Development of neonatal connectome dynamics and its prediction for cognitive and language outcomes at age 2.

The functional brain connectome is highly dynamic over time. However, how brain connectome dynamics evolves during the third trimester of pregnancy and is associated with later cognitive growth remains unknown. Here, we use resting-state functional Magnetic Resonance Imaging (MRI) data from 39 newborns aged 32 to 42 postmenstrual weeks to investigate the maturation process of connectome dynamics and its role in predicting neurocognitive outcomes at 2 years of age. Neonatal brain dynamics is assessed using a multilayer network model. Network dynamics decreases globally but increases in both modularity and diversity with development. Regionally, module switching decreases with development primarily in the lateral precentral gyrus, medial temporal lobe, and subcortical areas, with a higher growth rate in primary regions than in association regions. Support vector regression reveals that neonatal connectome dynamics is predictive of individual cognitive and language abilities at 2  years of age. Our findings highlight network-level neural substrates underlying early cognitive development.

Differential cortical microstructural maturation in the preterm human brain with diffusion kurtosis and tensor imaging.

During the third trimester, the human brain undergoes rapid cellular and molecular processes that reshape the structural architecture of the cerebral cortex. Knowledge of cortical differentiation obtained predominantly from histological studies is limited in localized and small cortical regions. How cortical microstructure is differentiated across cortical regions in this critical period is unknown. In this study, the cortical microstructural architecture across the entire cortex was delineated with non-Gaussian diffusion kurtosis imaging as well as conventional diffusion tensor imaging of 89 preterm neonates aged 31-42 postmenstrual weeks. The temporal changes of cortical mean kurtosis (MK) or fractional anisotropy (FA) were heterogeneous across the cortical regions. Cortical MK decreases were observed throughout the studied age period, while cortical FA decrease reached its plateau around 37 weeks. More rapid decreases in MK were found in the primary visual region, while faster FA declines were observed in the prefrontal cortex. We found that distinctive cortical microstructural changes were coupled with microstructural maturation of associated white matter tracts. Both cortical MK and FA measurements predicted the postmenstrual age of preterm infants accurately. This study revealed a differential 4D spatiotemporal cytoarchitectural signature inferred by non-Gaussian diffusion barriers inside the cortical plate during the third trimester. The cytoarchitectural processes, including dendritic arborization and neuronal density decreases, were inferred by regional cortical FA and MK measurements. The presented findings suggest that cortical MK and FA measurements could be used as effective imaging markers for cortical microstructural changes in typical and potentially atypical brain development.

Development and Emergence of Individual Variability in the Functional Connectivity Architecture of the Preterm Human Brain.

Individual variability in human brain networks underlies individual differences in cognition and behaviors. However, researchers have not conclusively determined when individual variability patterns of the brain networks emerge and how they develop in the early phase. Here, we employed resting-state functional MRI data and whole-brain functional connectivity analyses in 40 neonates aged around 31-42 postmenstrual weeks to characterize the spatial distribution and development modes of individual variability in the functional network architecture. We observed lower individual variability in primary sensorimotor and visual areas and higher variability in association regions at the third trimester, and these patterns are generally similar to those of adult brains. Different functional systems showed dramatic differences in the development of individual variability, with significant decreases in the sensorimotor network; decreasing trends in the visual, subcortical, and dorsal and ventral attention networks, and limited change in the default mode, frontoparietal and limbic networks. The patterns of individual variability were negatively correlated with the short- to middle-range connection strength/number and this distance constraint was significantly strengthened throughout development. Our findings highlight the development and emergence of individual variability in the functional architecture of the prenatal brain, which may lay network foundations for individual behavioral differences later in life.

Structural network maturation of the preterm human brain.

During the 3rd trimester, large-scale neural circuits are formed in the human brain, resulting in a highly efficient and segregated connectome at birth. Despite recent findings identifying important preterm human brain network properties such as rich-club organization, how the structural network develops differentially across brain regions and among different types of connections in this period is not yet known. Here, using high resolution diffusion MRI of 77 preterm-born and full-term neonates scanned at 31.9-41.7 postmenstrual weeks (PMW), we constructed structural connectivity matrices and performed graph-theory-based analyses. Faster increases of nodal efficiency were mainly located at the brain hubs distributed in primary sensorimotor regions, superior-middle frontal, and precuneus regions during 31.9-41.7PMW. Higher rates of edge strength increases were found in the rich-club and within-module connections, compared to other connections. The edge strength of short-range connections increased faster than that of long-range connections. Nodal efficiencies of the hubs predicted individual postmenstrual ages more accurately than those of non-hubs. Collectively, these findings revealed more rapid efficiency increases of the hub and rich-club connections as well as higher developmental rates of edge strength in short-range and within-module connections. These jointly underlie network segregation and differentiated emergence of brain functions.

