Delineation of early brain development from fetuses to infants with diffusion MRI and beyond

Oligodendrocyte-specific expression of PSG8-AS1 suggests a role in myelination with prognostic value in oligodendroglioma

The segmentally duplicated Pregnancy-specific glycoprotein (PSG) locus on chromosome 19q13 may be one of the most rapidly evolving in the human genome. It comprises ten coding genes (PSG1-9, 11) and one predominantly non-coding gene (PSG10) that are expressed in the placenta and gut, in addition to several poorly characterized long non-coding RNAs. We report that long non-coding RNA PSG8-AS1 has an oligodendrocyte-specific expression pattern and is co-expressed with genes encoding key myelin constituents. PSG8-AS1 exhibits two peaks of expression during human brain development coinciding with the most active periods of oligodendrogenesis and myelination. PSG8-AS1 orthologs were found in the genomes of several primates but significant expression was found only in the human, suggesting a recent evolutionary origin of its proposed role in myelination. Additionally, because co-deletion of chromosomes 1p/19q is a genomic marker of oligodendroglioma, expression of PSG8-AS1 was examined in these tumors. PSG8-AS1 may be a promising diagnostic biomarker for glioma, with prognostic value in oligodendroglioma.

Comparative Analysis of Brain Age Prediction Using Structural and Diffusion MRIs in Neonates

Using machine learning techniques to predict brain age from multimodal data has become a crucial biomarker for assessing brain development. Among various types of brain imaging data, structural magnetic resonance imaging (sMRI) and diffusion magnetic resonance imaging (dMRI) are the most commonly used modalities. sMRI focuses on depicting macrostructural features of the brain, while dMRI reveals the orientation of major white matter fibers and changes in tissue microstructure. However, their differential capabilities in reflecting newborn age and clinical implications have not been systematically studied. This study aims to explore the impact of sMRI and dMRI on brain age prediction. Comparing predictions based on T2-weighted(T2w) and fractional anisotropy (FA) images, we found their mean absolute errors (MAE) in predicting infant age to be similar. Exploratory analysis revealed for T2w images, areas such as the cerebral cortex and ventricles contribute most significantly to age prediction, whereas FA images highlight the cerebral cortex and regions of the main white matter tracts. Despite both modalities focusing on the cerebral cortex, they exhibit significant region-wise differences, reflecting developmental disparities in macro- and microstructural aspects of the cortex. Additionally, we examined the effects of prematurity, gender, and hemispherical asymmetry of the brain on age prediction for both modalities. Results showed significant differences (p<0.05) in age prediction biases based on FA images across gender and hemispherical asymmetry, whereas no significant differences were observed with T2w images. This study underscores the differences between T2w and FA images in predicting infant brain age, offering new perspectives for studying infant brain development and aiding more effective assessment and tracking of infant development.

Maternal adverse childhood experiences and infant visual-limbic white matter development

BACKGROUND

Maternal adverse childhood experiences (ACEs) are robust predictors of mental health for both the exposed individual and the next generation; however, the pathway through which such intergenerational risk is conferred remains unknown. The current study evaluated the association between maternal ACEs and infant brain development, including an a priori focus on circuits implicated in emotional and sensory processing.

METHODS

The sample included 101 mother-infant dyads from a longitudinal study. Maternal ACEs were assessed with the Adverse Childhood Questionnaire dichotomized into low (0 or 1) and high (≥2) groups. White matter microstructure, as indexed by fractional anisotropy (FA), was assessed using structural magnetic resonance imaging in infants (41.6-46.0 weeks' postconceptional age) within a priori tracts (the cingulum, fornix, uncinate, inferior frontal occipital fasciculus, and inferior longitudinal fasciculus). Exploratory analyses were also conducted across the whole brain.

RESULTS

High maternal ACEs (≥2) were associated with decreased infant left inferior longitudinal fasciculus (ILF) FA (F(1,94) = 7.78, p < .006) relative to infants of low ACE mothers. No group difference was observed within the right ILF following correction for multiple comparisons (F(1,95) = 4.29, p < .041). Follow-up analyses within the left ILF demonstrated associations between high maternal ACEs and increased left radial diffusivity (F(1,95) = 5.10, p < .006). Exploratory analyses demonstrated preliminary support for differences in visual processing networks (e.g. optic tract) as well as additional circuits less frequently examined in the context of early life adversity exposure, (e.g. corticothalamic tract).

CONCLUSIONS

Maternal ACEs predict neural circuit development of the inferior longitudinal fasciculus. Findings suggest that early developing sensory circuits within the infant brain are susceptible to maternal adverse childhood experiences and may have implications for the maturation of higher order emotional and cognitive circuits.

Anatomically constrained tractography of the fetal brain

Diffusion-weighted Magnetic Resonance Imaging (dMRI) is increasingly used to study the fetal brain in utero. An important computation enabled by dMRI is streamline tractography, which has unique applications such as tract-specific analysis of the brain white matter and structural connectivity assessment. However, due to the low fetal dMRI data quality and the challenging nature of tractography, existing methods tend to produce highly inaccurate results. They generate many false streamlines while failing to reconstruct the streamlines that constitute the major white matter tracts. In this paper, we advocate for anatomically constrained tractography based on an accurate segmentation of the fetal brain tissue directly in the dMRI space. We develop a deep learning method to compute the segmentation automatically. Experiments on independent test data show that this method can accurately segment the fetal brain tissue and drastically improve the tractography results. It enables the reconstruction of highly curved tracts such as optic radiations. Importantly, our method infers the tissue segmentation and streamline propagation direction from a diffusion tensor fit to the dMRI data, making it applicable to routine fetal dMRI scans. The proposed method can facilitate the study of fetal brain white matter tracts with dMRI.

Towards a neurodevelopmental cognitive perspective of temporal processing

The ability to organize and memorize the unfolding of events over time is a fundamental feature of cognition, which develops concurrently with the maturation of the brain. Nonetheless, how temporal processing evolves across the lifetime as well as the links with the underlying neural substrates remains unclear. Here, we intend to retrace the main developmental stages of brain structure, function, and cognition linked to the emergence of timing abilities. This neurodevelopmental perspective aims to untangle the puzzling trajectory of temporal processing aspects across the lifetime, paving the way to novel neuropsychological assessments and cognitive rehabilitation strategies.

Spatiotemporal cerebral blood flow dynamics underlies emergence of the limbic-sensorimotor-association cortical gradient in human infancy

Infant cerebral blood flow (CBF) delivers nutrients and oxygen to fulfill brain energy consumption requirements for the fastest period of postnatal brain development across the lifespan. However, organizing principle of whole-brain CBF dynamics during infancy remains obscure. Leveraging a unique cohort of 100+ infants with high-resolution arterial spin labeled MRI, we found the emergence of the cortical hierarchy revealed by the highest-resolution infant CBF maps available to date. Infant CBF across cortical regions increased in a biphasic pattern with initial rapid and sequentially slower rate, with break-point ages increasing along the limbic-sensorimotor-association cortical gradient. Increases in CBF in sensorimotor cortices were associated with enhanced language and motor skills, and frontoparietal association cortices for cognitive skills. The study discovered emergence of the hierarchical limbic-sensorimotor-association cortical gradient in infancy, and offers standardized reference of infant brain CBF and insight into the physiological basis of cortical specialization and real-world infant developmental functioning.

