Localization of spontaneous bursting neuronal activity in the preterm human brain with simultaneous EEG-fMRI

Infant neuroscience: how to measure brain activity in the youngest minds

The functional properties of the infant brain are poorly understood. Recent advances in cognitive neuroscience are opening new avenues for measuring brain activity in human infants. These include novel uses of existing technologies such as electroencephalography (EEG) and magnetoencephalography (MEG), the availability of newer technologies including functional near-infrared spectroscopy (fNIRS) and optically pumped magnetometry (OPM), and innovative applications of functional magnetic resonance imaging (fMRI) in awake infants during cognitive tasks. In this review article we catalog these available non-invasive methods, discuss the challenges and opportunities encountered when applying them to human infants, and highlight the potential they may ultimately hold for advancing our understanding of the youngest minds.

Does Electrophysiological Maturation Shape Language Acquisition?

Infants master temporal patterns of their native language at a developmental trajectory from slow to fast: Shortly after birth, they recognize the slow acoustic modulations specific to their native language before tuning into faster language-specific patterns between 6 and 12 months of age. We propose here that this trajectory is constrained by neuronal maturation-in particular, the gradual emergence of high-frequency neural oscillations in the infant electroencephalogram. Infants' initial focus on slow prosodic modulations is consistent with the prenatal availability of slow electrophysiological activity (i.e., theta- and delta-band oscillations). Our proposal is consistent with the temporal patterns of infant-directed speech, which initially amplifies slow modulations, approaching the faster modulation range of adult-directed speech only as infants' language has advanced sufficiently. Moreover, our proposal agrees with evidence from premature infants showing maturational age is a stronger predictor of language development than ex utero exposure to speech, indicating that premature infants cannot exploit their earlier availability of speech because of electrophysiological constraints. In sum, we provide a new perspective on language acquisition emphasizing neuronal development as a critical driving force of infants' language development.

Early development of the functional brain network in newborns

During the prenatal period and the first postnatal years, the human brain undergoes rapid growth, which establishes a preliminary infrastructure for the subsequent development of cognition and behavior. To understand the underlying processes of brain functioning and identify potential sources of developmental disorders, it is essential to uncover the developmental rules that govern this critical period. In this study, graph theory modeling and network science analysis were employed to investigate the impact of age, gender, weight, and typical and atypical development on brain development. Local and global topologies of functional connectomes obtained from rs-fMRI data were collected from 421 neonates aged between 31 and 45 postmenstrual weeks who were in natural sleep without any sedation. The results showed that global efficiency, local efficiency, clustering coefficient, and small-worldness increased with age, while modularity and characteristic path length decreased with age. The normalized rich-club coefficient displayed a U-shaped pattern during development. The study also examined the global and local impacts of gender, weight, and group differences between typical and atypical cases. The findings presented some new insights into the maturation of functional brain networks and their relationship with cognitive development and neurodevelopmental disorders.

Disrupted resting-sate brain network dynamics in children born extremely preterm

The developing brain has to adapt to environmental and intrinsic insults after extremely preterm (EPT) birth. Ongoing maturational processes maximize their fit to the environment and this can provide a substrate for neurodevelopmental failures. Resting-state functional magnetic resonance imaging was used to scan 33 children born EPT, at < 27 weeks of gestational age, and 26 full-term controls at 10 years of age. We studied the capability of a brain area to propagate neural information (intrinsic ignition) and its variability across time (node-metastability). This framework was computed for the dorsal attention network (DAN), frontoparietal, default-mode network (DMN), and the salience, limbic, visual, and somatosensory networks. The EPT group showed reduced intrinsic ignition in the DMN and DAN, compared with the controls, and reduced node-metastability in the DMN, DAN, and salience networks. Intrinsic ignition and node-metastability values correlated with cognitive performance at 12 years of age in both groups, but only survived in the term group after adjustment. Preterm birth disturbed the signatures of functional brain organization at rest in 3 core high-order networks: DMN, salience, and DAN. Identifying vulnerable resting-state networks after EPT birth may lead to interventions that aim to rebalance brain function.

An Opportunity to Increase Collaborative Science in Fetal, Infant, and Toddler Neuroimaging

The field of fetal, infant, and toddler (FIT) neuroimaging research—including magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography, and functional near-infrared spectroscopy, among others—offers pioneering insights into early brain development and has grown in popularity over the past 2 decades. In broader neuroimaging research, multisite collaborative projects, data sharing, and open-source code have increasingly become the norm, fostering big data, consensus standards, and rapid knowledge transfer and development. Given the aforementioned benefits, along with recent initiatives from funding agencies to support multisite and multimodal FIT neuroimaging studies, the FIT field now has the opportunity to establish sustainable, collaborative, and open science practices. By combining data and resources, we can tackle the most pressing issues of the FIT field, including small effect sizes, replicability problems, generalizability issues, and the lack of field standards for data collection, processing, and analysis—together. Thus, the goals of this commentary are to highlight some of the potential barriers that have waylaid these efforts and to discuss the emerging solutions that have the potential to revolutionize how we work together to study the developing brain early in life.

Parsing brain-behavior heterogeneity in very preterm born children using integrated similarity networks

Very preterm birth (VPT; ≤32 weeks' gestation) is associated with altered brain development and cognitive and behavioral difficulties across the lifespan. However, heterogeneity in outcomes among individuals born VPT makes it challenging to identify those most vulnerable to neurodevelopmental sequelae. Here, we aimed to stratify VPT children into distinct behavioral subgroups and explore between-subgroup differences in neonatal brain structure and function. 198 VPT children (98 females) previously enrolled in the Evaluation of Preterm Imaging Study (EudraCT 2009-011602-42) underwent Magnetic Resonance Imaging at term-equivalent age and neuropsychological assessments at 4-7 years. Using an integrative clustering approach, we combined neonatal socio-demographic, clinical factors and childhood socio-emotional and executive function outcomes, to identify distinct subgroups of children based on their similarity profiles in a multidimensional space. We characterized resultant subgroups using domain-specific outcomes (temperament, psychopathology, IQ and cognitively stimulating home environment) and explored between-subgroup differences in neonatal brain volumes (voxel-wise Tensor-Based-Morphometry), functional connectivity (voxel-wise degree centrality) and structural connectivity (Tract-Based-Spatial-Statistics). Results showed two- and three-cluster data-driven solutions. The two-cluster solution comprised a 'resilient' subgroup (lower psychopathology and higher IQ, executive function and socio-emotional scores) and an 'at-risk' subgroup (poorer behavioral and cognitive outcomes). No neuroimaging differences between the resilient and at-risk subgroups were found. The three-cluster solution showed an additional third 'intermediate' subgroup, displaying behavioral and cognitive outcomes intermediate between the resilient and at-risk subgroups. The resilient subgroup had the most cognitively stimulating home environment and the at-risk subgroup showed the highest neonatal clinical risk, while the intermediate subgroup showed the lowest clinical, but the highest socio-demographic risk. Compared to the intermediate subgroup, the resilient subgroup displayed larger neonatal insular and orbitofrontal volumes and stronger orbitofrontal functional connectivity, while the at-risk group showed widespread white matter microstructural alterations. These findings suggest that risk stratification following VPT birth is feasible and could be used translationally to guide personalized interventions aimed at promoting children's resilience.

