Initiating PeriCBD to probe perinatal influences on neurodevelopment during 3-10 years in China.

Adverse perinatal factors can interfere with the normal development of the brain, potentially resulting in long-term effects on the comprehensive development of children. Presently, the understanding of cognitive and neurodevelopmental processes under conditions of adverse perinatal factors is substantially limited. There is a critical need for an open resource that integrates various perinatal factors with the development of the brain and mental health to facilitate a deeper understanding of these developmental trajectories. In this Data Descriptor, we introduce a multicenter database containing information on perinatal factors that can potentially influence children's brain-mind development, namely, periCBD, that combines neuroimaging and behavioural phenotypes with perinatal factors at county/region/central district hospitals. PeriCBD was designed to establish a platform for the investigation of individual differences in brain-mind development associated with perinatal factors among children aged 3-10 years. Ultimately, our goal is to help understand how different adverse perinatal factors specifically impact cognitive development and neurodevelopment. Herein, we provide a systematic overview of the data acquisition/cleaning/quality control/sharing, processes of periCBD.

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.

Maternal immunoglobulin G affects brain development of mouse offspring.

Maternal immunoglobulin (Ig)G is present in breast milk and has been shown to contribute to the development of the immune system in infants. In contrast, maternal IgG has no known effect on early childhood brain development. We found maternal IgG immunoreactivity in microglia, which are resident macrophages of the central nervous system of the pup brain, peaking at postnatal one week. Strong IgG immunoreactivity was observed in microglia in the corpus callosum and cerebellar white matter. IgG stimulation of primary cultured microglia activated the type I interferon feedback loop by Syk. Analysis of neonatal Fc receptor knockout (FcRn KO) mice that could not take up IgG from their mothers revealed abnormalities in the proliferation and/or survival of microglia, oligodendrocytes, and some types of interneurons. Moreover, FcRn KO mice also exhibited abnormalities in social behavior and lower locomotor activity in their home cages. Thus, changes in the mother-derived IgG levels affect brain development in offsprings.

Hydroxylated polychlorinated biphenyls may affect the thyroid hormone-induced brain development during metamorphosis of Xenopus laevis by disturbing the expression of matrix metalloproteinases.

BACKGROUND: Thyroid hormones are primarily responsible for the brain development in perinatal mammals. However, this process can be inhibited by external factors such as environmental chemicals. Perinatal mammals are viviparous, which makes direct fetal examination difficult. METHODS: We used metamorphic amphibians, which exhibit many similarities to perinatal mammals, as an experimental system. Therefore, using metamorphic amphibians, we characterized the gene expression of matrix metalloproteinases, which play an important role in brain development. RESULTS: The expression of many matrix metalloproteinases (mmps) was characteristically induced during metamorphosis. We also found that the expression of many mmps was induced by T3 and markedly inhibited by hydroxylated polychlorinated biphenyls (PCBs). CONCLUSION: Overall, our findings suggest that hydroxylated PCBs disrupt normal brain development by disturbing the gene expression of mmps.

Disproportionate neuroanatomical effects of DCC haploinsufficiency in adolescence compared with adulthood: links to dopamine, connectivity, covariance, and gene expression brain maps in mice.

