Abstract
Accurate and efficient source analysis in electro- and magnetoencephalography using sophisticated realistic head geometries requires advanced numerical approaches. This paper presents DUNEuro, a free and open-source C++ software toolbox for the numerical computation of forward solutions in bioelectromagnetism. Building upon the DUNE framework, it provides implementations of modern fitted and unfitted finite element methods to efficiently solve the forward problems of electro- and magnetoencephalography. The user can choose between a variety of different source models that are implemented. The software’s aim is to provide interfaces that are extendable and easy-to-use. In order to enable a closer integration into existing analysis pipelines, interfaces to Python and MATLAB are provided. The practical use is demonstrated by a source analysis example of somatosensory evoked potentials using a realistic six-compartment head model. Detailed installation instructions and example scripts using spherical and realistic head models are appended.
Highlights
We present DUNEuro, an open-source software toolbox for the numerical computation of forward solutions in bioelectromagnetism
In this paper we presented the DUNEuro software, a toolbox for solving forward problems in bioelectromagnetism
The practical usability of the library was demonstrated by a source analysis of experimental data of a somatosensory stimulation
Summary
We present DUNEuro, an open-source software toolbox for the numerical computation of forward solutions in bioelectromagnetism. DUNEuro provides interfaces to Python and MATLAB so that the user is not exposed to the high complexity of a C++ finite element code and the forward solutions can be embedded in an already existing analysis pipeline. One existing library for finite element computations is DUNE, the Distributed and Unified Numerics Environment (http://www.dune-project.org) It is a general purpose open-source C++ library for solving partial differential equations using mesh-based methods [31]. We first give a short summary on the background of solving the EEG and MEG forward problems with finite element methods This is followed by a general description of the structure and design of the toolbox, its use of existing frameworks for solving partial differential equations and its main concepts of different interfaces used within the library. In S2 Appendix, several example data sets and scripts in Python and MATLAB are provided and explained in detail
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