Demographic variables were analyzed using the independent t-test. RCFT performance was analyzed using a one-way analysis of covariance (ANCOVA) with gender as a covariate. Hanning windowing with 1 s and fast Fourier transform was used to calculate absolute power (AP) for the theta (4–7 Hz), lower-alpha (8–9 Hz), and upper alpha (10–12 Hz) bands. Mean AP for 6 min represents the magnitude of the frequency (mV2/Hz). To identify areal changes in frequency activity, four regions of interest (ROIs), i.e., the frontal (average of F3, Fz, and F4), central (average of C3, Cz, and C4), parietal (average of P3, Pz, and P4), and occipital (average of O1, Oz, and O2) areas were selected (Núñez-Jaramillo et al., 2015). The values of each frequency band were compared by repeated-measures mixed-design ANCOVA, using the ROIs (frontal, central, parietal, and occipital) as a within-subject factor and group (BD and non-BD groups) as a between-subject factor. The Greenhouse-Geisser correction for sphericity was employed when appropriate, and the Bonferroni correction was applied to adjust for multiple comparisons.