Robust sex differences in functional brain connectivity are present in utero

Sex-based differences in brain structure and function are observable throughout development and are thought to contribute to differences in behavior, cognition, and the presentation of neurodevelopmental disorders. Using multiple support vector machine (SVM) models as a data-driven approach to assess sex differences, we sought to identify regions exhibiting sex-dependent differences in functional connectivity and determine whether they were robust and sufficiently reliable to classify sex even prior to birth. To accomplish this, we used a sample of 110 human fetal resting state fMRI scans from 95 fetuses, performed between 19 and 40 gestational weeks. Functional brain connectivity patterns classified fetal sex with 73% accuracy. Across SVM models, we identified features (functional connections) that reliably differentiated fetal sex. Highly consistent predictors included connections in the somatomotor and frontal areas alongside the hippocampus, cerebellum, and basal ganglia. Moreover, high consistency features also implicated a greater magnitude of cross-region connections in females, while male weighted features were predominately within anatomically bounded regions. Our findings indicate that these differences, which have been observed later in childhood, are present and reliably detectable even before birth. These results show that sex differences arise before birth in a manner that is consistent and reliable enough to be highly identifiable.

Feasibility of automated early postnatal sleep staging in extremely and very preterm neonates using dual-channel EEG

OBJECTIVE

To investigate the feasibility of automated sleep staging based on quantitative analysis of dual-channel electroencephalography (EEG) for extremely and very preterm infants during their first postnatal days.

METHODS

We enrolled 17 preterm neonates born between 25 and 30 weeks of gestational age. Three-hour behavioral sleep observations and simultaneous dual-channel EEG monitoring were conducted for each infant within their first 72 hours after birth. Four kinds of representative and complementary quantitative EEG (qEEG) metrics (i.e., bursting, synchrony, spectral power, and complexity) were calculated and compared between active sleep, quiet sleep, and wakefulness. All analyses were performed in offline mode.

RESULTS

In separate comparison analyses, significant differences between sleep-wake states were found for bursting, spectral power and complexity features. The automated sleep-wake state classifier based on the combination of all qEEG features achieved a macro-averaged area under the curve of receiver operating characteristic of 74.8%. The complexity features contributed the most to sleep-wake state classification.

CONCLUSIONS

It is feasible to distinguish between sleep-wake states within the first 72 postnatal hours for extremely and very preterm infants using qEEG metrics.

SIGNIFICANCE

Our findings offer the possibility of starting personalized care dependent on preterm infants' sleep-wake states directly after birth, potentially yielding long-run benefits for their developmental outcomes.

Altered cortical microstructure in preterm infants at term-equivalent age relative to term-born neonates

Preterm (PT) birth is a potential factor for abnormal brain development. Although various alterations of cortical structure and functional connectivity in preterm infants have been reported, the underlying microstructural foundation is still undetected thoroughly in PT infants relative to full-term (FT) neonates. To detect the very early cortical microstructural alteration noninvasively with advanced neurite orientation dispersion and density imaging (NODDI) on a whole-brain basis, we used multi-shell diffusion MRI of healthy newborns selected from the Developing Human Connectome Project. 73 PT infants and 69 FT neonates scanned at term-equivalent age were included in this study. By extracting the core voxels of gray matter (GM) using GM-based spatial statistics (GBSS), we found that comparing to FT neonates, infants born preterm showed extensive lower neurite density in both primary and higher-order association cortices (FWE corrected, P < 0.025). Higher orientation dispersion was only found in very preterm subgroup in the orbitofrontal cortex, fronto-insular cortex, entorhinal cortex, a portion of posterior cingular gyrus, and medial parieto-occipital cortex. This study provided new insights into exploring structural MR for functional and behavioral variations in preterm population, and these findings may have marked clinical importance, particularly in the guidance of ameliorating the development of premature brain.

Dendritic Spines: Synaptogenesis and Synaptic Pruning for the Developmental Organization of Brain Circuits

Synaptic overproduction and elimination is a regular developmental event in the mammalian brain. In the cerebral cortex, synaptic overproduction is almost exclusively correlated with glutamatergic synapses located on dendritic spines. Therefore, analysis of changes in spine density on different parts of the dendritic tree in identified classes of principal neurons could provide insight into developmental reorganization of specific microcircuits.The activity-dependent stabilization and selective elimination of the initially overproduced synapses is a major mechanism for generating diversity of neural connections beyond their genetic determination. The largest number of overproduced synapses was found in the monkey and human cerebral cortex. The highest (exceeding adult values by two- to threefold) and most protracted overproduction (up to third decade of life) was described for associative layer IIIC pyramidal neurons in the human dorsolateral prefrontal cortex.Therefore, the highest proportion and extraordinarily extended phase of synaptic spine overproduction is a hallmark of neural circuitry in human higher-order associative areas. This indicates that microcircuits processing the most complex human cognitive functions have the highest level of developmental plasticity. This finding is the backbone for understanding the effect of environmental impact on the development of the most complex, human-specific cognitive and emotional capacities, and on the late onset of human-specific neuropsychiatric disorders, such as autism and schizophrenia.

Adult outcome of preterm birth: Implications for neurodevelopmental theories of psychosis

Preterm birth is associated with an elevated risk of developmental and adult psychiatric disorders, including psychosis. In this review, we evaluate the implications of neurodevelopmental, cognitive, motor, and social sequelae of preterm birth for developing psychosis, with an emphasis on outcomes observed in adulthood. Abnormal brain development precipitated by early exposure to the extra-uterine environment, and exacerbated by neuroinflammation, neonatal brain injury, and genetic vulnerability, can result in alterations of brain structure and function persisting into adulthood. These alterations, including abnormal regional brain volumes and white matter macro- and micro-structure, can critically impair functional (e.g. frontoparietal and thalamocortical) network connectivity in a manner characteristic of psychotic illness. The resulting executive, social, and motor dysfunctions may constitute the basis for behavioural vulnerability ultimately giving rise to psychotic symptomatology. There are many pathways to psychosis, but elucidating more precisely the mechanisms whereby preterm birth increases risk may shed light on that route consequent upon early neurodevelopmental insult.