Age-specific gray and white matter DTI atlas for human brain at 33, 36 and 39 postmenstrual weeks.

During the 3rd trimester, dramatic structural changes take place in the human brain, underlying the neural circuit formation. The survival rate of premature infants has increased significantly in recent years. The large morphological differences of the preterm brain at 33 or 36 postmenstrual weeks (PMW) from the brain at 40PMW (full term) make it necessary to establish age-specific atlases for preterm brains. In this study, with high quality (1.5 × 1.5 × 1.6 mm3 imaging resolution) diffusion tensor imaging (DTI) data obtained from 84 healthy preterm and term-born neonates, we established age-specific preterm and term-born brain templates and atlases at 33, 36 and 39PMW. Age-specific DTI templates include a single-subject template, a population-averaged template with linear transformation and a population-averaged template with nonlinear transformation. Each of the age-specific DTI atlases includes comprehensive labeling of 126 major gray matter (GM) and white matter (WM) structures, specifically 52 cerebral cortical structures, 40 cerebral WM structures, 22 brainstem and cerebellar structures and 12 subcortical GM structures. From 33 to 39 PMW, dramatic morphological changes of delineated individual neural structures such as ganglionic eminence and uncinate fasciculus were revealed. The evaluation based on measurements of Dice ratio and L1 error suggested reliable and reproducible automated labels from the age-matched atlases compared to labels from manual delineation. Applying these atlases to automatically and effectively delineate microstructural changes of major WM tracts during the 3rd trimester was demonstrated. The established age-specific DTI templates and atlases of 33, 36 and 39 PMW brains may be used for not only understanding normal functional and structural maturational processes but also detecting biomarkers of neural disorders in the preterm brains.

Peripheral nerve diffusion tensor imaging: Overview, pitfalls, and future directions.

Diffusion tensor imaging (DTI) is a noninvasive magnetic resonance imaging (MRI) technique that measures the extent of restricted water diffusion and anisotropy in biological tissue. Although DTI has been widely applied in the brain, more recently researchers have used it to characterize nerve pathology in the setting of entrapment neuropathy, traumatic injury, and tumor. DTI artifacts are exacerbated when imaging off isocenter in the body. Anecdotally, the most significant artifacts in peripheral nerve DTI include magnetic field inhomogeneity, motion, incomplete fat suppression, aliasing, and distortion. High spatial resolution is also required to reliably evaluate smaller peripheral nerves. This article provides an overview of such technical issues, particularly when trying to apply DTI in the clinical setting, and offers potential solutions. LEVEL OF EVIDENCE: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1171-1189.

Early Development of Functional Network Segregation Revealed by Connectomic Analysis of the Preterm Human Brain.

Human brain functional networks are topologically organized with nontrivial connectivity characteristics such as small-worldness and densely linked hubs to support highly segregated and integrated information processing. However, how they emerge and change at very early developmental phases remains poorly understood. Here, we used resting-state functional MRI and voxel-based graph theory analysis to systematically investigate the topological organization of whole-brain networks in 40 infants aged around 31 to 42 postmenstrual weeks. The functional connectivity strength and heterogeneity increased significantly in primary motor, somatosensory, visual, and auditory regions, but much less in high-order default-mode and executive-control regions. The hub and rich-club structures in primary regions were already present at around 31 postmenstrual weeks and exhibited remarkable expansions with age, accompanied by increased local clustering and shortest path length, indicating a transition from a relatively random to a more organized configuration. Moreover, multivariate pattern analysis using support vector regression revealed that individual brain maturity of preterm babies could be predicted by the network connectivity patterns. Collectively, we highlighted a gradually enhanced functional network segregation manner in the third trimester, which is primarily driven by the rapid increases of functional connectivity of the primary regions, providing crucial insights into the topological development patterns prior to birth.

Heterogeneous increases of regional cerebral blood flow during preterm brain development: Preliminary assessment with pseudo-continuous arterial spin labeled perfusion MRI.

