Simultaneous MEG and EEG source analysis.

A method is described to derive source and conductivity estimates in a simultaneous MEG and EEG source analysis. In addition the covariance matrix of the estimates is derived. Simulation studies with a concentric spheres model and a more realistic boundary element model indicate that this method has several advantages, even if only a few EEG sensors are added to a MEG configuration. First, a simultaneous analysis profits from the 'preferred' location directions of MEG and EEG. Second, deep sources can be estimated quite accurately, which is an advantage compared to MEG. Third, superficial sources profit from accurate MEG location and from accurate EEG moment. Fourth, the radial source component can be estimated, which is an advantage compared to MEG. Fifth, the conductivities can be estimated. It is shown that conductivity estimation gives a substantial increase in precision, even if the conductivities are not identified appropriately. An illustrative analysis of empirical data supports these findings.

[1]  J. Kenemans,et al.  Feature processing and attention in the human visual system: an overview , 1997, Biological Psychology.

[2]  J. D. de Munck,et al.  The influence of model parameters on the inverse solution based on MEGs and EEGs. , 1991, Acta oto-laryngologica. Supplementum.

[3]  Philip E. Gill,et al.  Practical optimization , 1981 .

[4]  Carlos H. Muravchik,et al.  MEG/EEG numerical error bounds for a dipole source with a realistic head model , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).

[5]  M. E. Spencer,et al.  Error bounds for EEG and MEG dipole source localization. , 1993, Electroencephalography and clinical neurophysiology.

[6]  M Wagner,et al.  Improving source reconstructions by combining bioelectric and biomagnetic data. , 1998, Electroencephalography and clinical neurophysiology.

[7]  R. Ilmoniemi,et al.  MEG-compatible multichannel EEG electrode array. , 1996, Electroencephalography and clinical neurophysiology.

[8]  P C Molenaar,et al.  Estimating and Testing the Sources of Evoked Potentials in the Brain. , 1994, Multivariate behavioral research.

[9]  V Diekmann,et al.  Localisation of epileptic foci with electric, magnetic and combined electromagnetic models. , 1998, Electroencephalography and clinical neurophysiology.

[10]  J. P. Ary,et al.  Location of Sources of Evoked Scalp Potentials: Corrections for Skull and Scalp Thicknesses , 1981, IEEE Transactions on Biomedical Engineering.

[11]  Cees J. Stok,et al.  The influence of model parameters on EEG/MEG single dipole source estimation , 1987, IEEE Transactions on Biomedical Engineering.

[12]  Peter C. M. Molenaar,et al.  Estimated generalized least squares electromagnetic source analysis based on a parametric noise covariance model [EEG/MEG] , 2001, IEEE Transactions on Biomedical Engineering.

[13]  J. Sarvas Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem. , 1987, Physics in medicine and biology.

[14]  J.C. de Munck,et al.  A random dipole model for spontaneous brain activity , 1992, IEEE Transactions on Biomedical Engineering.

[15]  J C de Munck,et al.  The application of electrical impedance tomography to reduce systematic errors in the EEG inverse problem - a simulation study , 2000, Physiological measurement.

[16]  A. H. C. van der Heijden,et al.  Selective Attention in Vision , 1991 .

[17]  R. Hari,et al.  Spatial resolution of neuromagnetic records: theoretical calculations in a spherical model. , 1988, Electroencephalography and clinical neurophysiology.

[18]  M. Browne,et al.  Automated Fitting of Nonstandard Models. , 1992, Multivariate behavioral research.

[19]  D. Cohen,et al.  Comparison of the magnetoencephalogram and electroencephalogram. , 1979, Electroencephalography and clinical neurophysiology.

[20]  F Takeuchi,et al.  Locating accuracy of a current source of neuromagnetic responses: simulation study for a single current dipole in a spherical conductor. , 1989, Electroencephalography and clinical neurophysiology.

[21]  P C Molenaar,et al.  Ordinary least squares dipole localization is influenced by the reference. , 1996, Electroencephalography and clinical neurophysiology.

[22]  J L Kenemans,et al.  Localization of spatial attention processes with the aid of a probe technique. , 1998, Electroencephalography and clinical neurophysiology.

[23]  B. Lutkenhoner Current dipole localization with an ideal magnetometer system , 1996, IEEE Transactions on Biomedical Engineering.

[24]  D. Cohen,et al.  Demonstration of useful differences between magnetoencephalogram and electroencephalogram. , 1983, Electroencephalography and clinical neurophysiology.

[25]  Sylvain Baillet,et al.  A Bayesian approach to introducing anatomo-functional priors in the EEG/MEG inverse problem , 1997, IEEE Transactions on Biomedical Engineering.

[26]  F Mauguière,et al.  A consensus statement on relative merits of EEG and MEG. European Concerted Action on Biomagnetism, Lyon meeting, November 26 and 27, 1991. , 1992, Electroencephalography and clinical neurophysiology.

[27]  Don M. Tucker,et al.  Regional head tissue conductivity estimation for improved EEG analysis , 2000, IEEE Transactions on Biomedical Engineering.

[28]  J. Haueisen,et al.  Influence of tissue resistivities on neuromagnetic fields and electric potentials studied with a finite element model of the head , 1997, IEEE Transactions on Biomedical Engineering.

[29]  R. Ilmoniemi,et al.  Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain , 1993 .