Atypical Intrinsic Hemispheric Interaction Associated with Autism Spectrum Disorder Is Present within the First Year of Life

Autism spectrum disorder (ASD) is characterized by atypical connectivity lateralization of functional networks. However, previous studies have not directly investigated if differences in specialization between ASD and typically developing (TD) peers are present in infancy, leaving the timing of onset of these differences relatively unknown. We studied the hemispheric asymmetries of connectivity in children with ASD and infants later meeting the diagnostic criteria for ASD. Analyses were performed in 733 children with ASD and TD peers and in 71 infants at high risk (HR) or normal risk (NR) for ASD, with data collected at 1 month and 9 months of age. Comparing children with ASD (n = 301) to TDs (n = 432), four regions demonstrated group differences in connectivity: posterior cingulate cortex (PCC), posterior superior temporal gyrus, extrastriate cortex, and anterior prefrontal cortex. At 1 month, none of these regions exhibited group differences between ASD (n = 10), HR-nonASD (n = 15), or NR (n = 18) infants. However, by 9 months, the PCC and extrastriate exhibited atypical connectivity in ASD (n = 11) and HR-nonASD infants (n = 24) compared to NR infants (n = 22). Connectivity did not correlate with symptoms in either sample. Our results demonstrate that differences in network asymmetries associated with ASD risk are observable prior to the age of a reliable clinical diagnosis.

EEG phase-amplitude coupling to stratify encephalopathy severity in the developing brain

BACKGROUND

Neonatal hypoxic ischemic encephalopathy (HIE) is difficult to classify within the narrow therapeutic window of hypothermia. Neurophysiological biomarkers are needed for timely differentiation of encephalopathy severity within the short therapeutic window for initiation of hypothermia therapy.

METHODS

A novel analysis of mean Phase Amplitude Coupling index, PAC_m, of amplitudes high frequencies (12-30 Hz) coupled with phases of low (1,2 Hz) frequencies was calculated from the 6 h EEG recorded during the first day of life. PAC_m values were compared to identify differences between mild versus higher-grade HIE, respectively, for each of the EEG electrodes. A receiver operating characteristic curve was generated to examine the performance of PAC_m.

RESULTS

38 newborns with different HIE grades were enrolled in the first 6 h of life. Threshold PAC_m 0.001 at Fz, O1, O2, P3, and P4 had AUC >0.9 to differentiate HIE severity and predict the persistence of moderate to severe encephalopathy that requires treatment with hypothermia.

CONCLUSION

PAC is a promising biomarker to identify mild from higher severity of HIE after birth.

Dear reviewers: Responses to common reviewer critiques about infant neuroimaging studies

The field of adult neuroimaging relies on well-established principles in research design, imaging sequences, processing pipelines, as well as safety and data collection protocols. The field of infant magnetic resonance imaging, by comparison, is a young field with tremendous scientific potential but continuously evolving standards. The present article aims to initiate a constructive dialog between researchers who grapple with the challenges and inherent limitations of a nascent field and reviewers who evaluate their work. We address 20 questions that researchers commonly receive from research ethics boards, grant, and manuscript reviewers related to infant neuroimaging data collection, safety protocols, study planning, imaging sequences, decisions related to software and hardware, and data processing and sharing, while acknowledging both the accomplishments of the field and areas of much needed future advancements. This article reflects the cumulative knowledge of experts in the FIT’NG community and can act as a resource for both researchers and reviewers alike seeking a deeper understanding of the standards and tradeoffs involved in infant neuroimaging.

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The field of infant MRI is young with evolving standards.

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We address 20 questions that researchers commonly receive reviewers.

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These come from research ethics boards, grant, and manuscript reviewers.

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This article reflects the cumulative knowledge of experts in the FIT’NG community.

The impact of premature extrauterine exposure on infants' stimulus-evoked brain activity across multiple sensory systems

Prematurity can result in widespread neurodevelopmental impairment, with the impact of premature extrauterine exposure on brain function detectable in infancy. A range of neurodynamic and haemodynamic functional brain measures have previously been employed to study the neurodevelopmental impact of prematurity, with methodological and analytical heterogeneity across studies obscuring how multiple sensory systems are affected. Here, we outline a standardised template analysis approach to measure evoked response magnitudes for visual, tactile, and noxious stimulation in individual infants (n = 15) using EEG. By applying these templates longitudinally to an independent cohort of very preterm infants (n = 10), we observe that the evoked response template magnitudes are significantly associated with age-related maturation. Finally, in a cross-sectional study we show that the visual and tactile response template magnitudes differ between a cohort of infants who are age-matched at the time of study but who differ according to whether they are born during the very preterm or late preterm period (n = 10 and 8 respectively). These findings demonstrate the significant impact of premature extrauterine exposure on brain function and suggest that prematurity can accelerate maturation of the visual and tactile sensory system in infants born very prematurely. This study highlights the value of using a standardised multi-modal evoked-activity analysis approach to assess premature neurodevelopment, and will likely complement resting-state EEG and behavioural assessments in the study of the functional impact of developmental care interventions.

Associations Between Neonatal Brain Structure, the Home Environment, and Childhood Outcomes Following Very Preterm Birth

Background

Very preterm birth is associated with an increased risk of childhood psychopathology and cognitive deficits. However, the extent to which these developmental problems associated with preterm birth are amenable to environmental factors or determined by neurobiology at birth remains unclear.

Methods

We derived neonatal brain structural covariance networks using non-negative matrix factorization in 384 very preterm infants (median gestational age [range], 30.29 [23.57–32.86] weeks) who underwent magnetic resonance imaging at term-equivalent age (median postmenstrual age, 42.57 [37.86–44.86] weeks). Principal component analysis was performed on 32 behavioral and cognitive measures assessed at preschool age (n = 206; median age, 4.65 [4.19–7.17] years) to identify components of childhood psychopathology and cognition. The Cognitively Stimulating Parenting Scale assessed the level of cognitively stimulating experiences available to the child at home.

Results

Cognitively stimulating parenting was associated with reduced expression of a component reflecting developmental psychopathology and executive dysfunction consistent with the preterm phenotype (inattention-hyperactivity, autism spectrum behaviors, and lower executive function scores). In contrast, a component reflecting better general cognitive abilities was associated with larger neonatal gray matter volume in regions centered on key nodes of the salience network, but not with cognitively stimulating parenting.

Conclusions

Our results suggest that while neonatal brain structure likely influences cognitive abilities in very preterm children, the severity of behavioral symptoms that are typically observed in these children is sensitive to a cognitively stimulating home environment. Very preterm children may derive meaningful mental health benefits from access to cognitively stimulating experiences during childhood.

Interactive relations between maternal prenatal stress, fetal brain connectivity, and gestational age at delivery

Studies reporting significant associations between maternal prenatal stress and child outcomes are frequently confounded by correlates of prenatal stress that influence the postnatal rearing environment. The major objective of this study is to identify whether maternal prenatal stress is associated with variation in human brain functional connectivity prior to birth. We utilized fetal fMRI in 118 fetuses [48 female; mean age 32.9 weeks (SD = 3.87)] to evaluate this association and further addressed whether fetal neural differences were related to maternal health behaviors, social support, or birth outcomes. Community detection was used to empirically define networks and enrichment was used to isolate differential within- or between-network connectivity effects. Significance for χ2 enrichment was determined by randomly permuting the subject pairing of fetal brain connectivity and maternal stress values 10,000 times. Mixtures modelling was used to test whether fetal neural differences were related to maternal health behaviors, social support, or birth outcomes. Increased maternal prenatal negative affect/stress was associated with alterations in fetal frontoparietal, striatal, and temporoparietal connectivity (β = 0.82, p < 0.001). Follow-up analysis demonstrated that these associations were stronger in women with better health behaviors, more positive interpersonal support, and lower overall stress (β = 0.16, p = 0.02). Additionally, magnitude of stress-related differences in neural connectivity was marginally correlated with younger gestational age at delivery (β = -0.18, p = 0.05). This is the first evidence that negative affect/stress during pregnancy is reflected in functional network differences in the human brain in utero, and also provides information about how positive interpersonal and health behaviors could mitigate prenatal brain programming.