The human brain develops rapidly during 32-45 postmenstrual weeks (PMW), a critical stage characterized by dramatic increases of metabolic demand. The increasing metabolic demand can be inferred through measurements of regional cerebral blood flow (CBF), which might be coupled to regional metabolism in preterm brains. Arterial spin labeled (ASL) perfusion MRI is one of the few viable approaches for imaging regional CBF of preterm brains, but must be optimized for the extremely slow blood velocity unique in preterm brains. In this study, we explored the spatiotemporal CBF distribution in newborns scanned at the age of 32-45PMW using a pseudo-continuous ASL (pCASL) protocol adapted to slow blood flow in neonates. A total of 89 neonates were recruited. PCASL MRI was acquired from 34 normal newborns and phase contrast (PC) images from 19 newborns. Diffusion tensor images (DTI) were acquired from all 89 neonates for measuring cortical fractional anisotropy (FA), which characterizes cortical microstructure. Reproducible CBF measurements were obtained with the adjusted pCASL sequence. Global CBF measurement based on PC MRI was found to double its value in the 3rd trimester. Regional CBF increases were heterogeneous across the brain with a significantly higher rate of CBF increase in the frontal lobe and a lower rate of CBF increase in the occipital lobe. A significant correlation was found between frontal cortical CBF and cortical FA measurements (p<0.01). Increasing CBF values observed in the frontal lobe corresponded to lower FA values, suggesting that dendritic arborization and synaptic formation might be associated with an elevated local CBF. These results offer a preliminary account of heterogeneous regional CBF increases in a vital early developmental period and may shed the light on underlying metabolic support for cortical microstructural changes during the developmental period of 32-45PMW. Preterm effects and limitations of pCASL techniques in newborns need to be carefully considered for interpretation these results.

Structural Development of Human Fetal and Preterm Brain Cortical Plate Based on Population-Averaged Templates.

We hypothesized that the distinct maturational processes take place across different cortical areas from middle fetal stage to normal time of birth and these maturational processes are altered in late third trimester. Fractional anisotropies (FA) from diffusion tensor imaging (DTI) infer the microstructures of the early developing cortical plate. High-resolution DTI of 11 fetal brain specimens at postmenstrual age of 20 weeks (or simplified as 20 weeks), 19 in vivo brains at 35 weeks, and 17 in vivo brains at normal time of birth at term (40 weeks) were acquired. Population-averaged age-specific DTI templates were established with large deformation diffeomorphic metric mapping for subject groups at 20, 35, and 40 weeks. To alleviate partial volume effects, skeletonized FA values were used for mapping averaged cortical FA to the cortical surface and measuring FA at 12 functionally distinctive cortical regions. Significant and heterogeneous FA decreases take place in distinct cortical areas from 20 to 35 weeks and from 35 to 40 weeks, suggesting differentiated cortical development patterns. Temporally nonuniform FA decrease patterns during 35-40 weeks compared with those during 20-35 weeks were observed in higher-order association cortex. Measured skeletonized FA suggested dissociated changes between cerebral cortex and white matter during 35-40 weeks.

Spatial mapping of structural and connectional imaging data for the developing human brain with diffusion tensor imaging.

During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain.

Development of human brain structural networks through infancy and childhood.

During human brain development through infancy and childhood, microstructural and macrostructural changes take place to reshape the brain's structural networks and better adapt them to sophisticated functional and cognitive requirements. However, structural topological configuration of the human brain during this specific development period is not well understood. In this study, diffusion magnetic resonance image (dMRI) of 25 neonates, 13 toddlers, and 25 preadolescents were acquired to characterize network dynamics at these 3 landmark cross-sectional ages during early childhood. dMRI tractography was used to construct human brain structural networks, and the underlying topological properties were quantified by graph-theory approaches. Modular organization and small-world attributes are evident at birth with several important topological metrics increasing monotonically during development. Most significant increases of regional nodes occur in the posterior cingulate cortex, which plays a pivotal role in the functional default mode network. Positive correlations exist between nodal efficiencies and fractional anisotropy of the white matter traced from these nodes, while correlation slopes vary among the brain regions. These results reveal substantial topological reorganization of human brain structural networks through infancy and childhood, which is likely to be the outcome of both heterogeneous strengthening of the major white matter tracts and pruning of other axonal fibers.

Quantitative assessment of global cerebral metabolic rate of oxygen (CMRO2) in neonates using MRI.

