Neural histology and neurogenesis of the human fetal and infant brain

Burst of gyrification in the human brain after birth

Gyrification, the intricate folding of the brain's cortex, begins mid-gestation and surges dramatically throughout the perinatal period. Yet, a critical factor has been largely overlooked in neurodevelopmental research: the profound impact of birth on brain structure. Leveraging the largest known perinatal MRI dataset-819 sessions spanning 21 to 45 postconceptional weeks-we reveal a burst in gyrification immediately following birth (~37 weeks post-conception), amounting to half the entire gyrification expansion occurring during the fetal period. Using state-of-the-art, homogenized imaging processing tools across varied acquisition protocols, and applying a regression discontinuity design approach that is novel to neuroimaging, we provide the first evidence of a sudden, birth-triggered shift in cortical development. Investigation of additional cortical features confirms that this effect is uniquely confined to gyrification. This finding sheds light onto the understanding of early brain development, suggesting that the neurobiological consequences of birth may hold significant behavioral and physiological relevance.

Gestational age at birth and cognitive outcomes in term-born children: Evidence from Chinese and British cohorts

INTRODUCTION

Older gestational age (GA) has been associated with more favourable cognitive outcomes in preterm children. Recent evidence suggests this may also apply to term-born children. This study aims to examine the association between GA and early neurodevelopmental outcomes in children born at term in China and the UK.

METHODS

Participants were term-born children from two cohorts, the Sichuan Multi-stratified Infants and Early Life (SMILE) study in China and the Developing Human Connectome Project (dHCP) in the UK. Early cognitive outcomes were assessed at 6 months in the SMILE study, and at 18 months in the dHCP. Linear regression models were conducted to examine the association between GA at birth and early cognitive outcomes in each cohort separately.

RESULTS

A sample of 1245 participants from the SMILE study and 406 participants for the dHCP were included in the analysis. In the SMILE study, longer GA was associated with better mental developmental (B = 2.47 [1.60, 3.34], P < .001) and psychomotor outcomes (B = 2.91 [2.01, 3.82], P < .001), after controlling for sex, parental education, family yearly income, maternal age, maternal depressive symptoms, and birth weight; in the dHCP, longer GA was associated with better cognitive (B = 1.35 [0.33, 2.37], P = .010) and motor outcomes (B = 1.49 [0.59, 2.39], P = .001), after controlling for sex, relative social deprivation, maternal depressive symptoms and birth weight.

CONCLUSIONS

Older GA in term-born toddlers is associated with more favourable developmental outcomes across different cultural contexts.

The Awakening of the Newborn Human Infant and the Emergence of Consciousness

Consciousness develops gradually in the womb and after birth, rather than being an all or none phenomenon. A newborn infant is aroused and wakes up at birth, due to the enormous sensory stimulation and stress that it undergoes during the transition from an aquatic environment to air. Its first breaths activate the locus coeruleus, as indicated by the large pupils of the newborn. The infant seems to be aware of its body and can recognise its mother's facial expressions, voice and smell. A default mode network matures soon after birth which appears to keep the brain in a conscious state. Thus the newborn infant is probably conscious, albeit at a low level. The foetus also shows some signs of being conscious after about 24 weeks of gestation, although it is mainly asleep in the womb and less aware of its environment. Before that stage, the nerves from the primary somatosensory, visual and auditory areas are not yet connected with the site of consciousness in the cerebral cortex.

Small brains but big challenges: white matter tractography in early life samples

In the human brain, white matter development is a complex and long-lasting process involving intermingling micro- and macrostructural mechanisms, such as fiber growth, pruning and myelination. Did you know that all these neurodevelopmental changes strongly affect MRI signals, with consequences on tractography performances and reliability? This communication aims to elaborate on these aspects, highlighting the importance of tracking and studying the developing connections with dedicated approaches.

Cortical scaling of the neonatal brain in typical and altered development

Theoretically derived scaling laws capture the nonlinear relationships between rapidly expanding brain volume and cortical gyrification across mammalian species and in adult humans. However, the preservation of these laws has not been comprehensively assessed in typical or pathological brain development. Here, we assessed the scaling laws governing cortical thickness (CT), surface area (SA), and cortical folding in the neonatal brain. We also assessed multivariate morphological terms that capture brain size, shape, and folding processes. The sample consisted of 345 typically developing infants, 73 preterm infants, and 107 infants with congenital heart disease (CHD) who underwent brain MRI. Our results show that typically developing neonates and those with CHD follow the cortical folding scaling law obtained from mammalian brains, children, and adults which captures the relationship between exposed SA, total SA, and CT. Cortical folding scaling was not affected by gestational age at birth, postmenstrual age at scan, sex, or multiple birth in these populations. CHD was characterized by a unique reduction in the multivariate morphological term capturing size, suggesting that CHD affects cortical growth overall but not cortical folding processes. In contrast, preterm birth was characterized by altered cortical folding scaling and altered shape, suggesting that the developmentally programmed processes of cortical folding are disrupted in this population. The degree of altered shape was associated with cognitive abilities in early childhood in preterm infants.

Development of brain metastable dynamics during the equivalent of the third gestational trimester

Metastability, a concept from dynamical systems theory, provides a framework for understanding how the brain shifts between various functional states and underpins essential cognitive, behavioural, and social function. While studied in adults, metastability in early brain development has only received recent attention. As the brain undergoes dramatic functional and structural changes over the third gestational trimester, here we review how these are reflected in changes in brain metastable dynamics in preterm, preterm at term-equivalent and full-term neonates. We synthesize findings from EEG, fMRI, fUS, and computational models, focusing on the spatial distribution and temporal dynamics of metastable states, which include functional integration and segregation, signal predictability and complexity. Despite fragmented evidence, studies suggest that neonatal metastability develops over the equivalent of the third gestational trimester, with increasing ability for integration-segregation, broader range of metastable states, faster metastable state transitions and greater signal complexity. Preterms at term-equivalent age exhibit immature metastability features compared to full-terms. We explain and interpret these changes in terms of maturation of the brain in a free energy landscape and establishment of cognitive functions.

Early Development and Co-Evolution of Microstructural and Functional Brain Connectomes: A Multi-Modal MRI Study in Preterm and Full-Term Infants

Functional networks characterized by coherent neural activity across distributed brain regions have been observed to emerge early in neurodevelopment. Synchronized maturation across regions that relate to functional connectivity (FC) could be partially reflected in the developmental changes in underlying microstructure. Nevertheless, covariation of regional microstructural properties, termed "microstructural connectivity" (MC), and its relationship to the emergence of functional specialization during the early neurodevelopmental period remain poorly understood. We investigated the evolution of MC and FC postnatally across a set of cortical and subcortical regions, focusing on 45 preterm infants scanned longitudinally, and compared to 45 matched full-term neonates as part of the developing Human Connectome Project (dHCP) using direct comparisons of grey-matter connectivity strengths as well as network-based analyses. Our findings revealed a global strengthening of both MC and FC with age, with connection-specific variability influenced by the connection maturational stage. Prematurity at term-equivalent age was associated with significant connectivity disruptions, particularly in FC. During the preterm period, direct comparisons of MC and FC strength showed a positive linear relationship, which seemed to weaken with development. On the other hand, overlaps between MC- and FC-derived networks (estimated with Mutual Information) increased with age, suggesting a potential convergence towards a shared underlying network structure that may support the co-evolution of microstructural and functional systems. Our study offers novel insights into the dynamic interplay between microstructural and functional brain development and highlights the potential of MC as a complementary descriptor for characterizing brain network development and alterations due to perinatal insults such as premature birth.

