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Reference Electrode Standardization Interpolation Technique (RESIT): A Novel Interpolation Method for Scalp EEG

“Bad channels” are common phenomena during scalp electroencephalography (EEG) recording that arise due to various technique-related reasons, and reconstructing signals from bad channels is an inevitable choice in EEG processing. However, current interpolation methods are all based on purely mathemat...

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Autores principales: Dong, Li, Zhao, Lingling, Zhang, Yufan, Yu, Xue, Li, Fali, Li, Jianfu, Lai, Yongxiu, Liu, Tiejun, Yao, Dezhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8195908/
https://www.ncbi.nlm.nih.gov/pubmed/33950323
http://dx.doi.org/10.1007/s10548-021-00844-2
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author Dong, Li
Zhao, Lingling
Zhang, Yufan
Yu, Xue
Li, Fali
Li, Jianfu
Lai, Yongxiu
Liu, Tiejun
Yao, Dezhong
author_facet Dong, Li
Zhao, Lingling
Zhang, Yufan
Yu, Xue
Li, Fali
Li, Jianfu
Lai, Yongxiu
Liu, Tiejun
Yao, Dezhong
author_sort Dong, Li
collection PubMed
description “Bad channels” are common phenomena during scalp electroencephalography (EEG) recording that arise due to various technique-related reasons, and reconstructing signals from bad channels is an inevitable choice in EEG processing. However, current interpolation methods are all based on purely mathematical interpolation theory, ignoring the neurophysiological basis of the EEG signals, and their performance needs to be further improved, especially when there are many scattered or adjacent bad channels. Therefore, a new interpolation method, named the reference electrode standardization interpolation technique (RESIT), was developed for interpolating scalp EEG channels. Resting-state and event-related EEG datasets were used to investigate the performance of the RESIT. The main results showed that (1) assuming 10% bad channels, RESIT can reconstruct the bad channels well; (2) as the percentage of bad channels increased (from 2% to 85%), the absolute and relative errors between the true and RESIT-reconstructed signals generally increased, and the correlations between the true and RESIT signals decreased; (3) for a range of bad channel percentages (2% ~ 85%), the RESIT had lower absolute error (approximately 2.39% ~ 33.5% reduction), lower relative errors (approximately 1.3% ~ 35.7% reduction) and higher correlations (approximately 2% ~ 690% increase) than traditional interpolation methods, including neighbor interpolation (NI) and spherical spline interpolation (SSI). In addition, the RESIT was integrated into the EEG preprocessing pipeline on the WeBrain cloud platform (https://webrain.uestc.edu.cn/). These results suggest that the RESIT is a promising interpolation method for both separate and simultaneous EEG preprocessing that benefits further EEG analysis, including event-related potential (ERP) analysis, EEG network analysis, and strict group-level statistics. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10548-021-00844-2.
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spelling pubmed-81959082021-06-28 Reference Electrode Standardization Interpolation Technique (RESIT): A Novel Interpolation Method for Scalp EEG Dong, Li Zhao, Lingling Zhang, Yufan Yu, Xue Li, Fali Li, Jianfu Lai, Yongxiu Liu, Tiejun Yao, Dezhong Brain Topogr Original Paper “Bad channels” are common phenomena during scalp electroencephalography (EEG) recording that arise due to various technique-related reasons, and reconstructing signals from bad channels is an inevitable choice in EEG processing. However, current interpolation methods are all based on purely mathematical interpolation theory, ignoring the neurophysiological basis of the EEG signals, and their performance needs to be further improved, especially when there are many scattered or adjacent bad channels. Therefore, a new interpolation method, named the reference electrode standardization interpolation technique (RESIT), was developed for interpolating scalp EEG channels. Resting-state and event-related EEG datasets were used to investigate the performance of the RESIT. The main results showed that (1) assuming 10% bad channels, RESIT can reconstruct the bad channels well; (2) as the percentage of bad channels increased (from 2% to 85%), the absolute and relative errors between the true and RESIT-reconstructed signals generally increased, and the correlations between the true and RESIT signals decreased; (3) for a range of bad channel percentages (2% ~ 85%), the RESIT had lower absolute error (approximately 2.39% ~ 33.5% reduction), lower relative errors (approximately 1.3% ~ 35.7% reduction) and higher correlations (approximately 2% ~ 690% increase) than traditional interpolation methods, including neighbor interpolation (NI) and spherical spline interpolation (SSI). In addition, the RESIT was integrated into the EEG preprocessing pipeline on the WeBrain cloud platform (https://webrain.uestc.edu.cn/). These results suggest that the RESIT is a promising interpolation method for both separate and simultaneous EEG preprocessing that benefits further EEG analysis, including event-related potential (ERP) analysis, EEG network analysis, and strict group-level statistics. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10548-021-00844-2. Springer US 2021-05-05 2021 /pmc/articles/PMC8195908/ /pubmed/33950323 http://dx.doi.org/10.1007/s10548-021-00844-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Paper
Dong, Li
Zhao, Lingling
Zhang, Yufan
Yu, Xue
Li, Fali
Li, Jianfu
Lai, Yongxiu
Liu, Tiejun
Yao, Dezhong
Reference Electrode Standardization Interpolation Technique (RESIT): A Novel Interpolation Method for Scalp EEG
title Reference Electrode Standardization Interpolation Technique (RESIT): A Novel Interpolation Method for Scalp EEG
title_full Reference Electrode Standardization Interpolation Technique (RESIT): A Novel Interpolation Method for Scalp EEG
title_fullStr Reference Electrode Standardization Interpolation Technique (RESIT): A Novel Interpolation Method for Scalp EEG
title_full_unstemmed Reference Electrode Standardization Interpolation Technique (RESIT): A Novel Interpolation Method for Scalp EEG
title_short Reference Electrode Standardization Interpolation Technique (RESIT): A Novel Interpolation Method for Scalp EEG
title_sort reference electrode standardization interpolation technique (resit): a novel interpolation method for scalp eeg
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8195908/
https://www.ncbi.nlm.nih.gov/pubmed/33950323
http://dx.doi.org/10.1007/s10548-021-00844-2
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