Altered functional network connectivity in preterm infants: antecedents of cognitive and motor impairments?

Inhibition abilities and functional brain connectivity in school-aged term-born and preterm-born children

BACKGROUND

Inhibition abilities are known to have impact on self-regulation, behavior, and academic success, and they are frequently impaired in children born preterm. We investigated the possible contributions of resting-state functional brain connectivity to inhibition following preterm birth.

METHODS

Forty-four preterm and 59 term-born participants aged 8-13 years were administered two inhibition tasks and resting-state functional MRI was performed. Functional connectivity (FC) networks were compared between groups using network-based statistics. Associations of FCNs and inhibition abilities were investigated through multivariate linear regression models accounting for the interaction between birth status and inhibition.

RESULTS

NBS revealed weaker FC in children born preterm compared to term-born peers in connections between motor and supplementary motor regions, frontal lobe, precuneus, and insula. Irrespective of birth status, connections between the cerebellum, frontal, and occipital lobes and inter-lobar, subcortical, intra-hemispheric long-range connections were positively correlated with one of the two inhibition tasks.

CONCLUSIONS

Preterm birth results in long-term alterations of FC at network level but these FCN alterations do not specifically account for inhibition problems in children born very preterm.

IMPACT

Irrespective of birth status, significant associations were found between the subdomain of response inhibition and functional connectivity in some subnetworks. A group comparisons of functional brain connectivity measured by rsfMRI in school-aged children born very preterm and at term. The investigation of network-level functional connectivity at rest does not appear adequate to explain differences in inhibition abilities between children born very preterm and at term, hence other imaging techniques might be more suited to explore the underlying neural mechanisms of inhibition abilities in school-aged children born very preterm.

DFC-Igloo: A dynamic functional connectome learning framework for identifying neurodevelopmental biomarkers in very preterm infants

BACKGROUND AND OBJECTIVE

Very preterm infants are susceptible to neurodevelopmental impairments, necessitating early detection of prognostic biomarkers for timely intervention. The study aims to explore possible functional biomarkers for very preterm infants at born that relate to their future cognitive and motor development using resting-state fMRI. Prior studies are limited by the sample size and suffer from efficient functional connectome (FC) construction algorithms that can handle the noisy data contained in neonatal time series, leading to equivocal findings. Therefore, we first propose an enhanced functional connectome construction algorithm as a prerequisite step. We then apply the new FC construction algorithm to our large prospective very preterm cohort to explore multi-level neurodevelopmental biomarkers.

METHODS

There exists an intrinsic relationship between the structural connectome (SC) and FC, with a notable coupling between the two. This observation implies a putative property of graph signal smoothness on the SC as well. Yet, this property has not been fully exploited for constructing intrinsic dFC. In this study, we proposed an advanced dynamic FC (dFC) learning model, dFC-Igloo, which leveraged SC information to iteratively refine dFC estimations by applying graph signal smoothness to both FC and SC. The model was evaluated on artificial small-world graphs and simulated graph signals.

RESULTS

The proposed model achieved the best and most robust recovery of the ground truth graph across different noise levels and simulated SC pairs from the simulation. The model was further applied to a cohort of very preterm infants from five Neonatal Intensive Care Units, where an enhanced dFC was obtained for each infant. Based on the improved dFC, we identified neurodevelopmental biomarkers for neonates across connectome-wide, regional, and subnetwork scales.

CONCLUSION

The identified markers correlate with cognitive and motor developmental outcomes, offering insights into early brain development and potential neurodevelopmental challenges.

Separating group- and individual-level brain signatures in the newborn functional connectome: A deep learning approach

Recent studies indicate that differences in cognition among individuals may be partially attributed to unique brain wiring patterns. While functional connectivity (FC)-based fingerprinting has demonstrated high accuracy in identifying adults, early studies on neonates suggest that individualized FC signatures are absent. We posit that individual uniqueness is present in neonatal FC data and that conventional linear models fail to capture the rapid developmental trajectories characteristic of newborn brains. To explore this hypothesis, we employed a deep generative model, known as a variational autoencoder (VAE), leveraging two extensive public datasets: one comprising resting-state functional MRI (rs-fMRI) scans from 100 adults and the other from 464 neonates. VAE models trained on rs-fMRI from both adults and newborns produced superior age prediction performance (with r between predicted- and actual age ∼ 0.7) and individual identification accuracy (∼45 %) compared to models trained solely on adult or neonatal data. The VAE model also showed significantly higher individual identification accuracy than linear models (=10∼30 %). Importantly, the VAE differentiated connections reflecting age-related changes from those indicative of individual uniqueness, a distinction not possible with linear models. Moreover, we derived 20 latent variables, each corresponding to distinct patterns of cortical functional network (CFNs). These CFNs varied in their representation of brain maturation and individual signatures; notably, certain CFNs that failed to capture neurodevelopmental traits, in fact, exhibited individual signatures. CFNs associated with neonatal neurodevelopment predominantly encompassed unimodal regions such as visual and sensorimotor areas, whereas those linked to individual uniqueness spanned multimodal and transmodal brain regions. The VAE's capacity to extract features from rs-fMRI data beyond the capabilities of linear models positions it as a valuable tool for delineating cognitive traits inherent in rs-fMRI and exploring individualized imaging phenotypes.

Socioeconomic status moderates associations between hippocampal development and cognition in preterms

OBJECTIVE

The hippocampus plays a critical role in cognitive networks. The anterior hippocampus is vulnerable to early-life stress and socioeconomic status (SES) with alterations persisting beyond childhood. How SES modifies the relationship between early hippocampal development and cognition remains poorly understood. This study examined associations between SES, structural and functional development of neonatal hippocampus, and 18-month cognition in very preterm neonates.

METHODS

In total, 179 preterm neonates were followed prospectively. Structural and resting-state functional MRI were obtained early-in-life and at term-equivalent age (median 32.9 and 41.1 weeks post-menstrual age) to calculate anterior and posterior hippocampal volumes and hippocampal functional connectivity strength. Eighteen-month cognition was assessed via Bayley-III. Longitudinal statistical analysis using generalized estimating equations, accounting for birth gestational age, post-menstrual age at scan, sex, and motion, was performed.

RESULTS

SES, measured as maternal education level, modified associations between anterior but not posterior hippocampal volumes and 18-month cognition (interaction term p = 0.005), and between hippocampal connectivity and cognition (interaction term p = 0.05). Greater anterior hippocampal volumes and hippocampal connectivity were associated with higher cognitive scores only in the lowest SES group. Maternal education alone did not predict neonatal hippocampal volume from early-in-life and term.

INTERPRETATION

SES modified the relationship between neonatal hippocampal development and 18-month cognition in very preterm neonates. The lack of direct association between maternal education and neonatal hippocampal volumes indicates that socio-environmental factors beyond the neonatal period contribute to modifying the relationship between hippocampal development and cognition. These findings point toward opportunities to more equitably promote optimal neurodevelopmental outcomes in very preterm infants.

