956 resultados para calibrated fMRI


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Using the framework of Desmet and Rossi-Hansberg (forthcoming), we present a model of spatial takeoff that is calibrated using spatially-disaggregated occupational data for England in c.1710. The model predicts changes in the spatial distribution of agricultural and manufacturing employment which match data for c.1817 and 1861. The model also matches a number of aggregate changes that characterise the first industrial revolution. Using counterfactual geographical distributions, we show that the initial concentration of productivity can matter for whether and when an industrial takeoff occurs. Subsidies to innovation in either sector can bring forward the date of takeoff while subsidies to the use of land by manufacturing firms can significantly delay a takeoff because it decreases spatial concentration of activity.

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Functional magnetic resonance imaging (fMRI) was used to measure changes in cerebral activity in patients with schizophrenia after participation in the Cognitive Remediation Program for Schizophrenia and other related disorders (RECOS). As RECOS therapists make use of problem-solving and verbal mediation techniques, known to be beneficial in the rehabilitation of dysexecutive syndromes, we expected an increased activation of frontal areas after remediation. Executive functioning and cerebral activation during a covert verbal fluency task were measured in eight patients with schizophrenia before (T1) and after (T2) 14 weeks of RECOS therapy. The same measures were recorded in eight patients with schizophrenia who did not participate in RECOS at the same intervals of time (TAU group). Increased activation in Broca's area, as well as improvements in performance of executive/frontal tasks, was observed after cognitive training. Metacognitive techniques of verbalization are hypothesized to be the main factor underlying the brain changes observed in the present study.

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The last several years have seen an increasing number of studies that describe effects of oxytocin and vasopressin on the behavior of animals or humans. Studies in humans have reported behavioral changes and, through fMRI, effects on brain function. These studies are paralleled by a large number of reports, mostly in rodents, that have also demonstrated neuromodulatory effects by oxytocin and vasopressin at the circuit level in specific brain regions. It is the scope of this review to give a summary of the most recent neuromodulatory findings in rodents with the aim of providing a potential neurophysiological basis for their behavioral effects. At the same time, these findings may point to promising areas for further translational research towards human applications.

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The primary auditory cortex (PAC) is central to human auditory abilities, yet its location in the brain remains unclear. We measured the two largest tonotopic subfields of PAC (hA1 and hR) using high-resolution functional MRI at 7 T relative to the underlying anatomy of Heschl's gyrus (HG) in 10 individual human subjects. The data reveals a clear anatomical-functional relationship that, for the first time, indicates the location of PAC across the range of common morphological variants of HG (single gyri, partial duplications, and complete duplications). In 20/20 individual hemispheres, two primary mirror-symmetric tonotopic maps were clearly observed with gradients perpendicular to HG. PAC spanned both divisions of HG in cases of partial and complete duplications (11/20 hemispheres), not only the anterior division as commonly assumed. Specifically, the central union of the two primary maps (the hA1-R border) was consistently centered on the full Heschl's structure: on the gyral crown of single HGs and within the sulcal divide of duplicated HGs. The anatomical-functional variants of PAC appear to be part of a continuum, rather than distinct subtypes. These findings significantly revise HG as a marker for human PAC and suggest that tonotopic maps may have shaped HG during human evolution. Tonotopic mappings were based on only 16 min of fMRI data acquisition, so these methods can be used as an initial mapping step in future experiments designed to probe the function of specific auditory fields.

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1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

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The availability of rich firm-level data sets has recently led researchers to uncover new evidence on the effects of trade liberalization. First, trade openness forces the least productive firms to exit the market. Secondly, it induces surviving firms to increase their innovation efforts and thirdly, it increases the degree of product market competition. In this paper we propose a model aimed at providing a coherent interpretation of these findings. We introducing firm heterogeneity into an innovation-driven growth model, where incumbent firms operating in oligopolistic industries perform cost-reducing innovations. In this framework, trade liberalization leads to higher product market competition, lower markups and higher quantity produced. These changes in markups and quantities, in turn, promote innovation and productivity growth through a direct competition effect, based on the increase in the size of the market, and a selection effect, produced by the reallocation of resources towards more productive firms. Calibrated to match US aggregate and firm-level statistics, the model predicts that a 10 percent reduction in variable trade costs reduces markups by 1:15 percent, firm surviving probabilities by 1 percent, and induces an increase in productivity growth of about 13 percent. More than 90 percent of the trade-induced growth increase can be attributed to the selection effect.

