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A case study of focal bayesian EEG inversion for whitney element source spaces: Mesh-based vs. cartesian orientations

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Details

Original languageEnglish
Title of host publicationEMBEC and NBC 2017 - Joint Conference of the European Medical and Biological Engineering Conference EMBEC 2017 and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2017
PublisherSpringer Verlag
Pages1065-1068
Number of pages4
ISBN (Print)9789811051210
DOIs
Publication statusPublished - 2018
Publication typeA4 Article in a conference publication
EventJoint Conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC) -
Duration: 1 Jan 1900 → …

Publication series

NameIFMBE Proceedings
Volume65
ISSN (Print)1680-0737

Conference

ConferenceJoint Conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC)
Period1/01/00 → …

Abstract

This paper concentrates on the Bayesian detection of the neuronal current distributions in the electroencephalography (EEG) imaging of the brain activity. In particular, we focus on a hierarchical maximum a posteriori inversion technique applicable when the lead field matrix is constructed via the finite element method. We utilize the linear Whitney (Raviart-Thomas) basis functions as source currents. In the numerical experiments, the accuracy was investigated using two spherical head models. The results obtained suggest that the interpolation of the dipolar source space does not necessarily bring any advantage for FEM based inverse computations. Furthermore, the divergence conforming Whitney-type sources were found to be sufficient for precise and highly focal Bayesian modeling of dipole-like currents.

ASJC Scopus subject areas

Keywords

  • Electroencephalography (EEG), Finite element method (FEM), Hierarchical Bayesian inverse model, Whitney elements

Publication forum classification

Field of science, Statistics Finland