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Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

BackgroundThe importance of energy homeostasis brain circuitry in the context of obesity is well established, however, the developmental ontogeny of this circuitry in humans is currently unknown. Here, we investigate the prospective association between newborn gray matter (GM) volume in the insula, a key brain region underlying energy homeostasis, and change in percent body fat accrual over the first six months of postnatal life, an outcome that represents among the most reliable infant predictors of childhood obesity risk.MethodsA total of 52 infants (29 male, 23 female, gestational age at birth=39(1.5) weeks) were assessed using structural MRI shortly after birth (postnatal age at MRI scan=25.9(12.2) days), and serial Dual X-Ray Absorptiometry shortly after birth (postnatal age at DXA scan 1=24.6(11.4) days) and at six months of age (postnatal age at DXA scan 2=26.7(3.3) weeks).ResultsInsula GM volume was inversely associated with change in percent body fat from birth to six-months postnatal age and accounted for 19% of its variance (β=-3.6%/S.D., P=0.001). This association was driven by the central-posterior portion of the insula, a region of particular importance for gustation and interoception. The direction of this effect is in concordance with observations in adults, and the results remained statistically significant after adjusting for relevant covariates and potential confounding variables.ConclusionsAltogether, these findings suggest an underlying neural basis of childhood obesity that precedes the influence of the postnatal environment. The identification of plausible brain-related biomarkers of childhood obesity risk that predate the influence of the postnatal obesogenic environment may contribute to an improved understanding of propensity for obesity, early identification of at-risk individuals, and intervention targets for primary prevention.

Background: Enlargement of the lateral ventricles is thought to originate from abnormal prenatal brain development and is associated with neurodevelopmental disorders. Fetal isolated mild ventriculomegaly (MVM) is associated with the enlargement of lateral ventricle volumes in the neonatal period and developmental delays in early childhood. However, little is known about postnatal brain development in these children.Methods: Twenty-eight children with fetal isolated MVM and 56 matched controls were followed at ages 1 and 2 years with structural imaging on a 3T Siemens scanner and assessment of cognitive development with the Mullen Scales of Early Learning. Lateral ventricle, total gray and white matter volumes, and Mullen cognitive composite scores and subscale scores were compared between groups.Results: Compared to controls, children with prenatal isolated MVM had significantly larger lateral ventricle volumes at ages 1 and 2 years. Lateral ventricle volume at 1 and 2 years of age was significantly correlated with prenatal ventricle size. Enlargement of the lateral ventricles was associated with increased intracranial volumes and increased gray and white matter volumes. Children with MVM had Mullen composite scores similar to controls, although there was evidence of delay in fine motor and expressive language skills.Conclusions: Children with prenatal MVM have persistent enlargement of the lateral ventricles through the age of 2 years; this enlargement is associated with increased gray and white matter volumes and some evidence of delay in fine motor and expressive language development. Further study is needed to determine if enlarged lateral ventricles are associated with increased risk for neurodevelopmental disorders. [ABSTRACT FROM AUTHOR]

Background: Poor prenatal maternal sleep is a pervasive, yet modifiable, health concern affecting maternal and foetal wellbeing. Experimental rodent studies demonstrate that prenatal maternal sleep deprivation affects offspring brain development and leads to adverse outcomes, including increased anxiety-like behaviour. We examined the relation between prenatal maternal sleep quality and neonatal white matter development and subsequent infant negative emotionality., Methods: Participants included 116 mother-infant (53% female) dyads. Prenatal sleep quality was prospectively assessed three times during gestation (16, 29, and 35 gestational weeks) using the Pittsburgh Sleep Quality Index. Neonatal white matter, as indexed by fractional anisotropy (FA), was assessed via diffusion weighted magnetic resonance imaging. Negative emotionality was measured via behavioural observation and maternal report when the infant was 6-months of age., Findings: More prenatal sleep problems across pregnancy were associated with higher neonatal FA in the uncinate fasciculus (left: b = 0.20, p = .004; right: b = 0.15, p = .027). Higher neonatal uncinate FA was linked to infant negative emotionality, and uncinate FA partially mediated the association between prenatal maternal sleep and behavioural observation of infant negative emotionality., Interpretation: Findings highlight prenatal sleep as an environmental signal that affects the developing neonatal brain and later infant negative emotionality., Funding: National Institutes of Health (R01MH109662, R01HL155744, P50HD103573, K12AR084226, F32 Training fellowships MH125572, HL165844, MH106440, and diversity supplement R01HL155744-01S1)., Competing Interests: Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier B.V.)