Quantitative Magnetic Resonance Imaging for Neurodevelopmental Outcome Prediction in Neonates Born Extremely Premature-An Exploratory Study

PURPOSE

Neonates born at < 28 weeks of gestation are at risk for neurodevelopmental delay. The aim of this study was to identify quantitative MR-based metrics for the prediction of neurodevelopmental outcomes in extremely preterm neonates.

METHODS

T1-/T2-relaxation times (T1R/T2R), ADC, and fractional anisotropy (FA) of the left/right posterior limb of the internal capsule (PLIC) and the brainstem were determined at term-equivalent ages in a sample of extremely preterm infants (n = 33). Scores for cognitive, language, and motor outcomes were collected at one year corrected-age. Pearson's correlation analyses detected relationships between quantitative measures and outcome data. Stepwise regression procedures identified imaging metrics to estimate neurodevelopmental outcomes.

RESULTS

Cognitive outcomes correlated significantly with T2R (r = 0.412; p = 0.017) and ADC (r = -0.401; p = 0.021) (medulla oblongata). Furthermore, there were significant correlations between motor outcomes and T1R (pontine tegmentum (r = 0.346; p = 0.049), midbrain (r = 0.415; p = 0.016), right PLIC (r = 0.513; p = 0.002), and left PLIC (r = 0.504; p = 0.003)); T2R (right PLIC (r = 0.405; p = 0.019)); ADC (medulla oblongata (r = -0.408; p = 0.018) and pontine tegmentum (r = -0.414; p = 0.017)); and FA (pontine tegmentum (r = -0.352; p = 0.045)). T2R/ADC (medulla oblongata) (cognitive outcomes (R2 = 0.296; p = 0.037)) and T1R (right PLIC)/ADC (medulla oblongata) (motor outcomes (R2 = 0.405; p = 0.009)) revealed predictive potential for neurodevelopmental outcomes.

CONCLUSION

There are relationships between relaxometry‑/DTI-based metrics determined by neuroimaging near term and neurodevelopmental outcomes collected at one year of age. Both modalities bear prognostic potential for the prediction of cognitive and motor outcomes. Thus, quantitative MRI at term-equivalent ages represents a promising approach with which to estimate neurologic development in extremely preterm infants.

Prenatal Opioid Exposure and Risk for Adverse Brain and Motor Outcomes in Infants Born Premature

OBJECTIVE

To compare brain magnetic resonance imaging (MRI) biomarkers and neurodevelopmental test scores in infants born preterm with and without prenatal opioid exposure (POE).

STUDY DESIGN

We examined 395 preterm infants (≤32 weeks gestational age) who had term-equivalent brain MRIs, composite scores from the Bayley Scales of Infant and Toddler Development-III at 2 years corrected age, and POE data. MRI parameters included total/regional brain volumes and severe punctate white matter lesions (PWMLs). We conducted bivariable analysis and multivariable logistic regression analyses.

RESULTS

The mean ± SD gestational age was 29.3 ± 2.5 weeks; 35 (8.9%) had POE and 20 (5.1%) had severe PWML. Compared with unexposed infants, those with POE exhibited higher rates of severe PWML (17.1% vs 3.9%, respectively; P = .002); findings remained significant with an OR of 4.16 (95% CI, 1.26-13.68) after adjusting for confounders. On mediation analysis, the significant relationship between POE and severe PWML was not indirectly mediated through preterm birth/gestational age (OR, 0.93; 95% CI, 0.78-1.10), thus suggesting the association was largely driven by a direct adverse effect of POE on white matter. In multivariable analyses, POE was associated with a significantly lower score by -6.2 (95% CI, -11.8 to -0.6) points on the Bayley Scales of Infant and Toddler Development-III Motor subscale compared with unexposed infants.

CONCLUSIONS

POE was associated with severe PWML; this outcome may be a direct effect of POE rather than being mediated by premature birth. POE was also associated with worse motor development. Continued follow-up to understand the long-term effects of POE is warranted.

Bedtime to the brain: how infants' sleep behaviours intertwine with non-rapid eye movement sleep electroencephalography features

Adequate sleep is critical for development and facilitates the maturation of the neurophysiological circuitries at the basis of cognitive and behavioural function. Observational research has associated early life sleep problems with worse later cognitive, psychosocial, and somatic health outcomes. Yet, the extent to which day-to-day sleep behaviours (e.g., duration, regularity) in early life relate to non-rapid eye movement (NREM) neurophysiology-acutely and the long-term-remains to be studied. We measured sleep behaviours in 32 healthy 6-month-olds assessed with actimetry and neurophysiology with high-density electroencephalography (EEG) to investigate the association between NREM sleep and habitual sleep behaviours. Our study revealed four findings: first, daytime sleep behaviours are related to EEG slow-wave activity (SWA). Second, night-time movement and awakenings from sleep are connected with spindle density. Third, habitual sleep timing is linked to neurophysiological connectivity quantified as delta coherence. And lastly, delta coherence at 6 months predicts night-time sleep duration at 12 months. These novel findings widen our understanding that infants' sleep behaviours are closely intertwined with three particular levels of neurophysiology: sleep pressure (determined by SWA), the maturation of the thalamocortical system (spindles), and the maturation of cortical connectivity (coherence). The crucial next step is to extend this concept to clinical groups to objectively characterise infants' sleep behaviours 'at risk' that foster later neurodevelopmental problems.

Altered resting-state functional connectivity in newborns with hypoxic ischemic encephalopathy assessed using high-density functional near-infrared spectroscopy

Hypoxic-ischemic encephalopathy (HIE) results from a lack of oxygen to the brain during the perinatal period. HIE can lead to mortality and various acute and long-term morbidities. Improved bedside monitoring methods are needed to identify biomarkers of brain health. Functional near-infrared spectroscopy (fNIRS) can assess resting-state functional connectivity (RSFC) at the bedside. We acquired resting-state fNIRS data from 21 neonates with HIE (postmenstrual age [PMA] = 39.96), in 19 neonates the scans were acquired post-therapeutic hypothermia (TH), and from 20 term-born healthy newborns (PMA = 39.93). Twelve HIE neonates also underwent resting-state functional magnetic resonance imaging (fMRI) post-TH. RSFC was calculated as correlation coefficients amongst the time courses for fNIRS and fMRI data, respectively. The fNIRS and fMRI RSFC maps were comparable. RSFC patterns were then measured with graph theory metrics and compared between HIE infants and healthy controls. HIE newborns showed significantly increased clustering coefficients, network efficiency and modularity compared to controls. Using a support vector machine algorithm, RSFC features demonstrated good performance in classifying the HIE and healthy newborns in separate groups. Our results indicate the utility of fNIRS-connectivity patterns as potential biomarkers for HIE and fNIRS as a new bedside tool for newborns with HIE.

