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Taking into account latency, amplitude, and morphology: improved estimation of single-trial ERPs by wavelet filtering and multiple linear regression

Taking into account latency, amplitude, and morphology: improved estimation of single-trial ERPs... Abstract Across-trial averaging is a widely used approach to enhance the signal-to-noise ratio (SNR) of event-related potentials (ERPs). However, across-trial variability of ERP latency and amplitude may contain physiologically relevant information that is lost by across-trial averaging. Hence, we aimed to develop a novel method that uses 1 ) wavelet filtering (WF) to enhance the SNR of ERPs and 2 ) a multiple linear regression with a dispersion term (MLR d ) that takes into account shape distortions to estimate the single-trial latency and amplitude of ERP peaks. Using simulated ERP data sets containing different levels of noise, we provide evidence that, compared with other approaches, the proposed WF+MLR d method yields the most accurate estimate of single-trial ERP features. When applied to a real laser-evoked potential data set, the WF+MLR d approach provides reliable estimation of single-trial latency, amplitude, and morphology of ERPs and thereby allows performing meaningful correlations at single-trial level. We obtained three main findings. First, WF significantly enhances the SNR of single-trial ERPs. Second, MLR d effectively captures and measures the variability in the morphology of single-trial ERPs, thus providing an accurate and unbiased estimate of their peak latency and amplitude. Third, intensity of pain perception significantly correlates with the single-trial estimates of N2 and P2 amplitude. These results indicate that WF+MLR d can be used to explore the dynamics between different ERP features, behavioral variables, and other neuroimaging measures of brain activity, thus providing new insights into the functional significance of the different brain processes underlying the brain responses to sensory stimuli. event-related potentials laser-evoked potentials single-trial analysis multiple linear regression with dispersion term Footnotes Copyright © 2011 the American Physiological Society « Previous | Next Article » Table of Contents This Article Published online before print August 2011 , doi: 10.​1152/​jn.​00220.​2011 AJP - JN Physiol December 2011 vol. 106 no. 6 3216-3229 » Abstract Free Full Text Free to you Full Text (PDF) Free to you All Versions of this Article: jn.00220.2011v1 106/6/3216 most recent Classifications Innovative Methodology Services Email this article to a friend Alert me when this article is cited Alert me if a correction is posted Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Download to citation manager Citing Articles Load citing article information Citing articles via Web of Science Google Scholar Articles by Hu, L. Articles by Iannetti, G. D. PubMed PubMed citation Articles by Hu, L. Articles by Iannetti, G. D. Related Content Load related web page information Current Issue December 2011, 106 (6) Alert me to new issues of AJP - JN Physiol About the Journal Information for Authors Submit a Manuscript Ethical Policies AuthorChoice PubMed Central Policy Reprints and Permissions Advertising Press Copyright © 2011 the American Physiological Society Print ISSN: 0022-3077 Online ISSN: 1522-1598 var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); var pageTracker = _gat._getTracker("UA-2924550-1"); pageTracker._trackPageview(); http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Neurophysiology The American Physiological Society

Taking into account latency, amplitude, and morphology: improved estimation of single-trial ERPs by wavelet filtering and multiple linear regression

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References (61)

Publisher
The American Physiological Society
Copyright
Copyright © 2011 the American Physiological Society
ISSN
0022-3077
eISSN
1522-1598
DOI
10.1152/jn.00220.2011
pmid
21880936
Publisher site
See Article on Publisher Site

Abstract

Abstract Across-trial averaging is a widely used approach to enhance the signal-to-noise ratio (SNR) of event-related potentials (ERPs). However, across-trial variability of ERP latency and amplitude may contain physiologically relevant information that is lost by across-trial averaging. Hence, we aimed to develop a novel method that uses 1 ) wavelet filtering (WF) to enhance the SNR of ERPs and 2 ) a multiple linear regression with a dispersion term (MLR d ) that takes into account shape distortions to estimate the single-trial latency and amplitude of ERP peaks. Using simulated ERP data sets containing different levels of noise, we provide evidence that, compared with other approaches, the proposed WF+MLR d method yields the most accurate estimate of single-trial ERP features. When applied to a real laser-evoked potential data set, the WF+MLR d approach provides reliable estimation of single-trial latency, amplitude, and morphology of ERPs and thereby allows performing meaningful correlations at single-trial level. We obtained three main findings. First, WF significantly enhances the SNR of single-trial ERPs. Second, MLR d effectively captures and measures the variability in the morphology of single-trial ERPs, thus providing an accurate and unbiased estimate of their peak latency and amplitude. Third, intensity of pain perception significantly correlates with the single-trial estimates of N2 and P2 amplitude. These results indicate that WF+MLR d can be used to explore the dynamics between different ERP features, behavioral variables, and other neuroimaging measures of brain activity, thus providing new insights into the functional significance of the different brain processes underlying the brain responses to sensory stimuli. event-related potentials laser-evoked potentials single-trial analysis multiple linear regression with dispersion term Footnotes Copyright © 2011 the American Physiological Society « Previous | Next Article » Table of Contents This Article Published online before print August 2011 , doi: 10.​1152/​jn.​00220.​2011 AJP - JN Physiol December 2011 vol. 106 no. 6 3216-3229 » Abstract Free Full Text Free to you Full Text (PDF) Free to you All Versions of this Article: jn.00220.2011v1 106/6/3216 most recent Classifications Innovative Methodology Services Email this article to a friend Alert me when this article is cited Alert me if a correction is posted Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Download to citation manager Citing Articles Load citing article information Citing articles via Web of Science Google Scholar Articles by Hu, L. Articles by Iannetti, G. D. PubMed PubMed citation Articles by Hu, L. Articles by Iannetti, G. D. Related Content Load related web page information Current Issue December 2011, 106 (6) Alert me to new issues of AJP - JN Physiol About the Journal Information for Authors Submit a Manuscript Ethical Policies AuthorChoice PubMed Central Policy Reprints and Permissions Advertising Press Copyright © 2011 the American Physiological Society Print ISSN: 0022-3077 Online ISSN: 1522-1598 var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); var pageTracker = _gat._getTracker("UA-2924550-1"); pageTracker._trackPageview();

Journal

Journal of NeurophysiologyThe American Physiological Society

Published: Dec 1, 2011

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