Introduction: Existing evidence suggests that exposure to phthalates is higher among younger age groups. However, limited knowledge exists on how phthalate exposure, as well as exposure to replacement plasticizers, di(isononyl) cyclohexane-1,2-dicarboxylate (DINCH) and di-2-ethylhexyl terephthalate (DEHTP), change from infancy through early childhood., Methods: Urine samples were collected across the first 5 years of life from typically developing infants and young children enrolled between 2017 and 2020 in the longitudinal UNC Baby Connectome Project. From 438 urine samples among 187 participants, we quantified concentrations of monobutyl phthalate (MnBP), mono-3-carboxypropyl phthalate (MCPP), monoisobutyl phthalate (MiBP), monoethyl phthalate (MEP), monobenzyl phthalate (MBzP), and metabolites of di(2-ethylhexyl) phthalate (DEHP), diisonoyl phthalate (DiNP), DINCH and DEHTP. Specific gravity (SG) adjusted metabolite and molar sum concentrations were compared across age groups. Intraclass correlation coefficients (ICCs) were calculated among 122 participants with multiple urine specimens (373 samples)., Results: Most phthalate metabolites showed high detection frequencies (>80% of samples). Replacement plasticizers DINCH (58-60%) and DEHTP (>97%) were also commonly found. DiNP metabolites were less frequently detected (<10%). For some metabolites, SG-adjusted concentrations were inversely associated with age, with the highest concentrations found in the first year of life. ICCs revealed low to moderate reliability in metabolite measurements (ρ = 0.10-0.48) suggesting a high degree of within-individual variation in exposure among this age group. The first 6 months (compared to remaining age groups) showed an increased ratio of carboxylated metabolites of DEHP and DEHTP, compared to other common metabolites, but no clear age trends for DINCH metabolite ratios were observed., Conclusion: Metabolites of phthalates and replacements plasticizers were widely detected in infancy and early childhood, with the highest concentrations observed in the first year of life for several metabolites. Higher proportions of carboxylated metabolites of DEHP and DEHTP in younger age groups indicate potential differences in metabolism during infancy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Turner syndrome, caused by complete or partial loss of an X-chromosome, is often accompanied by specific cognitive challenges. Magnetic resonance imaging studies of adults and children with Turner syndrome suggest these deficits reflect differences in anatomical and functional connectivity. However, no imaging studies have explored connectivity in infants with Turner syndrome. Consequently, it is unclear when in development connectivity differences emerge. To address this gap, we compared functional connectivity and white matter microstructure of 1-year-old infants with Turner syndrome to typically developing 1-year-old boys and girls. We examined functional connectivity between the right precentral gyrus and five regions that show reduced volume in 1-year old infants with Turner syndrome compared to controls and found no differences. However, exploratory analyses suggested infants with Turner syndrome have altered connectivity between right supramarginal gyrus and left insula and right putamen. To assess anatomical connectivity, we examined diffusivity indices along the superior longitudinal fasciculus and found no differences. However, an exploratory analysis of 46 additional white matter tracts revealed significant group differences in nine tracts. Results suggest that the first year of life is a window in which interventions might prevent connectivity differences observed at later ages, and by extension, some of the cognitive challenges associated with Turner syndrome., (© The Author(s) 2024. Published by Oxford University Press.)

Schizophrenia is a neurodevelopmental disorder associated with deficits in cognitive development and childhood psychopathology. Previous studies have focused on older children and the few studies of early childhood have yielded inconsistent findings. We studied cognitive development and psychopathology in children at familial high risk (FHR) of schizophrenia and matched controls from 1 to 6 years and hypothesized that FHR children would show consistent deficits across cognitive and behavioral measures in early childhood., Study Design: Cognitive development in children at high familial risk for schizophrenia or schizoaffective disorder (n = 33) and matched healthy controls (n = 66) was assessed at 1 and 2 years with the Mullen Scales of Early Learning, and at 4 and 6 years with the Stanford Binet Intelligence Scales, BRIEF-P/BRIEF and CANTAB. Psychopathology was assessed at 4 and 6 years with the BASC-2. General linear models were used to examine differences on outcome scores, and chi-square analyses were used to explore differences in the proportion of "at risk" or "below average" score profiles., Study Results: FHR children scored significantly lower than controls on Mullen Composite at age 2, and demonstrated broad deficits in IQ, executive function and working memory and 4 and 6 years. FHR children were also rated as significantly worse on most items of the BASC-2 at ages 4 and 6., Conclusions: Children at FHR for schizophrenia demonstrate abnormal cognitive development and psychopathology at younger ages than previously detected, suggesting that early detection and intervention needs to be targeted to very early childhood., Competing Interests: Declaration of competing interest All authors declare no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Emotional regulation involves managing attention, affect, and behavior, and is essential for long-term health and well-being, including positive school adjustment. The purpose of this secondary data analysis from the Durham Child Health and Development Study was to explore how parent and teacher reported emotional regulation behaviors related to school adjustment outcomes (social skills, academic performance, and academic achievement) during early childhood. Parent and teacher reports on emotional regulation behaviors showed mixed concordance, however they correlated with critical aspects of school adjustment. Clinical and practical implications are discussed, including the role of psychiatric nurses in promoting positive emotional regulation and school adjustment outcomes across settings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Amygdala function is implicated in the pathogenesis of autism spectrum disorder (ASD) and anxiety. We investigated associations between early trajectories of amygdala growth and anxiety and ASD outcomes at school age in two longitudinal studies: high- and low-familial likelihood for ASD, Infant Brain Imaging Study (IBIS, n = 257) and typically developing (TD) community sample, Early Brain Development Study (EBDS, n = 158). Infants underwent MRI scanning at up to 3 timepoints from neonate to 24 months. Anxiety was assessed at 6-12 years. Linear multilevel modeling tested whether amygdala volume growth was associated with anxiety symptoms at school age. In the IBIS sample, children with higher anxiety showed accelerated amygdala growth from 6 to 24 months. ASD diagnosis and ASD familial likelihood were not significant predictors. In the EBDS sample, amygdala growth from birth to 24 months was associated with anxiety. More anxious children had smaller amygdala volume and slower rates of amygdala growth. We explore reasons for the contrasting results between high-familial likelihood for ASD and TD samples, grounding results in the broader literature of variable associations between early amygdala volume and later anxiety. Results have the potential to identify mechanisms linking early amygdala growth to later anxiety in certain groups., Competing Interests: Declaration of Competing Interest The authors report no financial or personal relationships that influenced their work., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The human brain grows quickly during infancy and early childhood, but factors influencing brain maturation in this period remain poorly understood. To address this gap, we harmonized data from eight diverse cohorts, creating one of the largest pediatric neuroimaging datasets to date focused on birth to 6 years of age. We mapped the developmental trajectory of intracranial and subcortical volumes in ∼2,000 children and studied how sociodemographic factors and adverse birth outcomes influence brain structure and cognition. The amygdala was the first subcortical volume to mature, whereas the thalamus exhibited protracted development. Males had larger brain volumes than females, and children born preterm or with low birthweight showed catch-up growth with age. Socioeconomic factors exerted region- and time-specific effects. Regarding cognition, males scored lower than females; preterm birth affected all developmental areas tested, and socioeconomic factors affected visual reception and receptive language. Brain-cognition correlations revealed region-specific associations., (© 2023. The Author(s).)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Ltd.)

