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000000027 001__ 27
000000027 037__ $$aENY-PREPRINT-2008-001
000000027 041__ $$aeng
000000027 100__ $$aLeonowicz, Z$$uLaboratory for Advanced Brain Signal Processing, Brain Science Institute, RIKEN, Japan
000000027 245__ $$aOptimized robust averaging of event-related potentials
000000027 260__ $$c2004-03-17
000000027 300__ $$a31p
000000027 500__ $$aPreprint submitted to Journal of Neuroscience Methods 17 March 2004
000000027 520__ $$aAveraging is one of the most commonly used procedures in Neuroscience and is the basic procedure for obtaining event-related potentials (ERP). Averaging or the estimation of the location of data can be done in different ways, although only the arithmetic mean is routinely used in the current practice of ERP research. In this paper, a number of location estimators (mean, median, trimmed mean, Winsorised mean and recently introduced trimmed L-mean) are reviewed. A new robust location estimator tanh, which allows the data-dependent optimization, is proposed for averaging of small number of trials. The performance of the location estimators, expressed by the signal-to-noise ratio (SNR) of averaged waveforms, is compared for different number of epochs randomly drawn from a set of real auditory evoked potential (EP) data. Procedure of multi-averaging is developed to optimize the choice of the location estimator with respect to SNR or other criterion of the performance. Experiments with real auditory EPs demonstrate significant achievable gain compared to the mean averaging. The procedure of multi-averaging can be applied to a wide range of experimental data, when an objective criterion of the quality of the averaged data can be calculated.
000000027 6531_ $$aevent-related potentials
000000027 6531_ $$aERP
000000027 6531_ $$aaveraging
000000027 6531_ $$aoptimization
000000027 6531_ $$arobust estimators of location
000000027 6531_ $$amean
000000027 6531_ $$amedian
000000027 6531_ $$atrimmed mean
000000027 6531_ $$aWinsorised mean
000000027 6531_ $$atrimmed L-mean
000000027 6531_ $$asignal-to-noise ratio
000000027 6531_ $$aSNR
000000027 6531_ $$atanh estimator
000000027 6531_ $$amulti-averaging
000000027 700__ $$aKarvanen, J$$uLaboratory for Advanced Brain Signal Processing, Brain Science Institute, RIKEN, Japan
000000027 700__ $$aShishkin, S$$uLaboratory for Advanced Brain Signal Processing, Brain Science Institute, RIKEN, Japan
000000027 8560_ $$fzbigniew.leonowicz@pwr.wroc.pl
000000027 8564_ $$uhttp://zet10.ipee.pwr.wroc.pl/record/27/files/$$zAccess to Fulltext
000000027 909CO $$ooai:zet10.pwr.wroc.pl:27$$pglobal
000000027 980__ $$aPREPRINT