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The sensitivity of altitudinal and latitudinal tree-line ecotones to climate change, particularly that of temperature, has received much attention. To improve our understanding of the factors affecting tree-line position, we used the spatially explicit dynamic forest model TreeMig. Although well-suited because of its landscape dynamics functions, TreeMig features a parabolic temperature growth response curve, which has recently been questioned. and the species parameters are not specifically calibrated for cold temperatures. Our main goals were to improve the theoretical basis of the temperature growth response curve in the model and develop a method for deriving that curve's parameters from tree-ring data. We replaced the parabola with an asymptotic curve, calibrated for the main species at the subalpine (Swiss Alps: Pinus cembra, Larix decidua, Picea abies) and boreal (Fennoscandia: Pinus sylvestris, Betula pubescens, P. abies) tree-lines. After fitting new parameters, the growth curve matched observed tree-ring widths better. For the subalpine species, the minimum degree-day sum allowing, growth (kDDMin) was lowered by around 100 degree-days; in the case of Larix, the maximum potential ring-width was increased to 5.19 mm. At the boreal tree-line, the kDDMin for P. sylvestris was lowered by 210 degree-days and its maximum ring-width increased to 2.943 mm; for Betula (new in the model) kDDMin was set to 325 degree-days and the maximum ring-width to 2.51 mm; the values from the only boreal sample site for Picea were similar to the subalpine ones, so the same parameters were used. However, adjusting the growth response alone did not improve the model's output concerning species' distributions and their relative importance at tree-line. Minimum winter temperature (MinWiT, mean of the coldest winter month), which controls seedling establishment in TreeMig, proved more important for determining distribution. Picea, P. sylvestris and Betula did not previously have minimum winter temperature limits, so these values were set to the 95th percentile of each species' coldest MinWiT site (respectively -7, -11, -13). In a case study for the Alps, the original and newly calibrated versions of TreeMig were compared with biomass data from the National Forest Inventor), (NFI). Both models gave similar, reasonably realistic results. In conclusion, this method of deriving temperature responses from tree-rings works well. However, regeneration and its underlying factors seem more important for controlling species' distributions than previously thought. More research on regeneration ecology, especially at the upper limit of forests. is needed to improve predictions of tree-line responses to climate change further.

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Aquest projecte resol les fases inicials d'un altre projecte més gran que té com a objectiu la conversió automàtica de seqüències d'imatges a 3D. El projecte s'ha centrat en la reconstrucció calibrada de col·leccions d'imatges mitjançant la tècnica anomenada structure from motion. Aquesta tècnica forma part de l'àmbit de la visió per computador i s'utilitza per obtenir la posició i l'orientació de les diferents càmeres juntament amb una reconstrucció 3D de l'escena en forma de núvol de punts.

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In this paper we simulate and analyse the economic impact that sectorial productivity gains have on two regional Spanish economies (Catalonia and Extremadura). In particular we study the quantitative effect that each sector’s productivity gain has on household welfare (real disposable income and equivalent variation), on the consumption price indices and factor relative prices, on real production (GDP) and on the government’s net income (net taxation revenues of social transfers to households). The analytical approach consists of a computable general equilibrium model, in which we assume perfect competition and cleared markets, including factor markets. All the parameters and exogenous variables of the model are calibrated by means of two social accounting matrices, one for each region under study. The results allow us to identify those sectors with the greatest impact on consumer welfare as the key sectors in the regional economies. Keywords: Productivity gains, key sectors, computable general equilibrium

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In an uncertain environment, probabilities are key to predicting future events and making adaptive choices. However, little is known about how humans learn such probabilities and where and how they are encoded in the brain, especially when they concern more than two outcomes. During functional magnetic resonance imaging (fMRI), young adults learned the probabilities of uncertain stimuli through repetitive sampling. Stimuli represented payoffs and participants had to predict their occurrence to maximize their earnings. Choices indicated loss and risk aversion but unbiased estimation of probabilities. BOLD response in medial prefrontal cortex and angular gyri increased linearly with the probability of the currently observed stimulus, untainted by its value. Connectivity analyses during rest and task revealed that these regions belonged to the default mode network. The activation of past outcomes in memory is evoked as a possible mechanism to explain the engagement of the default mode network in probability learning. A BOLD response relating to value was detected only at decision time, mainly in striatum. It is concluded that activity in inferior parietal and medial prefrontal cortex reflects the amount of evidence accumulated in favor of competing and uncertain outcomes.