Objective: Maternal psychological stress during pregnancy is a common risk factor for psychiatric disorders in offspring, but little is known about how heterogeneity of stress trajectories during pregnancy affect brain systems and behavioral phenotypes in infancy. This study was designed to address this gap in knowledge., Methods: Maternal anxiety, stress, and depression were assessed at multiple time points during pregnancy in two independent low-risk mother-infant cohorts (N=115 and N=2,156). Trajectories in maternal stress levels in relation to infant negative affect were examined in both cohorts. Neonatal amygdala resting-state functional connectivity MRI was examined in a subset of one cohort (N=60) to explore the potential relationship between maternal stress trajectories and brain systems in infants relevant to negative affect., Results: Four distinct trajectory clusters, characterized by changing patterns of stress over time, and two magnitude clusters, characterized by severity of stress, were identified in the original mother-infant cohort (N=115). The magnitude clusters were not associated with infant outcomes. The trajectory characterized by increasing stress in late pregnancy was associated with blunted development of infant negative affect. This relationship was replicated in the second, larger cohort (N=2,156). In addition, the trajectories that included increasing or peak maternal stress in late pregnancy were related to stronger neonatal amygdala functional connectivity to the anterior insula and the ventromedial prefrontal cortex in the exploratory analysis., Conclusions: The trajectory of maternal stress appears to be important for offspring brain and behavioral development. Understanding heterogeneity in trajectories of maternal stress and their influence on infant brain and behavioral development is critical to developing targeted interventions., Competing Interests: Dr. Fair is a patent holder on Framewise Integrated Real-Time Motion Monitoring software, and he is a cofounder of Turing Medical. The other authors report no financial relationships with commercial interests.

Human brain undergoes rapid growth during the first few years of life. While previous research has employed graph theory to study early brain development, it has mostly focused on the topological attributes of the whole brain. However, examining regional graph-theory features may provide unique insights into the development of cognitive abilities. Utilizing a large and longitudinal rsfMRI dataset from the UNC/UMN Baby Connectome Project, we investigated the developmental trajectories of regional efficiency and evaluated the relationships between these changes and cognitive abilities using Mullen Scales of Early Learning during the first twenty-eight months of life. Our results revealed a complex and spatiotemporally heterogeneous development pattern of regional global and local efficiency during this age period. Furthermore, we found that the trajectories of the regional global efficiency at the left temporal occipital fusiform and bilateral occipital fusiform gyri were positively associated with cognitive abilities, including visual reception, expressive language, receptive language, and early learning composite scores (P < 0.05, FDR corrected). However, these associations were weakened with age. These findings offered new insights into the regional developmental features of brain topologies and their associations with cognition and provided evidence of ongoing optimization of brain networks at both whole-brain and regional levels., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Background: The white matter (WM) connectome is important for cognitive development and intelligence and is altered in neuropsychiatric illnesses. Little is known about how the WM connectome develops or its relationship to IQ in early childhood., Methods: The development of node centrality in the WM connectome was studied in a longitudinal cohort of 226 (123 female) children from the University of North Carolina Early Brain Development Study. Structural and diffusion-weighted images were acquired after birth and at 1, 2, 4, and 6 years, and IQ was assessed at 6 years. Eigenvector centrality, betweenness centrality, and the global graph metrics of global efficiency, small worldness, and modularity were determined at each age., Results: The greatest developmental change in eigenvector centrality and betweenness centrality occurred during the first year of life, with relative stability between ages 1 and 6 years. Most of the high-centrality hubs at age 6 were also high-centrality hubs at 1 year, and many were already high-centrality hubs at birth. There were generally small but significant changes in global efficiency and modularity from birth to 6 years, while small worldness increased between 2 and 4 years. Individual node centrality was not significantly correlated with IQ at 6 years., Conclusions: Node centrality in the WM connectome is established very early in childhood and is relatively stable from age 1 to 6 years. Many high-centrality hubs are established before birth, and most are present by age 1., (Copyright © 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