Association and shared biological bases between birth weight and cortical structure

Associations between birth weight and cortical structural phenotypes have been detected; however, the understanding is incomprehensive, and the potential biological bases are not well defined. Leveraging data from genome-wide association studies, we investigated the associations and the shared transcriptomic, proteomic and cellular bases of birth weight and 13 cortical structural phenotypes. Mendelian randomization analyses were performed to examine associations between birth weight and cortical structure. Downstream transcriptome-wide association study (TWAS), proteome-wide association study (PWAS) and summary-based Mendelian randomization (SMR) analyses were utilized to identify the shared cis-regulated gene expressions and proteins. Finally, cell-type expression-specific integration for complex traits (CELLECT) analyses were conducted to explore the enriched cell types. The Mendelian randomization analyses found positive associations between birth weight and global cortical folding index, intrinsic curvature index, local gyrification index, surface area and volume. Downstream transcriptomic-level TWAS and SMR identified three gene expressions both linked to birth weight and at least one cortical structural phenotype (CNNM2, RABGAP1 and CENPW). Parallel PWAS and SMR analyses at the proteomic level identified four proteins linked to both phenotypes (CNNM2, RAB7L1, RAB5B and PPA2), of which CNNM2 was replicated. CELLECT analyses revealed brain cell types enriched in birth weight, including pericytes, inhibitory GABAergic neurons and cerebrovascular cells. These findings support the importance of early life growth to cortical structure, and suggest underlying transcriptomic, proteomic and cellular bases. These results provide intriguing targets for further research into the mechanisms of cortical development.

Early White Matter Microstructure Alterations in Infants with Down Syndrome

Importance

Down syndrome, resulting from trisomy 21, is the most prevalent chromosomal disorder and a leading cause of intellectual disability. Despite its significant impact on brain development, research on the white matter microstructure in infants with Down syndrome remains limited.

Objective

To investigate early white matter microstructure in infants with Down syndrome using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI).

Design

Infants were recruited and scanned between March 2019 and May 2024 as participants in prospective studies conducted by the Infant Brain Imaging Study (IBIS) Network. Data were analyzed in October 2024.

Setting

Data collection occurred at five research centers in Minnesota, Missouri, North Carolina, Pennsylvania, and Washington.

Participants

Down syndrome and control infants were scanned at 6 months of age. Control infants had no Down syndrome diagnosis and either had a typically developing older sibling or, if they had an older sibling with autism, were confirmed not to meet clinical best estimate criteria for an autism diagnosis.

Exposure

Diagnosis of Down syndrome.

Main Outcomes and Measures

The outcome of interest was white matter microstructure quantified using DTI and NODDI measures.

Results

A total of 49 Down syndrome (28 [57.14%] female) and 37 control (18 [48.65%] female) infants were included. Infants with Down syndrome showed significant reductions in fractional anisotropy and neurite density index across multiple association tracts, particularly in the inferior fronto-occipital fasciculus and superior longitudinal fasciculus II, consistent with reduced structural integrity and neurite density. These tracts also demonstrated increased radial diffusivity, suggesting delayed myelination. The inferior fronto-occipital fasciculus and uncinate fasciculus exhibited increased neurite dispersion and fanning in Down syndrome infants, reflected by elevated orientation dispersion index. Notably, the optic tracts in Down syndrome infants exhibited a distinct pattern of elevated fractional anisotropy and axial diffusivity, and lower radial diffusivity and orientation dispersion index, suggesting an early maturation of these pathways.

Conclusions and Relevance

This first characterization of white matter microstructure in Down syndrome infants reveals widespread white matter developmental delays. These findings provide new insights into the early neurodevelopment of Down syndrome and may inform early therapeutic interventions.

A microanatomical study of the precentral cerebral wall in human fetuses of the second trimester with ventriculomegaly and corpus callosal dysgenesis

BACKGROUND

The complex structure and function of the cerebrum make it a key focus in neuroscience research. It develops from telencephalic vesicles through processes such as cell growth, division, and migration from the neuroepithelium's ventricular matrix, forming the six-layered isocortex or neocortex. Multipotent neuroepithelial cells give rise to both neuronal and glial precursors, which populate the cerebral cortex. This study investigated the number of cerebral layers and their thickness in second-trimester human fetuses with ventriculomegaly and corpus callosal dysgenesis.

MATERIALS AND METHODS

This study was conducted at Kasturba Medical College, Manipal, with Institutional Ethics Committee approval. The study analyzed the cerebral wall of 10 human fetuses in the second trimester. Histological sections were stained with hematoxylin and eosin, and the cortical layers were identified and measured.

RESULTS

The mean total cerebral wall thickness was 4079.2 μm in fetuses with ventriculomegaly and 6532.8 μm in fetuses with corpus callosal dysgenesis. The morphological findings in corpus callosal dysgenesis included disorganization of the cortical plate zone, which may impact brain development, as well as the presence of dilated blood vessels.

CONCLUSION

This study quantified the six transient layers of the precentral cerebral wall, which are distinct during the embryonic stage and disappear at term. These layers are generally associated with specific neurodevelopmental processes. Compared with ventriculomegaly, corpus callosal dysgenesis involves distinct morphological alterations. One sample had disorganized cells in the cortical plate, and another displayed dilated blood vessels in the subventricular zone. These findings indicate significant disruptions in cortical development in corpus callosal dysgenesis.

Whole Brain MRI Assessment of Age and Sex-Related R2* Changes in the Human Fetal Brain

Iron in the brain is essential to neurodevelopmental processes, as it supports neural functions, including processes of oxygen delivery, electron transport, and enzymatic activity. However, the development of brain iron before birth is scarcely understood. By estimating R2* (1/T2*) relaxometry from a sizable sample of fetal multiecho echo-planar imaging (EPI) scans, which is the standard sequence for functional magnetic resonance imaging (fMRI), across gestation, this study investigates age and sex-related changes in iron, across regions and tissue segments. Our findings reveal that brain R2* levels significantly increase throughout gestation spanning many different regions, except the frontal lobe. Furthermore, females exhibit a faster rate of R2* increase compared to males, in both gray matter and white matter. This sex effect is particularly notable within the left insula. This work represents the first MRI examination of iron accumulation and sex differences in developing fetal brains. This is also the first study to establish R2* estimation methodology in fetal multiecho functional MRI.

A detailed spatiotemporal atlas of the white matter tracts for the fetal brain

This study presents the construction of a comprehensive spatiotemporal atlas of white matter tracts in the fetal brain for every gestational week between 23 and 36 wk using diffusion MRI (dMRI). Our research leverages data collected from fetal MRI scans, capturing the dynamic changes in the brain's architecture and microstructure during this critical period. The atlas includes 60 distinct white matter tracts, including commissural, projection, and association fibers. We employed advanced fetal dMRI processing techniques and tractography to map and characterize the developmental trajectories of these tracts. Our findings reveal that the development of these tracts is characterized by complex patterns of fractional anisotropy (FA) and mean diffusivity (MD), coinciding with the intensity of histogenic processes such as axonal growth, involution of the radial-glial scaffolding, and synaptic pruning. This atlas can serve as a useful resource for neuroscience research and clinical practice, improving our understanding of the fetal brain and potentially aiding in the early diagnosis of neurodevelopmental disorders. By detailing the normal progression of white matter tract development, the atlas can be used as a benchmark for identifying deviations that may indicate neurological anomalies or predispositions to disorders.

Reversal of neurodevelopmental impairment and cognitive enhancement by pharmacological intervention with the polyphenol polydatin in a Down syndrome model

Intellectual disability (ID) is the unavoidable hallmark of Down syndrome (DS), a genetic condition due to triplication of chromosome 21. ID in DS is largely attributable to neurogenesis and dendritogenesis alterations taking place in the prenatal/neonatal period, the most critical time window for brain development. There are currently no treatments for ID in DS. Considering the timeline of brain development, treatment aimed at improving the neurological phenotypes of DS should be initiated as early as possible and use safe agents. The goal of this study was to establish whether it is possible to improve DS-linked neurodevelopmental defects through early treatment with polydatin, a natural polyphenol. We used the Ts65Dn mouse model of DS and focused on the hippocampus, a brain region fundamental for long-term memory. We found that in Ts65Dn mice of both sexes treated with polydatin from postnatal (P) day 3 to P15 there was full restoration of neurogenesis, neuron number, and dendritic development. These effects were accompanied by normalization of Cyclin D1 and DSCAM levels, which may account for the rescue of neurogenesis and dendritogenesis, respectively. Importantly, in Ts65Dn mice treated with polydatin from P3 to adolescence (∼P50) there was full restoration of hippocampus-dependent memory, indicating a pro-cognitive outcome of treatment. No adverse effects were observed on the body and brain weight. The efficacy and safety of polydatin in a model of DS prospect the possibility of its use during early life stages for amelioration of DS-linked neurodevelopmental alterations.

