Whole-brain mapping of structural connectivity in infants reveals altered connection strength associated with growth and preterm birth

Comparative evaluation of interpretation methods in surface-based age prediction for neonates

Significant changes in brain morphology occur during the third trimester of gestation. The capability of deep learning in leveraging these morphological features has enhanced the accuracy of brain age predictions for this critical period. Yet, the opaque nature of deep learning techniques, often described as "black box" approaches, limits their interpretability, posing challenges in clinical applications. Traditional interpretable methods developed for computer vision and natural language processing may not directly translate to the distinct demands of neuroimaging. In response, our research evaluates the effectiveness and adaptability of two interpretative methods-regional age prediction and the perturbation-based saliency map approach-for predicting the brain age of neonates. Analyzing 664 T1 MRI scans with the NEOCIVET pipeline to extract brain surface and cortical features, we assess how these methods illuminate key brain regions for age prediction, focusing on technical analysis with clinical insight. Through a comparative analysis of the saliency index (SI) with relative brain age (RBA) and the examination of structural covariance networks, we uncover the saliency index's enhanced ability to pinpoint regions vital for accurate indication of clinical factors. Our results highlight the advantages of perturbation techniques in addressing the complexities of medical data, steering clinical interventions for premature neonates towards more personalized and interpretable approaches. This study not only reveals the promise of these methods in complex medical scenarios but also offers a blueprint for implementing more interpretable and clinically relevant deep learning models in healthcare settings.

The effect of preterm birth on thalamic development based on shape and structural covariance analysis

Acting as a central hub in regulating brain functions, the thalamus plays a pivotal role in controlling high-order brain functions. Considering the impact of preterm birth on infant brain development, traditional studies focused on the overall development of thalamus other than its subregions. In this study, we compared the volumetric growth and shape development of the thalamic hemispheres between the infants born preterm and full-term (Left volume: P = 0.027, Left normalized volume: P < 0.0001; Right volume: P = 0.070, Right normalized volume: P < 0.0001). The ventral nucleus region, dorsomedial nucleus region, and posterior nucleus region of the thalamus exhibit higher vulnerability to alterations induced by preterm birth. The structural covariance (SC) between the thickness of thalamus and insula in preterm infants (Left: corrected P = 0.0091, Right: corrected P = 0.0119) showed significant increase as compared to full-term controls. Current findings suggest that preterm birth affects the development of the thalamus and has differential effects on its subregions. The ventral nucleus region, dorsomedial nucleus region, and posterior nucleus region of the thalamus are more susceptible to the impacts of preterm birth.

Associations of behavioral problems with white matter circuits connecting to the frontal lobes in school-aged children born at term and preterm

Introduction

This study investigated whether internalizing and externalizing behavioral problems in children were associated with fractional anisotropy of white matter tracts connecting other brain regions to the frontal lobes. We contrasted patterns of association between children born at term (FT) and very preterm (PT: gestational age at birth =< 32 weeks).

Methods

Parents completed the Child Behavior Checklist/6-18 questionnaire to quantify behavioral problems when their children were age 8 years (N = 36 FT and 37 PT). Diffusion magnetic resonance scans were collected at the same age and analyzed using probabilistic tractography. Multiple linear regressions investigated the strength of association between age-adjusted T-scores of internalizing and externalizing problems and mean fractional anisotropy (mean-FA) of right and left uncinate, arcuate, anterior thalamic radiations, and dorsal cingulate bundle, controlling for birth group and sex.

Results

Models predicting internalizing T-scores found significant group-by-tract interactions for left and right arcuate and right uncinate. Internalizing scores were negatively associated with mean-FA of left and right arcuate only in FT children (p left AF = 0.01, p right AF = 0.01). Models predicting externalizing T-scores found significant group-by-tract interactions for the left arcuate and right uncinate. Externalizing scores were negatively associated with mean-FA of right uncinate in FT (p right UF = 0.01) and positively associated in PT children (p right UF preterm = 0.01). Other models were not significant.

Conclusions

In children with a full range of scores on behavioral problems from normal to significantly elevated, internalizing and externalizing behavioral problems were negatively associated with mean-FA of white matter tracts connecting to frontal lobes in FT children; externalizing behavioral problems were positively associated with mean-FA of the right uncinate in PT children. The different associations by birth group suggest that the neurobiology of behavioral problems differs in the two birth groups.

Brain age predicted using graph convolutional neural network explains neurodevelopmental trajectory in preterm neonates

OBJECTIVES

Dramatic brain morphological changes occur throughout the third trimester of gestation. In this study, we investigated whether the predicted brain age (PBA) derived from graph convolutional network (GCN) that accounts for cortical morphometrics in third trimester is associated with postnatal abnormalities and neurodevelopmental outcome.

METHODS

In total, 577 T1 MRI scans of preterm neonates from two different datasets were analyzed; the NEOCIVET pipeline generated cortical surfaces and morphological features, which were then fed to the GCN to predict brain age. The brain age index (BAI; PBA minus chronological age) was used to determine the relationships among preterm birth (i.e., birthweight and birth age), perinatal brain injuries, postnatal events/clinical conditions, BAI at postnatal scan, and neurodevelopmental scores at 30 months.

RESULTS

Brain morphology and GCN-based age prediction of preterm neonates without brain lesions (mean absolute error [MAE]: 0.96 weeks) outperformed conventional machine learning methods using no topological information. Structural equation models (SEM) showed that BAI mediated the influence of preterm birth and postnatal clinical factors, but not perinatal brain injuries, on neurodevelopmental outcome at 30 months of age.

CONCLUSIONS

Brain morphology may be clinically meaningful in measuring brain age, as it relates to postnatal factors, and predicting neurodevelopmental outcome.

CLINICAL RELEVANCE STATEMENT

Understanding the neurodevelopmental trajectory of preterm neonates through the prediction of brain age using a graph convolutional neural network may allow for earlier detection of potential developmental abnormalities and improved interventions, consequently enhancing the prognosis and quality of life in this vulnerable population.

KEY POINTS

•Brain age in preterm neonates predicted using a graph convolutional network with brain morphological changes mediates the pre-scan risk factors and post-scan neurodevelopmental outcomes. •Predicted brain age oriented from conventional deep learning approaches, which indicates the neurodevelopmental status in neonates, shows a lack of sensitivity to perinatal risk factors and predicting neurodevelopmental outcomes. •The new brain age index based on brain morphology and graph convolutional network enhances the accuracy and clinical interpretation of predicted brain age for neonates.

Associations of behavioral problems with white matter circuits connecting to the frontal lobes in school-aged children born at term and preterm

Introduction

This study investigated whether behavioral problems in children were associated with fractional anisotropy (FA) of white matter tracts connecting from other brain regions to right and left frontal lobes. We considered internalizing and externalizing behavioral problems separately and contrasted patterns of associations in children born at term and very preterm.

Methods

Parents completed the Child Behavior Checklist/6-18 questionnaire to quantify behavioral problems when their children were age 8 years (N=36 FT and 37 PT). Diffusion magnetic resonance scans were collected at the same age and analyzed using probabilistic tractography. We used multiple linear regression to investigate the strength of association between age-adjusted T-scores of internalizing and externalizing problems and mean fractional anisotropy (mean-FA) of right and left uncinate, arcuate, and anterior thalamic radiations, controlling for birth group and sex.

Results

Regression models predicting internalizing T-scores from mean-FA found significant group-by-tract interactions for the left and right arcuate and right uncinate. Internalizing scores were negatively associated with mean-FA of left and right arcuate only in children born at term (pleft AF =0.01, pright AF =0.01). Regression models predicting externalizing T-scores from mean-FA found significant group-by-tract interactions for the left arcuate and right uncinate. Externalizing scores were negatively associated with mean-FA of right uncinate in children born at term (pright UF =0.01) and positively associated in children born preterm (pright UF preterm =0.01). Other models were not significant.

Conclusions

In this sample of children with scores for behavioral problems across the full range, internalizing and externalizing behavioral problems were negatively associated with mean-FA of white matter tracts connecting to frontal lobes in children born at term; externalizing behavioral problems were positively associated with mean-FA of the right uncinate in children born preterm. The different associations by birth group suggest that the neurobiology of behavioral problems differs in the two birth groups.