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., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Purpose: The purpose of this study was to investigate if social adversity is associated with mother reported emotional dysregulation behaviors and trajectories during infancy and early childhood., Design & Methods: A secondary data analysis from the Durham Child Health and Development study study included 206 child-mother dyads. Three models were used to explore the relationship between social adversity and mother reported emotional dysregulation during infancy (Infant Behavior Questionnaire-Revised) and early childhood (Child Behavior Checklist - Dysregulation Profile). Linear mixed effects models were adopted to investigate if social adversity was associated with mother reported emotional dysregulation longitudinally. Regression analysis was conducted to explore if social adversity was associated with maternal reported emotional dysregulation trajectory slope scores and maternal reported emotional dysregulation trajectory class. Maternal psychological distress and the child's sex assigned at birth were included as covariates in each analysis., Results: Infants with greater social adversity scores had significantly higher maternal reported fear responses across the first year of life. Social adversity was associated with maternal reported distress to limitations trajectory, dysregulated recovery class, and dysregulated distress to limitations class. During early childhood social adversity was significantly associated with maternal reported emotional dysregulation but not trajectories which showed little variability., Conclusion & Practical Implications: Our results indicate that social adversity is associated with maternal reported emotional dysregulation during infancy and early childhood. Nursing and other professionals can participate in early screening to determine risk and provide intervention., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Adult twin neuroimaging studies have revealed that cortical thickness (CT) and surface area (SA) are differentially influenced by genetic information, leading to their spatially distinct genetic patterning and topography. However, the postnatal origins of the genetic topography of CT and SA remain unclear, given the dramatic cortical development from neonates to adults. To fill this critical gap, this study unprecedentedly explored how genetic information differentially regulates the spatial topography of CT and SA in the neonatal brain by leveraging brain magnetic resonance (MR) images from 202 twin neonates with minimal influence by the complicated postnatal environmental factors. We capitalized on infant-dedicated computational tools and a data-driven spectral clustering method to parcellate the cerebral cortex into a set of distinct regions purely according to the genetic correlation of cortical vertices in terms of CT and SA, respectively, and accordingly created the first genetically informed cortical parcellation maps of neonatal brains. Both genetic parcellation maps exhibit bilaterally symmetric and hierarchical patterns, but distinct spatial layouts. For CT, regions with closer genetic relationships demonstrate an anterior-posterior (A-P) division, while for SA, regions with greater genetic proximity are typically within the same lobe. Certain genetically informed regions exhibit strong similarities between neonates and adults, with the most striking similarities in the medial surface in terms of SA, despite their overall substantial differences in genetic parcellation maps. These results greatly advance our understanding of the development of genetic influences on the spatial patterning of cortical morphology. SIGNIFICANCE STATEMENT Genetic influences on cortical thickness (CT) and surface area (SA) are complex and could evolve throughout the lifespan. However, studies revealing distinct genetic topography of CT and SA have been limited to adults. Using brain structural magnetic resonance (MR) images of twins, we unprecedentedly discovered the distinct genetically-informed parcellation maps of CT and SA in neonatal brains, respectively. Each genetic parcellation map comprises a distinct spatial layout of cortical regions, where vertices within the same region share high genetic correlation. These genetic parcellation maps of CT and SA of neonates largely differ from those of adults, despite their highly remarkable similarities in the medial cortex of SA. These discoveries provide important insights into the genetic organization of the early cerebral cortex development., (Copyright © 2023 the authors.)

Imaging genetics provides an opportunity to discern associations between genetic variants and brain imaging phenotypes. Historically, the field has focused on adults and adolescents; very few imaging genetics studies have focused on brain development in infancy and early childhood (from birth to age 6 years). This is an important knowledge gap because developmental changes in the brain during the prenatal and early postnatal period are regulated by dynamic gene expression patterns that likely play an important role in establishing an individual's risk for later psychiatric illness and neurodevelopmental disabilities. In this review, we summarize findings from imaging genetics studies spanning from early infancy to early childhood, with a focus on studies examining genetic risk for neuropsychiatric disorders. We also introduce the Organization for Imaging Genomics in Infancy (ORIGINs), a working group of the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium, which was established to facilitate large-scale imaging genetics studies in infancy and early childhood., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Functional magnetic resonance imaging has been used to identify complex brain networks by examining the correlation of blood-oxygen-level-dependent signals between brain regions during the resting state. Many of the brain networks identified in adults are detectable at birth, but genetic and environmental influences governing connectivity within and between these networks in early infancy have yet to be explored. We investigated genetic influences on neonatal resting-state connectivity phenotypes by generating intraclass correlations and performing mixed effects modeling to estimate narrow-sense heritability on measures of within network and between-network connectivity in a large cohort of neonate twins. We also used backwards elimination regression and mixed linear modeling to identify specific demographic and medical history variables influencing within and between network connectivity in a large cohort of typically developing twins and singletons. Of the 36 connectivity phenotypes examined, only 6 showed narrow-sense heritability estimates greater than 0.10, with none being statistically significant. Demographic and obstetric history variables contributed to between- and within-network connectivity. Our results suggest that in early infancy, genetic factors minimally influence brain connectivity. However, specific demographic and medical history variables, such as gestational age at birth and maternal psychiatric history, may influence resting-state connectivity measures., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Sex differences in behavior have been reported from infancy through adulthood, but little is known about sex effects on functional circuitry in early infancy. Moreover, the relationship between early sex effects on the functional architecture of the brain and later behavioral performance remains to be elucidated. In this study, we used resting-state fMRI and a novel heatmap analysis to examine sex differences in functional connectivity with cross-sectional and longitudinal mixed models in a large cohort of infants (n = 319 neonates, 1-, and 2-year-olds). An adult dataset (n = 92) was also included for comparison. We investigated the relationship between sex differences in functional circuitry and later measures of language (collected in 1- and 2-year-olds) as well as indices of anxiety, executive function, and intelligence (collected in 4-year-olds). Brain areas showing the most significant sex differences were age-specific across infancy, with two temporal regions demonstrating consistent differences. Measures of functional connectivity showing sex differences in infancy were significantly associated with subsequent behavioral scores of language, executive function, and intelligence. Our findings provide insights into the effects of sex on dynamic neurodevelopmental trajectories during infancy and lay an important foundation for understanding the mechanisms underlying sex differences in health and disease., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objective: Longer sleep duration in infancy supports cognitive and affective functioning - likely through effects on brain development. From childhood through old age, there is evidence for a close link between sleep and brain volume. However, little is known about the association between sleep duration and brain volume in infancy, a developmental period of unprecedented brain maturation. This study aimed to close this gap by assessing sleep duration across the first year of life and gray and white matter volume at 12-mo age., Method: Infant sleep duration trajectories across the first year of life were based on maternal reports at 1, 3, 6, 9, and 12 months of age. Infant specific trajectories were generated by running a logarithmic regression for each infant and residualizing the resulting slopes for their intercept. Structural magnetic resonance imaging (MRI) scans were acquired at 12-mo age. Gray and white matter volume estimates were residualized for intracranial volume and age at scan., Results: Data to calculate sleep trajectories was available for 112 infants. Overall, sleep duration decreased over the course of the first year of life and was best described by a logarithmic function. Of these infants, data on brain volume was available for 45 infants at 12-mo age. Infants whose sleep duration decreased less during the first year of life relative to their intercept had, on average, greater white matter volume (β = .36, p = .02). Furthermore, average sleep duration across the first year of life, and sleep duration specifically at 6 and 9 months were positively associated with white matter volume. Sleep duration during the first year of life was not significantly associated with gray matter volume at 12-mo age., Conclusion: Sufficient sleep duration may benefit infant white matter development - possibly by supporting myelination. The fact that sleep duration was not associated with gray matter volume is in line with preclinical studies suggesting that sleep may be crucial for the balance between synaptogenesis and synaptic pruning but not necessarily relate to a net increase in gray matter volume. Supporting sleep during periods of rapid brain development and intervening in case of sleep problems may have long-term benefits for cognitive function and mental health., Competing Interests: The authors declare no conflicts of interest., (© 2023 The Authors. Published by Elsevier Inc.)