A human forebrain organoid model reveals the essential function of GTF2IRD1-TTR-ERK axis for the neurodevelopmental deficits of Williams syndrome

Williams syndrome (WS; OMIM#194050) is a rare disorder, which is caused by the microdeletion of one copy of 25-27 genes, and WS patients display diverse neuronal deficits. Although remarkable progresses have been achieved, the mechanisms for these distinct deficits are still largely unknown. Here, we have shown that neural progenitor cells (NPCs) in WS forebrain organoids display abnormal proliferation and differentiation capabilities, and synapse formation. Genes with altered expression are related to neuronal development and neurogenesis. Single cell RNA-seq (scRNA-seq) data analysis revealed 13 clusters in healthy control and WS organoids. WS organoids show an aberrant generation of excitatory neurons. Mechanistically, the expression of transthyretin (TTR) are remarkably decreased in WS forebrain organoids. We have found that GTF2IRD1 encoded by one WS associated gene GTF2IRD1 binds to TTR promoter regions and regulates the expression of TTR. In addition, exogenous TTR can activate ERK signaling and rescue neurogenic deficits of WS forebrain organoids. Gtf2ird1-deficient mice display similar neurodevelopmental deficits as observed in WS organoids. Collectively, our study reveals critical function of GTF2IRD1 in regulating neurodevelopment of WS forebrain organoids and mice through regulating TTR-ERK pathway.

Development of the basic architecture of neocortical circuitry in the human fetus as revealed by the coupling spatiotemporal pattern of synaptogenesis along with microstructure and macroscale in vivo MR imaging

In humans, a quantifiable number of cortical synapses appears early in fetal life. In this paper, we present a bridge across different scales of resolution and the distribution of synapses across the transient cytoarchitectonic compartments: marginal zone (MZ), cortical plate (CP), subplate (SP), and in vivo MR images. The tissue of somatosensory cortex (7-26 postconceptional weeks (PCW)) was prepared for electron microscopy, and classified synapses with a determined subpial depth were used for creating histograms matched to the histological sections immunoreacted for synaptic markers and aligned to in vivo MR images (1.5 T) of corresponding fetal ages (maternal indication). Two time periods and laminar patterns of synaptogenesis were identified: an early and midfetal two-compartmental distribution (MZ and SP) and a late fetal three-compartmental distribution (CP synaptogenesis). During both periods, a voluminous, synapse-rich SP was visualized on the in vivo MR. Another novel finding concerns the phase of secondary expansion of the SP (13 PCW), where a quantifiable number of synapses appears in the upper SP. This lamina shows a T2 intermediate signal intensity below the low signal CP. In conclusion, the early fetal appearance of synapses shows early differentiation of putative genetic mechanisms underlying the synthesis, transport and assembly of synaptic proteins. "Pioneering" synapses are likely to play a morphogenetic role in constructing of fundamental circuitry architecture due to interaction between neurons. They underlie spontaneous, evoked, and resting state activity prior to ex utero experience. Synapses can also mediate genetic and environmental triggers, adversely altering the development of cortical circuitry and leading to neurodevelopmental disorders.

Prenatal Stress and Maternal Role in Neurodevelopment

This review summarizes recent findings on stress-related programming of brain development in utero, with an emphasis on situating findings within the mothers' broader psychosocial experiences. Meta-analyses of observational studies on prenatal stress exposure indicate the direction and size of effects on child neurodevelopment are heterogeneous across studies. Inspired by lifespan and topological frameworks of adversity, we conceptualize individual variation in mothers' lived experience during and prior to pregnancy as a key determinant of these heterogeneous effects across populations. We structure our review to discuss experiential categories that may uniquely shape the psychological and biological influence of stress on pregnant mothers and their developing children, including current socioeconomic resources, exposure to chronic and traumatic stressors, culture and historical trauma, and the contours of prenatal stress itself. We conclude by identifying next steps that hold potential to meaningfully advance the field of fetal programming.

Regulation of adult neurogenesis: the crucial role of astrocytic mitochondria

Neurogenesis has emerged as a promising therapeutic approach for central nervous system disorders. The role of neuronal mitochondria in neurogenesis is well-studied, however, recent evidence underscores the critical role of astrocytic mitochondrial function in regulating neurogenesis and the underlying mechanisms remain incompletely understood. This review highlights the regulatory effects of astrocyte mitochondria on neurogenesis, focusing on metabolic support, calcium homeostasis, and the secretion of neurotrophic factors. The effect of astrocytic mitochondrial dysfunction in the pathophysiology and treatment strategies of Alzheimer's disease and depression is discussed. Greater attention is needed to investigate the mitochondrial autophagy, dynamics, biogenesis, and energy metabolism in neurogenesis. Targeting astrocyte mitochondria presents a potential therapeutic strategy for enhancing neural regeneration.

The Impact of Early Life Experiences on Stress Neurobiology and the Development of Anxiety

We examine the association between stress exposure during early development (i.e., the prenatal period through the first two postnatal years) and variation in brain structure and function relevant to anxiety. Evidence of stress-related effects occurring in regions essential for emotional processing and regulation may increase susceptibility to anxiety.

Revisiting the functional monitoring of brain development in premature neonates. A new direction in clinical care and research

The first 1000 days of life are of paramount importance for neonatal development. Premature newborns are exposed early to the external environment, modifying the fetal exposome and leading to overexposure in some sensory domains and deprivation in others. The resulting neurodevelopmental effects may persist throughout the individual's lifetime. Several neonatal neuromonitoring techniques can be used to investigate neural mechanisms in early postnatal development. EEG is the most widely used, as it is easy to perform, even at the patient's bedside. It is not expensive and provides information with a high temporal resolution and relatively good spatial resolution when performed in high-density mode. Functional near-infrared spectroscopy (fNIRS), a technique for monitoring vascular network dynamics, can also be used at the patient's bedside. It is not expensive and has a good spatial resolution at the cortical surface. These two techniques can be combined for simultaneous monitoring of the neuronal and vascular networks in premature newborns, providing insight into neurodevelopment before term. However, the extent to which more general conclusions about fetal development can be drawn from findings for premature neonates remains unclear due to considerable differences in environmental and medical situations. Fetal MEG (fMEG, as an alternative to EEG for preterm infants) and fMRI (as an alternative to fNIRS for preterm infants) can also be used to investigate fetal neurodevelopment on a trimester-specific basis. These techniques should be used for validation purposes as they are the only tools available for evaluating neuronal dysfunction in the fetus at the time of the gene-environment interactions influencing transient neuronal progenitor populations in brain structures. But what do these techniques tell us about early neurodevelopment? We address this question here, from two points of view. We first discuss spontaneous neural activity and its electromagnetic and hemodynamic correlates. We then explore the effects of stimulating the immature developing brain with information from exogenous sources, reviewing the available evidence concerning the characteristics of electromagnetic and hemodynamic responses. Once the characteristics of the correlates of neural dynamics have been determined, it will be essential to evaluate their possible modulation in the context of disease and in at-risk populations. Evidence can be collected with various neuroimaging techniques targeting both spontaneous and exogenously driven neural activity. A multimodal approach combining the neuromonitoring of different functional compartments (neuronal and vascular) is required to improve our understanding of the normal functioning and dysfunction of the brain and to identify neurobiomarkers for predicting the neurodevelopmental outcome of premature neonate and fetus. Such an approach would provide a framework for exploring early neurodevelopment, paving the way for the development of tools for earlier diagnosis in these vulnerable populations, thereby facilitating preventive, rescue and reparative neurotherapeutic interventions.

