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  Efficient computation of lead field bases and influence matrix for the FEM-based EEG and MEG inverse problem

Wolters, C. H., Grasedyck, L., Anwander, A., & Hackbush, W. (2004). Efficient computation of lead field bases and influence matrix for the FEM-based EEG and MEG inverse problem. Inverse Problems, 20(4), 1099-1116. doi:10.1088/0266-5611/20/4/007.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-4110-1 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-4111-0
Genre: Journal Article

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 Creators:
Wolters, Carsten Hermann1, 2, Author              
Grasedyck, Lars2, Author
Anwander, Alfred3, Author              
Hackbush, Wolfgang2, Author
Affiliations:
1Methods and Development Unit MEG and EEG: Signal Analysis and Modelling, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634559              
2External Organizations, ou_persistent22              
3Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              

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 Abstract: The inverse problem in electro- and magneto-encephalography (EEG/MEG) aims at reconstructing the underlying current distribution in the human brain using potential differences and/or magnetic fluxes that are measured noninvasively directly, or at a close distance, from the head surface. The simulation of EEG and MEG fields for a given dipolar source in the brain using a volume-conduction model of the head is called the forward problem. The finite element (FE) method, used for the forward problem, is able to realistically model tissue conductivity inhomogeneities and anisotropies, which is crucial for an accurate reconstruction of the current distribution. So far, the computational complexity is quite large when using the necessary high resolution FE models. In this paper we will extend the concept of the EEG lead field basis to the MEG and present algorithms for their efficient computation. Exploiting the fact that the number of sensors is generally much smaller than the number of reasonable dipolar sources, our lead field approach will speed up the state-of-the-art forward approach by a factor of more than 100 for a realistic choice of the number of sensors and sources. Our approaches can be applied to inverse reconstruction algorithms in both continuous and discrete source parameter space for EEG and MEG. In combination with algebraic multigrid solvers, the presented approach leads to a highly efficient solution of FE-based source reconstruction problems.

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Language(s): eng - English
 Dates: 2003-11-112004-05-21
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1088/0266-5611/20/4/007
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Title: Inverse Problems
Source Genre: Journal
 Creator(s):
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Publ. Info: London? : IOP Pub.
Pages: - Volume / Issue: 20 (4) Sequence Number: - Start / End Page: 1099 - 1116 Identifier: ISSN: 0266-5611
CoNE: https://pure.mpg.de/cone/journals/resource/954925499121