BACKGROUND: Critical adolescent neural refinement is controlled by the DCC (deleted in colorectal cancer) protein, a receptor for the netrin-1 guidance cue. We sought to describe the effects of reduced DCC on neuroanatomy in the adolescent and adult mouse brain. METHODS: We examined neuronal connectivity, structural covariance, and molecular processes in a DCC-haploinsufficient mouse model, compared with wild-type mice, using new, custom analytical tools designed to leverage publicly available databases from the Allen Institute. RESULTS: We included 11 DCC-haploinsufficient mice and 16 wild-type littermates. Neuroanatomical effects of DCC haploinsufficiency were more severe in adolescence than adulthood and were largely restricted to the mesocorticolimbic dopamine system. The latter finding was consistent whether we identified the regions of the mesocorticolimbic dopamine system a priori or used connectivity data from the Allen Brain Atlas to determine de novo where these dopamine axons terminated. Covariance analyses found that DCC haploinsufficiency disrupted the coordinated development of the brain regions that make up the mesocorticolimbic dopamine system. Gene expression maps pointed to molecular processes involving the expression of DCC, UNC5C (encoding DCC's co-receptor), and NTN1 (encoding its ligand, netrin-1) as underlying our structural findings. LIMITATIONS: Our study involved a single sex (males) at only 2 ages. CONCLUSION: The neuroanatomical phenotype of DCC haploinsufficiency described in mice parallels that observed in DCC-haploinsufficient humans. It is critical to understand the DCC-haploinsufficient mouse as a clinically relevant model system.

Mapping brain function in adults and young children during naturalistic viewing with high-density diffuse optical tomography.

Human studies of early brain development have been limited by extant neuroimaging methods. MRI scanners present logistical challenges for imaging young children, while alternative modalities like functional near-infrared spectroscopy have traditionally been limited by image quality due to sparse sampling. In addition, conventional tasks for brain mapping elicit low task engagement, high head motion, and considerable participant attrition in pediatric populations. As a result, typical and atypical developmental trajectories of processes such as language acquisition remain understudied during sensitive periods over the first years of life. We evaluate high-density diffuse optical tomography (HD-DOT) imaging combined with movie stimuli for high resolution optical neuroimaging in awake children ranging from 1 to 7 years of age. We built an HD-DOT system with design features geared towards enhancing both image quality and child comfort. Furthermore, we characterized a library of animated movie clips as a stimulus set for brain mapping and we optimized associated data analysis pipelines. Together, these tools could map cortical responses to movies and contained features such as speech in both adults and awake young children. This study lays the groundwork for future research to investigate response variability in larger pediatric samples and atypical trajectories of early brain development in clinical populations.

Decreased brain iron deposition based on quantitative susceptibility mapping correlates with reduced neurodevelopmental status in children with autism spectrum disorder.

To investigate potential correlations between the susceptibility values of certain brain regions and the severity of disease or neurodevelopmental status in children with autism spectrum disorder (ASD), 18 ASD children and 15 healthy controls (HCs) were recruited. The neurodevelopmental status was assessed by the Gesell Developmental Schedules (GDS) and the severity of the disease was evaluated by the Autism Behavior Checklist (ABC). Eleven brain regions were selected as regions of interest and the susceptibility values were measured by quantitative susceptibility mapping. To evaluate the diagnostic capacity of susceptibility values in distinguishing ASD and HC, the receiver operating characteristic (ROC) curve was computed. Pearson and Spearman partial correlation analysis were used to depict the correlations between the susceptibility values, the ABC scores, and the GDS scores in the ASD group. ROC curves showed that the susceptibility values of the left and right frontal white matter had a larger area under the curve in the ASD group. The susceptibility value of the right globus pallidus was positively correlated with the GDS-fine motor scale score. These findings indicated that the susceptibility value of the right globus pallidus might be a viable imaging biomarker for evaluating the neurodevelopmental status of ASD children.

A novel adipose loss-of-function mutant in Drosophila.

To identify genes required for brain growth, we took an RNAi knockdown reverse genetic approach in Drosophila. One potential candidate isolated from this effort is the anti-lipogenic gene adipose (adp). Adp has an established role in the negative regulation of lipogenesis in the fat body of the fly and adipose tissue in mammals. While fat is key to proper development in general, adp has not been investigated during brain development. Here, we found that RNAi knockdown of adp in neuronal stem cells and neurons results in reduced brain lobe volume and sought to replicate this with a mutant fly. We generated a novel adp mutant that acts as a loss-of-function mutant based on buoyancy assay results. We found that despite a change in fat content in the body overall and a decrease in the number of larger (>5 µm) brain lipid droplets, there was no change in the brain lobe volume of mutant larvae. Overall, our work describes a novel adp mutant that can functionally replace the long-standing adp60 mutant and shows that the adp gene has no obvious involvement in brain growth.