Myelination of preterm brain networks at adolescence

Prematurity and preterm stressors severely affect the development of infants born before 37 weeks of gestation, with increasing effects seen at earlier gestations. Although preterm mortality rates have declined due to the advances in neonatal care, disability rates, especially in middle-income settings, continue to grow. With the advances in MR imaging technology, there has been a focus on safely imaging the preterm brain to better understand its development and discover the brain regions and networks affected by prematurity. Such studies aim to support interventions and improve the neurodevelopment of preterm infants and deliver accurate prognoses. Few studies, however, have focused on the fully developed brain of preterm born infants, especially in extremely preterm subjects. To assess the long-term effect of prematurity on the adult brain, myelin related biomarkers such as myelin water fraction and g-ratio are measured for a cohort of 19-year-old extremely preterm born subjects. Using multi-modal imaging techniques that combine T2 relaxometry and neurite density information, the results show that specific brain regions associated with white matter injuries due to preterm birth, such as the posterior limb of the internal capsule and corpus callosum, are still less myelinated in adulthood. Furthermore, a weak positive relationship between myelin water fraction values and Full-Scale Intelligence Quotient (FSIQ) scores was found in multiple brain regions previously defined as less myelinated in the Extremely Preterm (EPT) cohort. These findings might suggest altered connectivity in the adult preterm brain and explain differences in cognitive outcomes.

Longitudinal neonatal brain development and socio-demographic correlates of infant outcomes following preterm birth

Preterm birth results in premature exposure of the brain to the extrauterine environment during a critical period of neurodevelopment. Consequently, infants born preterm are at a heightened risk of adverse behavioural outcomes in later life. We characterise longitudinal development of neonatal regional brain volume and functional connectivity in the first weeks following preterm birth, sociodemographic factors, and their respective relationships to psychomotor outcomes and psychopathology in toddlerhood. We study 121 infants born preterm who underwent magnetic resonance imaging shortly after birth, at term-equivalent age, or both. Longitudinal regional brain volume and functional connectivity were modelled as a function of psychopathology and psychomotor outcomes at 18 months. Better psychomotor functioning in toddlerhood was associated with greater relative right cerebellar volume and a more rapid decrease over time of sensorimotor degree centrality in the neonatal period. In contrast, increased 18-month psychopathology was associated with a more rapid decrease in relative regional subcortical volume. Furthermore, while socio-economic deprivation was related to both psychopathology and psychomotor outcomes, cognitively stimulating parenting predicted psychopathology only. Our study highlights the importance of longitudinal imaging to better predict toddler outcomes following preterm birth, as well as disparate environmental influences on separable facets of behavioural development in this population.

Development of neonatal brain functional centrality and alterations associated with preterm birth

Formation of the functional connectome in early life underpins future learning and behavior. However, our understanding of how the functional organization of brain regions into interconnected hubs (centrality) matures in the early postnatal period is limited, especially in response to factors associated with adverse neurodevelopmental outcomes such as preterm birth. We characterized voxel-wise functional centrality (weighted degree) in 366 neonates from the Developing Human Connectome Project. We tested the hypothesis that functional centrality matures with age at scan in term-born babies and is disrupted by preterm birth. Finally, we asked whether neonatal functional centrality predicts general neurodevelopmental outcomes at 18 months. We report an age-related increase in functional centrality predominantly within visual regions and a decrease within the motor and auditory regions in term-born infants. Preterm-born infants scanned at term equivalent age had higher functional centrality predominantly within visual regions and lower measures in motor regions. Functional centrality was not related to outcome at 18 months old. Thus, preterm birth appears to affect functional centrality in regions undergoing substantial development during the perinatal period. Our work raises the question of whether these alterations are adaptive or disruptive and whether they predict neurodevelopmental characteristics that are more subtle or emerge later in life.

Early life factors and hippocampal functional connectivity in children with overweight/obesity

OBJECTIVE

We investigated the association of anthropometric neonatal data (birth length and birth weight) and breastfeeding practices (exclusive and any breastfeeding) with hippocampal functional connectivity and its academic implication in children with overweight/obesity.

METHODS

Ninety six children with overweight/obesity aged 8-11 years (10.01 ± 1.14), from the ActiveBrains project were included in this cross-sectional study. Anthropometric neonatal data were collected from birth records, whereas breastfeeding practices were reported by parents. A 3.0 Tesla Siemens Magnetom Tim Trio system was used to acquire T1-weighted and resting-state functional magnetic resonance images. Academic performance was assessed by the Woodcock-Muñoz standardized test. Hippocampal seed-based methods with post-hoc regression analyses were performed. Analyses were considered significant when surpassing Family-Wise Error corrections.

RESULTS

Birth weight showed a positive association with the connectivity between the hippocampus and the pre- and postcentral gyri, and the cerebellum. In addition, breastfeeding was negatively associated with the connectivity between the hippocampus and the primary motor cortex and the angular gyrus. Any breastfeeding, in turn, showed a positive association with the connectivity between the hippocampus and the middle temporal gyrus. None of the connectivity outcomes related to early life factors was coupled with better academic abilities (all p > 0.05).

CONCLUSIONS

Our findings suggest that birth weight at birth and breastfeeding are associated with hippocampal connectivity in children with overweight/obesity. Despite this, how the results relate to academic performance remains a matter of speculation. Our findings suggest that clinicians should recognize the importance early life factors for potentially avoiding consequences on offspring's brain development.

Altered development of structural MRI connectome hubs at near-term age in very and moderately preterm infants

Preterm infants may exhibit altered developmental patterns of the brain structural network by endogenous and exogenous stimuli, which are quantifiable through hub and modular network topologies that develop in the third trimester. Although preterm brain networks can compensate for white matter microstructural abnormalities of core connections, less is known about how the network developmental characteristics of preterm infants differ from those of full-term infants. We identified 13 hubs and 4 modules and revealed subtle differences in edgewise connectivity and local network properties between 134 preterm and 76 full-term infants, identifying specific developmental patterns of the brain structural network in preterm infants. The modules of preterm infants showed an imbalanced composition. The edgewise connectivity in preterm infants showed significantly decreased long- and short-range connections and local network properties in the dorsal superior frontal gyrus. In contrast, the fusiform gyrus and several nonhub regions showed significantly increased wiring of short-range connections and local network properties. Our results suggested that decreased local network in the frontal lobe and excessive development in the occipital lobe may contribute to the understanding of brain developmental deviances in preterm infants.

Neonatal motor functional connectivity and motor outcomes at age two years in very preterm children with and without high-grade brain injury

Preterm-born children have high rates of motor impairments, but mechanisms for early identification remain limited. We hypothesized that neonatal motor system functional connectivity (FC) would relate to motor outcomes at age two years; currently, this relationship is not yet well-described in very preterm (VPT; born <32 weeks' gestation) infants with and without brain injury. We recruited 107 VPT infants - including 55 with brain injury (grade III-IV intraventricular hemorrhage, cystic periventricular leukomalacia, post-hemorrhagic hydrocephalus) - and collected FC data at/near term-equivalent age (35-45 weeks postmenstrual age). Correlation coefficients were used to calculate the FC between bilateral motor and visual cortices and thalami. At two years corrected-age, motor outcomes were assessed with the Bayley Scales of Infant and Toddler Development, 3rd edition. Multiple imputation was used to estimate missing data, and regression models related FC measures to motor outcomes. Within the brain-injured group only, interhemispheric motor cortex FC was positively related to gross motor outcomes. Thalamocortical and visual FC were not related to motor scores. This suggests neonatal alterations in motor system FC may provide prognostic information about impairments in children with brain injury.