Preterm-birth alters the development of nodal clustering and neural connection pattern in brain structural network at term-equivalent age

Preterm-born neonates are prone to impaired neurodevelopment that may be associated with disrupted whole-brain structural connectivity. The present study aimed to investigate the longitudinal developmental pattern of the structural network from preterm birth to term-equivalent age (TEA), and identify how prematurity influences the network topological organization and properties of local brain regions. Multi-shell diffusion-weighted MRI of 28 preterm-born scanned a short time after birth (PB-AB) and at TEA (PB-TEA), and 28 matched term-born (TB) neonates in the Developing Human Connectome Project (dHCP) were used to construct structural networks through constrained spherical deconvolution tractography. Structural network development from preterm birth to TEA showed reduced shortest path length, clustering coefficient, and modularity, and more "connector" hubs linking disparate communities. Furthermore, compared with TB newborns, premature birth significantly altered the nodal properties (i.e., clustering coefficient, within-module degree, and participation coefficient) in the limbic/paralimbic, default-mode, and subcortical systems but not global topology at TEA, and we were able to distinguish the PB from TB neonates at TEA based on the nodal properties with 96.43% accuracy. Our findings demonstrated a topological reorganization of the structural network occurs during the perinatal period that may prioritize the optimization of global network organization to form a more efficient architecture; and local topology was more vulnerable to premature birth-related factors than global organization of the structural network, which may underlie the impaired cognition and behavior in PB infants.

Preterm birth accelerates the maturation of spontaneous and resting activity in the visual cortex

Prematurity is among the leading risks for poor neurocognitive outcomes. The brains of preterm infants show alterations in structure and electrical activity, but the underlying circuit mechanisms are unclear. To address this, we performed a cross-species study of the electrophysiological activity in the visual cortices of prematurely born infants and mice. Using electroencephalography (EEG) in a sample of healthy preterm (N = 29) and term (N = 28) infants, we found that the maturation of the aperiodic EEG component was accelerated in the preterm cohort, with a significantly flatter 1/f slope when compared to the term infants. The flatter slope was a result of decreased spectral power in the theta and alpha bands and was correlated with the degree of prematurity. To determine the circuit and cellular changes that potentially mediate the changes in 1/f slope after preterm birth, we used in vivo electrophysiology in preterm mice and found that, similar to infants, preterm birth results in a flattened 1/f slope. We analyzed neuronal activity in the visual cortex of preterm (N = 6) and term (N = 9) mice and found suppressed spontaneous firing of neurons. Using immunohistochemistry, we further found an accelerated maturation of inhibitory circuits. In both preterm mice and infants, the functional maturation of the cortex was accelerated, underscoring birth as a critical checkpoint in cortical maturation. Our study points to a potential mechanism of preterm birth-related changes in resting neural activity, highlighting the utility of a cross-species approach in studying the neural circuit mechanisms of preterm birth-related neurodevelopmental conditions.

Preterm birth accelerates the maturation of spontaneous and resting activity in the visual cortex

Prematurity is among the leading risks for poor neurocognitive outcomes. The brains of preterm infants show alterations in structure and electrical activity, but the underlying circuit mechanisms are unclear. To address this, we performed a cross-species study of the electrophysiological activity in the visual cortices of prematurely born infants and mice. Using electroencephalography (EEG) in a sample of healthy preterm (N=29) and term (N=28) infants, we found that the maturation of the aperiodic EEG component was accelerated in the preterm cohort, with a significantly flatter 1/f slope when compared to the term infants. The flatter slope was a result of decreased spectral power in the theta and alpha bands and was correlated with the degree of prematurity. To determine the circuit and cellular changes that potentially mediate the changes in 1/f slope after preterm birth, we used in vivo electrophysiology in preterm mice and found that, similar to infants, preterm birth results in a flattened 1/f slope. We analyzed neuronal activity in the visual cortex of preterm mice (N=6 preterm and 9 term mice) and found suppressed spontaneous firing of neurons. Using immunohistochemistry, we further found an accelerated maturation of inhibitory circuits. In both preterm mice and infants, the functional maturation of the cortex was accelerated, underscoring birth as a critical checkpoint in cortical maturation. Our study points to a potential mechanism of preterm birth-related changes in resting neural activity, highlighting the utility of a cross-species approach in studying the neural circuit mechanisms of preterm birth-related neurodevelopmental conditions.

ICAM-Reg: Interpretable Classification and Regression With Feature Attribution for Mapping Neurological Phenotypes in Individual Scans

An important goal of medical imaging is to be able to precisely detect patterns of disease specific to individual scans; however, this is challenged in brain imaging by the degree of heterogeneity of shape and appearance. Traditional methods, based on image registration, historically fail to detect variable features of disease, as they utilise population-based analyses, suited primarily to studying group-average effects. In this paper we therefore take advantage of recent developments in generative deep learning to develop a method for simultaneous classification, or regression, and feature attribution (FA). Specifically, we explore the use of a VAE-GAN (variational autoencoder - general adversarial network) for translation called ICAM, to explicitly disentangle class relevant features, from background confounds, for improved interpretability and regression of neurological phenotypes. We validate our method on the tasks of Mini-Mental State Examination (MMSE) cognitive test score prediction for the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, as well as brain age prediction, for both neurodevelopment and neurodegeneration, using the developing Human Connectome Project (dHCP) and UK Biobank datasets. We show that the generated FA maps can be used to explain outlier predictions and demonstrate that the inclusion of a regression module improves the disentanglement of the latent space. Our code is freely available on GitHub https://github.com/CherBass/ICAM.

Spatiotemporal Developmental Gradient of Thalamic Morphology, Microstructure, and Connectivity fromthe Third Trimester to Early Infancy

Thalamus is a critical component of the limbic system that is extensively involved in both basic and high-order brain functions. However, how the thalamic structure and function develops at macroscopic and microscopic scales during the perinatal period development is not yet well characterized. Here, we used multishell high-angular resolution diffusion MRI of 144 preterm-born and full-term infants in both sexes scanned at 32-44 postmenstrual weeks (PMWs) from the Developing Human Connectome Project database to investigate the thalamic development in morphology, microstructure, associated connectivity, and subnucleus division. We found evident anatomic expansion and linear increases of fiber integrity in the lateral side of thalamus compared with the medial part. The tractography results indicated that thalamic connection to the frontal cortex developed later than the other thalamocortical connections (parieto-occipital, motor, somatosensory, and temporal). Using a connectivity-based segmentation strategy, we revealed that functional partitions of thalamic subdivisions were formed at 32 PMWs or earlier, and the partition developed toward the adult pattern in a lateral-to-medial pattern. Collectively, these findings revealed faster development of the lateral thalamus than the central part as well as a posterior-to-anterior developmental gradient of thalamocortical connectivity from the third trimester to early infancy.SIGNIFICANCE STATEMENT This is the first study that characterizes the spatiotemporal developmental pattern of thalamus during the third trimester to early infancy. We found that thalamus develops in a lateral-to-medial pattern for both thalamic microstructures and subdivisions; and thalamocortical connectivity develops in a posterior-to-anterior gradient that thalamofrontal connectivity appears later than the other thalamocortical connections. These findings may enrich our understanding of the developmental principles of thalamus and provide references for the atypical brain growth in neurodevelopmental disorders.

Structural Brain Network Reorganization Following Anterior Callosotomy for Colloid Cysts: Connectometry and Graph Analysis Results

Introduction:

The plasticity of the neural circuits after injuries has been extensively investigated over the last decades. Transcallosal microsurgery for lesions affecting the third ventricle offers an interesting opportunity to investigate the whole-brain white matter reorganization occurring after a selective resection of the genu of the corpus callosum (CC).

Method

Diffusion MRI (dMRI) data and neuropsychological testing were collected pre- and postoperatively in six patients with colloid cysts, surgically treated with a transcallosal-transgenual approach. Longitudinal connectometry analysis on dMRI data and graph analysis on structural connectivity matrix were implemented to analyze how white matter pathways and structural network topology reorganize after surgery.

Results

Although a significant worsening in cognitive functions (e.g., executive and memory functioning) at early postoperative, a recovery to the preoperative status was observed at 6 months. Connectometry analysis, beyond the decrease of quantitative anisotropy (QA) near the resection cavity, showed an increase of QA in the body and forceps major CC subregions, as well as in the left intra-hemispheric corticocortical associative fibers. Accordingly, a reorganization of structural network topology was observed between centrality increasing in the left hemisphere nodes together with a rise in connectivity strength among mid and posterior CC subregions and cortical nodes.