Neural oscillations suggest periodicity encoding during auditory beat processing in the premature brain

When exposed to rhythmic patterns with temporal regularity, adults exhibit an inherent ability to extract and anticipate an underlying sequence of regularly spaced beats, which is internally constructed, as beats are experienced even when no events occur at beat positions (e.g., in the case of rests). Perception of rhythm and synchronization to periodicity is indispensable for development of cognitive functions, social interaction, and adaptive behavior. We evaluated neural oscillatory activity in premature newborns (n = 19, mean age, 32 ± 2.59 weeks gestational age) during exposure to an auditory rhythmic sequence, aiming to identify early traces of periodicity encoding and rhythm processing through entrainment of neural oscillations at this stage of neurodevelopment. The rhythmic sequence elicited a systematic modulation of alpha power, synchronized to expected beat locations coinciding with both tones and rests, and independent of whether the beat was preceded by tone or rest. In addition, the periodic alpha-band fluctuations reached maximal power slightly before the corresponding beat onset times. Together, our results show neural encoding of periodicity in the premature brain involving neural oscillations in the alpha range that are much faster than the beat tempo, through alignment of alpha power to the beat tempo, consistent with observations in adults on predictive processing of temporal regularities in auditory rhythms. RESEARCH HIGHLIGHTS: In response to the presented rhythmic pattern, systematic modulations of alpha power showed that the premature brain extracted the temporal regularity of the underlying beat. In contrast to evoked potentials, which are greatly reduced when there is no sounds event, the modulation of alpha power occurred for beats coinciding with both tones and rests in a predictive way. The findings provide the first evidence for the neural coding of periodicity in auditory rhythm perception before the age of term.

Near-Infrared Spectroscopy for Neonatal Sleep Classification

Sleep, notably active sleep (AS) and quiet sleep (QS), plays a pivotal role in the brain development and gradual maturation of (pre) term infants. Monitoring their sleep patterns is imperative, as it can serve as a tool in promoting neurological maturation and well-being, particularly important in preterm infants who are at an increased risk of immature brain development. An accurate classification of neonatal sleep states can contribute to optimizing treatments for high-risk infants, with respiratory rate (RR) and heart rate (HR) serving as key components in sleep assessment systems for neonates. Recent studies have demonstrated the feasibility of extracting both RR and HR using near-infrared spectroscopy (NIRS) in neonates. This study introduces a comprehensive sleep classification approach leveraging high-frequency NIRS signals recorded at a sampling rate of 100 Hz from a cohort of nine preterm infants admitted to a neonatal intensive care unit. Eight distinct features were extracted from the raw NIRS signals, including HR, RR, motion-related parameters, and proxies for neural activity. These features served as inputs for a deep convolutional neural network (CNN) model designed for the classification of AS and QS sleep states. The performance of the proposed CNN model was evaluated using two cross-validation approaches: ten-fold cross-validation of data pooling and five-fold cross-validation, where each fold contains two independently recorded NIRS data. The accuracy, balanced accuracy, F1-score, Kappa, and AUC-ROC (Area Under the Curve of the Receiver Operating Characteristic) were employed to assess the classifier performance. In addition, comparative analyses against six benchmark classifiers, comprising K-Nearest Neighbors, Naive Bayes, Support Vector Machines, Random Forest (RF), AdaBoost, and XGBoost (XGB), were conducted. Our results reveal the CNN model's superior performance, achieving an average accuracy of 88%, a balanced accuracy of 94%, an F1-score of 91%, Kappa of 95%, and an AUC-ROC of 96% in data pooling cross-validation. Furthermore, in both cross-validation methods, RF and XGB demonstrated accuracy levels closely comparable to the CNN classifier. These findings underscore the feasibility of leveraging high-frequency NIRS data, coupled with NIRS-based HR and RR extraction, for assessing sleep states in neonates, even in an intensive care setting. The user-friendliness, portability, and reduced sensor complexity of the approach suggest its potential applications in various less-demanding settings. This research thus presents a promising avenue for advancing neonatal sleep assessment and its implications for infant health and development.

Ex vivo Magnetic Resonance Imaging of the Human Fetal Brain

BACKGROUND

The fetal brain undergoes a dynamic process of development during gestation, marked by well-orchestrated events such as neuronal proliferation, migration, axonal outgrowth, and dendritic arborization, mainly elucidated through histological studies. Ex vivo magnetic resonance imaging (MRI) has emerged as a useful tool for 3D visualization of the developing fetal brain, serving as a complementary tool to traditional histology.

SUMMARY

In this review, we summarized the commonly employed ex vivo MRI techniques and their advances in fetal brain imaging, and proposed a standard protocol for postmortem fetal brain specimen collection and fixation. We then provided an overview of ex vivo MRI-based studies on the fetal brain.

KEY MESSAGES

According to our review, ex vivo T1- or T2-weighted structural MRI has contributed to the characterization of the anatomy of transient neuronal proliferative zones, the basal ganglia, and the cortex. Diffusion MRI-related techniques, such as diffusion tensor imaging and tractography, have helped investigate the microstructural patterns of fetal brain tissue, as well as the early emergence and development of neuronal migration pathways and white matter bundles. Ex vivo MRI findings have shown strong histological correlations, supporting the potential of MRI in evaluating the developmental events in the fetal brain. Postmortem MRI examinations have also demonstrated comparable, and in certain cases, superior performance to traditional autopsy in revealing fetal brain abnormalities. In conclusion, ex vivo fetal brain MRI is an invaluable tool that provides unique insights into the early stages of brain development.

Multi-echo Acquisition and Thermal Denoising Advances Precision Functional Imaging

The characterization of individual functional brain organization with Precision Functional Mapping has provided important insights in recent years in adults. However, little is known about the ontogeny of inter-individual differences in brain functional organization during human development. Precise characterization of systems organization during periods of high plasticity is likely to be essential for discoveries promoting lifelong health. Obtaining precision fMRI data during development has unique challenges that highlight the importance of establishing new methods to improve data acquisition, processing, and analysis. Here, we investigate two methods that can facilitate attaining this goal: multi-echo (ME) data acquisition and thermal noise removal with Noise Reduction with Distribution Corrected (NORDIC) principal component analysis. We applied these methods to precision fMRI data from adults, children, and newborn infants. In adults, both ME acquisitions and NORDIC increased temporal signal to noise ratio (tSNR) as well as the split-half reliability of functional connectivity matrices, with the combination helping more than either technique alone. The benefits of NORDIC denoising replicated in both our developmental samples. ME acquisitions revealed longer and more variable T2* relaxation times across the brain in infants relative to older children and adults, leading to major differences in the echo weighting for optimally combining ME data. This result suggests ME acquisitions may be a promising tool for optimizing developmental fMRI, albeit application in infants needs further investigation. The present work showcases methodological advances that improve Precision Functional Mapping in adults and developmental populations and, at the same time, highlights the need for further improvements in infant specific fMRI.

Cellularity Defects Are Not Ubiquitous in the Brains of Fetuses With Down Syndrome

Down syndrome (DS) is a genetic pathology characterized by various developmental defects. Unlike other clinical problems, intellectual disability is an invariant clinical trait of DS. Impairment of neurogenesis accompanied by brain hypotrophy is a typical neurodevelopmental phenotype of DS, suggesting that a reduction in the number of cells forming the brain may be a key determinant of intellectual disability. Previous evidence showed that fetuses with DS exhibit widespread hypocellularity in brain regions belonging to the temporal lobe memory systems, which may account for the typical explicit memory impairment that characterizes DS. In the current study, we have examined the basal ganglia, the insular cortex (INS), and the cingulate cortex (CCX) of fetuses with DS and age-matched controls (18-22 weeks of gestation), to establish whether cellularity defects involve regions that are not primarily involved in explicit memory. We found that fetuses with DS exhibit a notable hypocellularity in the putamen (-30%) and globus pallidus (-35%). In contrast, no cellularity differences were found in the INS and CCX, indicating that hypocellularity is not ubiquitous in the DS brain. The hypocellularity found in the basal ganglia, which are critically implicated in the control of movement, suggests that such alterations may contribute to the motor abnormalities of DS. The normal cytoarchitecture of the INS and CCX suggests that the alterations exhibited by people with DS in functions in which these regions are involved are not attributable to neuron paucity.