Characterizing normal perinatal development of the human brain structural connectivity

Early brain development is characterized by the formation of a highly organized structural connectome, which underlies brain's cognitive abilities and influences its response to diseases and environmental factors. Hence, quantitative assessment of structural connectivity in the perinatal stage is useful for studying normal and abnormal neurodevelopment. However, estimation of the connectome from diffusion MRI data involves complex computations. For the perinatal period, these computations are further challenged by the rapid brain development, inherently low signal quality, imaging difficulties, and high inter-subject variability. These factors make it difficult to chart the normal development of the structural connectome. As a result, there is a lack of reliable normative baselines of structural connectivity metrics at this critical stage in brain development. In this study, we developed a computational method based on spatio-temporal averaging in the image space for determining such baselines. We used this method to analyze the structural connectivity between 33 and 44 postmenstrual weeks using data from 166 subjects. Our results unveiled clear and strong trends in the development of structural connectivity in the perinatal stage. We observed increases in measures of network integration and segregation, and widespread strengthening of the connections within and across brain lobes and hemispheres. We also observed asymmetry patterns that were consistent between different connection weighting approaches. Connection weighting based on fractional anisotropy and neurite density produced the most consistent results. Our proposed method also showed considerable agreement with an alternative technique based on connectome averaging. The new computational method and results of this study can be useful for assessing normal and abnormal development of the structural connectome early in life.

Functional connectivity development in the prenatal and neonatal stages measured by functional magnetic resonance imaging: A systematic review

The prenatal and neonatal periods are two of the most important developmental stages of the human brain. It is therefore crucial to understand normal brain development and how early connections are established during these periods, in order to advance the state of knowledge on altered brain development and eventually identify early brain markers of neurodevelopmental disorders and diseases. In this systematic review (Prospero ID: CRD42024511365), we compiled resting state functional magnetic resonance imaging (fMRI) studies in healthy fetuses and neonates, in order to outline the main characteristics of typical development of the functional brain connectivity during the prenatal and neonatal periods. A systematic search of five databases identified a total of 12 573 articles. Of those, 28 articles met pre-established selection criteria based determined by the authors after surveying and compiling the major limitations reported within the literature. Inclusion criteria were: (1) resting state studies; (2) presentation of original results; (3) use of fMRI with minimum one Tesla; (4) a population ranging from 20 weeks of GA to term birth (around 37-42 weeks of PMA); (5) singleton pregnancy with normal development (absence of any complications known to alter brain development). Exclusion criteria were: (1) preterm studies; (2) post-mortem studies; (3) clinical or pathological studies; (4) twin studies; (5) papers with a sole focus on methodology (i.e. focused on tool and analysis development); (6) volumetric studies; (7) activation map studies; (8) cortical analysis studies; (9) conference papers. A risk of bias assessment was also done to evaluate each article's methodological rigor. 1877 participants were included across all the reviewed articles. Results consistently revealed a developmental gradient of increasing functional brain connectivity from posterior to anterior regions and from proximal-to-distal regions. A decrease in local small-world organization shortly after birth was also observed; small-world characteristics were present in fetuses and newborns, but appeared weaker in the latter group. Also, the posterior-to-anterior gradient could be associated with earlier development of the sensorimotor networks in the posterior regions while more complex higher-order networks (e.g. attention-related) mature later in the anterior regions. The main limitations of this systematic review stem from the inherent limitations of functional imaging in fetuses, mainly: unevenly distributed populations and limited sample sizes; fetal movements in the womb and other imaging obstacles; and a large voxel resolution when imaging a small brain. Another limitation specific to this review is the relatively small number of included articles compared to very a large search result, which may have led to relevant articles having been overlooked.

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.

High-resolution myelin-water fraction and quantitative relaxation mapping using 3D ViSTa-MR fingerprinting

PURPOSE

This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and proton-density (PD), all within a clinically feasible scan time.

METHODS

We developed 3D visualization of short transverse relaxation time component (ViSTa)-MRF, which combined ViSTa technique with MR fingerprinting (MRF), to achieve high-fidelity whole-brain MWF and T1/T2/PD mapping on a clinical 3T scanner. To achieve fast acquisition and memory-efficient reconstruction, the ViSTa-MRF sequence leverages an optimized 3D tiny-golden-angle-shuffling spiral-projection acquisition and joint spatial-temporal subspace reconstruction with optimized preconditioning algorithm. With the proposed ViSTa-MRF approach, high-fidelity direct MWF mapping was achieved without a need for multicompartment fitting that could introduce bias and/or noise from additional assumptions or priors.

RESULTS

The in vivo results demonstrate the effectiveness of the proposed acquisition and reconstruction framework to provide fast multi-parametric mapping with high SNR and good quality. The in vivo results of 1 mm- and 0.66 mm-isotropic resolution datasets indicate that the MWF values measured by the proposed method are consistent with standard ViSTa results that are 30× slower with lower SNR. Furthermore, we applied the proposed method to enable 5-min whole-brain 1 mm-iso assessment of MWF and T1/T2/PD mappings for infant brain development and for post-mortem brain samples.

CONCLUSIONS

In this work, we have developed a 3D ViSTa-MRF technique that enables the acquisition of whole-brain MWF, quantitative T1, T2, and PD maps at 1 and 0.66 mm isotropic resolution in 5 and 15 min, respectively. This advancement allows for quantitative investigations of myelination changes in the brain.

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.

Diffusion-tensor-imaging 1-year-old and 2-year-old infant brain atlases with comprehensive gray and white matter labels

Human infancy is marked by fastest postnatal brain structural changes. It also coincides with the onset of many neurodevelopmental disorders. Atlas-based automated structure labeling has been widely used for analyzing various neuroimaging data. However, the relatively large and nonlinear neuroanatomical differences between infant and adult brains can lead to significant offsets of the labeled structures in infant brains when adult brain atlas is used. Age-specific 1- and 2-year-old brain atlases covering all major gray and white matter (GM and WM) structures with diffusion tensor imaging (DTI) and structural MRI are critical for precision medicine for infant population yet have not been established. In this study, high-quality DTI and structural MRI data were obtained from 50 healthy children to build up three-dimensional age-specific 1- and 2-year-old brain templates and atlases. Age-specific templates include a single-subject template as well as two population-averaged templates from linear and nonlinear transformation, respectively. Each age-specific atlas consists of 124 comprehensively labeled major GM and WM structures, including 52 cerebral cortical, 10 deep GM, 40 WM, and 22 brainstem and cerebellar structures. When combined with appropriate registration methods, the established atlases can be used for highly accurate automatic labeling of any given infant brain MRI. We demonstrated that one can automatically and effectively delineate deep WM microstructural development from 3 to 38 months by using these age-specific atlases. These established 1- and 2-year-old infant brain DTI atlases can advance our understanding of typical brain development and serve as clinical anatomical references for brain disorders during infancy.

A diffusion tensor imaging comparison of white matter development in nonsyndromic craniosynostosis to neurotypical infants

PURPOSE

Nonsyndromic craniosynostosis (NSC) is associated with neurocognitive deficits, and intervention at infancy is standard of care to limit the negative effects of NSC on brain development. In this study, diffusion tensor imaging (DTI) was implemented to investigate white matter microstructure in infants with NSC undergoing cranial vault remodeling, and a comparison was made with white matter development in neurotypical controls.

