From early childhood to adulthood, synaptogenesis and synaptic pruning reshape the architecture of neuronal connections in developmental human brains. Disturbance of precisely balanced strengthening of certain axons and pruning of others may cause mental disorders such as autism and schizophrenia [1-2]. To characterize this balance, we defined and measured a cortical connectivity maturation index (CCMI) derived from short-range association tracts with diffusion MRI (dMRI) tractoghraphy traced from each parcellated cortical gyrus with T₁-weighted images. The goal is to develop a novel maturational index sensitive to connectivity of specific cortical regions in normal and pathological human brain development. Participants: 21 healthy subjects with age of 2-25 years were included in present study. Acquisition of dMRI and T₁-weighted image: All MR scans were performed on a 3T Philips Achieva MR system. dMRI were acquired using single-shot EPI with SENSE=2.3 and other parameters were: TR/TE=7960/83 ms, FOV=224x224mm², imaging resolution=2x2x2mm³, 65 slices, 30 independent diffusion-weighted directions, b-value=1000 sec/mm². T₁-weighted images were acquired using MPRAGE sequence with imaging resolution=1x1x1mm³, 160 slices. Fiber tracing from a parcellated cortical gyrus: With T₁-weighted image, the brain cortical surface was rendered and parcellated into 68 gyral labels [3] using Freesurfer (http://surfer.nmr.mgh.harvard.edu). Fiber assignment of continuous tractography (FACT) [4] was used to trace the whole brain fibers for all subjects in DiffusionToolkit (http://www.trackvis.org/dtk/) with FA threshold of 0.2 and angular threshold of 50^o. Using inferior parietal gyrus (IPG) as an example, the parcellated cortical ribbon transformed from T₁-weighted image space to dMRI space (Figure 1a) was then dilated by 8 mm (shown in green overlaid on b0 image in Figure 1b) with in-house program to get through the dense white matter (WM) zone for initiating fiber tracking [5]. All association fibers traced from IPG as seed ROI were shown in Figure 1c. Categorization of long- and short-range fibers based on termination location of the other end of fibers: The adjacent and non-adjacent gyral labels of each cortical gyrus were identified. Using IPG (shown in green in the 3D reconstructed brain) as an example (Figure 1d), its adjacent gyri are superior parietal gyrus(yellow), lateral occipital gyrus(red) and supra marginal gyrus(blue) and all other gyri are non-adjacent gyri for IPG. Then association fibers initiated from IPG can be categorized into short- and long-range based on the other end of fibers terminating in adjacent and non-adjacent gyri to IPG, respectively (Figure 1e). Regional CCMI of IPG was calculated as the ratio between number of short-range association fiber and total number of association fibers initiated from IPG. Global and regional CCMI developmental curve analysis: Global CCMI was calculated as the ratio between the total number of short-range association fibers and total number associate fibers from all 68 gyri. To investigate the developmental curve of CCMI, the following equation was used for fitting a quadratic or cubic model between y (global or regional CCMI) and age t, y=β₀+β₁t+β₂t²+β₃t³+ε using R software (https://www.r-project.org/), where β₀, β₁, β₂ and β₃ were parameters to be estimated (β3 is for cubic fitting only) and ε was an error term. The age at which lowest CCMI value of whole-brain and three representative cortical regions: primary somatosensory cortex (S1), visual cortex (V1) and prefrontal cortex were calculated.Figure 2 demonstrates the developmental curve of global and regional CCMI (fitted with quadratic and cubic model with a 95% confidence interval in shadow, respectively). Global CCMI decreases initially from 2 to 16 years of age, and then followed by a rise from 16 to 25 years of age (Figure 2a). In addition, we examined the developmental curve of regional CCMI in three representative functional regions of human brain: S1, V1 and prefrontal cortex (Figure 2b-2d). Similar as global CCMI, the developmental curves of regional CCMI from all three functional regions show initial decrease followed by a later rise. The developmental curves also suggested spatiotemperally heterogeneous CCMI dynamics. Specifically, the ages of minimum CCMI vary across these functional regions. The age of minimum CCMI for prefrontal cortex (~17 years) is later than those for S1 (~9 years) and V1 (~14 years), suggesting later maturation of higher-order functional regions than primary sensorimotor regions.The CCMI is spatiotemporally heterogeneous, decreasing in early childhood and increasing later with minimum CCMI observed at various ages among cortical gyri. The proposed CCMI reflecting the balance between strengthening of certain axons and pruning of others may be used to characterize normal brain development and detect atypical development under pathological conditions. Acquisition and analysis of dMRI data from more subjects are under way.