985 resultados para Spatial extent
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Classical studies of area summation measure contrast detection thresholds as a function of grating diameter. Unfortunately, (i) this approach is compromised by retinal inhomogeneity and (ii) it potentially confounds summation of signal with summation of internal noise. The Swiss cheese stimulus of T. S. Meese and R. J. Summers (2007) and the closely related Battenberg stimulus of T. S. Meese (2010) were designed to avoid these problems by keeping target diameter constant and modulating interdigitated checks of first-order carrier contrast within the stimulus region. This approach has revealed a contrast integration process with greater potency than the classical model of spatial probability summation. Here, we used Swiss cheese stimuli to investigate the spatial limits of contrast integration over a range of carrier frequencies (1–16 c/deg) and raised plaid modulator frequencies (0.25–32 cycles/check). Subthreshold summation for interdigitated carrier pairs remained strong (~4 to 6 dB) up to 4 to 8 cycles/check. Our computational analysis of these results implied linear signal combination (following square-law transduction) over either (i) 12 carrier cycles or more or (ii) 1.27 deg or more. Our model has three stages of summation: short-range summation within linear receptive fields, medium-range integration to compute contrast energy for multiple patches of the image, and long-range pooling of the contrast integrators by probability summation. Our analysis legitimizes the inclusion of widespread integration of signal (and noise) within hierarchical image processing models. It also confirms the individual differences in the spatial extent of integration that emerge from our approach.
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The sediments of Bear Creek near Baltimore, Maryland demonstrate substantial toxicity to benthic organisms, and contain a complex mixture of organic and inorganic contaminants. The present study maps the spatial extent and depth profile of toxicity and contamination in Bear Creek, and explores correlations between heavy metals, organic contaminants, and toxic responses. Two novel analytical techniques – handheld XRF and an antibody-based PAH biosensor – were applied to samples from the site to quantify total metals and total PAHs in sediments. By comprehensively assessing toxicity in Bear Creek, the present study provides data to inform future risk assessments and management decisions relating for the site, while demonstrating the benefits of applying joint biological assays and chemical assessment methods to sediments with complex contaminant mixtures.
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A recent estimate of CO(2) outgassing from Amazonian wetlands suggests that an order of magnitude more CO(2) leaves rivers through gas exchange with the atmosphere than is exported to the ocean as organic plus inorganic carbon. However, the contribution of smaller rivers is still poorly understood, mainly because of limitations in mapping their spatial extent. Considering that the largest extension of the Amazon River network is composed of small rivers, the authors` objective was to elucidate their role in air-water CO(2) exchange by developing a geographic information system ( GIS)- based model to calculate the surface area covered by rivers with channels less than 100 m wide, combined with estimated CO(2) outgassing rates at the Ji-Parana River basin, in the western Amazon. Estimated CO(2) outgassing was the main carbon export pathway for this river basin, totaling 289 Gg C yr(-1), about 2.4 times the amount of carbon exported as dissolved inorganic carbon ( 121 Gg C yr(-1)) and 1.6 times the dissolved organic carbon export ( 185 Gg C yr(-1)). The relationships established here between drainage area and channel width provide a new model for determining small river surface area, allowing regional extrapolations of air - water gas exchange. Applying this model to the entire Amazon River network of channels less than 100 m wide ( third to fifth order), the authors calculate that the surface area of small rivers is 0.3 +/- 0.05 million km(2), and it is potentially evading to the atmosphere 170 +/- 42 Tg C yr(-1) as CO(2). Therefore, these ecosystems play an important role in the regional carbon balance.
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Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.