METHODS

Infants presenting with NSC (n = 12) underwent DTI scans before and after cranial vault remodeling. Neurotypical infants (n = 5), age matched to NSC patients at preoperative scans, were compared to preoperative DTI scans. Pre- and postoperative NSC scans were compared in aggregate, and the sagittal synostosis (n = 8) patients were evaluated separately. Finally, neurotypical infants from the University of North Carolina/University of New Mexico Baby Connectome Project (BCP), who underwent DTI scans at timepoints matching the NSC pre- and postoperative DTI scans, were analyzed (n = 9). Trends over the same time period were compared between NSC and BCP scans.

RESULTS

No significant differences were found between preoperative NSC scans and controls. White matter development was more limited in NSC patients than in BCP patients, with microstructural parameters of the corpus body and genu and inferior and superior longitudinal fasciculi consistently lagging behind developmental changes observed in healthy patients.

CONCLUSION

Infant white matter development appears more limited in NSC patients undergoing cranial vault remodeling relative to that in neurotypical controls. Further investigation is needed to explore these differences and the specific effects of early surgical intervention.

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.

Shared Genetic Determinants of Schizophrenia and Autism Spectrum Disorder Implicate Opposite Risk Patterns: A Genome-Wide Analysis of Common Variants

BACKGROUND AND HYPOTHESIS

The synaptic pruning hypothesis posits that schizophrenia (SCZ) and autism spectrum disorder (ASD) may represent opposite ends of neurodevelopmental disorders: individuals with ASD exhibit an overabundance of synapses and connections while SCZ was characterized by excessive pruning of synapses and a reduction. Given the strong genetic predisposition of both disorders, we propose a shared genetic component, with certain loci having differential regulatory impacts.

STUDY DESIGN

Genome-Wide single nucleotide polymorphism (SNP) data of European descent from SCZ (N cases = 53 386, N controls = 77 258) and ASD (N cases = 18 381, N controls = 27 969) were analyzed. We used genetic correlation, bivariate causal mixture model, conditional false discovery rate method, colocalization, Transcriptome-Wide Association Study (TWAS), and Phenome-Wide Association Study (PheWAS) to investigate the genetic overlap and gene expression pattern.

STUDY RESULTS

We found a positive genetic correlation between SCZ and ASD (rg = .26, SE = 0.01, P = 7.87e-14), with 11 genomic loci jointly influencing both conditions (conjFDR <0.05). Functional analysis highlights a significant enrichment of shared genes during early to mid-fetal developmental stages. A notable genetic region on chromosome 17q21.31 (lead SNP rs2696609) showed strong evidence of colocalization (PP.H4.abf = 0.85). This SNP rs2696609 is linked to many imaging-derived brain phenotypes. TWAS indicated opposing gene expression patterns (primarily pseudogenes and long noncoding RNAs [lncRNAs]) for ASD and SCZ in the 17q21.31 region and some genes (LRRC37A4P, LINC02210, and DND1P1) exhibit considerable variation in the cerebellum across the lifespan.

CONCLUSIONS

Our findings support a shared genetic basis for SCZ and ASD. A common genetic variant, rs2696609, located in the Chr17q21.31 locus, may exert differential risk regulation on SCZ and ASD by altering brain structure. Future studies should focus on the role of pseudogenes, lncRNAs, and cerebellum in synaptic pruning and neurodevelopmental disorders.

Spatiotemporal cerebral blood flow dynamics underlies emergence of the limbic-sensorimotor-association cortical gradient in human infancy

Infant cerebral blood flow (CBF) delivers nutrients and oxygen to fulfill brain energy consumption requirements for the fastest period of postnatal brain development across lifespan. However, organizing principle of whole-brain CBF dynamics during infancy remains obscure. Leveraging a unique cohort of 100+ infants with high-resolution arterial spin labeled MRI, we found the emergence of the cortical hierarchy revealed by highest-resolution infant CBF maps available to date. Infant CBF across cortical regions increased in a biphasic pattern with initial rapid and sequentially slower rate, with break-point ages increasing along the limbic-sensorimotor-association cortical gradient. Increases in CBF in sensorimotor cortices were associated with enhanced language and motor skills, and frontoparietal association cortices for cognitive skills. The study discovered emergence of the hierarchical limbic-sensorimotor-association cortical gradient in infancy, and offers standardized reference of infant brain CBF and insight into the physiological basis of cortical specialization and real-world infant developmental functioning.

Cortical growth from infancy to adolescence in preterm and term-born children

Early life experiences can exert a significant influence on cortical and cognitive development. Very preterm birth exposes infants to several adverse environmental factors during hospital admission, which affect cortical architecture. However, the subsequent consequence of very preterm birth on cortical growth from infancy to adolescence has never been defined; despite knowledge of critical periods during childhood for establishment of cortical networks. Our aims were to: chart typical longitudinal cortical development and sex differences in cortical development from birth to adolescence in healthy term-born children; estimate differences in cortical development between children born at term and very preterm; and estimate differences in cortical development between children with normal and impaired cognition in adolescence. This longitudinal cohort study included children born at term (≥37 weeks' gestation) and very preterm (<30 weeks' gestation) with MRI scans at ages 0, 7 and 13 years (n = 66 term-born participants comprising 34 with one scan, 18 with two scans and 14 with three scans; n = 201 very preterm participants comprising 56 with one scan, 88 with two scans and 57 with three scans). Cognitive assessments were performed at age 13 years. Cortical surface reconstruction and parcellation were performed with state-of-the-art, equivalent MRI analysis pipelines for all time points, resulting in longitudinal cortical volume, surface area and thickness measurements for 62 cortical regions. Developmental trajectories for each region were modelled in term-born children, contrasted between children born at term and very preterm, and contrasted between all children with normal and impaired cognition. In typically developing term-born children, we documented anticipated patterns of rapidly increasing cortical volume, area and thickness in early childhood, followed by more subtle changes in later childhood, with smaller cortical size in females than males. In contrast, children born very preterm exhibited increasingly reduced cortical volumes, relative to term-born children, particularly during ages 0-7 years in temporal cortical regions. This reduction in cortical volume in children born very preterm was largely driven by increasingly reduced cortical thickness rather than area. This resulted in amplified cortical volume and thickness reductions by age 13 years in individuals born very preterm. Alterations in cortical thickness development were found in children with impaired language and memory. This study shows that the neurobiological impact of very preterm birth on cortical growth is amplified from infancy to adolescence. These data further inform the long-lasting impact on cortical development from very preterm birth, providing broader insights into neurodevelopmental consequences of early life experiences.

Diffusion-Weighted MRI of the Fetal Brain in Fetal Growth Restriction With Maternal Preeclampsia or Gestational Hypertension

BACKGROUND

The fetal neurodevelopmental microstructural alterations of intrauterine exposure to preeclampsia (PE) or gestational hypertension (GH) remain unknown.

PURPOSE

To evaluate the differences in diffusion-weighted imaging (DWI) of the fetal brain between normotensive pregnancies and PE/GH pregnancies, with a focus on PE/GH pregnancies with fetal growth restriction (FGR).

STUDY TYPE

Retrospective matched case-control study.

POPULATION

40 singleton pregnancies with PE/GH complicated by FGR, and 3 paired control groups (PE/GH without FGR, normotensive FGR, normotensive pregnancies) (28-38 gestational weeks).

