A fast method to compute the potential in the multisphere model (EEG application)

Munck, Jan C. de; Peters, M.J.

doi:10.1109/10.245635

Cited by 130 publications

(129 citation statements)

References 11 publications

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“…The multi-shell concentric spherical EEG forward calculation can be expressed analytically as an infinite series of Legendre polynomials, but it does not have a closed-form solution. On the other hand, the infinite series of Legendre polynomials can be approximated with some closed-form expressions (Ary et al, 1981;De Munck and Peters, 1993;Berg and Scherg, 1994;Zhang, 1995;Mosher et al, 1999). In the present study, the approach from Zhang (1995) and Mosher et al (1999) was adopted.…”

Section: Eeg and Meg Head Modelsmentioning

confidence: 99%

A novel integrated MEG and EEG analysis method for dipolar sources

et al. 2007

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The ability of magnetoencephalography (MEG) to accurately localize neuronal currents and obtain tangential components of the source is largely due to MEG's insensitivity to the conductivity profile of the head tissues. However, MEG cannot reliably detect the radial component of the neuronal current. In contrast, the localization accuracy of electroencephalography (EEG) is not as good as MEG, but EEG can detect both the tangential and radial components of the source. In the present study, we investigated the conductivity dependence in a new approach that combines MEG and EEG to accurately obtain, not only the location and tangential components, but also the radial component of the source. In this approach, the source location and tangential components are obtained from MEG alone, and optimal conductivity values of the EEG model are estimated by best-fitting EEG signal, while precisely matching the tangential components of the source in EEG and MEG. Then, the radial components are obtained from EEG using the previously estimated optimal conductivity values. Computer simulations testing this integrated approach demonstrated two main findings. First, there are well-organized optimal combinations of the conductivity values that provide an accurate fit to the combined MEG and EEG data. Second, the radial component, in addition to the location and tangential components, can be obtained with high accuracy without needing to know the precise conductivity profile of the head. We then demonstrated that this new approach performed reliably in an analysis of the 20-ms component from human somatosensory responses elicited by electric median-nerve stimulation.

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Section: Eeg and Meg Head Modelsmentioning

confidence: 99%

A novel integrated MEG and EEG analysis method for dipolar sources

et al. 2007

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“…The righthand side vector has only nonzero entries at the neighboring FE nodes to the considered dipole location. It is determined by (15) for a source at location , where the function determines the global index to each of the local indices .…”

Section: A the Fem-based Eeg Forward Problemmentioning

confidence: 99%

Geometry-Adapted Hexahedral Meshes Improve Accuracy of Finite-Element-Method-Based EEG Source Analysis

Wolters

Anwander

Berti³

et al. 2007

IEEE Trans. Biomed. Eng.

106

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Abstract-Mesh generation in finite-element-(FE) methodbased electroencephalography (EEG) source analysis generally influences greatly the accuracy of the results. It is thus important to determine a meshing strategy well adopted to achieve both acceptable accuracy for potential distributions and reasonable computation times and memory usage. In this paper, we propose to achieve this goal by smoothing regular hexahedral finite elements at material interfaces using a node-shift approach. We first present the underlying theory for two different techniques for modeling a current dipole in FE volume conductors, a subtraction and a direct potential method. We then evaluate regular and smoothed elements in a four-layer sphere model for both potential approaches and compare their accuracy. We finally compute and visualize potential distributions for a tangentially and a radially oriented source in the somatosensory cortex in regular and geometry-adapted three-compartment hexahedra FE volume conductor models of the human head using both the subtraction and the direct potential method. On the average, node-shifting reduces both topography and magnitude errors by more than a factor of 2 for tangential and 1.5 for radial sources for both potential approaches. Nevertheless, node-shifting has to be carried out with caution for sources located within or close to irregular hexahedra, because especially for the subtraction method extreme deformations might lead to larger overall errors. With regard to realistic volume conductor modeling, node-shifted hexahedra should thus be used for the skin and skull compartments while we would not recommend deforming elements at the grey and white matter surfaces.

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“…An analytical solution has been derived for obtaining the potential distribution on the surface of an ellipsoid given an arbitrarily located current dipole [15,16,17]. The analytical approach is used as the ground truth when testing new methods.…”

Section: Introductionmentioning

confidence: 99%

A finite-element reciprocity solution for EEG forward modeling with realistic individual head models

et al. 2014

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We present a finite element modeling (FEM) implementation for solving the forward problem in electroencephalography (EEG). The solution is based on Helmholtz's principle of reciprocity which allows for dramatically reduced computational time when constructing the leadfield matrix. The approach was validated using a 4-shell spherical model and shown to perform comparably with two current state-of-the-art alternatives (OpenMEEG for boundary element modeling and SimBio for finite element modeling).We applied the method to real human brain MRI data and created a model with five tissue types: white matter, grey matter, cerebrospinal fluid, skull, and scalp. By calculating conductivity tensors from diffusion-weighted MR images, we also demonstrate one of the main benefits of FEM: the ability to include anisotropic conductivities within the head model. Root-mean square deviation between the standard leadfield and the leadfield including white-matter anisotropy showed that ignoring the directional conductivity of white matter fiber tracts leads to orientation-specific errors in the forward model. Realistic head models are necessary for precise source localization in individuals. Our approach is fast, accurate, open-source and freely available online.

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A fast method to compute the potential in the multisphere model (EEG application)

Cited by 130 publications

References 11 publications

A novel integrated MEG and EEG analysis method for dipolar sources

A novel integrated MEG and EEG analysis method for dipolar sources

Geometry-Adapted Hexahedral Meshes Improve Accuracy of Finite-Element-Method-Based EEG Source Analysis

A finite-element reciprocity solution for EEG forward modeling with realistic individual head models

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