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 diffusive–like 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 Ornstein–Uhlenbeck 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 diffusive–like 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 one–dimensional 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 wave–like 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 “symmetry breaking mechanism” that allows waves to propagate

Technology and Urban Management. Semiannual Report, October 1, 1967 through March 31, 1968

The projects under Technology and Urban Management (TAUM) have continued during the last few months with considerable success. The individual studies conducted in the City of Oakland and the progress made are described in this report

Power Corrections to Fragmentation Functions in Non-Singlet Deep Inelastic Scattering

We investigate the power-suppressed corrections to the fragmentation functions of the current jet in non-singlet deep inelastic lepton-hadron scattering. The current jet is defined by selecting final-state particles in the current hemisphere in the Breit frame of reference. Our method is based on an analysis of one-loop Feynman graphs containing a massive gluon, which is equivalent to the evaluation of leading infrared renormalon contributions. We find that the leading corrections are proportional to $1/Q^2$, as in $e^+e^-$ annihilation, but their functional forms are different. We give quantitative estimates based on the hypothesis of universal low-energy behaviour of the strong coupling.Comment: 14 pages, 4 figures, LaTeX2e, uses JHEP.cls (included) and epsfi

Location data and privacy: a framework for analysis

Innovative services have exploited data about users’ physical location, sometimes but not always explicitly with their consent. As new applications that reveal users’ location data appear on the Web it essential to focus on the privacy implications, in particular with respect to inferences about context. This paper focuses on the understanding of location and contextual privacy by developing a framework for analysis, which is applied to existing systems that exploit location data. The analysis highlights the primal role of location in linking and inferring contextual data, but also how these inferences can extend to non-contextual data

Resummation of the transverse-energy distribution in Higgs boson production at the Large Hadron Collider

We compute the resummed hadronic transverse-energy ($E_T$) distribution due to initial-state QCD radiation in the production of a Standard Model Higgs boson of mass 126 GeV by gluon fusion at the Large Hadron Collider, with matching to next-to-leading order calculations at large $E_T$. Effects of hadronization, underlying event and limited detector acceptance are estimated using aMC@NLO with the Herwig++ and Pythia 8 event generators.Comment: 26 pages, 13 figures. Version to appear in JHE