Conclusion

A structural reorganization of intra- and inter-hemispheric connective fibers and structural network topology were observed following the resection of the genu of the CC. Beyond the postoperative transient cognitive impairment, it could be argued anterior CC resection does not preclude neural plasticity and may subserve the long-term postoperative cognitive recovery.

Predicting age and clinical risk from the neonatal connectome

The development of perinatal brain connectivity underpins motor, cognitive and behavioural abilities in later life. Diffusion MRI allows the characterisation of subtle inter-individual differences in structural brain connectivity. Individual brain connectivity maps (connectomes) are by nature high in dimensionality and complex to interpret. Machine learning methods are a powerful tool to uncover properties of the connectome which are not readily visible and can give us clues as to how and why individual developmental trajectories differ. In this manuscript we used Deep Neural Networks and Random Forests to predict demographic and neurodevelopmental characteristics from neonatal structural connectomes in a large sample of babies (n = 524) from the developing Human Connectome Project. We achieved an accurate prediction of post menstrual age (PMA) at scan in term-born infants (mean absolute error (MAE) = 0.72 weeks, r = 0.83 and p<0.001). We also achieved good accuracy when predicting gestational age at birth in a cohort of term and preterm babies scanned at term equivalent age (MAE = 2.21 weeks, r = 0.82, p<0.001). We subsequently used sensitivity analysis to obtain feature relevance from our prediction models, with the most important connections for prediction of PMA and GA found to predominantly involve frontal and temporal regions, thalami, and basal ganglia. From our models of PMA at scan for infants born at term, we computed a brain maturation index (predicted age minus actual age) of individual preterm neonates and found a significant correlation between this index and motor outcome at 18 months corrected age. Our results demonstrate the applicability of machine learning techniques in analyses of the neonatal connectome and suggest that a neural substrate of brain maturation with implications for future neurodevelopment is detectable at term equivalent age from the neonatal connectome.

Advanced Brain Imaging in Preterm Infants: A Narrative Review of Microstructural and Connectomic Disruption

Preterm birth disrupts the in utero environment, preventing the brain from fully developing, thereby causing later cognitive and behavioral disorders. Such cerebral alteration occurs beneath an anatomical scale, and is therefore undetectable by conventional imagery. Prematurity impairs the microstructure and thus the histological process responsible for the maturation, including the myelination. Cerebral MRI diffusion tensor imaging sequences, based on water’s motion into the brain, allows a representation of this maturation process. Similarly, the brain’s connections become disorganized. The connectome gathers structural and anatomical white matter fibers, as well as functional networks referring to remote brain regions connected one over another. Structural and functional connectivity is illustrated by tractography and functional MRI, respectively. Their organizations consist of core nodes connected by edges. This basic distribution is already established in the fetal brain. It evolves greatly over time but is compromised by prematurity. Finally, cerebral plasticity is nurtured by a lifetime experience at microstructural and macrostructural scales. A preterm birth causes a negative and early disruption, though it can be partly mitigated by positive stimuli based on developmental neonatal care.

Early spectral EEG in preterm infants correlates with neurocognitive outcomes in late childhood

BACKGROUND

Evidence regarding the predictive value of early amplitude-integrated electroencephalography (aEEG)/EEG on neurodevelopmental outcomes at school age and beyond is lacking. We  aimed to investigate whether there is an association between early postnatal EEG and neurocognitive outcomes in late childhood.

METHODS

This study is an observational prospective cohort study of premature infants with a gestational age <28 weeks. The total absolute band powers (tABP) of the delta, theta, alpha, and beta bands were analyzed from EEG recordings during the first three days of life. At 10-12 years of age, neurocognitive outcomes were assessed using the Wechsler Intelligence Scale for Children 4th edition (WISC-IV), Vineland adaptive behavior scales 2nd edition, and Behavior Rating Inventory of Executive Function (BRIEF). The mean differences in tABP were assessed for individuals with normal versus unfavorable neurocognitive scores.

RESULTS

Twenty-two infants were included. tABP values in all four frequency bands were significantly lower in infants with unfavorable results in the main composite scores (full intelligence quotient, adaptive behavior composite score, and global executive composite score) on all three tests (p < 0.05).

CONCLUSIONS

Early postnatal EEG has the potential to assist in predicting cognitive outcomes at 10-12 years of age in extremely premature infants <28 weeks' gestation.

IMPACT

Evidence regarding the value of early postnatal EEG in long-term prognostication in preterm infants is limited. Our study suggests that early EEG spectral analysis correlates with neurocognitive outcomes in late childhood in extremely preterm infants. Early identification of infants at-risk of later impairment is important to initiate early and targeted follow-up and intervention.

OUP accepted manuscript

One of the great frontiers of consciousness science is understanding how early consciousness arises in the development of the human infant. The reciprocal relationship between the default mode network and fronto-parietal networks—the dorsal attention and executive control network—is thought to facilitate integration of information across the brain and its availability for a wide set of conscious mental operations. It remains unknown whether the brain mechanism of conscious awareness is instantiated in infants from birth. To address this gap, we investigated the development of the default mode and fronto-parietal networks and of their reciprocal relationship in neonates. To understand the effect of early neonate age on these networks, we also assessed neonates born prematurely or before term-equivalent age. We used the Developing Human Connectome Project, a unique Open Science dataset which provides a large sample of neonatal functional MRI data with high temporal and spatial resolution. Resting state functional MRI data for full-term neonates (n = 282, age 41.2 weeks ± 12 days) and preterm neonates scanned at term-equivalent age (n = 73, 40.9 weeks ± 14.5 days), or before term-equivalent age (n = 73, 34.6 weeks ± 13.4 days), were obtained from the Developing Human Connectome Project, and for a reference adult group (n = 176, 22–36 years), from the Human Connectome Project. For the first time, we show that the reciprocal relationship between the default mode and dorsal attention network was present at full-term birth or term-equivalent age. Although different from the adult networks, the default mode, dorsal attention and executive control networks were present as distinct networks at full-term birth or term-equivalent age, but premature birth was associated with network disruption. By contrast, neonates before term-equivalent age showed dramatic underdevelopment of high-order networks. Only the dorsal attention network was present as a distinct network and the reciprocal network relationship was not yet formed. Our results suggest that, at full-term birth or by term-equivalent age, infants possess key features of the neural circuitry that enables integration of information across diverse sensory and high-order functional modules, giving rise to conscious awareness. Conversely, they suggest that this brain infrastructure is not present before infants reach term-equivalent age. These findings improve understanding of the ontogeny of high-order network dynamics that support conscious awareness and of their disruption by premature birth.

Aberrant cortico-thalamic structural connectivity in premature-born adults

Premature birth is associated with alterations in brain structure, particularly in white matter. Among white matter, alterations in cortico-thalamic connections are present in premature-born infants, and they have been suggested both to last until adulthood and to contribute to impaired cognitive functions. To test these hypotheses, 70 very premature-born adults and 67 full-term controls underwent cognitive testing and diffusion-weighted imaging. Each cortical hemisphere was parcellated into six lobes, from which probabilistic tractography was performed to the thalamus. Connection probability was chosen as metric of structural connectivity. We found increased cortico-thalamic connection probability between left prefrontal cortices and left medio-dorsal thalamus and reduced connection probability between bilateral temporal cortices and bilateral anterior thalami in very premature-born adults. Aberrant prefronto- and temporo-thalamic connection probabilities were correlated with birth weight and days on ventilation, respectively, supporting the suggestion that these connectivity changes relate with the degree of prematurity. Moreover, an increase in left prefronto-thalamic connection probability also correlated with lower verbal comprehension index indicating its relevance for verbal cognition. Together, our results demonstrate that cortico-thalamic structural connectivity is aberrant in premature-born adults, with these changes being linked with impairments in verbal cognitive abilities. Due to corresponding findings in infants, data suggest aberrant development of cortico-thalamic connectivity after premature birth with lasting effects into adulthood.

Eye-tracking for longitudinal assessment of social cognition in children born preterm

BACKGROUND AND OBJECTIVES

Preterm birth is associated with atypical social cognition in infancy, and cognitive impairment and social difficulties in childhood. Little is known about the stability of social cognition through childhood, and its relationship with neurodevelopment. We used eye-tracking in preterm and term-born infants to investigate social attentional preference in infancy and at 5 years, its relationship with neurodevelopment and the influence of socioeconomic deprivation.

