Armin Raznahan

How Does Your Cortex Grow

Understanding human cortical maturation is a central goal for developmental neuroscience. Significant advances toward this goal have come from two recent strands of in vivo structural magnetic resonance imaging research: (1) longitudinal study designs have revealed that factors such as sex, cognitive ability, and disease are often better related to variations in the tempo of anatomical change than to variations in anatomy at any one time point; (2) largely cross-sectional applications of new surface-based morphometry (SBM) methods have shown how the traditional focus on cortical volume (CV) can obscure information about the two evolutionarily and genetically distinct determinants of CV: cortical thickness (CT) and surface area (SA). Here, by combining these two strategies for the first time and applying SBM in >1250 longitudinally acquired brain scans from 647 healthy individuals aged 3–30 years, we deconstruct cortical development to reveal that distinct trajectories of anatomical change are hidden within, and give rise to, a curvilinear pattern of CV maturation. Developmental changes in CV emerge through the sexually dimorphic and age-dependent interaction of changes in CT and SA. Moreover, SA change itself actually reflects complex interactions between brain size-related changes in exposed cortical convex hull area, and changes in the degree of cortical gyrification, which again vary by age and sex. Knowing of these developmental dissociations, and further specifying their timing and sex-biases, provides potent new research targets for basic and clinical neuroscience.

Longitudinally mapping the influence of sex and androgen signaling on the dynamics of human cortical maturation in adolescence

Humans have systematic sex differences in brain-related behavior, cognition, and pattern of mental illness risk. Many of these differences emerge during adolescence, a developmental period of intense neurostructural and endocrine change. Here, by creating “movies” of sexually dimorphic brain development using longitudinal in vivo structural neuroimaging, we show regionally specific sex differences in development of the cerebral cortex during adolescence. Within cortical subsystems known to underpin domains of cognitive behavioral sex difference, structural change is faster in the sex that tends to perform less well within the domain in question. By stratifying participants through molecular analysis of the androgen receptor gene, we show that possession of an allele conferring more efficient functioning of this sex steroid receptor is associated with “masculinization” of adolescent cortical maturation. Our findings extend models first established in rodents, and suggest that in humans too, sex and sex steroids shape brain development in a spatiotemporally specific manner, within neural systems known to underpin sexually dimorphic behaviors.

The Convergence of Maturational Change and Structural Covariance in Human Cortical Networks

Large-scale covariance of cortical thickness or volume in distributed brain regions has been consistently reported by human neuroimaging studies. The mechanism of this population covariance of regional cortical anatomy has been hypothetically related to synchronized maturational changes in anatomically connected neuronal populations. Brain regions that grow together, i.e., increase or decrease in volume at the same rate over the course of years in the same individual, are thus expected to demonstrate strong structural covariance or anatomical connectivity across individuals. To test this prediction, we used a structural MRI dataset on healthy young people (N = 108; aged 9–22 years at enrollment), comprising 3–6 longitudinal scans on each participant over 6–12 years of follow-up. At each of 360 regional nodes, and for each participant, we estimated the following: (1) the cortical thickness in the median scan and (2) the linear rate of change in cortical thickness over years of serial scanning. We constructed structural and maturational association matrices and networks from these measurements. Both structural and maturational networks shared similar global and nodal topological properties, as well as mesoscopic features including a modular community structure, a relatively small number of highly connected hub regions, and a bias toward short distance connections. Using resting-state functional magnetic resonance imaging data on a subset of the sample (N = 32), we also demonstrated that functional connectivity and network organization was somewhat predictable by structural/maturational networks but demonstrated a stronger bias toward short distance connections and greater topological segregation. Brain structural covariance networks are likely to reflect synchronized developmental change in distributed cortical regions.

Review: magnetic resonance imaging of male/female differences in human adolescent brain anatomy

Improvements in neuroimaging technologies, and greater access to their use, have generated a plethora of data regarding male/female differences in the developing brain. Examination of these differences may shed light on the pathophysiology of the many illnesses that differ between the sexes and ultimately lead to more effective interventions. In this review, we attempt to synthesize the anatomic magnetic resonance imaging (MRI) literature of male/female brain differences with emphasis on studies encompassing adolescence – a time of divergence in physical and behavioral characteristics. Across all ages total brain size is consistently reported to be about 10% larger in males. Structures commonly reported to be different between sexes include the caudate nucleus, amygdala, hippocampus, and cerebellum – all noted to have a relatively high density of sex steroid receptors. The direction and magnitude of reported brain differences depends on the methodology of data acquisition and analysis, whether and how the subcomponents are adjusted for the total brain volume difference, and the age of the participants in the studies. Longitudinal studies indicate regional cortical gray matter volumes follow inverted U shaped developmental trajectories with peak size occurring one to three years earlier in females. Cortical gray matter differences are modulated by androgen receptor genotyope and by circulating levels of hormones. White matter volumes increase throughout childhood and adolescence in both sexes but more rapidly in adolescent males resulting in an expanding magnitude of sex differences from childhood to adulthood.

Performing label-fusion-based segmentation using multiple automatically generated templates.

Classically, model‐based segmentation procedures match magnetic resonance imaging (MRI) volumes to an expertly labeled atlas using nonlinear registration. The accuracy of these techniques are limited due to atlas biases, misregistration, and resampling error. Multi‐atlas‐based approaches are used as a remedy and involve matching each subject to a number of manually labeled templates. This approach yields numerous independent segmentations that are fused using a voxel‐by‐voxel label‐voting procedure. In this article, we demonstrate how the multi‐atlas approach can be extended to work with input atlases that are unique and extremely time consuming to construct by generating a library of multiple automatically generated templates of different brains (MAGeT Brain). We demonstrate the efficacy of our method for the mouse and human using two different nonlinear registration algorithms (ANIMAL and ANTs). The input atlases consist a high‐resolution mouse brain atlas and an atlas of the human basal ganglia and thalamus derived from serial histological data. MAGeT Brain segmentation improves the identification of the mouse anterior commissure (mean Dice Kappa values (κ = 0.801), but may be encountering a ceiling effect for hippocampal segmentations. Applying MAGeT Brain to human subcortical structures improves segmentation accuracy for all structures compared to regular model‐based techniques (κ = 0.845, 0.752, and 0.861 for the striatum, globus pallidus, and thalamus, respectively). Experiments performed with three manually derived input templates suggest that MAGeT Brain can approach or exceed the accuracy of multi‐atlas label‐fusion segmentation (κ = 0.894, 0.815, and 0.895 for the striatum, globus pallidus, and thalamus, respectively). Hum Brain Mapp 34:2635–2654, 2013.

Longitudinal four-dimensional mapping of subcortical anatomy in human development

Significance Our spatiotemporal understanding of subcortical development in humans lags far behind that of the cortical sheet. This disparity ignores that developmental refinements and disruptions of complex behavior involve systems spanning both components of the brain. We begin redressing this imbalance by applying new techniques for striatal, pallidal and thalamic morphometry to large-scale longitudinal neuroimaging data extending from childhood through early adulthood. This work (i) establishes the curvilinear, sexual dimorphic and often protracted nature of global volume change within each structure, (ii) reveals profound spatiotemporal complexities in striatal, pallidal and thalamic maturation that are organized by the known topography of primate cortico-subcortical connectivity, and (iii) identifies focal sex differences in subcortical maturation that strike regions implicated in psychopathologies with an adolescent-emergent sex-bias. Growing access to large-scale longitudinal structural neuroimaging data has fundamentally altered our understanding of cortical development en route to human adulthood, with consequences for basic science, medicine, and public policy. In striking contrast, basic anatomical development of subcortical structures such as the striatum, pallidum, and thalamus has remained poorly described—despite these evolutionarily ancient structures being both intimate working partners of the cortical sheet and critical to diverse developmentally emergent skills and disorders. Here, to begin addressing this disparity, we apply methods for the measurement of subcortical volume and shape to 1,171 longitudinally acquired structural magnetic resonance imaging brain scans from 618 typically developing males and females aged 5–25 y. We show that the striatum, pallidum, and thalamus each follow curvilinear trajectories of volume change, which, for the striatum and thalamus, peak after cortical volume has already begun to decline and show a relative delay in males. Four-dimensional mapping of subcortical shape reveals that (i) striatal, pallidal, and thalamic domains linked to specific fronto-parietal association cortices contract with age whereas other subcortical territories expand, and (ii) each structure harbors hotspots of sexually dimorphic change over adolescence—with relevance for sex-biased mental disorders emerging in youth. By establishing the developmental dynamism, spatial heterochonicity, and sexual dimorphism of human subcortical maturation, these data bring our spatiotemporal understanding of subcortical development closer to that of the cortex—allowing evolutionary, basic, and clinical neuroscience to be conducted within a more comprehensive developmental framework.

Child psychiatry branch of the National Institute of Mental Health longitudinal structural magnetic resonance imaging study of human brain development.

The advent of magnetic resonance imaging, which safely allows in vivo quantification of anatomical and physiological features of the brain, has revolutionized pediatric neuroscience. Longitudinal studies are useful for the characterization of developmental trajectories (ie, changes in imaging measures by age). Developmental trajectories (as opposed to static measures) have proven to have greater power in discriminating healthy from clinical groups and in predicting cognitive/behavioral measures, such as IQ. Here we summarize results from an ongoing longitudinal pediatric neuroimaging study that has been conducted at the Child Psychiatry Branch of the National Institute of Mental Health since 1989. Developmental trajectories of structural MRI brain measures from healthy youth are compared and contrasted with trajectories in attention-deficit/hyperactivity disorder (ADHD) and childhood-onset schizophrenia. Across ages 5–25 years, in both healthy and clinical populations, white matter volumes increase and gray matter volumes follow an inverted U trajectory, with peak size occurring at different times in different regions. At a group level, differences related to psychopathology are seen for gray and white matter volumes, rates of change, and for interconnectedness among disparate brain regions.

Prenatal growth in humans and postnatal brain maturation into late adolescence

Prenatal life encompasses a critical phase of human brain development, but neurodevelopmental consequences of normative differences in prenatal growth among full-term pregnancies remain largely uncharted. Here, we combine the power of a within-monozygotic twin study design with longitudinal neuroimaging methods that parse dissociable components of structural brain development between ages 3 and 30 y, to show that subtle variations of the in utero environment, as indexed by mild birth weight (BW) variation within monozygotic pairs, are accompanied by statistically significant (i) differences in postnatal intelligence quotient (IQ) and (ii) alterations of brain anatomy that persist at least into late adolescence. Greater BW within the normal range confers a sustained and generalized increase in brain volume, which in the cortical sheet, is specifically driven by altered surface area rather than cortical thickness. Surface area is maximally sensitive to BW variation within cortical regions implicated in the biology of several mental disorders, the risk for which is modified by normative BW variation. We complement this near-experimental test of prenatal environmental influences on human brain development by replicating anatomical findings in dizygotic twins and unrelated singletons. Thus, using over 1,000 brain scans, across three independent samples, we link subtle differences in prenatal growth, within ranges seen among the majority of human pregnancies, to protracted surface area alterations, that preferentially impact later-maturing associative cortices important for higher cognition. By mapping the sensitivity of postnatal human brain development to prenatal influences, our findings underline the potency of in utero life in shaping postnatal outcomes of neuroscientific and public health importance.

Compared to what? Early brain overgrowth in autism and the perils of population norms.

BACKGROUND Early brain overgrowth (EBO) in autism spectrum disorder (ASD) is among the best replicated biological associations in psychiatry. Most positive reports have compared head circumference (HC) in ASD (an excellent proxy for early brain size) with well-known reference norms. We sought to reappraise evidence for the EBO hypothesis given 1) the recent proliferation of longitudinal HC studies in ASD, and 2) emerging reports that several of the reference norms used to define EBO in ASD may be biased toward detecting HC overgrowth in contemporary samples of healthy children. METHODS Systematic review of all published HC studies in children with ASD. Comparison of 330 longitudinally gathered HC measures between birth and 18 months from male children with autism (n = 35) and typically developing control subjects (n = 22). RESULTS In systematic review, comparisons with locally recruited control subjects were significantly less likely to identify EBO in ASD than norm-based studies (p < .001). Through systematic review and analysis of new data, we replicate seminal reports of EBO in ASD relative to classical HC norms but show that this overgrowth relative to norms is mimicked by patterns of HC growth age in a large contemporary community-based sample of US children (n ~ 75,000). Controlling for known HC norm biases leaves inconsistent support for a subtle, later emerging and subgroup specific pattern of EBO in clinically ascertained ASD versus community control subjects. CONCLUSIONS The best-replicated aspects of EBO reflect generalizable HC norm biases rather than disease-specific biomarkers. The potential HC norm biases we detail are not specific to ASD research but apply throughout clinical and academic medicine.

Structural brain development between childhood and adulthood: Convergence across four longitudinal samples

Longitudinal studies including brain measures acquired through magnetic resonance imaging (MRI) have enabled population models of human brain development, crucial for our understanding of typical development as well as neurodevelopmental disorders. Brain development in the first two decades generally involves early cortical grey matter volume (CGMV) increases followed by decreases, and monotonic increases in cerebral white matter volume (CWMV). However, inconsistencies regarding the precise developmental trajectories call into question the comparability of samples. This issue can be addressed by conducting a comprehensive study across multiple datasets from diverse populations. Here, we present replicable models for gross structural brain development between childhood and adulthood (ages 8–30 years) by repeating analyses in four separate longitudinal samples (391 participants; 852 scans). In addition, we address how accounting for global measures of cranial/brain size affect these developmental trajectories. First, we found evidence for continued development of both intracranial volume (ICV) and whole brain volume (WBV) through adolescence, albeit following distinct trajectories. Second, our results indicate that CGMV is at its highest in childhood, decreasing steadily through the second decade with deceleration in the third decade, while CWMV increases until mid-to-late adolescence before decelerating. Importantly, we show that accounting for cranial/brain size affects models of regional brain development, particularly with respect to sex differences. Our results increase confidence in our knowledge of the pattern of brain changes during adolescence, reduce concerns about discrepancies across samples, and suggest some best practices for statistical control of cranial volume and brain size in future studies.