The cerebral metabolic rate of oxygen (CMRO2) is the rate of oxygen consumption by the brain, and is thought to be a direct index of energy homeostasis and brain health. However, in vivo measurement of CMRO2 is challenging, in particular for the neonatal population, in whom conventional radiotracer methods are not applicable because of safety concerns. In this study, we propose a method to quantify global CMRO2 in neonates based on arteriovenous differences in oxygen content, and employ separate measurements of oxygenation and cerebral blood flow (CBF) parameters. Specifically, arterial and venous oxygenation levels were determined with pulse oximetry and the novel T2 relaxation under spin tagging (TRUST) MRI, respectively. Global CBF was measured with phase contrast (PC) flow velocity MRI. The proposed method was implemented on a standard 3-T MRI scanner without the need for any exogenous tracers, and the total scan duration was less than 5 min. We demonstrated the feasibility of this method in 12 healthy neonates within an age range of 35-42 gestational weeks. CMRO2 values were successfully obtained from 10 neonates. It was found that the average CMRO2 in this age range was 38.3 ± 17.7 µmol/100 g/min and was positively correlated with age (p = 0.007; slope, 5.2 µmol/100 g/min per week), although the highest CMRO2 value in this age range was still less than half of the adult level. Test-retest studies showed a coefficient of variation of 5.8 ± 2.2% between repeated CMRO2 measurements. In addition, given the highly variable blood flow velocity within this age range, it is recommended that the TRUST labeling thickness and position should be determined on a subject-by-subject basis, and an automatic algorithm was developed for this purpose. Although this method provides a global CMRO2 measure only, the clinical significance of an energy consumption marker and the convenience of this technique may make it a useful tool in the functional assessment of the neonatal population.

Coupling diffusion imaging with histological and gene expression analysis to examine the dynamics of cortical areas across the fetal period of human brain development.

As a prominent component of the human fetal brain, the structure of the cerebral wall is characterized by its laminar organization which includes the radial glial scaffold during fetal development. Diffusion tensor imaging (DTI) is useful to quantitatively delineate the microstructure of the developing brain and to clearly identify transient fetal layers in the cerebral wall. In our study, the spatio-temporal microstructural changes in the developing human fetal cerebral wall were quantitatively characterized with high-resolution DTI data of postmortem fetal brains from 13 to 21 gestational weeks. Eleven regions of interest for each layer in the entire cerebral wall were included. Distinctive time courses of microstructural changes were revealed for 11 regions of the neocortical plate. A histological analysis was also integrated to elucidate the relationship between DTI fractional anisotropy (FA) and histology. High FA values correlated with organized radial architecture in histological image. Expression levels of 17565 genes were quantified for each of 11 regions of human fetal neocortex from 13 to 21 gestational weeks to identify transcripts showing significant correlation with FA change. These correlations suggest that the heterogeneous and regionally specific microstructural changes of the human neocortex are related to different gene expression patterns.

Development of sensorimotor-visual connectome gradient at birth predicts neurocognitive outcomes at 2 years of age.

Functional connectome gradients represent fundamental organizing principles of the brain. Here, we report the development of the connectome gradients in preterm and term babies aged 31-42 postmenstrual weeks using task-free functional MRI and its association with postnatal cognitive growth. We show that the principal sensorimotor-to-visual gradient is present during the late preterm period and continuously evolves toward a term-like pattern. The global measurements of this gradient, characterized by explanation ratio, gradient range, and gradient variation, increased with age (p < 0.05, corrected). Focal gradient development mainly occurs in the sensorimotor, lateral, and medial parietal regions, and visual regions (p < 0.05, corrected). The connectome gradient at birth predicts cognitive and language outcomes at 2-year follow-up (p < 0.005). These results are replicated using an independent dataset from the Developing Human Connectome Project. Our findings highlight early emergent rules of the brain connectome gradient and their implications for later cognitive growth.

Regional changes of cortical mean diffusivities with aging after correction of partial volume effects.

