Event-related components are structurally represented by intrinsic event-related potentials

Abstract The detection of event-related potentials (ERPs) through electroencephalogram (EEG) analysis is a well-established method for understanding brain functions during a cognitive process. To increase the signal-to-noise ratio (SNR) and stationarity of the data, ERPs are often filtered to a wide...

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Autores principales:	Chong-Chih Tsai, Wei-Kuang Liang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/65c1e9b0f132464aa2d8cda1a431fa7e
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spelling	oai:doaj.org-article:65c1e9b0f132464aa2d8cda1a431fa7e2021-12-02T13:33:44ZEvent-related components are structurally represented by intrinsic event-related potentials10.1038/s41598-021-85235-02045-2322https://doaj.org/article/65c1e9b0f132464aa2d8cda1a431fa7e2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-85235-0https://doaj.org/toc/2045-2322Abstract The detection of event-related potentials (ERPs) through electroencephalogram (EEG) analysis is a well-established method for understanding brain functions during a cognitive process. To increase the signal-to-noise ratio (SNR) and stationarity of the data, ERPs are often filtered to a wideband frequency range, such as 0.05–30 Hz. Alternatively, a natural-filtering procedure can be performed through empirical mode decomposition (EMD), which yields intrinsic mode functions (IMFs) for each trial of the EEG data, followed by averaging over trials to generate the event-related modes. However, although the EMD-based filtering procedure has advantages such as a high SNR, suitable waveform shape, and high statistical power, one fundamental drawback of the procedure is that it requires the selection of an IMF (or a partial sum of a range of IMFs) to determine an ERP component effectively. Therefore, in this study, we propose an intrinsic ERP (iERP) method to overcome the drawbacks and retain the advantages of event-related mode analysis for investigating ERP components. The iERP method can reveal multiple ERP components at their characteristic time scales and suitably cluster statistical effects among modes by using a tailored definition of each mode’s neighbors. We validated the iERP method by using realistic EEG data sets acquired from a face perception task and visual working memory task. By using these two data sets, we demonstrated how to apply the iERP method to a cognitive task and incorporate existing cluster-based tests into iERP analysis. Moreover, iERP analysis revealed the statistical effects between (or among) experimental conditions more effectively than the conventional ERP method did.Chong-Chih TsaiWei-Kuang LiangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Chong-Chih Tsai Wei-Kuang Liang Event-related components are structurally represented by intrinsic event-related potentials
description	Abstract The detection of event-related potentials (ERPs) through electroencephalogram (EEG) analysis is a well-established method for understanding brain functions during a cognitive process. To increase the signal-to-noise ratio (SNR) and stationarity of the data, ERPs are often filtered to a wideband frequency range, such as 0.05–30 Hz. Alternatively, a natural-filtering procedure can be performed through empirical mode decomposition (EMD), which yields intrinsic mode functions (IMFs) for each trial of the EEG data, followed by averaging over trials to generate the event-related modes. However, although the EMD-based filtering procedure has advantages such as a high SNR, suitable waveform shape, and high statistical power, one fundamental drawback of the procedure is that it requires the selection of an IMF (or a partial sum of a range of IMFs) to determine an ERP component effectively. Therefore, in this study, we propose an intrinsic ERP (iERP) method to overcome the drawbacks and retain the advantages of event-related mode analysis for investigating ERP components. The iERP method can reveal multiple ERP components at their characteristic time scales and suitably cluster statistical effects among modes by using a tailored definition of each mode’s neighbors. We validated the iERP method by using realistic EEG data sets acquired from a face perception task and visual working memory task. By using these two data sets, we demonstrated how to apply the iERP method to a cognitive task and incorporate existing cluster-based tests into iERP analysis. Moreover, iERP analysis revealed the statistical effects between (or among) experimental conditions more effectively than the conventional ERP method did.
format	article
author	Chong-Chih Tsai Wei-Kuang Liang
author_facet	Chong-Chih Tsai Wei-Kuang Liang
author_sort	Chong-Chih Tsai
title	Event-related components are structurally represented by intrinsic event-related potentials
title_short	Event-related components are structurally represented by intrinsic event-related potentials
title_full	Event-related components are structurally represented by intrinsic event-related potentials
title_fullStr	Event-related components are structurally represented by intrinsic event-related potentials
title_full_unstemmed	Event-related components are structurally represented by intrinsic event-related potentials
title_sort	event-related components are structurally represented by intrinsic event-related potentials
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/65c1e9b0f132464aa2d8cda1a431fa7e
work_keys_str_mv	AT chongchihtsai eventrelatedcomponentsarestructurallyrepresentedbyintrinsiceventrelatedpotentials AT weikuangliang eventrelatedcomponentsarestructurallyrepresentedbyintrinsiceventrelatedpotentials
_version_	1718392856446500864

Event-related components are structurally represented by intrinsic event-related potentials

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