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Introduction: Cognitive impairment affects 40-65% of multiple sclerosis (MS) patients, often since early stages of the disease (relapsing remitting MS, RRMS). Frequently affected functions are memory, attention or executive abilities but the most sensitive measure of cognitive deficits in early MS is the information processing speed (Amato, 2008). MRI has been extensively exploited to investigate the substrate of cognitive dysfunction in MS but the underlying physiopathological mechanisms remain unclear. White matter lesion load, whole-brain atrophy and cortical lesions' number play a role but correlations are in some cases modest (Rovaris, 2006; Calabrese, 2009). In this study, we aimed at characterizing and correlating the T1 relaxation times of cortical and sub-cortical lesions with cognitive deficits detected by neuropsychological tests in a group of very early RR MS patients. Methods: Ten female patients with very early RRMS (age: 31.6 ±4.7y; disease duration: 3.8 ±1.9y; EDSS disability score: 1.8 ±0.4) and 10 age- and gender-matched healthy volunteers (mean age: 31.2 ±5.8y) were included in the study. All participants underwent the following neuropsychological tests: Rao's Brief Repeatable Battery of Neuropsychological tests (BRB-N), Stockings of Cambridge, Trail Making Test (TMT, part A and B), Boston Naming Test, Hooper Visual Organization Test and copy of the Rey-Osterrieth Complex Figure. Within 2 weeks from neuropsychological assessment, participants underwent brain MRI at 3T (Magnetom Trio a Tim System, Siemens, Germany) using a 32-channel head coil. The imaging protocol included 3D sequences with 1x1x1.2 mm3 resolution and 256x256x160 matrix, except for axial 2D-FLAIR: -DIR (T2-weighted, suppressing both WM and CSF; Pouwels, 2006) -MPRAGE (T1-weighted; Mugler, 1991) -MP2RAGE (T1-weighted with T1 maps; Marques, 2010) -FLAIR SPACE (only for patient 4-10, T2-weighted; Mugler, 2001) -2D Axial FLAIR (0.9x0.9x2.5 mm3, 256x256x44 matrix). Lesions were identified by one experienced neurologist and radiologist using all contrasts, manually contoured and assigned to regional locations (cortical or sub-cortical). Lesion number, volume and T1 relaxation time were calculated for lesions in each contrast and in a merged mask representing the union of the lesions from all contrasts. T1 relaxation times of lesions were normalized with the mean T1 value in corresponding control regions of the healthy subjects. Statistical analysis was performed using GraphPad InStat software. Cognitive scores were compared between patients and controls with paired t-tests; p values ≤ 0.05 were considered significant. Spearmann correlation tests were performed between the cognitive tests, which differed significantly between patients and controls, and lesions' i) number ii) volume iii) T1 relaxation time iv) disease duration and v) years of study. Results: Cortical and sub-cortical lesions count, T1 values and volume are reported in Table 1 (A and B). All early RRMS patients showed cortical lesions (CLs) and the majority consisted of CLs type I (lesions with a cortical component extending to the sub-cortical tissue). The rest of cortical lesions were characterized as type II (intra-cortical lesions). No type III/IV lesions (large sub-pial lesions) were detected. RRMS patients were slightly less educated (13.5±2.5y vs. 16.3±1.8y of study, p=0.02) than the controls. Signs of cortical dysfunction (i.e. impaired learning, language, visuo-spatial skills or gnosis) were rare in all patients. However, patients showed on average lower scores on measures of visual attention and information processing speed (TMT-part A: p=0.01; TMT-part B: p=0.006; PASAT-included in the BRB-N: p=0.04). The T1 relaxation values of CLs type I negatively correlated with the TMT-part A score (r=0.78, p<0.01). The correlations of TMT-part B score and PASAT score with T1 relaxation time of lesions as well and the correlation between TMT-part A, TMT-part B and PASAT score with lesions' i) number ii) volume iii) disease duration and iv) years of study did not reach significance. In order to preclude possible influences from partial volume effects on the T1 values, the correlation between lesion volume and T1 value of CLs type I was calculated; no correlation was found, suggesting that partial volume effects did not affect the statistics. Conclusions: The present pilot study reports for the first time the presence and the T1 characteristics at 3 T of cortical lesions in very early RRMS (< 6 y disease duration). It also shows that CLS type I represents the most frequent cortical lesion type in this cohort of RRMS patients. In addition, it reveals a negative correlation between the attentional test TMT-part A and the T1 properties of cortical lesions type I. In other words, lower attention deficits are concomitant with longer T1-relaxation time in cortical lesions. In respect to this last finding, it could be speculated that long relaxation time correspond to a certain degree of tissue loss that is enough to stimulate compensatory mechanisms. This hypothesis is in line with previous fMRI studies showing functional compensatory mechanisms to help maintaining normal or sub-normal attention performances in RR MS patients (Penner, 2003).

