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OpenMEEG: opensource software for quasistatic bioelectromagnetics

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TLDR
The aim of this paper is to present OpenMEEG, both from the theoretical and the practical point of view, and to compare its performances with other competing software packages, to show that it represents the state of the art for forward computations.
Abstract
Interpreting and controlling bioelectromagnetic phenomena require realistic physiological models and accurate numerical solvers. A semi-realistic model often used in practise is the piecewise constant conductivity model, for which only the interfaces have to be meshed. This simplified model makes it possible to use Boundary Element Methods. Unfortunately, most Boundary Element solutions are confronted with accuracy issues when the conductivity ratio between neighboring tissues is high, as for instance the scalp/skull conductivity ratio in electro-encephalography. To overcome this difficulty, we proposed a new method called the symmetric BEM, which is implemented in the OpenMEEG software. The aim of this paper is to present OpenMEEG, both from the theoretical and the practical point of view, and to compare its performances with other competing software packages. We have run a benchmark study in the field of electro- and magneto-encephalography, in order to compare the accuracy of OpenMEEG with other freely distributed forward solvers. We considered spherical models, for which analytical solutions exist, and we designed randomized meshes to assess the variability of the accuracy. Two measures were used to characterize the accuracy. the Relative Difference Measure and the Magnitude ratio. The comparisons were run, either with a constant number of mesh nodes, or a constant number of unknowns across methods. Computing times were also compared. We observed more pronounced differences in accuracy in electroencephalography than in magnetoencephalography. The methods could be classified in three categories: the linear collocation methods, that run very fast but with low accuracy, the linear collocation methods with isolated skull approach for which the accuracy is improved, and OpenMEEG that clearly outperforms the others. As far as speed is concerned, OpenMEEG is on par with the other methods for a constant number of unknowns, and is hence faster for a prescribed accuracy level. This study clearly shows that OpenMEEG represents the state of the art for forward computations. Moreover, our software development strategies have made it handy to use and to integrate with other packages. The bioelectromagnetic research community should therefore be able to benefit from OpenMEEG with a limited development effort.

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MEG and EEG data analysis with MNE-Python

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References
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Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain

TL;DR: The mathematical theory of the method is explained in detail, followed by a thorough description of MEG instrumentation, data analysis, and practical construction of multi-SQUID devices.
Journal ArticleDOI

Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem

TL;DR: Basic mathematical and physical concepts of the biomagnetic inverse problem are reviewed with some new approaches and a weighted least-squares search with confidence limits and the method of minimum norm estimate are discussed.
Journal ArticleDOI

Realistic conductivity geometry model of the human head for interpretation of neuromagnetic data

TL;DR: A method to handle the numerical difficulties caused by the presence of poorly conducting skull is presented and it is shown numerically that for the computation of B produced by cerebral current sources, it is sufficient to consider a brain-shaped homogeneous conductor only.
Journal ArticleDOI

The magnetic lead field theorem in the quasi-static approximation and its use for magnetoencephalography forward calculation in realistic volume conductors.

TL;DR: A simple and fast method is formulated for the MEG forward calculation for one shell of arbitrary shape that corrects the corresponding lead field for a spherical volume conductor by a superposition of basis functions, gradients of harmonic functions constructed here from spherical harmonics, with coefficients fitted to the boundary conditions.
Book

Acoustic and electromagnetic equations

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