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Article: A novel approach for enhancing the signal-to-noise ratio and detecting automatically event-related potentials (ERPs) in single trials

TitleA novel approach for enhancing the signal-to-noise ratio and detecting automatically event-related potentials (ERPs) in single trials
Authors
KeywordsEvent-related potentials (ERPs)
Independent component analysis (ICA)
Laser-evoked potentials (LEPs)
Multiple linear regression
N1 wave
Single-trial analysis
Wavelet filtering
Issue Date2010
PublisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/ynimg
Citation
Neuroimage, 2010, v. 50 n. 1, p. 99-111 How to Cite?
AbstractBrief radiant laser pulses can be used to activate cutaneous Aδ and C nociceptors selectively and elicit a number of transient brain responses in the ongoing EEG (N1, N2 and P2 waves of laser-evoked brain potentials, LEPs). Despite its physiological and clinical relevance, the early-latency N1 wave of LEPs is often difficult to measure reliably, because of its small signal-to-noise ratio (SNR), thus producing unavoidable biases in the interpretation of the results. Here, we aimed to develop a method to enhance the SNR of the N1 wave and measure its peak latency and amplitude in both average and single-trial waveforms. We obtained four main findings. First, we suggest that the N1 wave can be better detected using a central-frontal montage (Cc-Fz), as compared to the recommended temporal-frontal montage (Tc-Fz). Second, we show that the N1 wave is optimally detected when the neural activities underlying the N2 wave, which interfere with the scalp expression of the N1 wave, are preliminary isolated and removed using independent component analysis (ICA). Third, we show that after these N2-related activities are removed, the SNR of the N1 wave can be further enhanced using a novel approach based on wavelet filtering. Fourth, we provide quantitative evidence that a multiple linear regression approach can be applied to these filtered waveforms to obtain an automatic, reliable and unbiased estimate of the peak latency and amplitude of the N1 wave, both in average and single-trial waveforms. © 2009 Elsevier Inc. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/170153
ISSN
2023 Impact Factor: 4.7
2023 SCImago Journal Rankings: 2.436
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorHu, Len_US
dc.contributor.authorMouraux, Aen_US
dc.contributor.authorHu, Yen_US
dc.contributor.authorIannetti, GDen_US
dc.date.accessioned2012-10-30T06:05:39Z-
dc.date.available2012-10-30T06:05:39Z-
dc.date.issued2010en_US
dc.identifier.citationNeuroimage, 2010, v. 50 n. 1, p. 99-111en_US
dc.identifier.issn1053-8119en_US
dc.identifier.urihttp://hdl.handle.net/10722/170153-
dc.description.abstractBrief radiant laser pulses can be used to activate cutaneous Aδ and C nociceptors selectively and elicit a number of transient brain responses in the ongoing EEG (N1, N2 and P2 waves of laser-evoked brain potentials, LEPs). Despite its physiological and clinical relevance, the early-latency N1 wave of LEPs is often difficult to measure reliably, because of its small signal-to-noise ratio (SNR), thus producing unavoidable biases in the interpretation of the results. Here, we aimed to develop a method to enhance the SNR of the N1 wave and measure its peak latency and amplitude in both average and single-trial waveforms. We obtained four main findings. First, we suggest that the N1 wave can be better detected using a central-frontal montage (Cc-Fz), as compared to the recommended temporal-frontal montage (Tc-Fz). Second, we show that the N1 wave is optimally detected when the neural activities underlying the N2 wave, which interfere with the scalp expression of the N1 wave, are preliminary isolated and removed using independent component analysis (ICA). Third, we show that after these N2-related activities are removed, the SNR of the N1 wave can be further enhanced using a novel approach based on wavelet filtering. Fourth, we provide quantitative evidence that a multiple linear regression approach can be applied to these filtered waveforms to obtain an automatic, reliable and unbiased estimate of the peak latency and amplitude of the N1 wave, both in average and single-trial waveforms. © 2009 Elsevier Inc. All rights reserved.en_US
dc.languageengen_US
dc.publisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/ynimgen_US
dc.relation.ispartofNeuroImageen_US
dc.subjectEvent-related potentials (ERPs)-
dc.subjectIndependent component analysis (ICA)-
dc.subjectLaser-evoked potentials (LEPs)-
dc.subjectMultiple linear regression-
dc.subjectN1 wave-
dc.subjectSingle-trial analysis-
dc.subjectWavelet filtering-
dc.subject.meshAdulten_US
dc.subject.meshAutomationen_US
dc.subject.meshBrain - Physiopathologyen_US
dc.subject.meshElectroencephalography - Methodsen_US
dc.subject.meshEvoked Potentialsen_US
dc.subject.meshFemaleen_US
dc.subject.meshHumansen_US
dc.subject.meshLasersen_US
dc.subject.meshLinear Modelsen_US
dc.subject.meshMaleen_US
dc.subject.meshPain - Physiopathologyen_US
dc.subject.meshPhysical Stimulationen_US
dc.subject.meshScalp - Physiopathologyen_US
dc.subject.meshSignal Processing, Computer-Assisteden_US
dc.subject.meshTime Factorsen_US
dc.subject.meshYoung Adulten_US
dc.titleA novel approach for enhancing the signal-to-noise ratio and detecting automatically event-related potentials (ERPs) in single trialsen_US
dc.typeArticleen_US
dc.identifier.emailHu, Y:yhud@hku.hken_US
dc.identifier.authorityHu, Y=rp00432en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1016/j.neuroimage.2009.12.010en_US
dc.identifier.pmid20004255-
dc.identifier.scopuseid_2-s2.0-75249093704en_US
dc.identifier.hkuros174070-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-75249093704&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume50en_US
dc.identifier.issue1en_US
dc.identifier.spage99en_US
dc.identifier.epage111en_US
dc.identifier.isiWOS:000274810100010-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridHu, L=34770075600en_US
dc.identifier.scopusauthoridMouraux, A=6602503125en_US
dc.identifier.scopusauthoridHu, Y=7407116091en_US
dc.identifier.scopusauthoridIannetti, GD=7005461102en_US
dc.identifier.citeulike6611770-
dc.identifier.issnl1053-8119-

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