The early development of brain white matter: A review of imaging studies in fetuses, newborns and infants

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.

Anat-SFSeg: Anatomically-guided superficial fiber segmentation with point-cloud deep learning

Diffusion magnetic resonance imaging (dMRI) tractography is a critical technique to map the brain's structural connectivity. Accurate segmentation of white matter, particularly the superficial white matter (SWM), is essential for neuroscience and clinical research. However, it is challenging to segment SWM due to the short adjacent gyri connection in a U-shaped pattern. In this work, we propose an Anatomically-guided Superficial Fiber Segmentation (Anat-SFSeg) framework to improve the performance on SWM segmentation. The framework consists of a unique fiber anatomical descriptor (named FiberAnatMap) and a deep learning network based on point-cloud data. The spatial coordinates of fibers represented as point clouds, as well as the anatomical features at both the individual and group levels, are fed into a neural network. The network is trained on Human Connectome Project (HCP) datasets and tested on the subjects with a range of cognitive impairment levels. One new metric named fiber anatomical region proportion (FARP), quantifies the ratio of fibers in the defined brain regions and enables the comparison with other methods. Another metric named anatomical region fiber count (ARFC), represents the average fiber number in each cluster for the assessment of inter-subject differences. The experimental results demonstrate that Anat-SFSeg achieves the highest accuracy on HCP datasets and exhibits great generalization on clinical datasets. Diffusion tensor metrics and ARFC show disorder severity associated alterations in patients with Alzheimer's disease (AD) and mild cognitive impairments (MCI). Correlations with cognitive grades show that these metrics are potential neuroimaging biomarkers for AD. Furthermore, Anat-SFSeg could be utilized to explore other neurodegenerative, neurodevelopmental or psychiatric disorders.

Deep learning microstructure estimation of developing brains from diffusion MRI: A newborn and fetal study

Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. Fiber orientation distribution functions (FODs) are a common way of representing the orientation and density of white matter fibers. However, with standard FOD computation methods, accurate estimation requires a large number of measurements that usually cannot be acquired for newborns and fetuses. We propose to overcome this limitation by using a deep learning method to map as few as six diffusion-weighted measurements to the target FOD. To train the model, we use the FODs computed using multi-shell high angular resolution measurements as target. Extensive quantitative evaluations show that the new deep learning method, using significantly fewer measurements, achieves comparable or superior results than standard methods such as Constrained Spherical Deconvolution and two state-of-the-art deep learning methods. For voxels with one and two fibers, respectively, our method shows an agreement rate in terms of the number of fibers of 77.5% and 22.2%, which is 3% and 5.4% higher than other deep learning methods, and an angular error of 10° and 20°, which is 6° and 5° lower than other deep learning methods. To determine baselines for assessing the performance of our method, we compute agreement metrics using densely sampled newborn data. Moreover, we demonstrate the generalizability of the new deep learning method across scanners, acquisition protocols, and anatomy on two clinical external datasets of newborns and fetuses. We validate fetal FODs, successfully estimated for the first time with deep learning, using post-mortem histological data. Our results show the advantage of deep learning in computing the fiber orientation density for the developing brain from in-vivo dMRI measurements that are often very limited due to constrained acquisition times. Our findings also highlight the intrinsic limitations of dMRI for probing the developing brain microstructure.

Functional and structural maturation of auditory cortex from 2 months to 2 years old

In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (P2m measured using magnetoencephalography, MEG) in a cross-sectional (2 to 24 months) as well as longitudinal cohort (2 to 29 months) of typically developing infants and toddlers. In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. After removing the variance associated with age in both P2m latency and auditory radiation diffusion measures, auditory radiation still accounted for significant variance in P2m latency. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. Findings provide strong support for a contribution of auditory radiation white matter to rapid cortical auditory encoding processes in infants.

Reconsidering the nature of threat in infancy: Integrating animal and human studies on neurobiological effects of infant stress

Early life stress has been associated with elevated risk for later psychopathology. One mechanism that may contribute to such long-term risk is alterations in amygdala development, a brain region critical to stress responsivity. Yet effects of stress on the amygdala during human infancy, a period of particularly rapid brain development, remain largely unstudied. In order to model how early stressors may affect infant amygdala development, several discrepancies across the existing literatures on early life stress among rodents and early threat versus deprivation among older human children and adults need to be reconciled. We briefly review the key findings of each of these literatures. We then consider them in light of emerging findings from studies of human infants regarding relations among maternal caregiving, infant cortisol response, and infant amygdala volume. Finally, we advance a developmental salience model of how early threat may impact the rapidly developing infant brain, a model with the potential to integrate across these divergent literatures. Future work to assess the value of this model is also proposed.

Constructing fine-grained spatiotemporal neonatal functional atlases with spectral functional network learning

The early stages of human development are increasingly acknowledged as pivotal in laying the groundwork for subsequent behavioral and cognitive development. Spatiotemporal (4D) brain functional atlases are important in elucidating the development of human brain functions. However, the scarcity of such atlases for early life stages stems from two primary challenges: (1) the significant noise in functional magnetic resonance imaging (fMRI) that complicates the generation of high-quality atlases for each age group, and (2) the rapid and complex changes in the early human brain that hinder the maintenance of temporal consistency in 4D atlases. This study tackles these challenges by integrating low-rank tensor learning with spectral embedding, thereby proposing a novel, data-driven 4D functional atlas generation framework based on spectral functional network learning (SFNL). This method utilizes low-rank tensor learning to capture common functional connectivity (FC) patterns across different ages, thus optimizing FCs for each age group to improve the temporal consistency of functional networks. Incorporating spectral embedding aids in mitigating potential noise in FC networks derived from fMRI data by reconstructing networks in the spectral space. Utilizing SFNL-generated functional networks enables the creation of consistent and highly qualified spatiotemporal functional atlases. The framework was applied to the developing Human Connectome Project (dHCP) dataset, generating the first neonatal 4D functional atlases with fine-grained temporal and spatial resolutions. Experimental evaluations focusing on functional homogeneity, reliability, and temporal consistency demonstrated the superiority of our framework compared to existing methods for constructing 4D atlases. Additionally, network analysis experiments, including individual identification, functional systems development, and local efficiency assessments, further corroborate the efficacy and robustness of the generated atlases. The 4D atlases and related codes will be made publicly accessible (https://github.com/zhaoyunxi/neonate-atlases).

Infants' top-down perceptual modulation is specific to own-race faces

Recent studies have revealed the influence of higher-level cognitive systems in modulating perceptual processing (top-down perceptual modulation) in infancy. However, more research is needed to understand how top-down processes in infant perception contribute to early perceptual development. To this end, this study examined infants' top-down perception of own- and other-race faces to reveal whether top-down modulation is linked to the emergence of perceptual specialization. Infants first learned an association between a sound and faces, with the race of the faces manipulated between groups (own race vs. other race). We then tested infants' face perception across various levels of perceptual difficulty (manipulated by presentation duration) and indexed top-down perception by the change in perception when infants heard the sound previously associated with the face (predictive sound) versus an irrelevant sound. Infants exhibited top-down face perception for own-race faces (Experiment 1). However, we present new evidence that infants did not show evidence of top-down modulation for other-race faces (Experiment 2), suggesting an experience-based specificity of this capacity with more effective top-down modulation in familiar perceptual contexts. In addition, we ruled out the possibility that this face race effect was due to differences in infants' associative learning of the sound and faces between the two groups. This work has important implications for understanding the mechanisms supporting perceptual development and how they relate to top-down perception in infancy.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Cerebral Palsy: A Current Perspective

Cerebral palsy (CP) is the most common cause of motor disability in children. Insults to the brain at different times lead to diverse injuries. As a result, CP is an extremely heterogeneous clinical diagnosis, presenting differently in each individual and at various ages. With improving survival rates of preterm newborns, increasing active resuscitation of extremely preterm newborns, and widespread availability of extensive genetic testing soon after birth, it is imperative to focus on earlier diagnosis and long-term outcomes of CP. CP is primarily classified into 4 categories based on type of motor impairment, functional ability, distribution, and etiology. As the understanding of CP has evolved significantly in the last 2 decades, the methods of early detection of CP have consequently advanced. Appropriate diagnosis is essential for proper education and counseling of affected families, and introduction of therapeutic interventions as early as possible. In this review, we focus on early brain development and provide an overview of the etiology, classification, diagnosis, early therapeutic options, and prognosis of CP.