FIELD STRENGTH/SEQUENCE

DWI with single-shot echo-planar imaging at 1.5 Tesla.

ASSESSMENT

The apparent diffusion coefficient (ADC) values were calculated in the centrum semi-ovale (CSO), parietal white matter (PWM), frontal white matter (FWM), occipital white matter (OWM), temporal white matter (TWM), basal ganglia, thalamus (THAL), pons, and cerebellar hemisphere.

STATISTICAL TESTS

Student t test or Wilcoxon matched test was used to reveal the difference of ADC values among the investigated brain regions. A correlation between gestational age (GA) and ADC values was determined by linear regression analysis.

RESULTS

Compared with fetuses in PE/GH without FGR and those with normotensive pregnancies, fetuses in the PE/GH with FGR group had significantly lower average ADC measurements of supratentorial regions (1.65 ± 0.09 vs. 1.71 ± 0.10 10-3  mm2 /sec; vs. 1.73 ± 0.11 10-3  mm2 /sec, respectively). Regions of significantly decreased ADC values in the fetal brain included CSO, FWM, PWM, OWM, TWM and THAL in cases of PE/GH with FGR. ADC values from supratentorial regions in PE/GH pregnancies were not significantly correlated with GA (P = 0.12, 0.26); however, this trend was statistically significant in the normotensive groups.

DATA CONCLUSION

ADC values may indicate fetal brain developmental alterations in PE/GH with FGR fetuses but more microscopic and morphological studies are necessary to provide additional evidence to offer a different interpretation of this trend in fetal brain.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY STAGE: 3.

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 developmental trajectory of 1H-MRS brain metabolites from childhood to adulthood

Human brain development is ongoing throughout childhood, with for example, myelination of nerve fibers and refinement of synaptic connections continuing until early adulthood. 1H-Magnetic Resonance Spectroscopy (1H-MRS) can be used to quantify the concentrations of endogenous metabolites (e.g. glutamate and γ -aminobutyric acid (GABA)) in the human brain in vivo and so can provide valuable, tractable insight into the biochemical processes that support postnatal neurodevelopment. This can feasibly provide new insight into and aid the management of neurodevelopmental disorders by providing chemical markers of atypical development. This study aims to characterize the normative developmental trajectory of various brain metabolites, as measured by 1H-MRS from a midline posterior parietal voxel. We find significant non-linear trajectories for GABA+ (GABA plus macromolecules), Glx (glutamate + glutamine), total choline (tCho) and total creatine (tCr) concentrations. Glx and GABA+ concentrations steeply decrease across childhood, with more stable trajectories across early adulthood. tCr and tCho concentrations increase from childhood to early adulthood. Total N-acetyl aspartate (tNAA) and Myo-Inositol (mI) concentrations are relatively stable across development. Trajectories likely reflect fundamental neurodevelopmental processes (including local circuit refinement) which occur from childhood to early adulthood and can be associated with cognitive development; we find GABA+ concentrations significantly positively correlate with recognition memory scores.

Development of sensorimotor-visual connectome gradient at birth predicts neurocognitive outcomes at 2 years of age

Functional connectome gradients represent fundamental organizing principles of the brain. Here, we report the development of the connectome gradients in preterm and term babies aged 31-42 postmenstrual weeks using task-free functional MRI and its association with postnatal cognitive growth. We show that the principal sensorimotor-to-visual gradient is present during the late preterm period and continuously evolves toward a term-like pattern. The global measurements of this gradient, characterized by explanation ratio, gradient range, and gradient variation, increased with age (p < 0.05, corrected). Focal gradient development mainly occurs in the sensorimotor, lateral, and medial parietal regions, and visual regions (p < 0.05, corrected). The connectome gradient at birth predicts cognitive and language outcomes at 2-year follow-up (p < 0.005). These results are replicated using an independent dataset from the Developing Human Connectome Project. Our findings highlight early emergent rules of the brain connectome gradient and their implications for later cognitive growth.

Reproducibility of Diffusion MRI-Based Tractography in the Fetal Brain

BACKGROUND

Tractography based on diffusion MRI (dMRI) is a useful tool to study white matter of the developing brain. However, its application in fetal brains is limited due to motion artifacts and low resolution of in utero dMRI, leading to reduced reliability, which was scarcely investigated in previous studies.

PURPOSE

To identify reliably traceable fibers in fetal brains and assess whether reproducibility varies with gestational age (GA) and varies between brain regions.

STUDY TYPE

Prospective cohort study.

SUBJECTS

A total of 44 healthy fetuses with GAs between 25 and 37 (31 ± 6).

FIELD STRENGTH/SEQUENCE

3-T, diffusion-weighted echo-planar imaging sequence (2-5 repeated dMRI scans within the same session per subject).

ASSESSMENT

We fitted dMRI with constrained spherical deconvolution model and conducted tractography on eight fibers. We extracted volume, fractional anisotropy, and fiber count for each fiber and assessed the reproducibility of these metrics between repeated scans within each subject. Data were divided into two age-based subgroups (≤30 weeks, N = 28, and >30 weeks, N = 16) for further tests.

STATISTICAL TESTS

The reproducibility were compared between fibers by analysis of variance and two-sample t tests. Multiple comparisons were corrected by the false discovery rate (5% was accepted).

RESULTS

The reproducibility of the anterior thalamic radiation, inferior longitudinal fasciculus (ILF), genu of the corpus callosum (GCC), and body of the corpus callosum (BCC) significantly decreased with advancing GA (correlation coefficient = 0.525-0.823), as confirmed by group comparisons between fetuses in early GA (≤30 weeks) and late GA (>30 weeks) groups. Corticospinal tract, inferior fronto-occipital fasciculus, and GCC showed high reproducibility for fiber count (weighted dice average = 0.846 vs. 0.814), while BCC and ILF exhibited the lowest reproducibility in both age groups.

DATA CONCLUSION

The study indicates that the reliability of fetal brain tractography depends on GA and varies among different fibers.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

White matter microstructure of children with sensory over-responsivity is associated with affective behavior

BACKGROUND

Sensory processing dysfunction (SPD) is linked to altered white matter (WM) microstructure in school-age children. Sensory over-responsivity (SOR), a form of SPD, affects at least 2.5% of all children and has substantial deleterious impact on learning and mental health. However, SOR has not been well studied using microstructural imaging such as diffusion MRI (dMRI). Since SOR involves hypersensitivity to external stimuli, we test the hypothesis that children with SOR require compensatory neuroplasticity in the form of superior WM microstructural integrity to protect against internalizing behavior, leaving those with impaired WM microstructure vulnerable to somatization and depression.

METHODS

Children ages 8-12 years old with neurodevelopmental concerns were assessed for SOR using a comprehensive structured clinical evaluation, the Sensory Processing 3 Dimensions Assessment, and underwent 3 Tesla MRI with multishell multiband dMRI. Tract-based spatial statistics was used to measure diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics from global WM and nineteen selected WM tracts. Correlations of DTI and NODDI measures with measures of somatization and emotional disturbance from the Behavioral Assessment System for Children, 3rd edition (BASC-3), were computed in the SOR group and in matched children with neurodevelopmental concerns but not SOR.

