Studentized Continuous Wavelet Transform (t-CWT) in the Analysis of Individual ERPs: Real and Simulated EEG Data

This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of...

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Main Authors: Ruben Gustav Leonhardt Real, Boris eKotchoubey, Andrea eKübler
Format: Article
Language:English
Published: Frontiers Media S.A. 2014-09-01
Series:Frontiers in Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00279/full
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author Ruben Gustav Leonhardt Real
Boris eKotchoubey
Andrea eKübler
author_facet Ruben Gustav Leonhardt Real
Boris eKotchoubey
Andrea eKübler
author_sort Ruben Gustav Leonhardt Real
collection DOAJ
description This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG data at six low signal-to-noise ratios. Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV. Applying the t-CWT to authentic EEG data obtained from 14 healthy participants confirmed its high sensitivity. The t-CWT may thus be well suited for the assessment of weak ERPs in single-subject settings.
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spelling doaj.art-24dc7168460742f49b347e5d1b80119b2022-12-22T02:28:29ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2014-09-01810.3389/fnins.2014.0027979000Studentized Continuous Wavelet Transform (t-CWT) in the Analysis of Individual ERPs: Real and Simulated EEG DataRuben Gustav Leonhardt Real0Boris eKotchoubey1Andrea eKübler2University of WürzburgUniversity of TübingenUniversity of WürzburgThis study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG data at six low signal-to-noise ratios. Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV. Applying the t-CWT to authentic EEG data obtained from 14 healthy participants confirmed its high sensitivity. The t-CWT may thus be well suited for the assessment of weak ERPs in single-subject settings.http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00279/fullEEGERPWaveletdetectionElectroencephalogramsignificance
spellingShingle Ruben Gustav Leonhardt Real
Boris eKotchoubey
Andrea eKübler
Studentized Continuous Wavelet Transform (t-CWT) in the Analysis of Individual ERPs: Real and Simulated EEG Data
Frontiers in Neuroscience
EEG
ERP
Wavelet
detection
Electroencephalogram
significance
title Studentized Continuous Wavelet Transform (t-CWT) in the Analysis of Individual ERPs: Real and Simulated EEG Data
title_full Studentized Continuous Wavelet Transform (t-CWT) in the Analysis of Individual ERPs: Real and Simulated EEG Data
title_fullStr Studentized Continuous Wavelet Transform (t-CWT) in the Analysis of Individual ERPs: Real and Simulated EEG Data
title_full_unstemmed Studentized Continuous Wavelet Transform (t-CWT) in the Analysis of Individual ERPs: Real and Simulated EEG Data
title_short Studentized Continuous Wavelet Transform (t-CWT) in the Analysis of Individual ERPs: Real and Simulated EEG Data
title_sort studentized continuous wavelet transform t cwt in the analysis of individual erps real and simulated eeg data
topic EEG
ERP
Wavelet
detection
Electroencephalogram
significance
url http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00279/full
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