786 resultados para Structural model of child well-being


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Eudaimonic well-being—a sense of purpose, meaning, and engagement with life—is protective against psychopathology and predicts physical health, including lower levels of the stress hormone cortisol. Although it has been suggested that the ability to engage the neural circuitry of reward may promote well-being and mediate the relationship between well-being and health, this hypothesis has remained untested. To test this hypothesis, we had participants view positive, neutral, and negative images while fMRI data were collected. Individuals with sustained activity in the striatum and dorsolateral prefrontal cortex to positive stimuli over the course of the scan session reported greater well-being and had lower cortisol output. This suggests that sustained engagement of reward circuitry in response to positive events underlies well-being and adaptive regulation of the hypothalamic-pituitary-adrenal axis.

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Introduction: Young onset dementia (YOD) affects about 1 in 1500 people aged under 65 years in the UK. It is associated with loss of employment, independence and an increase in psychological distress. This project set out to identify the benefits of a 2 hour week) structured activity programme of gardening for people with YOD. Method: A mixed qualitative quantitative study of therapeutic gardening for people with YOD, measuring outcomes for both participants with YOD and their carers. 12 participants were recruited from a county wide older adults mental health service, based on onset of dementia being before 65 years of age(range 43-65 years). 2 dropped out and 1 died during the project. Measures included the Mini Mental State Examination, Bradford Well Being Profile, Large Allen Cognitive Level Screen and Pool Activity Level. Results: Over a one year period the carers of the people with YOD found that the project had given participants a renewed sense of purpose and increased well-being. while cognitive functioning declined. Conclusions: This study suggests that a meaningful guided activity programme can maintain or improve well-being in the presence of cognitive deterioration.

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Neurovascular coupling in response to stimulation of the rat barrel cortex was investigated using concurrent multichannel electrophysiology and laser Doppler flowmetry. The data were used to build a linear dynamic model relating neural activity to blood flow. Local field potential time series were subject to current source density analysis, and the time series of a layer IV sink of the barrel cortex was used as the input to the model. The model output was the time series of the changes in regional cerebral blood flow (CBF). We show that this model can provide excellent fit of the CBF responses for stimulus durations of up to 16 s. The structure of the model consisted of two coupled components representing vascular dilation and constriction. The complex temporal characteristics of the CBF time series were reproduced by the relatively simple balance of these two components. We show that the impulse response obtained under the 16-s duration stimulation condition generalised to provide a good prediction to the data from the shorter duration stimulation conditions. Furthermore, by optimising three out of the total of nine model parameters, the variability in the data can be well accounted for over a wide range of stimulus conditions. By establishing linearity, classic system analysis methods can be used to generate and explore a range of equivalent model structures (e.g., feed-forward or feedback) to guide the experimental investigation of the control of vascular dilation and constriction following stimulation.

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We present a dynamic causal model that can explain context-dependent changes in neural responses, in the rat barrel cortex, to an electrical whisker stimulation at different frequencies. Neural responses were measured in terms of local field potentials. These were converted into current source density (CSD) data, and the time series of the CSD sink was extracted to provide a time series response train. The model structure consists of three layers (approximating the responses from the brain stem to the thalamus and then the barrel cortex), and the latter two layers contain nonlinearly coupled modules of linear second-order dynamic systems. The interaction of these modules forms a nonlinear regulatory system that determines the temporal structure of the neural response amplitude for the thalamic and cortical layers. The model is based on the measured population dynamics of neurons rather than the dynamics of a single neuron and was evaluated against CSD data from experiments with varying stimulation frequency (1–40 Hz), random pulse trains, and awake and anesthetized animals. The model parameters obtained by optimization for different physiological conditions (anesthetized or awake) were significantly different. Following Friston, Mechelli, Turner, and Price (2000), this work is part of a formal mathematical system currently being developed (Zheng et al., 2005) that links stimulation to the blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal through neural activity and hemodynamic variables. The importance of the model described here is that it can be used to invert the hemodynamic measurements of changes in blood flow to estimate the underlying neural activity.

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We describe a mathematical model linking changes in cerebral blood flow, blood volume and the blood oxygenation state in response to stimulation. The model has three compartments to take into account the fact that the cerebral blood flow and volume as measured concurrently using laser Doppler flowmetry and optical imaging spectroscopy have contributions from the arterial, capillary as well as the venous compartments of the vasculature. It is an extension to previous one-compartment hemodynamic models which assume that the measured blood volume changes are from the venous compartment only. An important assumption of the model is that the tissue oxygen concentration is a time varying state variable of the system and is driven by the changes in metabolic demand resulting from changes in neural activity. The model takes into account the pre-capillary oxygen diffusion by flexibly allowing the saturation of the arterial compartment to be less than unity. Simulations are used to explore the sensitivity of the model and to optimise the parameters for experimental data. We conclude that the three-compartment model was better than the one-compartment model at capturing the hemodynamics of the response to changes in neural activation following stimulation.