Mastering movement: A Cross-sectional investigation of motor competence in children and adolescents engaged in sports

INTRODUCTION

Motor Competence (MC) is related to the development of healthy lifestyles in children and adolescents, and many studies have compared it with different variables, including sports participation. This investigation aimed to characterize the components and total scores of MC regarding different physical activity practices, such as physical education (PE) classes, futsal, volleyball, and ballet, and to compare MC regarding sports, sex, and age-groups.

METHODS

Using a cross-sectional study, 398 Portuguese children and adolescents (398 participants: 200 boys and 198 girls; 12.649±3.46 years) were conveniently chosen between 2022 and 2023. Four groups of different sports were created: PE classes (n = 187), futsal (n = 80), volleyball (n = 101) and ballet (n = 30), and four different age groups: 7 to 9 years old (n = 117); 10 to 12 years old (n = 65), 13 to 15 years old (n = 96) and, 16 to 19 years old (n = 120). All participants reported to participate in at least two training sessions per week (1 hour each) for at least two years. MC was assessed with Motor Competence Assessment (MCA) comprising three components with six tests (two tests for each component). Participants' total MC was calculated as the average of the three components of the MCA. Data were analyzed by applying ANOVA one-way with LSD post-hoc.

RESULTS

Differences were found in MC among groups, where futsal participants showed better scores in general. Sex comparison showed that boys have a higher MC when practicing futsal, especially compared to volleyball players. Age-group analysis showed that younger participants had better MC levels compared to older ones.

CONCLUSION

The whole group showed the 50th percentile of MC, but volleyball adolescents showed results below this reference. MC is intrinsically linked to an individual's motor experiences and motivations rather than depending directly on the specific practice of the sport.

Automatic cortical surface parcellation in the fetal brain using attention-gated spherical U-net

Cortical surface parcellation for fetal brains is essential for the understanding of neurodevelopmental trajectories during gestations with regional analyses of brain structures and functions. This study proposes the attention-gated spherical U-net, a novel deep-learning model designed for automatic cortical surface parcellation of the fetal brain. We trained and validated the model using MRIs from 55 typically developing fetuses [gestational weeks: 32.9 ± 3.3 (mean ± SD), 27.4-38.7]. The proposed model was compared with the surface registration-based method, SPHARM-net, and the original spherical U-net. Our model demonstrated significantly higher accuracy in parcellation performance compared to previous methods, achieving an overall Dice coefficient of 0.899 ± 0.020. It also showed the lowest error in terms of the median boundary distance, 2.47 ± 1.322 (mm), and mean absolute percent error in surface area measurement, 10.40 ± 2.64 (%). In this study, we showed the efficacy of the attention gates in capturing the subtle but important information in fetal cortical surface parcellation. Our precise automatic parcellation model could increase sensitivity in detecting regional cortical anomalies and lead to the potential for early detection of neurodevelopmental disorders in fetuses.

Aging Brain from a Lifespan Perspective

Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.

Neurodevelopmental outcome in preterm infants with intraventricular hemorrhages: the potential of quantitative brainstem MRI

OBJECTIVES

This retrospective study aimed to identify quantitative magnetic resonance imaging markers in the brainstem of preterm neonates with intraventricular hemorrhages. It delves into the intricate associations between quantitative brainstem magnetic resonance imaging metrics and neurodevelopmental outcomes in preterm infants with intraventricular hemorrhage, aiming to elucidate potential relationships and their clinical implications.

MATERIALS AND METHODS

Neuroimaging was performed on preterm neonates with intraventricular hemorrhage using a multi-dynamic multi-echo sequence to determine T1 relaxation time, T2 relaxation time, and proton density in specific brainstem regions. Neonatal outcome scores were collected using the Bayley Scales of Infant and Toddler Development. Statistical analysis aimed to explore potential correlations between magnetic resonance imaging metrics and neurodevelopmental outcomes.

RESULTS

Sixty preterm neonates (mean gestational age at birth 26.26 ± 2.69 wk; n = 24 [40%] females) were included. The T2 relaxation time of the midbrain exhibited significant positive correlations with cognitive (r = 0.538, P < 0.0001, Pearson's correlation), motor (r = 0.530, P < 0.0001), and language (r = 0.449, P = 0.0008) composite scores at 1 yr of age.

CONCLUSION

Quantitative magnetic resonance imaging can provide valuable insights into neurodevelopmental outcomes after intraventricular hemorrhage, potentially aiding in identifying at-risk neonates. Multi-dynamic multi-echo sequence sequences hold promise as an adjunct to conventional sequences, enhancing the sensitivity of neonatal magnetic resonance neuroimaging and supporting clinical decision-making for these vulnerable patients.

Early versus late caffeine and/or non-steroidal anti-inflammatory drugs (NSAIDS) for prevention of intermittent hypoxia-induced neuroinflammation in the neonatal rat

Preterm infants often experience frequent intermittent hypoxia (IH) episodes which are associated with neuroinflammation. We tested the hypotheses that early caffeine and/or non-steroidal inflammatory drugs (NSAIDs) confer superior therapeutic benefits for protection against IH-induced neuroinflammation than late treatment. Newborn rats were exposed to IH or hyperoxia (50% O2) from birth (P0) to P14. For early treatment, the pups were administered: 1) daily caffeine (Caff) citrate (Cafcit, 20 mg/kg IP loading on P0, followed by 5 mg/kg from P1-P14); 2) ketorolac (Keto) topical ocular solution in both eyes from P0 to P14; 3) ibuprofen (Ibu, Neoprofen, 10 mg/kg loading dose on P0 followed by 5 mg/kg/day on P1 and P2); 4) Caff+Keto co-treatment; 5) Caff+Ibu co-treatment; or 6) equivalent volume saline (Sal). On P14, animals were placed in room air (RA) with no further treatment until P21. For late treatment, pups were exposed from P0 to P14, then placed in RA during which they received similar treatments from P15-P21 (Sal, Caff, and/or Keto), or P15-P17 (Ibu). RA controls were similarly treated. At P21, whole brains were assessed for histopathology, apoptosis, myelination, and biomarkers of inflammation. IH caused significant brain injury and hemorrhage, inflammation, reduced myelination, and apoptosis. Early treatment with Caff alone or in combination with NSAIDs conferred better neuroprotection against IH-induced damage than late treatment. Early postnatal treatment during a critical time of brain development, may be preferable for the prevention of IH-induced brain injury in preterm infants.

Distinct alterations in white matter properties and organization related to maternal treatment initiation in neonates exposed to HIV but uninfected

HIV exposed-uninfected (HEU) infants and children are at risk of developmental delays as compared to HIV uninfected unexposed (HUU) populations. The effects of exposure to in utero HIV and ART regimens on the HEU the developing brain are not well understood. In a cohort of 2-week-old newborns, we used diffusion tensor imaging (DTI) tractography and graph theory to examine the influence of HIV and ART exposure in utero on neonate white matter integrity and organisation. The cohort included HEU infants born to mothers who started ART before conception (HEUpre) and after conception (HEUpost), as well as HUU infants from the same community. We investigated HIV exposure and ART duration group differences in DTI metrics (fractional anisotropy (FA) and mean diffusivity (MD)) and graph measures across white matter. We found increased MD in white matter connections involving the thalamus and limbic system in the HEUpre group compared to HUU. We further identified reduced nodal efficiency in the basal ganglia. Within the HEUpost group, we observed reduced FA in cortical-subcortical and cerebellar connections as well as decreased transitivity in the hindbrain area compared to HUU. Overall, our analysis demonstrated distinct alterations in white matter integrity related to the timing of maternal ART initiation that influence regional brain network properties.

