Additionally, regressors for SPM realignment parameters and the mean signal amplitude of each volume obtained prior to global scaling were added to the model.
After realignment, the obtained mean EPI image was co-registered with the structural T1 image.
Covariates were modeled for the conditions of interest (novel and familiar target stimuli, standard picture), the six rigid-body movement parameters determined from realignment, and a single constant representing the mean over scans.
After realignment, PET frames were divided by the mean uptake in cerebellar cortex to obtain standard uptake ratio (SUVR) images.
In addition, six realignment parameters and two regressors consisting of the mean signal of white matter and CSF were included in the design matrix.
The mean image produced from the realignment stage was then spatially normalized to an MNI template image, using a 12-parameter linear affine transformation (translation, rotation, zoom, and shear in x, y, and z directions) and a linear combination of three dimensional discrete cosine transform basis functions.
A model was fit for each subject that included the motion parameter estimates from the image realignment stage, linear trends across each run, and the mean offset of each run.
Each participant's structural scan was coregistered to the mean EPI image produced from the realignment process and subsequently segmented and normalized to the Montreal Neurological Institute T1 average brain template.
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This shuffling, realignment and recalculation were repeated 1,000 times to obtain the mean and standard deviation of the relative entropy in each position.
