scholarly journals Effect of Brain-to-Skull Conductivity Ratio on EEG Source Localization Accuracy

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Gang Wang ◽  
Doutian Ren
Keyword(s):  
Source Localization ◽  
Conductivity Ratio ◽  
Source Reconstruction ◽  
Localization Accuracy ◽  
Scalp Eeg ◽  
Skull Conductivity ◽  
Localization Errors ◽  
The Mean ◽  
Eeg Source Localization ◽  
Dipole Sources

The goal of this study was to investigate the influence of the brain-to-skull conductivity ratio (BSCR) on EEG source localization accuracy. In this study, we evaluated four BSCRs: 15, 20, 25, and 80, which were mainly discussed according to the literature. The scalp EEG signals were generated by BSCR-related forward computation for each cortical dipole source. Then, for each scalp EEG measurement, the source reconstruction was performed to identify the estimated dipole sources by the actual BSCR and the misspecified BSCRs. The estimated dipole sources were compared with the simulated dipole sources to evaluate EEG source localization accuracy. In the case of considering noise-free EEG measurements, the mean localization errors were approximately equal to zero when using actual BSCR. The misspecified BSCRs resulted in substantial localization errors which ranged from 2 to 16 mm. When considering noise-contaminated EEG measurements, the mean localization errors ranged from 8 to 18 mm despite the BSCRs used in the inverse calculation. The present results suggest that the localization accuracy is sensitive to the BSCR in EEG source reconstruction, and the source activity can be accurately localized when the actual BSCR and the EEG scalp signals with high signal-to-noise ratio (SNR) are used.

Impact of skull-to-brain conductivity ratio for high resolution EEG source localization

2021 ◽  
Author(s):  
Gregoire DEMOULIN ◽  
Estelle Pruvost-Robieux ◽  
Angela Marchi ◽  
Celine Ramdani ◽  
Jean-Michel Badier ◽  
...  
Keyword(s):  
High Resolution ◽  
Source Localization ◽  
Conductivity Ratio ◽  
Eeg Source Localization ◽  
High Resolution Eeg

Experimental tests of EEG source localization accuracy in realistically shaped head models

2001 ◽  
Vol 112 (12) ◽  
pp. 2288-2292 ◽  
Author(s):  
B.Neil Cuffin ◽  
Donald L Schomer ◽  
John R Ives ◽  
Howard Blume
Keyword(s):  
Source Localization ◽  
Experimental Tests ◽  
Localization Accuracy ◽  
Eeg Source Localization

scholarly journals Skull Conductivity Estimation for EEG Source Localization

2017 ◽  
Vol 24 (4) ◽  
pp. 422-426
Author(s):  
Facundo Costa ◽  
Hadj Batatia ◽  
Thomas Oberlin ◽  
Jean-Yves Tourneret
Keyword(s):  
Source Localization ◽  
Skull Conductivity ◽  
Eeg Source Localization

scholarly journals Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity

NeuroImage ◽  
2019 ◽  
Vol 188 ◽  
pp. 252-260 ◽  
Author(s):  
Ville Rimpiläinen ◽  
Alexandra Koulouri ◽  
Felix Lucka ◽  
Jari P. Kaipio ◽  
Carsten H. Wolters
Keyword(s):  
Source Localization ◽  
Uncertainty Modelling ◽  
Skull Conductivity ◽  
Eeg Source Localization

Evaluation of Different EEG Source Localization Methods Using Testing Localization Errors

2013 ◽  
Vol 62 (3) ◽  
Author(s):  
Leila SaeidiAsl ◽  
Tahir Ahmad
Keyword(s):  
Inverse Problem ◽  
Source Localization ◽  
Forward Problem ◽  
Potential Fields ◽  
Uniqueness Property ◽  
Localization Errors ◽  
Source Models ◽  
Eeg Source Localization ◽  
The Brain ◽  
Dipolar Source

The ideas underlying the quantitative localization of the sources of the EEG review within the brain along with the current and emerging approaches to the problem. The ideas mentioned consist of distributed and dipolar source models and head models ranging from the spherical to the more realistic based on the boundary and finite elements. The forward and inverse problems in electroencephalography will debate. The inverse problem has non-uniqueness property in nature. More precisely, different combinations of sources can produce similar potential fields occur on the head. In contrast, the forward problem does have a unique solution. The forward problem calculates the potential field at the scalp from known source locations, source strengths and conductivity in the head, and it can be used to solve the inverse problem. In the final part of this paper, we compare the performance of three well–known EEG source localization techniques which applied to the underdetermined (distributed) source localization of the inverse problem. These techniques consist of LORETA, WMN and MN, which comparing by testing localization error.

A novel bearing-assisted TDOA-GROA approach for passive source localization

2018 ◽  
Vol 11 (1) ◽  
pp. 2-19 ◽  
Author(s):  
Ji-An Luo ◽  
Zhi-Wen Tan ◽  
Dong-Liang Peng
Keyword(s):  
Source Localization ◽  
Gaussian Noise ◽  
Design Methodology ◽  
Weighted Least Squares ◽  
Small Error ◽  
Content Type ◽  
Localization Accuracy ◽  
Passive Source Localization ◽  
The Mean ◽  
Localization Approach

Purpose The passive source localization (PSL) problem using angles of arrival (AOA), time differences of arrival (TDOA) or gain ratios of arrival (GROA) is generally nonlinear and nontrival. In this research, the purpose of this paper is to design an accurate hybrid source localization approach to solve the PSL problem. The inspiration is drawn from the fact that the bearings, TDOAs and GROAs are complementary in terms of their geometry properties. Design/methodology/approach The maximum-likelihood (ML) method is reexamined by using hybrid measurements. Being assisted by the bearings, a new hybrid weighted least-squares (WLS) method is then proposed by jointly utilizing the bearing, TDOA and GROA measurements. Findings Theoretical performance analysis illustrates that the mean-square error of the ML or WLS method can attain the Cramér-Rao lower bound for Gaussian noise over small error region. However, the WLS method has much lower computational complexity than the ML algorithm. Compared with the AOA-only, TDOA-only, AOA-TDOA, TDOA-GROA methods, the localization accuracy can be greatly improved by combining the AOAs, TDOAs and GROAs, especially for some specific geometries. Originality/value A novel bearing-assisted TDOA-GROA method is proposed for source localization, and a new hybrid WLS estimator is presented inspired from the fact that the bearings, TDOAs and GROAs are complementary in terms of their geometry properties.

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