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Land use intensification is estimated to result in an overall increase in sediment delivery to the Great Barrier Reef lagoon by a factor of approximately four. Modelling suggests that, following land use intensification, croplands cause the greatest increase of sediment yield and sediment concentration, whereas erosion of grazing land is the main contemporary source of sediments, primarily owing to the large spatial extent of this land use. The spatial pattern of sediment yield to the coast after land use intensification is strongly correlated with the pattern under natural conditions, although the greatest increase is estimated to have occurred in the wet-dry catchments. Sediment transport and resuspension processes have led to the development of a strongly sediment-partitioned shelf, with modern mud-rich sediments almost exclusively restricted to the inner and inner-middle shelf, northward-facing embayments and in the lee of headlands. Elevated sediment concentrations increase the potential transport rates of nutrients and other pollutants. Whether increased sediment supply to the coastal zone has impacted on reefs remains a point of contention. More sediment load data need to be collected and analysed in order to make detailed estimates of catchment yields and establish the possible sediment impact on the Great Barrier Reef.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies
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Developing a predictive understanding of subsurface flow and transport is complicated by the disparity of scales across which controlling hydrological properties and processes span. Conventional techniques for characterizing hydrogeological properties (such as pumping, slug, and flowmeter tests) typically rely on borehole access to the subsurface. Because their spatial extent is commonly limited to the vicinity near the wellbores, these methods often cannot provide sufficient information to describe key controls on subsurface flow and transport. The field of hydrogeophysics has evolved in recent years to explore the potential that geophysical methods hold for improving the quantification of subsurface properties and processes relevant for hydrological investigations. This chapter is intended to familiarize hydrogeologists and water-resource professionals with the state of the art as well as existing challenges associated with hydrogeophysics. We provide a review of the key components of hydrogeophysical studies, which include: geophysical methods commonly used for shallow subsurface characterization; petrophysical relationships used to link the geophysical properties to hydrological properties and state variables; and estimation or inversion methods used to integrate hydrological and geophysical measurements in a consistent manner. We demonstrate the use of these different geophysical methods, petrophysical relationships, and estimation approaches through several field-scale case studies. Among other applications, the case studies illustrate the use of hydrogeophysical approaches to quantify subsurface architecture that influence flow (such as hydrostratigraphy and preferential pathways); delineate anomalous subsurface fluid bodies (such as contaminant plumes); monitor hydrological processes (such as infiltration, freshwater-seawater interface dynamics, and flow through fractures); and estimate hydrological properties (such as hydraulic conductivity) and state variables (such as water content). The case studies have been chosen to illustrate how hydrogeophysical approaches can yield insights about complex subsurface hydrological processes, provide input that improves flow and transport predictions, and provide quantitative information over field-relevant spatial scales. The chapter concludes by describing existing hydrogeophysical challenges and associated research needs. In particular, we identify the area of quantitative watershed hydrogeophysics as a frontier area, where significant effort is required to advance the estimation of hydrological properties and processes (and their uncertainties) over spatial scales relevant to the management of water resources and contaminants.
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Introduction : Driving is a complex everyday task requiring mechanisms of perception, attention, learning, memory, decision making and action control, thus indicating that involves numerous and varied brain networks. If many data have been accumulated over time about the effects of alcohol consumption on driving capability, much less is known about the role of other psychoactive substances, such as cannabis (Chang et al.2007, Ramaekers et al, 2006). Indeed, the solicited brain areas during safe driving which could be affected by cannabis exposure have not yet been clearly identified. Our aim is to study these brain regions during a tracking task related to driving skills and to evaluate the modulation due to the tolerance of cannabis effects. Methods : Eight non-smoker control subjects participated to an fMRI experiment based on a visuo-motor tracking task, alternating active tracking blocks with passive tracking viewing and rest condition. Half of the active tracking conditions included randomly presented traffic lights as distractors. Subjects were asked to track with a joystick with their right hand and to press a button with their left index at each appearance of a distractor. Four smoking subjects participated to the same fMRI sessions once before and once after smoking cannabis and a placebo in two independent cross-over experiments. We quantified the performance of the subjects by measuring the precision of the behavioural responses (i.e. percentage of time of correct tracking and reaction times to distractors). Functional MRI data were acquired using on a 3.0T Siemens Trio system equipped with a 32-channel head coil. BOLD signals will be obtained with a gradient-echo EPI sequence (TR=2s, TE=30ms, FoV=216mm, FA=90°, matrix size 72×72, 32 slices, thickness 3mm). Preprocessing, single subject analysis and group statistics were conducted on SPM8b. Results were thresholded at p<0.05 (FWE corrected) and at k>30 for spatial extent. Results : Behavioural results showed a significant impairment in task and cognitive test performance of the subjects after cannabis inhalation when comparing their tracking accuracy either to the controls subjects or to their performances before the inhalation or after the placebo inhalation (p<0.001 corrected). In controls, fMRI BOLD analysis of the active tracking condition compared to the passive one revealed networks of polymodal areas in superior frontal and parietal cortex dealing with attention and visuo-spatial coordination. In accordance to what is known of the visual and sensory motor networks we found activations in V4, frontal eye-field, right middle frontal gyrus, intra-parietal sulcus, temporo-parietal junction, premotor and sensory-motor cortex. The presence of distractors added a significant activation in the precuneus. Preliminary results on cannabis smokers in the acute phase, compared either to themselves before the cannabis inhalation or to control subjects, showed a decreased activation in large portions of the frontal and parietal attention network during the simple tracking task, but greater involvement of precuneus, of the superior part of intraparietal sulcus and middle frontal gyrus bilaterally when distractors were present in the task. Conclusions : Our preliminary results suggest that acute cannabis smoking alters performances and brain activity during active tracking tasks, partly reorganizing the recruitment of brain areas of the attention network.