METHODS

A cohort of 81 preterm and 66 term infants with mean (range) gestational age at birth 28⁺⁵ (23⁺² -33⁺⁰ ) and 40⁺⁰ (37⁺⁰ -42⁺¹ ) respectively, completed eye-tracking at 7-9 months, with a subset re-assessed at 5 years. Three free-viewing social tasks of increasing stimulus complexity were presented, and a social preference score was derived from looking time to socially informative areas. Socioeconomic data and the Mullen Scales of Early Learning at 5 years were collected.

RESULTS

Preterm children had lower social preference scores at 7-9 months compared with term-born controls. Term-born children's scores were stable between time points, whereas preterm children showed a significant increase, reaching equivalent scores by 5 years. Low gestational age and socioeconomic deprivation were associated with reduced social preference scores at 7-9 months. At 5 years, preterm infants had lower Early Learning Composite scores than controls, but this was not associated with social attentional preference in infancy or at 5 years.

CONCLUSIONS

Preterm children have reduced social attentional preference at 7-9 months compared with term-born controls, but catch up by 5 years. Infant social cognition is influenced by socioeconomic deprivation and gestational age. Social cognition and neurodevelopment have different trajectories following preterm birth.

Microglia-Mediated Neurodegeneration in Perinatal Brain Injuries

Perinatal brain injuries, including encephalopathy related to fetal growth restriction, encephalopathy of prematurity, neonatal encephalopathy of the term neonate, and neonatal stroke, are a major cause of neurodevelopmental disorders. They trigger cellular and molecular cascades that lead in many cases to permanent motor, cognitive, and/or behavioral deficits. Damage includes neuronal degeneration, selective loss of subclasses of interneurons, blocked maturation of oligodendrocyte progenitor cells leading to dysmyelination, axonopathy and very likely synaptopathy, leading to impaired connectivity. The nature and severity of changes vary according to the type and severity of insult and maturation stage of the brain. Microglial activation has been demonstrated almost ubiquitously in perinatal brain injuries and these responses are key cell orchestrators of brain pathology but also attempts at repair. These divergent roles are facilitated by a diverse suite of transcriptional profiles and through a complex dialogue with other brain cell types. Adding to the complexity of understanding microglia and how to modulate them to protect the brain is that these cells have their own developmental stages, enabling them to be key participants in brain building. Of note, not only do microglia help build the brain and respond to brain injury, but they are a key cell in the transduction of systemic inflammation into neuroinflammation. Systemic inflammatory exposure is a key risk factor for poor neurodevelopmental outcomes in preterm born infants. Based on these observations, microglia appear as a key cell target for neuroprotection in perinatal brain injuries. Numerous strategies have been developed experimentally to modulate microglia and attenuate brain injury based on these strong supporting data and we will summarize these.

Delayed maturation of the structural brain connectome in neonates with congenital heart disease

There is emerging evidence for delayed brain development in neonates with congenital heart disease. We hypothesize that the perioperative development of the structural brain connectome is a proxy to such delays. Therefore, we set out to quantify the alterations and longitudinal pre- to post-operative changes in the connectome in congenital heart disease neonates relative to healthy term newborns and assess factors contributing to disturbed perioperative network development. In this prospective cohort study, 114 term neonates with congenital heart disease underwent cardiac surgery at the University Children's Hospital Zurich. Forty-six healthy term newborns were included as controls. Pre- and post-operative structural connectomes were derived from mean fractional anisotropy values of fibre pathways traced using diffusion MR tractography. Graph theory parameters calculated across a proportional cost threshold range were compared between groups by multi-threshold permutation correction adjusting for confounders. Network-based statistic was calculated for edgewise network comparison. White-matter injury volume was quantified on 3D T1-weighted images. Random coefficient mixed models with interaction terms of (i) cardiac subtype and (ii) injury volume with post-menstrual age at MRI, respectively, were built to assess modifying effects on network development. Pre- and post-operatively, at the global level, efficiency, indicative of network integration, was lower in heart disease neonates than controls. In contrast, local efficiency and transitivity, indicative of network segregation, were higher compared to controls (all P < 0.025 for one-sided t-tests). Pre-operatively, these group differences were also found across multiple widespread nodes (all P < 0.025, accounting for multiple comparison), whereas post-operatively nodal differences were not evident. At the edge-level, the majority of weaker connections in heart disease neonates compared to controls involved inter-hemispheric connections (66.7% pre-operatively; 54.5% post-operatively). A trend showing a more rapid pre- to post-operative decrease in local efficiency was found in class I cardiac sub-type (biventricular defect without aortic arch obstruction) compared to controls. In congenital heart disease neonates, larger white-matter injury volume was associated with lower strength (P = 0.0026) and global efficiency (P = 0.0097). The maturation of the structural connectome is delayed in congenital heart disease neonates, with a pattern of lower structural integration and higher segregation compared to controls. Trend-level evidence indicated that normalized post-operative cardiac physiology in class I sub-types might improve structural network topology. In contrast, the burden of white-matter injury negatively impacts network strength and integration. Further research is needed to elucidate how aberrant structural network development in congenital heart disease represents neural correlates of later neurodevelopmental impairments.

Reduced apparent fiber density in the white matter of premature-born adults

Premature-born adults exhibit lasting white matter alterations as demonstrated by widespread reduction in fractional anisotropy (FA) based on diffusion-weighted imaging (DWI). FA reduction, however, is non-specific for microscopic underpinnings such as aberrant myelination or fiber density (FD). Using recent advances in DWI, we tested the hypothesis of reduced FD in premature-born adults and investigated its link with the degree of prematurity and cognition. 73 premature- and 89 mature-born adults aged 25-27 years underwent single-shell DWI, from which a FD measure was derived using convex optimization modeling for microstructure informed tractography (COMMIT). Premature-born adults exhibited lower FD in numerous tracts including the corpus callosum and corona radiata compared to mature-born adults. These FD alterations were associated with both the degree of prematurity, as assessed via gestational age and birth weight, as well as with reduced cognition as measured by full-scale IQ. Finally, lower FD overlapped with lower FA, suggesting lower FD underlie unspecific FA reductions. Results provide evidence that premature birth leads to lower FD in adulthood which links with lower full-scale IQ. Data suggest that lower FD partly underpins FA reductions of premature birth but that other processes such as hypomyelination might also take place.

Preterm birth leads to impaired rich-club organization and fronto-paralimbic/limbic structural connectivity in newborns

Prematurity disrupts brain development during a critical period of brain growth and organization and is known to be associated with an increased risk of neurodevelopmental impairments. Investigating whole-brain structural connectivity alterations accompanying preterm birth may provide a better comprehension of the neurobiological mechanisms related to the later neurocognitive deficits observed in this population. Using a connectome approach, we aimed to study the impact of prematurity on neonatal whole-brain structural network organization at term-equivalent age. In this cohort study, twenty-four very preterm infants at term-equivalent age (VPT-TEA) and fourteen full-term (FT) newborns underwent a brain MRI exam at term age, comprising T2-weighted imaging and diffusion MRI, used to reconstruct brain connectomes by applying probabilistic constrained spherical deconvolution whole-brain tractography. The topological properties of brain networks were quantified through a graph-theoretical approach. Furthermore, edge-wise connectivity strength was compared between groups. Overall, VPT-TEA infants' brain networks evidenced increased segregation and decreased integration capacity, revealed by an increased clustering coefficient, increased modularity, increased characteristic path length, decreased global efficiency and diminished rich-club coefficient. Furthermore, in comparison to FT, VPT-TEA infants had decreased connectivity strength in various cortico-cortical, cortico-subcortical and intra-subcortical networks, the majority of them being intra-hemispheric fronto-paralimbic and fronto-limbic. Inter-hemispheric connectivity was also decreased in VPT-TEA infants, namely through connections linking to the left precuneus or left dorsal cingulate gyrus - two regions that were found to be hubs in FT but not in VPT-TEA infants. Moreover, posterior regions from Default-Mode-Network (DMN), namely precuneus and posterior cingulate gyrus, had decreased structural connectivity in VPT-TEA group. Our finding that VPT-TEA infants' brain networks displayed increased modularity, weakened rich-club connectivity and diminished global efficiency compared to FT infants suggests a delayed transition from a local architecture, focused on short-range connections, to a more distributed architecture with efficient long-range connections in those infants. The disruption of connectivity in fronto-paralimbic/limbic and posterior DMN regions might underlie the behavioral and social cognition difficulties previously reported in the preterm population.