Diurnal variations of resting-state fMRI data: A graph-based analysis

Circadian rhythms (lasting approximately 24 h) control and entrain various physiological processes, ranging from neural activity and hormone secretion to sleep cycles and eating habits. Several studies have shown that time of day (TOD) is associated with human cognition and brain functions. In this study, utilizing a chronotype-based paradigm, we applied a graph theory approach on resting-state functional MRI (rs-fMRI) data to compare whole-brain functional network topology between morning and evening sessions and between morning-type (MT) and evening-type (ET) participants. Sixty-two individuals (31 MT and 31 ET) underwent two fMRI sessions, approximately 1 hour (morning) and 10 h (evening) after their wake-up time, according to their declared habitual sleep-wake pattern on a regular working day. In the global analysis, the findings revealed the effect of TOD on functional connectivity (FC) patterns, including increased small-worldness, assortativity, and synchronization across the day. However, we identified no significant differences based on chronotype categories. The study of the modular structure of the brain at mesoscale showed that functional networks tended to be more integrated with one another in the evening session than in the morning session. Local/regional changes were affected by both factors (i.e., TOD and chronotype), mostly in areas associated with somatomotor, attention, frontoparietal, and default networks. Furthermore, connectivity and hub analyses revealed that the somatomotor, ventral attention, and visual networks covered the most highly connected areas in the morning and evening sessions: the latter two were more active in the morning sessions, and the first was identified as being more active in the evening. Finally, we performed a correlation analysis to determine whether global and nodal measures were associated with subjective assessments across participants. Collectively, these findings contribute to an increased understanding of diurnal fluctuations in resting brain activity and highlight the role of TOD in future studies on brain function and the design of fMRI experiments.

Magnetic resonance spectroscopy brain metabolites at term and 3-year neurodevelopmental outcomes in very preterm infants

BACKGROUND

Noninvasive advanced neuroimaging and neurochemical assessment can identify subtle abnormalities and predict neurodevelopmental impairments. Our objective was to quantify white matter metabolite levels and evaluate their relationship with neurodevelopmental outcomes at age 3 years.

METHODS

Our study evaluated a longitudinal prospective cohort of very premature infants (<32 weeks gestational age) with single-voxel proton magnetic resonance spectroscopy from the centrum semiovale performed at term-equivalent age and standardized cognitive, verbal, and motor assessments at 3 years corrected age. We separately examined metabolite ratios in the left and right centrum semiovale. We also conducted an exploratory interaction analysis for high/low socioeconomic status (SES) to evaluate the relationship between metabolites and neurodevelopmental outcomes, after adjusting for confounders.

RESULTS

We found significant relationships between choline/creatine levels in the left and right centrum semiovale and motor development scores. Exploratory interaction analyses revealed that, for infants with low SES, there was a negative association between choline/creatine in the left centrum semiovale and motor assessment scores at age 3 years.

CONCLUSIONS

Brain metabolites from the centrum semiovale at term-equivalent age were associated with motor outcomes for very preterm infants at 3 years corrected age. This effect may be most pronounced for infants with low SES.

IMPACT

Motor development at 3 years corrected age for very preterm infants is inversely associated with choline neurochemistry within the centrum semiovale on magnetic resonance spectroscopy at term-equivalent age, especially in infants with low socioeconomic status. No prior studies have studied metabolites in the centrum semiovale to predict neurodevelopmental outcomes at 3 years corrected age based on high/low socioeconomic status. For very preterm infants with lower socioeconomic status, higher choline-to-creatine ratio in central white matter is associated with worse neurodevelopmental outcomes.

Early development of sleep and brain functional connectivity in term-born and preterm infants

The proper development of sleep and sleep-wake rhythms during early neonatal life is crucial to lifelong neurological well-being. Recent data suggests that infants who have poor quality sleep demonstrate a risk for impaired neurocognitive outcomes. Sleep ontogenesis is a complex process, whereby alternations between rudimentary brain states-active vs. wake and active sleep vs. quiet sleep-mature during the last trimester of pregnancy. If the infant is born preterm, much of this process occurs in the neonatal intensive care unit, where environmental conditions might interfere with sleep. Functional brain connectivity (FC), which reflects the brain's ability to process and integrate information, may become impaired, with ensuing risks of compromised neurodevelopment. However, the specific mechanisms linking sleep ontogenesis to the emergence of FC are poorly understood and have received little investigation, mainly due to the challenges of studying causal links between developmental phenomena and assessing FC in newborn infants. Recent advancements in infant neuromonitoring and neuroimaging strategies will allow for the design of interventions to improve infant sleep quality and quantity. This review discusses how sleep and FC develop in early life, the dynamic relationship between sleep, preterm birth, and FC, and the challenges associated with understanding these processes. IMPACT: Sleep in early life is essential for proper functional brain development, which is essential for the brain to integrate and process information. This process may be impaired in infants born preterm. The connection between preterm birth, early development of brain functional connectivity, and sleep is poorly understood. This review discusses how sleep and brain functional connectivity develop in early life, how these processes might become impaired, and the challenges associated with understanding these processes. Potential solutions to these challenges are presented to provide direction for future research.

Differential age-dependent development of inter-area brain connectivity in term and preterm neonates

BACKGROUND

Among preterm infants, higher morbidities of neurological disturbances and developmental delays are critical issues. Resting-state networks (RSNs) in the brain are suitable measures for assessing higher-level neurocognition. Since investigating task-related brain activity is difficult in neonates, assessment of RSNs provides invaluable insight into their neurocognitive development.

METHODS

The participants, 32 term and 71 preterm neonates, were divided into three groups based on gestational age (GA) at birth. Cerebral hemodynamic activity of RSNs was measured using functional near-infrared spectroscopy in the temporal, frontal, and parietal regions.

RESULTS

High-GA preterm infants (GA ≥ 30 weeks) had a significantly stronger RSN than low-GA preterm infants and term infants. Regression analyses of RSNs as a function of postnatal age (PNA) revealed a steeper regression line in the high-GA preterm and term infants than in the low-GA infants, particularly for inter-area brain connectivity between the frontal and left temporal areas.

CONCLUSIONS

Slower PNA-dependent development of the frontal-temporal network found only in the low-GA group suggests that significant brain growth optimal in the intrauterine environment takes place before 30 weeks of gestation. The present study suggests a likely reason for the high incidence of neurodevelopmental impairment in early preterm infants.

IMPACT

Resting-state fNIRS measurements in three neonate groups differing in gestational age (GA) showed stronger networks in the high-GA preterm infants than in the term and low-GA infants, which was partly explained by postnatal age (PNA). Regression analyses revealed a similar PNA-dependence in the development of the inter-area networks in the frontal and temporal lobes in the high-GA and term infants, and significantly slower development in the low-GA infants. These results suggest that optimal intrauterine brain growth takes place before 30 weeks of gestation. This explains one of the reasons for the high incidence of neurodevelopmental impairment in early preterm infants.

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.