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North South Survey of Children’s Height, Weight and Body Mass Index, 2002. As part of a North South Survey of Childrenâ?Ts Oral Health conducted in Ireland in 2001/â?T02 [1], the heights and weights of a representative sample of children and adolescents age 4-16 years was measured. Data were collected by 34 teams of trained and calibrated dentists and dental nurses for 17,518 children aged 4-16 in the Republic of Ireland (RoI) and 2,099 in Northern Ireland (NI). Click here to download PDF 379kb

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As part of a North South Survey of Childrens Oral Health conducted in Ireland in 2001/’02 [1], the heights and weights of a representative sample of children and adolescents age 4-16 years was measured. Data were collected by 34 teams of trained and calibrated dentists and dental nurses for 17,518 children aged 4-16 in the Republic of Ireland (RoI) and 2,099 in Northern Ireland (NI). This report presents the results of the study which provide a baseline measurement of Childrens height and weight against which future change can be measured. By comparing these data with international norms we can estimate the current prevalence of overweight and obesity among children and adolescents in Ireland.

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Prismatic adaptation has been shown to induce a realignment of visuoproprioceptive representations and to involve parietocerebellar networks. We have investigated in humans how far other types of functions known to involve the parietal cortex are influenced by a brief exposure to prismatic adaptation. Normal subjects underwent an fMRI evaluation before and after a brief session of prismatic adaptation using rightward deviating prisms for one group or after an equivalent session using plain glasses for the other group. Activation patterns to three tasks were analyzed: (1) visual detection; (2) visuospatial short-term memory; and (3) verbal short-term memory. The prismatic adaptation-related changes were found bilaterally in the inferior parietal lobule when prisms, but not plain glasses, were used. This effect was driven by selective changes during the visual detection task: an increase in neural activity was induced on the left and a decrease on the right parietal side after prismatic adaptation. Comparison of activation patterns after prismatic adaptation on the visual detection task demonstrated a significant increase of the ipsilateral field representation in the left inferior parietal lobule and a significant decrease in the right inferior parietal lobule. In conclusion, a brief exposure to prismatic adaptation modulates differently left and right parietal activation during visual detection but not during short-term memory. Furthermore, the visuospatial representation within the inferior parietal lobule changes, with a decrease of the ipsilateral hemifield representation on the right and increase on the left side, suggesting thus a left hemispheric dominance.

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Recent advances in signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method capable of providing spatio-temporal information regarding brain (dys)function. Because of the increasing interest in the temporal dynamics of brain networks, and because of the straightforward compatibility of the EEG with other brain imaging techniques, EEG is increasingly used in the neuroimaging community. However, the full capability of EEG is highly underestimated. Many combined EEG-fMRI studies use the EEG only as a spike-counter or an oscilloscope. Many cognitive and clinical EEG studies use the EEG still in its traditional way and analyze grapho-elements at certain electrodes and latencies. We here show that this way of using the EEG is not only dangerous because it leads to misinterpretations, but it is also largely ignoring the spatial aspects of the signals. In fact, EEG primarily measures the electric potential field at the scalp surface in the same way as MEG measures the magnetic field. By properly sampling and correctly analyzing this electric field, EEG can provide reliable information about the neuronal activity in the brain and the temporal dynamics of this activity in the millisecond range. This review explains some of these analysis methods and illustrates their potential in clinical and experimental applications.