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Rockfall hazard zoning is usually achieved using a qualitative estimate of hazard, and not an absolute scale. In Switzerland, danger maps, which correspond to a hazard zoning depending on the intensity of the considered phenomenon (e.g. kinetic energy for rockfalls), are replacing hazard maps. Basically, the danger grows with the mean frequency and with the intensity of the rockfall. This principle based on intensity thresholds may also be applied to other intensity threshold values than those used in Switzerland for rockfall hazard zoning method, i.e. danger mapping. In this paper, we explore the effect of slope geometry and rockfall frequency on the rockfall hazard zoning. First, the transition from 2D zoning to 3D zoning based on rockfall trajectory simulation is examined; then, its dependency on slope geometry is emphasized. The spatial extent of hazard zones is examined, showing that limits may vary widely depending on the rockfall frequency. This approach is especially dedicated to highly populated regions, because the hazard zoning has to be very fine in order to delineate the greatest possible territory containing acceptable risks.
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Positron emission tomography with [18F] fluorodeoxyglucose (FDG-PET) plays a well-established role in assisting early detection of frontotemporal lobar degeneration (FTLD). Here, we examined the impact of intensity normalization to different reference areas on accuracy of FDG-PET to discriminate between patients with mild FTLD and healthy elderly subjects. FDG-PET was conducted at two centers using different acquisition protocols: 41 FTLD patients and 42 controls were studied at center 1, 11 FTLD patients and 13 controls were studied at center 2. All PET images were intensity normalized to the cerebellum, primary sensorimotor cortex (SMC), cerebral global mean (CGM), and a reference cluster with most preserved FDG uptake in the aforementioned patients group of center 1. Metabolic deficits in the patient group at center 1 appeared 1.5, 3.6, and 4.6 times greater in spatial extent, when tracer uptake was normalized to the reference cluster rather than to the cerebellum, SMC, and CGM, respectively. Logistic regression analyses based on normalized values from FTLD-typical regions showed that at center 1, cerebellar, SMC, CGM, and cluster normalizations differentiated patients from controls with accuracies of 86%, 76%, 75% and 90%, respectively. A similar order of effects was found at center 2. Cluster normalization leads to a significant increase of statistical power in detecting early FTLD-associated metabolic deficits. The established FTLD-specific cluster can be used to improve detection of FTLD on a single case basis at independent centers - a decisive step towards early diagnosis and prediction of FTLD syndromes enabling specific therapies in the future.
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Introduction: The primary somatosensory cortex (SI) contains Brodmann areas (BA) 1, 2, 3a, and 3b. Research in non-human primates showed that BAs 3b, 1, and 2 each contain one full representation of the hand with separate representations for each finger. This research also showed that the finger representation in BA3b has larger and clearer finger somatotopy than BA1 and 2. Although several efforts to map finger somatotopy in SI by fMRI have been made at 1.5 and 3T these studies have yielded variable results and were not able to detect single subject finger somatotopy, probably due to the limited spatial extent of the cortical areas representing a digit (close to the resolution in most fMRI experiments), complications due to acquisition of consistent maps for individual subjects (Schweizer et al 2008), or inter-individual variability in sulcal anatomy impeding group studies. Here, we used 7T fMRI to investigate finger somatotopy in SI, some of its functional characteristics, and its reproducibility. Methods: Eight right-handed male subjects were scanned on a 7T scanner (Siemens Medical, Germany) with an 8-channel Tx/Rx rf-coil (Rapid Biomedical, Germany). 1.3x1.3x1.3mm3 resolution fMRI data were acquired using a sinusoidal readout EPI sequence (Speck et al, 2008) and FOV=210mm, TE/TR=27ms/2.5s, GRAPPA=2. Each volume contained 28 transverse slices covering SI. A single EPI volume with 64 slices was acquired to aid coregistration. 1x1x1mm3 anatomical data were acquire using the MP2RAGE sequence (Marques et al, 2009; TE/TR/TI1,2/TRmprage=2.63ms/7.2ms/0.9,3.2s/5s). Subjects were positioned supine in the scanner with their right arm comfortably against the magnet bore. An experimenter was positioned at the entrance of the bore where he could easily reach and stroke successively the two distal phalanxes of each digit. The order of stroked digit was D1 (thumb)-D3-D5-D2-D4, with 20s ON, 10s OFF alternated. This sequence was repeated four times per run and two functional runs were acquired per subject. Realignment, smoothing (FWHM 2 mm), coregistration of the anatomical to the fMRI data and calculation of t-statistics were done using SPM8. An SI mask was obtained via an F-contrast (p<0.001) over all digits. Within the mask, voxels were labeled with the number of the digit demonstrating the highest t-value for that particular voxel. Results: For all subjects, areas corresponding to the five digits were identified in contralateral SI. BA3b showed the most consistent somatotopic finger representation (see an example in Fig.1). The five digits were localized in a consecutive order in the cortex, with D1 most anterior, inferior and distal and D5, most posterior, superior and medial (mean distance between centres of mass of digit representations ±stderr: 4.2±0.7mm; see Fig. 2). The analysis of average beta values within each finger representation region revealed the specificity of the somatotopic region to the tactile input for each tested finger (except digit 4 and 5). Five of these subjects also presented an orderly and consecutive representation of the five digits in BA1 and 2. Conclusions: Our data reveal that the increased BOLD sensitivity at 7T and the high spatial resolution used in this study allow consistent somatotopic mapping using human touch as a stimulus and that human SI contains at least three separate regions that contain five separate representations of all single contralateral fingers. Moreover, adjacent fingers were represented at adjacent cortical regions across the three SI regions. The spatial organization of SI as reflected in individual subject topography corresponds well with previous electrophysiological data in non-human primates. The small distance between digit representations highlights the need for the high spatial resolution available at 7T.