The cerebrospinal fluid proteome of preterm infants predicts neurodevelopmental outcome

BACKGROUND

Survival rate increases for preterm infants, but long-term neurodevelopmental outcome predictors are lacking. Our primary aim was to determine whether a specific proteomic profile in cerebrospinal fluid (CSF) of preterm infants differs from that of term infants and to identify novel biomarkers of neurodevelopmental outcome in preterm infants.

METHODS

Twenty-seven preterm infants with median gestational age 27 w + 4 d and ten full-term infants were enrolled prospectively. Protein profiling of CSF were performed utilizing an antibody suspension bead array. The relative levels of 178 unique brain derived proteins and inflammatory mediators, selected from the Human Protein Atlas, were measured.

RESULTS

The CSF protein profile of preterm infants differed from that of term infants. Increased levels of brain specific proteins that are associated with neurodevelopment and neuroinflammatory pathways made up a distinct protein profile in the preterm infants. The most significant differences were seen in proteins involved in neurodevelopmental regulation and synaptic plasticity, as well as components of the innate immune system. Several proteins correlated with favorable outcome in preterm infants at 18-24 months corrected age. Among the proteins that provided strong predictors of outcome were vascular endothelial growth factor C, Neurocan core protein and seizure protein 6, all highly important in normal brain development.

CONCLUSION

Our data suggest a vulnerability of the preterm brain to postnatal events and that alterations in protein levels may contribute to unfavorable neurodevelopmental outcome.

Association between brain structural network efficiency at term-equivalent age and early development of cerebral palsy in very preterm infants

Very preterm infants (born at less than 32 weeks gestational age) are at high risk for serious motor impairments, including cerebral palsy (CP). The brain network changes that antecede the early development of CP in infants are not well characterized, and a better understanding may suggest new strategies for risk-stratification at term, which could lead to earlier access to therapies. Graph theoretical methods applied to diffusion MRI-derived brain connectomes may help quantify the organization and information transfer capacity of the preterm brain with greater nuance than overt structural or regional microstructural changes. Our aim was to shed light on the pathophysiology of early CP development, before the occurrence of early intervention therapies and other environmental confounders, to help identify the best early biomarkers of CP risk in VPT infants. In a cohort of 395 very preterm infants, we extracted cortical morphometrics and brain volumes from structural MRI and also applied graph theoretical methods to diffusion MRI connectomes, both acquired at term-equivalent age. Metrics from graph network analysis, especially global efficiency, strength values of the major sensorimotor tracts, and local efficiency of the motor nodes and novel non-motor regions were strongly inversely related to early CP diagnosis. These measures remained significantly associated with CP after correction for common risk factors of motor development, suggesting that metrics of brain network efficiency at term may be sensitive biomarkers for early CP detection. We demonstrate for the first time that in VPT infants, early CP diagnosis is anteceded by decreased brain network segregation in numerous nodes, including motor regions commonly-associated with CP and also novel regions that may partially explain the high rate of cognitive impairments concomitant with CP diagnosis. These advanced MRI biomarkers may help identify the highest risk infants by term-equivalent age, facilitating earlier interventions that are informed by early pathophysiological changes.

Deep Multimodal Learning From MRI and Clinical Data for Early Prediction of Neurodevelopmental Deficits in Very Preterm Infants

The prevalence of disabled survivors of prematurity has increased dramatically in the past 3 decades. These survivors, especially, very preterm infants (VPIs), born ≤ 32 weeks gestational age, are at high risk for neurodevelopmental impairments. Early and clinically effective personalized prediction of outcomes, which forms the basis for early treatment decisions, is urgently needed during the peak neuroplasticity window—the first couple of years after birth—for at-risk infants, when intervention is likely to be most effective. Advances in MRI enable the noninvasive visualization of infants' brains through acquired multimodal images, which are more informative than unimodal MRI data by providing complementary/supplementary depicting of brain tissue characteristics and pathology. Thus, analyzing quantitative multimodal MRI features affords unique opportunities to study early postnatal brain development and neurodevelopmental outcome prediction in VPIs. In this study, we investigated the predictive power of multimodal MRI data, including T2-weighted anatomical MRI, diffusion tensor imaging, resting-state functional MRI, and clinical data for the prediction of neurodevelopmental deficits. We hypothesize that integrating multimodal MRI and clinical data improves the prediction over using each individual data modality. Employing the aforementioned multimodal data, we proposed novel end-to-end deep multimodal models to predict neurodevelopmental (i.e., cognitive, language, and motor) deficits independently at 2 years corrected age. We found that the proposed models can predict cognitive, language, and motor deficits at 2 years corrected age with an accuracy of 88.4, 87.2, and 86.7%, respectively, significantly better than using individual data modalities. This current study can be considered as proof-of-concept. A larger study with external validation is important to validate our approach to further assess its clinical utility and overall generalizability.

Sustained peripheral immune hyper-reactivity (SPIHR): an enduring biomarker of altered inflammatory responses in adult rats after perinatal brain injury

Background

Chorioamnionitis (CHORIO) is a principal risk factor for preterm birth and is the most common pathological abnormality found in the placentae of preterm infants. CHORIO has a multitude of effects on the maternal–placental–fetal axis including profound inflammation. Cumulatively, these changes trigger injury in the developing immune and central nervous systems, thereby increasing susceptibility to chronic sequelae later in life. Despite this and reports of neural–immune changes in children with cerebral palsy, the extent and chronicity of the peripheral immune and neuroinflammatory changes secondary to CHORIO has not been fully characterized.

Methods

We examined the persistence and time course of peripheral immune hyper-reactivity in an established and translational model of perinatal brain injury (PBI) secondary to CHORIO. Pregnant Sprague–Dawley rats underwent laparotomy on embryonic day 18 (E18, preterm equivalent). Uterine arteries were occluded for 60 min, followed by intra-amniotic injection of lipopolysaccharide (LPS). Serum and peripheral blood mononuclear cells (PBMCs) were collected at young adult (postnatal day P60) and middle-aged equivalents (P120). Serum and PBMCs secretome chemokines and cytokines were assayed using multiplex electrochemiluminescent immunoassay. Multiparameter flow cytometry was performed to interrogate immune cell populations.

Results

Serum levels of interleukin-1β (IL-1β), IL-5, IL-6, C–X–C Motif Chemokine Ligand 1 (CXCL1), tumor necrosis factor-α (TNF-α), and C–C motif chemokine ligand 2/monocyte chemoattractant protein-1 (CCL2/MCP-1) were significantly higher in CHORIO animals compared to sham controls at P60. Notably, CHORIO PBMCs were primed. Specifically, they were hyper-reactive and secreted more inflammatory mediators both at baseline and when stimulated in vitro. While serum levels of cytokines normalized by P120, PBMCs remained primed, and hyper-reactive with a robust pro-inflammatory secretome concomitant with a persistent change in multiple T cell populations in CHORIO animals.

Conclusions

The data indicate that an in utero inflammatory insult leads to neural–immune changes that persist through adulthood, thereby conferring vulnerability to brain and immune system injury throughout the lifespan. This unique molecular and cellular immune signature including sustained peripheral immune hyper-reactivity (SPIHR) and immune cell priming may be a viable biomarker of altered inflammatory responses following in utero insults and advances our understanding of the neuroinflammatory cascade that leads to perinatal brain injury and later neurodevelopmental disorders, including cerebral palsy.