Functional myelin in cognition and neurodevelopmental disorders

In vertebrates, oligodendrocytes (OLs) are glial cells of the central nervous system (CNS) responsible for the formation of the myelin sheath that surrounds the axons of neurons. The myelin sheath plays a crucial role in the transmission of neuronal information by promoting the rapid saltatory conduction of action potentials and providing neurons with structural and metabolic support. Saltatory conduction, first described in the peripheral nervous system (PNS), is now generally recognized as a universal evolutionary innovation to respond quickly to the environment: myelin helps us think and act fast. Nevertheless, the role of myelin in the central nervous system, especially in the brain, may not be primarily focused on accelerating conduction speed but rather on ensuring precision. Its principal function could be to coordinate various neuronal networks, promoting their synchronization through oscillations (or rhythms) relevant for specific information processing tasks. Interestingly, myelin has been directly involved in different types of cognitive processes relying on brain oscillations, and myelin plasticity is currently considered to be part of the fundamental mechanisms for memory formation and maintenance. However, despite ample evidence showing the involvement of myelin in cognition and neurodevelopmental disorders characterized by cognitive impairments, the link between myelin, brain oscillations, cognition and disease is not yet fully understood. In this review, we aim to highlight what is known and what remains to be explored to understand the role of myelin in high order brain processes.

Urban environment during pregnancy and childhood and white matter microstructure in preadolescence in two European birth cohorts

Growing evidence suggests that urban environment may influence cognition and behavior in children, but the underlying pollutant and neurobiological mechanisms are unclear. We evaluated the association of built environment and urban natural space indicators during pregnancy and childhood with brain white matter microstructure in preadolescents, and examined the potential mediating role of air pollution and road-traffic noise. We used data of the Generation R Study, a population-based birth cohort in Rotterdam, the Netherlands (n = 2725; 2002-2006) for the primary analyses. Replication of the main findings was attempted on an independent neuroimaging dataset from the PELAGIE birth cohort, France (n = 95; 2002-2006). We assessed exposures to 12 built environment and 4 urban natural spaces indicators from conception up to 9 years of age. We computed 2 white matter microstructure outcomes (i.e., average of fractional anisotropy (FA) and mean diffusivity (MD) from 12 white matte tracts) from diffusion tensor imaging data. Greater distance to the nearest major green space during pregnancy was associated with higher whole-brain FA (0.001 (95%CI 0.000; 0.002) per 7 m increase), and higher land use diversity during childhood was associated with lower whole-brain MD (-0.001 (95%CI -0.002; -0.000) per 0.12-point increase), with no evidence of mediation by air pollution nor road-traffic noise. Higher percentage of transport and lower surrounding greenness during pregnancy were associated with lower whole-brain FA, and road-traffic noise mediated 19% and 52% of these associations, respectively. We found estimates in the same direction in the PELAGIE cohort, although confidence intervals were larger and included the null. This study suggests an association between urban environment and white matter microstructure, mainly through road-traffic noise, indicating that greater access to green space nearby might promote white matter development.

Assessment of brain structure and volume reveals neurodevelopmental abnormalities in preterm infants with low-grade intraventricular hemorrhage

There is increasing evidence of abnormal neurodevelopmental outcomes in preterm infants with low-grade intraventricular hemorrhage (IVH). The purpose of the study was to explore whether brain microstructure and volume are associated with neuro-behavioral outcomes at 40 weeks corrected gestational age in preterm infants with low-grade IVH. MR imaging at term-equivalent age (TEA) was performed in 25 preterm infants with mild IVH (Papile grading I/II) and 40 control subjects without IVH. These subjects all had neonatal behavioral neurological assessment (NBNA) at 40 weeks' corrected age. Microstructure and volume evaluation of the brain were performed by using diffusion kurtosis imaging (DKI) and Synthetic MRI. Correlations among microstructure parameters, volume, and developmental outcomes were explored by using Spearman's correlation. In preterm infants with low-grade IVH, the volume of brain parenchymal fraction (BPF) was reduced. In addition, mean kurtosis (MK), fractional anisotropy (FA), radial kurtosis (RK), axial kurtosis (AK) in several major brain regions were reduced, while mean diffusivity (MD) was increased (P < 0.05). BPF, RK in the cerebellum, MK in the genu of the corpus callosum, and MK in the thalamus of preterm infants with low-grade IVH were associated with lower NBNA scores (r = 0.831, 0.836, 0.728, 0.772, P < 0.05). DKI and Synthetic MRI can quantitatively evaluate the microstructure alterations and brain volumes in preterm infants with low-grade IVH, which provides clinicians with a more comprehensive and accurate neurobehavioral assessment of preterm infants with low-grade IVH.

Evaluation of PET imaging as a tool for detecting neonatal hypoxic-ischemic encephalopathy in a preclinical animal model

Hypoxic-ischemic encephalopathy due to insufficient oxygen delivery to brain tissue is a leading cause of death or severe morbidity in neonates. The early recognition of the most severely affected individuals remains a clinical challenge. We hypothesized that hypoxic-ischemic injury can be detected using PET radiotracers for hypoxia ([18F]EF5), glucose metabolism ([18F]FDG), and inflammation ([18F]F-DPA).

METHODS

A preclinical model of neonatal hypoxic-ischemic brain injury was made in 9-d-old rat pups by permanent ligation of the left common carotid artery followed by hypoxia (8% oxygen and 92% nitrogen) for 120 min. In vivo PET imaging was performed immediately after injury induction or at different timepoints up to 21 d later. After imaging, ex vivo brain autoradiography was performed. Brain sections were stained with cresyl violet to evaluate the extent of the brain injury and to correlate it with [18F]FDG uptake.

RESULTS

PET imaging revealed that all three of the radiotracers tested had significant uptake in the injured brain hemisphere. Ex vivo autoradiography revealed high [18F]EF5 uptake in the hypoxic hemisphere immediately after the injury (P < 0.0001), decreasing to baseline even 1 d postinjury. [18F]FDG uptake was highest in the injured hemisphere on the day of injury (P < 0.0001), whereas [18F]F-DPA uptake was evident after 4 d (P = 0.029), peaking 7 d postinjury (P < 0.0001), and remained significant 21 d after the injury. Targeted evaluation demonstrated that [18F]FDG uptake measured by in vivo imaging 1 d postinjury correlated positively with the brain volume loss detected 21 d later (r = 0.72, P = 0.028).

CONCLUSION

Neonatal hypoxic-ischemic brain injury can be detected using PET imaging. Different types of radiotracers illustrate distinct phases of hypoxic brain damage. PET may be a new useful technique, worthy of being explored for clinical use, to predict and evaluate the course of the injury.

The Association Between Repeated Measured Febrile Episodes During Early Childhood and Attention Deficit Hyperactivity Disorder: A Large-Scale Population-Based Study

OBJECTIVE

We examined the association between the number, magnitude, and frequency of febrile episodes during the 0 to 4 years of life and subsequent diagnosis of ADHD.

METHODS

This population-based case-control study in an Israeli HMO, Leumit Health Services (LHS), uses a database for all LHS members aged 5 to 18 years between 1/1/2002 and 1/30/2022. The number and magnitude of measured fever episodes during the 0 to 4 years were recorded in individuals with ADHD (N = 18,558) and individually matched non-ADHD controls in a 1:2 ratio (N = 37,116).

RESULTS

A significant, independent association was found between the number and magnitude of febrile episodes during the 0 to 4 years and the probability of a later diagnosis of ADHD. Children who never had a measured temperature >37.5°C had a significantly lower rate of ADHD (OR = 0.834, 95% CI [0.802, 0.866], p < .0001).

CONCLUSIONS

Febrile episodes during 0 to 4 years are associated with a significantly increased rate of a later diagnosis of ADHD in a doseresponse relationship.

