Brainstorm-DUNEuro: An integrated and user-friendly Finite Element Method for modeling electromagnetic brain activity
Takfarinas Medani,
Juan Garcia-Prieto,
Francois Tadel,
Marios Antonakakis,
Tim Erdbrügger,
Malte Höltershinken,
Wayne Mead,
Sophie Schrader,
Anand Joshi,
Christian Engwer,
Carsten H. Wolters,
John C. Mosher,
Richard M. Leahy
Affiliations
Takfarinas Medani
Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, United States; Corresponding authors.
Juan Garcia-Prieto
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States; Harvard Medical School, Boston, Massachusetts, United States; Corresponding authors.
Francois Tadel
Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, United States
Marios Antonakakis
Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany; School of Electrical and Computer Engineering, Technical University of Crete, Greece
Tim Erdbrügger
Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
Malte Höltershinken
Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
Wayne Mead
Department of Neurology, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States
Sophie Schrader
Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany; Department of Applied Mathematics, University of Münster, Germany
Anand Joshi
Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, United States
Christian Engwer
Department of Applied Mathematics, University of Münster, Germany
Carsten H. Wolters
Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany; Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
John C. Mosher
Department of Neurology, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States
Richard M. Leahy
Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, United States
Human brain activity generates scalp potentials (electroencephalography – EEG), intracranial potentials (iEEG), and external magnetic fields (magnetoencephalography – MEG). These electrophysiology (e-phys) signals can often be measured simultaneously for research and clinical applications. The forward problem involves modeling these signals at their sensors for a given equivalent current dipole configuration within the brain. While earlier researchers modeled the head as a simple set of isotropic spheres, today's magnetic resonance imaging (MRI) data allow for a detailed anatomic description of brain structures and anisotropic characterization of tissue conductivities. We present a complete pipeline, integrated into the Brainstorm software, that allows users to automatically generate an individual and accurate head model based on the subject's MRI and calculate the electromagnetic forward solution using the finite element method (FEM). The head model generation is performed by integrating the latest tools for MRI segmentation and FEM mesh generation. The final head model comprises the five main compartments: white-matter, gray-matter, CSF, skull, and scalp. The anisotropic brain conductivity model is based on the effective medium approach (EMA), which estimates anisotropic conductivity tensors from diffusion-weighted imaging (DWI) data. The FEM electromagnetic forward solution is obtained through the DUNEuro library, integrated into Brainstorm, and accessible with either a user-friendly graphical interface or scripting. With tutorials and example data sets available in an open-source format on the Brainstorm website, this integrated pipeline provides access to advanced FEM tools for electromagnetic modeling to a broader neuroscience community.
