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Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model

Objective. In electroencephalography (EEG) measurements, the signal of each recording electrode is contrasted with a reference electrode or a combination of electrodes. The estimation of a neutral reference is a long-standing issue in EEG data analysis, which has motivated the proposal of different...

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Autores principales: Liu, Quanying, Balsters, Joshua H, Baechinger, Marc, van der Groen, Onno, Wenderoth, Nicole, Mantini, Dante
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOP Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4719184/
https://www.ncbi.nlm.nih.gov/pubmed/26305167
http://dx.doi.org/10.1088/1741-2560/12/5/056012
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author Liu, Quanying
Balsters, Joshua H
Baechinger, Marc
van der Groen, Onno
Wenderoth, Nicole
Mantini, Dante
author_facet Liu, Quanying
Balsters, Joshua H
Baechinger, Marc
van der Groen, Onno
Wenderoth, Nicole
Mantini, Dante
author_sort Liu, Quanying
collection PubMed
description Objective. In electroencephalography (EEG) measurements, the signal of each recording electrode is contrasted with a reference electrode or a combination of electrodes. The estimation of a neutral reference is a long-standing issue in EEG data analysis, which has motivated the proposal of different re-referencing methods, among which linked-mastoid re-referencing (LMR), average re-referencing (AR) and reference electrode standardization technique (REST). In this study we quantitatively assessed the extent to which the use of a high-density montage and a realistic head model can impact on the optimal estimation of a neutral reference for EEG recordings. Approach. Using simulated recordings generated by projecting specific source activity over the sensors, we assessed to what extent AR, REST and LMR may distort the scalp topography. We examined the impact electrode coverage has on AR and REST, and how accurate the REST reconstruction is for realistic and less realistic (three-layer and single-layer spherical) head models, and with possible uncertainty in the electrode positions. We assessed LMR, AR and REST also in the presence of typical EEG artifacts that are mixed in the recordings. Finally, we applied them to real EEG data collected in a target detection experiment to corroborate our findings on simulated data. Main results. Both AR and REST have relatively low reconstruction errors compared to LMR, and that REST is less sensitive than AR and LMR to artifacts mixed in the EEG data. For both AR and REST, high electrode density yields low re-referencing reconstruction errors. A realistic head model is critical for REST, leading to a more accurate estimate of a neutral reference compared to spherical head models. With a low-density montage, REST shows a more reliable reconstruction than AR either with a realistic or a three-layer spherical head model. Conversely, with a high-density montage AR yields better results unless precise information on electrode positions is available. Significance. Our study is the first to quantitatively assess the performance of EEG re-referencing techniques in relation to the use of a high-density montage and a realistic head model. We hope our study will help researchers in the choice of the most effective re-referencing approach for their EEG studies.
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spelling pubmed-47191842016-01-20 Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model Liu, Quanying Balsters, Joshua H Baechinger, Marc van der Groen, Onno Wenderoth, Nicole Mantini, Dante J Neural Eng Paper Objective. In electroencephalography (EEG) measurements, the signal of each recording electrode is contrasted with a reference electrode or a combination of electrodes. The estimation of a neutral reference is a long-standing issue in EEG data analysis, which has motivated the proposal of different re-referencing methods, among which linked-mastoid re-referencing (LMR), average re-referencing (AR) and reference electrode standardization technique (REST). In this study we quantitatively assessed the extent to which the use of a high-density montage and a realistic head model can impact on the optimal estimation of a neutral reference for EEG recordings. Approach. Using simulated recordings generated by projecting specific source activity over the sensors, we assessed to what extent AR, REST and LMR may distort the scalp topography. We examined the impact electrode coverage has on AR and REST, and how accurate the REST reconstruction is for realistic and less realistic (three-layer and single-layer spherical) head models, and with possible uncertainty in the electrode positions. We assessed LMR, AR and REST also in the presence of typical EEG artifacts that are mixed in the recordings. Finally, we applied them to real EEG data collected in a target detection experiment to corroborate our findings on simulated data. Main results. Both AR and REST have relatively low reconstruction errors compared to LMR, and that REST is less sensitive than AR and LMR to artifacts mixed in the EEG data. For both AR and REST, high electrode density yields low re-referencing reconstruction errors. A realistic head model is critical for REST, leading to a more accurate estimate of a neutral reference compared to spherical head models. With a low-density montage, REST shows a more reliable reconstruction than AR either with a realistic or a three-layer spherical head model. Conversely, with a high-density montage AR yields better results unless precise information on electrode positions is available. Significance. Our study is the first to quantitatively assess the performance of EEG re-referencing techniques in relation to the use of a high-density montage and a realistic head model. We hope our study will help researchers in the choice of the most effective re-referencing approach for their EEG studies. IOP Publishing 2015-10 2015-08-26 /pmc/articles/PMC4719184/ /pubmed/26305167 http://dx.doi.org/10.1088/1741-2560/12/5/056012 Text en © 2015 IOP Publishing Ltd http://creativecommons.org/licenses/by/3.0/ Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence (http://creativecommons.org/licenses/by/3.0) . Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
spellingShingle Paper
Liu, Quanying
Balsters, Joshua H
Baechinger, Marc
van der Groen, Onno
Wenderoth, Nicole
Mantini, Dante
Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model
title Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model
title_full Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model
title_fullStr Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model
title_full_unstemmed Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model
title_short Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model
title_sort estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model
topic Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4719184/
https://www.ncbi.nlm.nih.gov/pubmed/26305167
http://dx.doi.org/10.1088/1741-2560/12/5/056012
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