Background: The rapid maturation of the fetal brain renders the fetus susceptible to prenatal environmental signals. Prenatal maternal sleep quality is known to have important health implications for newborns including risk for preterm birth, however, the effect on the fetal brain is poorly understood., Method: Participants included 94 pregnant participants and their newborns (53% female). Pregnant participants (M age = 30; SD age = 5.29) reported on sleep quality three times throughout pregnancy. Newborn hippocampal and amygdala volumes were assessed using structural magnetic resonance imaging. Multilevel modeling was used to test the associations between trajectories of prenatal maternal sleep quality and newborn hippocampal and amygdala volume., Results: The overall trajectory of prenatal maternal sleep quality was associated with hippocampal volume (left: b = 0.00003, p = 0.013; right: b = 0.00003, p = .008). Follow up analyses assessing timing of exposure indicate that poor sleep quality early in pregnancy was associated with larger hippocampal volume bilaterally (e.g., late gestation left: b = 0.002, p = 0.24; right: b = 0.004, p = .11). Prenatal sleep quality was not associated with amygdala volume., Conclusion: These findings highlight the implications of poor prenatal maternal sleep quality and its role in contributing to newborn hippocampal development., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Ltd.)

Background: A large body of research supports the deleterious effects of adverse childhood experiences (ACEs) on disease susceptibility and health for both the exposed individual and the next generation. It is likely that there is an intergenerational transmission of risk from mother to child; however, the mechanisms through which such risk is conferred remain unknown. The current study evaluated the association between maternal ACEs, neonatal brain development of the amygdala and hippocampus, and later infant negative emotionality at six months of age., Methods: The sample included 85 mother-infant dyads (44 female infants) from a longitudinal study. Maternal ACEs were assessed with the Adverse Childhood Experiences Questionnaire (ACE-Q) and neonatal hippocampal and amygdala volume was assessed using structural magnetic resonance imaging (MRI). Infant negative emotionality was assessed at 6 months using the Infant Behavior Questionnaire (IBQ)., Results: Multivariate analyses demonstrated that maternal ACEs were associated with bilateral amygdala volume ( F (2,78) = 3.697, p = .029). Specifically, higher maternal ACEs were associated with smaller left (β = -0.220, t (79) = -2.661, p  = .009, R 2 = 0.494, and right (β = -0.167, t (79) = -2.043, p  = .044, R 2 = 0.501) amygdala volume. No significant association between maternal ACEs and bilateral hippocampal volume ( F (2,78) = 0.215, p = .0807) was found. Follow-up regression analyses demonstrated that both high maternal ACEs and smaller left amygdala volume were associated with higher infant negative emotionality at six months of age (β = .232, p  = .040, R 2 = 0.094, and β = -0.337, p  = .022, R 2 = 0.16, respectively) although statistically significant mediation of this effect was not observed (Indirect effect = 0.0187, 95% CI [-0.0016-0.0557])., Conclusions: Maternal ACEs are associated with both newborn amygdala volume and subsequent infant negative emotionality. These findings linking maternal adverse childhood experiences and infant brain development and temperament provide evidence to support the intergenerational transmission of adversity from mother to child., Competing Interests: Dr. Bagonis reports employment at PrimeNeuro. All other authors report having no biomedical financial interests or potential conflicts of interest., (© 2022 The Authors.)

Motivated by the recent great success of attention modeling in computer vision, it is highly desired to extend the Transformer architecture from the conventional Euclidean space to non-Euclidean spaces. Given the intrinsic spherical topology of brain cortical surfaces in neuroimaging, in this study, we propose a novel Spherical Transformer, an effective general-purpose backbone using the self-attention mechanism for analysis of cortical surface data represented by triangular meshes. By mapping the cortical surface onto a sphere and splitting it uniformly into overlapping spherical surface patches, we encode the long-range dependency within each patch by the self-attention operation and formulate the cross-patch feature transmission via overlapping regions. By limiting the self-attention computation to local patches, our proposed Spherical Transformer preserves detailed contextual information and enjoys great efficiency with linear computational complexity with respect to the patch size. Moreover, to better process longitudinal cortical surfaces, which are increasingly popular in neuroimaging studies, we unprecedentedly propose the spatiotemporal self-attention operation to jointly extract the spatial context and dynamic developmental patterns within a single layer, thus further enlarging the expressive power of the generated representation. To comprehensively evaluate the performance of our Spherical Transformer, we validate it on a surface-level prediction task and a vertex-level dense prediction task, respectively, i.e., the cognition prediction and cortical thickness map development prediction, which are important in early brain development mapping. Both applications demonstrate the competitive performance of our Spherical Transformer in comparison with the state-of-the-art methods.

