Brainstorm-DUNEuro: An integrated and user-friendly Finite Element Method for modeling electromagnetic brain activity

Area of Science:

• Neuroscience
• Biophysics
• Computational Biology

Background:

• Electrophysiology (e-phys) signals like electroencephalography (EEG), intracranial potentials (iEEG), and magnetoencephalography (MEG) reflect human brain activity.
• Accurate modeling of the forward problem, which predicts sensor signals from brain activity, is crucial for research and clinical applications.
• Traditional isotropic spherical head models are limited; modern MRI data enable more detailed, anisotropic models.

Purpose of the Study:

• To present an integrated pipeline within the Brainstorm software for generating accurate, individual head models.
• To calculate the electromagnetic forward solution using the finite element method (FEM) based on subject-specific MRI data.
• To provide accessible advanced FEM tools for the neuroscience community.

Main Methods:

• Automatic head model generation using MRI segmentation and FEM mesh tools, including white matter, gray matter, CSF, skull, and scalp compartments.
• Anisotropic brain conductivity modeling using the effective medium approach (EMA) with diffusion-weighted imaging (DWI) data.
• Finite element method (FEM) electromagnetic forward solution computation via the DUNEuro library integrated into Brainstorm.

Main Results:

• A complete pipeline for generating subject-specific anisotropic head models.
• Accurate calculation of the electromagnetic forward solution using FEM.
• Integration into Brainstorm software with both graphical and scripting interfaces.

Conclusions:

• The developed pipeline provides a user-friendly and accurate method for electromagnetic modeling in neuroscience.
• This tool enhances the ability to study brain activity using EEG and MEG by improving forward modeling.
• Open-source availability and tutorials promote broader adoption of advanced FEM techniques in the neuroscience community.