Spatiotemporal cerebral blood flow dynamics underlies emergence of the limbic-sensorimotor-association cortical gradient in human infancy

Abstract

Infant cerebral blood flow (CBF) delivers nutrients and oxygen to fulfill brain energy consumption requirements for the fastest period of postnatal brain development across the lifespan. However, organizing principle of whole-brain CBF dynamics during infancy remains obscure. Leveraging a unique cohort of 100+ infants with high-resolution arterial spin labeled MRI, we found the emergence of the cortical hierarchy revealed by the highest-resolution infant CBF maps available to date. Infant CBF across cortical regions increased in a biphasic pattern with initial rapid and sequentially slower rate, with break-point ages increasing along the limbic-sensorimotor-association cortical gradient. Increases in CBF in sensorimotor cortices were associated with enhanced language and motor skills, and frontoparietal association cortices for cognitive skills. The study discovered emergence of the hierarchical limbic-sensorimotor-association cortical gradient in infancy, and offers standardized reference of infant brain CBF and insight into the physiological basis of cortical specialization and real-world infant developmental functioning.

Keywords: arterial-spin-labeled MRI; behavior; brain development; cerebral blood flow; infant; limbic-sensorimotor-association cortical gradient; neurodevelopmental outcome.

Figure 1.. Developmental curve of global cerebral blood flow (CBF) throughout infancy.

Global CBF increases in a logarithmic manner during infancy (r = 0.823, P < 2×10⁻¹⁶). The red line in the main panel indicates the best linear fit of global CBF = 16.38×log(age)+16.85 (Supplementary Fig. 2 and Supplementary Table 2), and the shaded envelope denotes the 95% confidence interval. Data points represent global CBF measured with phase-contrast MRI of each infant (N = 119). In the bottom-right panel, segmented regression analysis indicates a biphasic pattern of global CBF increase (red line) with a break point at 10.75 months. The fitted bilinear regression line was generated with segmented regression analysis (See Methods section).

Figure 2.. Precise physiological variability at finer detail across infant brain regions.

Population-averaged regional cerebral blood flow (rCBF) maps in template space from infants age groups of 0–3, 3–6, 6–9, 9–12, 12–18 and 18–28 months. High-resolution (2.5×2.5×2.5mm³) rCBF maps were acquired with 3D multi-shot, stack-of-spirals pseudo-continuous arterial spin labeled (pCASL) perfusion MRI. (A) Six representative axial slices of averaged rCBF maps from inferior to superior are shown from the left to right for each age group. (B) Averaged rCBF maps are projected to the 3D reconstructed surface of a template brain and displayed in lateral and medial view of both hemispheres. White, purple and orange arrows indicate relatively higher CBF values in the primary sensorimotor, auditory and visual cortices, respectively, in younger age group.

Figure 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. Images thresholded at z > 5.1 (Bonferroni corrected p < 0.05). (B) Regional CBF increases varied 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. 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; DMN: default-mode network; FPN: fronto-parietal network; LIM: limbic; SM: sensorimotor; VA: ventral attention; VIS: visual. (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). Data points in scatter plots represent rCBF measured with advanced pCASL for each infant. The red lines in the right panels indicate the best linear fit of rCBF, and the shaded envelope denotes the 95% confidence interval.

Figure 4.. Infant rCBF increases according to a hierarchical limbic-sensorimotor-association gradient.

(A) Cortical voxels were clustered into three groups (limbic, sensorimotor, and frontoparietal clusters) identified by non-negative matrix factorization (NMF) according to the pattern of rCBF increase over time. The respective locations of the three clusters on the cortical surface are displayed in lateral and medial views. Segmented regression analysis indicates a biphasic developmental pattern of averaged rCBF in each cluster (red line) overlaid on 200 randomly sampled voxel developmental curves from each cluster (gray thin lines). The identified break-point ages (black dashed lines) from segmented regression analysis varied across clusters and were provided at the bottom of each plot. (B) Histograms showed the profile of break-point age from cortical voxels within each cluster. (C) rCBF increase rate (ml/100g/min/month) across cortical voxels within each cluster. (D) Heterogeneous rCBF increase rate across cortex at milestone ages during infancy. Slower and faster rCBF increase rates are shown in cool and warm colors, respectively.

Figure 5:. Regionally specific rCBF increases are associated with developmental functioning in infants.

Of all cortical regions examined, the regions in red-yellow showed significant positive associations ($P_{\text{corrected}}<0.05$, cluster with k > 100 voxels, t > 2.02) between rCBF in infants and their behavior and developmental functioning quantified with Bayley scales of infant and toddler development across domains of (A) motor, (B) language, and (C) cognitive. The identified three clusters across infant rCBF hierarchy are shown in different colors in panel A-C, with limbic in light yellow, sensorimotor in light green and frontoparietal in pink. Scatter plots show the significant positive correlations between infant’s behavioral scores and the averaged rCBF values from the largest, blue circled clusters (Bonferroni corrected p < 0.05). The bold line indicates the best linear fit, and the shaded envelope denotes the 95% confidence interval. (D) River plot shows spatial distribution of voxels with significant association of each score across the identified rCBF hierarchy. Ribbons are normalized by the total number of voxels with significant associations in each behavioral score, shown in a different color. LIM, limbic; SM, sensorimotor; FP, frontoparietal; L/R, left/right hemisphere; ANG, angular gyrus; CingG, cingulate gyrus; Fu, fusiform gyrus; Hippo: hippocampus; IOG, inferior occipital gyrus; ITG, inferior temporal gyrus; LFOG, lateral fronto-orbital gyrus; LG, lingual gyrus; MFG, middle frontal gyrus; MFOG, medial fronto-orbital gyrus; MOG, middle occipital gyrus; MTG, middle temporal gyrus; PoCG, postcentral gyrus; PrCG, precentral gyrus; SFG, superior frontal gyrus; SOG, superior occipital gyrus; SPG, superior parietal lobule.

Figure 6:. Infant rCBF reorganized by spatiotemporally varying energy demand for brain maturation.

(A) The upper-left panel shows the adult cerebral metabolic rate of glucose (CMRglc) map, acquired from published average maps across 28 healthy adults from Shokri-Kojori et al. (2019). The adult CMRglc map highlights frontal lobe and precuneus as the most metabolically demanding regions. The bottom-left panel shows the rCBF map acquired from a healthy adult using the same scanner and identical pCASL protocol as the infant cohort. Shown in the right panel, adult rCBF significantly correlated with the adult CMRglc (r = 0.594, $P_{perm}<{10}^{-4}$; Pearson correlation with permutation test). (B) Spatial distribution of infant rCBF map is progressively reorganized during development and gradually aligns with the adult CMRglc distribution pattern. Spatial alignment between fitted infant rCBF map from 1 to 28 months (m) and adult CMRglc slowly increases, reaching a plateau at 10m of age. RCBF-CMRglc associations at two representative ages (red circled) of 1.5 and 28 months are also shown. Unlikely the weak association between 1.5m infant rCBF and adult CMRglc maps, the distribution of 28m infant rCBF is highly aligned with the adult metabolic distribution map.