Resting-State Network Complexity and Magnitude Are Reduced in Prematurely Born Infants

Third Trimester Brain Growth in Preterm Infants Compared With In Utero Healthy Fetuses

BACKGROUND AND OBJECTIVES

Compared with term infants, preterm infants have impaired brain development at term-equivalent age, even in the absence of structural brain injury. However, details regarding the onset and progression of impaired preterm brain development over the third trimester are unknown. Our primary objective was to compare third-trimester brain volumes and brain growth trajectories in ex utero preterm infants without structural brain injury and in healthy in utero fetuses. As a secondary objective, we examined risk factors associated with brain volumes in preterm infants over the third-trimester postconception.

METHODS

Preterm infants born before 32 weeks of gestational age (GA) and weighing <1500 g with no evidence of structural brain injury on conventional MRI and healthy pregnant women were prospectively recruited. Anatomic T2-weighted brain images of preterm infants and healthy fetuses were parcellated into the following regions: cerebrum, cerebellum, brainstem, and intracranial cavity.

RESULTS

We studied 205 participants (75 preterm infants and 130 healthy control fetuses) between 27 and 39 weeks' GA. Third-trimester brain volumes were reduced and brain growth trajectories were slower in the ex utero preterm group compared with the in utero healthy fetuses in the cerebrum, cerebellum, brainstem, and intracranial cavity. Clinical risk factors associated with reduced brain volumes included dexamethasone treatment, the presence of extra-axial blood on brain MRI, confirmed sepsis, and duration of oxygen support.

CONCLUSIONS

These preterm infants exhibited impaired third-trimester global and regional brain growth in the absence of cerebral/cerebellar parenchymal injury detected by using conventional MRI.

Prenatal stress alters amygdala functional connectivity in preterm neonates

Exposure to prenatal and early-life stress results in alterations in neural connectivity and an increased risk for neuropsychiatric disorders. In particular, alterations in amygdala connectivity have emerged as a common effect across several recent studies. However, the impact of prenatal stress exposure on the functional organization of the amygdala has yet to be explored in the prematurely-born, a population at high risk for neuropsychiatric disorders. We test the hypothesis that preterm birth and prenatal exposure to maternal stress alter functional connectivity of the amygdala using two independent cohorts. The first cohort is used to establish the effects of preterm birth and consists of 12 very preterm neonates and 25 term controls, all without prenatal stress exposure. The second is analyzed to establish the effects of prenatal stress exposure and consists of 16 extremely preterm neonates with prenatal stress exposure and 10 extremely preterm neonates with no known prenatal stress exposure. Standard resting-state functional magnetic resonance imaging and seed connectivity methods are used. When compared to term controls, very preterm neonates show significantly reduced connectivity between the amygdala and the thalamus, the hypothalamus, the brainstem, and the insula (p < 0.05). Similarly, when compared to extremely preterm neonates without exposure to prenatal stress, extremely preterm neonates with exposure to prenatal stress show significantly less connectivity between the left amygdala and the thalamus, the hypothalamus, and the peristriate cortex (p < 0.05). Exploratory analysis of the combined cohorts suggests additive effects of prenatal stress on alterations in amygdala connectivity associated with preterm birth. Functional connectivity from the amygdala to other subcortical regions is decreased in preterm neonates compared to term controls. In addition, these data, for the first time, suggest that prenatal stress exposure amplifies these decreases.

Prediction of brain maturity in infants using machine-learning algorithms

Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prematurely-born infants. Application of new analytical approaches can help translate the improved understanding of early functional connectivity provided through these studies into predictive models of neurodevelopmental outcome. One approach to achieving this goal is multivariate pattern analysis, a machine-learning, pattern classification approach well-suited for high-dimensional neuroimaging data. It has previously been adapted to predict brain maturity in children and adolescents using structural and resting state-functional MRI data. In this study, we evaluated resting state-functional MRI data from 50 preterm-born infants (born at 23-29weeks of gestation and without moderate-severe brain injury) scanned at term equivalent postmenstrual age compared with data from 50 term-born control infants studied within the first week of life. Using 214 regions of interest, binary support vector machines distinguished term from preterm infants with 84% accuracy (p<0.0001). Inter- and intra-hemispheric connections throughout the brain were important for group categorization, indicating that widespread changes in the brain's functional network architecture associated with preterm birth are detectable by term equivalent age. Support vector regression enabled quantitative estimation of birth gestational age in single subjects using only term equivalent resting state-functional MRI data, indicating that the present approach is sensitive to the degree of disruption of brain development associated with preterm birth (using gestational age as a surrogate for the extent of disruption). This suggests that support vector regression may provide a means for predicting neurodevelopmental outcome in individual infants.