Accurately measuring the cortical mean diffusivity (MD) derived from diffusion tensor imaging (DTI) at the comprehensive lobe, gyral and voxel level of young, elderly healthy brains and those with Alzheimer's disease (AD) may provide insights on heterogeneous cortical microstructural changes caused by aging and AD. Due to partial volume effects (PVE), the measurement of cortical MD is overestimated with contamination of cerebrospinal fluid (CSF). The bias is especially severe for aging and AD brains because of significant cortical thinning of these brains. In this study, we aimed to quantitatively characterize the unbiased regional cortical MD changes due to aging and AD and delineate the effects of cortical thinning of elderly healthy and AD groups on MD measurements. DTI and T1-weighted images of 14 young, 15 elderly healthy subjects and 17 AD patients were acquired. With the parcellated cortical gyri and lobes from T1 weighted image transformed to DTI, regional cortical MD of all subjects before and after PVE correction were measured. CSF contamination model was used to correct bias of MD caused by PVE. Compared to cortical MD of young group, significant increases of corrected MD for elderly healthy and AD groups were found only in frontal and limbic regions, respectively, while there were significant increases of uncorrected MD all over the cortex. Uncorrected MD are significantly higher in limbic and temporal gyri in AD group, compared to those in elderly healthy group but higher MD only remained in limbic gyri after PVE correction. Cortical thickness was also measured for all groups. The correlation slopes between cortical MD and thickness for elderly healthy and AD groups were significantly decreased after PVE correction compared to before correction while no significant change of correlation slope was detected for young group. It suggests that the cortical thinning in elderly healthy and AD groups is a significant contributor to the bias of uncorrected cortical MD measurement. The established comprehensive unbiased cortical MD profiles of young, elderly healthy subjects and AD patients at the lobe, gyral and voxel level may serve as clinical references for cortical microstructure.

Fractal dimension analysis of the cortical ribbon in mild Alzheimer's disease.

Fractal analysis methods are used to quantify the complexity of the human cerebral cortex. Many recent studies have focused on high resolution three-dimensional reconstructions of either the outer (pial) surface of the brain or the junction between the gray and white matter, but ignore the structure between these surfaces. This study uses a new method to incorporate the entire cortical thickness. Data were obtained from the Alzheimer's Disease (AD) Neuroimaging Initiative database (Control N=35, Mild AD N=35). Image segmentation was performed using a semi-automated analysis program. The fractal dimension of three cortical models (the pial surface, gray/white surface and entire cortical ribbon) were calculated using a custom cube-counting triangle-intersection algorithm. The fractal dimension of the cortical ribbon showed highly significant differences between control and AD subjects (p<0.001). The inner surface analysis also found smaller but significant differences (p<0.05). The pial surface dimensionality was not significantly different between the two groups. All three models had a significant positive correlation with the cortical gyrification index (r>0.55, p<0.001). Only the cortical ribbon had a significant correlation with cortical thickness (r=0.832, p<0.001) and the Alzheimer's Disease Assessment Scale cognitive battery (r=-0.513, p=0.002). The cortical ribbon dimensionality showed a larger effect size (d=1.12) in separating control and mild AD subjects than cortical thickness (d=1.01) or gyrification index (d=0.84). The methodological change shown in this paper may allow for further clinical application of cortical fractal dimension as a biomarker for structural changes that accrue with neurodegenerative diseases.

Diffusion-MRI-based regional cortical microstructure at birth for predicting neurodevelopmental outcomes of 2-year-olds.

Cerebral cortical architecture at birth encodes regionally differential dendritic arborization and synaptic formation. It underlies behavioral emergence of 2-year-olds. Brain changes in 0-2 years are most dynamic across the lifespan. Effective prediction of future behavior with brain microstructure at birth will reveal structural basis of behavioral emergence in typical development and identify biomarkers for early detection and tailored intervention in atypical development. Here we aimed to evaluate the neonate whole-brain cortical microstructure quantified by diffusion MRI for predicting future behavior. We found that individual cognitive and language functions assessed at the age of 2 years were robustly predicted by neonate cortical microstructure using support vector regression. Remarkably, cortical regions contributing heavily to the prediction models exhibited distinctive functional selectivity for cognition and language. These findings highlight regional cortical microstructure at birth as a potential sensitive biomarker in predicting future neurodevelopmental outcomes and identifying individual risks of brain disorders.

Evaluation of two collagen conduits and autograft in rabbit sciatic nerve regeneration with quantitative magnetic resonance DTI, electrophysiology, and histology.

