using a 3 Hz lowpass 3rd order Butterworth filter, to isolate delta-band activity. These theta- and delta-filtered signals were then each transformed into time-frequency energy distributions (surfaces) using the binomial reduced interference distribution (RID) variant of Cohen’s class of time-frequency transforms (for details, see Bernat et al., 2005). Next, the TF-PCA was applied to an area corresponding to the zero-to-750 ms time range and 0-to-10 Hz frequency range, separately for theta- and delta-filtered TF distributions. The variance accounted for by the first principal component (PC) in each analysis (theta band: 54.95%; delta band: 78.89%) substantially exceeded that accounted for by the next PC (theta band: 12.80%; delta band: 7.89%), indicating that retention of a single PC was justifiable in each case. These TF-based theta and delta PCs (depicted in Figure 1) served as the primary dependent variables in the analyses of brain reactivity to feedback stimuli reported below. As with the time-domain FRN and P300 measures, electrodes FCz and Cz, respectively, were most proximal topographically to the maximum of the theta and delta Gain-Loss condition differences (see Figure 2). Data from these electrode sites were thus employed in the statistical analyses of TF component scores reported below.