The Conundrum of Mechanics Versus Genetics in Congenital Hydrocephalus and Its Implications for Fetal Therapy Approaches: A Scoping Review

Recent advances in gene therapy, particularly for single-gene disorders (SGDs), have led to significant progress in developing innovative precision medicine approaches that hold promise for treating conditions such as primary hydrocephalus (CH), which is characterized by increased cerebrospinal fluid (CSF) volumes and cerebral ventricular dilation as a result of impaired brain development, often due to genetic causes. CH is a significant contributor to childhood morbidity and mortality and a driver of healthcare costs. In many cases, prenatal ultrasound can readily identify ventriculomegaly as early as 14-20 weeks of gestation, with severe cases showing poor neurodevelopmental outcomes. Postnatal surgical approaches, such as ventriculoperitoneal shunts, do not address the underlying genetic causes, have high complication rates, and result in a marginal improvement of neurocognitive deficits. Prenatal somatic cell gene therapy (PSCGT) promises a novel approach to conditions such as CH by targeting genetic mutations in utero, potentially improving long-term outcomes. To better understand the pathophysiology, genetic basis, and molecular pathomechanisms of CH, we conducted a scoping review of the literature that identified over 160 published genes linked to CH. Mutations in L1CAM, TRIM71, MPDZ, and CCDC88C play a critical role in neural stem cell development, subventricular zone architecture, and the maintenance of the neural stem cell niche, driving the development of CH. Early prenatal interventions targeting these genes could curb the development of the expected CH phenotype, improve neurodevelopmental outcomes, and possibly limit the need for surgical approaches. However, further research is needed to establish robust genotype-phenotype correlations and develop safe and effective PSCGT strategies for CH.

Gray matter based spatial statistics framework in the 1-month brain: insights into gray matter microstructure in infancy

The neurodevelopmental epoch from fetal stages to early life embodies a critical window of peak growth and plasticity in which differences believed to be associated with many neurodevelopmental and psychiatric disorders first emerge. Obtaining a detailed understanding of the developmental trajectories of the cortical gray matter microstructure is necessary to characterize differential patterns of neurodevelopment that may subserve future intellectual, behavioral, and psychiatric challenges. The neurite orientation dispersion density imaging (NODDI) Gray-Matter Based Spatial Statistics (GBSS) framework leverages information from the NODDI model to enable sensitive characterization of the gray matter microstructure while limiting partial volume contamination and misregistration errors between images collected in different spaces. However, limited contrast of the underdeveloped brain poses challenges for implementing this framework with infant diffusion MRI (dMRI) data. In this work, we aim to examine the development of cortical microstructure in infants. We utilize the NODDI GBSS framework and propose refinements to the original framework that aim to improve the delineation and characterization of gray matter in the infant brain. Taking this approach, we cross-sectionally investigate age relationships in the developing gray matter microstructural organization in infants within the first month of life and reveal widespread relationships with the gray matter architecture.

Altered thalamocortical tract trajectory growth with undisrupted thalamic parcellation pattern in human lissencephaly brain at mid-gestational stage

Proper topographically organized neural connections between the thalamus and the cerebral cortex are mandatory for thalamus function. Thalamocortical (TC) fiber growth begins during the embryonic period and completes by the third trimester of gestation, so that human neonates at birth have a thalamus with a near-facsimile of adult functional parcellation. Whether congenital neocortical anomaly (e.g., lissencephaly) affects TC connection in humans is unknown. Here, via diffusion MRI fiber-tractography analysis of long-term formalin-fixed postmortem fetal brain diagnosed as lissencephaly in comparison with an age-matched normal one, we found similar topological patterns of thalamic subregions and of internal capsule parcellated by TC fibers. However, lissencephaly fetal brain showed white matter structural changes, including fewer/less organized TC fibers and optic radiations, and much less cortical plate invasion by TC fibers - particularly around the shallow central sulcus. Diffusion MRI fiber tractography of normal fetal brains at 15, 23, and 26 gestational weeks (GW) revealed dynamic volumetric change of each parcellated thalamic subregion, suggesting coupled developmental progress of the thalamus with the corresponding cortex. Moreover, from GW23 and GW26 normal fetal brains, TC endings in the cortical plate could be delineated to reflect cumulative progressive TC invasion of cortical plate. By contrast, lissencephaly brain showed a dramatic decrease in TC invasion of the cortical plate. Our study thus shows the feasibility of diffusion MRI fiber tractography in postmortem long-term formalin-fixed fetal brains to disclose the developmental progress of TC tracts coordinating with thalamic and neocortical growth both in normal and lissencephaly fetal brains at mid-gestational stage.

Association between sleep stages and brain microstructure in preterm infants: Insights from DTI analysis

STUDY OBJECTIVES

The aim of this study was to investigate the relationship between sleep stages and neural microstructure - measured using diffusion tensor imaging - of the posterior limb of the internal capsule and corticospinal tract in preterm infants.

METHODS

A retrospective cohort of 50 preterm infants born between 24 + 4 and 29 + 3 weeks gestational age was included in the study. Sleep stages were continuously measured for 5-7 consecutive days between 29 + 0 and 31 + 6 weeks postmenstrual age using an in-house-developed, and recently published, automated sleep staging algorithm based on routinely measured heart rate and respiratory rate. Additionally, a diffusion tensor imaging scan was conducted at term equivalent age as part of standard care. Region of interest analysis of the posterior limb of the internal capsule was performed, and tractography was used to analyze the corticospinal tract. The association between sleep and white matter microstructure of the posterior limb of the internal capsule and corticospinal tract was examined using a multiple linear regression model, adjusted for potential confounders.

RESULTS

The results of the analyses revealed an interaction effect between sleep stage and days of invasive ventilation on the fractional anisotropy of the left and right posterior limb of the internal capsule (β = 0.04, FDR-adjusted p = 0.001 and β = 0.04, FDR-adjusted p = 0.02, respectively). Furthermore, an interaction effect between sleep stage and days of invasive ventilation was observed for the radial diffusivity of the mean of the left and right PLIC (β = -4.1e-05, FDR-adjusted p = 0.04).

CONCLUSIONS

Previous research has shown that, in very preterm infants, invasive ventilation has a negative effect on white matter tract maturation throughout the brain. A positive association between active sleep and white matter microstructure of the posterior limb of the internal capsule, may indicate a protective role of sleep in this vulnerable population.

In vivo T2 measurements of the fetal brain using single-shot fast spin echo sequences

PURPOSE

We propose a quantitative framework for motion-corrected T2 fetal brain measurements in vivo and validate the single-shot fast spin echo (SS-FSE) sequence to perform these measurements.

METHODS

Stacks of two-dimensional SS-FSE slices are acquired with different echo times (TE) and motion-corrected with slice-to-volume reconstruction (SVR). The quantitative T2 maps are obtained by a fit to a dictionary of simulated signals. The sequence is selected using simulated experiments on a numerical phantom and validated on a physical phantom scanned on a 1.5T system. In vivo quantitative T2 maps are obtained for five fetuses with gestational ages (GA) 21-35 weeks on the same 1.5T system.

RESULTS

The simulated experiments suggested that a TE of 400 ms combined with the clinically utilized TEs of 80 and 180 ms were most suitable for T2 measurements in the fetal brain. The validation on the physical phantom confirmed that the SS-FSE T2 measurements match the gold standard multi-echo spin echo measurements. We measured average T2s of around 200 and 280 ms in the fetal brain grey and white matter, respectively. This was slightly higher than fetal T2* and the neonatal T2 obtained from previous studies.