BACKGROUND: We compared different surgical techniques for nerve regeneration in a rabbit sciatic nerve gap model using magnetic resonance diffusion tensor imaging (DTI), electrophysiology, limb function, and histology. METHODS: A total of 24 male New Zealand white rabbits were randomized into three groups: autograft (n = 8), hollow conduit (n = 8), and collagen-filled conduit (n = 8). A 10-mm segment of the rabbit proximal sciatic nerve was cut, and autograft or collagen conduit was used to bridge the gap. DTI on a 3-T system was performed preoperatively and 13 weeks after surgery using the contralateral, nonoperated nerve as a control. RESULTS: Overall, autograft performed better compared with both conduit groups. Differences in axonal diameter were significant (autograft > hollow conduit > collagen-filled conduit) at 13 weeks (autograft vs. hollow conduit, p = 0.001, and hollow conduit vs. collagen-filled conduit, p < 0.001). Significant group differences were found for axial diffusivity but not for any of the other DTI metrics (autograft > hollow conduit > collagen-filled conduit) (autograft vs. hollow conduit, p = 0.001 and hollow conduit vs. collagen-filled conduit, p = 0.021). As compared with hollow conduit (autograft > collagen-filled conduit > hollow conduit), collagen-filled conduit animals demonstrated a nonsignificant increased maximum tetanic force. CONCLUSIONS: Autograft-treated rabbits demonstrated improved sciatic nerve regeneration compared with collagen-filled and hollow conduits as assessed by histologic, functional, and DTI parameters at 13 weeks.

Population-averaged macaque brain atlas with high-resolution ex vivo DTI integrated into in vivo space.

Animal models of the rhesus macaque (Macaca mulatta), the most widely used nonhuman primate, have been irreplaceable in neurobiological studies. However, a population-averaged macaque brain diffusion tensor imaging (DTI) atlas, including comprehensive gray and white matter labeling as well as bony and facial landmarks guiding invasive experimental procedures, is not available. The macaque white matter tract pathways and microstructures have been rarely recorded. Here, we established a population-averaged macaque brain atlas with high-resolution ex vivo DTI integrated into in vivo space incorporating bony and facial landmarks, and delineated microstructures and three-dimensional pathways of major white matter tracts in vivo MRI/DTI and ex vivo (postmortem) DTI of ten rhesus macaque brains were acquired. Single-subject macaque brain DTI template was obtained by transforming the postmortem high-resolution DTI data into in vivo space. Ex vivo DTI of ten macaque brains was then averaged in the in vivo single-subject template space to generate population-averaged macaque brain DTI atlas. The white matter tracts were traced with DTI-based tractography. One hundred and eighteen neural structures including all cortical gyri, white matter tracts and subcortical nuclei, were labeled manually on population-averaged DTI-derived maps. The in vivo microstructural metrics of fractional anisotropy, axial, radial and mean diffusivity of the traced white matter tracts were measured. Population-averaged digital atlas integrated into in vivo space can be used to label the experimental macaque brain automatically. Bony and facial landmarks will be available for guiding invasive procedures. The DTI metric measurements offer unique insights into heterogeneous microstructural profiles of different white matter tracts.

Global and regional cortical connectivity maturation index (CCMI) of developmental human brain with quantification of short-range association tracts.

From early childhood to adulthood, synaptogenesis and synaptic pruning continuously reshape the structural architecture and neural connection in developmental human brains. Disturbance of the precisely balanced strengthening of certain axons and pruning of others may cause mental disorders such as autism and schizophrenia. To characterize this balance, we proposed a novel measurement based on cortical parcellation and diffusion MRI (dMRI) tractography, a cortical connectivity maturation index (CCMI). To evaluate the spatiotemporal sensitivity of CCMI as a potential biomarker, dMRI and T1 weighted datasets of 21 healthy subjects 2-25 years were acquired. Brain cortex was parcellated into 68 gyral labels using T1 weighted images, then transformed into dMRI space to serve as the seed region of interest for dMRI-based tractography. Cortico-cortical association fibers initiated from each gyrus were categorized into long- and short-range ones, based on the other end of fiber terminating in non-adjacent or adjacent gyri of the seed gyrus, respectively. The regional CCMI was defined as the ratio between number of short-range association tracts and that of all association tracts traced from one of 68 parcellated gyri. The developmental trajectory of the whole brain CCMI follows a quadratic model with initial decreases from 2 to 16 years followed by later increases after 16 years. Regional CCMI is heterogeneous among different cortical gyri with CCMI dropping to the lowest value earlier in primary somatosensory cortex and visual cortex while later in the prefrontal cortex. The proposed CCMI may serve as sensitive biomarker for brain development under normal or pathological conditions.