DUNEuro

DUNEuro implements forward modeling for electroencephalography (EEG) and magnetoencephalography (MEG) in C++ using the DUNE (Distributed and Unified Numerics Environment) framework to support accurate source analysis.


Key Features:

  • DUNE-based C++ implementation: Built in C++ on the DUNE framework for advanced numerical computations.
  • Advanced numerical approaches: Employs fitted and unfitted finite element methods to solve EEG/MEG forward problems.
  • Versatile source models: Supports a variety of source models for modeling neural current sources.
  • Realistic head models: Implements detailed six-compartment head models to represent realistic head geometries.
  • Demonstrated examples: Includes source analysis examples demonstrated for cases such as somatosensory evoked potentials.

Scientific Applications:

  • Source localization: Provides forward solutions used for localization of neural sources from EEG/MEG data.
  • Simulation studies: Enables simulation of bioelectromagnetic fields using realistic head geometries for hypothesis testing and method evaluation.
  • Forward-model development: Facilitates development and comparison of numerical forward models for EEG/MEG research.
  • Analysis of evoked potentials: Applied in source analysis of evoked responses such as somatosensory evoked potentials.

Methodology:

Implemented in C++ using the DUNE framework and employing fitted and unfitted finite element methods to solve EEG/MEG forward problems on realistic six-compartment head geometries with multiple source model formulations.

Topics

Details

License:
GPL-3.0
Cost:
Free of charge
Tool Type:
library
Operating Systems:
Mac, Linux, Windows
Programming Languages:
C++, Python, MATLAB
Added:
11/5/2021
Last Updated:
11/5/2021

Operations

Data Inputs & Outputs

Publications

Schrader S, Westhoff A, Piastra MC, Miinalainen T, Pursiainen S, Vorwerk J, Brinck H, Wolters CH, Engwer C. DUNEuro—A software toolbox for forward modeling in bioelectromagnetism. PLOS ONE. 2021;16(6):e0252431. doi:10.1371/journal.pone.0252431. PMID:34086715. PMCID:PMC8177522.

PMID: 34086715
PMCID: PMC8177522
Funding: - Deutsche Forschungsgemeinschaft: EXC 1003-194347757, EXC 2044-390685587, WO1425/5-2, WO1425/7-1 - Academy of Finland: 305055, 317165, 326668, 334465, 336792, 344712 - Horizon 2020: 641652, - Deutscher Akademischer Austauschdienst: 57405052, 57523877 - Austrian Wissenschaftsfonds: project I 3790-B27 (https://www.fwf.ac.at/en)

Documentation

Links