Beyond antiviral: role of IFN-I in brain development.

Interferons and central nervous system resident macrophages, microglia, are well-known for their respective roles in antiviral defense and phagocytosis. Using a classic experimental paradigm for examining activity-dependent neural plasticity, Escoubas, Dorman, et al. recently identified a role for microglial type I interferon signaling in the clearance of unwanted neurons during mouse brain development.

Comprehensive analysis of synthetic learning applied to neonatal brain MRI segmentation.

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

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

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

Delta like 4 regulates cerebrovascular development and endothelial integrity via DLL4-NOTCH-CLDN5 pathway and is vulnerable to neonatal hyperoxia.

The mechanisms governing brain vascularization during development remain poorly understood. A key regulator of developmental vascularization is delta like 4 (DLL4), a Notch ligand prominently expressed in endothelial cells (EC). Exposure to hyperoxia in premature infants can disrupt the development and functions of cerebral blood vessels and lead to long-term cognitive impairment. However, its role in cerebral vascular development and the impact of postnatal hyperoxia on DLL4 expression in mouse brain EC have not been explored. We determined the DLL4 expression pattern and its downstream signalling gene expression in brain EC using Dll4+/+ and Dll4+/LacZ mice. We also performed in vitro studies using human brain microvascular endothelial cells. Finally, we determined Dll4 and Cldn5 expression in mouse brain EC exposed to postnatal hyperoxia. DLL4 is expressed in various cell types, with EC being the predominant one in immature brains. Moreover, DLL4 deficiency leads to persistent abnormalities in brain microvasculature and increased vascular permeability both in vivo and in vitro. We have identified that DLL4 insufficiency compromises endothelial integrity through the NOTCH-NICD-RBPJ-CLDN5 pathway, resulting in the downregulation of the tight junction protein claudin 5 (CLDN5). Finally, exposure to neonatal hyperoxia reduces DLL4 and CLDN5 expression in developing mouse brain EC. We reveal that DLL4 is indispensable for brain vascular development and maintaining the blood-brain barrier's function and is repressed by neonatal hyperoxia. We speculate that reduced DLL4 signalling in brain EC may contribute to the impaired brain development observed in neonates exposed to hyperoxia. KEY POINTS: The role of delta like 4 (DLL4), a Notch ligand in vascular endothelial cells, in brain vascular development and functions remains unknown. We demonstrate that DLL4 is expressed at a high level during postnatal brain development in immature brains and DLL4 insufficiency leads to abnormal cerebral vasculature and increases vascular permeability both in vivo and in vitro. We identify that DLL4  regulates endothelial integrity through NOTCH-NICD-RBPJ-CLDN5 signalling. Dll4 and Cldn5 expression are decreased in mouse brain endothelial cells exposed to postnatal hyperoxia.

Myelin-Specific microRNA-23a/b Cluster Deletion Inhibits Myelination in the Central Nervous System during Postnatal Growth and Aging.

Microribonucleic acids (miRNAs) comprising miR-23a/b clusters, specifically miR-23a and miR-27a, are recognized for their divergent roles in myelination within the central nervous system. However, cluster-specific miRNA functions remain controversial as miRNAs within the same cluster have been suggested to function complementarily. This study aims to clarify the role of miR-23a/b clusters in myelination using mice with a miR-23a/b cluster deletion (KO mice), specifically in myelin expressing proteolipid protein (PLP). Inducible conditional KO mice were generated by crossing miR-23a/b clusterflox/flox mice with PlpCre-ERT2 mice; the offspring were injected with tamoxifen at 10 days or 10 weeks of age to induce a myelin-specific miR-23a/b cluster deletion. Evaluation was performed at 10 weeks or 12 months of age and compared with control mice that were not treated with tamoxifen. KO mice exhibit impaired motor function and hypoplastic myelin sheaths in the brain and spinal cord at 10 weeks and 12 months of age. Simultaneously, significant decreases in myelin basic protein (MBP) and PLP expression occur in KO mice. The percentages of oligodendrocyte precursors and mature oligodendrocytes are consistent between the KO and control mice. However, the proportion of oligodendrocytes expressing MBP is significantly lower in KO mice. Moreover, changes in protein expression occur in KO mice, with increased leucine zipper-like transcriptional regulator 1 expression, decreased R-RAS expression, and decreased phosphorylation of extracellular signal-regulated kinases. These findings highlight the significant influence of miR-23a/b clusters on myelination during postnatal growth and aging.