Diffuse white matter abnormality in very preterm infants at term reflects reduced brain network efficiency

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Most preterm infants exhibit regions of high signal intensity on T2 MRI at term.

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Debate remains as to whether this signal (DWMA) is pathological.

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We quantified DWMA and used graph theory to measure brain network efficiency.

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Whole-brain and regional network efficiency at term decreased with greater DWMA.

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DWMA in very preterm infants is associated with reduced brain efficiency at term.

Between 50 and 80% of very preterm infants (<32 weeks gestational age) exhibit increased white matter signal intensity on T2-weighted MRI at term-equivalent age, known as diffuse white matter abnormality (DWMA). A few studies have linked DWMA with microstructural abnormalities, but the exact relationship remains poorly understood. We related DWMA extent to graph theory measures of network efficiency at term in a representative cohort of 343 very preterm infants. We performed anatomic and diffusion MRI at term and quantified DWMA volume with our novel, semi-automated algorithm. From diffusion-weighted structural connectomes, we calculated the graph theory metrics local efficiency and clustering coefficient, which measure the ability of groups of nodes to perform specialized processing, and global efficiency, which assesses the ability of brain regions to efficiently combine information. We computed partial correlations between these measures and DWMA volume, adjusted for confounders. Increasing DWMA volume was associated with decreased global efficiency of the entire very preterm brain and decreased local efficiency and clustering coefficient in a variety of regions supporting cognitive, linguistic, and motor function. We show that DWMA is associated with widespread decreased brain network efficiency, suggesting that it is pathologic and likely has adverse developmental consequences.

Effect of first-month head-size growth trajectory on cognitive outcomes in preterm infants

BACKGROUND

To examine whether the patterns of head-size growth trajectory in the first month after birth are associated with different susceptibility to cognitive impairment outcomes at age 24 months.

METHODS

This retrospective cohort study included 590 infants of very-preterm survivors born between 2001 and 2016 receiving neurodevelopmental assessment at age 24 months. 403 children were enrolled for analysis after excluding infants with small-for-gestational age and severe brain injury. The head circumference (HC) growth evaluated weekly in the first month after birth compared to the at-birth HC was analyzed using group-based trajectory modeling. Neurocognition outcomes were determined as normal, borderline delay, or impaired using the Bayley Scales of Infant Development.

RESULTS

The HC growth dynamics in the first month after birth showed three trajectory patterns: delayed catch-up (31.5%), slow catch-up (54.0%), and fast catch-up (14.5%), which significantly corresponded to different rates of impaired cognition at 19.5%, 6.0%, and 8.5%, respectively (p < 0.001). While 60% of the fast catch-up group had normal cognition, only one-third of the delayed catch-up group showed normal cognition. Three neonatal risk factors, gestational age (p = 0.006), respiratory distress syndrome requiring surfactant therapy (p = 0.012), and hemodynamically significant patent ductus arteriosus requiring intervention (p = 0.047) significantly affected HC growth trajectory patterning that led to cognitive impairment outcomes at follow-up.

CONCLUSIONS

Preterm infants with delayed catch-up of head-size growth in the first month of age is susceptible to cognitive impairment outcome.

Resting-state brain networks in neonatal hypoxic-ischemic brain damage: a functional near-infrared spectroscopy study

Significance: There is an emerging need for convenient and continuous bedside monitoring of full-term newborns with hypoxic-ischemic brain damage (HIBD) to determine whether early intervention is required. Functional near-infrared spectroscopy (fNIRS)-based resting-state brain network analysis, which could provide an effective evaluation method, remains to be extensively studied. Aim: Our study aims to verify the feasibility of fNIRS-based resting-state brain networks for evaluating brain function in infants with HIBD to provide a new and effective means for clinical research in neonatal HIBD. Approach: Thirteen neonates with HIBD were scanned using fNIRS in the resting state. The brain network properties were explored to attempt to extract effective features as recognition indicators. Results: Compared with healthy controls, newborns with HIBD showed decreased brain functional connectivity. Specifically, there were severe losses of long-range functional connectivity of the contralateral parietal-temporal lobe, contralateral parietal-frontal lobe, and contralateral parietal lobe. The node degree showed a widespread decrease in the left frontal middle gyrus, left superior frontal gyrus dorsal, and right central posterior gyrus. However, newborns with HIBD showed a significantly higher local network efficiency (* p < 0.05 ). Subsequently, network indicators based on small-worldness, local efficiency, modularity, and normalized clustering coefficient were extracted for HIBD identification with the accuracy observed as 79.17%. Conclusions: Our findings indicate that fNIRS-based resting-state brain network analysis could support early HIBD diagnosis.

Early protein intake predicts functional connectivity and neurocognition in preterm born children

Nutritional intake can promote early neonatal brain development in very preterm born neonates (< 32 weeks’ gestation). In a group of 7-year-old very preterm born children followed since birth, we examined whether early nutrient intake in the first weeks of life would be associated with long-term brain function and neurocognitive skills at school age. Children underwent resting-state functional MRI (fMRI), intelligence testing (Wechsler Intelligence Scale for Children, 5th Ed) and visual-motor processing (Beery-Buktenica, 5th Ed) at 7 years. Relationships were assessed between neonatal macronutrient intakes, functional connectivity strength between thalamic and default mode networks (DMN), and neuro-cognitive function using multivariable regression. Greater functional connectivity strength between thalamic networks and DMN was associated with greater intake of protein in the first week (β = 0.17; 95% CI 0.11, 0.23, p < 0.001) but lower intakes of fat (β = − 0.06; 95% CI − 0.09, − 0.02, p = 0.001) and carbohydrates (β = − 0.03; 95% CI − 0.04, − 0.01, p = 0.003). Connectivity strength was also associated with protein intake during the first month (β = 0.22; 95% CI 0.06, 0.37, p = 0.006). Importantly, greater thalamic-DMN connectivity strength was associated with higher processing speed indices (β = 26.9; 95% CI 4.21, 49.49, p = 0.02) and visual processing scores (β = 9.03; 95% CI 2.27, 15.79, p = 0.009). Optimizing early protein intake may contribute to promoting long-term brain health in preterm-born children.

Identifying Diurnal Variability of Brain Connectivity Patterns Using Graph Theory

Significant differences exist in human brain functions affected by time of day and by people’s diurnal preferences (chronotypes) that are rarely considered in brain studies. In the current study, using network neuroscience and resting-state functional MRI (rs-fMRI) data, we examined the effect of both time of day and the individual’s chronotype on whole-brain network organization. In this regard, 62 participants (39 women; mean age: 23.97 ± 3.26 years; half morning- versus half evening-type) were scanned about 1 and 10 h after wake-up time for morning and evening sessions, respectively. We found evidence for a time-of-day effect on connectivity profiles but not for the effect of chronotype. Compared with the morning session, we found relatively higher small-worldness (an index that represents more efficient network organization) in the evening session, which suggests the dominance of sleep inertia over the circadian and homeostatic processes in the first hours after waking. Furthermore, local graph measures were changed, predominantly across the left hemisphere, in areas such as the precentral gyrus, putamen, inferior frontal gyrus (orbital part), inferior temporal gyrus, as well as the bilateral cerebellum. These findings show the variability of the functional neural network architecture during the day and improve our understanding of the role of time of day in resting-state functional networks.