Stable behavioral state-specific large scale activity patterns in the developing cortex of neonates

Intrinsic neuronal activity is a hallmark of the developing brain. In rodents, a handful of such activities were described in different cortical areas but the unifying macroscopic perspective is still lacking. Here we combined large-scale in vivo Ca²⁺ imaging of the dorsal cortex in non-anesthetized neonatal mice with mathematical analyses to reveal unique behavioral state-specific maps of intrinsic activity. These maps were remarkably stable over time within and across experiments and used patches of correlated activity with little hemispheric symmetry as well as stationary and propagating waves as building blocks. Importantly, the maps recorded during motion and rest were almost inverse, with frontoparietal areas active during motion and posterior-lateral areas active at rest. The retrosplenial cortex engaged in both resting- and motion-related activities via functional long-range connections with respective cortical areas. The data obtained bind different region-specific activity patterns described so far into a single consistent picture and set the stage for future inactivation studies, probing the exact function of this complex activity pattern for cortical wiring in neonates.

Spontaneous activity in developing thalamic and cortical sensory networks

Developing sensory circuits exhibit different patterns of spontaneous activity, patterns that are related to the construction and refinement of functional networks. During the development of different sensory modalities, spontaneous activity originates in the immature peripheral sensory structures and in the higher-order central structures, such as the thalamus and cortex. Certainly, the perinatal thalamus exhibits spontaneous calcium waves, a pattern of activity that is fundamental for the formation of sensory maps and for circuit plasticity. Here, we review our current understanding of the maturation of early (including embryonic) patterns of spontaneous activity and their influence on the assembly of thalamic and cortical sensory networks. Overall, the data currently available suggest similarities between the developmental trajectory of brain activity in experimental models and humans, which in the future may help to improve the early diagnosis of developmental disorders.

Identifying Emergent Mesoscopic-Macroscopic Functional Brain Network Dynamics in Infants at Term-Equivalent Age with Electric Source Neuroimaging

Aim: To identify and characterize the functional brain networks at the time when the brain is yet to develop higher order functions in term-born and preterm infants at term-equivalent age. Introduction: Although functional magnetic resonance imaging (fMRI) data have revealed the existence of spatially structured resting-state brain activity in infants, the temporal information of fMRI data limits the characterization of fast timescale brain oscillations. In this study, we use infants' high-density electroencephalography (EEG) to characterize spatiotemporal and spectral functional organizations of brain network dynamics. Methods: We used source-reconstructed EEG and graph theoretical analyses in 100 infants (84 preterm, 16 term born) to identify the rich-club topological organization, temporal dynamics, and spectral fingerprints of dynamic functional brain networks. Results: Five dynamic functional brain networks are identified, which have rich-club topological organizations, distinctive spectral fingerprints (in the delta and low-alpha frequency), and scale-invariant temporal dynamics (<0.1 Hz): The default mode, primary sensory-limbic system, thalamo-frontal, thalamo-sensorimotor, and visual-limbic system. The temporal dynamics of these networks are correlated in a hierarchically leading-following organization, showing that infant brain networks arise from long-range synchronization of band-limited cortical oscillation based on interacting fast- and slow-coherent cortical oscillations. Conclusion: Dynamic functional brain networks do not solely depend on the maturation of cognitive networks; instead, the brain network dynamics exist in infants at term age well before the childhood and adulthood, and hence, it offers a quantitative measurement of neurotypical development in infants. Clinical Trial Registration Number: ACTRN12615000591550. Impact statement Our work offers novel functional insights into the brain network characterization in infants, providing a new functional basis for future deployable prognostication approaches.

A limited role of NKCC1 in telencephalic glutamatergic neurons for developing hippocampal network dynamics and behavior

NKCC1 is the primary transporter mediating chloride uptake in immature principal neurons, but its role in the development of in vivo network dynamics and cognitive abilities remains unknown. Here, we address the function of NKCC1 in developing mice using electrophysiological, optical, and behavioral approaches. We report that NKCC1 deletion from telencephalic glutamatergic neurons decreases in vitro excitatory actions of γ-aminobutyric acid (GABA) and impairs neuronal synchrony in neonatal hippocampal brain slices. In vivo, it has a minor impact on correlated spontaneous activity in the hippocampus and does not affect network activity in the intact visual cortex. Moreover, long-term effects of the developmental NKCC1 deletion on synaptic maturation, network dynamics, and behavioral performance are subtle. Our data reveal a neural network function of NKCC1 in hippocampal glutamatergic neurons in vivo, but challenge the hypothesis that NKCC1 is essential for major aspects of hippocampal development.

Understanding Vulnerability and Adaptation in Early Brain Development using Network Neuroscience

Early adversity influences brain development and emerging behavioral phenotypes relevant for psychiatric disorders. Understanding the effects of adversity before and after conception on brain development has implications for contextualizing current public health crises and pervasive health inequities. The use of functional magnetic resonance imaging (fMRI) to study the brain at rest has shifted understanding of brain functioning and organization in the earliest periods of life. Here we review applications of this technique to examine effects of early life stress (ELS) on neurodevelopment in infancy, and highlight targets for future research. Building on the foundation of existing work in this area will require tackling significant challenges, including greater inclusion of often marginalized segments of society, and conducting larger, properly powered studies.

The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity

The Developing Human Connectome Project is an Open Science project that provides the first large sample of neonatal functional MRI data with high temporal and spatial resolution. These data enable mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organization in humans. Here, we characterize in unprecedented detail the maturation and integrity of resting state networks (RSNs) at term-equivalent age in 337 infants (including 65 born preterm). First, we applied group independent component analysis to define 11 RSNs in term-born infants scanned at 43.5–44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37–43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder, which occur frequently in preterm children. Overall, we found a robust, modular, symmetrical functional brain organization at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity.

Relationship Between Early Functional and Structural Brain Developments and Brain Injury in Preterm Infants

Background

Recent studies explored the relationship between early brain function and brain morphology, based on the hypothesis that increased brain activity can positively affect structural brain development and that excitatory neuronal activity stimulates myelination.

Objective

To investigate the relationship between maturational features from early and serial aEEGs after premature birth and MRI metrics characterizing structural brain development and injury, measured around 30weeks postmenstrual age (PMA) and at term. Moreover, we aimed to verify whether previously developed maturational EEG features are related with PMA.