Strength and resilience of developing brain circuits predict adolescent emotional and stress responses during the COVID-19 pandemic.

The COVID-19 pandemic has had profound but incompletely understood adverse effects on youth. To elucidate the role of brain circuits in how adolescents responded to the pandemic's stressors, we investigated their prepandemic organization as a predictor of mental/emotional health in the first ~15 months of the pandemic. We analyzed resting-state networks from n = 2,641 adolescents [median age (interquartile range) = 144.0 (13.0) months, 47.7% females] in the Adolescent Brain Cognitive Development study, and longitudinal assessments of mental health, stress, sadness, and positive affect, collected every 2 to 3 months from May 2020 to May 2021. Topological resilience and/or network strength predicted overall mental health, stress and sadness (but not positive affect), at multiple time points, but primarily in December 2020 and May 2021. Higher resilience of the salience network predicted better mental health in December 2020 (ß = 0.19, 95% CI = [0.06, 0.31], P = 0.01). Lower connectivity of left salience, reward, limbic, and prefrontal cortex and its thalamic, striatal, amygdala connections, predicted higher stress (ß = -0.46 to -0.20, CI = [-0.72, -0.07], P < 0.03). Lower bilateral robustness (higher fragility) and/or connectivity of these networks predicted higher sadness in December 2020 and May 2021 (ß = -0.514 to -0.19, CI = [-0.81, -0.05], P < 0.04). These findings suggest that the organization of brain circuits may have played a critical role in adolescent stress and mental/emotional health during the pandemic.

Salience network connectivity is altered in 6-week-old infants at heightened likelihood for developing autism.

Converging evidence implicates disrupted brain connectivity in autism spectrum disorder (ASD); however, the mechanisms linking altered connectivity early in development to the emergence of ASD symptomatology remain poorly understood. Here we examined whether atypicalities in the Salience Network - an early-emerging neural network involved in orienting attention to the most salient aspects of one's internal and external environment - may predict the development of ASD symptoms such as reduced social attention and atypical sensory processing. Six-week-old infants at high likelihood of developing ASD based on family history exhibited stronger Salience Network connectivity with sensorimotor regions; infants at typical likelihood of developing ASD demonstrated stronger Salience Network connectivity with prefrontal regions involved in social attention. Infants with higher connectivity with sensorimotor regions had lower connectivity with prefrontal regions, suggesting a direct tradeoff between attention to basic sensory versus socially-relevant information. Early alterations in Salience Network connectivity predicted subsequent ASD symptomatology, providing a plausible mechanistic account for the unfolding of atypical developmental trajectories associated with vulnerability to ASD.

Normative volumes and relaxation times at 3T during brain development.

While research has unveiled and quantified brain markers of abnormal neurodevelopment, clinicians still work with qualitative metrics for MRI brain investigation. The purpose of the current article is to bridge the knowledge gap between case-control cohort studies and individual patient care. Here, we provide a unique dataset of seventy-three 3-to-17 years-old healthy subjects acquired with a 6-minute MRI protocol encompassing T1 and T2 relaxation quantitative sequence that can be readily implemented in the clinical setting; MP2RAGE for T1 mapping and the prototype sequence GRAPPATINI for T2 mapping. White matter and grey matter volumes were automatically quantified. We further provide normative developmental curves based on these two imaging sequences; T1, T2 and volume normative ranges with respect to age were computed, for each ROI of a pediatric brain atlas. This open-source dataset provides normative values allowing to position individual patients acquired with the same protocol on the brain maturation curve and as such provides potentially useful quantitative biomarkers facilitating precise and personalized care.