A neural window on the emergence of cognition

Can babies think? A fundamental challenge for cognitive neuroscience is to answer when brain functions begin and in what form they first emerge. This is challenging with behavioral tasks, as it is difficult to communicate to an infant what a task requires, and motor function is impoverished, making execution of the appropriate response difficult. To circumvent these requirements, neuroimaging provides a complementary route for assessing the emergence of cognition. Starting from the prerequisites of cognitive function and building stepwise, we review when the cortex forms and when it becomes gyrated and regionally differentiated. We then discuss when white matter tracts mature and when functional brain networks arise. Finally, we assess the responsiveness of these brain systems to external events. We find that many cognitive systems are observed surprisingly early. Some emerge before birth, with activations in the frontal lobe even in the first months of gestation. These discoveries are changing our understanding of the nature of cognitive networks and their early function, transforming cognitive neuroscience, and opening new windows for education and investigation. Infant neuroimaging also has tremendous clinical potential, for both detecting atypical development and facilitating earlier intervention. Finally, we discuss the key technical developments that are enabling this nascent field.

N-methyl-D-aspartate receptor encephalitis mediates loss of intrinsic activity measured by functional MRI

Spontaneous brain activity is required for the development and maintenance of normal brain function. Many disease processes disrupt the organization of intrinsic brain activity, but few pervasively reduce the amplitude of resting state blood oxygen level dependent (BOLD) fMRI fluctuations. We report the case of a female with anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis, longitudinally studied during the course of her illness to determine the contribution of NMDAR signaling to spontaneous brain activity. Resting state BOLD fMRI was measured at the height of her illness and 18 weeks following discharge from hospital. Conventional resting state networks were defined using established methods. Correlation and covariance matrices were calculated by extracting the BOLD time series from regions of interest and calculating either the correlation or covariance quantity. The intrinsic activity was compared between visits, and to expected activity from 45 similarly aged healthy individuals. Near the height of the illness, the patient exhibited profound loss of consciousness, high-amplitude slowing of the electroencephalogram, and a severe reduction in the amplitude of spontaneous BOLD fMRI fluctuations. The patient's neurological status and measures of intrinsic activity improved following treatment. We conclude that NMDAR-mediated signaling plays a critical role in the mechanisms that give rise to organized spontaneous brain activity. Loss of intrinsic activity is associated with profound disruptions of consciousness and cognition.

Functional magnetic resonance connectivity studies in infants born preterm: suggestions of proximate and long-lasting changes in language organization

Sophisticated neuroimaging strategies demonstrate alterations in functional connectivity at school age, adolescence, and young adulthood in individuals born preterm. Recent data suggest these alterations are present in the postnatal period prior to term-equivalent age in neonates born preterm. Likewise, functional organization increases across development, but the influence of preterm birth on this fundamental infrastructure is immediate and unchanging. This article briefly reviews the current methods of measuring functional connectivity throughout development in those born preterm, and the association of functional connectivity with language disorders. Taken together, these data suggest that the effects of preterm birth on the functional organization of language in the developing brain are both proximate and long-lasting.

Language at rest: A longitudinal study of intrinsic functional connectivity in preterm children

BACKGROUND

Preterm (PT) children show early cognitive and language deficits and display altered cortical connectivity for language compared to term (T) children. Developmentally, functional connectivity networks become more segregated and integrated, through the weakening of short-range and strengthening of long-range connections.

METHODS

Longitudinal intrinsic connectivity distribution (ICD) values were assessed in PT (n = 13) compared to T children (n = 12) at ages 8 vs. 16 using a Linear Mixed Effects model. Connectivity values in regions generated by the group × age interaction analysis were then correlated to scores on full IQ (FSIQ), verbal IQ (VIQ), verbal comprehension IQ (VCIQ), performance IQ (PIQ), Peabody picture vocabulary test-revised (PPVT-R), and Rapid Naming Composite (RDRL_Cmp).