Mental development is associated with cortical connectivity of the ventral and nonspecific thalamus of preterm newborns

INTRODUCTION

The thalamus is a key hub for regulating cortical connectivity. Dysmaturation of thalamocortical networks that accompany white matter injury has been hypothesized as neuroanatomical correlate of late life neurocognitive impairment following preterm birth. Our objective was to find a link between thalamocortical connectivity measures at term equivalent age and two-year neurodevelopmental outcome in preterm infants.

METHODS

Diffusion tensor MRI data of 58 preterm infants (postmenstrual age at birth, mean (SD), 29.71 (1.47) weeks) were used in the study. We utilized probabilistic diffusion tractography to trace connections between the cortex and thalami. Possible associations between connectivity strength, the length of the probabilistic fiber pathways, and developmental scores (Bayley Scales of Infant Development, Second Edition) were analyzed using multivariate linear regression models.

RESULTS

We found strong correlation between mental developmental index and two complementary measures of thalamocortical networks: Connectivity strength projected to a cortical skeleton and pathway length emerging from thalamic voxels (partial correlation, R = .552 and R = .535, respectively, threshold-free cluster enhancement, corrected p-value < .05), while psychomotor development was not associated with thalamocortical connectivity. Post hoc stepwise linear regression analysis revealed that parental socioeconomic scale, postmenstrual age, and the duration of mechanical ventilation at the intensive care unit contribute to the variability of outcome.

CONCLUSIONS

Our findings independently validated previous observations in preterm infants, providing additional evidence injury or dysmaturation of tracts emerging from ventral-specific and various nonspecific thalamus projecting to late-maturing cortical regions are predictive of mental, but not psychomotor developmental outcomes.

More than meets the eye: Longitudinal visual system neurodevelopment in very preterm children and anophthalmia

Anophthalmia, characterized by the absence of an eye(s), is a rare major birth defect with a relatively unexplored neuroanatomy. Longitudinal comparison of white matter development in an anophthalmic (AC) very preterm (VPT) child with both binocular VPT and full-term (FT) children provides unique insights into early neurodevelopment of the visual system. VPT-born neonates (<32wks gestational age), including the infant with unilateral anophthalmia, underwent neuroimaging every two years from birth until 8 years. DTI images (N = 168) of the optic radiation (OR) and a control track, the posterior limb of the internal capsule (PLIC), were analysed. The diameter of the optic nerves (ON) were analysed using T1-weighted images. Significant group differences in FA and AD were found bilaterally in the OR and PLIC. This extends the literature on altered white matter development in VPT children, being the first longitudinal study showing stable group differences across the 4, 6 and 8 year timepoints. AC showed greater deficits in FA and AD bilaterally, but recovered towards VPT group means from 4 to 8 years-of-age. Complete lack of binocular input would be responsible for these early deficits; compensatory mechanisms may facilitate structural improvement over time. AC's ON exhibited significant atrophy ipsilateral to the anophthalmic eye. Functionally, AC displayed normal visual acuity and form perception, but naso-temporal bias in motion perception. Following these groups and AC longitudinally enabled novel understanding of the joint influence of monocular vision and VPT birth on neurodevelopment.

Cortical Gray Matter Injury in Encephalopathy of Prematurity: Link to Neurodevelopmental Disorders

Preterm-born infants frequently suffer from an array of neurological damage, collectively termed encephalopathy of prematurity (EoP). They also have an increased risk of presenting with a neurodevelopmental disorder (e.g., autism spectrum disorder; attention deficit hyperactivity disorder) later in life. It is hypothesized that it is the gray matter injury to the cortex, in addition to white matter injury, in EoP that is responsible for the altered behavior and cognition in these individuals. However, although it is established that gray matter injury occurs in infants following preterm birth, the exact nature of these changes is not fully elucidated. Here we will review the current state of knowledge in this field, amalgamating data from both clinical and preclinical studies. This will be placed in the context of normal processes of developmental biology and the known pathophysiology of neurodevelopmental disorders. Novel diagnostic and therapeutic tactics required integration of this information so that in the future we can combine mechanism-based approaches with patient stratification to ensure the most efficacious and cost-effective clinical practice.

Early neurobehavior at 30 weeks postmenstrual age is related to outcome at term equivalent age

AIMS

To determine 1) the relationship between infant medical factors and early neurobehavior, and 2) the relationship between early neurobehavior at 30 weeks postmenstrual age (PMA) and neurobehavior at term equivalent age.

STUDY DESIGN

In this prospective longitudinal study, 88 very preterm infants born ≤30 weeks estimated gestational age (EGA) had neurobehavioral assessments at 30 weeks PMA using the Premie-Neuro and at term equivalent age using the NICU Network Neurobehavioral Scale (NNNS) and Hammersmith Neonatal Neurological Evaluation (HNNE).

RESULTS

Lower Premie-Neuro scores at 30 weeks PMA were related to being more immature at birth (p = 0.01; β = 3.87); the presence of patent ductus arteriosus (PDA; p < 0.01; β = -16.50) and cerebral injury (p < 0.01; β = -20.46); and prolonged exposure to oxygen therapy (p < 0.01; β = -0.01), endotracheal intubation (p < 0.01; β = -0.23), and total parenteral nutrition (p < 0.01; β = -0.35). After controlling for EGA, PDA, and number of days of endotracheal intubation, lower Premie-Neuro scores at 30 weeks PMA were independently related to lower total HNNE scores at term (p < 0.01; β = 0.12) and worse outcome on the NNNS with poorer quality of movement (p < 0.01; β = 0.02) and more stress (p < 0.01; ß = -0.004), asymmetry (p = 0.01; β = -0.04), excitability (p < 0.01; β = -0.05) and suboptimal reflexes (p < 0.01; ß = -0.06).

CONCLUSION

Medical factors were associated with early neurobehavioral performance at 30 weeks PMA. Early neurobehavior at 30 weeks PMA was a good marker of adverse neurobehavior at NICU discharge.

Inhibition is associated with whole-brain structural brain connectivity on network level in school-aged children born very preterm and at term

Inhibition abilities are often impaired in children born very preterm. In typically-developing individuals, inhibition has been associated with structural brain connectivity (SC). As SC is frequently altered following preterm birth, this study investigated whether aberrant SC underlies inhibition deficits in school-aged children born very preterm. In a group of 67 very preterm participants aged 8-13 years and 69 term-born peers, inhibition abilities were assessed with two tasks. In a subgroup of 50 very preterm and 62 term-born participants, diffusion tensor imaging (DTI) data were collected. Using network-based statistics (NBS), mean fractional anisotropy (FA_mean) was compared between groups. Associations of FA_mean and inhibition abilities were explored through linear regression. The composite score of inhibition abilities was lower in the very preterm group (M ​= ​-0.4, SD ​= ​0.8) than in the term-born group (M ​= ​0.0, SD ​= ​0.8) but group differences were not significant when adjusting for age, sex and socio-economic status (β ​= ​-0.13, 95%-CI [-0.30, 0.04], p ​= ​0.13). In the very preterm group, FA_mean was significantly lower in a network comprising thalamo-frontal, thalamo-temporal, frontal, cerebellar and intra-hemispheric connections than in the term-born group (t ​= ​5.21, lowest p-value ​= ​0.001). Irrespective of birth status, a network comprising parietal, cerebellar and subcortical connections was positively associated with inhibition abilities (t ​= ​4.23, lowest p-value ​= ​0.02). Very preterm birth results in long-term alterations of SC at network-level. As networks underlying inhibition abilities do not overlap with those differing between the groups, FA_mean may not be adequate to explain inhibition problems in very preterm children. Future studies should combine complementary measures of brain connectivity to address neural correlates of inhibition abilities.