Longitudinal MRI of the developing ferret brain reveals regional variations in timing and rate of growth.

Normative ferret brain development was characterized using magnetic resonance imaging. Brain growth was longitudinally monitored in 10 ferrets (equal numbers of males and females) from postnatal day 8 (P8) through P38 in 6-d increments. Template T2-weighted images were constructed at each age, and these were manually segmented into 12 to 14 brain regions. A logistic growth model was used to fit data from whole brain volumes and 8 of the individual regions in both males and females. More protracted growth was found in males, which results in larger brains; however, sex differences were not apparent when results were corrected for body weight. Additionally, surface models of the developing cortical plate were registered to one another using the anatomically-constrained Multimodal Surface Matching algorithm. This, in turn, enabled local logistic growth parameters to be mapped across the cortical surface. A close similarity was observed between surface area expansion timing and previous reports of the transverse neurogenic gradient in ferrets. Regional variation in the extent of surface area expansion and the maximum expansion rate was also revealed. This characterization of normative brain growth over the period of cerebral cortex folding may serve as a reference for ferret studies of brain development.

Executive functions and brain morphology of male and female dominant and subordinate cichlid fish.

BACKGROUND: Living in a social dominance hierarchy presents different benefits and challenges for dominant and subordinate males and females, which might in turn affect their cognitive needs. Despite the extensive research on social dominance in group-living species, there is still a knowledge gap regarding how social status impacts brain morphology and cognitive abilities. METHODS: Here, we tested male and female dominants and subordinates of Neolamprologus pulcher, a social cichlid fish species with size-based hierarchy. We ran three executive cognitive function tests for cognitive flexibility (reversal learning test), self-control (detour test), and working memory (object permanence test), followed by brain and brain region size measurements. RESULTS: Performance was not influenced by social status or sex. However, dominants exhibited a brain-body slope that was relatively steeper than that of subordinates. Furthermore, individual performance in reversal learning and detour tests correlated with brain morphology, with some trade-offs among major brain regions like telencephalon, cerebellum, and optic tectum. CONCLUSION: As individuals' brain growth strategies varied depending on social status without affecting executive functions, the different associated challenges might yield a potential effect on social cognition instead. Overall, the findings highlight the importance of studying the individual and not just species to understand better how the individual's ecology might shape its brain and cognition.

Shedding a Light on Dark Genes: A Comparative Expression Study of PRR12 Orthologues during Zebrafish Development.

Haploinsufficiency of the PRR12 gene is implicated in a human neuro-ocular syndrome. Although identified as a nuclear protein highly expressed in the embryonic mouse brain, PRR12 molecular function remains elusive. This study explores the spatio-temporal expression of zebrafish PRR12 co-orthologs, prr12a and prr12b, as a first step to elucidate their function. In silico analysis reveals high evolutionary conservation in the DNA-interacting domains for both orthologs, with significant syntenic conservation observed for the prr12b locus. In situ hybridization and RT-qPCR analyses on zebrafish embryos and larvae reveal distinct expression patterns: prr12a is expressed early in zygotic development, mainly in the central nervous system, while prr12b expression initiates during gastrulation, localizing later to dopaminergic telencephalic and diencephalic cell clusters. Both transcripts are enriched in the ganglion cell and inner neural layers of the 72 hpf retina, with prr12b widely distributed in the ciliary marginal zone. In the adult brain, prr12a and prr12b are found in the cerebellum, amygdala and ventral telencephalon, which represent the main areas affected in autistic patients. Overall, this study suggests PRR12's potential involvement in eye and brain development, laying the groundwork for further investigations into PRR12-related neurobehavioral disorders.