RESULTS

Global WM fractional anisotropy (FA) is negatively correlated with somatization and with emotional disturbance in the SOR group but not the non-SOR group. Also observed in children with SOR are positive correlations of radial diffusivity (RD) and free water fraction (FISO) with somatization and, in most cases, emotional disturbance. These effects are significant in boys with SOR, whereas the study is underpowered for girls. The most affected white matter are medial lemniscus and internal capsule sensory tracts, although effects of SOR are observed in many cerebral, cerebellar, and brainstem tracts.

CONCLUSION

White matter microstructure is related to affective behavior in children with SOR.

Arachidonic and docosahexaenoic acid supplementation and brain maturation in preterm infants; a double blind RCT

BACKGROUND

Arachidonic acid (ARA) and docosahexaenoic acid (DHA) are important structural components of neural cellular membranes and possess anti-inflammatory properties. Very preterm infants are deprived of the enhanced placental supply of these fatty acids, but the benefit of postnatal supplementation on brain development is uncertain. The aim of this study was to test the hypothesis that early enteral supplementation with ARA and DHA in preterm infants improves white matter (WM) microstructure assessed by diffusion-weighted MRI at term equivalent age.

METHODS

In this double-blind, randomized controlled trial, infants born before 29 weeks gestational age were allocated to either 100 mg/kg ARA and 50 mg/kg DHA (ARA:DHA group) or medium chain triglycerides (control). Supplements were started on the second day of life and provided until 36 weeks postmenstrual age. The primary outcome was brain maturation assessed by diffusion tensor imaging (DTI) using Tract-Based Spatial Statistics (TBSS) analysis.

RESULTS

We included 120 infants (60 per group) in the trial; mean (range) gestational age was 26+3 (22+6 - 28+6) weeks and postmenstrual age at scan was 41+3 (39+1 - 47+0) weeks. Ninety-two infants underwent MRI imaging, and of these, 90 had successful T1/T2 weighted MR images and 74 had DTI data of acceptable quality. TBSS did not show significant differences in mean or axial diffusivity between the groups, but demonstrated significantly higher fractional anisotropy in several large WM tracts in the ARA:DHA group, including corpus callosum, the anterior and posterior limb of the internal capsula, inferior occipitofrontal fasciculus, uncinate fasciculus, and the inferior longitudinal fasciculus. Radial diffusivity was also significantly lower in several of the same WM tracts in the ARA:DHA group.

CONCLUSION

This study suggests that supplementation with ARA and DHA at doses matching estimated fetal accretion rates improves WM maturation compared to control treatment, but further studies are needed to ascertain any functional benefit.

CLINICAL TRIAL REGISTRATION

www.

CLINICALTRIALS

gov; ID:NCT03555019.

High-resolution myelin-water fraction and quantitative relaxation mapping using 3D ViSTa-MR fingerprinting

Purpose

This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and proton-density (PD), all within a clinically feasible scan time.

Methods

We developed 3D ViSTa-MRF, which combined Visualization of Short Transverse relaxation time component (ViSTa) technique with MR Fingerprinting (MRF), to achieve high-fidelity whole-brain MWF and T1/T2/PD mapping on a clinical 3T scanner. To achieve fast acquisition and memory-efficient reconstruction, the ViSTa-MRF sequence leverages an optimized 3D tiny-golden-angle-shuffling spiral-projection acquisition and joint spatial-temporal subspace reconstruction with optimized preconditioning algorithm. With the proposed ViSTa-MRF approach, high-fidelity direct MWF mapping was achieved without a need for multi-compartment fitting that could introduce bias and/or noise from additional assumptions or priors.

Results

The in-vivo results demonstrate the effectiveness of the proposed acquisition and reconstruction framework to provide fast multi-parametric mapping with high SNR and good quality. The in-vivo results of 1mm- and 0.66mm-iso datasets indicate that the MWF values measured by the proposed method are consistent with standard ViSTa results that are 30x slower with lower SNR. Furthermore, we applied the proposed method to enable 5-minute whole-brain 1mm-iso assessment of MWF and T1/T2/PD mappings for infant brain development and for post-mortem brain samples.

Conclusions

In this work, we have developed a 3D ViSTa-MRF technique that enables the acquisition of whole-brain MWF, quantitative T1, T2, and PD maps at 1mm and 0.66mm isotropic resolution in 5 and 15 minutes, respectively. This advancement allows for quantitative investigations of myelination changes in the brain.

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.

Traveling Subject-Informed Harmonization Increases Reliability of Brain Diffusion Tensor and Neurite Mapping

Diffusion-weighted magnetic resonance imaging (dMRI) of brain has helped elucidate the microstructural changes of psychiatric and neurodegenerative disorders. Inconsistency between MRI models has hampered clinical application of dMRI-based metrics. Using harmonized dMRI data of 300 scans from 69 traveling subjects (TS) scanning the same individuals at multiple conditions with 13 MRI models and 2 protocols, the widely-used metrics such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) were evaluated before and after harmonization with a combined association test (ComBat) or TS-based general linear model (TS-GLM). Results showed that both ComBat and TS-GLM significantly reduced the effects of the MRI site, model, and protocol for diffusion metrics while maintaining the intersubject biological effects. The harmonization power of TS-GLM based on TS data model is more powerful than that of ComBat. In conclusion, our research demonstrated that although ComBat and TS-GLM harmonization approaches were effective at reducing the scanner effects of the site, model, and protocol for DTI and NODDI metrics in WM, they exhibited high retainability of biological effects. Therefore, we suggest that, after harmonizing DTI and NODDI metrics, a multisite study with large cohorts can accurately detect small pathological changes by retaining pathological effects.

Automated motion artifact detection in early pediatric diffusion MRI using a convolutional neural network

Diffusion MRI (dMRI) is a widely used method to investigate the microstructure of the brain. Quality control (QC) of dMRI data is an important processing step that is performed prior to analysis using models such as diffusion tensor imaging (DTI) or neurite orientation dispersion and density imaging (NODDI). When processing dMRI data from infants and young children, where intra-scan motion is common, the identification and removal of motion artifacts is of the utmost importance. Manual QC of dMRI data is (1) time-consuming due to the large number of diffusion directions, (2) expensive, and (3) prone to subjective errors and observer variability. Prior techniques for automated dMRI QC have mostly been limited to adults or school-age children. Here, we propose a deep learning-based motion artifact detection tool for dMRI data acquired from infants and toddlers. The proposed framework uses a simple three-dimensional convolutional neural network (3DCNN) trained and tested on an early pediatric dataset of 2,276 dMRI volumes from 121 exams acquired at 1 month and 24 months of age. An average classification accuracy of 95% was achieved following four-fold cross-validation. A second dataset with different acquisition parameters and ages ranging from 2-36 months (consisting of 2,349 dMRI volumes from 26 exams) was used to test network generalizability, achieving 98% classification accuracy. Finally, to demonstrate the importance of motion artifact volume removal in a dMRI processing pipeline, the dMRI data were fit to the DTI and NODDI models and the parameter maps were compared with and without motion artifact removal.

[Stress during prenatal and early postnatal period when everything begins]

Early severe stresses are known to affect the biological and psychological development in childhood. Good and adaptable stress during prenatal and early postnatal period can switch to traumatic during these highly susceptible developmental stages. These different stresses modulate genetic/epigenetic processes and the setting up of connectome during these highly plastic and adaptable time periods. The polyvagal processes control the base of the security/well-being perception of the newborn by the onset of synchronized interactions between the mother/parent/nurse and the baby. These positive adjustments in mirror lead to attachment and social links and to implicit learning processes leading to a balanced emotional and cognitive development.