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This article elucidates the Typological Primacy Model (TPM; Rothman, 2010, 2011, 2013) for the initial stages of adult third language (L3) morphosyntactic transfer, addressing questions that stem from the model and its application. The TPM maintains that structural proximity between the L3 and the L1 and/or the L2 determines L3 transfer. In addition to demonstrating empirical support for the TPM, this article articulates a proposal for how the mind unconsciously determines typological (structural) proximity based on linguistic cues from the L3 input stream used by the parser early on to determine holistic transfer of one previous (the L1 or the L2) system. This articulated version of the TPM is motivated by argumentation appealing to cognitive and linguistic factors. Finally, in line with the general tenets of the TPM, I ponder if and why L3 transfer might obtain differently depending on the type of bilingual (e.g. early vs. late) and proficiency level of bilingualism involved in the L3 process.

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We present an efficient method of combining wide angle neutron scattering data with detailed atomistic models, allowing us to perform a quantitative and qualitative mapping of the organisation of the chain conformation in both glass and liquid phases. The structural refinement method presented in this work is based on the exploitation of the intrachain features of the diffraction pattern and its intimate linkage with atomistic models by the use of internal coordinates for bond lengths, valence angles and torsion rotations. Atomic connectivity is defined through these coordinates that are in turn assigned by pre-defined probability distributions, thus allowing for the models in question to be built stochastically. Incremental variation of these coordinates allows for the construction of models that minimise the differences between the observed and calculated structure factors. We present a series of neutron scattering data of 1,2 polybutadiene at the region 120-400K. Analysis of the experimental data yield bond lengths for C-C and C=C of 1.54Å and 1.35Å respectively. Valence angles of the backbone were found to be at 112° and the torsion distributions are characterised by five rotational states, a three-fold trans-skew± for the backbone and gauche± for the vinyl group. Rotational states of the vinyl group were found to be equally populated, indicating a largely atactic chan. The two backbone torsion angles exhibit different behaviour with respect to temperature of their trans population, with one of them adopting an almost all trans sequence. Consequently the resulting configuration leads to a rather persistent chain, something indicated by the value of the characteristic ratio extrapolated from the model. We compare our results with theoretical predictions, computer simulations, RIS models and previously reported experimental results.

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Current feed evaluation systems for ruminants are too imprecise to describe diets in terms of their acidosis risk. The dynamic mechanistic model described herein arises from the integration of a lactic acid (La) metabolism module into an extant model of whole-rumen function. The model was evaluated using published data from cows and sheep fed a range of diets or infused with various doses of La. The model performed well in simulating peak rumen La concentrations (coefficient of determination = 0.96; root mean square prediction error = 16.96% of observed mean), although frequency of sampling for the published data prevented a comprehensive comparison of prediction of time to peak La accumulation. The model showed a tendency for increased La accumulation following feeding of diets rich in nonstructural carbohydrates, although less-soluble starch sources such as corn tended to limit rumen La concentration. Simulated La absorption from the rumen remained low throughout the feeding cycle. The competition between bacteria and protozoa for rumen La suggests a variable contribution of protozoa to total La utilization. However, the model was unable to simulate the effects of defaunation on rumen La metabolism, indicating a need for a more detailed description of protozoal metabolism. The model could form the basis of a feed evaluation system with regard to rumen La metabolism.

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Burst suppression in the electroencephalogram (EEG) is a well-described phenomenon that occurs during deep anesthesia, as well as in a variety of congenital and acquired brain insults. Classically it is thought of as spatially synchronous, quasi-periodic bursts of high amplitude EEG separated by low amplitude activity. However, its characterization as a “global brain state” has been challenged by recent results obtained with intracranial electrocortigraphy. Not only does it appear that burst suppression activity is highly asynchronous across cortex, but also that it may occur in isolated regions of circumscribed spatial extent. Here we outline a realistic neural field model for burst suppression by adding a slow process of synaptic resource depletion and recovery, which is able to reproduce qualitatively the empirically observed features during general anesthesia at the whole cortex level. Simulations reveal heterogeneous bursting over the model cortex and complex spatiotemporal dynamics during simulated anesthetic action, and provide forward predictions of neuroimaging signals for subsequent empirical comparisons and more detailed characterization. Because burst suppression corresponds to a dynamical end-point of brain activity, theoretically accounting for its spatiotemporal emergence will vitally contribute to efforts aimed at clarifying whether a common physiological trajectory is induced by the actions of general anesthetic agents. We have taken a first step in this direction by showing that a neural field model can qualitatively match recent experimental data that indicate spatial differentiation of burst suppression activity across cortex.

