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Published Article / AZ I07/2005/I-002 ENY-ARTICLE-2009-248

Trimmed estimators for robust averaging of event-related potentials

Leonowicz, Z (Wroclaw University of Technology, Poland) ; Karvanen, J (Helsinki University of Technology, Finland) ; Shishkin, S L (Lomonosov State University, Russia)


Abstract: 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.

Keyword(s): averaging ; event-related potentials ; evoked potentials ; mean ; median ; trimmed mean ; robust estimators of location ; trimmed estimators
Note: Journal of Neuroscience Methods, 2005, vol. 142, No. 1, pp. 17-26.

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Record created 2009-02-01, last modified 2009-02-01

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