Multimodal assessment shows misalignment of structural and functional thalamocortical connectivity in children and adolescents born very preterm

Thalamocortical connections are altered following very preterm birth but it is unknown whether structural and functional alterations are linked and how they contribute to neurodevelopmental deficits. We used a multimodal approach in 27 very preterm and 35 term-born children and adolescents aged 10-16 years: Structural thalamocortical connectivity was quantified with two measures derived from probabilistic tractography of diffusion tensor data, namely the volume of thalamic segments with cortical connections and mean fractional anisotropy (FA) within the respective segments. High-density sleep EEG was recorded and sleep spindles were identified at each electrode. Sleep spindle density and integrated spindle activity (ISA) were calculated to quantify functional thalamocortical connectivity. In term-born participants, the volume of the global thalamic segment with cortical connections was strongly related to sleep spindles across the entire head (mean r ​= ​.53 ​± .10; range ​= ​0.35 to 0.78). Regionally, the volume of the thalamic segment connecting to frontal brain regions correlated with sleep spindle density in two clusters of electrodes over fronto-temporal brain regions (.42 ​± .06; 0.35 to 0.51 and 0.43 ​± .08; 0.35 to 0.62) and the volume of the thalamic segment connecting to parietal brain regions correlated with sleep spindle density over parietal brain regions (mean r ​= ​.43 ​± .07; 0.35 to 0.61). In very preterm participants, the volume of the thalamic segments was not associated with sleep spindles. In the very preterm group, mean FA within the global thalamic segment was negatively correlated with ISA over a cluster of frontal and temporo-occipital brain regions (mean r ​= ​-.53 ​± .07; -.41 to -.72). No association between mean FA and ISA was found in the term-born group. With this multimodal study protocol, we identified a potential misalignment between structural and functional thalamocortical connectivity in children and adolescents born very preterm. Eventually, this may shed further light on the neuronal mechanisms underlying neurodevelopmental sequelae of preterm birth.

Developmental Pathoconnectomics and Advanced Fetal MRI

Developmental pathoconnectomics is an emerging field that aims to unravel the events leading to and outcome from disrupted brain connectivity development. Advanced magnetic resonance imaging (MRI) technology enables the portrayal of human brain connectivity before birth and has the potential to offer novel insights into normal and pathological human brain development. This review gives an overview of the currently used MRI techniques for connectomic imaging, with a particular focus on recent studies that have successfully translated these to the in utero or postmortem fetal setting. Possible mechanisms of how pathologies, maternal, or environmental factors may interfere with the emergence of the connectome are considered. The review highlights the importance of advanced image post processing and the need for reproducibility studies for connectomic imaging. Further work and novel data-sharing efforts would be required to validate or disprove recent observations from in utero connectomic studies, which are typically limited by low case numbers and high data drop out. Novel knowledge with regard to the ontogenesis, architecture, and temporal dynamics of the human brain connectome would lead to the more precise understanding of the etiological background of neurodevelopmental and mental disorders. To achieve this goal, this review considers the growing evidence from advanced fetal connectomic imaging for the increased vulnerability of the human brain during late gestation for pathologies that might lead to impaired connectome development and subsequently interfere with the development of neural substrates serving higher cognition.

Network based statistics reveals trophic and neuroprotective effect of early high dose erythropoetin on brain connectivity in very preterm infants

Periventricular white matter injury is common in very preterm infants and it is associated with long term neurodevelopmental impairments. While evidence supports the protective effects of erythropoetin (EPO) in preventing injury, we currently lack the complete understanding of how EPO affects the emergence and maturation of anatomical brain connectivity and function. In this case-control study, connectomic analysis based on diffusion MRI tractography was applied to evaluate the effect of early high-dose EPO in preterm infants. A whole brain, network-level analysis revealed a sub-network of anatomical brain connections in which connectivity strengths were significantly stronger in the EPO group. This distributed network comprised connections predominantly in the frontal and temporal lobe bilaterally, and the effect of EPO was focused on peripheral and feeder connections of the core structural connectivity network. EPO resulted in a globally increased clustering coefficient, higher global and average local efficiency, while higher strength and increased clustering was found for regions in the frontal lobe and cingulate gyrus. The connectivity network most affected by the EPO treatment showed a steeper increase graph theoretical measures with age compared to the placebo group. Our results demonstrate a weak but widespread effect of EPO on the structural connectivity network and a possible trophic effect of EPO reflected by increasing network segregation, predominantly in local connections.

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Erythropoietin (EPO) is a potential neuroprotective agent in very preterm infants.

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EPO leads to increased structural brain connectivity in fronto-temporal regions.

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Clustering coefficient, local and global efficiency increases after EPO treatment.

Executive Function in Relation to White Matter in Preterm and Full Term Children

Background: Executive function (EF) refers to cognitive abilities used to guide goal-directed behavior. Diffusion Tensor Imaging (DTI) provides quantitative characterization of white matter tracts in the brain. Children with preterm birth often have EF impairments and white matter injury. Aim: To examine the degree of association between EF scores and white matter fractional anisotropy (FA) as measured by DTI in children born preterm and term Study design: Cross-sectional study Subjects: Participants, 9-16 years of age, born preterm (n = 25; mean gestational age 28.6 weeks; mean birth weight 1,191 grams), and full term (n = 20) Outcome measures: White matter FA analyzed with Tract-Based Spatial Statistics, a technique that generates a skeleton representing the core of white matter tracts throughout the brain. Behavioral scores from EF tasks examining working memory, spatial memory capacity, and multiple skills from the Stockings of Cambridge. Results: The groups performed comparably on all tasks. In both groups, unfavorable working memory strategy scores were associated with lower FA. Other measures of EF were not associated with whole skeleton FA in either group in either direction. Conclusions: Strategy score on a spatial working memory task was associated with FA in preterm and full term children, suggesting common underlying neurobiology in both groups. Associations were found in frontal-parietal connections and other major tracts. Lack of associations between other EF tasks and FA may be due to variation in how children accomplish these EF tasks. Future research is required to fully understand the neurobiology of EF in children born preterm.

Neonatal brain injury and aberrant connectivity

Brain injury sustained during the neonatal period may disrupt development of critical structural and functional connectivity networks leading to subsequent neurodevelopmental impairment in affected children. These networks can be characterized using structural (via diffusion MRI) and functional (via resting state-functional MRI) neuroimaging techniques. Advances in neuroimaging have led to expanded application of these approaches to study term- and prematurely-born infants, providing improved understanding of cerebral development and the deleterious effects of early brain injury. Across both modalities, neuroimaging data are conducive to analyses ranging from characterization of individual white matter tracts and/or resting state networks through advanced 'connectome-style' approaches capable of identifying highly connected network hubs and investigating metrics of network topology such as modularity and small-worldness. We begin this review by summarizing the literature detailing structural and functional connectivity findings in healthy term and preterm infants without brain injury during the postnatal period, including discussion of early connectome development. We then detail common forms of brain injury in term- and prematurely-born infants. In this context, we next review the emerging body of literature detailing studies employing diffusion MRI, resting state-functional MRI and other complementary neuroimaging modalities to characterize structural and functional connectivity development in infants with brain injury. We conclude by reviewing technical challenges associated with neonatal neuroimaging, highlighting those most relevant to studying infants with brain injury and emphasizing the need for further targeted study in this high-risk population.

Sex-specific alterations in preterm brain

BACKGROUND

The literature on brain imaging in premature infants is mostly made up of studies that evaluate neonates, yet the most dynamic time of brain development happens from birth to 1 year of age. This study was designed to obtain quantitative brain measures from magnetic resonance imaging scans of infants born prematurely at 12 months of age.

METHODS

The subject group was designed to capture a wide range of gestational age (GA) from premature to full-term infants. An age-specific atlas generated quantitative brain measures. A regression model was used to predict effects of GA and sex on brain measures.

RESULTS

There was a primary effect of sex on: (1) intracranial volume, males > females; (2) proportional cerebral cortical gray matter (females > males), and (3) cerebral white matter (males > females). GA predicted cerebral volume and cerebral spinal fluid. GA also predicted cortical gray matter in a sex-specific manner with GA having a significant effect on cortical volume in the males, but not in females.

CONCLUSIONS AND RELEVANCE

Sex differences in brain structure are large early in life. GA had sex-specific effects highlighting the importance evaluating sex effects in neurodevelopmental outcomes of premature infants.

Accelerated Small-World Property of Structural Brain Networks in Preterm Infants at Term-Equivalent Age

BACKGROUND

The prediction of neurodevelopmental outcomes in preterm infants is one of the clinical challenges of pediatrics. Despite the recent interest in brain development and white matter connectivity using a network-based analysis, very little is known about the brain network of at term-equivalent age in preterm infants.

OBJECTIVE

We aimed to investigate the structural brain network using diffusion MRI following preterm delivery at term-equivalent age compared with term infants and explored the influence of gestational age (GA) and clinical factors.

METHOD

Diffusion tensor imaging data were acquired prospectively from 55 preterm neonates without apparent brain abnormalities (mean gestational age: 29.43 weeks) and 21 full-term infants at term-equivalent age. The global structural brain networks were produced by probabilistic white matter tractography in combination with the Johns Hopkins University neonate atlas to quantify connectivity between different cortical regions.