Deep Learning for Generalized EEG Seizure Detection after Hypoxia-Ischemia-Preclinical Validation

Brain maturity and many clinical treatments such as therapeutic hypothermia (TH) can significantly influence the morphology of neonatal EEG seizures after hypoxia-ischemia (HI), and so there is a need for generalized automatic seizure identification. This study validates efficacy of advanced deep-learning pattern classifiers based on a convolutional neural network (CNN) for seizure detection after HI in fetal sheep and determines the effects of maturation and brain cooling on their accuracy. The cohorts included HI-normothermia term (n = 7), HI-hypothermia term (n = 14), sham-normothermia term (n = 5), and HI-normothermia preterm (n = 14) groups, with a total of >17,300 h of recordings. Algorithms were trained and tested using leave-one-out cross-validation and k-fold cross-validation approaches. The accuracy of the term-trained seizure detectors was consistently excellent for HI-normothermia preterm data (accuracy = 99.5%, area under curve (AUC) = 99.2%). Conversely, when the HI-normothermia preterm data were used in training, the performance on HI-normothermia term and HI-hypothermia term data fell (accuracy = 98.6%, AUC = 96.5% and accuracy = 96.9%, AUC = 89.6%, respectively). Findings suggest that HI-normothermia preterm seizures do not contain all the spectral features seen at term. Nevertheless, an average 5-fold cross-validated accuracy of 99.7% (AUC = 99.4%) was achieved from all seizure detectors. This significant advancement highlights the reliability of the proposed deep-learning algorithms in identifying clinically translatable post-HI stereotypic seizures in 256Hz recordings, regardless of maturity and with minimal impact from hypothermia.

White matter development and language abilities during infancy in autism spectrum disorder

White matter (WM) fiber tract differences are present in autism spectrum disorder (ASD) and could be important markers of behavior. One of the earliest phenotypic differences in ASD are language atypicalities. Although language has been linked to WM in typical development, no work has evaluated this association in early ASD. Participants came from the Infant Brain Imaging Study and included 321 infant siblings of children with ASD at high likelihood (HL) for developing ASD; 70 HL infants were later diagnosed with ASD (HL-ASD), and 251 HL infants were not diagnosed with ASD (HL-Neg). A control sample of 140 low likelihood infants not diagnosed with ASD (LL-Neg) were also included. Infants contributed expressive language, receptive language, and diffusion tensor imaging data at 6-, 12-, and 24 months. Mixed effects regression models were conducted to evaluate associations between WM and language trajectories. Trajectories of microstructural changes in the right arcuate fasciculus were associated with expressive language development. HL-ASD infants demonstrated a different developmental pattern compared to the HL-Neg and LL-Neg groups, wherein the HL-ASD group exhibited a positive association between WM fractional anisotropy and language whereas HL-Neg and LL-Neg groups showed weak or no association. No other fiber tracts demonstrated significant associations with language. In conclusion, results indicated arcuate fasciculus WM is linked to language in early toddlerhood for autistic toddlers, with the strongest associations emerging around 24 months. To our knowledge, this is the first study to evaluate associations between language and WM development during the pre-symptomatic period in ASD.

Associations of Perinatal Metal and Metalloid Exposures with Early Child Behavioral Development Over Time in the New Hampshire Birth Cohort Study

Research on the neurodevelopmental effects of metal(loid)s has focused mainly on outcomes assessed at one time point, even though brain development progresses over time. We investigated biomarkers of perinatal exposure to metals and changes in child behavior over time. We followed 268 participants from the prospective New Hampshire Birth Cohort Study between birth and age 5 years. We measured arsenic (As), copper (Cu), manganese (Mn), lead (Pb), selenium (Se), and zinc (Zn) in toenails from 6-week-old infants. The Behavioral Symptoms Index (BSI), externalizing, and internalizing symptoms were assessed using the Behavior Assessment System for Children, 2nd edition (BASC-2) at ages 3 and 5 years. Multivariable linear regression was used to estimate associations of metals with behavior change, calculated as the difference in symptom raw scores between 3 and 5 years, in addition to the associations for symptom scores at 3 and 5 years separately. Sex-specific associations were also explored using stratified models and a sex-metal interaction term. Adjusted associations of metals and change in behavior varied by exposure and outcome. Each 1 μg/g increase in ln toenail Cu was associated with improved behavior between 3 and 5 years [BSI: β = - 3.88 (95%CI: - 7.12, - 0.64); Externalizing problems: β = - 2.20 (95%CI: - 4.07, - 0.33)]. Increasing Zn was associated with increased externalizing behavior over time (β = 3.42 (95%CI: 0.60, 6.25). Sex-stratified analyses suggested more pronounced associations among boys compared to girls. Perinatal exposure to metals may alter behavioral development between ages 3 and 5 years. Findings support the need for more research on associations between metals and neurodevelopment over longer time periods.

Machine Learning-Derived Active Sleep as an Early Predictor of White Matter Development in Preterm Infants

White matter dysmaturation is commonly seen in preterm infants admitted to the neonatal intensive care unit (NICU). Animal research has shown that active sleep is essential for early brain plasticity. This study aimed to determine the potential of active sleep as an early predictor for subsequent white matter development in preterm infants. Using heart and respiratory rates routinely monitored in the NICU, we developed a machine learning-based automated sleep stage classifier in a cohort of 25 preterm infants (12 females). The automated classifier was subsequently applied to a study cohort of 58 preterm infants (31 females) to extract active sleep percentage over 5-7 consecutive days during 29-32 weeks of postmenstrual age. Each of the 58 infants underwent high-quality T2-weighted magnetic resonance brain imaging at term-equivalent age, which was used to measure the total white matter volume. The association between active sleep percentage and white matter volume was examined using a multiple linear regression model adjusted for potential confounders. Using the automated classifier with a superior sleep classification performance [mean area under the receiver operating characteristic curve (AUROC) = 0.87, 95% CI 0.83-0.92], we found that a higher active sleep percentage during the preterm period was significantly associated with an increased white matter volume at term-equivalent age [β = 0.31, 95% CI 0.09-0.53, false discovery rate (FDR)-adjusted p-value = 0.021]. Our results extend the positive association between active sleep and early brain development found in animal research to human preterm infants and emphasize the potential benefit of sleep preservation in the NICU setting.

Thalamic connectivity topography in newborns with spina bifida: association with neurological functional level but not developmental outcome at 2 years

Spina bifida affects spinal cord and cerebral development, leading to motor and cognitive delay. We investigated whether there are associations between thalamocortical connectivity topography, neurological function, and developmental outcomes in open spina bifida. Diffusion tensor MRI was used to assess thalamocortical connectivity in 44 newborns with open spina bifida who underwent prenatal surgical repair. We quantified the volume of clusters formed based on the strongest probabilistic connectivity to the frontal, parietal, and temporal cortex. Developmental outcomes were assessed using the Bayley III Scales, while the functional level of the lesion was assessed by neurological examination at 2 years of age. Higher functional level was associated with smaller thalamo-parietal, while lower functional level was associated with smaller thalamo-temporal connectivity clusters (Bonferroni-corrected P < 0.05). Lower functional levels were associated with weaker thalamic temporal connectivity, particularly in the ventrolateral and ventral anterior nuclei. No associations were found between thalamocortical connectivity and developmental outcomes. Our findings suggest that altered thalamocortical circuitry development in open spina bifida may contribute to impaired lower extremity function, impacting motor function and independent ambulation. We hypothesize that the neurologic function might not merely be caused by the spinal cord lesion, but further impacted by the disruption of cerebral neuronal circuitry.

Distinct alterations in white matter properties and organization related to maternal treatment initiation in neonates exposed to HIV but uninfected

HIV exposed-uninfected (HEU) infants and children are at risk of developmental delays as compared to uninfected unexposed (HUU) populations. The effects of exposure to in utero HIV and ART regimens on the HEU the developing brain are not well understood. In a cohort of 2-week-old newborns, we used diffusion tensor imaging (DTI) tractography and graph theory to examine the influence of HIV and ART exposure in utero on neonate white matter integrity and organisation. The cohort included HEU infants born to mothers who started ART before conception (HEUpre) and after conception (HEUpost), as well as HUU infants from the same community. We investigated HIV exposure and ART duration group differences in DTI metrics (fractional anisotropy (FA) and mean diffusivity (MD)) and graph measures across white matter. We found increased MD in white matter connections involving the thalamus and limbic system in the HEUpre group compared to HUU. We further identified reduced nodal efficiency in the basal ganglia. Within the HEUpost group, we observed reduced FA in cortical-subcortical and cerebellar connections as well as decreased transitivity in the hindbrain area compared to HUU. Overall, our analysis demonstrated distinct alterations in white matter integrity related to the timing of maternal ART initiation that influence regional brain network properties.

