Within Subject Multiple Regressor Analyses: The orthogonal regressors of interest were the four images (happy, angry, fearful, and circle/oval controls) which were convolved with a gamma variate function modeling a prototypical hemodynamic response (6–8 second delay) and to account for temporal dynamics of the hemodynamic response (typically 12–16 seconds), with each convolved time series normalized as a regressor of interest (Friston et al., 1995). Along with baseline, linear, and motion regressors (roll, pitch, and yaw), the AFNI program 3dDeconvolve determined the height of each regressor of interest for each subject time series. The main dependent measure was the voxel-wise normalized percent signal change created by dividing the regressor coefficient by the zero-order regressor (i.e., baseline). A Gaussian filter (FWHM 4mm) was used to account for variations in anatomy across individuals. Spatially smoothed percent signal change data were transformed into anatomical magnetic resonance image Talairach coordinates.