RESULTS

Nine regions were generated by the group × age interaction analysis. PT connectivity significantly increased over time in all but two regions, and they ultimately displayed greater relative connectivity at age 16 than Ts in all areas except the left occipito-temporal cortex (OTC). PTs underwent significant connectivity reductions in the left OTC, which corresponded with worse performance on FSIQ, VIQ, and PIQ. These findings differed from Ts, who did not undergo any significant changes in connectivity over time.

CONCLUSIONS

These findings suggest that the developmental alterations in connectivity in PT children at adolescence are both pervasive and widespread. The persistent and worsening cognitive and language deficits noted in the PT subjects may be attributed to the loss of connections in the left OTC.

Functional properties of resting state networks in healthy full-term newborns

Objective, early, and non-invasive assessment of brain function in high-risk newborns is critical to initiate timely interventions and to minimize long-term neurodevelopmental disabilities. A prerequisite to identifying deviations from normal, however, is the availability of baseline measures of brain function derived from healthy, full-term newborns. Recent advances in functional MRI combined with graph theoretic techniques may provide important, currently unavailable, quantitative markers of normal neurodevelopment. In the current study, we describe important properties of resting state networks in 60 healthy, full-term, unsedated newborns. The neonate brain exhibited an efficient and economical small world topology: densely connected nearby regions, sparse, but well integrated, distant connections, a small world index greater than 1, and global/local efficiency greater than network cost. These networks showed a heavy-tailed degree distribution, suggesting the presence of regions that are more richly connected to others (‘hubs’). These hubs, identified using degree and betweenness centrality measures, show a more mature hub organization than previously reported. Targeted attacks on hubs show that neonate networks are more resilient than simulated scale-free networks. Networks fragmented faster and global efficiency decreased faster when betweenness, as opposed to degree, hubs were attacked suggesting a more influential role of betweenness hub in the neonate network.

Preterm birth alters neonatal, functional rich club organization

Alterations in neural networks are associated with the cognitive difficulties of the prematurely born. Using functional magnetic resonance imaging, we analyzed functional connectivity for preterm (PT) and term neonates at term equivalent age. Specifically, we constructed whole-brain networks and examined rich club (RC) organization, a common construct among complex systems where important (or "rich") nodes connect preferentially to other important nodes. Both PT and term neonates showed RC organization with PT neonates exhibiting significantly reduced connections between these RC nodes. Additionally, PT neonates showed evidence of weaker functional segregation. Our results suggest that PT birth is associated with fundamental changes of functional organization in the developing brain.

Machine-learning to characterise neonatal functional connectivity in the preterm brain

Brain development is adversely affected by preterm birth. Magnetic resonance image analysis has revealed a complex fusion of structural alterations across all tissue compartments that are apparent by term-equivalent age, persistent into adolescence and adulthood, and associated with wide-ranging neurodevelopment disorders. Although functional MRI has revealed the relatively advanced organisational state of the neonatal brain, the full extent and nature of functional disruptions following preterm birth remain unclear.

In this study, we apply machine-learning methods to compare whole-brain functional connectivity in preterm infants at term-equivalent age and healthy term-born neonates in order to test the hypothesis that preterm birth results in specific alterations to functional connectivity by term-equivalent age.

Functional connectivity networks were estimated in 105 preterm infants and 26 term controls using group-independent component analysis and a graphical lasso model. A random forest–based feature selection method was used to identify discriminative edges within each network and a nonlinear support vector machine was used to classify subjects based on functional connectivity alone.

We achieved 80% cross-validated classification accuracy informed by a small set of discriminative edges. These edges connected a number of functional nodes in subcortical and cortical grey matter, and most were stronger in term neonates compared to those born preterm. Half of the discriminative edges connected one or more nodes within the basal ganglia.

These results demonstrate that functional connectivity in the preterm brain is significantly altered by term-equivalent age, confirming previous reports of altered connectivity between subcortical structures and higher-level association cortex following preterm birth.

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Robust classification of preterm and term-born neonates using functional connectivity patterns.

