Minhui Ouyang

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

Abstract 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.

Atypical age-dependent effects of autism on white matter microstructure in children of 2-7 years.

Atypical age‐dependent changes of white matter (WM) microstructure play a central role in abnormal brain maturation of the children with autism spectrum disorder (ASD), but their early manifestations have not been systematically characterized. The entire brain core WM voxels were surveyed to detect differences in WM microstructural development between 31 children with ASD of 2–7 years and 19 age‐matched children with typical development (TD), using measurements of fractional anisotropy (FA) and radial diffusivity (RD) from diffusion tensor imaging (DTI). The anatomical locations, distribution, and extent of the core WM voxels with atypical age‐dependent changes in a specific tract or tract group were delineated and evaluated by integrating the skeletonized WM with a digital atlas. Exclusively, unidirectional FA increases and RD decreases in widespread WM tracts were revealed in children with ASD before 4 years, with bi‐directional changes found for children with ASD of 2–7 years. Compared to progressive development that raised FA and lowered RD during 2–7 years in the TD group, flattened curves of WM maturation were found in multiple major WM tracts of all five tract groups, particularly associational and limbic tracts, in the ASD group with trend lines of ASD and TD crossed around 4 years. We found atypical age‐dependent changes of FA and RD widely and heterogeneously distributed in WM tracts of children with ASD. The early higher WM microstructural integrity before 4 years reflects abnormal neural patterning, connectivity, and pruning that may contribute to aberrant behavioral and cognitive development in ASD. Hum Brain Mapp 37:819–832, 2016.

Human Fetal Brain Connectome: Structural Network Development from Middle Fetal Stage to Birth

Complicated molecular and cellular processes take place in a spatiotemporally heterogeneous and precisely regulated pattern in the human fetal brain, yielding not only dramatic morphological and microstructural changes, but also macroscale connectomic transitions. As the underlying substrate of the fetal brain structural network, both dynamic neuronal migration pathways and rapid developing fetal white matter (WM) fibers could fundamentally reshape early fetal brain connectome. Quantifying structural connectome development can not only shed light on the brain reconfiguration in this critical yet rarely studied developmental period, but also reveal alterations of the connectome under neuropathological conditions. However, transition of the structural connectome from the mid-fetal stage to birth is not yet known. The contribution of different types of neural fibers to the structural network in the mid-fetal brain is not known, either. In this study, diffusion tensor magnetic resonance imaging (DT-MRI or DTI) of 10 fetal brain specimens at the age of 20 postmenstrual weeks (PMW), 12 in vivo brains at 35 PMW, and 12 in vivo brains at term (40 PMW) were acquired. The structural connectome of each brain was established with evenly parcellated cortical regions as network nodes and traced fiber pathways based on DTI tractography as network edges. Two groups of fibers were categorized based on the fiber terminal locations in the cerebral wall in the 20 PMW fetal brains. We found that fetal brain networks become stronger and more efficient during 20–40 PMW. Furthermore, network strength and global efficiency increase more rapidly during 20–35 PMW than during 35–40 PMW. Visualization of the whole brain fiber distribution by the lengths suggested that the network reconfiguration in this developmental period could be associated with a significant increase of major long association WM fibers. In addition, non-WM neural fibers could be a major contributor to the structural network configuration at 20 PMW and small-world network organization could exist as early as 20 PMW. These findings offer a preliminary record of the fetal brain structural connectome maturation from the middle fetal stage to birth and reveal the critical role of non-WM neural fibers in structural network configuration in the middle fetal stage.

