The University of Southampton
University of Southampton Institutional Repository

Misallocation of variance in event-related potentials: simulation studies on the effects of test power, topography, and baseline-to-peak versus principal component quantifications

Misallocation of variance in event-related potentials: simulation studies on the effects of test power, topography, and baseline-to-peak versus principal component quantifications
Misallocation of variance in event-related potentials: simulation studies on the effects of test power, topography, and baseline-to-peak versus principal component quantifications
Since Wood and McCarthy's simulation study (Electroenceph Clin Neurophysiol 1984;59:249-260), the use of principal component analysis (PCA) as a tool for the identification and quantification of event-related potentials (ERP) has been considered a challenge. Three relevant aspects have not been fully acknowledged in previous studies, however, and were therefore investigated in the present simulation study. Firstly, the impact of test power on the amount of variance misallocation was studied. Secondly, the impact of ERP component topography on variance misallocation was investigated. Thirdly, a systematic evaluation of variance misallocation in baseline-to-peak derived ERP measures was performed. Results based on an overall set of 2700 simulations indicate that: (a) variance misallocation is reduced to an almost acceptable level when an appropriate test power is simulated; (b) the overall amount of variance misallocation remains at an almost acceptable level when systematic topographic effects are simulated in combination with an appropriate test power; and (c) variance misallocation is in fact also a problem in baseline-to-peak measures. These findings confirm that, when used appropriately, PCA is a helpful and efficient tool for the identification and quantification of ERPs.
ERP, PCA, misallocation of variance, baseline-to-peak measurement, varimax, topography
0165-0270
103-112
Beauducel, André
3313dcba-b8a2-4a64-94c1-14abaecbc90e
Debener, Stefan
e6bf9143-09a8-45c0-8536-3564885375d4
Beauducel, André
3313dcba-b8a2-4a64-94c1-14abaecbc90e
Debener, Stefan
e6bf9143-09a8-45c0-8536-3564885375d4

Beauducel, André and Debener, Stefan (2003) Misallocation of variance in event-related potentials: simulation studies on the effects of test power, topography, and baseline-to-peak versus principal component quantifications. Journal of Neuroscience Methods, 124 (1), 103-112. (doi:10.1016/S0165-0270(02)00381-3).

Record type: Article

Abstract

Since Wood and McCarthy's simulation study (Electroenceph Clin Neurophysiol 1984;59:249-260), the use of principal component analysis (PCA) as a tool for the identification and quantification of event-related potentials (ERP) has been considered a challenge. Three relevant aspects have not been fully acknowledged in previous studies, however, and were therefore investigated in the present simulation study. Firstly, the impact of test power on the amount of variance misallocation was studied. Secondly, the impact of ERP component topography on variance misallocation was investigated. Thirdly, a systematic evaluation of variance misallocation in baseline-to-peak derived ERP measures was performed. Results based on an overall set of 2700 simulations indicate that: (a) variance misallocation is reduced to an almost acceptable level when an appropriate test power is simulated; (b) the overall amount of variance misallocation remains at an almost acceptable level when systematic topographic effects are simulated in combination with an appropriate test power; and (c) variance misallocation is in fact also a problem in baseline-to-peak measures. These findings confirm that, when used appropriately, PCA is a helpful and efficient tool for the identification and quantification of ERPs.

This record has no associated files available for download.

More information

Published date: 2003
Keywords: ERP, PCA, misallocation of variance, baseline-to-peak measurement, varimax, topography

Identifiers

Local EPrints ID: 27532
URI: http://eprints.soton.ac.uk/id/eprint/27532
ISSN: 0165-0270
PURE UUID: 33be3419-b1fc-4005-b9a7-0773a1bd915c

Catalogue record

Date deposited: 27 Apr 2006
Last modified: 15 Mar 2024 07:19

Export record

Altmetrics

Contributors

Author: André Beauducel
Author: Stefan Debener

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×