Statistical analysis of timing errors.

Abstract

Human rhythmic activities are variable. Cycle-to-cycle fluctuations form the behavioral observable. Traditional analysis focuses on statistical measures such as mean and variance. In this article we show that, by treating the fluctuations as a time series, one can apply techniques such as power spectra and rescaled range analysis to gain insight into the mechanisms underlying the remarkable abilities of humans to perform a variety of rhythmic movements, from maintaining memorized temporal patterns to anticipating and timing their movements to predictable sensory stimuli.