CONCLUSION

The motion-corrected SS-FSE acquisitions with varying TEs offer a promising practical framework for quantitative T2 measurements of the moving fetus.

Profiling cortical morphometric similarity in perinatal brains: Insights from development, sex difference, and inter-individual variation

The topological organization of the macroscopic cortical networks important for the development of complex brain functions. However, how the cortical morphometric organization develops during the third trimester and whether it demonstrates sexual and individual differences at this particular stage remain unclear. Here, we constructed the morphometric similarity network (MSN) based on morphological and microstructural features derived from multimodal MRI of two independent cohorts (cross-sectional and longitudinal) scanned at 30-44 postmenstrual weeks (PMW). Sex difference and inter-individual variations of the MSN were also examined on these cohorts. The cross-sectional analysis revealed that both network integration and segregation changed in a nonlinear biphasic trajectory, which was supported by the results obtained from longitudinal analysis. The community structure showed remarkable consistency between bilateral hemispheres and maintained stability across PMWs. Connectivity within the primary cortex strengthened faster than that within high-order communities. Compared to females, male neonates showed a significant reduction in the participation coefficient within prefrontal and parietal cortices, while their overall network organization and community architecture remained comparable. Furthermore, by using the morphometric similarity as features, we achieved over 65 % accuracy in identifying an individual at term-equivalent age from images acquired after birth, and vice versa. These findings provide comprehensive insights into the development of morphometric similarity throughout the perinatal cortex, enhancing our understanding of the establishment of neuroanatomical organization during early life.

Postoperative Analgesia With Modified Thoracoabdominal Nerve Block Through Perichondrial Approach in Neonatal and Infantile Abdominal Surgery

Modified thoracoabdominal nerve block through the perichondrial approach (M-TAPA) is a novel strategy for peripheral nerve block in the abdomen. Its usefulness has been highlighted in adults, but no literature is currently available regarding its efficacy in infants. This report describes the cases of a one-day-old neonate in open abdominal surgery and a one-month-old infant in laparoscopic surgery who received M-TAPA. The postoperative condition of the infants was assessed through a neonate pain scale and the Face, Legs, Activity, Cry, and Consolability behavioral scale, respectively; both scales remained at 0 until discharge. Despite the need for special attention, M-TAPA may provide effective analgesia in neonatal and infant abdominal surgery in addition to adult cases, and its indications should be considered.

Population Atlas Analysis of Emerging Brain Structural Connections in the Human Fetus

BACKGROUND

A lack of in utero imaging data hampers our understanding of the connections in the human fetal brain. Generalizing observations from postmortem subjects and premature newborns is inaccurate due to technical and biological differences.

PURPOSE

To evaluate changes in fetal brain structural connectivity between 23 and 35 weeks postconceptional age using a spatiotemporal atlas of diffusion tensor imaging (DTI).

STUDY TYPE

Retrospective.

POPULATION

Publicly available diffusion atlases, based on 60 healthy women (age 18-45 years) with normal prenatal care, from 23 and 35 weeks of gestation.

FIELD STRENGTH/SEQUENCE

3.0 Tesla/DTI acquired with diffusion-weighted echo planar imaging (EPI).

ASSESSMENT

We performed whole-brain fiber tractography from DTI images. The cortical plate of each diffusion atlas was segmented and parcellated into 78 regions derived from the Edinburgh Neonatal Atlas (ENA33). Connectivity matrices were computed, representing normalized fiber connections between nodes. We examined the relationship between global efficiency (GE), local efficiency (LE), small-worldness (SW), nodal efficiency (NE), and betweenness centrality (BC) with gestational age (GA) and with laterality.

STATISTICAL TESTS

Linear regression was used to analyze changes in GE, LE, NE, and BC throughout gestation, and to assess changes in laterality. The t-tests were used to assess SW. P-values were corrected using Holm-Bonferroni method. A corrected P-value <0.05 was considered statistically significant.

RESULTS

Network analysis revealed a significant weekly increase in GE (5.83%/week, 95% CI 4.32-7.37), LE (5.43%/week, 95% CI 3.63-7.25), and presence of SW across GA. No significant hemisphere differences were found in GE (P = 0.971) or LE (P = 0.458). Increasing GA was significantly associated with increasing NE in 41 nodes, increasing BC in 3 nodes, and decreasing BC in 2 nodes.

DATA CONCLUSION

Extensive network development and refinement occur in the second and third trimesters, marked by a rapid increase in global integration and local segregation.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Cortical Face-Selective Responses Emerge Early in Human Infancy

In human adults, multiple cortical regions respond robustly to faces, including the occipital face area (OFA) and fusiform face area (FFA), implicated in face perception, and the superior temporal sulcus (STS) and medial prefrontal cortex (MPFC), implicated in higher-level social functions. When in development, does face selectivity arise in each of these regions? Here, we combined two awake infant functional magnetic resonance imaging (fMRI) datasets to create a sample size twice the size of previous reports (n = 65 infants; 2.6-9.6 months). Infants watched movies of faces, bodies, objects, and scenes, while fMRI data were collected. Despite variable amounts of data from each infant, individual subject whole-brain activation maps revealed responses to faces compared to nonface visual categories in the approximate location of OFA, FFA, STS, and MPFC. To determine the strength and nature of face selectivity in these regions, we used cross-validated functional region of interest analyses. Across this larger sample size, face responses in OFA, FFA, STS, and MPFC were significantly greater than responses to bodies, objects, and scenes. Even the youngest infants (2-5 months) showed significantly face-selective responses in FFA, STS, and MPFC, but not OFA. These results demonstrate that face selectivity is present in multiple cortical regions within months of birth, providing powerful constraints on theories of cortical development.

Characterizing Large-Scale Human Circuit Development with In Vivo Neuroimaging

Large-scale coordinated patterns of neural activity are crucial for the integration of information in the human brain and to enable complex and flexible human behavior across the life span. Through recent advances in noninvasive functional magnetic resonance imaging (fMRI) methods, it is now possible to study this activity and how it emerges in the living fetal brain across the second half of human gestation. This work has demonstrated that functional activity in the fetal brain has several features in keeping with highly organized networks of activity, which are undergoing a highly programmed and rapid sequence of development before birth, in which long-range connections emerge and core features of the mature functional connectome (such as hub regions and a gradient organization) are established. In this review, the findings of these studies are summarized, their relationship to the known changes in developmental neurobiology is considered, and considerations for future work in the context of limitations to the fMRI approach are presented.

Development of neonatal connectome dynamics and its prediction for cognitive and language outcomes at age 2

The functional brain connectome is highly dynamic over time. However, how brain connectome dynamics evolves during the third trimester of pregnancy and is associated with later cognitive growth remains unknown. Here, we use resting-state functional Magnetic Resonance Imaging (MRI) data from 39 newborns aged 32 to 42 postmenstrual weeks to investigate the maturation process of connectome dynamics and its role in predicting neurocognitive outcomes at 2 years of age. Neonatal brain dynamics is assessed using a multilayer network model. Network dynamics decreases globally but increases in both modularity and diversity with development. Regionally, module switching decreases with development primarily in the lateral precentral gyrus, medial temporal lobe, and subcortical areas, with a higher growth rate in primary regions than in association regions. Support vector regression reveals that neonatal connectome dynamics is predictive of individual cognitive and language abilities at 2  years of age. Our findings highlight network-level neural substrates underlying early cognitive development.

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.

Intelligence Sparse Sensor Network for Automatic Early Evaluation of General Movements in Infants

General movements (GMs) have been widely used for the early clinical evaluation of infant brain development, allowing immediate evaluation of potential development disorders and timely rehabilitation. The infants' general movements can be captured digitally, but the lack of quantitative assessment and well-trained clinical pediatricians presents an obstacle for many years to achieve wider deployment, especially in low-resource settings. There is a high potential to explore wearable sensors for movement analysis due to outstanding privacy, low cost, and easy-to-use features. This work presents a sparse sensor network with soft wireless IMU devices (SWDs) for automatic early evaluation of general movements in infants. The sparse network consisting of only five sensor nodes (SWDs) with robust mechanical properties and excellent biocompatibility continuously and stably captures full-body motion data. The proof-of-the-concept clinical testing with 23 infants showcases outstanding performance in recognizing neonatal activities, confirming the reliability of the system. Taken together with a tiny machine learning algorithm, the system can automatically identify risky infants based on the GMs, with an accuracy of up to 100% (99.9%). The wearable sparse sensor network with an artificial intelligence-based algorithm facilitates intelligent evaluation of infant brain development and early diagnosis of development disorders.

