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Multivariate assessment of event-related potentials with the t-CWT method

BACKGROUND: Event-related brain potentials (ERPs) are usually assessed with univariate statistical tests although they are essentially multivariate objects. Brain–computer interface applications are a notable exception to this practice, because they are based on multivariate classification of single...

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Autor principal: Bostanov, Vladimir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4635610/
https://www.ncbi.nlm.nih.gov/pubmed/26541673
http://dx.doi.org/10.1186/s12868-015-0185-z
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author Bostanov, Vladimir
author_facet Bostanov, Vladimir
author_sort Bostanov, Vladimir
collection PubMed
description BACKGROUND: Event-related brain potentials (ERPs) are usually assessed with univariate statistical tests although they are essentially multivariate objects. Brain–computer interface applications are a notable exception to this practice, because they are based on multivariate classification of single-trial ERPs. Multivariate ERP assessment can be facilitated by feature extraction methods. One such method is t-CWT, a mathematical-statistical algorithm based on the continuous wavelet transform (CWT) and Student’s t-test. RESULTS: This article begins with a geometric primer on some basic concepts of multivariate statistics as applied to ERP assessment in general and to the t-CWT method in particular. Further, it presents for the first time a detailed, step-by-step, formal mathematical description of the t-CWT algorithm. A new multivariate outlier rejection procedure based on principal component analysis in the frequency domain is presented as an important pre-processing step. The MATLAB and GNU Octave implementation of t-CWT is also made publicly available for the first time as free and open source code. The method is demonstrated on some example ERP data obtained in a passive oddball paradigm. Finally, some conceptually novel applications of the multivariate approach in general and of the t-CWT method in particular are suggested and discussed. CONCLUSIONS: Hopefully, the publication of both the t-CWT source code and its underlying mathematical algorithm along with a didactic geometric introduction to some basic concepts of multivariate statistics would make t-CWT more accessible to both users and developers in the field of neuroscience research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12868-015-0185-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-46356102015-11-07 Multivariate assessment of event-related potentials with the t-CWT method Bostanov, Vladimir BMC Neurosci Methodology Article BACKGROUND: Event-related brain potentials (ERPs) are usually assessed with univariate statistical tests although they are essentially multivariate objects. Brain–computer interface applications are a notable exception to this practice, because they are based on multivariate classification of single-trial ERPs. Multivariate ERP assessment can be facilitated by feature extraction methods. One such method is t-CWT, a mathematical-statistical algorithm based on the continuous wavelet transform (CWT) and Student’s t-test. RESULTS: This article begins with a geometric primer on some basic concepts of multivariate statistics as applied to ERP assessment in general and to the t-CWT method in particular. Further, it presents for the first time a detailed, step-by-step, formal mathematical description of the t-CWT algorithm. A new multivariate outlier rejection procedure based on principal component analysis in the frequency domain is presented as an important pre-processing step. The MATLAB and GNU Octave implementation of t-CWT is also made publicly available for the first time as free and open source code. The method is demonstrated on some example ERP data obtained in a passive oddball paradigm. Finally, some conceptually novel applications of the multivariate approach in general and of the t-CWT method in particular are suggested and discussed. CONCLUSIONS: Hopefully, the publication of both the t-CWT source code and its underlying mathematical algorithm along with a didactic geometric introduction to some basic concepts of multivariate statistics would make t-CWT more accessible to both users and developers in the field of neuroscience research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12868-015-0185-z) contains supplementary material, which is available to authorized users. BioMed Central 2015-11-05 /pmc/articles/PMC4635610/ /pubmed/26541673 http://dx.doi.org/10.1186/s12868-015-0185-z Text en © Bostanov. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Bostanov, Vladimir
Multivariate assessment of event-related potentials with the t-CWT method
title Multivariate assessment of event-related potentials with the t-CWT method
title_full Multivariate assessment of event-related potentials with the t-CWT method
title_fullStr Multivariate assessment of event-related potentials with the t-CWT method
title_full_unstemmed Multivariate assessment of event-related potentials with the t-CWT method
title_short Multivariate assessment of event-related potentials with the t-CWT method
title_sort multivariate assessment of event-related potentials with the t-cwt method
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4635610/
https://www.ncbi.nlm.nih.gov/pubmed/26541673
http://dx.doi.org/10.1186/s12868-015-0185-z
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