Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials
In EEG research, the classical Event-Related Potential (ERP) model often proves to be a limited method when studying complex brain dynamics. For this reason, spectral techniques adapted from signal processing such as Event-Related Spectral Perturbation (ERSP) – and its variant ERS (Event-Related Syn...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2011-09-01
|
Series: | Frontiers in Psychology |
Subjects: | |
Online Access: | http://journal.frontiersin.org/Journal/10.3389/fpsyg.2011.00236/full |
id |
doaj-290fa522234f43e5a4c7b343b57509f7 |
---|---|
record_format |
Article |
spelling |
doaj-290fa522234f43e5a4c7b343b57509f72020-11-24T23:16:38ZengFrontiers Media S.A.Frontiers in Psychology1664-10782011-09-01210.3389/fpsyg.2011.0023610583Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trialsRomain eGrandchamp0Romain eGrandchamp1Arnaud eDelorme2Arnaud eDelorme3Arnaud eDelorme4Paul Sabatier UniversityCNRSPaul Sabatier UniversityCNRSUniversity of CaliforniaIn EEG research, the classical Event-Related Potential (ERP) model often proves to be a limited method when studying complex brain dynamics. For this reason, spectral techniques adapted from signal processing such as Event-Related Spectral Perturbation (ERSP) – and its variant ERS (Event-Related Synchronization) and ERD (Event-Related Desynchronization) – have been used over the past 20-years. They represent average spectral changes in response to a stimulus.These spectral methods do not have strong consensus for comparing pre and post-stimulus activity. When computing ERSP, pre-stimulus baseline removal is usually performed after averaging the spectral estimate of multiple trials. Correcting the baseline of each single-trial prior to averaging spectral estimates is an alternative baseline correction method. However, we show that this method leads to positively skewed post-stimulus ERSP values. We eventually present new single-trial based ERSP baseline correction methods that perform trial normalization or centering prior to applying classical baseline correction methods. We show that single-trial correction methods minimize the contribution of artifactual data trials with high-amplitude spectral estimates and are robust to outliers when performing statistical inference testing. We then characterize these methods in terms of their time-frequency responses and behavior when performing statistical inference testing compared to classical ERSP methods.http://journal.frontiersin.org/Journal/10.3389/fpsyg.2011.00236/fullEEGERPadditive modelbaselineERSPmultiplicative gain model |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Romain eGrandchamp Romain eGrandchamp Arnaud eDelorme Arnaud eDelorme Arnaud eDelorme |
spellingShingle |
Romain eGrandchamp Romain eGrandchamp Arnaud eDelorme Arnaud eDelorme Arnaud eDelorme Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials Frontiers in Psychology EEG ERP additive model baseline ERSP multiplicative gain model |
author_facet |
Romain eGrandchamp Romain eGrandchamp Arnaud eDelorme Arnaud eDelorme Arnaud eDelorme |
author_sort |
Romain eGrandchamp |
title |
Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials |
title_short |
Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials |
title_full |
Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials |
title_fullStr |
Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials |
title_full_unstemmed |
Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials |
title_sort |
single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Psychology |
issn |
1664-1078 |
publishDate |
2011-09-01 |
description |
In EEG research, the classical Event-Related Potential (ERP) model often proves to be a limited method when studying complex brain dynamics. For this reason, spectral techniques adapted from signal processing such as Event-Related Spectral Perturbation (ERSP) – and its variant ERS (Event-Related Synchronization) and ERD (Event-Related Desynchronization) – have been used over the past 20-years. They represent average spectral changes in response to a stimulus.These spectral methods do not have strong consensus for comparing pre and post-stimulus activity. When computing ERSP, pre-stimulus baseline removal is usually performed after averaging the spectral estimate of multiple trials. Correcting the baseline of each single-trial prior to averaging spectral estimates is an alternative baseline correction method. However, we show that this method leads to positively skewed post-stimulus ERSP values. We eventually present new single-trial based ERSP baseline correction methods that perform trial normalization or centering prior to applying classical baseline correction methods. We show that single-trial correction methods minimize the contribution of artifactual data trials with high-amplitude spectral estimates and are robust to outliers when performing statistical inference testing. We then characterize these methods in terms of their time-frequency responses and behavior when performing statistical inference testing compared to classical ERSP methods. |
topic |
EEG ERP additive model baseline ERSP multiplicative gain model |
url |
http://journal.frontiersin.org/Journal/10.3389/fpsyg.2011.00236/full |
work_keys_str_mv |
AT romainegrandchamp singletrialnormalizationforeventrelatedspectraldecompositionreducessensitivitytonoisytrials AT romainegrandchamp singletrialnormalizationforeventrelatedspectraldecompositionreducessensitivitytonoisytrials AT arnaudedelorme singletrialnormalizationforeventrelatedspectraldecompositionreducessensitivitytonoisytrials AT arnaudedelorme singletrialnormalizationforeventrelatedspectraldecompositionreducessensitivitytonoisytrials AT arnaudedelorme singletrialnormalizationforeventrelatedspectraldecompositionreducessensitivitytonoisytrials |
_version_ |
1725586568626831360 |