Short-range connections in the developmental connectome during typical and atypical brain maturation

HighlightsShort‐range connectivity plays a key role in information transfer in human brain.It contributes to segregation and integration of developmental connectome.Its maturation is spatiotemporally unique and heterogeneous in typical development.Its maturation follows the sequence from primary to higher‐order brain regions.Alterations of short‐range connections are associated with autism and schizophrenia. Abstract The human brain is remarkably complex with connectivity constituting its basic organizing principle. Although long‐range connectivity has been focused on in most research, short‐range connectivity is characterized by unique and spatiotemporally heterogeneous dynamics from infancy to adulthood. Alterations in the maturational dynamics of short‐range connectivity has been associated with neuropsychiatric disorders, such as autism and schizophrenia. Recent advances in neuroimaging techniques, especially diffusion magnetic resonance imaging (dMRI), resting‐state functional MRI (rs‐fMRI), electroencephalography (EEG) and magnetoencephalography (MEG), have made quantification of short‐range connectivity possible in pediatric populations. This review summarizes findings on the development of short‐range functional and structural connections at the macroscale. These findings suggest an inverted U‐shaped pattern of maturation from primary to higher‐order brain regions, and possible “hyper‐” and “hypo‐” short‐range connections in autism and schizophrenia, respectively. The precisely balanced short‐ and long‐range connections contribute to the integration and segregation of the connectome during development. The mechanistic relationship among short‐range connectivity maturation, the developmental connectome and emerging brain functions needs further investigation, including the refinement of methodological approaches.

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

ABSTRACT 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. HIGHLIGHTSCBF increases heterogeneously across cortical regions in preterm brains.Adjusted pCASL MRI could yield reproducible CBF measures of preterm brains.Global CBF doubles its value during the 3rd trimester.Regional CBF measures were correlated with cortical microstructure.

Synchronous Changes of Cortical Thickness and Corresponding White Matter Microstructure During Brain Development Accessed by Diffusion MRI Tractography from Parcellated Cortex.

Cortical thickness (CT) changes during normal brain development is associated with complicated cellular and molecular processes including synaptic pruning and apoptosis. In parallel, the microstructural enhancement of developmental white matter (WM) axons with their neuronal bodies in the cerebral cortex has been widely reported with measurements of metrics derived from diffusion tensor imaging (DTI), especially fractional anisotropy (FA). We hypothesized that the changes of CT and microstructural enhancement of corresponding axons are highly interacted during development. DTI and T1-weighted images of 50 healthy children and adolescents between the ages of 7 and 25 years were acquired. With the parcellated cortical gyri transformed from T1-weighted images to DTI space as the tractography seeds, probabilistic tracking was performed to delineate the WM fibers traced from specific parcellated cortical regions. CT was measured at certain cortical regions and FA was measured from the WM fibers traced from same cortical regions. The CT of all frontal cortical gyri, including Brodmann areas 4, 6, 8, 9, 10, 11, 44, 45, 46, and 47, decreased significantly and heterogeneously; concurrently, significant, and heterogeneous increases of FA of WM traced from corresponding regions were found. We further revealed significant correlation between the slopes of the CT decrease and the slopes of corresponding WM FA increase in all frontal cortical gyri, suggesting coherent cortical pruning and corresponding WM microstructural enhancement. Such correlation was not found in cortical regions other than frontal cortex. The molecular and cellular mechanisms of these synchronous changes may be associated with overlapping signaling pathways of axonal guidance, synaptic pruning, neuronal apoptosis, and more prevalent interstitial neurons in the prefrontal cortex. Revealing the coherence of cortical and WM structural changes during development may open a new window for understanding the underlying mechanisms of developing brain circuits and structural abnormality associated with mental disorders.

Delineation of early brain development from fetuses to infants with diffusion MRI and beyond

&NA; Dynamic macrostructural and microstructural changes take place from the mid‐fetal stage to 2 years after birth. Delineating structural changes of the brain during early development provides new insights into the complicated processes of both typical development and the pathological mechanisms underlying various psychiatric and neurological disorders including autism, attention deficit hyperactivity disorder and schizophrenia. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The recent improvements in magnetic resonance imaging (MRI) techniques, especially diffusion MRI (dMRI), relaxometry imaging, and magnetization transfer imaging (MTI) have provided unprecedented opportunities to non‐invasively quantify and map the early developmental changes at whole brain and regional levels. Here, we review the recent advances in understanding early brain structural development during the second half of gestation and the first two postnatal years using modern MR techniques. Specifically, we review studies that delineate the emergence and microstructural maturation of white matter tracts, as well as dynamic mapping of inhomogeneous cortical microstructural organization unique to fetuses and infants. These imaging studies converge into maturational curves of MRI measurements that are distinctive across different white matter tracts and cortical regions. Furthermore, contemporary models offering biophysical interpretations of the dMRI‐derived measurements are illustrated to infer the underlying microstructural changes. Collectively, this review summarizes findings that contribute to charting spatiotemporally heterogeneous gray and white matter structural development, offering MRI‐based biomarkers of typical brain development and setting the stage for understanding aberrant brain development in neurodevelopmental disorders. HighlightsDramatic microstructural changes take place in developing fetal and infant brain.Diffusion and other MRI modalities effectively quantify these developmental changes.Emergence of different white matter tracts were delineated with dMRI tractography.Cerebral cortical microstructural changes were quantified with dMRI metrics.4D spatiotemporal patterns of brain structural development were delineated.