Dietary supplementation of 3'-sialyllactose or 6'-sialyllactose elicits minimal influence on cognitive and brain development in growing pigs

Sialylated human milk oligosaccharides (HMO), such as 3'-sialyllactose (3'-SL) and 6'-sialyllactose (6'-SL), are abundant throughout lactation and at much higher concentrations than are present in bovine milk or infant formulas. Previous studies have suggested that sialylated HMO may have neurocognitive benefits in early life. Recent research has focused on infant formula supplementation with key nutrients and bioactives to narrow the developmental gap between formula-fed and breastfed infants. Herein, we investigated the impact of supplemental 3'-SL or 6'-SL on cognitive and brain development at two time-points [postnatal days (PND) 33 and 61]. Two-day-old piglets (N = 75) were randomly assigned to commercial milk replacer ad libitum without or with 3'-SL or 6'-SL (added in a powdered form at a rate of 0.2673% on an as-is weight basis). Cognitive development was assessed via novel object recognition and results were not significant at both time-points (p > 0.05). Magnetic resonance imaging was used to assess structural brain development. Results varied between scan type, diet, and time-point. A main effect of diet was observed for absolute volume of white matter and 9 other regions of interest (ROI), as well as for relative volume of the pons on PND 30 (p < 0.05). Similar effects were observed on PND 58. Diffusion tensor imaging indicated minimal differences on PND 30 (p > 0.05). However, several dietary differences across the diffusion outcomes were observed on PND 58 (p < 0.05) indicating dietary impacts on brain microstructure. Minimal dietary differences were observed from myelin water fraction imaging at either time-point. Overall, sialyllactose supplementation had no effects on learning and memory as assessed by novel object recognition, but may influence temporally-dependent aspects of brain development.

Trends in research related to fetal therapy from 2012 to 2022: a bibliometric analysis

Background

The development of prenatal diagnosis technology allows prompt detection of severe fetal diseases. To address adverse factors that threaten fetal survival, fetal therapy came into existence, which aims to preserve the function after birth to a higher degree and improve the quality of life.

Objective

To conduct a comprehensive bibliometric analysis of studies on fetal therapy in the past decade and explore the research trends and hotspots in this field.

Methods

We conducted a systematic search on the Web of Science Core Collection to retrieve studies related to fetal therapy published from 2012 to 2022. VOSviewer and CiteSpace were used to analyze the key features of studies, including annual output, countries/regions, institutions, authors, references, research hotspots, and frontiers.

Results

A total of 9,715 articles were included after eliminating duplicates. The annual distribution of the number of articles showed that the number of articles published in fetal therapy had increased in the past decade. Countries and institutions showed that fetal therapy is more mature in the United States. Author analysis showed the core investigators in the field. Keyword analysis showed the clustering and emergence frequency, which helped summarize the research results and frontier hotspots in this field. The cocited references were sorted out to determine the literature with a high ranking of fetal therapy in recent years, and the research trend in recent years was analyzed.

Conclusions

This study reveals that countries, institutions, and researchers should promote wider cooperation and establish multicenter research cooperation in fetal therapy research. Moreover, fetal therapy has been gradually explored from traditional surgical treatment to gene therapy and stem cell therapy. In recent years, fetoscopic laser surgery, guideline, and magnetic resonance imaging have become the research hotspots in the field.

Growth in early infancy drives optimal brain functional connectivity which predicts cognitive flexibility in later childhood

Functional brain network organization, measured by functional connectivity (FC), reflects key neurodevelopmental processes for healthy development. Early exposure to adversity, e.g. undernutrition, affects neurodevelopment, observable via disrupted FC, and leads to poorer outcomes from preschool age onward. We assessed longitudinally the impact of early growth trajectories on developmental FC in a rural Gambian population from age 5 to 24 months. To investigate how these early trajectories relate to later childhood outcomes, we assessed cognitive flexibility at 3-5 years. We observed that early physical growth before the fifth month of life drove optimal developmental trajectories of FC that in turn predicted cognitive flexibility at pre-school age. In contrast to previously studied developmental populations, this Gambian sample exhibited long-range interhemispheric FC that decreased with age. Our results highlight the measurable effects that poor growth in early infancy has on brain development and the subsequent impact on pre-school age cognitive development, underscoring the need for early life interventions throughout global settings of adversity.

Prenatal and Postnatal Maternal Depressive Symptoms Are Associated With White Matter Integrity in 5-Year-Olds in a Sex-Specific Manner

BACKGROUND

Prenatal and postnatal maternal psychological distress predicts various detrimental consequences on social, behavioral, and cognitive development of offspring, especially in girls. Maturation of white matter (WM) continues from prenatal development into adulthood and is thus susceptible to exposures both before and after birth.

METHODS

WM microstructural features of 130 children (mean age, 5.36 years; range, 5.04-5.79 years; 63 girls) and their association with maternal prenatal and postnatal depressive and anxiety symptoms were investigated with diffusion tensor imaging, tract-based spatial statistics, and regression analyses. Maternal questionnaires were collected during first, second, and third trimesters and at 3, 6, and 12 months postpartum with the Edinburgh Postnatal Depression Scale (EPDS) for depressive symptoms and Symptom Checklist-90 for general anxiety. Covariates included child's sex; child's age; maternal prepregnancy body mass index; maternal age; socioeconomic status; and exposures to smoking, selective serotonin reuptake inhibitors, and synthetic glucocorticoids during pregnancy.

RESULTS

Prenatal second-trimester EPDS scores were positively associated with fractional anisotropy in boys (p < .05, 5000 permutations) after controlling for EPDS scores 3 months postpartum. In contrast, postpartum EPDS scores at 3 months correlated negatively with fractional anisotropy (p < .01, 5000 permutations) in widespread areas only in girls after controlling for prenatal second-trimester EPDS scores. Perinatal anxiety was not associated with WM structure.

CONCLUSIONS

These results suggest that prenatal and postnatal maternal psychological distress is associated with brain WM tract developmental alterations in a sex- and timing-dependent manner. Future studies including behavioral data are required to consolidate associative outcomes for these alterations.

Bursting with Potential: How Sensorimotor Beta Bursts Develop from Infancy to Adulthood

Beta activity is thought to play a critical role in sensorimotor processes. However, little is known about how activity in this frequency band develops. Here, we investigated the developmental trajectory of sensorimotor beta activity from infancy to adulthood. We recorded EEG from 9-month-old, 12-month-old, and adult humans (male and female) while they observed and executed grasping movements. We analyzed "beta burst" activity using a novel method that combines time-frequency decomposition and principal component analysis. We then examined the changes in burst rate and waveform motifs along the selected principal components. Our results reveal systematic changes in beta activity during action execution across development. We found a decrease in beta burst rate during movement execution in all age groups, with the greatest decrease observed in adults. Additionally, we identified three principal components that defined waveform motifs that systematically changed throughout the trial. We found that bursts with waveform shapes closer to the median waveform were not rate-modulated, whereas those with waveform shapes further from the median were differentially rate-modulated. Interestingly, the decrease in the rate of certain burst motifs occurred earlier during movement and was more lateralized in adults than in infants, suggesting that the rate modulation of specific types of beta bursts becomes increasingly refined with age.SIGNIFICANCE STATEMENT We demonstrate that, like in adults, sensorimotor beta activity in infants during reaching and grasping movements occurs in bursts, not oscillations like thought traditionally. Furthermore, different beta waveform shapes were differentially modulated with age, including more lateralization in adults. Aberrant beta activity characterizes various developmental disorders and motor difficulties linked to early brain injury, so looking at burst waveform shape could provide more sensitivity for early identification and treatment of affected individuals before any behavioral symptoms emerge. More generally, comparison of beta burst activity in typical versus atypical motor development will also be instrumental in teasing apart the mechanistic functional roles of different types of beta bursts.