Design/Methods

One hundred six extremely preterm infants received bedside aEEGs during the first 72h and weekly until week 5. 3T-MRIs were performed at 30weeks PMA and at term. Specific features were extracted to assess EEG maturation: (1) the spectral content, (2) the continuity [percentage of spontaneous activity transients (SAT%) and the interburst interval (IBI)], and (3) the complexity. Automatic MRI segmentation to assess volumes and MRI score was performed. The relationship between the maturational EEG features and MRI measures was investigated.

Results

Both SAT% and EEG complexity were correlated with PMA. IBI was inversely associated with PMA. Complexity features had a positive correlation with the cerebellar size at 30weeks, while event-based measures were related to the cerebellar size at term. Cerebellar width, cortical grey matter, and total brain volume at term were inversely correlated with the relative power in the higher frequency bands.

Conclusions

The continuity and complexity of the EEG steadily increase with increasing postnatal age. Increasing complexity and event-based features are associated with cerebellar size, a structure with enormous development during preterm life. Brain activity is important for later structural brain development.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12311-021-01232-z.

Delta brushes are not just a hallmark of EEG in human preterm infants

The delta brush, a well-known characteristic waveform of the human preterm electroencephalogram, represents spontaneous electrical activity. Recent experimental animal model evidence suggests that delta brushes are not only spontaneous intrinsic activity but are also evoked by external sensory stimulation or spontaneous movement. They are also likely to reflect the activity of subplate neurons, which play an important role in early brain development and network organization. Here, evidence about delta brushes in human preterm electroencephalogram is provided along with future perspectives.

Normal EEG during the neonatal period: maturational aspects from premature to full-term newborns

Electroencephalography (EEG) is the reference tool for the analysis of brain function, reflecting normal and pathological neuronal network activity. During the neonatal period, EEG patterns evolve weekly, according to gestational age. The first analytical criteria for the various maturational stages and standardized neonatal EEG terminology were published by a group of French neurophysiologists training in Paris (France) in 1999. These criteria, defined from analog EEG, were completed in 2010 with digital EEG analysis. Since then, this work has continued, aided by the technical progress in EEG acquisition, the improvement of knowledge on the maturating processes of neuronal networks, and the evolution of critical care. In this review, we present an exhaustive and didactic overview of EEG characteristics from extremely premature to full-term infants. This update is based on the scientific literature, enhanced by the study of normal EEGs of extremely premature infants by our group of neurophysiologists. For educational purposes, particular attention has been paid to illustrations using new digital tools.

Meaning before grammar: A review of ERP experiments on the neurodevelopmental origins of semantic processing

According to traditional linguistic theories, the construction of complex meanings relies firmly on syntactic structure-building operations. Recently, however, new models have been proposed in which semantics is viewed as being partly autonomous from syntax. In this paper, we discuss some of the developmental implications of syntax-based and autonomous models of semantics. We review event-related brain potential (ERP) studies on semantic processing in infants and toddlers, focusing on experiments reporting modulations of N400 amplitudes using visual or auditory stimuli and different temporal structures of trials. Our review suggests that infants can relate or integrate semantic information from temporally overlapping stimuli across modalities by 6 months of age. The ability to relate or integrate semantic information over time, within and across modalities, emerges by 9 months. The capacity to relate or integrate information from spoken words in sequences and sentences appears by 18 months. We also review behavioral and ERP studies showing that grammatical and syntactic processing skills develop only later, between 18 and 32 months. These results provide preliminary evidence for the availability of some semantic processes prior to the full developmental emergence of syntax: non-syntactic meaning-building operations are available to infants, albeit in restricted ways, months before the abstract machinery of grammar is in place. We discuss this hypothesis in light of research on early language acquisition and human brain development.

Micro Three-Dimensional Neuronal Cultures Generate Developing Cortex-Like Activity Patterns

Studies aimed at neurological drug discovery have been carried out both in vitro and in vivo. In vitro cell culture models have showed potential as drug testing platforms characterized by high throughput, low cost, good reproducibility and ease of handling and observation. However, in vitro neuronal culture models are facing challenges in replicating in vivo-like activity patterns. This work reports an in vitro culture technique that is capable of producing micro three-dimensional (μ3D) cultures of only a few tens of neurons. The μ3D cultures generated by this method were uniform in size and density of neurons. These μ3D cultures had complex spontaneous synchronized neuronal activity patterns which were similar to those observed in the developing cortex and in much larger 3D cultures, but not in 2D cultures. Bursts could be reliably evoked by stimulation of single neurons. Synchronized bursts in μ3D cultures were abolished by inhibitors of glutamate receptors, while inhibitors of GABA_A receptors had a more complex effect. This pharmacological profile is similar to bursts in neonatal cortex. Since large numbers of reproducible μ3D cultures can be created and observed in parallel, this model of the developing cortex may find applications in high-throughput drug discovery experiments.

Development of Brain Networks In Utero: Relevance for Common Neural Disorders

Magnetic resonance imaging, histological, and gene analysis approaches in living and nonliving human fetuses and in prematurely born neonates have provided insight into the staged processes of prenatal brain development. Increased understanding of micro- and macroscale brain network development before birth has spurred interest in understanding the relevance of prenatal brain development to common neurological diseases. Questions abound as to the sensitivity of the intrauterine brain to environmental programming, to windows of plasticity, and to the prenatal origin of disorders of childhood that involve disruptions in large-scale network connectivity. Much of the available literature on human prenatal neural development comes from cross-sectional or case studies that are not able to resolve the longitudinal consequences of individual variation in brain development before birth. This review will 1) detail specific methodologies for studying the human prenatal brain, 2) summarize large-scale human prenatal neural network development, integrating findings from across a variety of experimental approaches, 3) explore the plasticity of the early developing brain as well as potential sex differences in prenatal susceptibility, and 4) evaluate opportunities to link specific prenatal brain developmental processes to the forms of aberrant neural connectivity that underlie common neurological disorders of childhood.

Sleep State Modulates Resting-State Functional Connectivity in Neonates

The spontaneous cerebral activity that gives rise to resting-state networks (RSNs) has been extensively studied in infants in recent years. However, the influence of sleep state on the presence of observable RSNs has yet to be formally investigated in the infant population, despite evidence that sleep modulates resting-state functional connectivity in adults. This effect could be extremely important, as most infant neuroimaging studies rely on the neonate to remain asleep throughout data acquisition. In this study, we combine functional near-infrared spectroscopy with electroencephalography to simultaneously monitor sleep state and investigate RSNs in a cohort of healthy term born neonates. During active sleep (AS) and quiet sleep (QS) our newborn neonates show functional connectivity patterns spatially consistent with previously reported RSN structures. Our three independent functional connectivity analyses revealed stronger interhemispheric connectivity during AS than during QS. In turn, within hemisphere short-range functional connectivity seems to be enhanced during QS. These findings underline the importance of sleep state monitoring in the investigation of RSNs.