Longitudinal developmental trajectories of functional connectivity reveal regional distribution of distinct age effects in infancy

Prior work has shown that different functional brain networks exhibit different maturation rates, but little is known about whether and how different brain areas may differ in the exact shape of longitudinal functional connectivity growth trajectories during infancy. We used resting-state functional magnetic resonance imaging (fMRI) during natural sleep to characterize developmental trajectories of different regions using a longitudinal cohort of infants at 3 weeks (neonate), 1 year, and 2 years of age (n = 90; all with usable data at three time points). A novel whole brain heatmap analysis was performed with four mixed-effect models to determine the best fit of age-related changes for each functional connection: (i) growth effects: positive-linear-age, (ii) emergent effects: positive-log-age, (iii) pruning effects: negative-quadratic-age, and (iv) transient effects: positive-quadratic-age. Our results revealed that emergent (logarithmic) effects dominated developmental trajectory patterns, but significant pruning and transient effects were also observed, particularly in connections centered on inferior frontal and anterior cingulate areas that support social learning and conflict monitoring. Overall, unique global distribution patterns were observed for each growth model indicating that developmental trajectories for different connections are heterogeneous. All models showed significant effects concentrated in association areas, highlighting the dominance of higher-order social/cognitive development during the first 2 years of life.

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.

Geodesic theory of long association fibers arrangement in the human fetal cortex

Association fibers connect different areas of the cerebral cortex over long distances and integrate information to achieve higher brain functions, particularly in humans. Prototyped association fibers are developed to the respective tangential direction throughout the cerebral hemispheres along the deepest border of the subplate during the fetal period. However, how guidance to remote areas is achieved is not known. Because the subplate is located below the cortical surface, the tangential direction of the fibers may be biased by the curved surface geometry due to Sylvian fissure and cortical poles. The fiber length can be minimized if the tracts follow the shortest paths (geodesics) of the curved surface. Here, we propose and examine a theory that geodesics guide the tangential direction of long association fibers by analyzing how geodesics are spatially distributed on the fetal human brains. We found that the geodesics were dense on the saddle-shaped surface of the perisylvian region and sparse on the dome-shaped cortical poles. The geodesics corresponded with the arrangement of five typical association fibers, supporting the theory. Thus, the geodesic theory provides directional guidance information for wiring remote areas and suggests that long association fibers emerge from minimizing their tangential length in fetal brains.

Characterizing normal perinatal development of the human brain structural connectivity

Early brain development is characterized by the formation of a highly organized structural connectome. The interconnected nature of this connectome underlies the brain's cognitive abilities and influences its response to diseases and environmental factors. Hence, quantitative assessment of structural connectivity in the perinatal stage is useful for studying normal and abnormal neurodevelopment. However, estimation of the connectome from diffusion MRI data involves complex computations. For the perinatal period, these computations are further challenged by the rapid brain development and imaging difficulties. Combined with high inter-subject variability, these factors make it difficult to chart the normal development of the structural connectome. As a result, there is a lack of reliable normative baselines of structural connectivity metrics at this critical stage in brain development. In this study, we developed a computational framework, based on spatio-temporal averaging, for determining such baselines. We used this framework to analyze the structural connectivity between 33 and 44 postmenstrual weeks using data from 166 subjects. Our results unveiled clear and strong trends in the development of structural connectivity in perinatal stage. Connection weighting based on fractional anisotropy and neurite density produced the most consistent results. We observed increases in global and local efficiency, a decrease in characteristic path length, and widespread strengthening of the connections within and across brain lobes and hemispheres. We also observed asymmetry patterns that were consistent between different connection weighting approaches. The new computational method and results are useful for assessing normal and abnormal development of the structural connectome early in life.

Human white matter myelinates faster in utero than ex utero

The formation of myelin, the fatty sheath that insulates nerve fibers, is critical for healthy brain function. A fundamental open question is what impact being born has on myelin growth. To address this, we evaluated a large (n = 300) cross-sectional sample of newborns from the Developing Human Connectome Project (dHCP). First, we developed software for the automated identification of 20 white matter bundles in individual newborns that is well suited for large samples. Next, we fit linear models that quantify how T1w/T2w (a myelin-sensitive imaging contrast) changes over time at each point along the bundles. We found faster growth of T1w/T2w along the lengths of all bundles before birth than right after birth. Further, in a separate longitudinal sample of preterm infants (N = 34), we found lower T1w/T2w than in full-term peers measured at the same age. By applying the linear models fit on the cross-section sample to the longitudinal sample of preterm infants, we find that their delay in T1w/T2w growth is well explained by the amount of time they spent developing in utero and ex utero. These results suggest that white matter myelinates faster in utero than ex utero. The reduced rate of myelin growth after birth, in turn, explains lower myelin content in individuals born preterm and could account for long-term cognitive, neurological, and developmental consequences of preterm birth. We hypothesize that closely matching the environment of infants born preterm to what they would have experienced in the womb may reduce delays in myelin growth and hence improve developmental outcomes.

Mechanical hierarchy in the formation and modulation of cortical folding patterns

The important mechanical parameters and their hierarchy in the growth and folding of the human brain have not been thoroughly understood. In this study, we developed a multiscale mechanical model to investigate how the interplay between initial geometrical undulations, differential tangential growth in the cortical plate, and axonal connectivity form and regulate the folding patterns of the human brain in a hierarchical order. To do so, different growth scenarios with bilayer spherical models that features initial undulations on the cortex and uniform or heterogeneous distribution of axonal fibers in the white matter were developed, statistically analyzed, and validated by the imaging observations. The results showed that the differential tangential growth is the inducer of cortical folding, and in a hierarchal order, high-amplitude initial undulations on the surface and axonal fibers in the substrate regulate the folding patterns and determine the location of gyri and sulci. The locations with dense axonal fibers after folding settle in gyri rather than sulci. The statistical results also indicated that there is a strong correlation between the location of positive (outward) and negative (inward) initial undulations and the locations of gyri and sulci after folding, respectively. In addition, the locations of 3-hinge gyral folds are strongly correlated with the initial positive undulations and locations of dense axonal fibers. As another finding, it was revealed that there is a correlation between the density of axonal fibers and local gyrification index, which has been observed in imaging studies but not yet fundamentally explained. This study is the first step in understanding the linkage between abnormal gyrification (surface morphology) and disruption in connectivity that has been observed in some brain disorders such as Autism Spectrum Disorder. Moreover, the findings of the study directly contribute to the concept of the regularity and variability of folding patterns in individual human brains.