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Pronounced intermodel differences in the projected response of land surface precipitation (LSP) to future anthropogenic forcing remain in the Coupled Model Intercomparison Project Phase 5 model integrations. A large fraction of the intermodel spread in projected LSP trends is demonstrated here to be associated with systematic differences in simulated sea surface temperature (SST) trends, especially the representation of changes in (i) the interhemispheric SST gradient and (ii) the tropical Pacific SSTs. By contrast, intermodel differences in global mean SST, representative of differing global climate sensitivities, exert limited systematic influence on LSP patterns. These results highlight the importance to regional terrestrial precipitation changes of properly simulating the spatial distribution of large-scale, remote changes as reflected in the SST response to increasing greenhouse gases. Moreover, they provide guidance regarding which region-specific precipitation projections may be potentially better constrained for use in climate change impact assessments.

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Increasing prominence of the psychological ownership (PO) construct in management studies raises questions about how PO manifests at the level of the individual. In this article, we unpack the mechanism by which individuals use PO to express aspects of their identity and explore how PO manifestations can display congruence as well as incongruence between layers of self. As a conceptual foundation, we develop a dynamic model of individual identity that differentiates between four layers of self, namely, the “core self,” “learned self,” “lived self,” and “perceived self.” We then bring identity and PO literatures together to suggest a framework of PO manifestation and expression viewed through the lens of the four presented layers of self. In exploring our framework, we develop a number of propositions that lay the foundation for future empirical and conceptual work and discuss implications for theory and practice.

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This article elucidates the Typological Primacy Model (TPM; Rothman, 2010, 2011, 2013) for the initial stages of adult third language (L3) morphosyntactic transfer, addressing questions that stem from the model and its application. The TPM maintains that structural proximity between the L3 and the L1 and/or the L2 determines L3 transfer. In addition to demonstrating empirical support for the TPM, this article articulates a proposal for how the mind unconsciously determines typological (structural) proximity based on linguistic cues from the L3 input stream used by the parser early on to determine holistic transfer of one previous (the L1 or the L2) system. This articulated version of the TPM is motivated by argumentation appealing to cognitive and linguistic factors. Finally, in line with the general tenets of the TPM, I ponder if and why L3 transfer might obtain differently depending on the type of bilingual (e.g. early vs. late) and proficiency level of bilingualism involved in the L3 process.

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Economic theory makes no predictions about social factors affecting decisions under risk. We examine situations in which a decision maker decides for herself and another person under conditions of payoff equality, and compare them to individual decisions. By estimating a structural model, we find that responsibility leaves utility curvature unaffected, but accentuates the subjective distortion of very small and very large probabilities for both gains and losses. We also find that responsibility reduces loss aversion, but that these results only obtain under some specific definitions of the latter. These results serve to generalize and reconcile some of the still largely contradictory findings in the literature. They also have implications for financial agency, which we discuss.

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Animal models of acquired epilepsies aim to provide researchers with tools for use in understanding the processes underlying the acquisition, development and establishment of the disorder. Typically, following a systemic or local insult, vulnerable brain regions undergo a process leading to the development, over time, of spontaneous recurrent seizures. Many such models make use of a period of intense seizure activity or status epilepticus, and this may be associated with high mortality and/or global damage to large areas of the brain. These undesirable elements have driven improvements in the design of chronic epilepsy models, for example the lithium-pilocarpine epileptogenesis model. Here, we present an optimised model of chronic epilepsy that reduces mortality to 1% whilst retaining features of high epileptogenicity and development of spontaneous seizures. Using local field potential recordings from hippocampus in vitro as a probe, we show that the model does not result in significant loss of neuronal network function in area CA3 and, instead, subtle alterations in network dynamics appear during a process of epileptogenesis, which eventually leads to a chronic seizure state. The model’s features of very low mortality and high morbidity in the absence of global neuronal damage offer the chance to explore the processes underlying epileptogenesis in detail, in a population of animals not defined by their resistance to seizures, whilst acknowledging and being driven by the 3Rs (Replacement, Refinement and Reduction of animal use in scientific procedures) principles.

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Trust and reputation are important factors that influence the success of both traditional transactions in physical social networks and modern e-commerce in virtual Internet environments. It is difficult to define the concept of trust and quantify it because trust has both subjective and objective characteristics at the same time. A well-reported issue with reputation management system in business-to-consumer (BtoC) e-commerce is the “all good reputation” problem. In order to deal with the confusion, a new computational model of reputation is proposed in this paper. The ratings of each customer are set as basic trust score events. In addition, the time series of massive ratings are aggregated to formulate the sellers’ local temporal trust scores by Beta distribution. A logical model of trust and reputation is established based on the analysis of the dynamical relationship between trust and reputation. As for single goods with repeat transactions, an iterative mathematical model of trust and reputation is established with a closed-loop feedback mechanism. Numerical experiments on repeated transactions recorded over a period of 24 months are performed. The experimental results show that the proposed method plays guiding roles for both theoretical research into trust and reputation and the practical design of reputation systems in BtoC e-commerce.