Paper Info
Title
Error bounds of EEG/MEG for a stationary dipole source with a realistic head model
Abstract
We derive Cramer-Rao bounds (CRBs) on the errors of estimating the parameters (location and moment) of a current dipole source using data from electro-encephalography (EEG), magneto-encephalography (MEG), or the combined EEG/MEG modality. We use a realistic head model based on knowledge of surfaces separating tissues of different conductivities, obtained from magnetic resonance (MR) or computer tomography (CT) imaging systems. The electric potentials and magnetic field components at the respective sensors are functions of the source parameters through integral equations. These potentials and field are computed using the boundary or the finite element method (BEM or FEM), with a weighted residuals technique. We present a unified framework for the measurements computed by these methods that enables the derivation of the bounds. The resulting bounds may be used, for instance, to choose the best configuration of the sensors for a given patient and region of expected source location. Numerical results are used to demonstrate an application for shelving expected accuracies in estimating the source parameters as a function of its position in the brain, based on real EEG/MEG system and MR or CT images. The results include contours of equal precision in the estimation and surfaces showing the size of the 90% confidence volume for a dipole on a sphere inside the brain.
Year
DOI
Venue
2000
10.1109/ICASSP.2000.860221
Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference
Keywords
Field
DocType
bioelectric potentials,biomedical MRI,computerised tomography,electroencephalography,finite element analysis,magnetic fields,magnetoencephalography,parameter estimation,patient care,BEM,CT imaging systems,Cramer-Rao bounds,EEG/MEG,FEM,MR imaging systems,brain,computer tomography,confidence volume,electric potentials,electro-encephalography,error bounds,finite element method,head model,integral equations,magnetic field components,magnetic resonance,magneto-encephalography,parameter estimation errors,patient,source parameters,sphere,stationary dipole source,tissue conductivity,weighted residuals technique
Magnetic field,Pattern recognition,Computer science,Mathematical analysis,Integral equation,Finite element method,Tomography,Artificial intelligence,Estimation theory,Dipole,Electroencephalography,Magnetoencephalography
Conference
Volume
ISSN
ISBN
6
1520-6149
0-7803-6293-4
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
C. Muravchik154368.59
Nehorai, Arye21934309.00