A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data.

The amplitude and latency of single-trial EEG/MEG signals may provide valuable information concerning human brain functioning. In this article we propose a new method to reliably estimate single-trial amplitude and latency of EEG/MEG signals. The advantages of the method are fourfold. First, no a-pr...

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Main Authors: Wouter D Weeda, Raoul P P P Grasman, Lourens J Waldorp, Maria C van de Laar, Maurits W van der Molen, Hilde M Huizenga
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2012-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3382617?pdf=render
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spelling doaj-2529079ca2644e4ba6f3e8876b738bfa2020-11-24T21:26:05ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0176e3829210.1371/journal.pone.0038292A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data.Wouter D WeedaRaoul P P P GrasmanLourens J WaldorpMaria C van de LaarMaurits W van der MolenHilde M HuizengaThe amplitude and latency of single-trial EEG/MEG signals may provide valuable information concerning human brain functioning. In this article we propose a new method to reliably estimate single-trial amplitude and latency of EEG/MEG signals. The advantages of the method are fourfold. First, no a-priori specified template function is required. Second, the method allows for multiple signals that may vary independently in amplitude and/or latency. Third, the method is less sensitive to noise as it models data with a parsimonious set of basis functions. Finally, the method is very fast since it is based on an iterative linear least squares algorithm. A simulation study shows that the method yields reliable estimates under different levels of latency variation and signal-to-noise ratioÕs. Furthermore, it shows that the existence of multiple signals can be correctly determined. An application to empirical data from a choice reaction time study indicates that the method describes these data accurately.http://europepmc.org/articles/PMC3382617?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Wouter D Weeda
Raoul P P P Grasman
Lourens J Waldorp
Maria C van de Laar
Maurits W van der Molen
Hilde M Huizenga
spellingShingle Wouter D Weeda
Raoul P P P Grasman
Lourens J Waldorp
Maria C van de Laar
Maurits W van der Molen
Hilde M Huizenga
A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data.
PLoS ONE
author_facet Wouter D Weeda
Raoul P P P Grasman
Lourens J Waldorp
Maria C van de Laar
Maurits W van der Molen
Hilde M Huizenga
author_sort Wouter D Weeda
title A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data.
title_short A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data.
title_full A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data.
title_fullStr A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data.
title_full_unstemmed A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data.
title_sort fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial eeg/meg data.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2012-01-01
description The amplitude and latency of single-trial EEG/MEG signals may provide valuable information concerning human brain functioning. In this article we propose a new method to reliably estimate single-trial amplitude and latency of EEG/MEG signals. The advantages of the method are fourfold. First, no a-priori specified template function is required. Second, the method allows for multiple signals that may vary independently in amplitude and/or latency. Third, the method is less sensitive to noise as it models data with a parsimonious set of basis functions. Finally, the method is very fast since it is based on an iterative linear least squares algorithm. A simulation study shows that the method yields reliable estimates under different levels of latency variation and signal-to-noise ratioÕs. Furthermore, it shows that the existence of multiple signals can be correctly determined. An application to empirical data from a choice reaction time study indicates that the method describes these data accurately.
url http://europepmc.org/articles/PMC3382617?pdf=render
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