The purpose of this functional magnetic resonance imaging (fMRI) study was to investigate the effects of smoothing kernel size and the extent of physiological noise correction on neuronal activity estimation. The fMRI data acquired from heavy smokers were used to evaluate the effect of preprocessing options. Three different smoothing kernel sizes (i.e., 4, 6, and 8 mm) were applied to compare neuronal activation between two different conditions (e.g., abstained and satiated conditions). In addition, the physiological noise was extracted from white matter and cerebrospinal fluid via principal component analysis and different numbers of the principal components (PCs) were removed (i.e., 0, 1, 3, and 5). As results, as smoothing kernel size increased, the more number of voxels survived in a group-level analysis. Also, removing 3 noise-related PCs leaded to the largest statistical value within activated foci compared to the other cases.
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