Maternal Childhood Abuse Versus Neglect Associated with Differential Patterns of Infant Brain Development

Severity of maternal childhood maltreatment has been associated with lower infant grey matter volume and amygdala volume during the first two years of life. A developing literature argues that effects of threat (abuse) and of deprivation (neglect) should be assessed separately because these distinct aspects of adversity may have different impacts on developmental outcomes. However, distinct effects of threat versus deprivation have not been assessed in relation to intergenerational effects of child maltreatment. The objective of this study was to separately assess the links of maternal childhood abuse and neglect with infant grey matter volume (GMV), white matter volume (WMV), amygdala and hippocampal volume. Participants included 57 mother-infant dyads. Mothers were assessed for childhood abuse and neglect using the Adverse Childhood Experiences (ACE) questionnaire in a sample enriched for childhood maltreatment. Between 4 and 24 months (M age = 12.28 months, SD = 5.99), under natural sleep, infants completed an MRI using a 3.0 T Siemens scanner. GMV, WMV, amygdala and hippocampal volumes were extracted via automated segmentation. Maternal history of neglect, but not abuse, was associated with lower infant GMV. Maternal history of abuse, but not neglect, interacted with age such that abuse was associated with smaller infant amygdala volume at older ages. Results are consistent with a threat versus deprivation framework, in which threat impacts limbic regions central to the stress response, whereas deprivation impacts areas more central to cognitive function. Further studies are needed to identify mechanisms contributing to these differential intergenerational associations of threat versus deprivation.

Adolescents at risk for depression show increased white matter microstructure with age across diffuse areas of the brain

Maternal history of depression is a strong predictor of depression in offspring and linked to structural and functional alterations in the developing brain. However, very little work has examined differences in white matter in adolescents at familial risk for depression. In a sample aged 9-14 (n = 117), we used tract-based spatial statistics (TBSS) to examine differences in white matter microstructure between adolescents with (n = 42) and without (n = 75) maternal history of depression. Microstructure was indexed using fractional anisotropy (FA). Threshold-free cluster enhancement was applied and cluster maps were thresholded at whole-brain family-wise error < .05. There was no significant main effect of risk status on FA. However, there was a significant interaction between risk status and age, such that large and diffuse portions of the white matter skeleton showed relatively increased FA with age for youth with a maternal history of depression compared to those without. Most tracts identified by the interaction were robust to controlling for sex, youth internalizing, in-scanner motion, neighborhood SES, and intra-cranial volume, evidence that maternal depression is a unique predictor of white matter alterations in youth. Widespread increases in FA with age may correspond to a global pattern of accelerated brain maturation in youth at risk for depression.

General anaesthesia, the developing brain, and cerebral white matter alterations: a narrative review

The potential neurotoxic impact of anaesthetic agents has been the subject of sustained debate and continuing research. White matter, which comprises more than half of the brain volume and largely consists of myelinated axonal bundles, is critical for communication between diverse brain regions and for supporting neurobehavioural function. Evidence points to a correlation between exposure to anaesthesia and white matter alterations, which might underpin the ensuing cognitive and behavioural abnormalities. This review summarises the neuropathological and neuroimaging findings related to anaesthesia-induced white matter alterations in the developing brain. Future research is required to understand the effects of anaesthesia exposure on white matter development.

Structural and functional connectome relationships in early childhood

There is strong evidence that the functional connectome is highly related to the white matter connectome in older children and adults, though little is known about structure-function relationships in early childhood. We investigated the development of cortical structure-function coupling in children longitudinally scanned at 1, 2, 4, and 6 years of age (N = 360) and in a comparison sample of adults (N = 89). We also applied a novel graph convolutional neural network-based deep learning model with a new loss function to better capture inter-subject heterogeneity and predict an individual's functional connectivity from the corresponding structural connectivity. We found regional patterns of structure-function coupling in early childhood that were consistent with adult patterns. In addition, our deep learning model improved the prediction of individual functional connectivity from its structural counterpart compared to existing models.

Structural networking of the developing brain: from maturation to neurosurgical implications

Modern neuroscience agrees that neurological processing emerges from the multimodal interaction among multiple cortical and subcortical neuronal hubs, connected at short and long distance by white matter, to form a largely integrated and dynamic network, called the brain "connectome." The final architecture of these circuits results from a complex, continuous, and highly protracted development process of several axonal pathways that constitute the anatomical substrate of neuronal interactions. Awareness of the network organization of the central nervous system is crucial not only to understand the basis of children's neurological development, but also it may be of special interest to improve the quality of neurosurgical treatments of many pediatric diseases. Although there are a flourishing number of neuroimaging studies of the connectome, a comprehensive vision linking this research to neurosurgical practice is still lacking in the current pediatric literature. The goal of this review is to contribute to bridging this gap. In the first part, we summarize the main current knowledge concerning brain network maturation and its involvement in different aspects of normal neurocognitive development as well as in the pathophysiology of specific diseases. The final section is devoted to identifying possible implications of this knowledge in the neurosurgical field, especially in epilepsy and tumor surgery, and to discuss promising perspectives for future investigations.

T1-weighted fast fluid-attenuated inversion-recovery sequence (T1-FFLAIR) enables the visualization and quantification of fetal brain myelination in utero

OBJECTIVES

To investigate the advantage of T1-weighted fast fluid-attenuated inversion-recovery MRI sequence without (T1-FFLAIR) and with compressed sensing technology (T1-FFLAIR-CS), which shows improved T1-weighted contrast, over standard used T1-weighted fast field echo (T1-FFE) sequence for the assessment of fetal myelination.

MATERIALS AND METHODS

This retrospective single-center study included 115 consecutive fetal brain MRI examinations (63 axial and 76 coronal, mean gestational age (GA) 28.56 ± 5.23 weeks, range 19-39 weeks). Two raters, blinded to GA, qualitatively assessed a fetal myelin total score (MTS) on each T1-weighted sequence at five brain regions (medulla oblongata, pons, mesencephalon, thalamus, central region). One rater performed region-of-interest quantitative analysis (n = 61) at the same five brain regions. Pearson correlation analysis was applied for correlation of MTS and of the signal intensity ratios (relative to muscle) with GA on each T1-weighted sequence. Fetal MRI-based results were compared with myelination patterns of postmortem fetal human brains (n = 46; GA 18 to 42), processed by histological and immunohistochemical analysis.

RESULTS

MTS positively correlated with GA on all three sequences (all r between 0.802 and 0.908). The signal intensity ratios measured at the five brain regions correlated best with GA on T1-FFLAIR (r between 0.583 and 0.785). T1-FFLAIR demonstrated significantly better correlations with GA than T1-FFE for both qualitative and quantitative analysis (all p < 0.05). Furthermore, T1-FFLAIR enabled the best visualization of myelinated brain structures when compared to histology.

CONCLUSION

T1-FFLAIR outperforms the standard T1-FFE sequence in the visualization of fetal brain myelination, as demonstrated by qualitative and quantitative methods.

CLINICAL RELEVANCE STATEMENT

T1-weighted fast fluid-attenuated inversion-recovery sequence (T1-FFLAIR) provided best visualization and quantification of myelination in utero that, in addition to the relatively short acquisition time, makes feasible its routine application in fetal MRI for the assessment of brain myelination.

KEY POINTS

• So far, the assessment of fetal myelination in utero was limited due to the insufficient contrast. • T1-weighted fast fluid-attenuated inversion-recovery sequence allows a qualitative and quantitative assessment of fetal brain myelination. • T1-weighted fast fluid-attenuated inversion-recovery sequence outperforms the standard used T1-weighted sequence for visualization and quantification of myelination in utero.

Bridging the Divide: Brain and Behavior in Developmental Language Disorder

Developmental language disorder (DLD) is a heterogenous neurodevelopmental disorder that affects a child's ability to comprehend and/or produce spoken and/or written language, yet it cannot be attributed to hearing loss or overt neurological damage. It is widely believed that some combination of genetic, biological, and environmental factors influences brain and language development in this population, but it has been difficult to bridge theoretical accounts of DLD with neuroimaging findings, due to heterogeneity in language impairment profiles across individuals and inconsistent neuroimaging findings. Therefore, the purpose of this overview is two-fold: (1) to summarize the neuroimaging literature (while drawing on findings from other language-impaired populations, where appropriate); and (2) to briefly review the theoretical accounts of language impairment patterns in DLD, with the goal of bridging the disparate findings. As will be demonstrated with this overview, the current state of the field suggests that children with DLD have atypical brain volume, laterality, and activation/connectivity patterns in key language regions that likely contribute to language difficulties. However, the precise nature of these differences and the underlying neural mechanisms contributing to them remain an open area of investigation.

