Within each of the GO and NOGO conditions, P3 peak and P3 latency measures at Fz, Cz, and Pz were entered into a MANCOVA model using age as a covariate and diagnosis as the between groups factor. When an overall MANCOVA model showed significant effect of diagnosis, the relevant univariate ANCOVA values were then evaluated for each dependent variable. Time–frequency analysis data were then evaluated at sites (Fz, Cz, or Pz) showing significant diagnosis or age effects for P3 amplitude or latency. This was accomplished using ANCOVA models with diagnosis as a between groups factor and age as a covariate for variables showing significant effects of diagnosis. Bivariate relations were tested with Pearson correlations. Stepwise multiple regression using age and the time–frequency analysis measures for variables showing significant effects of age. Finally, time–frequency variables significantly associated with age or diagnosis were evaluated with bivariate and stepwise multiple regression, using age, BMI, FA, and diffusivity measures (λT and λL) from the cingulate bundles (left and right cingulate bundles were averaged) and from the genu and splenium of the corpus callosum to determine the relations of white matter integrity to indices of EEG.
