The orthogonal regressors of interest were the four images (happy, angry, fearful, and circle/oval [i.e., shape]). These 0–1 regressors were convolved with a gamma variate function [50] modeling a prototypical hemodynamic response (6–8 second delay [51]) and to account for the temporal dynamics of the hemodynamic response (typically 12–16 seconds) [52], with each convolved time series normalized as a regressor of interest. These regressors, along with motion regressors, were entered into the AFNI program 3dDeconvolve to determine the height of each regressor for each subject. The main dependent measure was the voxel-wise normalized percent signal change created by dividing the regressor coefficient by the zero-order regressor. A Gaussian filter (FWHM 4mm) was used to account for variations in anatomy for individuals, and we did not use a high-pass filter. Spatially smoothed percent signal change data were transformed into anatomical magnetic resonance image Talairach coordinates, followed by manual transformation in AFNI.
