A Comprehensive Quantitative Genetic Analysis of Cerebral Surface Area in Youth

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.

A Bivariate Twin Study of Cortical Surface Area and Verbal and Nonverbal Intellectual Skills in Adolescence

Understanding the biological basis of cognitive differences between individuals is the goal in human intelligence research. The surface area of the cortex is considered to be a key determinant of human intelligence. Adolescence is a period of development characterized by physiological, emotional, behavioral, and psychosocial changes, which is related to the recombination and optimization of the cerebral cortex, and cognitive ability changes significantly in children and adolescents. This study examined the effects of common genetic and environmental factors between the surface area of the cerebral cortex and intelligence in typical developing adolescents (twins, n = 114, age 12-18 years old). Cortical surface area data were parsed into subregions (i.e., frontal, parietal, occipital, and temporal areas) and intelligence into verbal and nonverbal skills. We found a phenotypic correlation between regional surface areas and verbal intelligence. No correlation was observed between regional surface areas and nonverbal intelligence, except for the occipital lobe and the right hemisphere. In the bivariate twin analyses, the differences in phenotypic correlation between regional surface areas and verbal intelligence were not due to unshared environmental effects or measurement error, but to genetic effects. In summary, the current study has broadened the previous genetic investigations of cognitive ability and cortical surface area.

Toward reframing brain-social dynamics: current assumptions and future challenges

Evolutionary analyses suggest that the human social brain and sociality appeared together. The two fundamental tools that accelerated the concurrent emergence of the social brain and sociality include learning and plasticity. The prevailing core idea is that the primate brain and the cortex in particular became reorganised over the course of evolution to facilitate dynamic adaptation to ongoing changes in physical and social environments. Encouraged by computational or survival demands or even by instinctual drives for living in social groups, the brain eventually learned how to learn from social experience via its massive plastic capacity. A fundamental framework for modeling these orchestrated dynamic responses is that social plasticity relies upon neuroplasticity. In the present article, we first provide a glimpse into the concepts of plasticity, experience, with emphasis on social experience. We then acknowledge and integrate the current theoretical concepts to highlight five key intertwined assumptions within social neuroscience that underlie empirical approaches for explaining the brain-social dynamics. We suggest that this epistemological view provides key insights into the ontology of current conceptual frameworks driving future research to successfully deal with new challenges and possible caveats in favour of the formulation of novel assumptions. In the light of contemporary societal challenges, such as global pandemics, natural disasters, violent conflict, and other human tragedies, discovering the mechanisms of social brain plasticity will provide new approaches to support adaptive brain plasticity and social resilience.

Variability of the Surface Area of the V1, V2, and V3 Maps in a Large Sample of Human Observers

How variable is the functionally defined structure of early visual areas in human cortex and how much variability is shared between twins? Here we quantify individual differences in the best understood functionally defined regions of cortex: V1, V2, V3. The Human Connectome Project 7T Retinotopy Dataset includes retinotopic measurements from 181 subjects (109 female, 72 male), including many twins. We trained four "anatomists" to manually define V1-V3 using retinotopic features. These definitions were more accurate than automated anatomical templates and showed that surface areas for these maps varied more than threefold across individuals. This threefold variation was little changed when normalizing visual area size by the surface area of the entire cerebral cortex. In addition to varying in size, we find that visual areas vary in how they sample the visual field. Specifically, the cortical magnification function differed substantially among individuals, with the relative amount of cortex devoted to central vision varying by more than a factor of 2. To complement the variability analysis, we examined the similarity of visual area size and structure across twins. Whereas the twin sample sizes are too small to make precise heritability estimates (50 monozygotic pairs, 34 dizygotic pairs), they nonetheless reveal high correlations, consistent with strong effects of the combination of shared genes and environment on visual area size. Collectively, these results provide the most comprehensive account of individual variability in visual area structure to date, and provide a robust population benchmark against which new individuals and developmental and clinical populations can be compared.SIGNIFICANCE STATEMENT Areas V1, V2, and V3 are among the best studied functionally defined regions in human cortex. Using the largest retinotopy dataset to date, we characterized the variability of these regions across individuals and the similarity between twin pairs. We find that the size of visual areas varies dramatically (up to 3.5×) across healthy young adults, far more than the variability of the cerebral cortex size as a whole. Much of this variability appears to arise from inherited factors, as we find very high correlations in visual area size between monozygotic twin pairs, and lower but still substantial correlations between dizygotic twin pairs. These results provide the most comprehensive assessment of how functionally defined visual cortex varies across the population to date.