Subcortico-Cortical Functional Connectivity in the Fetal Brain: A Cognitive Development Blueprint

Recent evidence has shown that patterns of cortico-cortical functional synchronization are consistently traceable by the end of the third trimester of pregnancy. The involvement of subcortical structures in early functional and cognitive development has never been explicitly investigated, notwithstanding their pivotal role in different cognitive processes. We address this issue by exploring subcortico-cortical functional connectivity at rest in a group of normally developing fetuses between the 25th and 32nd weeks of gestation. Results show significant functional coupling between subcortical nuclei and cortical networks related to: (i) sensorimotor processing, (ii) decision making, and (iii) learning capabilities. This functional maturation framework unearths a Cognitive Development Blueprint, according to which grounding cognitive skills are planned to develop with higher ontogenetic priority. Specifically, our evidence suggests that a newborn already possesses the ability to: (i) perceive the world and interact with it, (ii) create salient representations for the selection of adaptive behaviors, and (iii) store, retrieve, and evaluate the outcomes of interactions, in order to gradually improve adaptation to the extrauterine environment.

Temporal ordering of input modulates connectivity formation in a developmental neuronal network model of the cortex

Preterm infant brain activity is discontinuous; bursts of activity recorded using EEG (electroencephalography), thought to be driven by subcortical regions, display scale free properties and exhibit a complex temporal ordering known as long-range temporal correlations (LRTCs). During brain development, activity-dependent mechanisms are essential for synaptic connectivity formation, and abolishing burst activity in animal models leads to weak disorganised synaptic connectivity. Moreover, synaptic pruning shares similar mechanisms to spike-timing dependent plasticity (STDP), suggesting that the timing of activity may play a critical role in connectivity formation. We investigated, in a computational model of leaky integrate-and-fire neurones, whether the temporal ordering of burst activity within an external driving input could modulate connectivity formation in the network. Connectivity evolved across the course of simulations using an approach analogous to STDP, from networks with initial random connectivity. Small-world connectivity and hub neurones emerged in the network structure—characteristic properties of mature brain networks. Notably, driving the network with an external input which exhibited LRTCs in the temporal ordering of burst activity facilitated the emergence of these network properties, increasing the speed with which they emerged compared with when the network was driven by the same input with the bursts randomly ordered in time. Moreover, the emergence of small-world properties was dependent on the strength of the LRTCs. These results suggest that the temporal ordering of burst activity could play an important role in synaptic connectivity formation and the emergence of small-world topology in the developing brain.

Functional Connectome of the Fetal Brain

Large-scale functional connectome formation and reorganization is apparent in the second trimester of pregnancy, making it a crucial and vulnerable time window in connectome development. Here we identified which architectural principles of functional connectome organization are initiated before birth, and contrast those with topological characteristics observed in the mature adult brain. A sample of 105 pregnant women participated in human fetal resting-state fMRI studies (fetal gestational age between 20 and 40 weeks). Connectome analysis was used to analyze weighted network characteristics of fetal macroscale brain wiring. We identified efficient network attributes, common functional modules, and high overlap between the fetal and adult brain network. Our results indicate that key features of the functional connectome are present in the second and third trimesters of pregnancy. Understanding the organizational principles of fetal connectome organization may bring opportunities to develop markers for early detection of alterations of brain function.SIGNIFICANCE STATEMENT The fetal to neonatal period is well known as a critical stage in brain development. Rapid neurodevelopmental processes establish key functional neural circuits of the human brain. Prenatal risk factors may interfere with early trajectories of connectome formation and thereby shape future health outcomes. Recent advances in MRI have made it possible to examine fetal brain functional connectivity. In this study, we evaluate the network topography of normative functional network development during connectome genesis in utero Understanding the developmental trajectory of brain connectivity provides a basis for understanding how the prenatal period shapes future brain function and disease dysfunction.

Neonatal infant EEG bursts are altered by prenatal maternal depression and serotonin selective reuptake inhibitor use

OBJECTIVE

Increasingly, serotonin selective reuptake inhibitor (SSRI) medications are prescribed in pregnancy. These medications pass freely into the developing fetus but little is known about their effect on brain development in humans. In this study we determine if prenatal maternal depression and SSRI medication change the EEG infant delta brush bursts which are an early marker of normal brain maturation.

METHODS

We measured delta brush bursts from the term infants of three groups of mothers (controls (N = 52), depressed untreated (N = 15), and those taking serotonin SSRI medication (N = 10). High density EEGs were obtained during sleep at an average age of 44 weeks post conceptional age. We measured the rate of occurrence, brush amplitude, oscillation frequency and duration of the bursts.

RESULTS

Compared to infants of control mothers, the parameters of delta brush bursts of the offspring of depressed and SSRI-using mothers are significantly altered: burst amplitude is decreased; the oscillation frequency increased, and the duration increased (SSRI only). These significant differences were found during both sleep states.

CONCLUSIONS

Electrocortical bursting activity (i.e. delta brushes) is known to play an important role in early central nervous system (CNS) synaptic formation and function.

SIGNIFICANCE

Maternal depression or SSRI use may alter brain function in their offspring.

GABA Regulation of Burst Firing in Hippocampal Astrocyte Neural Circuit: A Biophysical Model

It is now widely accepted that glia cells and gamma-aminobutyric acidergic (GABA) interneurons dynamically regulate synaptic transmission and neuronal activity in time and space. This paper presents a biophysical model that captures the interaction between an astrocyte cell, a GABA interneuron and pre/postsynaptic neurons. Specifically, GABA released from a GABA interneuron triggers in astrocytes the release of calcium (Ca²⁺) from the endoplasmic reticulum via the inositol 1, 4, 5-trisphosphate (IP₃) pathway. This results in gliotransmission which elevates the presynaptic transmission probability rate (PR) causing weight potentiation and a gradual increase in postsynaptic neuronal firing, that eventually stabilizes. However, by capturing the complex interactions between IP₃, generated from both GABA and the 2-arachidonyl glycerol (2-AG) pathway, and PR, this paper shows that this interaction not only gives rise to an initial weight potentiation phase but also this phase is followed by postsynaptic bursting behavior. Moreover, the model will show that there is a presynaptic frequency range over which burst firing can occur. The proposed model offers a novel cellular level mechanism that may underpin both seizure-like activity and neuronal synchrony across different brain regions.