We develop a computationally efficient alternative, TwinEQTL, to a linear mixed-effects model for twin genome-wide association study data. Instead of analyzing all twin samples together with linear mixed-effects model, TwinEQTL first splits twin samples into 2 independent groups on which multiple linear regression analysis can be validly performed separately, followed by an appropriate meta-analysis-like approach to combine the 2 nonindependent test results. Through mathematical derivations, we prove the validity of TwinEQTL algorithm and show that the correlation between 2 dependent test statistics at each single-nucleotide polymorphism is independent of its minor allele frequency. Thus, the correlation is constant across all single-nucleotide polymorphisms. Through simulations, we show empirically that TwinEQTL has well controlled type I error with negligible power loss compared with the gold-standard linear mixed-effects models. To accommodate expression quantitative loci analysis with twin subjects, we further implement TwinEQTL into an R package with much improved computational efficiency. Our approaches provide a significant leap in terms of computing speed for genome-wide association study and expression quantitative loci analysis with twin samples., (© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Sex differences in the human brain emerge as early as mid-gestation and have been linked to sex hormones, particularly testosterone. Here, we analyzed the influence of markers of early sex hormone exposure (polygenic risk score (PRS) for testosterone, salivary testosterone, number of CAG repeats, digit ratios, and PRS for estradiol) on the growth pattern of cortical surface area in a longitudinal cohort of 722 infants. We found PRS for testosterone and right-hand digit ratio to be significantly associated with surface area, but only in females. PRS for testosterone at the most stringent P value threshold was positively associated with surface area development over time. Higher right-hand digit ratio, which is indicative of low prenatal testosterone levels, was negatively related to surface area in females. The current work suggests that variation in testosterone levels during both the prenatal and postnatal period may contribute to cortical surface area development in female infants., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Diffusion Tensor Imaging (DTI) is a non-invasive neuroimaging method that has become the most widely employed MRI modality for investigations of white matter fiber pathways. DTI has proven especially valuable for improving our understanding of normative white matter maturation across the life span and has also been used to index clinical pathology and cognitive function. Despite its increasing popularity, especially in pediatric research, the majority of existing studies examining infant white matter maturation depend on regional or white matter skeleton-based approaches. These methods generally lack the sensitivity and spatial specificity of more advanced functional analysis options that provide information about microstructural properties of white matter along fiber bundles. DTI studies of early postnatal brain development show that profound microstructural and maturational changes take place during the first two years of life. The pattern and rate of these changes vary greatly throughout the brain during this time compared to the rest of the life span. For this reason, appropriate image processing of infant MR imaging requires the use of age-specific reference atlases. This article provides an overview of the pre-processing, atlas building, and the fiber tractography procedures used to generate two atlas resources, one for neonates and one for 1- to 2-year-old populations. Via the UNC-NAMIC DTI Fiber Analysis Framework, our pediatric atlases provide the computational templates necessary for the fully automatic analysis of infant DTI data. To the best of our knowledge, these atlases are the first comprehensive population diffusion fiber atlases in early pediatric ages that are publicly available., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Short, Jang, Steiner, Stephens, Girault, Styner and Gilmore.)

Genetic influences on cortical thickness (CT) and surface area (SA) are known to vary across the life span. Little is known about the extent to which genetic factors influence CT and SA in infancy and toddlerhood. We performed the first longitudinal assessment of genetic influences on variation in CT and SA in 501 twins who were aged 0-2 years. We observed substantial additive genetic influences on both average CT (0.48 in neonates, 0.37 in 1-year-olds, and 0.44 in 2-year-olds) and total SA (0.59 in neonates, 0.74 in 1-year-olds, and 0.73 in 2-year-olds). In addition, we found strong heritability of the change in average CT (0.49) from neonates to 1-year-olds, but not from 1- to 2-year-olds. Moreover, we found strong genetic correlations for average CT (rG = 0.92) between 1- and 2-year-olds and strong genetic correlations for total SA across all timepoints (rG = 0.96 between neonates and 1-year-olds, rG = 1 between 1- and 2-year-olds). In addition, we found CT and SA are strongly genetic correlated at birth, but weaken over time. Overall, results suggest a dynamic genetic relationship between CT and SA during first 2 years of life and provide novel insights into how genetic influences shape the cortical structure during early brain development., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The prenatal period represents a critical time for brain growth and development. These rapid neurological advances render the fetus susceptible to various influences with life-long implications for mental health. Maternal distress signals are a dominant early life influence, contributing to birth outcomes and risk for offspring psychopathology. This prospective longitudinal study evaluated the association between prenatal maternal distress and infant white matter microstructure. Participants included a racially and socioeconomically diverse sample of 85 mother-infant dyads. Prenatal distress was assessed at 17 and 29 weeks' gestational age (GA). Infant structural data were collected via diffusion tensor imaging at 42-45 weeks' postconceptional age. Findings demonstrated that higher prenatal maternal distress at 29 weeks' GA was associated with increased fractional anisotropy ( b = .283, t (64) = 2.319, p = .024) and with increased axial diffusivity ( b = .254, t (64) = 2.067, p = .043) within the right anterior cingulate white matter tract. No other significant associations were found with prenatal distress exposure and tract fractional anisotropy or axial diffusivity at 29 weeks' GA, nor earlier in gestation., Competing Interests: Conflicts of Interest: None.

Background: Turner syndrome (TS) is a genetic disorder associated with complete or partial absence of an X chromosome affecting approximately 1/2000 live female births. Available evidence suggests that, in the school-age years, girls with TS often require speech and language services; however, little is known about the language development of infants and toddlers., Method: This study (N = 31) explored the language profiles of 12- and 24-month-old girls with TS, as well as the percentage of girls who might be "at risk" for language delays. We also followed a subset of 12-month-old girls with TS to 24 months of age to determine the stability of the 12-month findings., Results: Although all mean scores were within the average range at both time points, results revealed a higher prevalence of 24-month-old girls with TS "at risk" for receptive language difficulties. In addition, expressive language skills significantly exceeded receptive language skills at both time points. We found 12-month-old girls to be "at risk" for social and symbolic difficulties based on clinical assessment; only symbolic difficulties were significant based on caregiver report. At 24 months, clinical assessment indicated greater use of speech sounds and words than normative expectations. Caregivers reported greater use of speech sounds, and also, greater use of gestures. Although some changes occurred over a 1-year time span (12 to 24 months), all mean test scores remained within the average range and the changes in the percentage of girls manifesting "at risk" status on either the PLS-4 or CSBS-DP were non-significant., Conclusions: Although within normal limits, receptive language skills were found to be significantly lower than expressive language skills at both ages. Social and symbolic communication skills also were in the average range, with both showing significant improvement from 12 to 24 months based on clinical assessment. Caregiver report found that use of gestures and production of speech sounds not only improved from 12 to 24 months, but also exceeded normative expectations. Findings suggest the presence of relatively intact speech and language abilities during the first 2 years of life, with perhaps some emergent concerns for receptive language development. Ongoing developmental surveillance will be important., (© 2021. The Author(s).)

