Researchers in psychology are paying increasing attention to temporal correlations in performance on cognitive tasks. Recently, Thornton and Gilden (2005) introduced a spectral method for analyzing psychological time series; in particular, this method is tailored to distinguish transient serial correlations from the persistent correlations characterized by 1/f noise. Thornton and Gilden applied their method to word-naming data to support the claimed ubiquity of 1/f noise in psychological time series. We argue that a previously presented method for distinguishing transient and persistent correlations (e.g., Wagenmakers, Farrell, and Ratcliff, 2004) compares favorably with the new method presented by Thornton and Gilden. We apply Thornton and Gilden's method to time series from a range of cognitive tasks and show that 1/f noise is not a ubiquitous property of psychological time series. Finally, we assess the theoretical developments in this area and argue that the development of well-specified models of the principles or mechanisms of human cognition giving rise to 1/f noise is long overdue.