Trimmed estimators for robust averaging of event-related potentials.
Averaging (in statistical terms, estimation of the location of data) is one of the most commonly used procedures in neuroscience and the basic procedure for obtaining event-related potentials (ERP). Only the arithmetic mean is routinely used in the current practice of ERP research, though its sensitivity to outliers is well-known. Weighted averaging is sometimes used as a more robust procedure, however, it can be not sufficiently appropriate when the signal is nonstationary within a trial. Trimmed estimators provide an alternative way to average data. In this paper, a number of such location estimators (trimmed mean, Winsorized mean and recently introduced trimmed L-mean) are reviewed, as well as arithmetic mean and median. A new robust location estimator tanh, which allows the data-dependent optimization, is proposed for averaging of small number of trials. The possibilities to improve signal-to-noise ratio (SNR) of averaged waveforms using trimmed location estimators are demonstrated for epochs randomly drawn from a set of real auditory evoked potential data.
Leonowicz
Zbigniew
Z
Laboratory for Advanced Brain Signal Processing, RIKEN Brain Science Institute, Saitama 351-0198, Japan. zbigniew.leonowicz@pwr.wroc.pl
Karvanen
Juha
J
Shishkin
Sergei L
SL
D000328:Adult; D000465:Algorithms; D016477:Artifacts; D002540:Cerebral Cortex / Q000502:physiology; D004569:Electroencephalography / Q000295:instrumentation / Q000379:methods*; D004594:Electrophysiology / Q000295:instrumentation / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology*; D005072:Evoked Potentials, Auditory / Q000502:physiology; D006801:Humans; D008297:Male; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted