Impact of Demographic and Obstetric Factors on Infant Brain Volumes: A Population Neuroscience Study

Prenatal Social Determinants of Health: Narrative review of maternal environments and neonatal brain development

The Social Determinants of Health, a set of social factors including socioeconomic status, community context, and neighborhood safety among others, are well-known predictors of mental and physical health across the lifespan. Recent research has begun to establish the importance of these social factors at the earliest points of brain development, including during the prenatal period. Prenatal socioeconomic status, perceived stress, and neighborhood safety have all been reported to impact neonatal brain structure and function, with exploratory work suggesting subsequent effects on infant and child behavior. Secondary effects of the Social Determinants of Health, such as maternal sleep and psychopathology during pregnancy, have also been established as important predictors of infant brain development. This research not only establishes prenatal Social Determinants of Health as important predictors of future outcomes but may be effectively applied even before birth. Future research replicating and extending the effects in this nascent literature has great potential to produce more specific and mechanistic understanding of the social factors that shape early neurobehavioral development. IMPACT: This review synthesizes the research to date examining the effects of the Social Determinants of Health during the prenatal period and neonatal brain outcomes. Structural, functional, and diffusion-based imaging methodologies are included along with the limited literature assessing subsequent infant behavior. The degree to which results converge between studies is discussed, in combination with the methodological and sampling considerations that may contribute to divergence in study results. Several future directions are identified, including new theoretical approaches to assessing the impact of the Social Determinants of Health during the perinatal period.

Sex Differences in Human Brain Structure at Birth

BACKGROUND

Sex differences in human brain anatomy have been well-documented, though remain significantly underexplored during early development. The neonatal period is a critical stage for brain development and can provide key insights into the role that prenatal and early postnatal factors play in shaping sex differences in the brain.

METHODS

Here, we assessed on-average sex differences in global and regional brain volumes in 514 newborns aged 0-28 days (236 birth-assigned females and 278 birth-assigned males) using data from the developing Human Connectome Project. We also assessed sex-by-age interactions to investigate sex differences in early postnatal brain development.

RESULTS

On average, males had significantly larger intracranial and total brain volumes, even after controlling for birth weight. After controlling for total brain volume, females showed significantly greater total cortical gray matter volumes, whilst males showed greater total white matter volumes. After controlling for total brain volume in regional comparisons, females had significantly increased white matter volumes in the corpus callosum and increased gray matter volumes in the bilateral parahippocampal gyri (posterior parts), left anterior cingulate gyrus, bilateral parietal lobes, and left caudate nucleus. Males had significantly increased gray matter volumes in the right medial and inferior temporal gyrus (posterior part) and right subthalamic nucleus. Effect sizes ranged from small for regional comparisons to large for global comparisons. Significant sex-by-age interactions were noted in the left anterior cingulate gyrus and left superior temporal gyrus (posterior parts).

CONCLUSIONS

Our findings demonstrate that sex differences in brain structure are already present at birth and remain comparatively stable during early postnatal development, highlighting an important role of prenatal factors in shaping sex differences in the brain.

Trajectories of brain and behaviour development in the womb, at birth and through infancy

Birth is often seen as the starting point for studying effects of the environment on human development, with much research focused on the capacities of young infants. However, recent imaging advances have revealed that the complex behaviours of the fetus and the uterine environment exert influence. Birth is now viewed as a punctuate event along a developmental pathway of increasing autonomy of the child from their mother. Here we highlight (1) increasing physiological autonomy and perceptual sensitivity in the fetus, (2) physiological and neurochemical processes associated with birth that influence future behaviour, (3) the recalibration of motor and sensory systems in the newborn to adapt to the world outside the womb and (4) the effect of the prenatal environment on later infant behaviours and brain function. Taken together, these lines of evidence move us beyond nature-nurture issues to a developmental human lifespan view beginning within the womb.

Fetal influence on the human brain through the lifespan

Human fetal development has been associated with brain health at later stages. It is unknown whether growth in utero, as indexed by birth weight (BW), relates consistently to lifespan brain characteristics and changes, and to what extent these influences are of a genetic or environmental nature. Here we show remarkably stable and lifelong positive associations between BW and cortical surface area and volume across and within developmental, aging and lifespan longitudinal samples (N = 5794, 4-82 y of age, w/386 monozygotic twins, followed for up to 8.3 y w/12,088 brain MRIs). In contrast, no consistent effect of BW on brain changes was observed. Partly environmental effects were indicated by analysis of twin BW discordance. In conclusion, the influence of prenatal growth on cortical topography is stable and reliable through the lifespan. This early-life factor appears to influence the brain by association of brain reserve, rather than brain maintenance. Thus, fetal influences appear omnipresent in the spacetime of the human brain throughout the human lifespan. Optimizing fetal growth may increase brain reserve for life, also in aging.

Structural brain correlates of non-verbal cognitive ability in 5-year-old children: Findings from the FinnBrain birth cohort study

Non-verbal cognitive ability predicts multiple important life outcomes, for example, school and job performance. It has been associated with parieto-frontal cortical anatomy in prior studies in adult and adolescent populations, while young children have received relatively little attention. We explored the associations between cortical anatomy and non-verbal cognitive ability in 165 5-year-old participants (mean scan age 5.40 years, SD 0.13; 90 males) from the FinnBrain Birth Cohort study. T1-weighted brain magnetic resonance images were processed using FreeSurfer. Non-verbal cognitive ability was measured using the Performance Intelligence Quotient (PIQ) estimated from the Block Design and Matrix Reasoning subtests from the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III). In vertex-wise general linear models, PIQ scores associated positively with volumes in the left caudal middle frontal and right pericalcarine regions, as well as surface area in left the caudal middle frontal, left inferior temporal, and right lingual regions. There were no associations between PIQ and cortical thickness. To the best of our knowledge, this is the first study to examine structural correlates of non-verbal cognitive ability in a large sample of typically developing 5-year-olds. The findings are generally in line with prior findings from older age groups, with the important addition of the positive association between volume / surface area in the right medial occipital region and non-verbal cognitive ability. This finding adds to the literature by discovering a new brain region that should be considered in future studies exploring the role of cortical structure for cognitive development in young children.

The Association Between Maternal Cortisol and Infant Amygdala Volume Is Moderated by Socioeconomic Status

Background

It has been well established that socioeconomic status is associated with mental and physical health as well as brain development, with emerging data suggesting that these relationships begin in utero. However, less is known about how prenatal socioeconomic environments interact with the gestational environment to affect neonatal brain volume.

Methods

Maternal cortisol output measured at each trimester of pregnancy and neonatal brain structure were assessed in 241 mother-infant dyads. We examined associations between the trajectory of maternal cortisol output across pregnancy and volumes of cortisol receptor-rich regions of the brain, including the amygdala, hippocampus, medial prefrontal cortex, and caudate. Given the known effects of poverty on infant brain structure, socioeconomic disadvantage was included as a moderating variable.

Results

Neonatal amygdala volume was predicted by an interaction between maternal cortisol output across pregnancy and socioeconomic disadvantage (standardized β = -0.31, p < .001), controlling for postmenstrual age at scan, infant sex, and total gray matter volume. Notably, amygdala volumes were positively associated with maternal cortisol for infants with maternal disadvantage scores 1 standard deviation below the mean (i.e., less disadvantage) (simple slope = 123.36, p < .01), while the association was negative in infants with maternal disadvantage 1 standard deviation above the mean (i.e., more disadvantage) (simple slope = -82.70, p = .02). Individuals with disadvantage scores at the mean showed no association, and there were no significant interactions in the other brain regions examined.

Conclusions

These data suggest that fetal development of the amygdala is differentially affected by maternal cortisol production at varying levels of socioeconomic advantage.

Quantitative assessment of cerebrospinal fluid flow and volume in enlargement of the subarachnoid spaces of infancy using MRI

BACKGROUND

The etiology of enlarged subarachnoid spaces of infancy is unknown; however, there is radiologic similarity with normal pressure hydrocephalus. Adults with normal pressure hydrocephalus have been shown to have altered cerebrospinal (CSF) flow through the cerebral aqueduct.

OBJECTIVE

To explore potential similarity between enlarged subarachnoid spaces of infancy and normal pressure hydrocephalus, we compared MRI-measured CSF flow through the cerebral aqueduct in infants with enlarged subarachnoid spaces of infancy to infants with normal brain MRIs.

MATERIALS AND METHODS

This was an IRB approved retrospective study. Clinical brain MRI examinations including axial T2 imaging and phase contrast through the aqueduct were reviewed for infants with enlarged subarachnoid spaces of infancy and for infants with a qualitatively normal brain MRI. The brain and CSF volumes were segmented using a semi-automatic technique (Analyze 12.0) and CSF flow parameters were measured (cvi42, 5.14). All data was assessed for significant differences while controlling for age and sex using analysis of covariance (ANCOVA).

RESULTS

Twenty-two patients with enlarged subarachnoid spaces (mean age 9.0 months, 19 males) and 15 patients with normal brain MRI (mean age 18.9 months, 8 females) were included. Volumes of the subarachnoid space (P < 0.001), lateral (P < 0.001), and third ventricles (P < 0.001) were significantly larger in infants with enlarged subarachnoid spaces of infancy. Aqueductal stroke volume significantly increased with age (P = 0.005), regardless of group.

CONCLUSION

CSF volumes were significantly larger in infants with enlarged subarachnoid spaces of infancy versus infants with a normal MRI; however, there was no significant difference in CSF flow parameters between the two groups.

Association of Preterm Birth and Socioeconomic Status With Neonatal Brain Structure

Importance

Preterm birth and socioeconomic status (SES) are associated with brain structure in childhood, but the relative contributions of each during the neonatal period are unknown.

Objective

To investigate associations of birth gestational age (GA) and SES with neonatal brain morphology by testing 3 hypotheses: GA and SES are associated with brain morphology; associations between SES and brain morphology vary with GA; and associations between SES and brain structure and morphology depend on how SES is operationalized.

Design, Setting, and Participants

This cohort study recruited participants from November 2016 to September 2021 at a single center in the United Kingdom. Participants were 170 extremely and very preterm infants and 91 full-term or near-term infants. Exclusion criteria were major congenital malformation, chromosomal abnormality, congenital infection, cystic periventricular leukomalacia, hemorrhagic parenchymal infarction, and posthemorrhagic ventricular dilatation.

Exposures

Birth GA and SES, operationalized at the neighborhood level (using the Scottish Index of Multiple Deprivation), the family level (using parental education and occupation), and subjectively (World Health Organization Quality of Life measure).

Main Outcomes and Measures

Brain volume (85 parcels) and 5 whole-brain cortical morphology measures (gyrification index, thickness, sulcal depth, curvature, surface area) at term-equivalent age (median [range] age, 40 weeks, 5 days [36 weeks, 2 days to 45 weeks, 6 days] and 42 weeks [38 weeks, 2 days to 46 weeks, 1 day] for preterm and full-term infants, respectively).

Results

Participants were 170 extremely and very preterm infants (95 [55.9%] male; 4 of 166 [2.4%] Asian, 145 of 166 [87.3%] White) and 91 full-term or near-term infants (50 [54.9%] male; 3 of 86 [3.5%] Asian, 78 of 86 [90.7%] White infants) with median (range) birth GAs of 30 weeks, 0 days (22 weeks, 1 day, to 32 weeks, 6 days) and 39 weeks, 4 days (36 weeks, 3 days, to 42 weeks, 1 day), respectively. In fully adjusted models, birth GA was associated with a higher proportion of brain volumes (27 of 85 parcels [31.8%]; β range, -0.20 to 0.24) than neighborhood-level SES (1 of 85 parcels [1.2%]; β = 0.17 [95% CI, -0.16 to 0.50]) or family-level SES (maternal education: 4 of 85 parcels [4.7%]; β range, 0.09 to 0.15; maternal occupation: 1 of 85 parcels [1.2%]; β = 0.06 [95% CI, 0.02 to 0.11] respectively). There were interactions between GA and both family-level and subjective SES measures on regional brain volumes. Birth GA was associated with cortical surface area (β = 0.10 [95% CI, 0.02 to 0.18]) and gyrification index (β = 0.16 [95% CI, 0.07 to 0.25]); no SES measure was associated with cortical measures.

Conclusions and Relevance

In this cohort study of UK infants, birth GA and SES were associated with neonatal brain morphology, but low GA had more widely distributed associations with neonatal brain structure than SES. Further work is warranted to elucidate the mechanisms underlying the association of both GA and SES with early brain development.

Development of Gestational Age-Based Fetal Brain and Intracranial Volume Reference Norms Using Deep Learning

BACKGROUND AND PURPOSE

Fetal brain MR imaging interpretations are subjective and require subspecialty expertise. We aimed to develop a deep learning algorithm for automatically measuring intracranial and brain volumes of fetal brain MRIs across gestational ages.

MATERIALS AND METHODS

This retrospective study included 246 patients with singleton pregnancies at 19-38 weeks gestation. A 3D U-Net was trained to segment the intracranial contents of 2D fetal brain MRIs in the axial, coronal, and sagittal planes. An additional 3D U-Net was trained to segment the brain from the output of the first model. Models were tested on MRIs of 10 patients (28 planes) via Dice coefficients and volume comparison with manual reference segmentations. Trained U-Nets were applied to 200 additional MRIs to develop normative reference intracranial and brain volumes across gestational ages and then to 9 pathologic fetal brains.

RESULTS

Fetal intracranial and brain compartments were automatically segmented in a mean of 6.8 (SD, 1.2) seconds with median Dices score of 0.95 and 0.90, respectively (interquartile ranges, 0.91-0.96/0.89-0.91) on the test set. Correlation with manual volume measurements was high (Pearson r = 0.996, P < .001). Normative samples of intracranial and brain volumes across gestational ages were developed. Eight of 9 pathologic fetal intracranial volumes were automatically predicted to be >2 SDs from this age-specific reference mean. There were no effects of fetal sex, maternal diabetes, or maternal age on intracranial or brain volumes across gestational ages.

CONCLUSIONS

Deep learning techniques can quickly and accurately quantify intracranial and brain volumes on clinical fetal brain MRIs and identify abnormal volumes on the basis of a normative reference standard.

Perinatal and early childhood biomarkers of psychosocial stress and adverse experiences

The human brain develops through a complex interplay of genetic and environmental influences. During critical periods of development, experiences shape brain architecture, often with long-lasting effects. If experiences are adverse, the effects may include the risk of mental and physical disease, whereas positive environments may increase the likelihood of healthy outcomes. Understanding how psychosocial stress and adverse experiences are embedded in biological systems and how we can identify markers of risk may lead to discovering new approaches to improve patient care and outcomes. Biomarkers can be used to identify specific intervention targets and at-risk children early when physiological system malleability increases the likelihood of intervention success. However, identifying reliable biomarkers has been challenging, particularly in the perinatal period and the first years of life, including in preterm infants. This review explores the landscape of psychosocial stress and adverse experience biomarkers. We highlight potential benefits and challenges of identifying risk clinically and different sub-signatures of stress, and in their ability to inform targeted interventions. Finally, we propose that the combination of preterm birth and adversity amplifies the risk for abnormal development and calls for a focus on this group of infants within the field of psychosocial stress and adverse experience biomarkers. IMPACT: Reviews the landscape of biomarkers of psychosocial stress and adverse experiences in the perinatal period and early childhood and highlights the potential benefits and challenges of their clinical utility in identifying risk status in children, and in developing targeted interventions. Explores associations between psychosocial stress and adverse experiences in childhood with prematurity and identifies potential areas of assessment and intervention to improve outcomes in this at-risk group.

Cortical Structure and Cognition in Infants and Toddlers

Cortical structure has been consistently related to cognitive abilities in children and adults, yet we know little about how the cortex develops to support emergent cognition in infancy and toddlerhood when cortical thickness (CT) and surface area (SA) are maturing rapidly. In this report, we assessed how regional and global measures of CT and SA in a sample (N = 487) of healthy neonates, 1-year-olds, and 2-year-olds related to motor, language, visual reception, and general cognitive ability. We report novel findings that thicker cortices at ages 1 and 2 and larger SA at birth, age 1, and age 2 confer a cognitive advantage in infancy and toddlerhood. While several expected brain-cognition relationships were observed, overlapping cortical regions were also implicated across cognitive domains, suggesting that infancy marks a period of plasticity and refinement in cortical structure to support burgeoning motor, language, and cognitive abilities. CT may be a particularly important morphological indicator of ability, but its impact on cognition is relatively weak when compared with gestational age and maternal education. Findings suggest that prenatal and early postnatal cortical developments are important for cognition in infants and toddlers but should be considered in relation to other child and demographic factors.

Considering Sex as a Biological Variable in Basic and Clinical Studies: An Endocrine Society Scientific Statement

In May 2014, the National Institutes of Health (NIH) stated its intent to "require applicants to consider sex as a biological variable (SABV) in the design and analysis of NIH-funded research involving animals and cells." Since then, proposed research plans that include animals routinely state that both sexes/genders will be used; however, in many instances, researchers and reviewers are at a loss about the issue of sex differences. Moreover, the terms sex and gender are used interchangeably by many researchers, further complicating the issue. In addition, the sex or gender of the researcher might influence study outcomes, especially those concerning behavioral studies, in both animals and humans. The act of observation may change the outcome (the "observer effect") and any experimental manipulation, no matter how well-controlled, is subject to it. This is nowhere more applicable than in physiology and behavior. The sex of established cultured cell lines is another issue, in addition to aneuploidy; chromosomal numbers can change as cells are passaged. Additionally, culture medium contains steroids, growth hormone, and insulin that might influence expression of various genes. These issues often are not taken into account, determined, or even considered. Issues pertaining to the "sex" of cultured cells are beyond the scope of this Statement. However, we will discuss the factors that influence sex and gender in both basic research (that using animal models) and clinical research (that involving human subjects), as well as in some areas of science where sex differences are routinely studied. Sex differences in baseline physiology and associated mechanisms form the foundation for understanding sex differences in diseases pathology, treatments, and outcomes. The purpose of this Statement is to highlight lessons learned, caveats, and what to consider when evaluating data pertaining to sex differences, using 3 areas of research as examples; it is not intended to serve as a guideline for research design.

Canonical correlation analysis for elliptical copulas

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.

[Formula: see text] Neural correlates of socioeconomic status in early childhood: a systematic review of the literature

It is now established that socioeconomic variables are associated with cognitive, academic achievement, and psychiatric outcomes. Recent years have shown the advance in our understanding of how socioeconomic status (SES) relates to brain development in the first years of life (ages 0-5 years). However, it remains unknown which neural structures and functions are most sensitive to the environmental experiences associated with SES. Pubmed, PsycInfo, and Google Scholar databases from January 1, 2000, to December 31, 2019, were systematically searched using terms "Neural" OR "Neuroimaging" OR "Brain" OR "Brain development," AND "Socioeconomic" OR "SES" OR "Income" OR "Disadvantage" OR "Education," AND "Early childhood" OR "Early development". Nineteen studies were included in the full review after applying all exclusion criteria. Studies revealed associations between socioeconomic and neural measures and indicated that, in the first years of life, certain neural functions and structures (e.g., those implicated in language and executive function) may be more sensitive to socioeconomic context than others. Findings broadly support the hypothesis that SES associations with neural structure and function operate on a gradient. Socioeconomic status is reflected in neural architecture and function of very young children, as early as shortly after birth, with its effects possibly growing throughout early childhood as a result of postnatal experiences. Although socioeconomic associations with neural measures were relatively consistent across studies, results from this review are not conclusive enough to supply a neural phenotype of low SES. Further work is necessary to understand causal mechanisms underlying SES-brain associations.

Genome-Wide Association Analysis of Neonatal White Matter Microstructure

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.

Subdural Hemorrhage in Asymptomatic Neonates: Neurodevelopmental Outcomes and MRI Findings at 2 Years

Background Subdural hemorrhage (SDH) is thought to have a benign course in asymptomatic neonates. However, effects on neurodevelopmental outcomes have not been established. Purpose To evaluate neurodevelopmental outcomes, gray matter volumes, and MRI findings in asymptomatic neonates with SDH compared with control neonates. Materials and Methods This retrospective analysis was conducted between 2003 and 2016 and was based on data from the University of North Carolina Early Brain Development Study. Neurodevelopmental outcomes were evaluated at 2 years of age by using the Mullen Scales of Early Learning (MSEL). All infants were imaged with 3.0-T MRI machines and were evaluated for SDH at baseline (neonates) and at ages 1 and 2 years. Volumetric MRI for brain segmentation was performed at ages 1 and 2 years. A secondary analysis was performed in neonates matched 1:1 with control neonates. Differences in categorical variables were measured by using the Fisher exact test, and the t test was used for continuous variables. Results A total of 311 neonates (mean gestational age ± standard deviation, 39.3 weeks ± 1.5), including 57 with SDH (mean gestational age, 39.5 weeks ± 1.2), were evaluated. The subgroup included 55 neonates with SDH (mean gestational age, 39.6 weeks ± 1.2) and 55 matched control neonates (mean gestational age, 39.7 weeks ± 1.2). Fifty-five of 57 neonates with SDH (97%; 95% CI: 92, 100) were delivered vaginally compared with 157 of 254 control neonates (62%, 95% CI: 56, 68; P < .001). Otherwise, there were no differences in perinatal, maternal, or obstetric parameters. There were no differences in composite MSEL scores (115 ± 15 and 109 ± 16 at 2 years, respectively; P = .05) or gray matter volumes between the neonatal SDH group and control neonates (730 cm3 ± 85 and 742 cm3 ± 76 at 2 years, respectively; P = .70). There was no evidence of rebleeding at follow-up MRI. Conclusion Neurodevelopmental scores and gray matter volumes at age 2 years did not differ between asymptomatic neonates with subdural hemorrhage and control neonates. © RSNA, 2020 Online supplemental material is available for this article.

X-chromosome regulation and sex differences in brain anatomy

Humans show reproducible sex-differences in cognition and psychopathology that may be contributed to by influences of gonadal sex-steroids and/or sex-chromosomes on regional brain development. Gonadal sex-steroids are well known to play a major role in sexual differentiation of the vertebrate brain, but far less is known regarding the role of sex-chromosomes. Our review focuses on this latter issue by bridging together two literatures that have to date been largely disconnected. We first consider "bottom-up" genetic and molecular studies focused on sex-chromosome gene content and regulation. This literature nominates specific sex-chromosome genes that could drive developmental sex-differences by virtue of their sex-biased expression and their functions within the brain. We then consider the complementary "top down" view, from magnetic resonance imaging studies that map sex- and sex chromosome effects on regional brain anatomy, and link these maps to regional gene-expression within the brain. By connecting these top-down and bottom-up approaches, we emphasize the potential role of X-linked genes in driving sex-biased brain development and outline key goals for future work in this field.

Neonatal brain metabolite concentrations: Associations with age, sex, and developmental outcomes

Age and sex differences in brain metabolite concentrations in early life are not well understood. We examined the associations of age and sex with brain metabolite levels in healthy neonates, and investigated the associations between neonatal brain metabolite concentrations and developmental outcomes. Forty-one infants (36–42 gestational weeks at birth; 39% female) of predominantly Hispanic/Latina mothers (mean 18 years of age) underwent MRI scanning approximately two weeks after birth. Multiplanar chemical shift imaging was used to obtain voxel-wise maps of N-acetylaspartate (NAA), creatine, and choline concentrations across the brain. The Bayley Scales of Infant and Toddler Development, a measure of cognitive, language, and motor skills, and mobile conjugate reinforcement paradigm, a measure of learning and memory, were administered at 4 months of age. Findings indicated that postmenstrual age correlated positively with NAA concentrations in multiple subcortical and white matter regions. Creatine and choline concentrations showed similar but less pronounced age related increases. Females compared with males had higher metabolite levels in white matter and subcortical gray matter. Neonatal NAA concentrations were positively associated with learning and negatively associated with memory at 4 months. Age-related increases in NAA, creatine, and choline suggest rapid development of neuronal viability, cellular energy metabolism, and cell membrane turnover, respectively, during early life. Females may undergo earlier and more rapid regional developmental increases in the density of viable neurons compared to males.

White Matter Development from Birth to 6 Years of Age: A Longitudinal Study

Human white matter development in the first years of life is rapid, setting the foundation for later development. Microstructural properties of white matter are linked to many behavioral and psychiatric outcomes; however, little is known about when in development individual differences in white matter microstructure are established. The aim of the current study is to characterize longitudinal development of white matter microstructure from birth through 6 years to determine when in development individual differences are established. Two hundred and twenty-four children underwent diffusion-weighted imaging after birth and at 1, 2, 4, and 6 years. Diffusion tensor imaging data were computed for 20 white matter tracts (9 left-right corresponding tracts and 2 commissural tracts), with tract-based measures of fractional anisotropy and axial and radial diffusivity. Microstructural maturation between birth and 1 year are much greater than subsequent changes. Further, by 1 year, individual differences in tract average values are consistently predictive of the respective 6-year values, explaining, on average, 40% of the variance in 6-year microstructure. Results provide further evidence of the importance of the first year of life with regard to white matter development, with potential implications for informing early intervention efforts that target specific sensitive periods.

Individual Variation of Human Cortical Structure Is Established in the First Year of Life

BACKGROUND

Individual differences in cortical gray matter (GM) structure are associated with cognitive function and psychiatric disorders with developmental origins. Identifying when individual differences in cortical structure are established in childhood is critical for understanding the timing of abnormal cortical development associated with neuropsychiatric disorders.

METHODS

We studied the development of cortical GM and white matter volume, cortical thickness, and surface area using structural magnetic resonance imaging in two unique cohorts of singleton (121 male and 131 female) and twin (99 male and 83 female) children imaged longitudinally from birth to 6 years.

RESULTS

Cortical GM volume increases rapidly in the first year of life, with more gradual growth thereafter. Between ages 1 and 6 years, total surface area expands 29%, while average cortical thickness decreases about 3.5%. In both cohorts, a large portion of individual variation in cortical GM volume (81%-87%) and total surface area (73%-83%) at age 6 years is present by age 1 year. Regional heterogeneity of cortical thickness observed at age 6 is largely in place at age 1.

CONCLUSIONS

These findings indicate that individual differences in cortical GM structure are largely established by the end of the first year of life, following a period of rapid postnatal GM growth. This suggests that alterations in GM structure associated with psychiatric disorders with developmental origins may largely arise in the first year of life and that interventions to normalize or mitigate abnormal GM development may need to be targeted to very early childhood.

Functional dissection of prenatal drug effects on baby brain and behavioral development

Prenatal drug exposure (PDE) is known to affect fetal brain development with documented long‐term consequences. Most studies of PDE effects on the brain are based on animal models. In this study, based on a large sample of 133 human neonates and leveraging a novel linear mixed‐effect model designed for intersubject variability analyses, we studied the effects of six prenatally exposed drugs (i.e., nicotine, alcohol, selective serotonin reuptake inhibitor, marijuana, cocaine, and opioids) on neonatal whole‐brain functional organization and compared them with five other critical nondrug variables (i.e., gestational age at birth/scan, sex, birth weight, and maternal depression). The behavioral implications were also examined. Magnitude‐wise, through summing across individual drug effects, our results highlighted ~5% of whole‐brain functional connections (FCs) affected by PDE, which was highly comparable with the combined effects of the five nond rug variables. Spatially, the detected PDE effects featured drug‐specific patterns with a common bias in higher‐order brain regions/networks. Regarding brain–behavioral relationships, the detected connections showing significant drug effects also demonstrated significant correlations with 3‐month behavioral outcomes. Further mediation analyses supported a mediation role of the detected brain FCs between PDE status and cognitive/language outcomes. Our findings of widespread, and spatially biased PDE effect patterns coupled with significant behavioral implications may hopefully stimulate more human‐based studies into effects of PDE on long‐term developmental outcomes.

Parental age effects on neonatal white matter development

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Advanced paternal age is associated with a range of later negative outcomes.

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It is not known if these negative outcomes are due to genetics or environment.

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We use neonatal diffusion MRI to demonstrate paternal age effect on white matter.

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The babies of older fathers had reduced fractional anisotropy in multiple areas.

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These changes correlated with cognitive outcome at 18 months.

Objective

Advanced paternal age is associated with poor offspring developmental outcome. Though an increase in paternal age-related germline mutations may affect offspring white matter development, outcome differences could also be due to psychosocial factors. Here we investigate possible cerebral changes prior to strong environmental influences using brain MRI in a cohort of healthy term-born neonates.

Methods

We used structural and diffusion MRI images acquired soon after birth from a cohort (n = 275) of healthy term-born neonates. Images were analysed using a customised tract based spatial statistics (TBSS) processing pipeline. Neurodevelopmental assessment using the Bayley-III scales was offered to all participants at age 18 months. For statistical analysis neonates were compared in two groups, representing the upper quartile (paternal age ≥38 years) and lower three quartiles. The same method was used to assess associations with maternal age.

Results

In infants with older fathers (≥38 years), fractional anisotropy, a marker of white matter organisation, was significantly reduced in three early maturing anatomical locations (the corticospinal tract, the corpus callosum, and the optic radiation). Fractional anisotropy in these locations correlated positively with Bayley-III cognitive composite score at 18 months in the advanced paternal age group. A small but significant reduction in total brain volume was also observed in in the infants of older fathers. No significant associations were found between advanced maternal age and neonatal imaging.

Conclusions

The epidemiological association between advanced paternal age and offspring outcome is extremely robust. We have for the first time demonstrated a neuroimaging phenotype of advanced paternal age before sustained parental interaction that correlates with later outcome.

Patterns of sociocognitive stratification and perinatal risk in the child brain

The expanding behavioral repertoire of the developing brain during childhood and adolescence is shaped by complex brain-environment interactions and flavored by unique life experiences. The transition into young adulthood offers opportunities for adaptation and growth but also increased susceptibility to environmental perturbations, such as the characteristics of social relationships, family environment, quality of schools and activities, financial security, urbanization and pollution, drugs, cultural practices, and values, that all act in concert with our genetic architecture and biology. Our multivariate brain-behavior mapping in 7,577 children aged 9 to 11 y across 585 brain imaging phenotypes and 617 cognitive, behavioral, psychosocial, and socioeconomic measures revealed three population modes of brain covariation, which were robust as assessed by cross-validation and permutation testing, taking into account siblings and twins, identified using genetic data. The first mode revealed traces of perinatal complications, including preterm and twin birth, eclampsia and toxemia, shorter period of breastfeeding, and lower cognitive scores, with higher cortical thickness and lower cortical areas and volumes. The second mode reflected a pattern of sociocognitive stratification, linking lower cognitive ability and socioeconomic status to lower cortical thickness, area, and volumes. The third mode captured a pattern related to urbanicity, with particulate matter pollution (PM²⁵) inversely related to home value, walkability, and population density, associated with diffusion properties of white matter tracts. These results underscore the importance of a multidimensional and interdisciplinary understanding, integrating social, psychological, and biological sciences, to map the constituents of healthy development and to identify factors that may precede maladjustment and mental illness.

Environmental Influences on Infant Cortical Thickness and Surface Area

Cortical thickness (CT) and surface area (SA) vary widely between individuals and are associated with intellectual ability and risk for various psychiatric and neurodevelopmental conditions. Factors influencing this variability remain poorly understood, but the radial unit hypothesis, as well as the more recent supragranular cortex expansion hypothesis, suggests that prenatal and perinatal influences may be particularly important. In this report, we examine the impact of 17 major demographic and obstetric history variables on interindividual variation in CT and SA in a unique sample of 805 neonates who received MRI scans of the brain around 2 weeks of age. Birth weight, postnatal age at MRI, gestational age at birth, and sex emerged as important predictors of SA. Postnatal age at MRI, paternal education, and maternal ethnicity emerged as important predictors of CT. These findings suggest that individual variation in infant CT and SA is explained by different sets of environmental factors with neonatal SA more strongly influenced by sex and obstetric history and CT more strongly influenced by socioeconomic and ethnic disparities. Findings raise the possibility that interventions aimed at reducing disparities and improving obstetric outcomes may alter prenatal/perinatal cortical development.

Extra-axial Cerebrospinal Fluid Relationships to Infant Brain Structure, Cognitive Development, and Risk for Schizophrenia

BACKGROUND

Increased volume of extra-axial cerebrospinal fluid (EA-CSF) is associated with autism spectrum disorder diagnosis in young children. However, little is known about EA-CSF development in typically developing (TD) children or in children at risk for schizophrenia (SCZHR).

METHODS

3T magnetic resonance imaging scans were obtained in TD children (n = 105) and in SCZHR children (n = 38) at 1 and 2 years of age. EA-CSF volume and several measures of brain structure were generated, including global tissue volumes, cortical thickness, and surface area. Cognitive and motor abilities at 1 and 2 years of age were assessed using the Mullen Scales of Early Learning.

RESULTS

In the TD children, EA-CSF volume was positively associated with total brain volume, gray and white matter volumes, and total surface area at 1 and 2 years of age. In contrast, EA-CSF volume was negatively associated with average cortical thickness. Lower motor ability was associated with increased EA-CSF volume at 1 year of age. EA-CSF was not significantly increased in SCZHR children compared with TD children.

CONCLUSIONS

EA-CSF volume is positively associated with overall brain size and cortical surface area but negatively associated with cortical thickness. Increased EA-CSF is associated with delayed motor development at 1 year of age, similar to studies of children at risk for autism, suggesting that increased EA-CSF may be an early biomarker of abnormal brain development in infancy. Infants in the SCZHR group did not exhibit significantly increased EA-CSF, suggesting that increased EA-CSF could be specific to neurodevelopmental disorders with an earlier onset, such as autism.

Neuroscience and Sex/Gender: Looking Back and Forward

Phoenix et al. (1959) reported that treating pregnant guinea pigs with testosterone had enduring effects on the sex-related behavior of their female offspring. Since then, similar enduring effects of early testosterone exposure have been found in other species, including humans, and for other behaviors that show average sex differences. In humans, the affected outcomes include gender identity, sexual orientation, and children's sex-typical play behavior. The evidence linking early testosterone exposure to sex-typed play is particularly robust, and sex-typed play is also influenced by many other factors, including socialization by parents and peers and self-socialization, based on cognitive understanding of gender. In addition to influencing behavior, testosterone and hormones produced from testosterone affect mammalian brain structure. Studies using human autopsy material have found some sex differences in the human brain similar to those seen in other species, and have reported that some brain sex differences correlate with sexual orientation or gender identity, although the causes of these brain/behavior relationships are unclear. Studies that have imaged the living human brain have found only a small number of sex differences, and these differences are generally small in magnitude. In addition, they have not been linked to robust psychological or behavioral sex differences. Future research might benefit from improved imaging technology, and attention to other brain characteristics. In addition, it might usefully explore how different types of factors, such as early testosterone exposure and parental socialization, work together in the developmental system that produces sex/gender differences in human brain and behavior.

Effects of Maternal Psychopathology and Education Level on Neurocognitive Development in Infants of Adolescent Mothers Living in Poverty in Brazil

BACKGROUND

Adolescent motherhood remains common in developing countries and is associated with risk factors that adversely impact infant neurodevelopment, including poverty, low maternal education, and increased maternal psychopathology. Yet, no published work has assessed how these factors affect early brain development in developing countries.

METHODS

This pilot study examined effects of maternal psychopathology and education on early neurocognitive development in a sample of adolescent mothers (N = 50, final n = 31) and their infants living in poverty in São Paulo, Brazil. Maternal symptoms of anxiety, depression, and attention-deficit/hyperactivity disorder and education level were assessed during pregnancy. Infant neurocognitive development was assessed at 6 months of age, with oscillatory power and functional connectivity in the theta (4-6 Hz), alpha (6-9 Hz), and gamma (30-50 Hz) frequencies derived from resting-state electroencephalography; temperament (negative affect, attention, and regulation); and cognitive, language, and motor skills. Cluster-based permutation testing and graph-theoretical methods were used to identify alterations in oscillatory power and connectivity that were associated with maternal psychopathology and education. Correlations between power and connectivity alterations were examined in relation to infants' overt cognitive behavioral abilities.

RESULTS

Increased maternal anxiety and lower maternal education were associated with weaker oscillatory connectivity in alpha-range networks. Infants with the weakest connectivity in the alpha network associated with maternal anxiety also showed the lowest cognitive ability. Greater maternal anxiety and attention-deficit/hyperactivity disorder were associated with increased absolute and relative theta power.

CONCLUSIONS

Our findings highlight the importance of addressing maternal psychopathology and improving education in poor adolescent mothers to prevent negative effects on infant neurodevelopment.

Gut microbiome and brain functional connectivity in infants-a preliminary study focusing on the amygdala

Recently, there has been a surge of interest in the possibility that microbial communities inhabiting the human gut could affect cognitive development and increase risk for mental illness via the "microbiome-gut-brain axis." Infancy likely represents a critical period for the establishment of these relationships, as it is the most dynamic stage of postnatal brain development and a key period in the maturation of the microbiome. Indeed, recent reports indicate that characteristics of the infant gut microbiome are associated with both temperament and cognitive performance. The neural circuits underlying these relationships have not yet been delineated. To address this gap, resting-state fMRI scans were acquired from 39 1-year-old human infants who had provided fecal samples for identification and relative quantification of bacterial taxa. Measures of alpha diversity were generated and tested for associations with measures of functional connectivity. Primary analyses focused on the amygdala as manipulation of the gut microbiota in animal models alters the structure and neurochemistry of this brain region. Secondary analyses explored functional connectivity of nine canonical resting-state functional networks. Alpha diversity was significantly associated with functional connectivity between the amygdala and thalamus and between the anterior cingulate cortex and anterior insula. These regions play an important role in processing/responding to threat. Alpha diversity was also associated with functional connectivity between the supplementary motor area (SMA, representing the sensorimotor network) and the inferior parietal lobule (IPL). Importantly, SMA-IPL connectivity also related to cognitive outcomes at 2 years of age, suggesting a potential pathway linking gut microbiome diversity and cognitive outcomes during infancy. These results provide exciting new insights into the gut-brain axis during early human development and should stimulate further studies into whether microbiome-associated changes in brain circuitry influence later risk for psychopathology.

White matter connectomes at birth accurately predict cognitive abilities at age 2

Cognitive ability is an important predictor of mental health outcomes that is influenced by neurodevelopment. Evidence suggests that the foundational wiring of the human brain is in place by birth, and that the white matter (WM) connectome supports developing brain function. It is unknown, however, how the WM connectome at birth supports emergent cognition. In this study, a deep learning model was trained using cross-validation to classify full-term infants (n = 75) as scoring above or below the median at age 2 using WM connectomes generated from diffusion weighted magnetic resonance images at birth. Results from this model were used to predict individual cognitive scores. We additionally identified WM connections important for classification. The model was also evaluated in a separate set of preterm infants (n = 37) scanned at term-age equivalent. Findings revealed that WM connectomes at birth predicted 2-year cognitive score group with high accuracy in both full-term (89.5%) and preterm (83.8%) infants. Scores predicted by the model were strongly correlated with actual scores (r = 0.98 for full-term and r = 0.96 for preterm). Connections within the frontal lobe, and between the frontal lobe and other brain areas were found to be important for classification. This work suggests that WM connectomes at birth can accurately predict a child's 2-year cognitive group and individual score in full-term and preterm infants. The WM connectome at birth appears to be a useful neuroimaging biomarker of subsequent cognitive development that deserves further study.

Associations of age and sex with brain volumes and asymmetry in 2-5-week-old infants

Information on normal brain structure and development facilitates the recognition of abnormal developmental trajectories and thus needs to be studied in more detail. We imaged 68 healthy infants aged 2-5 weeks with high-resolution structural MRI (magnetic resonance imaging) and investigated hemispheric asymmetry as well as the associations of various total and lobar brain volumes with infant age and sex. We found similar hemispheric asymmetry in both sexes, seen as larger volumes of the right temporal lobe, and of the left parietal and occipital lobes. The degree of asymmetry did not vary with age. Regardless of controlling for gestational age, gray and white matter had different age-related growth patterns. This is a reflection of gray matter growth being greater in the first years, while white matter growth extends into early adulthood. Sex-dependent differences were seen in gray matter as larger regional absolute volumes in males and as larger regional relative volumes in females. Our results are in line with previous studies and expand our understanding of infant brain development.

Prenatal exposures and infant brain: Review of magnetic resonance imaging studies and a population description analysis

Brain development is most rapid during the fetal period and the first years of life. This process can be affected by many in utero factors, such as chemical exposures and maternal health characteristics. The goal of this review is twofold: to review the most recent findings on the effects of these prenatal factors on the developing brain and to qualitatively assess how those factors were generally reported in studies on infants up to 2 years of age. To capture the latest findings in the field, we searched articles from PubMed 2012 onward with search terms referring to magnetic resonance imaging (MRI), brain development, and infancy. We identified 19 MRI studies focusing on the effects of prenatal environment and summarized them to highlight the recent advances in the field. We assessed population descriptions in a representative sample of 67 studies and conclude that prenatal factors that have been shown to affect brain metrics are not generally reported comprehensively. Based on our findings, we propose some improvements for population descriptions to account for plausible confounders and in time enable reliable meta-analyses to be performed. This could help the pediatric neuroimaging field move toward more reliable identification of biomarkers for developmental outcomes and to better decipher the nuances of normal and abnormal brain development.

White matter microstructural development and cognitive ability in the first 2 years of life

White matter (WM) integrity has been related to cognitive ability in adults and children, but it remains largely unknown how WM maturation in early life supports emergent cognition. The associations between tract-based measures of fractional anisotropy (FA) and axial and radial diffusivity (AD, RD) shortly after birth, at age 1, and at age 2 and cognitive measures at 1 and 2 years were investigated in 447 healthy infants. We found that generally higher FA and lower AD and RD across many WM tracts in the first year of life were associated with better performance on measures of general cognitive ability, motor, language, and visual reception skills at ages 1 and 2, suggesting an important role for the overall organization, myelination, and microstructural properties of fiber pathways in emergent cognition. RD in particular was consistently related to ability, and protracted development of RD from ages 1 to 2 years in several tracts was associated with higher cognitive scores and better language performance, suggesting prolonged plasticity may confer cognitive benefits during the second year of life. However, we also found that cognition at age 2 was weakly associated with WM properties across infancy in comparison to child and demographic factors including gestational age and maternal education. Our findings suggest that early postnatal WM integrity across the brain is important for infant cognition, though its role in cognitive development should be considered alongside child and demographic factors.

Genetic influences on neonatal cortical thickness and surface area

Genetic and environmental influences on cortical thickness (CT) and surface area (SA) are thought to vary in a complex and dynamic way across the lifespan. It has been established that CT and SA are genetically distinct in older children, adolescents, and adults, and that heritability varies across cortical regions. Very little, however, is known about how genetic and environmental factors influence infant CT and SA. Using structural MRI, we performed the first assessment of genetic and environmental influences on normal variation of SA and CT in 360 twin neonates. We observed strong and significant additive genetic influences on total SA (a²  = 0.78) and small and nonsignificant genetic influences on average CT (a²  = 0.29). Moreover, we found significant genetic overlap (genetic correlation = 0.65) between these global cortical measures. Regionally, there were minimal genetic influences across the cortex for both CT and SA measures and no distinct patterns of genetic regionalization. Overall, outcomes from this study suggest a dynamic relationship between CT and SA during the neonatal period and provide novel insights into how genetic influences shape cortical structure during early development.

A cortical shape-adaptive approach to local gyrification index

The amount of cortical folding, or gyrification, is typically measured within local cortical regions covered by an equidistant geodesic or nearest neighborhood-ring kernel. However, without careful design, such a kernel can easily cover multiple sulcal and gyral regions that may not be functionally related. Furthermore, this can result in smoothing out details of cortical folding, which consequently blurs local gyrification measurements. In this paper, we propose a novel kernel shape to locally quantify cortical gyrification within sulcal and gyral regions. We adapt wavefront propagation to generate a spatially varying kernel shape that encodes cortical folding patterns: neighboring gyral crowns, sulcal fundi, and sulcal banks. For this purpose, we perform anisotropic wavefront propagation that runs fast along gyral crowns and sulcal fundi by solving a static Hamilton-Jacobi partial differential equation. The resulting kernel adaptively elongates along gyral crowns and sulcal fundi, while keeping a uniform shape over flat regions like sulcal banks. We then measure local gyrification within the proposed spatially varying kernel. The experimental results show that the proposed kernel-based gyrification measure achieves a higher reproducibility than the conventional method in a multi-scan dataset. We further apply the proposed kernel to a brain development study in the early postnatal phase from neonate to 2 years of age. In this study we find that our kernel yields both positive and negative associations of gyrification with age, whereas the conventional method only captures positive associations. In general, our method yields sharper and more detailed statistical maps that associate cortical folding with sex and gestational age.

The Predictive Value of Developmental Assessments at 1 and 2 for Intelligence Quotients at 6

Intelligence is an important individual difference factor related to mental health, academic achievement, and life success, yet there is a lack of research into its early cognitive predictors. This study investigated the predictive value of infant developmental assessment scores for school-age intelligence in a large, heterogeneous sample of single- and twin-born subjects (N = 521). We found that Early Learning Composite (ELC) scores from the Mullen Scales of Early Learning have similar predictive power to that of other infant tests. ELC scores at age 2 were predictive of Stanford-Binet abbreviated intelligence (ABIQ) scores at age 6 (r = 0.46) even after controlling for sex, gestation number, and parental education. ELC scores at age 1 were less predictive of 6-year ABIQ scores (r = 0.17). When the sample was split to test robustness of findings, we found that results from the full sample replicated in a subset of children born at ≥32 weeks gestation without birth complications (n = 405), though infant cognitive scores did not predict IQ in a subset born very prematurely or with birth complications (n = 116). Scores at age 2 in twins and singletons showed similar predictive ability for scores at age 6, though twins had particularly high correlations between ELC at age 1 and ABIQ at age 6.

Imaging structural and functional brain development in early childhood

In humans, the period from term birth to ∼2 years of age is characterized by rapid and dynamic brain development and plays an important role in cognitive development and risk of disorders such as autism and schizophrenia. Recent imaging studies have begun to delineate the growth trajectories of brain structure and function in the first years after birth and their relationship to cognition and risk of neuropsychiatric disorders. This Review discusses the development of grey and white matter and structural and functional networks, as well as genetic and environmental influences on early-childhood brain development. We also discuss initial evidence regarding the usefulness of early imaging biomarkers for predicting cognitive outcomes and risk of neuropsychiatric disorders.