The functions of the resting state networks (RSNs) revealed by functional MRI remain unclear, but it has seemed possible that networks emerge in parallel with the development of related cognitive functions. We tested the alternative hypothesis: that the full repertoire of resting state dynamics emerges during the period of rapid neural growth before the normal time of birth at term (around 40 wk of gestation). We used a series of independent analytical techniques to map in detail the development of different networks in 70 infants born between 29 and 43 wk of postmenstrual age (PMA). We characterized and charted the development of RSNs from recognizable but often fragmentary elements at 30 wk of PMA to full facsimiles of adult patterns at term. Visual, auditory, somatosensory, motor, default mode, frontoparietal, and executive control networks developed at different rates; however, by term, complete networks were present, several of which were integrated with thalamic activity. These results place the emergence of RSNs largely during the period of rapid neural growth in the third trimester of gestation, suggesting that they are formed before the acquisition of cognitive competencies in later childhood.blood oxygen level-dependent | functional MRI | neurodevelopment | intrinsic brain activity | newborn T he detection of spontaneous spatially coherent fluctuations of the blood oxygen level-dependent (BOLD) signal by functional MRI (fMRI) (1) offers potential insights into the largescale organization of neural function at the system levels (comprehensive review presented in 2). These resting state networks (RSNs) replicate the set of functional networks exhibited by the brain over its range of possible tasks (3), encompassing various spatially distinct neural systems, including the medial visual and lateral visual, auditory, somatosensory, motor, cerebellum, executive control, and frontoparietal or dorsal visual stream networks as well as the default mode network (DMN) (2-4). However, although the configurations and consistency of these networks are established, their functions are still not fully understood.Elucidating the ontogeny of RSNs could clarify the role of this large-scale neural organization. Previous studies at the time of normal birth [term, around 40 wk of postmenstrual age (PMA)] have detected RSNs in the primary visual areas, somatosensory and motor cortices, temporal cortex, cerebellum, prefrontal cortex (5, 6), and incomplete DMN (7) but did not find the complete DMN, executive control network, or dorsal visual network. This led to the suggestion that the full architecture emerges during later childhood in parallel with the development of corresponding cognitive functions.Here, we test the alternative hypothesis: that the full adult repertoire of resting state dynamics emerges during the period of rapid neural growth before the normal time of birth at 38-43 postconceptional weeks (term).We used a series of independent analytical techniques to map in detail the development of different networks in ...

Combining diffusion magnetic resonance imaging and network analysis in the adult human brain has identified a set of highly connected cortical hubs that form a "rich club"-a high-cost, highcapacity backbone thought to enable efficient network communication. Rich-club architecture appears to be a persistent feature of the mature mammalian brain, but it is not known when this structure emerges during human development. In this longitudinal study we chart the emergence of structural organization in mid to late gestation. We demonstrate that a rich club of interconnected cortical hubs is already present by 30 wk gestation. Subsequently, until the time of normal birth, the principal development is a proliferation of connections between core hubs and the rest of the brain. We also consider the impact of environmental factors on early network development, and compare term-born neonates to preterm infants at term-equivalent age. Though rich-club organization remains intact following premature birth, we reveal significant disruptions in both in cortical-subcortical connectivity and short-distance corticocortical connections. Rich club organization is present well before the normal time of birth and may provide the fundamental structural architecture for the subsequent emergence of complex neurological functions. Premature exposure to the extrauterine environment is associated with altered network architecture and reduced network capacity, which may in part account for the high prevalence of cognitive problems in preterm infants.connectome | brain development | tractography | preterm birth T o understand the functional properties of a complex network it is necessary to examine its structural organization and topological properties. In the human brain this can be achieved at a macroscale by tracing white matter connections between brain regions with diffusion MRI; this enables the interrogation of structural network topology in vivo with millimeter-scale spatial resolution, providing complementary evidence to experimental studies (1, 2).Network analysis of the adult human structural connectome has revealed a set of highly connected cortical "hubs" predominantly located in heteromodal association cortex, that provide a foundation for coherent neuronal activation across distal cortical regions (3-5). Further, some hub regions tend to be densely connected to each other, forming a "rich club" comprised of frontal and parietal cortex, precuneus, cingulate and the insula, as well as the hippocampus, thalamus, and putamen (6). Rich-club organization has been identified in a number of complex networks (7) and represents an attractive feature for investigation in the brain because rich-club connections tend to dominate network topology (8). Rich-club architecture appears to be a fundamental feature of the mature mammalian brain with similar organization identified in animal models (9, 10).It has been suggested that the emergence of complex neurological function is associated with the integration of major hubs across the cortex (11,...

