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Cortical Source Analysis of High-Density EEG Recordings in Children
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A realistic, accurate and fast source modeling approach for the EEG forward problem.

Tuuli Miinalainen1, Atena Rezaei2, Defne Us3

  • 1Laboratory of Mathematics, Tampere University of Technology, P.O. Box 692, 33101, Tampere, Finland; Institute for Biomagnetism and Biosignalanalysis, University of Münster, Germany, Malmedyweg 15, D-48149, Münster, Germany; Institute for Computational and Applied Mathematics, University of Münster, Germany, Einsteinstrasse 62, D-48149, Münster, Germany; Department of Applied Physics, University of Eastern Finland, P.O.Box 1627, FI-70211 Kuopio, Finland.

Neuroimage
|August 31, 2018
PubMed
Summary

This study introduces a new current-preserving dipolar source model for electroencephalography (EEG) analysis. This advanced finite element method (FEM) model improves accuracy in thin cortical structures, crucial for pediatric and pathological brain research.

Keywords:
DUNE toolboxDivergence conforming vector fieldsElectroencephalography (EEG)Finite element method (FEM)Focal sources

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Area of Science:

  • Neuroscience
  • Biophysics
  • Computational Biology

Background:

  • Standard electroencephalography (EEG) source analysis often uses simplified head models.
  • Existing models struggle with accuracy in thin cortical structures, particularly in pediatric or pathological cases.
  • There is a need for more realistic, accurate, and computationally efficient EEG source models.

Purpose of the Study:

  • To advance EEG source analysis by developing a novel finite element method (FEM) head volume conductor model.
  • To incorporate brain tissue inhomogeneity (gray matter, white matter, cerebrospinal fluid) for improved accuracy.
  • To create a source model that balances focality, realism, numerical accuracy, and computational speed for thin cortical structures.

Main Methods:

  • Developed and investigated a current-preserving (divergence conforming) dipolar source model with a varying number of basis elements (n=1-5).
  • Validated the model using numerical experiments in a multi-layered spherical domain with an analytical solution.
  • Compared the current-preserving approach against partial integration and St. Venant FEM source modeling techniques.

Main Results:

  • Model accuracy increased with the number of basis elements, while focality decreased.
  • Optimal balance for thin cortices achieved with n=4 (or n=3), while n=5 recommended for thicker cortices.
  • The best current-preserving source model outperformed competing FEM methods in overall balance.
  • FEM transfer matrices ensured high computational speed for all tested approaches.

Conclusions:

  • The proposed current-preserving dipolar source model offers an improved balance between accuracy and focality for EEG source analysis, especially in thin cortical regions.
  • The developed model, implemented in the open-source duneuro library, facilitates broader use in brain research.
  • Further validation through inversion tests on realistic head models demonstrates the practical utility of the new approach.