A detailed spatio-temporal atlas of the white matter tracts for the fetal brain

This study presents the construction of a comprehensive spatiotemporal atlas detailing the development of white matter tracts in the fetal brain using diffusion magnetic resonance imaging (dMRI). Our research leverages data collected from fetal MRI scans conducted between 22 and 37 weeks of gestation, capturing the dynamic changes in the brain's microstructure during this critical period. The atlas includes 60 distinct white matter tracts, including commissural, projection, and association fibers. We employed advanced fetal dMRI processing techniques and tractography to map and characterize the developmental trajectories of these tracts. Our findings reveal that the development of these tracts is characterized by complex patterns of fractional anisotropy (FA) and mean diffusivity (MD), reflecting key neurodevelopmental processes such as axonal growth, involution of the radial-glial scaffolding, and synaptic pruning. This atlas can serve as a useful resource for neuroscience research and clinical practice, improving our understanding of the fetal brain and potentially aiding in the early diagnosis of neurodevelopmental disorders. By detailing the normal progression of white matter tract development, the atlas can be used as a benchmark for identifying deviations that may indicate neurological anomalies or predispositions to disorders.

Predicting 2-year neurodevelopmental outcomes in preterm infants using multimodal structural brain magnetic resonance imaging with local connectivity

The neurodevelopmental outcomes of preterm infants can be stratified based on the level of prematurity. We explored brain structural networks in extremely preterm (EP; < 28 weeks of gestation) and very-to-late (V-LP; ≥ 28 and < 37 weeks of gestation) preterm infants at term-equivalent age to predict 2-year neurodevelopmental outcomes. Using MRI and diffusion MRI on 62 EP and 131 V-LP infants, we built a multimodal feature set for volumetric and structural network analysis. We employed linear and nonlinear machine learning models to predict the Bayley Scales of Infant and Toddler Development, Third Edition (BSID-III) scores, assessing predictive accuracy and feature importance. Our findings revealed that models incorporating local connectivity features demonstrated high predictive performance for BSID-III subsets in preterm infants. Specifically, for cognitive scores in preterm (variance explained, 17%) and V-LP infants (variance explained, 17%), and for motor scores in EP infants (variance explained, 15%), models with local connectivity features outperformed others. Additionally, a model using only local connectivity features effectively predicted language scores in preterm infants (variance explained, 15%). This study underscores the value of multimodal feature sets, particularly local connectivity, in predicting neurodevelopmental outcomes, highlighting the utility of machine learning in understanding microstructural changes and their implications for early intervention.

Comprehensive analysis of synthetic learning applied to neonatal brain MRI segmentation

Brain segmentation from neonatal MRI images is a very challenging task due to large changes in the shape of cerebral structures and variations in signal intensities reflecting the gestational process. In this context, there is a clear need for segmentation techniques that are robust to variations in image contrast and to the spatial configuration of anatomical structures. In this work, we evaluate the potential of synthetic learning, a contrast-independent model trained using synthetic images generated from the ground truth labels of very few subjects. We base our experiments on the dataset released by the developmental Human Connectome Project, for which high-quality images are available for more than 700 babies aged between 26 and 45 weeks postconception. First, we confirm the impressive performance of a standard UNet trained on a few volumes, but also confirm that such models learn intensity-related features specific to the training domain. We then confirm the robustness of the synthetic learning approach to variations in image contrast. However, we observe a clear influence of the age of the baby on the predictions. We improve the performance of this model by enriching the synthetic training set with realistic motion artifacts and over-segmentation of the white matter. Based on extensive visual assessment, we argue that the better performance of the model trained on real T2w data may be due to systematic errors in the ground truth. We propose an original experiment allowing us to show that learning from real data will reproduce any systematic bias affecting the training set, while synthetic models can avoid this limitation. Overall, our experiments confirm that synthetic learning is an effective solution for segmenting neonatal brain MRI. Our adapted synthetic learning approach combines key features that will be instrumental for large multisite studies and clinical applications.

Feature similarity gradients detect alterations in the neonatal cortex associated with preterm birth

The early life environment programmes cortical architecture and cognition across the life course. A measure of cortical organisation that integrates information from multimodal MRI and is unbound by arbitrary parcellations has proven elusive, which hampers efforts to uncover the perinatal origins of cortical health. Here, we use the Vogt-Bailey index to provide a fine-grained description of regional homogeneities and sharp variations in cortical microstructure based on feature gradients, and we investigate the impact of being born preterm on cortical development at term-equivalent age. Compared with term-born controls, preterm infants have a homogeneous microstructure in temporal and occipital lobes, and the medial parietal, cingulate, and frontal cortices, compared with term infants. These observations replicated across two independent datasets and were robust to differences that remain in the data after matching samples and alignment of processing and quality control strategies. We conclude that cortical microstructural architecture is altered in preterm infants in a spatially distributed rather than localised fashion.

The role of acoustic features of maternal infant-directed singing in enhancing infant sensorimotor, language and socioemotional development

The quality of infant-directed speech (IDS) and infant-directed singing (IDSi) are considered vital to children, but empirical studies on protomusical qualities of the IDSi influencing infant development are rare. The current prospective study examines the role of IDSi acoustic features, such as pitch variability, shape and movement, and vocal amplitude vibration, timbre, and resonance, in associating with infant sensorimotor, language, and socioemotional development at six and 18 months. The sample consists of 236 Palestinian mothers from Gaza Strip singing to their six-month-olds a song by their own choice. Maternal IDSi was recorded and analyzed by the OpenSMILE- tool to depict main acoustic features of pitch frequencies, variations, and contours, vocal intensity, resonance formants, and power. The results are based on completed 219 maternal IDSi. Mothers reported about their infants' sensorimotor, language-vocalization, and socioemotional skills at six months, and psychologists tested these skills by Bayley Scales for Infant Development at 18 months. Results show that maternal IDSi characterized by wide pitch variability and rich and high vocal amplitude and vibration were associated with infants' optimal sensorimotor, language vocalization, and socioemotional skills at six months, and rich and high vocal amplitude and vibration predicted these optimal developmental skills also at 18 months. High resonance and rhythmicity formants were associated with optimal language and vocalization skills at six months. To conclude, the IDSi is considered important in enhancing newborn and risk infants' wellbeing, and the current findings argue that favorable acoustic singing qualities are crucial for optimal multidomain development across infancy.

Scaling patterns of cortical folding and thickness in early human brain development in comparison with primates

Across mammalia, brain morphology follows specific scaling patterns. Bigger bodies have bigger brains, with surface area outpacing volume growth, resulting in increased foldedness. We have recently studied scaling rules of cortical thickness, both local and global, finding that the cortical thickness difference between thick gyri and thin sulci also increases with brain size and foldedness. Here, we investigate early brain development in humans, using subjects from the Developing Human Connectome Project, scanned shortly after pre-term or full-term birth, yielding magnetic resonance images of the brain from 29 to 43 postmenstrual weeks. While the global cortical thickness does not change significantly during this development period, its distribution does, with sulci thinning, while gyri thickening. By comparing our results with our recent work on humans and 11 non-human primate species, we also compare the trajectories of primate evolution with human development, noticing that the 2 trends are distinct for volume, surface area, cortical thickness, and gyrification index. Finally, we introduce the global shape index as a proxy for gyrification index; while correlating very strongly with gyrification index, it offers the advantage of being calculated only from local quantities without generating a convex hull or alpha surface.