Preterm birth is a leading cause of cognitive impairment in childhood and is associated with cerebral gray and white matter abnormalities. Using multimodal image analysis, we tested the hypothesis that altered thalamic development is an important component of preterm brain injury and is associated with other macro- and microstructural alterations. T1- and T2-weighted magnetic resonance images and 15-direction diffusion tensor images were acquired from 71 preterm infants at term-equivalent age. Deformation-based morphometry, Tract-Based Spatial Statistics, and tissue segmentation were combined for a nonsubjective whole-brain survey of the effect of prematurity on regional tissue volume and microstructure. Increasing prematurity was related to volume reduction in the thalamus, hippocampus, orbitofrontal lobe, posterior cingulate cortex, and centrum semiovale. After controlling for prematurity, reduced thalamic volume predicted: lower cortical volume; decreased volume in frontal and temporal lobes, including hippocampus, and to a lesser extent, parietal and occipital lobes; and reduced fractional anisotropy in the corticospinal tracts and corpus callosum. In the thalamus, reduced volume was associated with increased diffusivity. This demonstrates a significant effect of prematurity on thalamic development that is related to abnormalities in allied brain structures. This suggests that preterm delivery disrupts specific aspects of cerebral development, such as the thalamocortical system.

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In the rodent brain the hemodynamic response to a brief external stimulus changes significantly during development. Analogous changes in human infants would complicate the determination and use of the hemodynamic response function (HRF) for functional magnetic resonance imaging (fMRI) in developing populations. We aimed to characterize HRF in human infants before and after the normal time of birth using rapid sampling of the Blood Oxygen Level Dependent (BOLD) signal. A somatosensory stimulus and an event related experimental design were used to collect data from 10 healthy adults, 15 sedated infants at term corrected post menstrual age (PMA) (median 41 + 1 weeks), and 10 preterm infants (median PMA 34 + 4 weeks). A positive amplitude HRF waveform was identified across all subject groups, with a systematic maturational trend in terms of decreasing time-to-peak and increasing positive peak amplitude associated with increasing age. Application of the age-appropriate HRF models to fMRI data significantly improved the precision of the fMRI analysis. These findings support the notion of a structured development in the brain's response to stimuli across the last trimester of gestation and beyond.

Thalamocortical connections are: essential for brain function, established early in development, and significantly impaired following preterm birth. Impaired cognitive abilities in preterm infants may be related to disruptions in thalamocortical connectivity. The aim of this study was to test the hypothesis: thalamocortical connectivity in the preterm brain at term-equivalent is correlated with cognitive performance in early childhood. We examined 57 infants who were born <35 weeks gestational age (GA) and had no evidence of focal abnormality on magnetic resonance imaging (MRI). Infants underwent diffusion MRI at term and cognitive performance at 2 years was assessed using the Bayley III scales of Infant and Toddler development. Cognitive scores at 2 years were correlated with structural connectivity between the thalamus and extensive cortical regions at term. Mean thalamocortical connectivity across the whole cortex explained 11% of the variance in cognitive scores at 2 years. The inclusion of GA at birth and parental socioeconomic group in the model explained 30% of the variance in subsequent cognitive performance. Identifying impairments in thalamocortical connectivity as early as term equivalent can help identify those infants at risk of subsequent cognitive delay and may be useful to assess efficacy of potential treatments at an early age.

Detailed morphometric analysis of the neonatal brain is required to characterise brain development and define neuroimaging biomarkers related to impaired brain growth. Accurate automatic segmentation of neonatal brain MRI is a prerequisite to analyse large datasets. We have previously presented an accurate and robust automatic segmentation technique for parcellating the neonatal brain into multiple cortical and subcortical regions. In this study, we further extend our segmentation method to detect cortical sulci and provide a detailed delineation of the cortical ribbon. These detailed segmentations are used to build a 4-dimensional spatio-temporal structural atlas of the brain for 82 cortical and subcortical structures throughout this developmental period. We employ the algorithm to segment an extensive database of 420 MR images of the developing brain, from 27 to 45 weeks post-menstrual age at imaging. Regional volumetric and cortical surface measurements are derived and used to investigate brain growth and development during this critical period and to assess the impact of immaturity at birth. Whole brain volume, the absolute volume of all structures studied, cortical curvature and cortical surface area increased with increasing age at scan. Relative volumes of cortical grey matter, cerebellum and cerebrospinal fluid increased with age at scan, while relative volumes of white matter, ventricles, brainstem and basal ganglia and thalami decreased. Preterm infants at term had smaller whole brain volumes, reduced regional white matter and cortical and subcortical grey matter volumes, and reduced cortical surface area compared with term born controls, while ventricular volume was greater in the preterm group. Increasing prematurity at birth was associated with a reduction in total and regional white matter, cortical and subcortical grey matter volume, an increase in ventricular volume, and reduced cortical surface area.

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