These TF applications with go/no-go data are largely based on trial-level data, and it is important to explain that TF approaches can be applied to both trial-level or condition averaged data. While TF applications using averaged data will contain mostly phase-locked information, applications to trial-level data will contain all activity, phase-locked and non phase-locked. Broadly, the majority of TF applications in the literature have focused on trial-level data, with the goal of assessing the new information available at the trial-level that cannot be modeled in the condition averaged data from which common time-domain measures are taken (N2, P3, etc.). The work reported here, however, is focused on application of TF analysis using condition averaged data, with the goal of re-representing widely studied time-domain N2 and P3 components in terms of TF theta and delta activity. The idea is to use exactly the same averaged data in both time-domain and time-frequency approaches to show direct correspondence between the measures across the two domains. This approach has recently contributed important new information to the understanding of the FN and P3 time-domain components
