Global sensitivity of EEG source analysis to tissue conductivity uncertainties

被引:3
|
作者
Vorwerk, Johannes [1 ]
Wolters, Carsten H. [2 ,3 ]
Baumgarten, Daniel [1 ]
机构
[1] UMIT TIROL Private Univ Hlth Sci & Hlth Technol, Inst Elect & Biomed Engn, Hall In Tirol, Austria
[2] Univ Munster, Inst Biomagnetism & Biosignalanalysis, Munster, Germany
[3] Univ Munster, Otto Creutzfeldt Ctr Cognit & Behav Neurosci, Munster, Germany
来源
基金
奥地利科学基金会;
关键词
EEG; forward modeling; finite element method; source analysis; sensitivity analysis; uncertainty quantification; FINITE-ELEMENT MODEL; SOURCE LOCALIZATION; HEAD MODELS; SKULL; MEG; POTENTIALS; ACCURACY; ERRORS;
D O I
10.3389/fnhum.2024.1335212
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Introduction To reliably solve the EEG inverse problem, accurate EEG forward solutions based on a detailed, individual volume conductor model of the head are essential. A crucial-but often neglected-aspect in generating a volume conductor model is the choice of the tissue conductivities, as these may vary from subject to subject. In this study, we investigate the sensitivity of EEG forward and inverse solutions to tissue conductivity uncertainties for sources distributed over the whole cortex surface.Methods We employ a detailed five-compartment head model distinguishing skin, skull, cerebrospinal fluid, gray matter, and white matter, where we consider uncertainties of skin, skull, gray matter, and white matter conductivities. We use the finite element method (FEM) to calculate EEG forward solutions and goal function scans (GFS) as inverse approach. To be able to generate the large number of EEG forward solutions, we employ generalized polynomial chaos (gPC) expansions.Results For sources up to a depth of 4 cm, we find the strongest influence on the signal topography of EEG forward solutions for the skull conductivity and a notable effect for the skin conductivity. For even deeper sources, e.g., located deep in the longitudinal fissure, we find an increasing influence of the white matter conductivity. The conductivity variations translate to varying source localizations particularly for quasi-tangential sources on sulcal walls, whereas source localizations of quasi-radial sources on the top of gyri are less affected. We find a strong correlation between skull conductivity and the variation of source localizations and especially the depth of the reconstructed source for quasi-tangential sources. We furthermore find a clear but weaker correlation between depth of the reconstructed source and the skin conductivity.Discussion Our results clearly show the influence of tissue conductivity uncertainties on EEG source analysis. We find a particularly strong influence of skull and skin conductivity uncertainties.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] Sensitivity of the Electrocardiography Inverse Solution to the Torso Conductivity Uncertainties
    Zemzemi, N.
    Aboulaich, R.
    Fikal, N.
    El Guarmah, E.
    FUNCTIONAL IMAGING AND MODELING OF THE HEART (FIMH 2015), 2015, 9126 : 475 - 483
  • [22] Skull Conductivity Estimation for EEG Source Localization
    Costa, Facundo
    Batatia, Hadj
    Oberlin, Thomas
    Tourneret, Jean-Yves
    IEEE SIGNAL PROCESSING LETTERS, 2017, 24 (04) : 422 - 426
  • [23] Reduction of the impact of multiple uncertain conductivity valueson EEG dipole source analysis
    Yitembe, B. R.
    Crevecoeur, G.
    Van Keer, R.
    Dupre, L.
    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, 2013, 29 (03) : 363 - 379
  • [24] Global Sensitivity Analysis for a perfusion bioreactor system in tissue engineering
    Nascu, Ioana
    Chen, Tao
    Du, Wenli
    IFAC PAPERSONLINE, 2021, 54 (15): : 550 - 555
  • [25] Stochastic Uncertainty Quantification of the Conductivity in EEG Source Analysis by Using Polynomial Chaos Decomposition
    Gaignaire, Roman
    Crevecoeur, Guillaume
    Dupre, Luc
    Sabariego, Ruth V.
    Dular, Patrick
    Geuzaine, Christophe
    IEEE TRANSACTIONS ON MAGNETICS, 2010, 46 (08) : 3457 - 3460
  • [26] Global sensitivity analysis of failure probability of structures with uncertainties of random variable and their distribution parameters
    Wang, Pan
    Li, Chunyu
    Liu, Fuchao
    Zhou, Hanyuan
    ENGINEERING WITH COMPUTERS, 2022, 38 (SUPPL 5) : 4367 - 4385
  • [27] Uncertainties propagation and global sensitivity analysis of the frequency response function of piezoelectric energy harvesters
    Ruiz, Rafael O.
    Meruane, Viviana
    SMART MATERIALS AND STRUCTURES, 2017, 26 (06)
  • [28] Control Structure Design Using Global Sensitivity Analysis for Mineral Processes under Uncertainties
    Mamani-Quinonez, Oscar
    Cisternas, Luis A.
    Lopez-Arenas, Teresa
    Lucay, Freddy A.
    MINERALS, 2022, 12 (06)
  • [29] Extended affine arithmetic-based global sensitivity analysis for power flow with uncertainties
    Liao, Xiaobing
    Liu, Kaipei
    Le, Jian
    Zhu, Shu
    Huai, Qing
    Li, Ben
    Zhang, Yantian
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2020, 115 (115)
  • [30] Global sensitivity analysis of failure probability of structures with uncertainties of random variable and their distribution parameters
    Pan Wang
    Chunyu Li
    Fuchao Liu
    Hanyuan Zhou
    Engineering with Computers, 2022, 38 : 4367 - 4385