Exposure to maternal anxiety symptoms during infancy has been associated with difficulties in development and greater risk for developing anxiety later in life. Although previous studies have examined associations between prenatal maternal distress, infant brain development, and developmental outcomes, it is still largely unclear if there are associations between postnatal anxiety, infant brain development, and cognitive development in infancy. In this study, we used resting-state functional magnetic resonance imaging to examine the association between maternal anxiety symptoms and resting-state functional connectivity in the first year of life. We also examine the association between frontolimbic functional connectivity and infant cognitive development. The sample consisted of 21 infants (mean age = 24.15 months, SD = 4.17) that were scanned during their natural sleep using. We test the associations between maternal trait anxiety symptoms and amygdala-anterior cingulate cortex (ACC) functional connectivity, a neural circuit implicated in early life stress exposure. We also test the associations between amygdala-ACC connectivity and cognitive development. We found a significant negative association between maternal trait anxiety symptoms and left amygdala-right ACC functional connectivity (p < .05, false discovery rate corrected). We found a significant negative association between left amygdala-right ACC functional connectivity and infant cognitive development (p < .05). These findings have potential implications for understanding the role of postpartum maternal anxiety symptoms in functional brain and cognitive development in infancy., (© 2021 Wiley Periodicals LLC.)

Different functional networks exhibit distinct longitudinal trajectories throughout development, but the timeline of the dynamics of functional connectivity across the whole brain remains to be elucidated. Here we used resting-state fMRI to investigate the development of voxel-level changes in functional connectivity across the first six years of life. Globally, we found that developmental changes in functional connectivity are nonlinear with more changes during the first postnatal year than the second, followed by most significant changes from ages 2-4 and from ages 4-6. However, the overall global difference observed between the first and second year appears to have been driven by girls. Limbic and subcortical areas consistently demonstrated the most substantial changes, whereas primary sensory areas were the most stable. These patterns were consistent in full-term and preterm subgroups. Validation on randomly divided subsamples as well as in an independent cross-sectional sample revealed global patterns consistent with the main results. Overall, the derived developmental heatmaps reveal novel dynamics underlying functional circuit development during the first 6 years of life., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Maternal psychosocial stress during pregnancy can impact the developing fetal brain and influence offspring mental health. In this context, animal studies have identified the hippocampus and amygdala as key brain regions of interest, however, evidence in humans is sparse. We, therefore, examined the associations between maternal prenatal psychosocial stress, newborn hippocampal and amygdala volumes, and child social-emotional development. In a sample of 86 mother-child dyads, maternal perceived stress was assessed serially in early, mid and late pregnancy. Following birth, newborn (aged 5-64 postnatal days, mean: 25.8 ± 12.9) hippocampal and amygdala volume was assessed using structural magnetic resonance imaging. Infant social-emotional developmental milestones were assessed at 6- and 12-months age using the Bayley-III. After adjusting for covariates, maternal perceived stress during pregnancy was inversely associated with newborn left hippocampal volume ( β  = -0.26, p = .019), but not with right hippocampal ( β  = -0.170, p  = .121) or bilateral amygdala volumes ( p s > .5). Furthermore, newborn left hippocampal volume was positively associated with infant social-emotional development across the first year of postnatal life (B = 0.01, p = .011). Maternal perceived stress was indirectly associated with infant social-emotional development via newborn left hippocampal volume (B = -0.34, 95% CI BC [-0.97, -0.01]), suggesting mediation. This study provides prospective evidence in humans linking maternal psychosocial stress in pregnancy with newborn hippocampal volume and subsequent infant social-emotional development across the first year of life. These findings highlight the importance of maternal psychosocial state during pregnancy as a target amenable to interventions to prevent or attenuate its potentially unfavorable neural and behavioral consequences in the offspring., Competing Interests: None., (© 2021 The Authors.)

Canonical correlation analysis (CCA) is a common method used to estimate the associations between two different sets of variables by maximizing the Pearson correlation between linear combinations of the two sets of variables. We propose a version of CCA for transelliptical distributions with an elliptical copula using pairwise Kendall's tau to estimate a latent scatter matrix. Because Kendall's tau relies only on the ranks of the data this method does not make any assumptions about the marginal distributions of the variables, and is valid when moments do not exist. We establish consistency and asymptotic normality for canonical directions and correlations estimated using Kendall's tau. Simulations indicate that this estimator outperforms standard CCA for data generated from heavy tailed elliptical distributions. Our method also identifies more meaningful relationships when the marginal distributions are skewed. We also propose a method for testing for non-zero canonical correlations using bootstrap methods. This testing procedure does not require any assumptions on the joint distribution of the variables and works for all elliptical copulas. This is in contrast to permutation tests which are only valid when data are generated from a distribution with a Gaussian copula. This method's practical utility is shown in an analysis of the association between radial diffusivity in white matter tracts and cognitive tests scores for six-year-old children from the Early Brain Development Study at UNC-Chapel Hill. An R package implementing this method is available at github.com/blangworthy/transCCA.

