In order to control for the possibility that the observed association between FA/Mode and IHTT was driven by variations in age and gender, we entered these variables into the regression model as nuisance covariates. The resulting model: IHTT(P9/10)=−274∗FA+92∗Mode+.62∗Age+14.7∗Gender accounted for a significant proportion (36.8%) of the variance in IHTT (F4,33=4.224, p=0.008). Gender was the weakest predictor variable (β=.12, p=.425), and dropping it did not result in a significant reduction in the amount of variance accounted for by the model (R2-change=.014, Fchange1,29=.654, p=.425). The revised model: IHTT(P9/10)=−276∗FA+87∗Mode+.62∗Age accounted for 35.4% of the variance in IHTT (F3,33=5.478, p=.004). To control for the possibility that the observed association between IHTT and FA/Mode was driven by within-subject variations in fiber length or fiber curvature, we calculated indices for these two variables and entered them into the regression analysis. Average fiber length was calculated by integrating the distance between consecutive points on each of the tractography-defined visual callosal fibers, and averaging over all fibers. Mean curvature for each fiber was calculated by integrating the inverse of the radius of the osculating circle along the fiber
