Fast reconstruction of harmonic functions from Cauchy data using the Dirichlet-to-Neumann map and integral equations

We propose and investigate a method for the stable determination of a harmonic function from knowledge of its value and its normal derivative on a part of the boundary of the (bounded) solution domain (Cauchy problem). We reformulate the Cauchy problem as an operator equation on the boundary using the Dirichlet-to-Neumann map. To discretize the obtained operator, we modify and employ a method denoted as Classic II given in [J. Helsing, Faster convergence and higher accuracy for the Dirichlet–Neumann map, J. Comput. Phys. 228 (2009), pp. 2578–2576, Section 3], which is based on Fredholm integral equations and Nyström discretization schemes. Then, for stability reasons, to solve the discretized integral equation we use the method of smoothing projection introduced in [J. Helsing and B.T. Johansson, Fast reconstruction of harmonic functions from Cauchy data using integral equation techniques, Inverse Probl. Sci. Eng. 18 (2010), pp. 381–399, Section 7], which makes it possible to solve the discretized operator equation in a stable way with minor computational cost and high accuracy. With this approach, for sufficiently smooth Cauchy data, the normal derivative can also be accurately computed on the part of the boundary where no data is initially given.

Distinct contrast response functions in striate and extra-striate regions of visual cortex revealed with magnetoencephalography (MEG)

Objective: To spatially and temporally characterise the cortical contrast response function to pattern onset stimuli in humans. Methods: Magnetoencephalography (MEG) was used to investigate the human cortical contrast response function to pattern onset stimuli with high temporal and spatial resolution. A beamformer source reconstruction approach was used to spatially localise and identify the time courses of activity at various visual cortical loci. Results: Consistent with the findings of previous studies, MEG beamformer analysis revealed two simultaneous generators of the pattern onset evoked response. These generators arose from anatomically discrete locations in striate and extra-striate visual cortex. Furthermore, these loci demonstrated notably distinct contrast response functions, with striate cortex increasing approximately linearly with contrast, whilst extra-striate visual cortex followed a saturating function. Conclusions: The generators that underlie the pattern onset visual evoked response arise from two distinct regions in striate and extra-striate visual cortex. Significance: The spatially, temporally and functionally distinct mechanisms of contrast processing within the visual cortex may account for the disparate results observed across earlier studies and assist in elucidating causal mechanisms of aberrant contrast processing in neurological disorders. © 2005 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Numerical solution of the Dirichlet initial boundary value problem for the heat equation in exterior 3-dimensional domains using integral equations

A numerical method for the Dirichlet initial boundary value problem for the heat equation in the exterior and unbounded region of a smooth closed simply connected 3-dimensional domain is proposed and investigated. This method is based on a combination of a Laguerre transformation with respect to the time variable and an integral equation approach in the spatial variables. Using the Laguerre transformation in time reduces the parabolic problem to a sequence of stationary elliptic problems which are solved by a boundary layer approach giving a sequence of boundary integral equations of the first kind to solve. Under the assumption that the boundary surface of the solution domain has a one-to-one mapping onto the unit sphere, these integral equations are transformed and rewritten over this sphere. The numerical discretisation and solution are obtained by a discrete projection method involving spherical harmonic functions. Numerical results are included.