Oxytocin modulates local topography of human functional connectome in healthy men at rest

Oxytocin has recently received remarkable attention for its role as a modulator of human behaviour. Here, we aimed to expand our knowledge of the neural circuits engaged by oxytocin by investigating the effects of intranasal and intravenous oxytocin on the functional connectome at rest in 16 healthy men. Oxytocin modulates the functional connectome within discrete neural systems, but does not affect the global capacity for information transfer. These local effects encompass key hubs of the oxytocin system (e.g. amygdala) but also regions overlooked in previous hypothesis-driven research (i.e. the visual circuits, temporal lobe and cerebellum). Increases in levels of oxytocin in systemic circulation induce broad effects on the functional connectome, yet we provide indirect evidence supporting the involvement of nose-to-brain pathways in at least some of the observed changes after intranasal oxytocin. Together, our results suggest that oxytocin effects on human behaviour entail modulation of multiple levels of brain processing distributed across different systems.

Breastfeeding improves dynamic reorganization of functional connectivity in preterm infants: a temporal brain network study

Substantial evidences have shown the benefits of breastfeeding to infants in terms of better nutrition and neurodevelopmental outcome. However, the relationship between brain development and feeding in preterm infants, who are physiologically and developmentally immature at birth, is only beginning to be quantitatively assessed, coinciding with the recent advent of neuroimaging techniques. In the current work, we studied a sample of 50 preterm infants-born between 29 and 33 weeks (32.20 ± 0.89 weeks) of gestational age, where 30 of them were breastfed and the remaining 20 were formula-fed. Resting-state functional magnetic resonance imaging (fMRI) was recorded around term-equivalent age (40.00 ± 1.31 weeks, range 39-44 weeks) using a 1.5-T scanner under sedation condition. Temporal brain networks were estimated by the correlation of sliding time-window time courses among regions of a predefined atlas. Through our newly introduced temporal efficiency approach, we examined, for the first time, the 3D spatiotemporal architecture of the temporal brain network. We found prominent temporal small-world properties in both groups, suggesting the arrangement of dynamic functional connectivity permits effective coordination of various brain regions for efficient information transfer over time at both local and global levels. More importantly, we showed that breastfed preterm infants exhibited greater temporal global efficiency in comparison with formula-fed preterm infants. Specifically, we found localized elevation of temporal nodal properties in the right temporal gyrus and bilateral caudate. Taken together, these findings provide new evidence to support the notion that breast milk promotes early brain development and cognitive function, which may have neurobiological and public health implications for parents and pediatricians.Breastfeeding has long been recognized to have beneficial effect on early neurodevelopment in infants. However, the influence of breastfeeding on reorganization of functional connectivity in preterm infants are largely unknown. To this end, we utilized our recently developed temporal brain network analysis framework to investigate the dynamic reorganization of brain functional connectivity in preterm infants fed with breast milk. We found that beyond an optimal temporal small-world topology, breastfed preterm infants exhibited improved network efficiency at both global and regional levels in comparisons with those of formula-fed infants. Graphical abstract: Breastfeeding has long been recognized to have beneficial effect on early neurodevelopment in infants. However, the influence of breastfeeding on reorganization of brain functional connectivity in preterm infants are largely unknown. To this end, we utilized our recently developed temporal brain network analysis framework to investigate the dynamic reorganization of functional connectivity in preterm infants fed with breast milk. We found that beyond an optimal temporal small-world topology, breastfed preterm infants exhibited improved network efficiency at both global and regional levels in comparisons with those of formula-fed infants.

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.

Current Evidence on Cell Death in Preterm Brain Injury in Human and Preclinical Models

Despite tremendous advances in neonatal intensive care over the past 20 years, prematurity carries a high burden of neurological morbidity lasting lifelong. The term encephalopathy of prematurity (EoP) coined by Volpe in 2009 encompasses all aspects of the now known effects of prematurity on the immature brain, including altered and disturbed development as well as specific lesional hallmarks. Understanding the way cells are damaged is crucial to design brain protective strategies, and in this purpose, preclinical models largely contribute to improve the comprehension of the cell death mechanisms. While neuronal cell death has been deeply investigated and characterized in (hypoxic–ischemic) encephalopathy of the newborn at term, little is known about the types of cell death occurring in preterm brain injury. Three main different morphological cell death types are observed in the immature brain, specifically in models of hypoxic–ischemic encephalopathy, namely, necrotic, apoptotic, and autophagic cell death. Features of all three types may be present in the same dying neuron. In preterm brain injury, description of cell death types is sparse, and cell loss primarily concerns immature oligodendrocytes and, infrequently, neurons. In the present review, we first shortly discuss the different main severe preterm brain injury conditions that have been reported to involve cell death, including periventricular leucomalacia (PVL), diffuse white matter injury (dWMI), and intraventricular hemorrhages, as well as potentially harmful iatrogenic conditions linked to premature birth (anesthesia and caffeine therapy). Then, we present an overview of current evidence concerning cell death in both clinical human tissue data and preclinical models by focusing on studies investigating the presence of cell death allowing discriminating between the types of cell death involved. We conclude that, to improve brain protective strategies, not only apoptosis but also other cell death (such as regulated necrotic and autophagic) pathways now need to be investigated together in order to consider all cell death mechanisms involved in the pathogenesis of preterm brain damage.

Hand Preference Develops Across Childhood and Adolescence in Extremely Preterm Children: The EPICure Study

AIM

We attempted to determine how handedness changes with age and its relation to brain injury and cognition following birth before 26 weeks of gestation.

METHODS

We used data from the EPICure study of health and development following birth in the British Isles in 1995. Handedness was determined by direct observation during standardized testing at age 2.5, six, and 11 years and by self-report using the Edinburgh Handedness Inventory at 19 years. Control data from term births were included at six, 11, and 19 years.

RESULTS

In extremely preterm children left handedness increased from 9% to 27% between 2.5 and 19 years, with a progressive reduction in mixed handedness from 59% to 13%. Although individual handedness scores varied over childhood, the between-group effects were consistent through 19 years, with greatest differences in females. In extremely preterm participants, neonatal brain injury was associated with lower right handedness scores at each age and left-handed participants had lower cognitive scores at 19 years after controlling for confounders, but not at other ages.

CONCLUSION

Increasing hand lateralization is seen over childhood in extremely preterm survivors, but consistently more individuals have non-right preferences at each age than control individuals.

Association of Circulating Proinflammatory and Anti-inflammatory Protein Biomarkers in Extremely Preterm Born Children with Subsequent Brain Magnetic Resonance Imaging Volumes and Cognitive Function at Age 10 Years

OBJECTIVES

To examine elevated neonatal inflammatory and neurotrophic proteins from children born extremely preterm in relation to later childhood brain Magnetic Resonance Imaging volumes and cognition.

