A General Linear Model approach was used to analyze the “between-factor” × “within-factors” interaction effect. The between-subject factor was “group” (HV vs. MAtot or HV vs. MA subgroups); the within-subject factor was “blocks”. Two models of repeated measures ANOVA (rm-ANOVA) followed by univariate ANOVAs were employed to investigate the interaction effect. Univariate results were analyzed only if Wilks’ Lambda multivariate significance criterion was achieved. The sphericity of the covariance matrix was verified with the Mauchly Sphericity Test; in the case of violation of the sphericity assumption, Greenhouse-Geisser (G-G) epsilon (ε) adjustment was used. In rm-ANOVA and ANOVA models, partial eta2ηp2 and observed power (op) were used as measures of effect size and power, respectively. To define which comparison(s) contributed to the major effects, post hoc tests were performed with Tukey Honest Significant Difference (HSD) test.