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

&NA; 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. HighlightsDramatic structural changes during 3rd trimester require setup of age‐specific atlas.Age‐specific DTI templates were established with 84 preterm and term‐born datasets.Age‐specific DTI atlases at 33, 36 and 39 postmenstrual weeks were established.Each age‐specific DTI atlas includes 126 comprehensive gray and white matter labels.The atlases can be used to measure the tract‐based microstructures automatically.

Calibrated imaging reveals altered grey matter metabolism related to white matter microstructure and symptom severity in multiple sclerosis

Multiple sclerosis (MS) involves damage to white matter microstructures. This damage has been related to grey matter function as measured by standard, physiologically‐nonspecific neuroimaging indices (i.e., blood‐oxygen‐level dependent signal [BOLD]). Here, we used calibrated functional magnetic resonance imaging and diffusion tensor imaging to examine the extent to which specific, evoked grey matter physiological processes were associated with white matter diffusion in MS. Evoked changes in BOLD, cerebral blood flow (CBF), and oxygen metabolism (CMRO2) were measured in visual cortex. Individual differences in the diffusion tensor measure, radial diffusivity, within occipital tracts were strongly associated with MS patients’ BOLD and CMRO2. However, these relationships were in opposite directions, complicating the interpretation of the relationship between BOLD and white matter microstructural damage in MS. CMRO2 was strongly associated with individual differences in patients’ fatigue and neurological disability, suggesting that alterations to evoked oxygen metabolic processes may be taken as a marker for primary symptoms of MS. This work demonstrates the first application of calibrated and diffusion imaging together and details the first application of calibrated functional MRI in a neurological population. Results lend support for neuroenergetic hypotheses of MS pathophysiology and provide an initial demonstration of the utility of evoked oxygen metabolism signals for neurology research. Hum Brain Mapp 38:5375–5390, 2017.

Evaluation of Visual-Evoked Cerebral Metabolic Rate of Oxygen as a Diagnostic Marker in Multiple Sclerosis

A multiple sclerosis (MS) diagnosis often relies upon clinical presentation and qualitative analysis of standard, magnetic resonance brain images. However, the accuracy of MS diagnoses can be improved by utilizing advanced brain imaging methods. We assessed the accuracy of a new neuroimaging marker, visual-evoked cerebral metabolic rate of oxygen (veCMRO2), in classifying MS patients and closely age- and sex-matched healthy control (HC) participants. MS patients and HCs underwent calibrated functional magnetic resonance imaging (cfMRI) during a visual stimulation task, diffusion tensor imaging, T1- and T2-weighted imaging, neuropsychological testing, and completed self-report questionnaires. Using resampling techniques to avoid bias and increase the generalizability of the results, we assessed the accuracy of veCMRO2 in classifying MS patients and HCs. veCMRO2 classification accuracy was also examined in the context of other evoked visuofunctional measures, white matter microstructural integrity, lesion-based measures from T2-weighted imaging, atrophy measures from T1-weighted imaging, neuropsychological tests, and self-report assays of clinical symptomology. veCMRO2 was significant and within the top 16% of measures (43 total) in classifying MS status using both within-sample (82% accuracy) and out-of-sample (77% accuracy) observations. High accuracy of veCMRO2 in classifying MS demonstrated an encouraging first step toward establishing veCMRO2 as a neurodiagnostic marker of MS.