STUDY DESIGN

We measured circulating inflammation-related proteins and neurotrophic proteins on postnatal days 1, 7, and 14 in 166 children at 10 years of age (73 males; 93 females). Top quartile levels on ≥2 days for ≥3 inflammation-related proteins and for ≥4 neurotrophic proteins defined exposure. We examined associations among protein levels, brain Magnetic Resonance Imaging volumes, and cognition with multiple linear and logistic regressions.

RESULTS

Analyses were adjusted for gestational age at birth and sex. Children with ≥3 elevated inflammation-related proteins had smaller grey matter, brain stem/cerebellar, and total brain volumes than those without elevated inflammation-related proteins, adjusted for neurotrophic proteins. When adjusted for inflammation-related proteins, children with ≥4 neurotrophic proteins, compared with children with no neurotrophic proteins, had larger grey matter and total brain volumes. Higher grey matter, white matter, and cerebellum and brainstem volumes were significantly correlated with higher IQ. Grey and white matter volumes were correlated with each other (r = -0.18; P = .021), and cerebellum and brainstem was highly correlated with grey matter (r = 0.55; P < .001) and white matter (r = 0.29; P < .001). Adjusting for other brain compartments, cerebellum and brainstem was associated with IQ (P = .016), but the association with white matter was marginally significant (P = .051). Grey matter was not associated with IQ. After adjusting for brain volumes, elevated inflammation-related proteins remained significantly associated with a lower IQ, and elevated neurotrophic proteins remained associated with a higher IQ.

CONCLUSIONS

Newborn inflammatory and neurotrophin protein levels are associated with later brain volumes and cognition, but their effects on cognition are not entirely explained by altered brain volumes.

Exploring the EEG mu rhythm associated with observation and execution of a goal-directed action in 14-month-old preterm infants

Electroencephalographic mu rhythm desynchronization is thought to reflect Mirror Neuron System (MNS) activity and represents an important neural correlate of the coupling between action execution and perception. It is still unclear if the MNS in human ontogeny is already available at the beginning of postnatal life and how early experience impacts its development. Premature birth provides a "natural condition" for investigating the effects of early, atypical extra-uterine experience on MNS. The main aim of the present study was to investigate whether the MNS activity is associated with prematurity. We compared the mu rhythm activity in preterm (PT) and full-term (FT) 14-month old infants during an action observation/execution (AO/AE) task. Mu rhythm desynchronization was computed over frontal, central, parietal and occipital regions. Both groups showed mu rhythm suppression in all the scalp regions during action execution. Different desynchronization patterns emerged during action observation. Specifically, FT infants showed mu suppression in the right frontal, bilateral parietal and occipital regions; whereas PT infants exhibited mu suppression only in the right parietal region. Overall, these preliminary findings indicate that an atypical extra uterine experience might have an impact on the MNS activity.

Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review

Background: Analysis of the human connectome using functional magnetic resonance imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to discover the neural underpinnings of human cognition and neurological disorders. In general, brain connectivity patterns from fMRI data are classified as statistical dependencies (functional connectivity) or causal interactions (effective connectivity) among various neural units. Computational methods, especially graph theory-based methods, have recently played a significant role in understanding brain connectivity architecture. Objectives: Thanks to the emergence of graph theoretical analysis, the main purpose of the current paper is to systematically review how brain properties can emerge through the interactions of distinct neuronal units in various cognitive and neurological applications using fMRI. Moreover, this article provides an overview of the existing functional and effective connectivity methods used to construct the brain network, along with their advantages and pitfalls. Methods: In this systematic review, the databases Science Direct, Scopus, arXiv, Google Scholar, IEEE Xplore, PsycINFO, PubMed, and SpringerLink are employed for exploring the evolution of computational methods in human brain connectivity from 1990 to the present, focusing on graph theory. The Cochrane Collaboration's tool was used to assess the risk of bias in individual studies. Results: Our results show that graph theory and its implications in cognitive neuroscience have attracted the attention of researchers since 2009 (as the Human Connectome Project launched), because of their prominent capability in characterizing the behavior of complex brain systems. Although graph theoretical approach can be generally applied to either functional or effective connectivity patterns during rest or task performance, to date, most articles have focused on the resting-state functional connectivity. Conclusions: This review provides an insight into how to utilize graph theoretical measures to make neurobiological inferences regarding the mechanisms underlying human cognition and behavior as well as different brain disorders.

Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review

Background: Analysis of the human connectome using functional magnetic resonance imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to discover the neural underpinnings of human cognition and neurological disorders. In general, brain connectivity patterns from fMRI data are classified as statistical dependencies (functional connectivity) or causal interactions (effective connectivity) among various neural units. Computational methods, especially graph theory-based methods, have recently played a significant role in understanding brain connectivity architecture. Objectives: Thanks to the emergence of graph theoretical analysis, the main purpose of the current paper is to systematically review how brain properties can emerge through the interactions of distinct neuronal units in various cognitive and neurological applications using fMRI. Moreover, this article provides an overview of the existing functional and effective connectivity methods used to construct the brain network, along with their advantages and pitfalls. Methods: In this systematic review, the databases Science Direct, Scopus, arXiv, Google Scholar, IEEE Xplore, PsycINFO, PubMed, and SpringerLink are employed for exploring the evolution of computational methods in human brain connectivity from 1990 to the present, focusing on graph theory. The Cochrane Collaboration's tool was used to assess the risk of bias in individual studies. Results: Our results show that graph theory and its implications in cognitive neuroscience have attracted the attention of researchers since 2009 (as the Human Connectome Project launched), because of their prominent capability in characterizing the behavior of complex brain systems. Although graph theoretical approach can be generally applied to either functional or effective connectivity patterns during rest or task performance, to date, most articles have focused on the resting-state functional connectivity. Conclusions: This review provides an insight into how to utilize graph theoretical measures to make neurobiological inferences regarding the mechanisms underlying human cognition and behavior as well as different brain disorders.

Altered resting-state functional connectivity in children and adolescents born very preterm short title

The formation of resting-state functional networks in infancy has been reported to be strongly impacted by very preterm birth. Studies in childhood and adolescence have largely focused on language processing networks and identified both decreased and increased functional connectivity. It is unclear, however, whether functional connectivity strength is altered globally in children and adolescents born very preterm and whether these alterations are related to the frequently occurring cognitive deficits. Here, resting-state functional MRI was assessed in a group of 32 school-aged children and adolescents born very preterm with normal intellectual and motor abilities and 39 healthy term-born peers. Functional connectivity within and between a comprehensive set of well-established resting-state networks was compared between the groups. IQ and executive function abilities were tested with standardized tasks and potential associations with connectivity strength were explored. Functional connectivity was weaker in the very preterm compared to the term-born group between the sensorimotor network and the visual and dorsal attention network, within the sensorimotor network and within the central executive network. In contrast, functional connectivity was stronger in the very preterm group between the sensorimotor network and parts of the salience and the central executive network. Little evidence was found that these alterations underlie lower IQ or poorer executive function abilities. This study provides evidence for a long-lasting impact of very preterm birth on the organization of resting-state networks. The potential consequence of these alterations for other neurodevelopmental domains than the ones investigated in the current study warrants further investigation.