Error bounds for EEG and MEG dipole source localization
نویسندگان
چکیده
منابع مشابه
Error bounds for EEG and MEG dipole source localization.
General formulas are presented for computing a lower bound on localization and moment error for electroencephalographic (EEG) or magnetoencephalographic (MEG) current source dipole models with arbitrary sensor array geometry. Specific EEG and MEG formulas are presented for multiple dipoles in a head model with 4 spherical shells. Localization error bounds are presented for both EEG and MEG for ...
متن کاملMEG/EEG hybrid method for source localization of a dipole with radial component
MEG is a useful method to know brain activities, and has a remarkable feature that the source location is estimated with high accuracy. However MEG is insensitive to a radial current dipole, because a radial dipole in a sphere makes no magnetic field outside the sphere and the shape of human head resembles a sphere. To realize more accurate localization, there is a requirement to estimate a rad...
متن کاملEEG/MEC error bounds for a static dipole source with a realistic head model
This work presents the background and derivation of Cramér-Rao bounds on the errors of estimating the parameters (moment and location) of a dynamic current dipole source using data from electro- and magneto-encephalography. A realistic head model, based on knowledge of surfaces separating tissues of different conductivities, is used.
متن کاملLarge-scale EEG/MEG source localization with spatial flexibility
We propose a novel approach to solving the electro-/magnetoencephalographic (EEG/MEG) inverse problem which is based upon a decomposition of the current density into a small number of spatial basis fields. It is designed to recover multiple sources of possibly different extent and depth, while being invariant with respect to phase angles and rotations of the coordinate system. We demonstrate th...
متن کاملMEG/EEG Source Localization Using Spatio-temporal Sparse Representations
1. Abstract Inverse MEG/EEG problem is known to be ill-posed and no single solution can be found without utilizing some prior knowledge about the nature of signal sources, the way the signals are propagating and finally collected by the sensors. The signals are assumed to have a sparse representation in appropriate domain, e.g. wavelet transform, and spatial locality of sources is assumed, the ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Electroencephalography and Clinical Neurophysiology
سال: 1993
ISSN: 0013-4694
DOI: 10.1016/0013-4694(93)90043-u