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Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials.

Abstract : In electroencephalography, the classical event-related potential model often proves to be a limited method to study complex brain dynamics. For this reason, spectral techniques adapted from signal processing such as event-related spectral perturbation (ERSP) - and its variant event-related synchronization and 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 compared to classical ERSP methods.
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Contributor : Catherine Marlot Connect in order to contact the contributor
Submitted on : Monday, October 17, 2011 - 4:56:52 PM
Last modification on : Thursday, January 13, 2022 - 6:20:04 PM
Long-term archiving on: : Wednesday, January 18, 2012 - 2:30:26 AM


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Romain Grandchamp, Arnaud Delorme. Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials.. Frontiers in Psychology, Frontiers, 2011, 2, pp.236. ⟨10.3389/fpsyg.2011.00236⟩. ⟨hal-00633169⟩



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