Effect of head shape variations in magnetoencephalography

IEEE Transactions on Biomedical Engineering, 2000

We study the effect of the head shape variations on the EEG/MEG forward and inverse problems.

Frontiers in neuroscience, 2016

Magnetoencephalography (MEG) signals are influenced by skull defects. However, there is a lack of evidence of this influence during source reconstruction. Our objectives are to characterize errors in source reconstruction from MEG signals due to ignoring skull defects and to assess the ability of an exact finite element head model to eliminate such errors. A detailed finite element model of the head of a rabbit used in a physical experiment was constructed from magnetic resonance and co-registered computer tomography imaging that differentiated nine tissue types. Sources of the MEG measurements above intact skull and above skull defects respectively were reconstructed using a finite element model with the intact skull and one incorporating the skull defects. The forward simulation of the MEG signals reproduced the experimentally observed characteristic magnitude and topography changes due to skull defects. Sources reconstructed from measured MEG signals above intact skull matched th...

Annals of Biomedical Engineering, 2003

Volume currents are important for the accurate calculation of magnetoencephalographic ͑MEG͒ forward or inverse simulations in realistic head models. We verify the accuracy of our finite element method implementation for MEG simulations by comparing its results for spheres containing dipoles to those obtained from the analytic solution. We then use this finite element method to show that, in an inhomogeneous, nonspherical realistic head model, the magnetic field normal to the MEG detector due to volume currents often has a magnitude on the same order or greater than the magnitude of the normal component of the primary magnetic field from the dipole. We also demonstrate the disparity in forward solutions between a model that employs spheres, one that uses the realistic head and primary currents alone, and a realistic head model that incorporates both primary and volume currents. In forward and inverse MEG simulations using the inhomogeneous realistic model, the results obtained from calculations containing volume currents are more accurate than those derived without considering volume currents.

IEEE Transactions on Biomedical Engineering, 2004

The influence of head tissue conductivity on magnetoencephalography (MEG) was investigated by comparing the normal component of the magnetic field calculated at 61 detectors and the localization accuracy of realistic head finite element method (FEM) models using dipolar sources and containing altered scalp, skull, cerebrospinal fluid, gray, and white matter conductivities to the results obtained using a FEM realistic head model with the same dipolar sources but containing published baseline conductivity values. In the models containing altered conductivity values, the tissue conductivity values were varied, one at a time, between 10% and 200% of their baseline values, and then varied simultaneously. Although changes in conductivity values for a single tissue layer often altered the calculated magnetic field and source localization accuracy only slightly, varying multiple conductivity layers simultaneously caused significant discrepancies in calculated results. The conductivity of scalp, and to a lesser extent that of white and gray matter, appears especially influential in determining the magnetic field. Comparing the results obtained from models containing the baseline conductivity values to the results obtained using other published conductivity values suggests that inaccuracies can occur depending upon which tissue conductivity values are employed. We show the importance of accurate head tissue conductivities for MEG source localization in human brain, especially for deep dipole sources or when an accuracy greater than 1.4 cm is needed.

Biomedical Engineering Online, 2006

The magnetoencephalograms (MEGs) are mainly due to the source currents. However, there is a significant contribution to MEGs from the volume currents. The structure of the anatomical surfaces, e.g., gray and white matter, could severely influence the flow of volume currents in a head model. This, in turn, will also influence the MEGs and the inverse source localizations. This was examined in detail with three different human head models.

Volume currents are important for the accurate calculation of magnetoencephalographic (MEG) forward or inverse sim- ulations in realistic head models. We verify the accuracy of the finite element method in MEG simulations by comparing its results for spheres containing dipoles to those obtained from the analytic solution. We then use the finite element method to show that,in an inhomogeneous,non-spherical realistic head model,the magnetic field normal to the MEG detector due to volume currents often has a magnitude on the same order or greater than the magnitude of the normal component of the primary magnetic field from the dipole. We also demonstrate the disparity in forward solutions be- tween a model which employs spheres,one which uses the realistic head and primary currents alone,and a realistic head model,which incorporates both primary and volume currents. In forward and inverse MEG simulations using the realistic model,the results obtained from calculations containing volume...

IEEE Transactions on Magnetics, 2009

This paper presents the methodology and some of the results of accurate solution of the forward problem in magnetic-field tomography based on magnetoencephalography for brain imaging. The solution is based on modeling and computation of magnetic-field distribution in and around the head produced by distributed 2-D cortical and 3-D volume lead current sources. The 3-D finite-element model of the brain incorporates realistic geometry based on accurate magnetic resonance imaging data and inhomogeneous conductivity properties. The model allows arbitrary placement of line, surface, and volume current sources. This gives flexibility in the source current approximation in terms of size, orientation, placement, and spatial distribution.

IEEE Transactions on Biomedical Engineering, 2006

Magnetoencephalography (MEG) provides unique insights into the spatio-temporal dynamics of neural activation in the human brain. Unfortunately, the accuracy with which neural sources can be localized is limited by the highly illposed nature of the inverse problem. A large number of inverse methods have been proposed that deal with this illposedness using a range of different modeling and regularization procedures. Here we describe an objective task-based framework for comparing different inverse methods. Using the free-response receiver operating characteristic (FROC) we compare the performance of matched filters, cortically constrained dipole scanning, and minimum norm imaging methods for the task of detecting focal cortical activation. Our results indicate that the scanning methods outperform matched filters and minimum norm imaging for the case of one and two 2 cm2 patches of cortical activity when the dynamics of the two patches are both strongly and weakly correlated and irrespective of the spacing of the two activated regions.

2006

This Thesis concerns the application of two numerical methods, Boundary Element Method (BEM) and Finite Element Method (FEM) to forward problem solution of bioelectromagnetic source localization in the brain. The aim is to improve the accuracy of the forward problem solution in estimating the electrical activity of the human brain from electric and magnetic field measurements outside the head. Electro-and magnetoencephalography (EEG, MEG) are the most important tools enabling us to gather knowledge about the human brain non-invasively. This task is alternatively named brain mapping. An important step in brain mapping is determining from where the brain signals originate. Using appropriate mathematical models, a localization of the sources of measured signals can be performed. A general motivation of this work was the fact that source localization accuracy can be improved by solving the forward problem with higher accuracy. In BEM studies, accurate representation of model geometry using higher order elements improves the solution of the forward problem. In FEM, complex conductivity information can be incorporated into numerical model. Using Whitneytype finite elements instead of using singular sources such as point dipoles, primary and volume currents are represented as continuous sources. With comparison to analytical solutions available in simple geometries such as sphere, the studied numerical methods show improvements in the forward problem solution of bioelectromagnetic source imaging.

Methods in Molecular Biology, 2009

Magnetoencephalography (MEG) encompasses a family of non-contact, non-invasive techniques for detecting the magnetic field generated by the electrical activity of the brain, for analyzing this MEG signal and for using the results to study brain function. The overall purpose of MEG is to extract estimates of the spatiotemporal patterns of electrical activity in the brain from the measured magnetic field outside the head. The electrical activity in the brain is a manifestation of collective neuronal activity and, to a large extent, the currency of brain function. The estimates of brain activity derived from MEG can therefore be used to study mechanisms and processes that support normal brain function in humans and help us understand why, when and how they fail.