RESULTS

Compared with full-term infants, preterm infants had significantly lower global efficiency (p = 0.048) and increased small worldness (p = 0.012) after correcting for sex and age at MRI scan. The increased small worldness in the brain network at term-equivalent age was significantly linearly correlated with lower GA after adjusting for sex and the effects of postmenstrual age at MRI scan on the data in preterm infants (β = -0.020, p = 0.037). In multivariate analysis, infants with chronic lung disease had significantly decreased changes in clustering (p = 0.014) and local efficiency (p = 0.027).

CONCLUSION

The accelerated small worldness in preterm infants suggests that the structural brain network after preterm birth is reorganized in maximizing integrated and segregated processing, implying resilience against prematurity-associated pathology.

Trajectories of brain development in school-age children born preterm with very low birth weight

Preterm birth (gestational age < 37 weeks) with very low birth weight (VLBW, birth weight ≤ 1500 g) is associated with lifelong cognitive deficits, including in executive function, and persistent alterations in cortical and subcortical structures. However, it remains unclear whether “catch-up” growth is possible in the preterm/VLBW brain. Longitudinal structural MRI was conducted with children born preterm with VLBW (n = 41) and term-born peers participating in the Norwegian Mother and Child Cohort Study (MoBa) (n = 128) at two timepoints in early school age (mean ages 8.0 and 9.3 years). Images were analyzed with the FreeSurfer 5.3.0 longitudinal stream to assess differences in development of cortical thickness, surface area, and brain structure volumes, as well as associations with executive function development (NEPSY Statue and WMS-III Spatial Span scores) and perinatal health markers. No longitudinal group × time effects in cortical thickness, surface area, or subcortical volumes were seen, indicating similar brain growth trajectories in the groups over an approximately 16-month period in middle childhood. Higher IQ scores within the VLBW group were associated with greater surface area in left parieto-occipital and inferior temporal regions. Among VLBW preterm-born children, cortical surface area was smaller across the cortical mantle, and cortical thickness was thicker occipitally and frontally and thinner in lateral parietal and posterior temporal areas. Smaller volumes of corpus callosum, right globus pallidus, and right thalamus persisted in the VLBW group from timepoint 1 to 2. VLBW children had on average IQ 1 SD below term-born MoBa peers and significantly worse scores on WMS-III Spatial Span. Executive function scores did not show differential associations with morphometry between groups cross-sectionally or longitudinally. This study investigated divergent or “catch-up” growth in terms of cortical thickness, surface area, and volumes of subcortical gray matter structures and corpus callosum in children born preterm/VLBW and did not find group × time interactions. Greater surface area at mean age 9.3 in left parieto-occipital and inferior temporal cortex was associated with higher IQ in the VLBW group. These results suggest that preterm VLBW children may have altered cognitive networks, yet have structural growth trajectories that appear generally similar to their term-born peers in this early school age window.

Whole mouse brain structural connectomics using magnetic resonance histology

Diffusion tensor histology holds great promise for quantitative characterization of structural connectivity in mouse models of neurological and psychiatric conditions. There has been extensive study in both the clinical and preclinical domains on the complex tradeoffs between the spatial resolution, the number of samples in diffusion q-space, scan time, and the reliability of the resultant data. We describe here a method for accelerating the acquisition of diffusion MRI data to support quantitative connectivity measurements in the whole mouse brain using compressed sensing (CS). The use of CS allows substantial increase in spatial resolution and/or reduction in scan time. Compared to the fully sampled results at the same scan time, the subtle anatomical details of the brain, such as cortical layers, dentate gyrus, and cerebellum, were better visualized using CS due to the higher spatial resolution. Compared to the fully sampled results at the same spatial resolution, the scalar diffusion metrics, including fractional anisotropy (FA) and mean diffusivity (MD), showed consistently low error across the whole brain (< 6.0%) even with 8.0 times acceleration. The node properties of connectivity (strength, cluster coefficient, eigenvector centrality, and local efficiency) demonstrated correlation of better than 95.0% between accelerated and fully sampled connectomes. The acceleration will enable routine application of this technology to a wide range of mouse models of neurologic diseases.

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.

Rapid Infant Prefrontal Cortex Development and Sensitivity to Early Environmental Experience

Over the last fifteen years, the emerging field of developmental cognitive neuroscience has described the relatively late development of prefrontal cortex in children and the relation between gradual structural changes and children's protracted development of prefrontal-dependent skills. Widespread recognition by the broader scientific community of the extended development of prefrontal cortex has led to the overwhelming perception of prefrontal cortex as a "late developing" region of the brain. However, despite its supposedly protracted development, multiple lines of research have converged to suggest that prefrontal cortex development may be particularly susceptible to individual differences in children's early environments. Recent studies demonstrate that the impacts of early adverse environments on prefrontal cortex are present very early in development: within the first year of life. This review provides a comprehensive overview of new neuroimaging evidence demonstrating that prefrontal cortex should be characterized as a "rapidly developing" region of the brain, discusses the converging impacts of early adversity on prefrontal circuits, and presents potential mechanisms via which adverse environments shape both concurrent and long-term measures of prefrontal cortex development. Given that environmentally-induced disparities are present in prefrontal cortex development within the first year of life, translational work in intervention and/or prevention science should focus on intervening early in development to take advantages of this early period of rapid prefrontal development and heightened plasticity.

Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project

The developing Human Connectome Project is set to create and make available to the scientific community a 4-dimensional map of functional and structural cerebral connectivity from 20 to 44 weeks post-menstrual age, to allow exploration of the genetic and environmental influences on brain development, and the relation between connectivity and neurocognitive function. A large set of multi-modal MRI data from fetuses and newborn infants is currently being acquired, along with genetic, clinical and developmental information. In this overview, we describe the neonatal diffusion MRI (dMRI) image processing pipeline and the structural connectivity aspect of the project. Neonatal dMRI data poses specific challenges, and standard analysis techniques used for adult data are not directly applicable. We have developed a processing pipeline that deals directly with neonatal-specific issues, such as severe motion and motion-related artefacts, small brain sizes, high brain water content and reduced anisotropy. This pipeline allows automated analysis of in-vivo dMRI data, probes tissue microstructure, reconstructs a number of major white matter tracts, and includes an automated quality control framework that identifies processing issues or inconsistencies. We here describe the pipeline and present an exemplar analysis of data from 140 infants imaged at 38–44 weeks post-menstrual age.

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A comprehensive and automated pipeline to consistently analyse neonatal dMRI data.

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Optimised motion and distortions correction to address newborn specific challenges.

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The automated QC framework allows to detect issues and to quantify data quality.

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Automated white matter segmentation allows to extract tract-specific masks.

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Preliminary data analysis of 140 infants imaged at 38–44 weeks post-menstrual age.

Longitudinal Study of White Matter Development and Outcomes in Children Born Very Preterm

Identifying trajectories of early white matter development is important for understanding atypical brain development and impaired functional outcomes in children born very preterm (<32 weeks gestational age [GA]). In this study, 161 diffusion images were acquired in children born very preterm (median GA: 29 weeks) shortly following birth (75), term-equivalent (39), 2 years (18), and 4 years of age (29). Diffusion tensors were computed to obtain measures of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), which were aligned and averaged. A paediatric atlas was applied to obtain diffusion metrics within 12 white matter tracts. Developmental trajectories across time points demonstrated age-related changes which plateaued between term-equivalent and 2 years of age in the majority of posterior tracts and between 2 and 4 years of age in anterior tracts. Between preterm and term-equivalent scans, FA rates of change were slower in anterior than posterior tracts. Partial least squares analyses revealed associations between slower MD and RD rates of change within the external and internal capsule with lower intelligence quotients and language scores at 4 years of age. These results uniquely demonstrate early white matter development and its linkage to cognitive functions.

Annual Research Review: Not just a small adult brain: understanding later neurodevelopment through imaging the neonatal brain

BACKGROUND

There has been a recent proliferation in neuroimaging research focusing on brain development in the prenatal, neonatal and very early childhood brain. Early brain injury and preterm birth are associated with increased risk of neurodevelopmental disorders, indicating the importance of this early period for later outcome.

SCOPE AND METHODOLOGY

Although using a wide range of different methodologies and investigating diverse samples, the common aim of many of these studies has been to both track normative development and investigate deviations in this development to predict behavioural, cognitive and neurological function in childhood. Here we review structural and functional neuroimaging studies investigating the developing brain. We focus on practical and technical complexities of studying this early age range and discuss how neuroimaging techniques have been successfully applied to investigate later neurodevelopmental outcome.

