Forward Field Computation with OpenMEEG

To recover the sources giving rise to electro- and magnetoencephalography in individual measurements, realistic physiological modeling is required, and accurate numerical solutions must be computed. We present OpenMEEG, which solves the electromagnetic forward problem in the quasistatic regime, for...

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Main Authors: Alexandre Gramfort, Théodore Papadopoulo, Emmanuel Olivi, Maureen Clerc
Format: Article
Language:English
Published: Hindawi Limited 2011-01-01
Series:Computational Intelligence and Neuroscience
Online Access:http://dx.doi.org/10.1155/2011/923703
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spelling doaj-0be68ad074b443ce90afa9fd79255f612020-11-24T23:29:22ZengHindawi LimitedComputational Intelligence and Neuroscience1687-52651687-52732011-01-01201110.1155/2011/923703923703Forward Field Computation with OpenMEEGAlexandre Gramfort0Théodore Papadopoulo1Emmanuel Olivi2Maureen Clerc3Parietal Project Team, INRIA Saclay Ile-de-France, Neurospin-CEA, Bât 145, Point Courrier 156, 91191 Gif/Yvette, FranceAthena Project Team, INRIA Sophia Antipolis-Méditerranée, 2004, Route des Lucioles, 06902 Sophia Antipolis, FranceAthena Project Team, INRIA Sophia Antipolis-Méditerranée, 2004, Route des Lucioles, 06902 Sophia Antipolis, FranceAthena Project Team, INRIA Sophia Antipolis-Méditerranée, 2004, Route des Lucioles, 06902 Sophia Antipolis, FranceTo recover the sources giving rise to electro- and magnetoencephalography in individual measurements, realistic physiological modeling is required, and accurate numerical solutions must be computed. We present OpenMEEG, which solves the electromagnetic forward problem in the quasistatic regime, for head models with piecewise constant conductivity. The core of OpenMEEG consists of the symmetric Boundary Element Method, which is based on an extended Green Representation theorem. OpenMEEG is able to provide lead fields for four different electromagnetic forward problems: Electroencephalography (EEG), Magnetoencephalography (MEG), Electrical Impedance Tomography (EIT), and intracranial electric potentials (IPs). OpenMEEG is open source and multiplatform. It can be used from Python and Matlab in conjunction with toolboxes that solve the inverse problem; its integration within FieldTrip is operational since release 2.0.http://dx.doi.org/10.1155/2011/923703
collection DOAJ
language English
format Article
sources DOAJ
author Alexandre Gramfort
Théodore Papadopoulo
Emmanuel Olivi
Maureen Clerc
spellingShingle Alexandre Gramfort
Théodore Papadopoulo
Emmanuel Olivi
Maureen Clerc
Forward Field Computation with OpenMEEG
Computational Intelligence and Neuroscience
author_facet Alexandre Gramfort
Théodore Papadopoulo
Emmanuel Olivi
Maureen Clerc
author_sort Alexandre Gramfort
title Forward Field Computation with OpenMEEG
title_short Forward Field Computation with OpenMEEG
title_full Forward Field Computation with OpenMEEG
title_fullStr Forward Field Computation with OpenMEEG
title_full_unstemmed Forward Field Computation with OpenMEEG
title_sort forward field computation with openmeeg
publisher Hindawi Limited
series Computational Intelligence and Neuroscience
issn 1687-5265
1687-5273
publishDate 2011-01-01
description To recover the sources giving rise to electro- and magnetoencephalography in individual measurements, realistic physiological modeling is required, and accurate numerical solutions must be computed. We present OpenMEEG, which solves the electromagnetic forward problem in the quasistatic regime, for head models with piecewise constant conductivity. The core of OpenMEEG consists of the symmetric Boundary Element Method, which is based on an extended Green Representation theorem. OpenMEEG is able to provide lead fields for four different electromagnetic forward problems: Electroencephalography (EEG), Magnetoencephalography (MEG), Electrical Impedance Tomography (EIT), and intracranial electric potentials (IPs). OpenMEEG is open source and multiplatform. It can be used from Python and Matlab in conjunction with toolboxes that solve the inverse problem; its integration within FieldTrip is operational since release 2.0.
url http://dx.doi.org/10.1155/2011/923703
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