Simultaneous EEG-fMRI: Evaluating the Effect of the EEG Cap-Cabling Configuration on the Gradient Artifact

Electroencephalography (EEG) data recorded during simultaneous EEG-fMRI experiments are contaminated by large gradient artifacts (GA). The amplitude of the GA depends on the area of the wire loops formed by the EEG leads, as well as on the rate of switching of the magnetic field gradients, which are essential for MR imaging. Average artifact subtraction (AAS), the most commonly used method for GA correction, relies on the EEG amplifier having a large enough dynamic range to characterize the artifact voltages. Low-pass filtering (250 Hz cut-off) is generally used to attenuate the high-frequency voltage fluctuations of the GA, but even with this precaution channel saturation can occur, particularly during acquisition of high spatial resolution MRI data. Previous work has shown that the ribbon cable, used to connect the EEG cap and amplifier, makes a significant contribution to the GA, since the cable geometry produces large effective wire-loop areas. However, by appropriately connecting the wires of the ribbon cable to the EEG cap it should be possible to minimize the overall range and root mean square (RMS) amplitude of the GA by producing partial cancelation of the cap and cable contributions. Here by modifying the connections of the EEG cap to a 1 m ribbon cable we were able to reduce the range of the GA for a high-resolution coronal echo planar Imaging (EPI) acquisition by a factor of ∼ 1.6 and by a factor of ∼ 1.15 for a standard axial EPI acquisition. These changes could potentially be translated into a reduction in the required dynamic range, an increase in the EEG bandwidth or an increase in the achievable image resolution without saturation, all of which could be beneficially exploited in EEG-fMRI studies. The re-wiring could also prevent the system from saturating when small subject movements occur using the standard recording bandwidth.

Prenatal lead exposure impacts cross-hemispheric and long-range connectivity in the human fetal brain

Lead represents a highly prevalent metal toxicant with potential to alter human biology in lasting ways. A population segment that is particularly vulnerable to the negative consequences of lead exposure is the human fetus, as exposure events occurring before birth are linked to varied and long-ranging negative health and behavioral outcomes. An area that has yet to be addressed is the potential that lead exposure during pregnancy alters brain development even before an individual is born. Here, we combine prenatal lead exposure information extracted from newborn bloodspots with the human fetal brain functional MRI data to assess whether neural network connectivity differs between lead-exposed and lead-naïve fetuses. We found that neural connectivity patterns differed in lead-exposed and comparison groups such that fetuses that were not exposed demonstrated stronger age-related increases in cross-hemispheric connectivity, while the lead-exposed group demonstrated stronger age-related increases in posterior cingulate cortex (PCC) to lateral prefrontal cortex (PFC) connectivity. These are the first results to demonstrate metal toxicant-related alterations in human fetal neural connectivity. Remarkably, the findings point to alterations in systems that support higher-order cognitive and regulatory functions. Objectives for future work are to replicate these results in larger samples and to test the possibility that these alterations may account for significant variation in future child cognitive and behavioral outcomes.

How Early Can a Seizure Happen? Pathophysiological Considerations of Extremely Premature Infant Brain Development

Seizures in neonates represent a neurologic emergency requiring prompt recognition, determination of etiology, and treatment. Yet, the definition and identification of neonatal seizures remain challenging and controversial, in part due to the unique physiology of brain development at this life stage. These issues are compounded when considering seizures in premature infants, in whom the complexities of brain development may engender different clinical and electrographic seizure features at different points in neuronal maturation. In extremely premature infants (< 28 weeks gestational age), seizure pathophysiology has not been explored in detail. This review discusses the physiological and structural development of the brain in this developmental window, focusing on factors that may lead to seizures and their consequences at this early time point. We hypothesize that the clinical and electrographic phenomenology of seizures in extremely preterm infants reflects the specific pathophysiology of brain development in that age window.

Behavioural discrimination of noxious stimuli in infants is dependent on brain maturation

Changes in facial expression are an essential form of social communication and in nonverbal infants are often used to alert care providers to pain-related distress. However, studies of early human brain development suggest that premature infants aged less than 34 weeks' gestation do not display discriminative brain activity patterns to equally salient noxious and innocuous events. Here we examine the development of facial expression in 105 infants, aged between 28 and 42 weeks' gestation. We show that the presence of facial expression change after noxious and innocuous stimulation is age-dependent and that discriminative facial expressions emerge from approximately 33 weeks' gestation. In a subset of 49 infants, we also recorded EEG brain activity and demonstrated that the temporal emergence of facial discrimination mirrors the developmental profile of the brain's ability to generate discriminative responses. Furthermore, within individual infants, the ability to display discriminative facial expressions is significantly related to brain response maturity. These data demonstrate that the emergence of behavioural discrimination in early human life corresponds to our brain's ability to discriminate noxious and innocuous events and raises fundamental questions as to how best to interpret infant behaviours when measuring and treating pain in premature infants.

Neonatal brain injury and aberrant connectivity

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

Developmental trajectory of movement-related cortical oscillations during active sleep in a cross-sectional cohort of pre-term and full-term human infants

In neonatal animal models, isolated limb movements during active sleep provide input to immature somatomotor cortex necessary for its development and are somatotopically encoded by alpha-beta oscillations as late as the equivalent of human full-term. Limb movements elicit similar neural patterns in very pre-term human infants (average 30 corrected gestational weeks), suggesting an analogous role in humans, but it is unknown until when they subserve this function. In a cohort of 19 neonates (31-42 corrected gestational weeks) we showed that isolated hand movements during active sleep continue to induce these same somatotopically distributed oscillations well into the perinatal period, but that these oscillations decline towards full-term and fully disappear at 41 corrected gestational weeks (equivalent to the end of gestation). We also showed that these highly localised alpha-beta oscillations are associated with an increase in delta oscillations which extends to the frontal area and does not decline with age. These results suggest that isolated limb movements during active sleep could have an important role in experience-dependent somatomotor development up until normal birth in humans.

Decreased BOLD fluctuations in lateral temporal cortices of premature born adults

Lasting volume reductions in subcortical and temporal-insular cortices after premature birth suggest altered ongoing activity in these areas. We hypothesized altered fluctuations in ongoing neural excitability and activity, as measured by slowly fluctuating blood oxygenation of resting-state functional MRI (rs-fMRI), in premature born adults, with altered fluctuations being linked with underlying brain volume reductions. To investigate this hypothesis, 94 very preterm/very low birth weight (VP/VLBW) and 92 full-term born young adults underwent structural and rs-fMRI data acquisition with voxel-based morphometry and amplitude of low-frequency fluctuations (ALFF) as main outcome measure. In VP/VLBW adults, ALFF was reduced in lateral temporal cortices, and this reduction was positively associated with lower birth weight. Regions of reduced ALFF overlapped with reduced brain volume. On the one hand, ALFF reduction remained after controlling for volume loss, supporting the functional nature of ALFF reductions. On the other hand, ALFF decreases were positively associated with underlying brain volume loss, indicating a relation between structural and functional changes. Furthermore, within the VP/VLBW group, reduced ALFF was associated with reduced IQ, indicating the behavioral relevance of ALFF decreases in temporal cortices. These results demonstrate long-term impact of premature birth on ongoing BOLD fluctuations in lateral temporal cortices, which are linked with brain volume reductions. Data suggest permanently reduced fluctuations in ongoing neural excitability and activity in structurally altered lateral temporal cortices after premature birth.

