MaxKappa, AUC, adjusted D-2) compare to presenceonly measures (AVI, CVI, Boyce index) for evaluating generalised linear models (GLM). Moreover we propose a new, threshold-independent evaluator, which we call "continuous Boyce index". All indices were implemented in the B10MAPPER software. We show that the presence-only evaluators are fairly correlated (p > 0.7) to the presence/absence ones. The Boyce indices are closer to AUC than to MaxKappa and are fairly insensitive to species prevalence. In addition, the Boyce indices provide predicted-toexpected ratio curves that offer further insights into the model quality: robustness, habitat suitability resolution and deviation from randomness. This information helps reclassifying predicted maps into meaningful habitat suitability classes. The continuous Boyce index is thus both a complement to usual evaluation of presence/absence models and a reliable measure of presence-only based predictions.

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We use numerical simulations to investigate how the chain length and topology of freely fluctuating knotted polymer rings affect their various spatial characteristics such as the radius of the smallest sphere enclosing momentary configurations of simulated polymer chains. We describe how the average value of a characteristic changes with the chain size and how this change depends on the topology of the modeled polymers. Although the scaling profiles of a spatial characteristic for distinct knot types do not intersect (at least, in the range of our data), the profiles for nontrivial knots intersect the corresponding profile obtained for phantom polymers, i.e., those that are free to explore all available topological states. For each knot type, this point of intersection defines its equilibrium length with respect to the spatial characteristic. At this chain length, a polymer forming a given knot type will not tend to increase or decrease. on average, the value of the spatial characteristic when the polymer is released from its topological constraint. We show interrelations between equilibrium lengths defined with respect to spatial characteristics of different character and observe that they are related to the lengths of ideal geometric configurations of the corresponding knot types.

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Predictive species distribution modelling (SDM) has become an essential tool in biodiversity conservation and management. The choice of grain size (resolution) of environmental layers used in modelling is one important factor that may affect predictions. We applied 10 distinct modelling techniques to presence-only data for 50 species in five different regions, to test whether: (1) a 10-fold coarsening of resolution affects predictive performance of SDMs, and (2) any observed effects are dependent on the type of region, modelling technique, or species considered. Results show that a 10 times change in grain size does not severely affect predictions from species distribution models. The overall trend is towards degradation of model performance, but improvement can also be observed. Changing grain size does not equally affect models across regions, techniques, and species types. The strongest effect is on regions and species types, with tree species in the data sets (regions) with highest locational accuracy being most affected. Changing grain size had little influence on the ranking of techniques: boosted regression trees remain best at both resolutions. The number of occurrences used for model training had an important effect, with larger sample sizes resulting in better models, which tended to be more sensitive to grain. Effect of grain change was only noticeable for models reaching sufficient performance and/or with initial data that have an intrinsic error smaller than the coarser grain size.

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Oscillations have been increasingly recognized as a core property of neural responses that contribute to spontaneous, induced, and evoked activities within and between individual neurons and neural ensembles. They are considered as a prominent mechanism for information processing within and communication between brain areas. More recently, it has been proposed that interactions between periodic components at different frequencies, known as cross-frequency couplings, may support the integration of neuronal oscillations at different temporal and spatial scales. The present study details methods based on an adaptive frequency tracking approach that improve the quantification and statistical analysis of oscillatory components and cross-frequency couplings. This approach allows for time-varying instantaneous frequency, which is particularly important when measuring phase interactions between components. We compared this adaptive approach to traditional band-pass filters in their measurement of phase-amplitude and phase-phase cross-frequency couplings. Evaluations were performed with synthetic signals and EEG data recorded from healthy humans performing an illusory contour discrimination task. First, the synthetic signals in conjunction with Monte Carlo simulations highlighted two desirable features of the proposed algorithm vs. classical filter-bank approaches: resilience to broad-band noise and oscillatory interference. Second, the analyses with real EEG signals revealed statistically more robust effects (i.e. improved sensitivity) when using an adaptive frequency tracking framework, particularly when identifying phase-amplitude couplings. This was further confirmed after generating surrogate signals from the real EEG data. Adaptive frequency tracking appears to improve the measurements of cross-frequency couplings through precise extraction of neuronal oscillations.