Characterizing microstructural development in the fetal brain using diffusion MRI from 23 to 36 weeks of gestation

We utilized motion-corrected diffusion tensor imaging (DTI) to evaluate microstructural changes in healthy fetal brains during the late second and third trimesters. Data were derived from fetal magnetic resonance imaging scans conducted as part of a prospective study spanning from 2013 March to 2019 May. The study included 44 fetuses between the gestational ages (GAs) of 23 and 36 weeks. We reconstructed fetal brain DTI using a motion-tracked slice-to-volume registration framework. Images were segmented into 14 regions of interest (ROIs) through label propagation using a fetal DTI atlas, with expert refinement. Statistical analysis involved assessing changes in fractional anisotropy (FA) and mean diffusivity (MD) throughout gestation using mixed-effects models, and identifying points of change in trajectory for ROIs with nonlinear trends. Results showed significant GA-related changes in FA and MD in all ROIs except in the thalamus' FA and corpus callosum's MD. Hemispheric asymmetries were found in the FA of the periventricular white matter (pvWM), intermediate zone, and subplate and in the MD of the ganglionic eminence and pvWM. This study provides valuable insight into the normal patterns of development of MD and FA in the fetal brain. These changes are closely linked with cytoarchitectonic changes and display indications of early functional specialization.

The normal 14-18 gestational weeks "parasagittal complex" view of the fetal brain. A 3D transvaginal neurosonographic study

OBJECTIVE

To study the early second trimester development of brain hemispheres, lateral ventricles, choroid plexus, and ganglionic eminence/basal ganglia complex (GEBG).

METHODS

A retrospective analysis of TVUS 3D volumes of 14-18 gestational weeks (GW) fetuses. Hemispheres were analyzed for wall thickness, choroid plexus extension, GEBG height and length, lamination pattern (intermediate zone and the subplate border, IZ-SP), ventricle height, width, and angle. Measurements were correlated with GW and assessed for symmetry and impact of probe resolution.

RESULTS

We included 84 fetuses (168 hemispheres). The CP location is variable at 14-16 GW, becoming consistently and symmetrically posterior at 18 GW. Hemispheric thickness, GEBG height and length grow significantly with fetal age, whereas ventricle height, width, and angle regress. The detection rate of the IZ-SP line at 14, 15, 16, 17, and 18 weeks was 0%, 24%, 78.26%, 100%, and 100%, respectively. The ratio between the upper and lower segments of the cerebral lamination grows with GW. For all brain structures, the asymmetry between sides was significant only for ventricular height. The transducer type did not have a significant effect on any outcome except for ventricle height.

CONCLUSION

These normal features of the parasagittal view should aid clinicians in fetal brain assessment during the early weeks of the second trimester.

Developmental Pattern of Individual Morphometric Similarity Network in the Human Fetal Brain

The development of the cerebral cortex during the fetal period is a complex yet well-coordinated process. MRI-based morphological brain network provides a powerful tool for describing this process at a network level. Due to the challenges of in-utero MRI acquisition and image processing, the fetal morphological brain network has not been established. In this study, utilizing high-resolution in-utero MRI data, we constructed an individual morphometric similarity network for each fetus based on multiple cortical features. The spatiotemporal development of morphological connections was described at the level of edge, node, and lobe, respectively. Based on graph theoretical method, the topology structure of fetal morphological network was characterized. Edge analysis demonstrated an increase of morphological dissimilarity between hemispheres with gestational age, especially for the parietal cortex. The limbic and parieto-occipital regions exhibited the most drastic changes of morphological connections at both the edge and node levels. Between- and within-lobe analysis illustrated that the limbic lobe became more similar to other lobes, while the parietal and occipital lobes became more dissimilar to other lobes. Graph theoretical analysis indicated that the small-world structure of the fetal morphological network appeared as early as 22 weeks and that the network topology exhibited an enhanced integration and reduced segregation during prenatal development. The findings obtained from the preterm-born neonates agreed well with those of the fetuses. In summary, this study fills a gap in prenatal morphological brain network research and provides a piece of important evidence for understanding the normal development of fetal brain connectome during the second-third trimester.

Celf4 controls mRNA translation underlying synaptic development in the prenatal mammalian neocortex

Abnormalities in neocortical and synaptic development are linked to neurodevelopmental disorders. However, the molecular and cellular mechanisms governing initial synapse formation in the prenatal neocortex remain poorly understood. Using polysome profiling coupled with snRNAseq on human cortical samples at various fetal phases, we identify human mRNAs, including those encoding synaptic proteins, with finely controlled translation in distinct cell populations of developing frontal neocortices. Examination of murine and human neocortex reveals that the RNA binding protein and translational regulator, CELF4, is expressed in compartments enriched in initial synaptogenesis: the marginal zone and the subplate. We also find that Celf4/CELF4-target mRNAs are encoded by risk genes for adverse neurodevelopmental outcomes translating into synaptic proteins. Surprisingly, deleting Celf4 in the forebrain disrupts the balance of subplate synapses in a sex-specific fashion. This highlights the significance of RNA binding proteins and mRNA translation in evolutionarily advanced synaptic development, potentially contributing to sex differences.

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.

Melatonin as a Therapy for Preterm Brain Injury: What Is the Evidence?

Despite significant improvements in survival following preterm birth in recent years, the neurodevelopmental burden of prematurity, with its long-term cognitive and behavioral consequences, remains a significant challenge in neonatology. Neuroprotective treatment options to improve neurodevelopmental outcomes in preterm infants are therefore urgently needed. Alleviating inflammatory and oxidative stress (OS), melatonin might modify important triggers of preterm brain injury, a complex combination of destructive and developmental abnormalities termed encephalopathy of prematurity (EoP). Preliminary data also suggests that melatonin has a direct neurotrophic impact, emphasizing its therapeutic potential with a favorable safety profile in the preterm setting. The current review outlines the most important pathomechanisms underlying preterm brain injury and correlates them with melatonin's neuroprotective potential, while underlining significant pharmacokinetic/pharmacodynamic uncertainties that need to be addressed in future studies.

Prenatal exposure to environmental air pollution and psychosocial stress jointly contribute to the epigenetic regulation of the serotonin transporter gene in newborns

Antenatal exposures to maternal stress and to particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) have been independently associated with developmental outcomes in early infancy and beyond. Knowledge about their joint impact, biological mechanisms of their effects and timing-effects, is still limited. Both PM2.5 and maternal stress exposure during pregnancy might result in altered patterns of DNA methylation in specific stress-related genes, such as the serotonin transporter gene (SLC6A4 DNAm), that might, in turn, influence infant development across several domains, including bio-behavioral, cognitive and socio-emotional domains. Here, we investigated the independent and interactive influence of variations in antenatal exposures to maternal pandemic-related stress (PRS) and PM2.5 on SLC6A4 DNAm levels in newborns. Mother-infant dyads (N = 307) were enrolled at delivery during the COVID-19 pandemic. Infants' methylation status was assessed in 13 CpG sites within the SLC6A4 gene's region (chr17:28562750-28562958) in buccal cells at birth and women retrospectively report on PRS. PM2.5 exposure throughout the entire gestation and at each gestational trimester was estimated using a spatiotemporal model based on residential address. Among several potentially confounding socio-demographic and health-related factors, infant's sex was significantly associated with infants' SLC6A4 DNAm levels, thus hierarchical regression models were adjusted for infant's sex. Higher levels of SLC6A4 DNAm at 6 CpG sites were found in newborns born to mothers reporting higher levels of antenatal PRS and greater PM2.5 exposure across gestation, while adjusting for infant's sex. These effects were especially evident when exposure to elevated PM2.5 occurred during the second trimester of pregnancy. Several important brain processes (e.g., synaptogenesis and myelination) occur during mid-pregnancy, potentially making the second trimester a sensitive time window for the effects of stress-related exposures. Understanding the interplay between environmental and individual-level stressors has important implications for the improvement of mother-infant health during and after the pandemic.