Single-Trial Normalization for Event-Related Spectral Decomposition Reduces Sensitivity to Noisy Trials

September 30, 2011
Arnaud Delorme, PhD

Grandchamp R, Delorme A. (2011)  Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials. Frontiers in Psychology. Sep 30;2:236. doi: 10.3389/fpsyg.2011.00236. eCollection 2011.


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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