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This paper characterizes and evaluates the potential of three commercial CT iterative reconstruction methods (ASIR?, VEO? and iDose(4 ()?())) for dose reduction and image quality improvement. We measured CT number accuracy, standard deviation (SD), noise power spectrum (NPS) and modulation transfer function (MTF) metrics on Catphan phantom images while five human observers performed four-alternative forced-choice (4AFC) experiments to assess the detectability of low- and high-contrast objects embedded in two pediatric phantoms. Results show that 40% and 100% ASIR as well as iDose(4) levels 3 and 6 do not affect CT number and strongly decrease image noise with relative SD constant in a large range of dose. However, while ASIR produces a shift of the NPS curve apex, less change is observed with iDose(4) with respect to FBP methods. With second-generation iterative reconstruction VEO, physical metrics are even further improved: SD decreased to 70.4% at 0.5 mGy and spatial resolution improved to 37% (MTF(50%)). 4AFC experiments show that few improvements in detection task performance are obtained with ASIR and iDose(4), whereas VEO makes excellent detections possible even at an ultra-low-dose (0.3 mGy), leading to a potential dose reduction of a factor 3 to 7 (67%-86%). In spite of its longer reconstruction time and the fact that clinical studies are still required to complete these results, VEO clearly confirms the tremendous potential of iterative reconstructions for dose reduction in CT and appears to be an important tool for patient follow-up, especially for pediatric patients where cumulative lifetime dose still remains high.

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We have selectively inhibited Notch1 signaling in oligodendrocyte precursors (OPCs) using the Cre/loxP system in transgenic mice to investigate the role of Notch1 in oligodendrocyte (OL) development and differentiation. Early development of OPCs appeared normal in the spinal cord. However, at embryonic day 17.5, premature OL differentiation was observed and ectopic immature OLs were present in the gray matter. At birth, OL apoptosis was strongly increased in Notch1 mutant animals. Premature OL differentiation was also observed in the cerebrum, indicating that Notch1 is required for the correct spatial and temporal regulation of OL differentiation in various regions of the central nervous system. These findings establish a widespread function of Notch1 in the late steps of mammalian OPC development in vivo.

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This article aims to present the conceptual and methodological framework in which models techniques for species and ecosystems distribution are developed. An historical review of concepts behind these techniques is made as well as the presentation of the major methodological steps involved in these tests. A discussion on how these approaches are useful for the development of new questions in the field of biogeography and biological conservation is generated. Finally, an application of distribution modeling techniques, using the specie Beilschmiedia miersii (belloto Del Norte) as a study case, is presented. This conceptual and methodological review as well as the example applied, seeks to clarify the usefulness and potential of distribution models techniques, with the objective to go forward in biogeography research and thus, farther progress in understanding spatial and temporal patterns of organism's distribution

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The large spatial inhomogeneity in transmit B, field (B-1(+)) observable in human MR images at hi h static magnetic fields (B-0) severely impairs image quality. To overcome this effect in brain T-1-weighted images the, MPRAGE sequence was modified to generate two different images at different inversion times MP2RAGE By combining the two images in a novel fashion, it was possible to create T-1-weigthed images where the result image was free of proton density contrast, T-2* contrast, reception bias field, and, to first order transmit field inhomogeneity. MP2RAGE sequence parameters were optimized using Bloch equations to maximize contrast-to-noise ratio per unit of time between brain tissues and minimize the effect of B-1(+) variations through space. Images of high anatomical quality and excellent brain tissue differentiation suitable for applications such as segmentation and voxel-based morphometry were obtained at 3 and 7 T. From such T-1-weighted images, acquired within 12 min, high-resolution 3D T-1 maps were routinely calculated at 7 T with sub-millimeter voxel resolution (0.65-0.85 mm isotropic). T-1 maps were validated in phantom experiments. In humans, the T, values obtained at 7 T were 1.15 +/- 0.06 s for white matter (WM) and 1.92 +/- 0.16 s for grey matter (GM), in good agreement with literature values obtained at lower spatial resolution. At 3 T, where whole-brain acquisitions with 1 mm isotropic voxels were acquired in 8 min the T-1 values obtained (0.81 +/- 0.03 S for WM and 1.35 +/- 0.05 for GM) were once again found to be in very good agreement with values in the literature. (C) 2009 Elsevier Inc. All rights reserved.

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Full-field X-ray microscopy is a valuable tool for 3D observation of biological systems. In the soft X-ray domain organelles can be visualized in individual cells while hard X-ray microscopes excel in imaging of larger complex biological tissue. The field of view of these instruments is typically 10(3) times the spatial resolution. We exploit the assets of the hard X-ray sub-micrometer imaging and extend the standard approach by widening the effective field of view to match the size of the sample. We show that global tomography of biological systems exceeding several times the field of view is feasible also at the nanoscale with moderate radiation dose. We address the performance issues and limitations of the TOMCAT full-field microscope and more generally for Zernike phase contrast imaging. Two biologically relevant systems were investigated. The first being the largest known bacteria (Thiomargarita namibiensis), the second is a small myriapod species (Pauropoda sp.). Both examples illustrate the capacity of the unique, structured condenser based broad-band full-field microscope to access the 3D structural details of biological systems at the nanoscale while avoiding complicated sample preparation, or even keeping the sample environment close to the natural state.