993 resultados para Statistical Distributions.
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Introduction: Neuroimaging of the self focused on high-level mechanisms such as language, memory or imagery of the self. Recent evidence suggests that low-level mechanisms of multisensory and sensorimotor integration may play a fundamental role in encoding self-location and the first-person perspective (Blanke and Metzinger, 2009). Neurological patients with out-of body experiences (OBE) suffer from abnormal self-location and the first-person perspective due to a damage in the temporo-parietal junction (Blanke et al., 2004). Although self-location and the first-person perspective can be studied experimentally (Lenggenhager et al., 2009), the neural underpinnings of self-location have yet to be investigated. To investigate the brain network involved in self-location and first-person perspective we used visuo-tactile multisensory conflict, magnetic resonance (MR)-compatible robotics, and fMRI in study 1, and lesion analysis in a sample of 9 patients with OBE due to focal brain damage in study 2. Methods: Twenty-two participants saw a video showing either a person's back or an empty room being stroked (visual stimuli) while the MR-compatible robotic device stroked their back (tactile stimulation). Direction and speed of the seen stroking could either correspond (synchronous) or not (asynchronous) to those of the seen stroking. Each run comprised the four conditions according to a 2x2 factorial design with Object (Body, No-Body) and Synchrony (Synchronous, Asynchronous) as main factors. Self-location was estimated using the mental ball dropping (MBD; Lenggenhager et al., 2009). After the fMRI session participants completed a 6-item adapted from the original questionnaire created by Botvinick and Cohen (1998) and based on questions and data obtained by Lenggenhager et al. (2007, 2009). They were also asked to complete a questionnaire to disclose the perspective they adopted during the illusion. Response times (RTs) for the MBD and fMRI data were analyzed with a 3-way mixed model ANOVA with the in-between factor Perspective (up, down) and the two with-in factors Object (body, no-body) and Stroking (synchronous, asynchronous). Quantitative lesion analysis was performed using MRIcron (Rorden et al., 2007). We compared the distributions of brain lesions confirmed by multimodality imaging (Knowlton, 2004) in patients with OBE with those showing complex visual hallucinations involving people or faces, but without any disturbance of self-location and first person perspective. Nine patients with OBE were investigated. The control group comprised 8 patients. Structural imaging data were available for normalization and co-registration in all the patients. Normalization of each patient's lesion into the common MNI (Montreal Neurological Institute) reference space permitted simple, voxel-wise, algebraic comparisons to be made. Results: Even if in the scanner all participants were lying on their back and were facing upwards, analysis of perspective showed that half of the participants had the impression to be looking down at the virtual human body below them, despite any cues about their body position (Down-group). The other participants had the impression to be looking up at the virtual body above them (Up-group). Analysis of Q3 ("How strong was the feeling that the body you saw was you?") indicated stronger self-identification with the virtual body during the synchronous stroking. RTs in the MBD task confirmed these subjective data (significant 3-way interaction between perspective, object and stroking). fMRI results showed eight cortical regions where the BOLD signal was significantly different during at least one of the conditions resulting from the combination of Object and Stroking, relative to baseline: right and left temporo-parietal junction, right EBA, left middle occipito-temporal gyrus, left postcentral gyrus, right medial parietal lobe, bilateral medial occipital lobe (Fig 1). The activation patterns in right and left temporo-parietal junction and right EBA reflected changes in self-location and perspective as revealed by statistical analysis that was performed on the percentage of BOLD change with respect to the baseline. Statistical lesion overlap comparison (using nonparametric voxel based lesion symptom mapping) with respect to the control group revealed the right temporo-parietal junction, centered at the angular gyrus (Talairach coordinates x = 54, y =-52, z = 26; p>0.05, FDR corrected). Conclusions: The present questionnaire and behavioural results show that - despite the noisy and constraining MR environment) our participants had predictable changes in self-location, self-identification, and first-person perspective when robotic tactile stroking was applied synchronously with the robotic visual stroking. fMRI data in healthy participants and lesion data in patients with abnormal self-location and first-person perspective jointly revealed that the temporo-parietal cortex especially in the right hemisphere encodes these conscious experiences. We argue that temporo-parietal activity reflects the experience of the conscious "I" as embodied and localized within bodily space.
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A-7 Statistical Report On FIP Applications And Cases Discontinued
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A-1 Monthly Public Assistance Statistical Report Family Investment Program
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Statistical Report On FIP Applications And Cases Discontinued
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Statistical Report On FIP Applications And Cases Discontinued
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Statistical Report On FIP Applications And Cases Discontinued
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A1-Monthly Public Assistance Statistical Report Family Investment Program
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A-7 Statistical Report On FIP Applications And Cases Discontinued
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Monthly Public Assistance Statistical Report Family Investment Program
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Statistical Report On FIP Applications And Cases Discontinued
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A-1 Monthly Public Assistance Statistical Report Family Investment Program
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A-7 Statistical Report On FIP Applications And Cases Discontinued
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Given the rate of projected environmental change for the 21st century, urgent adaptation and mitigation measures are required to slow down the on-going erosion of biodiversity. Even though increasing evidence shows that recent human-induced environmental changes have already triggered species' range shifts, changes in phenology and species' extinctions, accurate projections of species' responses to future environmental changes are more difficult to ascertain. This is problematic, since there is a growing awareness of the need to adopt proactive conservation planning measures using forecasts of species' responses to future environmental changes. There is a substantial body of literature describing and assessing the impacts of various scenarios of climate and land-use change on species' distributions. Model predictions include a wide range of assumptions and limitations that are widely acknowledged but compromise their use for developing reliable adaptation and mitigation strategies for biodiversity. Indeed, amongst the most used models, few, if any, explicitly deal with migration processes, the dynamics of population at the "trailing edge" of shifting populations, species' interactions and the interaction between the effects of climate and land-use. In this review, we propose two main avenues to progress the understanding and prediction of the different processes A occurring on the leading and trailing edge of the species' distribution in response to any global change phenomena. Deliberately focusing on plant species, we first explore the different ways to incorporate species' migration in the existing modelling approaches, given data and knowledge limitations and the dual effects of climate and land-use factors. Secondly, we explore the mechanisms and processes happening at the trailing edge of a shifting species' distribution and how to implement them into a modelling approach. We finally conclude this review with clear guidelines on how such modelling improvements will benefit conservation strategies in a changing world. (c) 2007 Rubel Foundation, ETH Zurich. Published by Elsevier GrnbH. All rights reserved.
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Monthly Public Assistance Statistical Report Family Investment Program
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Monthly Public Assistance Statistical Report Family Investment Program