Emergence of mature cortical activity in wakefulness and sleep in healthy preterm and full-term infants

Study Objectives

Cortical activity patterns develop rapidly over the equivalent of the last trimester of gestation, in parallel with the establishment of sleep architecture. However, the emergence of mature cortical activity in wakefulness compared with sleep states in healthy preterm infants is poorly understood.

Methods

To investigate whether the cortical activity has a different developmental profile in each sleep-wake state, we recorded 11-channels electroencephalography (EEG), electrooculography (EOG), and respiratory movement for 1 hr from 115 infants 34 to 43 weeks-corrected age, with 0.5-17 days of postnatal age. We characterized the trajectory of δ, θ, and α-β oscillations in wakefulness, rapid eye movement (REM) sleep, and non-REM sleep by calculating the power spectrum of the EEG, averaged across artifact-free epochs.

Results

δ-Oscillations in wakefulness and REM sleep decrease with corrected age, particularly in the temporal region, but not in non-REM sleep. θ-Oscillations increase with corrected age in sleep, especially non-REM sleep, but not in wakefulness. On the other hand, α-β oscillations decrease predominantly with postnatal age, independently of sleep-wake state, particularly in the occipital region.

Conclusions

The developmental trajectory of δ and θ rhythms is state-dependent and results in changed cortical activity patterns between states with corrected age, which suggests that these frequency bands may have particular functional roles in each state. Interestingly, postnatal age is associated with a decrease in α-β oscillations overlying primary visual cortex in every sleep-wake state, suggesting that postnatal experience (including the first visual input through open eyes during periods of wakefulness) is associated with resting-state visual cortical activity changes.

Early human brain development: Starring the subplate

This review summarizes early human brain development on the basis of neuroanatomical data and functional connectomics. It indicates that the most significant changes in the brain occur during the second half of gestation and the first three months post-term, in particular in the cortical subplate and cerebellum. As the transient subplate pairs a high rate of intricate developmental changes and interactions with clear functional activity, two phases of development are distinguished: a) the transient cortical subplate phase, ending at 3 months post-term when the permanent circuitries in the primary motor, somatosensory and visual cortices have replaced the subplate; and subsequently, b) the phase in which the permanent circuitries dominate. In the association areas the subplate dissolves in the remainder of the first postnatal year. During both phases developmental changes are paralleled by continuous reconfigurations in network activity. The reviewed literature also suggests that disruption of subplate development may play a pivotal role in developmental disorders, such as cerebral palsy, autism spectrum disorders, attention deficit hyperactivity disorder and schizophrenia.

Imaging structural and functional brain development in early childhood

In humans, the period from term birth to ∼2 years of age is characterized by rapid and dynamic brain development and plays an important role in cognitive development and risk of disorders such as autism and schizophrenia. Recent imaging studies have begun to delineate the growth trajectories of brain structure and function in the first years after birth and their relationship to cognition and risk of neuropsychiatric disorders. This Review discusses the development of grey and white matter and structural and functional networks, as well as genetic and environmental influences on early-childhood brain development. We also discuss initial evidence regarding the usefulness of early imaging biomarkers for predicting cognitive outcomes and risk of neuropsychiatric disorders.

Hubs in the human fetal brain network

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Network analysis has identified highly connected regions, or hubs, in the human brain.

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Whether network hubs emerge in utero has yet to be examined.

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We found that fetal hubs were located in both primary and association cortices.

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Interestingly, hubs were identified close to fusiform facial and Wernicke’s areas.

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These putative hubs may be points of vulnerability in fetal brain development.

Advances in neuroimaging and network analyses have lead to discovery of highly connected regions, or hubs, in the connectional architecture of the human brain. Whether these hubs emerge in utero, has yet to be examined. The current study addresses this question and aims to determine the location of neural hubs in human fetuses. Fetal resting-state fMRI data (N = 105) was used to construct connectivity matrices for 197 discrete brain regions. We discovered that within the connectional functional organization of the human fetal brain key hubs are emerging. Consistent with prior reports in infants, visual and motor regions were identified as emerging hub areas, specifically in cerebellar areas. We also found evidence for network hubs in association cortex, including areas remarkably close to the adult fusiform facial and Wernicke areas. Functional significance of hub structure was confirmed by computationally deleting hub versus random nodes and observing that global efficiency decreased significantly more when hubs were removed (p < .001). Taken together, we conclude that both primary and association brain regions demonstrate centrality in network organization before birth. While fetal hubs may be important for facilitating network communication, they may also form potential points of vulnerability in fetal brain development.

Machine learning shows association between genetic variability in PPARG and cerebral connectivity in preterm infants

Preterm birth affects 11% of births globally; 35% of infants develop long-term neurocognitive problems, and prematurity leads to the loss of 75 million disability adjusted life years per annum worldwide. Imaging studies have shown that these infants have extensive alterations in brain development, but little is known about the molecular or cellular mechanisms involved. This imaging genetics study found a strong association between abnormal cerebral connectivity and variability in the PPARG gene, implicating PPARG signaling in abnormal white-matter development in preterm infants and suggesting a tractable new target for therapeutic research.

Preterm infants show abnormal structural and functional brain development, and have a high risk of long-term neurocognitive problems. The molecular and cellular mechanisms involved are poorly understood, but novel methods now make it possible to address them by examining the relationship between common genetic variability and brain endophenotype. We addressed the hypothesis that variability in the Peroxisome Proliferator Activated Receptor (PPAR) pathway would be related to brain development. We employed machine learning in an unsupervised, unbiased, combined analysis of whole-brain diffusion tractography together with genomewide, single-nucleotide polymorphism (SNP)-based genotypes from a cohort of 272 preterm infants, using Sparse Reduced Rank Regression (sRRR) and correcting for ethnicity and age at birth and imaging. Empirical selection frequencies for SNPs associated with cerebral connectivity ranged from 0.663 to zero, with multiple highly selected SNPs mapping to genes for PPARG (six SNPs), ITGA6 (four SNPs), and FXR1 (two SNPs). SNPs in PPARG were significantly overrepresented (ranked 7–11 and 67 of 556,000 SNPs; P < 2.2 × 10⁻⁷), and were mostly in introns or regulatory regions with predicted effects including protein coding and nonsense-mediated decay. Edge-centric graph-theoretic analysis showed that highly selected white-matter tracts were consistent across the group and important for information transfer (P < 2.2 × 10⁻¹⁷); they most often connected to the insula (P < 6 × 10⁻¹⁷). These results suggest that the inhibited brain development seen in humans exposed to the stress of a premature extrauterine environment is modulated by genetic factors, and that PPARG signaling has a previously unrecognized role in cerebral development.

Structured Spontaneity: Building Circuits in the Human Prenatal Brain

Early brain activity is crucial for neurogenesis and the development of brain networks. However, it has been challenging to localize regions in the developing human brain that contribute to spontaneous waves of neuronal activity. Recently, Arichi and colleagues reported that the temporal and heteromodal insular cortices have a central role in propagating these neural instructional signals.