In vivo labeling and quantitative imaging of neuronal populations using MRI

The study of neural circuits, which underlies perception, cognition, emotion, and behavior, is essential for understanding the mammalian brain, a complex organ consisting of billions of neurons. To study the structure and function of the brain, in vivo neuronal labeling and imaging techniques are crucial as they provide true physiological information that ex vivo methods cannot offer. In this paper, we present a new strategy for in vivo neuronal labeling and quantification using MRI. We demonstrate the efficacy of this method by delivering the oatp1a1 gene to the target neurons using rAAV2-retro virus. OATP1A1 protein expression on the neuronal membrane increased the uptake of a specific MRI contrast agent (Gd-EOB-DTPA), leading to hyperintense signals on T1W images of labeled neuronal populations. We also used dynamic contrast enhancement-based methods to obtain quantitative information on labeled neuronal populations in vivo.

Neurocomputational modeling of speech motor development

This review describes a computational approach for modeling the development of speech motor control in infants. We address the development of two levels of control: articulation of individual speech sounds (defined here as phonemes, syllables, or words for which there is an optimized motor program) and production of sound sequences such as phrases or sentences. We describe the DIVA model of speech motor control and its application to the problem of learning individual sounds in the infant's native language. Then we describe the GODIVA model, an extension of DIVA, and how chunking of frequently produced phoneme sequences is implemented within it.

Quantitative Relaxometry Assessment of Brain Microstructural Abnormality of Preschool Children With Autism Spectrum Disorder With Synthetic Magnetic Resonance Imaging

OBJECTIVE

This study aimed to perform an assessment of brain microstructure in children with autism aged 2 to 5 years using relaxation times acquired by synthetic magnetic resonance imaging.

MATERIALS AND METHODS

Thirty-four children with autism spectrum disorder (ASD) (ASD group) and 17 children with global developmental delay (GDD) (GDD group) were enrolled, and synthetic magnetic resonance imaging was performed to obtain T1 and T2 relaxation times. The differences in brain relaxation times between the 2 groups of children were compared, and the correlation between significantly changed T1/T2 and clinical neuropsychological scores in the ASD group was analyzed.

RESULTS

Compared with the GDD group, shortened T1 relaxation times in the ASD group were distributed in the genu of corpus callosum (GCC) ( P = 0.003), splenium of corpus callosum ( P = 0.002), and right thalamus (TH) ( P = 0.014), whereas shortened T2 relaxation times in the ASD group were distributed in GCC ( P = 0.011), left parietal white matter ( P = 0.035), and bilateral TH (right, P = 0.014; left, P = 0.016). In the ASD group, the T2 of the left parietal white matter is positively correlated with gross motor (developmental quotient [DQ] 2) and personal-social behavior (DQ5), respectively ( r = 0.377, P = 0.028; r = 0.392, P = 0.022); the T2 of the GCC was positively correlated with DQ5 ( r = 0.404, P = 0.018); and the T2 of the left TH is positively correlated with DQ2 and DQ5, respectively ( r = 0.433, P = 0.009; r = 0.377, P = 0.028). All significantly changed relaxation values were not significantly correlated with Childhood Autism Rating Scale scores.

CONCLUSIONS

The shortened relaxometry times in the brain of children with ASD may be associated with the increased myelin content and decreased water content in the brain of children with ASD in comparison with GDD, contributing the understanding of the pathophysiology of ASD. Therefore, the T1 and T2 relaxometry may be used as promising imaging markers for ASD diagnosis.

Multi-echo Acquisition and Thermal Denoising Advances Infant 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, but precise characterization of systems organization during periods of high plasticity might be most influential towards discoveries promoting lifelong health. Collecting and analyzing precision fMRI data during early development has unique challenges and emphasizes the importance of novel methods to improve data acquisition, processing, and analysis strategies in infant samples. Here, we investigate the applicability of two such methods from adult MRI research, multi-echo (ME) data acquisition and thermal noise removal with Noise reduction with distribution corrected principal component analysis (NORDIC), in precision fMRI data from three newborn infants. Compared to an adult example subject, T2* relaxation times calculated from ME data in infants were longer and more variable across the brain, pointing towards ME acquisition being a promising tool for optimizing developmental fMRI. The application of thermal denoising via NORDIC increased tSNR and the overall strength of functional connections as well as the split-half reliability of functional connectivity matrices in infant ME data. While our findings related to NORDIC denoising are coherent with the adult literature and ME data acquisition showed high promise, its application in developmental samples needs further investigation. The present work reveals gaps in our understanding of the best techniques for developmental brain imaging and highlights the need for further developmentally-specific methodological advances and optimizations, towards precision functional imaging in infants.

Prospective assessment of early developmental markers and their association with neuropsychological impairment

Children who experience adversities in the pre-perinatal period are at increased risk of developing impairment later in life, despite the absence of overt brain and neurological abnormalities. However, many of these children exhibit sequelae several years after a period of normal appearance. As a result, the need for reliable developmental assessments for the early detection of infants at high risk of adverse neurodevelopmental outcomes has emerged. The Griffiths Mental Developmental Scales have a promising but poorly explored prognostic ability. This longitudinal study evaluated the predictive power of the Griffiths Mental Developmental Scales at 12 and 24 months on the cognitive and neuropsychological profile at 6 years of age in a sample of 70 children with a history of prematurity or perinatal asphyxia but without brain and neurological abnormalities. We found that the Griffiths Mental Developmental Scales at 24 months had good predictive ability on the intelligence quotient at 6 years and the capacity to predict some neuropsychological performances. On the other hand, the Griffiths Mental Developmental Scale at 12 months was not associated with the performance at 6 years or 24 months.   Conclusion: Data on brain development converge to indicate that the first two years of age represent a critical stage of development, particularly for children experiencing mild pre-perinatal adversities who are thought to exhibit white matter dysmaturity. For this reason, this age is crucial for identifying which children are at major risk, leaving enough time to intervene before overt deficits become apparent. Brain development in the first 2 years could explain the limited reliability of early neurodevelopmental testing. What is Known: • Pre-perinatal adversities increase the risk of developing neurodevelopmental disorders. • The predictive ability of the Griffith scale is poorly explored in low-grade conditions. What is New: • The predictive ability of the Griffith scale has been investigated in low-risk children. • A complete neuropsychological profile could offer a more accurate prediction than the intellectual quotient.

Prospective Association between Total and Trimester-Specific Gestational Weight Gain Rate and Physical Growth Status in Children within 24 Months after Birth

In this study, our aim was to investigate the potential correlation between the mother's total gestational weight gain (GWG) rate and the trimester-specific GWG rate (GWGR) with the physical development status of the child within 24 months of age. We utilized linear regression models and linear mixed effects models to explore both time point and longitudinal relationships between GWGR and children's anthropometric outcome z-scores at 0, 1, 2, 4, 6, 9, 12, 18, and 24 months. To examine the critical exposure windows, we employed multiple informant models. We also conducted a stratified analysis considering pre-pregnancy BMI and the gender of the children. Our findings revealed notable positive associations between total GWGR and z-scores for body mass index for age (BMIZ), head circumference for age (HCZ), weight for age (WAZ), length for age (LAZ), and weight for length (WHZ) across different trimesters of pregnancy (pint < 0.05). The GWGR during the first two trimesters mainly influenced the relationship between total GWGR and BMIZ, WAZ, and LAZ, while the GWGR during the first trimester had a significant impact on the correlation with HCZ (0.206, 95% CI 0.090 to 0.322). Notably, the associations of GWGR and children's BMIZ were pronounced in male children and pre-pregnancy normal-weight women. In conclusion, our study findings indicated that a higher GWGR during each trimester was associated with greater physical growth during the first 24 months of life, especially GWGR in the first and second trimesters.

