Functional MRI Processing

Functional MRI images were preprocessed using the Analysis of Functional Neuroimaging software (Cox, 1996). The preprocessing steps consisted of slice timing correction, motion correction, spatial smoothing (FWMH = 6 mm), band-pass temporal filtering (0.01–0.1 Hz), spatial normalization to standard Talairach space and removal of the head motion profiles, the WM, and cerebrospinal fluid (CSF) signal. To moderate the effects of head motion on estimates of resting-state functional connectivity (rsFC) (Power et al., 2012; Satterthwaite et al., 2012; van Dijk et al., 2012), we first calculated the average root mean square (RMS) of head motion and found no significant between-group difference (F = 1.15, P = 0.32). The average RMS of head movement for all three groups was considerably below the cutoff of 1 mm (average RMS = 0.13 for NC, 0.13 for aMCI, and 0.14 for SVMCI). Second, we censored volumes within each subject’s fMRI time-series that were associated with sudden head movements. For each subject, fMRI volume was censored if it is frame-wise displacement (FD) > 0.35.

We computed rsFC of the BG regions as follows. Within each seed region, we calculated the Pearson correlations with Fisher’s z-transformation between the averaged time courses of the seed region and all other brain voxels. Within-group one-sample t-test was performed for each seed region, and an rsFC map for each group was created by applying a threshold of p < 0.0001 with a cluster size of 86 voxels (P_corrected < 0.001 based on Monte Carlo simulations).