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Discriminative pattern of alterations in basal ganglia and frontal connections.

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Reflects system-wide disruption of subcortical–cortical connections following preterm birth.

Brain Injury in the Preterm Infant: New Horizons for Pathogenesis and Prevention

Preterm neonates are surviving with a milder spectrum of motor and cognitive disabilities that appear to be related to widespread disturbances in cell maturation that target cerebral gray and white matter. Whereas the preterm brain was previously at high risk for destructive lesions, preterm survivors now commonly display less severe injury that is associated with aberrant regeneration and repair responses that result in reduced cerebral growth. Impaired cerebral white matter growth is related to myelination disturbances that are initiated by acute death of premyelinating oligodendrocytes, but are followed by rapid regeneration of premyelinating oligodendrocytes that fail to normally mature to myelinating cells. Although immature neurons are more resistant to cell death than mature neurons, they display widespread disturbances in maturation of their dendritic arbors and synapses, which further contributes to impaired cerebral growth. Thus, even more mild cerebral injury involves disrupted repair mechanisms in which neurons and premyelinating oligodendrocytes fail to fully mature during a critical window in development of neural circuitry. These recently recognized distinct forms of cerebral gray and white matter dysmaturation raise new diagnostic challenges and suggest new therapeutic strategies to promote brain growth and repair.

The predictive validity of neonatal MRI for neurodevelopmental outcome in very preterm children

Very preterm children are at a high risk for neurodevelopmental impairments, but there is variability in the pattern and severity of outcome. Neonatal magnetic resonance imaging (MRI) enhances the capacity to detect brain injury and altered brain development and assists in the prediction of high-risk children who warrant surveillance and early intervention. This review describes the application of conventional and advanced MRI with very preterm neonates, specifically focusing on the relationship between neonatal MRI findings and later neurodevelopmental outcome. Research demonstrates that conventional MRI is strongly associated with neurodevelopmental outcome in childhood. Further studies are needed to examine the role of advanced MRI techniques in predicting outcome in very preterm children, but early research findings are promising. In conclusion, neonatal MRI is predictive of later neurodevelopment but is dependent on appropriately trained specialists and should be interpreted in conjunction with other clinical and social information.

Use of resting-state functional MRI to study brain development and injury in neonates

Advances in methodology have led to expanded application of resting-state functional MRI (rs-fMRI) to the study of term and prematurely born infants during the first years of life, providing fresh insight into the earliest forms of functional cerebral development. In this review, we detail our evolving understanding of the use of rs-fMRI for studying neonates. We initially focus on the biological processes of cortical development related to resting-state network development. We then review technical issues principally affecting neonatal investigations, including the effects of subject motion during acquisition and image distortions related to magnetic susceptibility effects. We next summarize the literature in which rs-fMRI is used to study normal brain development during the early postnatal period, the effects of prematurity, and the effects of cerebral injury. Finally, we review potential future directions for the field, such as the use of complementary imaging modalities and advanced analysis techniques.

Functional Imaging of the Developing Brain at the Bedside Using Diffuse Optical Tomography

While histological studies and conventional magnetic resonance imaging (MRI) investigations have elucidated the trajectory of structural changes in the developing brain, less is known regarding early functional cerebral development. Recent investigations have demonstrated that resting-state functional connectivity MRI (fcMRI) can identify networks of functional cerebral connections in infants. However, technical and logistical challenges frequently limit the ability to perform MRI scans early or repeatedly in neonates, particularly in those at greatest risk for adverse neurodevelopmental outcomes. High-density diffuse optical tomography (HD-DOT), a portable imaging modality, potentially enables early continuous and quantitative monitoring of brain function in infants. We introduce an HD-DOT imaging system that combines advancements in cap design, ergonomics, and data analysis methods to allow bedside mapping of functional brain development in infants. In a cohort of healthy, full-term neonates scanned within the first days of life, HD-DOT results demonstrate strong congruence with those obtained using co-registered, subject-matched fcMRI and reflect patterns of typical brain development. These findings represent a transformative advance in functional neuroimaging in infants, and introduce HD-DOT as a powerful and practical method for quantitative mapping of early functional brain development in normal and high-risk neonates.