Large-scale EEG/MEG source localization with spatial flexibility

Stefan Haufe; Ryota Tomioka; Thorsten Dickhaus; Claudia Sannelli; Benjamin Blankertz; Guido Nolte; Klaus Robert Müller

doi:10.1016/j.neuroimage.2010.09.003

Large-scale EEG/MEG source localization with spatial flexibility

Stefan Haufe, Ryota Tomioka, Thorsten Dickhaus, Claudia Sannelli, Benjamin Blankertz, Guido Nolte, Klaus Robert Müller

Research output: Contribution to journal › Article › peer-review

80 Citations (Scopus)

Abstract

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 the method's ability to reconstruct simulated sources of random shape and show that the accuracy of the recovered sources can be increased, when interrelated field patterns are co-localized. Technically, this leads to large-scale mathematical problems, which are solved using recent advances in convex optimization. We apply our method for localizing brain areas involved in different types of motor imagery using real data from Brain-Computer Interface (BCI) sessions. Our approach based on single-trial localization of complex Fourier coefficients yields class-specific focal sources in the sensorimotor cortices.

Original language	English
Pages (from-to)	851-859
Number of pages	9
Journal	NeuroImage
Volume	54
Issue number	2
DOIs	https://doi.org/10.1016/j.neuroimage.2010.09.003
Publication status	Published - 2011 Jan 15
Externally published	Yes

Bibliographical note

Funding Information:
This work was supported in part by BMBF grant no. 01GQ0850 , DFG grant no. MU 987/3-1 and the FP7-ICT Programme of the European Community , under the PASCAL2 Network of Excellence, ICT-216886 . We thank Vojtech Franc, Marius Kloft, Vadim Nikulin, Volker Roth and Alexander Zien for valuable discussions.

Keywords

Basis field
Brain-computer interfaces
EEG
Inverse problem
Large-scale optimization
MEG
Motor imagery

ASJC Scopus subject areas

Neurology
Cognitive Neuroscience

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10.1016/j.neuroimage.2010.09.003

Cite this

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abstract = "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 the method's ability to reconstruct simulated sources of random shape and show that the accuracy of the recovered sources can be increased, when interrelated field patterns are co-localized. Technically, this leads to large-scale mathematical problems, which are solved using recent advances in convex optimization. We apply our method for localizing brain areas involved in different types of motor imagery using real data from Brain-Computer Interface (BCI) sessions. Our approach based on single-trial localization of complex Fourier coefficients yields class-specific focal sources in the sensorimotor cortices.",

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AU - Nolte, Guido

AU - Müller, Klaus Robert

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Large-scale EEG/MEG source localization with spatial flexibility

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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