Prenatal depressive symptoms are associated with altered structural brain networks in infants and moderated by infant sleep

BACKGROUND

The prevalence of prenatal depressive symptoms has more than doubled during the COVID-19 pandemic, raising substantial concerns about child outcomes including sleep problems and altered brain development. The objective of this work was to determine relationships between prenatal depressive symptoms, infant brain network structure, and infant sleep.

METHODS

Pregnant individuals were recruited as part of the Pregnancy during the Pandemic (PdP) study. Maternal depressive symptoms were measured in pregnancy and postpartum. When infants of those participants were 3 months of age (n=66; 26 females), infants underwent diffusion magnetic resonance imaging and infant sleep was evaluated. Using tractography, we calculated structural connectivity matrices for the default mode (DMN) and limbic networks. We examined associations between graph theory metrics of infant brain networks and prenatal maternal depressive symptoms, with infant sleep as a moderator.

RESULTS

Prenatal depressive symptoms were negatively related to average DMN clustering coefficient and local efficiency in infant brains. Infant sleep duration was related to DMN global efficiency and moderated the relationship between prenatal depressive symptoms and density of limbic connections such that infants who slept less had a more negative relationship between prenatal depressive symptoms and local brain connectivity.

CONCLUSIONS

Prenatal depressive symptoms appear to impact early topological development in brain networks important for emotion regulation. In the limbic network, sleep duration moderated this relationship, suggesting sleep may play a role in infant brain network development.

Diagnostic performance of synthetic relaxometry for predicting neurodevelopmental outcomes in premature infants: a feasibility study

OBJECTIVES

To investigate the predictability of synthetic relaxometry for neurodevelopmental outcomes in premature infants and to evaluate whether a combination of relaxation times with clinical variables or qualitative MRI abnormalities improves the predictive performance.

METHODS

This retrospective study included 33 premature infants scanned with synthetic MRI near or at term equivalent age. Based on neurodevelopmental assessments at 18-24 months of corrected age, infants were classified into two groups (no/mild disability [n = 23] vs. moderate/severe disability [n = 10]). Clinical and MRI characteristics associated with moderate/severe disability were explored, and combined models incorporating independent predictors were established. Ultimately, the predictability of relaxation times, clinical variables, MRI findings, and a combination of the two were evaluated and compared. The models were internally validated using bootstrap resampling.

RESULTS

Prolonged T1-frontal/parietal and T2-parietal periventricular white matter (PVWM), moderate-to-severe white matter abnormality, and bronchopulmonary dysplasia were significantly associated with moderate/severe disability. The overall predictive performance of each T1-frontal/-parietal PVWM model was comparable to that of individual MRI finding and clinical models (AUC = 0.71 and 0.76 vs. 0.73 vs. 0.83, respectively; p > 0.27). The combination of clinical variables and T1-parietal PVWM achieved an AUC of 0.94, sensitivity of 90%, and specificity of 91.3%, outperforming the clinical model alone (p = 0.049). The combination of MRI finding and T1-frontal PVWM yielded AUC of 0.86, marginally outperforming the MRI finding model (p = 0.09). Bootstrap resampling showed that the models were valid.

CONCLUSIONS

It is feasible to predict adverse outcomes in premature infants by using early synthetic relaxometry. Combining relaxation time with clinical variables or MRI finding improved prediction.

CLINICAL RELEVANCE STATEMENT

Synthetic relaxometry performed during the neonatal period may serve as a biomarker for predicting adverse neurodevelopmental outcomes in premature infants.

KEY POINTS

• Synthetic relaxometry based on T1 relaxation time of parietal periventricular white matter showed acceptable performance in predicting adverse outcome with an AUC of 0.76 and an accuracy of 78.8%. • The combination of relaxation time with clinical variables and/or structural MRI abnormalities improved predictive performance of adverse outcomes. • Synthetic relaxometry performed during the neonatal period helps predict adverse neurodevelopmental outcome in premature infants.

Effect of number of diffusion encoding directions in neonatal diffusion tensor imaging using Tract-Based Spatial Statistical analysis

Diffusion tensor imaging (DTI) has been used to study the developing brain in early childhood, infants and in utero studies. In infants, number of used diffusion encoding directions has traditionally been smaller in earlier studies down to the minimum of 6 orthogonal directions. Whereas the more recent studies often involve more directions, number of used directions remain an issue when acquisition time is optimized without compromising on data quality and in retrospective studies. Variability in the number of used directions may introduce bias and uncertainties to the DTI scalar estimates that affect cross-sectional and longitudinal study of the brain. We analysed DTI images of 133 neonates, each data having 54 directions after quality control, to evaluate the effect of number of diffusion weighting directions from 6 to 54 with interval of 6 to the DTI scalars with Tract-Based Spatial Statistics (TBSS) analysis. The TBSS analysis was applied to DTI scalar maps, and the mean region of interest (ROI) values were extracted using JHU atlas. We found significant bias in ROI mean values when only 6 directions were used (positive in fractional anisotropy [FA] and negative in fractional anisotropy [MD], axial diffusivity [AD] and fractional anisotropy [RD]), while when using 24 directions and above, the difference to scalar values calculated from 54 direction DTI was negligible. In repeated measures voxel-wise analysis, notable differences to 54 direction DTI were observed with 6, 12 and 18 directions. DTI measurements from data with at least 24 directions may be used in comparisons with DTI measurements from data with higher numbers of directions.

Lateralization of major white matter tracts during infancy is time-varying and tract-specific

Lateralization patterns are a major structural feature of brain white matter and have been investigated as a neural architecture that indicates and supports the specialization of cognitive processing and observed behaviors, e.g. language skills. Many neurodevelopmental disorders have been associated with atypical lateralization, reinforcing the need for careful measurement and study of this structural characteristic. Unfortunately, there is little consensus on the direction and magnitude of lateralization in major white matter tracts during the first months and years of life-the period of most rapid postnatal brain growth and cognitive maturation. In addition, no studies have examined white matter lateralization in a longitudinal pediatric sample-preventing confirmation of if and how white matter lateralization changes over time. Using a densely sampled longitudinal data set from neurotypical infants aged 0-6 months, we aim to (i) chart trajectories of white matter lateralization in 9 major tracts and (ii) link variable findings from cross-sectional studies of white matter lateralization in early infancy. We show that patterns of lateralization are time-varying and tract-specific and that differences in lateralization results during this period may reflect the dynamic nature of lateralization through development, which can be missed in cross-sectional studies.

Network controllability of structural connectomes in the neonatal brain

White matter connectivity supports diverse cognitive demands by efficiently constraining dynamic brain activity. This efficiency can be inferred from network controllability, which represents the ease with which the brain moves between distinct mental states based on white matter connectivity. However, it remains unclear how brain networks support diverse functions at birth, a time of rapid changes in connectivity. Here, we investigate the development of network controllability during the perinatal period and the effect of preterm birth in 521 neonates. We provide evidence that elements of controllability are exhibited in the infant's brain as early as the third trimester and develop rapidly across the perinatal period. Preterm birth disrupts the development of brain networks and altered the energy required to drive state transitions at different levels. In addition, controllability at birth is associated with cognitive ability at 18 months. Our results suggest network controllability develops rapidly during the perinatal period to support cognitive demands but could be altered by environmental impacts like preterm birth.

Early adversity changes the economic conditions of mouse structural brain network organization

Early adversity can change educational, cognitive, and mental health outcomes. However, the neural processes through which early adversity exerts these effects remain largely unknown. We used generative network modeling of the mouse connectome to test whether unpredictable postnatal stress shifts the constraints that govern the organization of the structural connectome. A model that trades off the wiring cost of long-distance connections with topological homophily (i.e., links between regions with shared neighbors) generated simulations that successfully replicate the rodent connectome. The imposition of early life adversity shifted the best-performing parameter combinations toward zero, heightening the stochastic nature of the generative process. Put simply, unpredictable postnatal stress changes the economic constraints that reproduce rodent connectome organization, introducing greater randomness into the development of the simulations. While this change may constrain the development of cognitive abilities, it could also reflect an adaptive mechanism that facilitates effective responses to future challenges.