6,042 research outputs found
Front propagation in stochastic neural fields
We analyse the effects of extrinsic multiplicative noise on front propagation in a scalar neural field with excitatory connections. Using a separation of time scales, we represent the fluctuating front in terms of a diffusiveâlike displacement (wandering) of the front from its uniformly translating position at long time scales, and fluctuations in the front profile around its instantaneous position at short time scales. One major result of our analysis is a comparison between freely propagating fronts and fronts locked to an externally moving stimulus. We show that the latter are much more robust to noise, since the stochastic wandering of the mean front profile is described by an OrnsteinâUhlenbeck process rather than a Wiener process, so that the variance in front position saturates in the long time limit rather than increasing linearly with time. Finally, we consider a stochastic neural field that supports a pulled front in the deterministic limit, and show that the wandering of such a front is now subdiffusive
The effects of noise on binocular rivalry waves: a stochastic neural field model
We analyse the effects of extrinsic noise on traveling waves of visual perception in a competitive neural field model of binocular rivalry. The model consists of two one-dimensional excitatory neural fields, whose activity variables represent the responses to left-eye and right-eye stimuli, respectively. The two networks mutually inhibit each other, and slow adaptation is incorporated into the model by taking the network connections to exhibit synaptic depression. We first show how, in the absence of any noise, the system supports a propagating composite wave consisting of an invading activity front in one network co-moving with a retreating front in the other network. Using a separation of time scales and perturbation methods previously developed for stochastic reaction-diffusion equations, we then show how multiplicative noise in the activity variables leads to a diffusiveâlike displacement (wandering) of the composite wave from its uniformly translating position at long time scales, and fluctuations in the wave profile around its instantaneous position at short time scales. The multiplicative noise also renormalizes the mean speed of the wave. We use our analysis to calculate the first passage time distribution for a stochastic rivalry wave to travel a fixed distance, which we find to be given by an inverse Gaussian. Finally, we investigate the effects of noise in the depression variables, which under an adiabatic approximation leads to quenched disorder in the neural fields during propagation of a wave
Neural field model of binocular rivalry waves
We present a neural field model of binocular rivalry waves in visual cortex. For each eye we consider a oneâdimensional network of neurons that respond maximally to a particular feature of the corresponding image such as the orientation of a grating stimulus. Recurrent connections within each one-dimensional network are assumed to be excitatory, whereas connections between the two networks are inhibitory (cross-inhibition). Slow adaptation is incorporated into the model by taking the network connections to exhibit synaptic depression. We derive an analytical expression for the speed of a binocular rivalry wave as a function of various neurophysiological parameters, and show how properties of the wave are consistent with the waveâlike propagation of perceptual dominance observed in recent psychophysical experiments. In addition to providing an analytical framework for studying binocular rivalry waves, we show how neural field methods provide insights into the mechanisms underlying the generation of the waves. In particular, we highlight the important role of slow adaptation in providing a âsymmetry breaking mechanismâ that allows waves to propagate
The cultural, ethnic and linguistic classification of populations and neighbourhoods using personal names
There are growing needs to understand the nature and detailed composition of ethnicgroups in today?s increasingly multicultural societies. Ethnicity classifications areoften hotly contested, but still greater problems arise from the quality and availabilityof classifications, with knock on consequences for our ability meaningfully tosubdivide populations. Name analysis and classification has been proposed as oneefficient method of achieving such subdivisions in the absence of ethnicity data, andmay be especially pertinent to public health and demographic applications. However,previous approaches to name analysis have been designed to identify one or a smallnumber of ethnic minorities, and not complete populations.This working paper presents a new methodology to classify the UK population andneighbourhoods into groups of common origin using surnames and forenames. Itproposes a new ontology of ethnicity that combines some of its multidimensionalfacets; language, religion, geographical region, and culture. It uses data collected atvery fine temporal and spatial scales, and made available, subject to safeguards, at thelevel of the individual. Such individuals are classified into 185 independentlyassigned categories of Cultural Ethnic and Linguistic (CEL) groups, based on theprobable origins of names. We include a justification for the need of classifyingethnicity, a proposed CEL taxonomy, a description of how the CEL classification wasbuilt and applied, a preliminary external validation, and some examples of current andpotential applications
A Positive-Weight Next-to-Leading-Order Monte Carlo for e+e- Annihilation to Hadrons
We apply the positive-weight Monte Carlo method of Nason for simulating QCD
processes accurate to Next-To-Leading Order to the case of e+e- annihilation to
hadrons. The method entails the generation of the hardest gluon emission first
and then subsequently adding a `truncated' shower before the emission. We have
interfaced our result to the Herwig++ shower Monte Carlo program and obtained
better results than those obtained with Herwig++ at leading order with a matrix
element correction.Comment: 21 pages, 11 figures, 2 tables Reason for replacement: minor
corrections, typos and 1 changed referenc
The wellbeing of allotment gardeners: a mixed methodological study
Purpose: The potential for ââgreenââ interventions to promote mental wellbeing and reduce mental distress is increasingly being recognized. Preliminary evidence suggests that allotment gardening activities may have a
significant effect on mental well-being, but a need for further research has been highlighted. This study investigated the relationships between allotment gardening, feeling connected to nature, and well-being.
Design: A mixed-methods design was utilized. Measures of subjective well-being (quality of life), eudaimonic well-being, and connectedness to nature were administered, and qualitative data were collected via a cross-sectional online survey of 171 allotment gardeners in the United Kingdom.
Findings: Allotment gardenersâ eudaimonic well-being and quality of life in the environmental domain were significantly higher than population means reported in the literature. Regression analysis showed that the amount of time gardeners spent on their allotment during summer predicted eudaimonic well-being. This relationship was fully mediated by feelings of connectedness to nature. Four main themes emerged from the qualitative data: allotments provided a space of oneâs own, meaningful activity, increased feelings of connectedness, and improved physical and mental health.
Conclusions: The results suggest that allotment gardening is associated with increased eudaimonic well-being but not subjective wellbeing. Furthermore, a mechanism through which allotment gardening enhances well-being is suggested: increased connectedness to nature. Limitations of the study and clinical and research implications are discussed.
Key Words: Allotment gardeningâConnectedness to natureâWell-beingâEudaimonia
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