The acute effects of repetitive transcranial magnetic stimulation on laminar diffusion anisotropy of neocortical gray matter

Repetitive transcranial magnetic stimulation (rTMS) is increasingly used to treat neuropsychiatric disorders. Inhibitory and excitatory regimens have been both adopted but the exact mechanism of action remains unclear, and investigating their differential effects on laminar diffusion profiles of neocortex may add important evidence. Twenty healthy participants were randomly assigned to receive a low-frequency/inhibitory or high-frequency/excitatory rTMS targeting the left dorsolateral prefrontal cortex (DLPFC). With the brand-new submillimeter diffusion tensor imaging of whole brain and specialized surface-based laminar analysis, fractional anisotropy (FA) and mean diffusion (MD) profiles of cortical layers at different cortical depths were characterized before/after rTMS. Inhibitory and excitatory rTMS both showed impacts on diffusion metrics of somatosensory, limbic, and sensory regions, but different patterns of changes were observed-increased FA with inhibitory rTMS, whereas decreased FA with excitatory rTMS. More importantly, laminar analysis indicated laminar specificity of changes in somatosensory regions during different rTMS patterns-inhibitory rTMS affected the superficial layers contralateral to the DLPFC, while excitatory rTMS led to changes in the intermediate/deep layers bilateral to the DLPFC. These findings provide novel insights into acute neurobiological effects on diffusion profiles of rTMS that may add critical evidence relevant to different protocols of rTMS on neocortex.

Maturation of auditory cortex neural responses during infancy and toddlerhood

The infant auditory system rapidly matures across the first years of life, with a primary goal of obtaining ever-more-accurate real-time representations of the external world. Our understanding of how left and right auditory cortex neural processes develop during infancy, however, is meager, with few studies having the statistical power to detect potential hemisphere and sex differences in primary/secondary auditory cortex maturation. Using infant magnetoencephalography (MEG) and a cross-sectional study design, left and right auditory cortex P2m responses to pure tones were examined in 114 typically developing infants and toddlers (66 males, 2 to 24 months). Non-linear maturation of P2m latency was observed, with P2m latencies decreasing rapidly as a function of age during the first year of life, followed by slower changes between 12 and 24 months. Whereas in younger infants auditory tones were encoded more slowly in the left than right hemisphere, similar left and right P2m latencies were observed by ∼21 months of age due to faster maturation rate in the left than right hemisphere. No sex differences in the maturation of the P2m responses were observed. Finally, an earlier left than right hemisphere P2m latency predicted better language performance in older infants (12 to 24 months). Findings indicate the need to consider hemisphere when examining the maturation of auditory cortex neural activity in infants and toddlers and show that the pattern of left-right hemisphere P2m maturation is associated with language performance.

ADC values as a biomarker of fetal brain maturation

BACKGROUND

During the period of fetal development, myelination plays a key role and follows specific time and spatial sequences. The water content in the brain is inversely proportional to myelination - the more myelinated the brain, the lower the water content in it. The diffusion of water molecules can be quantitatively assessed using the apparent diffusion coefficient (ADC). We were interested in whether, by determining the ADC values, we could quantitatively evaluate the development of the fetal brain.

PATIENTS AND METHODS

The study included 42 fetuses with gestational age 25 to 35 weeks. We manually selected 13 regions on diffusion-weighted images. Statistically significant differences between ADC values were checked using one-way analysis of variance and Tukey's post hoc test. The relationship between the ADC values and the gestational age of the fetuses was then assessed using linear regression.

RESULTS

The average gestational age of the fetuses was 29.8 ± 2.4 weeks. ADC values in the thalami, pons and cerebellum differed significantly among each other and from the ADC values in other brain regions. In the thalami, pons and cerebellum, linear regression showed a significant decrease in ADC values with increasing gestational age.

CONCLUSIONS

ADC values change with the increasing gestational age of the fetus and differ among different brain regions. In the pons, cerebellum and thalami, the ADC coefficient could be used as a biomarker of fetal brain maturation since ADC values decrease linearly with increasing gestational age.

Down and up! Does the mu rhythm index a gating mechanism in the developing motor system?

Developmental research on action processing in the motor cortex relies on a key neural marker - a decrease in 6-12 Hz activity (coined mu suppression). However, recent evidence points towards an increase in mu power, specific for the observation of others' actions. Complementing the findings on mu suppression, this raises the critical question for the functional role of the mu rhythm in the developing motor system. We here discuss a potential solution to this seeming controversy by suggesting a gating function of the mu rhythm: A decrease in mu power may index the facilitation, while an increase may index the inhibition of motor processes, which are critical during action observation. This account may advance our conception of action understanding in early brain development and points towards critical directions for future research.

The neurobiology of autism spectrum disorder as it relates to twice exceptionality

There is a long-standing association between exceptional cognitive abilities of various sorts and neuropsychiatric illness, but it has historically largely been investigated in an exploratory and non-systematic way. One group in which this association has been investigated with more rigor is in subjects who have been identified as twice exceptional; an educational term describing subjects who are both gifted and diagnosed with a neuropsychiatric disorder. This term covers multiple conditions, but is of specific interest in particular in the study of autism spectrum disorder. Recent findings have led to the development of a hypothesis that a certain degree of the neurobiology associated with autism might even be advantageous for individuals and could lead to high giftedness, while becoming disadvantageous, once a certain threshold is surpassed. In this model, the same neurobiological mechanisms confer an increasing advantage up to a certain threshold, but become pathological past that point. Twice-exceptional individuals would be exactly at the inflection point, being highly gifted, but also symptomatic at the same time. Here, we review how existing neuroimaging literature on autism spectrum disorder can inform research on twice exceptionality specifically. We propose to study key neural networks with a robust implication in ASD to identify the neurobiology underlying twice-exceptionality. A better understanding of the neural mechanisms of twice exceptionality should help to better understand resilience and vulnerability to neurodevelopmental disorders and to. further support affected individuals.

Normal reference values for magnetic resonance imaging measurements of the fetal internal jugular veins in middle and late pregnancy

BACKGROUND

At present, there is a lack of normal magnetic resonance imaging (MRI) morphometric reference values for fetal internal jugular veins during middle and late pregnancy.

OBJECTIVE

We used MRI to assess the morphology and cross-sectional area of the internal jugular veins of fetuses during middle and late pregnancy and to explore the clinical value of these parameters.

MATERIALS AND METHODS

The MRI images of 126 fetuses in middle and late pregnancy were retrospectively analysed to determine the optimal sequence for imaging the internal jugular veins. Morphological observation of the fetal internal jugular veins in each gestational week was carried out, lumen cross-sectional area was measured and the relationship between these data and gestational age was analysed.

RESULTS

The balanced steady-state free precession sequence was superior to other MRI sequences used for fetal imaging. The cross section of fetal internal jugular veins was predominantly circular in both the middle and late stages of pregnancy, however the prevalence of an oval cross section was significantly higher in the late gestational age group. The cross-sectional area of the lumen of the fetal internal jugular veins increased with increasing gestational age. Fetal jugular vein asymmetry was common, with the right jugular vein being dominant in the high gestational age group.

CONCLUSION

We provide normal reference values for fetal internal jugular veins measured by MRI. These values may form the basis for clinical assessment of abnormal dilation or stenosis.

A computational framework for characterizing normative development of structural brain connectivity in the perinatal stage

Quantitative assessment of the brain's structural connectivity in the perinatal stage is useful for studying normal and abnormal neurodevelopment. However, estimation of the structural connectome from diffusion MRI data involves a series of complex and ill-posed computations. For the perinatal period, this analysis is further challenged by the rapid brain development and difficulties of imaging subjects at this stage. These factors, along with high inter-subject variability, have made it difficult to chart the normative development of the structural connectome. Hence, there is a lack of baseline trends in connectivity metrics that can be used as reliable references for assessing normal and abnormal brain development at this critical stage. In this paper we propose a computational framework, based on spatio-temporal atlases, for determining such baselines. We apply the framework on data from 169 subjects between 33 and 45 postmenstrual weeks. We show that this framework can unveil clear and strong trends in the development of structural connectivity in the perinatal stage. Some of our interesting findings include that connection weighting based on neurite density produces more consistent trends and that the trends in global efficiency, local efficiency, and characteristic path length are more consistent than in other metrics.