CONCLUSIONS

Neuroimaging markers of later outcome still have surprisingly low predictive power and their specificity to individual neurodevelopmental disorders is still under question. However, the field is still young, and substantial challenges to both acquiring and modeling neonatal data are being met.

Children's academic attainment is linked to the global organization of the white matter connectome

Literacy and numeracy are important skills that are typically learned during childhood, a time that coincides with considerable shifts in large-scale brain organization. However, most studies emphasize focal brain contributions to literacy and numeracy development by employing case-control designs and voxel-by-voxel statistical comparisons. This approach has been valuable, but may underestimate the contribution of overall brain network organization. The current study includes children (N = 133 children; 86 male; mean age = 9.42, SD = 1.715; age range = 5.92-13.75y) with a broad range of abilities, and uses whole-brain structural connectomics based on diffusion-weighted MRI data. The results indicate that academic attainment is associated with differences in structural brain organization, something not seen when focusing on the integrity of specific regions. Furthermore, simulated disruption of highly-connected brain regions known as hubs suggests that the role of these regions for maintaining the architecture of the network may be more important than specific aspects of processing. Our findings indicate that distributed brain systems contribute to the etiology of difficulties with academic learning, which cannot be captured using a more traditional voxel-wise statistical approach.

Altered white matter development in children born very preterm

Children born very preterm (VPT) at less than 32 weeks' gestational age (GA) are prone to disrupted white matter maturation and impaired cognitive development. The aims of the present study were to identify differences in white matter microstructure and connectivity of children born VPT compared to term-born children, as well as relations between white matter measures with cognitive outcomes and early brain injury. Diffusion images and T1-weighted anatomical MR images were acquired along with developmental assessments in 31 VPT children (mean GA: 28.76 weeks) and 28 term-born children at 4 years of age. FSL's tract-based spatial statistics was used to create a cohort-specific template and mean fractional anisotropy (FA) skeleton that was applied to each child's DTI data. Whole brain deterministic tractography was performed and graph theoretical measures of connectivity were calculated based on the number of streamlines between cortical and subcortical nodes derived from the Desikan-Killiany atlas. Between-group analyses included FSL Randomise for voxel-wise statistics and permutation testing for connectivity analyses. Within-group analyses between FA values and graph measures with IQ, language and visual-motor scores as well as history of white matter injury (WMI) and germinal matrix/intraventricular haemorrhage (GMH/IVH) were performed. In the children born VPT, FA values within major white matter tracts were reduced compared to term-born children. Reduced measures of local strength, clustering coefficient, local and global efficiency were present in the children born VPT within nodes in the lateral frontal, middle and superior temporal, cingulate, precuneus and lateral occipital regions. Within-group analyses revealed associations in term-born children between FA, Verbal IQ, Performance IQ and Full scale IQ within regions of the superior longitudinal fasciculus, inferior fronto-occipital fasciculus, forceps minor and forceps major. No associations with outcome were found in the VPT group. Global efficiency was reduced in the children born VPT with a history of WMI and GMH/IVH. These findings are evidence for under-developed and less connected white matter in children born VPT, contributing to our understanding of white matter development within this population.

A latent measure explains substantial variance in white matter microstructure across the newborn human brain

A latent measure of white matter microstructure (g WM) provides a neural basis for information processing speed and intelligence in adults, but the temporal emergence of g WM during human development is unknown. We provide evidence that substantial variance in white matter microstructure is shared across a range of major tracts in the newborn brain. Based on diffusion MRI scans from 145 neonates [gestational age (GA) at birth range 23+2-41+5 weeks], the microstructural properties of eight major white matter tracts were calculated using probabilistic neighborhood tractography. Principal component analyses (PCAs) were carried out on the correlations between the eight tracts, separately for four tract-averaged water diffusion parameters: fractional anisotropy, and mean, radial and axial diffusivities. For all four parameters, PCAs revealed a single latent variable that explained around half of the variance across all eight tracts, and all tracts showed positive loadings. We considered the impact of early environment on general microstructural properties, by comparing term-born infants with preterm infants at term equivalent age. We found significant associations between GA at birth and the latent measure for each water diffusion measure; this effect was most apparent in projection and commissural fibers. These data show that a latent measure of white matter microstructure is present in very early life, well before myelination is widespread. Early exposure to extra-uterine life is associated with altered general properties of white matter microstructure, which could explain the high prevalence of cognitive impairment experienced by children born preterm.

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.

Volumetric grey matter alterations in adolescents and adults born very preterm suggest accelerated brain maturation

Previous research investigating structural neurodevelopmental alterations in individuals who were born very preterm demonstrated a complex pattern of grey matter changes that defy straightforward summary. Here we addressed this problem by characterising volumetric brain alterations in individuals who were born very preterm from adolescence to adulthood at three hierarchically related levels - global, modular and regional. We demarcated structural components that were either particularly resilient or vulnerable to the impact of very preterm birth. We showed that individuals who were born very preterm had smaller global grey matter volume compared to controls, with subcortical and medial temporal regions being particularly affected. Conversely, frontal and lateral parieto-temporal cortices were relatively resilient to the effects of very preterm birth, possibly indicating compensatory mechanisms. Exploratory analyses supported this hypothesis by showing a stronger association between lateral parieto-temporal volume and IQ in the very preterm group compared to controls. We then related these alterations to brain maturation processes. Very preterm individuals exhibited a higher maturation index compared to controls, indicating accelerated brain maturation and this was specifically associated with younger gestational age. We discuss how the findings of accelerated maturation might be reconciled with evidence of delayed maturation at earlier stages of development.

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Hierarchically related structural brain alterations in very preterm individuals span adolescence and adulthood.

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Structural volumetric components that showed resiliency in very preterm individuals were associated with higher IQ.

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Very preterm individuals showed accelerated brain maturation compared to a large dataset of term-born controls.

Importance of neonatal immunoglobulin transfer for hippocampal development and behaviour in the newborn pig

Neurological disorders are among the main clinical problems affecting preterm children and often result in the development of communication and learning disabilities later in life. Several factors are of importance for brain development, however the role of immunoglobulins (passive immunity transfer) has not yet been investigated. Piglets are born agammaglobulinemic, as a result of the lack of transfer of maternal immunoglobulins in utero, thus, they serve as an ideal model to mimic the condition of immunoglobulin deficiency in preterm infants. Thirty six, unsuckled newborn piglets were fed an infant formula or colostrum and supplemented orally or intravenously with either species-specific or foreign immunoglobulin and then compared to both newborn and sow-reared piglets. Two days after the piglets were born behavioural tests (novel recognition and olfactory discrimination of conspecifics scent) were performed, after which the piglets were sacrificed and blood, cerebrospinal fluid and hippocampi samples were collected for analyses. Both parameters of neuronal plasticity (neuronal maturation and synapse-associated proteins) and behavioural test parameters appeared to be improved by the appearance of species-specific porcine immunoglulin in the circulation and cerebrospinal fluid of the piglets. In conclusion, we postulate possible positive clinical effects following intravenous infusion of human immunoglobulin in terms of neuronal plasticity and cognitive function in preterm infants born with low blood immunoglobulin levels.

Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex

The macro-connectome elucidates the pathways through which brain regions are structurally connected or functionally coupled to perform a specific cognitive task. It embodies the notion of representing and understanding all connections within the brain as a network, while the subdivision of the brain into interacting functional units is inherent in its architecture. As a result, the definition of network nodes is one of the most critical steps in connectivity network analysis. Although brain atlases obtained from cytoarchitecture or anatomy have long been used for this task, connectivity-driven methods have arisen only recently, aiming to delineate more homogeneous and functionally coherent regions. This study provides a systematic comparison between anatomical, connectivity-driven and random parcellation methods proposed in the thriving field of brain parcellation. Using resting-state functional MRI data from the Human Connectome Project and a plethora of quantitative evaluation techniques investigated in the literature, we evaluate 10 subject-level and 24 groupwise parcellation methods at different resolutions. We assess the accuracy of parcellations from four different aspects: (1) reproducibility across different acquisitions and groups, (2) fidelity to the underlying connectivity data, (3) agreement with fMRI task activation, myelin maps, and cytoarchitectural areas, and (4) network analysis. This extensive evaluation of different parcellations generated at the subject and group level highlights the strengths and shortcomings of the various methods and aims to provide a guideline for the choice of parcellation technique and resolution according to the task at hand. The results obtained in this study suggest that there is no optimal method able to address all the challenges faced in this endeavour simultaneously.