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Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.
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Cerebral blood flow can be studied in a multislice mode with a recently proposed perfusion sequence using inversion of water spins as an endogenous tracer without magnetization transfer artifacts. The magnetization transfer insensitive labeling technique (TILT) has been used for mapping blood flow changes at a microvascular level under motor activation in a multislice mode. In TILT, perfusion mapping is achieved by subtraction of a perfusion-sensitized image from a control image. Perfusion weighting is accomplished by proximal blood labeling using two 90 degrees radiofrequency excitation pulses. For control preparation the labeling pulses are modified such that they have no net effect on blood water magnetization. The percentage of blood flow change, as well as its spatial extent, has been studied in single and multislice modes with varying delays between labeling and imaging. The average perfusion signal change due to activation was 36.9 +/- 9.1% in the single-slice experiments and 38.1 +/- 7.9% in the multislice experiments. The volume of activated brain areas amounted to 1.51 +/- 0.95 cm3 in the contralateral primary motor (M1) area, 0.90 +/- 0.72 cc in the ipsilateral M1 area, 1.27 +/- 0.39 cm3 in the contralateral and 1.42 +/- 0.75 cm3 in the ipsilateral premotor areas, and 0.71 +/- 0.19 cm3 in the supplementary motor area.
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Niche-based models calibrated in the native range by relating species observations to climatic variables are commonly used to predict the potential spatial extent of species' invasion. This climate matching approach relies on the assumption that invasive species conserve their climatic niche in the invaded ranges. We test this assumption by analysing the climatic niche spaces of Spotted Knapweed in western North America and Europe. We show with robust cross-continental data that a shift of the observed climatic niche occurred between native and non-native ranges, providing the first empirical evidence that an invasive species can occupy climatically distinct niche spaces following its introduction into a new area. The models fail to predict the current invaded distribution, but correctly predict areas of introduction. Climate matching is thus a useful approach to identify areas at risk of introduction and establishment of newly or not-yet-introduced neophytes, but may not predict the full extent of invasions.
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Detailed knowledge of the anatomy and connectivity pattern of cortico-basal ganglia circuits is essential to an understanding of abnormal cortical function and pathophysiology associated with a wide range of neurological and neuropsychiatric diseases. We aim to study the spatial extent and topography of human basal ganglia connectivity in vivo. Additionally, we explore at an anatomical level the hypothesis of coexistent segregated and integrative cortico-basal ganglia loops. We use probabilistic tractography on magnetic resonance diffusion weighted imaging data to segment basal ganglia and thalamus in 30 healthy subjects based on their cortical and subcortical projections. We introduce a novel method to define voxel-based connectivity profiles that allow representation of projections from a source to more than one target region. Using this method, we localize specific relay nuclei within predefined functional circuits. We find strong correlation between tractography-based basal ganglia parcellation and anatomical data from previously reported invasive tracing studies in nonhuman primates. Additionally, we show in vivo the anatomical basis of segregated loops and the extent of their overlap in prefrontal, premotor, and motor networks. Our findings in healthy humans support the notion that probabilistic diffusion tractography can be used to parcellate subcortical gray matter structures on the basis of their connectivity patterns. The coexistence of clearly segregated and also overlapping connections from cortical sites to basal ganglia subregions is a neuroanatomical correlate of both parallel and integrative networks within them. We believe that this method can be used to examine pathophysiological concepts in a number of basal ganglia-related disorders.