The hippocampus is a key limbic region involved in higher-order cognitive processes including learning and memory. Although both typical and atypical functional connectivity patterns of the hippocampus have been well-studied in adults, the developmental trajectory of hippocampal connectivity during infancy and how it relates to later working memory performance remains to be elucidated. Here we used resting state fMRI (rsfMRI) during natural sleep to examine the longitudinal development of hippocampal functional connectivity using a large cohort (N = 202) of infants at 3 weeks (neonate), 1 year, and 2 years of age. Next, we used multivariate modeling to investigate the relationship between both cross-sectional and longitudinal growth in hippocampal connectivity and 4-year working memory outcome. Results showed robust local functional connectivity of the hippocampus in neonates with nearby limbic and subcortical regions, with dramatic maturation and increasing connectivity with key default mode network (DMN) regions resulting in adult-like topology of the hippocampal functional connectivity by the end of the first year. This pattern was stabilized and further consolidated by 2 years of age. Importantly, cross-sectional and longitudinal measures of hippocampal connectivity in the first year predicted subsequent behavioral measures of working memory at 4 years of age. Taken together, our findings provide insight into the development of hippocampal functional circuits underlying working memory during this early critical period., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Convolutional Neural Networks (CNNs) have achieved overwhelming success in learning-related problems for 2D/3D images in the Euclidean space. However, unlike in the Euclidean space, the shapes of many structures in medical imaging have an inherent spherical topology in a manifold space, e.g., the convoluted brain cortical surfaces represented by triangular meshes. There is no consistent neighborhood definition and thus no straightforward convolution/pooling operations for such cortical surface data. In this paper, leveraging the regular and hierarchical geometric structure of the resampled spherical cortical surfaces, we create the 1-ring filter on spherical cortical triangular meshes and accordingly develop convolution/pooling operations for constructing Spherical U-Net for cortical surface data. However, the regular nature of the 1-ring filter makes it inherently limited to model fixed geometric transformations. To further enhance the transformation modeling capability of Spherical U-Net, we introduce the deformable convolution and deformable pooling to cortical surface data and accordingly propose the Spherical Deformable U-Net (SDU-Net). Specifically, spherical offsets are learned to freely deform the 1-ring filter on the sphere to adaptively localize cortical structures with different sizes and shapes. We then apply the SDU-Net to two challenging and scientifically important tasks in neuroimaging: cortical surface parcellation and cortical attribute map prediction. Both applications validate the competitive performance of our approach in accuracy and computational efficiency in comparison with state-of-the-art methods.

Tracing the early paths leading to developmental disorders is critical for prevention. In previous work, we detected an interaction between genomic risk scores for schizophrenia (GRSs) and early-life complications (ELCs), so that the liability of the disorder explained by genomic risk was higher in the presence of a history of ELCs, compared with its absence. This interaction was specifically driven by loci harboring genes highly expressed in placentae from normal and complicated pregnancies [G. Ursini et al., Nat. Med. 24, 792-801 (2018)]. Here, we analyze whether fractionated genomic risk scores for schizophrenia and other developmental disorders and traits, based on placental gene-expression loci (PlacGRSs), are linked with early neurodevelopmental outcomes in individuals with a history of ELCs. We found that schizophrenia's PlacGRSs are negatively associated with neonatal brain volume in singletons and offspring of multiple pregnancies and, in singletons, with cognitive development at 1 y and, less strongly, at 2 y, when cognitive scores become more sensitive to other factors. These negative associations are stronger in males, found only with GRSs fractionated by placental gene expression, and not found in PlacGRSs for other developmental disorders and traits. The relationship of PlacGRSs with brain volume persists as an anlage of placenta biology in adults with schizophrenia, again selectively in males. Higher placental genomic risk for schizophrenia, in the presence of ELCs and particularly in males, alters early brain growth and function, defining a potentially reversible neurodevelopmental path of risk that may be unique to schizophrenia., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Adolescence is a transitional period between childhood and adulthood characterized by significant changes in global and regional brain tissue volumes. It is also a period of increasing vulnerability to psychiatric illness. The relationship between these patterns and increased levels of circulating sex steroids during adolescence remains unclear. The objective of the current study was to determine whether gonadectomy, prior to puberty, alters adolescent brain development in male rhesus macaques. Ninety-six structural MRI scans were acquired from 12 male rhesus macaques (8 time points per animal over a two-year period). Six animals underwent gonadectomy and 6 animals underwent a sham operation at 29 months of age. Mixed-effects models were used to determine whether gonadectomy altered developmental trajectories of global and regional brain tissue volumes. We observed a significant effect of gonadectomy on the developmental trajectory of prefrontal gray matter (GM), with intact males showing peak volumes around 3.5 years of age with a subsequent decline. In contrast, prefrontal GM volumes continued to increase in gonadectomized males until the end of the study. We did not observe a significant effect of gonadectomy on prefrontal white matter or on any other global or regional brain tissue volumes, though we cannot rule out that effects might be detected in a larger sample. Results suggest that the prefrontal cortex is more vulnerable to gonadectomy than other brain regions., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

A better understanding of genetic influences on early white matter development could significantly advance our understanding of neurological and psychiatric conditions characterized by altered integrity of axonal pathways. We conducted a genome-wide association study (GWAS) of diffusion tensor imaging (DTI) phenotypes in 471 neonates. We used a hierarchical functional principal regression model (HFPRM) to perform joint analysis of 44 fiber bundles. HFPRM revealed a latent measure of white matter microstructure that explained approximately 50% of variation in our tractography-based measures and accounted for a large proportion of heritable variation in each individual bundle. An intronic SNP in PSMF1 on chromosome 20 exceeded the conventional GWAS threshold of 5 x 10-8 (p = 4.61 x 10-8). Additional loci nearing genome-wide significance were located near genes with known roles in axon growth and guidance, fasciculation, and myelination., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)