Maturation of large-scale brain systems over the first month of life

The period immediately after birth is a critical developmental window, capturing rapid maturation of brain structure and a child's earliest experiences. Large-scale brain systems are present at delivery, but how these brain systems mature during this narrow window (i.e. first weeks of life) marked by heightened neuroplasticity remains uncharted. Using multivariate pattern classification techniques and functional connectivity magnetic resonance imaging, we detected robust differences in brain systems related to age in newborns (n = 262; R2 = 0.51). Development over the first month of life occurred brain-wide, but differed and was more pronounced in brain systems previously characterized as developing early (i.e. sensorimotor networks) than in those characterized as developing late (i.e. association networks). The cingulo-opercular network was the only exception to this organizing principle, illuminating its early role in brain development. This study represents a step towards a normative brain "growth curve" that could be used to identify atypical brain maturation in infancy.

Applications of advanced diffusion MRI in early brain development: a comprehensive review

Brain development follows a protracted developmental timeline with foundational processes of neurodevelopment occurring from the third trimester of gestation into the first decade of life. Defining structural maturational patterns of early brain development is a critical step in detecting divergent developmental trajectories associated with neurodevelopmental and psychiatric disorders that arise later in life. While considerable advancements have already been made in diffusion magnetic resonance imaging (dMRI) for pediatric research over the past three decades, the field of neurodevelopment is still in its infancy with remarkable scientific and clinical potential. This comprehensive review evaluates the application, findings, and limitations of advanced dMRI methods beyond diffusion tensor imaging, including diffusion kurtosis imaging (DKI), constrained spherical deconvolution (CSD), neurite orientation dispersion and density imaging (NODDI) and composite hindered and restricted model of diffusion (CHARMED) to quantify the rapid and dynamic changes supporting the underlying microstructural architectural foundations of the brain in early life.

Prediction of the Topography of the Corticospinal Tract on T1-Weighted MR Images Using Deep-Learning-Based Segmentation

INTRODUCTION

Tractography is an invaluable tool in the planning of tumor surgery in the vicinity of functionally eloquent areas of the brain as well as in the research of normal development or of various diseases. The aim of our study was to compare the performance of a deep-learning-based image segmentation for the prediction of the topography of white matter tracts on T1-weighted MR images to the performance of a manual segmentation.

METHODS

T1-weighted MR images of 190 healthy subjects from 6 different datasets were utilized in this study. Using deterministic diffusion tensor imaging, we first reconstructed the corticospinal tract on both sides. After training a segmentation model on 90 subjects of the PIOP2 dataset using the nnU-Net in a cloud-based environment with graphical processing unit (Google Colab), we evaluated its performance using 100 subjects from 6 different datasets.

RESULTS

Our algorithm created a segmentation model that predicted the topography of the corticospinal pathway on T1-weighted images in healthy subjects. The average dice score was 0.5479 (0.3513-0.7184) on the validation dataset.

CONCLUSIONS

Deep-learning-based segmentation could be applicable in the future to predict the location of white matter pathways in T1-weighted scans.

Designing an App for Parents and Caregivers to Promote Cognitive and Socioemotional Development and Well-being Among Children Aged 0 to 5 Years in Diverse Cultural Settings: Scientific Framework

Recent years have seen remarkable progress in our scientific understanding of early childhood social, emotional, and cognitive development, as well as our capacity to widely disseminate health information by using digital technologies. Together, these scientific and technological advances offer exciting opportunities to deliver high-quality information about early childhood development (ECD) to parents and families globally, which may ultimately lead to greater knowledge and confidence among parents and better outcomes among children (particularly in lower- and middle-income countries). With these potential benefits in mind, we set out to design, develop, implement, and evaluate a new parenting app-Thrive by Five-that will be available in 30 countries. The app will provide caregivers and families with evidence-based and culturally appropriate information about ECD, accompanied by sets of collective actions that go beyond mere tips for parenting practices. Herein, we describe this ongoing global project and discuss the components of our scientific framework for developing and prototyping the app's content. Specifically, we describe (1) 5 domains that are used to organize the content and goals of the app's information and associated practices; (2) 5 neurobiological systems that are relevant to ECD and can be behaviorally targeted to potentially influence social, emotional, and cognitive development; (3) our anthropological and cultural framework for learning about local contexts and appreciating decolonization perspectives; and (4) our approach to tailoring the app's content to local contexts, which involves collaboration with in-country partner organizations and local and international subject matter experts in ECD, education, medicine, psychology, and anthropology, among others. Finally, we provide examples of the content that was incorporated in Thrive by Five when it launched globally.

Disrupted white matter microstructure correlates with impulsivity in children and adolescents with bipolar disorder

Altered white matter (WM) microstructure likely occurs in children with bipolar disorder (BD) with impulsivity representing one of the core features. However, altered WM microstructures and their age-related trendlines in children with BD and those at high-risk of developing BD, as well as correlations of WM microstructures with impulsivity, have been poorly investigated. In this study, diffusion MRI, cognitive, and impulsivity assessments were obtained from children/adolescents diagnosed with BD, offspring of individuals with BD (high-risk BD) and age-matched healthy controls. A novel atlas-based WM skeleton measurement approach was used to quantify WM microstructural integrity with all diffusion-tensor-imaging (DTI) metrics including fractional anisotropy, axial, mean and radial diffusivity to survey entire WM tracts and ameliorate partial volume effects. Among all DTI-derived metric measures, radial diffusivity quantifying WM myelination was found significantly higher primarily in corpus callosum and in the corona radiata in children with BD compared to controls. Distinguished from age-related progressively decreasing diffusivities and increasing fractional anisotropy in healthy controls, flattened age-related trendlines were found in BD group, and intermediate developmental rates were observed in high-risk group. Larger radial diffusivity in the corpus callosum and corona radiata significantly correlated with shorter response times to affective words that indicate higher impulsivity in the BD group, whereas no such correlation was found in the healthy control group. This work corroborates the progressive nature of pediatric BD and suggests that WM microstructural disruption involved in affective regulation and sensitive to impulsivity may serve as a biomarker of pediatric BD progression.

Infant brain regional cerebral blood flow increases supporting emergence of the default-mode network

Human infancy is characterized by most rapid regional cerebral blood flow (rCBF) increases across lifespan and emergence of a fundamental brain system default-mode network (DMN). However, how infant rCBF changes spatiotemporally across the brain and how the rCBF increase supports emergence of functional networks such as DMN remains unknown. Here, by acquiring cutting-edge multi-modal MRI including pseudo-continuous arterial-spin-labeled perfusion MRI and resting-state functional MRI of 48 infants cross-sectionally, we elucidated unprecedented 4D spatiotemporal infant rCBF framework and region-specific physiology-function coupling across infancy. We found that faster rCBF increases in the DMN than visual and sensorimotor networks. We also found strongly coupled increases of rCBF and network strength specifically in the DMN, suggesting faster local blood flow increase to meet extraneuronal metabolic demands in the DMN maturation. These results offer insights into the physiological mechanism of brain functional network emergence and have important implications in altered network maturation in brain disorders.

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

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