Fig. 3: Nonuniform age-related increases of regional CBF during infancy.

a Regional CBF increases in a logarithmic fashion across the cortex, most prominent in the heteromodal association cortex than unimodal cortex. Regional CBF increase is modeled for every cortical voxel using the statistical model of Eq. (4), with z > 5.1 indicating significant age effects after Bonferroni correction for multiple comparisons (Bonferroni corrected p < 0.05; two-sided). b Regional CBF increases vary heterogeneously by functional brain networks defined by Yeo et al., (2011) (top panel). The box plots in the bottom panel reflect the voxel-wise age effect of infant rCBF in seven functional networks ordered by median value. The centers of boxes are median values. Bounds of boxes are first and third quartile, with ends of whiskers representing the minima and maxima of non-outlier points of the distribution. Regional CBF increases most significantly with age in the fronto-parietal and default-mode networks, and less so in the limbic and sensorimotor networks. DA: dorsal attention (N = 13,730 voxels); DMN: default-mode network (N = 25,424 voxels); FPN: fronto-parietal network (N = 16,829 voxels); LIM: limbic (N = 7,641 voxels); SM: sensorimotor (N = 17,311 voxels); VA: ventral attention (N = 11,366 voxels); VIS: visual (N = 17,057 voxels). c The developmental curves of infant rCBF from representative voxels located in four brain networks: sensorimotor as SM-rep (upper-left panel), limbic as LIM-rep (bottom-left panel), fronto-parietal as FPN-rep (upper-right panel) and default-mode as DMN-rep (bottom-right panel). Voxel locations were indicated in (a). Each of the data points (N = 76) in a scatter plot represents rCBF measured with advanced pCASL for each infant. The red central lines indicate the best logarithmic fit of rCBF with the 95% confidence interval of fitted curves indicated by light grey shading. Source data are provided as a Source Data file.