Figure 1.

Work flow of the study. Three rs‐fMRI runs (107 consecutive image volumes) were acquired. For each session, we performed preprocessing, including slice‐timing correction, head motion correction, denoising, temporal filtering, image normalization, and gray‐matter segmentation. For preprocessing 1, denoising included CompCor and the regression of six head motion parameters and global signal. Denoising for preprocessing 2 included CompCor. Then, the functional connectivity strength of each pair of gray‐matter voxels was calculated and transformed to Z values for each run (Z1, Z2, and Z3). These 3 values were averaged (Z = (Z1 + Z2 + Z3)/3). An adjacent matrix was then determined using the Z matrix with three different thresholds (1.96, 2.58, or 3.28) to calculate normalized alpha centrality (nAC₀ and nAC₁) at each gray‐matter voxel. Global connectivity (GC) was the difference between the two values (nAC₁–nAC₀)