A New Weighted Correlation Coefficient Method to Evaluate Reconstructed Brain Electrical Sources

Various inverse algorithms have been proposed to estimate brain electrical activities with magnetoencephalography (MEG) and electroencephalography (EEG). To validate and compare the performances of inverse algorithms, many researchers have used artificially constructed EEG and MEG datasets. When the...

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Main Authors: Jong-Ho Choi, Min-Hyuk Kim, Luan Feng, Chany Lee, Hyun-Kyo Jung
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2012/251295
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spelling doaj-8a5101f8c1894c03bdc72de8c52f6d512020-11-25T01:05:25ZengHindawi LimitedJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/251295251295A New Weighted Correlation Coefficient Method to Evaluate Reconstructed Brain Electrical SourcesJong-Ho Choi0Min-Hyuk Kim1Luan Feng2Chany Lee3Hyun-Kyo Jung4School of Electrical Engineering and Computer Science, College of Engineering, Seoul National University, Seoul 151744, Republic of KoreaSchool of Electrical Engineering and Computer Science, College of Engineering, Seoul National University, Seoul 151744, Republic of KoreaSchool of Electrical Engineering and Computer Science, College of Engineering, Seoul National University, Seoul 151744, Republic of KoreaCollege of Medicine, Korea University, Seoul 136705, Republic of KoreaSchool of Electrical Engineering and Computer Science, College of Engineering, Seoul National University, Seoul 151744, Republic of KoreaVarious inverse algorithms have been proposed to estimate brain electrical activities with magnetoencephalography (MEG) and electroencephalography (EEG). To validate and compare the performances of inverse algorithms, many researchers have used artificially constructed EEG and MEG datasets. When the artificial sources are reconstructed on the cortical surface, accuracy of the source estimates has been difficult to evaluate. In this paper, we suggest a new measure to evaluate the reconstructed EEG/MEG cortical sources more accurately. To validate the usefulness of the proposed method, comparison between conventional and proposed evaluation metrics was conducted using artificial cortical sources simulated under different noise conditions. The simulation results demonstrated that only the proposed method could reflect the source space geometry regardless of the number of source peaks.http://dx.doi.org/10.1155/2012/251295
collection DOAJ
language English
format Article
sources DOAJ
author Jong-Ho Choi
Min-Hyuk Kim
Luan Feng
Chany Lee
Hyun-Kyo Jung
spellingShingle Jong-Ho Choi
Min-Hyuk Kim
Luan Feng
Chany Lee
Hyun-Kyo Jung
A New Weighted Correlation Coefficient Method to Evaluate Reconstructed Brain Electrical Sources
Journal of Applied Mathematics
author_facet Jong-Ho Choi
Min-Hyuk Kim
Luan Feng
Chany Lee
Hyun-Kyo Jung
author_sort Jong-Ho Choi
title A New Weighted Correlation Coefficient Method to Evaluate Reconstructed Brain Electrical Sources
title_short A New Weighted Correlation Coefficient Method to Evaluate Reconstructed Brain Electrical Sources
title_full A New Weighted Correlation Coefficient Method to Evaluate Reconstructed Brain Electrical Sources
title_fullStr A New Weighted Correlation Coefficient Method to Evaluate Reconstructed Brain Electrical Sources
title_full_unstemmed A New Weighted Correlation Coefficient Method to Evaluate Reconstructed Brain Electrical Sources
title_sort new weighted correlation coefficient method to evaluate reconstructed brain electrical sources
publisher Hindawi Limited
series Journal of Applied Mathematics
issn 1110-757X
1687-0042
publishDate 2012-01-01
description Various inverse algorithms have been proposed to estimate brain electrical activities with magnetoencephalography (MEG) and electroencephalography (EEG). To validate and compare the performances of inverse algorithms, many researchers have used artificially constructed EEG and MEG datasets. When the artificial sources are reconstructed on the cortical surface, accuracy of the source estimates has been difficult to evaluate. In this paper, we suggest a new measure to evaluate the reconstructed EEG/MEG cortical sources more accurately. To validate the usefulness of the proposed method, comparison between conventional and proposed evaluation metrics was conducted using artificial cortical sources simulated under different noise conditions. The simulation results demonstrated that only the proposed method could reflect the source space geometry regardless of the number of source peaks.
url http://dx.doi.org/10.1155/2012/251295
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