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, & 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.