Associations between brain imaging and polygenic scores of mental health and educational attainment in children aged 9-11

Psychiatric disorders are highly heritable and polygenic, and many have their peak onset in late childhood and adolescence, a period of tremendous changes. Although the neurodevelopmental antecedents of mental illness are widely acknowledged, research in youth population cohorts is still scarce, preventing our progress towards the early characterization of these disorders. We included 7,124 children (9-11 years old) from the Adolescent Brain and Cognitive Development Study to map the associations of structural and diffusion brain imaging with common genetic variants and polygenic scores for psychiatric disorders and educational attainment. We used principal component analysis to derive imaging components, and calculated their heritability. We then assessed the relationship of imaging components with genetic and clinical psychiatric risk with univariate models and Canonical correlation analysis (CCA). Most imaging components had moderate heritability. Univariate models showed limited evidence and small associations of polygenic scores with brain structure at this age. CCA revealed two significant modes of covariation. The first mode linked higher polygenic scores for educational attainment with less externalizing problems and larger surface area. The second mode related higher polygenic scores for schizophrenia, bipolar disorder, and autism spectrum disorder to higher global cortical thickness, smaller white matter volumes of the fornix and cingulum, larger medial occipital surface area and smaller surface area of lateral and medial temporal regions. While cross-validation suggested limited generalizability, our results highlight the potential of multivariate models to better understand the transdiagnostic and distributed relationships between mental health and brain structure in late childhood.

Cingulate and hippocampal subregion abnormalities in combat-exposed veterans with PTSD

BACKGROUND

The hippocampus and cingulate gyrus are strongly interconnected brain regions that have been implicated in the neurobiology of post-traumatic stress disorder (PTSD). These brain structures are comprised of functionally distinct subregions that may contribute to the expression of PTSD symptoms or associated cardio-metabolic markers, but have not been well investigated in prior studies.

METHODS

Two divisions of the cingulate cortex (i.e., rostral and caudal) and 11 hippocampal subregions were investigated in 22 male combat-exposed veterans with PTSD and 22 male trauma-exposed veteran controls (TC). Cardio-metabolic measures included cholesterol, body mass index, and mean arterial pressure.

RESULTS

Individuals with PTSD had less caudal cingulate area compared to TC even after controlling for caudal cingulate thickness. Total hippocampus volume was lower in PTSD compared to TC, accounted for by differences in CA1-CA4, granule cell layer of the dentate gyrus, molecular layer, and subiculum. Individuals with PTSD had higher mean arterial pressure compared to TC, which correlated with hippocampus volume only in the PTSD group.

LIMITATIONS

Sample size, cross-sectional analysis, no control for medications and findings limited to males.

CONCLUSIONS

These data demonstrate preferential involvement of caudal cingulate area (vs. thickness) and hippocampus subregions in PTSD. The inverse association between hippocampus volume and mean arterial pressure may contribute to accelerated aging known to be associated with PTSD.

Associations Between Traumatic Stress, Brain Volumes and Post-traumatic Stress Disorder Symptoms in Children: Data from the ABCD Study

Reduced volumes in brain regions of interest (ROIs), primarily from adult samples, are associated with posttraumatic stress disorder (PTSD). We extended this work to children using data from the Adolescent Brain Cognitive Development (ABCD) Study® (N = 11,848; Mage = 9.92). Structural equation modeling and an elastic-net (EN) machine-learning approach were used to identify potential effects of traumatic events (TEs) on PTSD symptoms (PTSDsx) directly, and indirectly via the volumes 300 subcortical and cortical ROIs. We then estimated the genetic and environmental variation in the phenotypes. TEs were directly associated with PTSDsx (r = 0.92) in children, but their indirect effects (r < 0.0004)-via the volumes of EN-identified subcortical and cortical ROIs-were negligible at this age. Additive genetic factors explained a modest proportion of the variance in TEs (23.4%) and PTSDsx (21.3%), and accounted for most of the variance of EN-identified volumes of four of the five subcortical (52.4-61.8%) three of the nine cortical ROIs (46.4-53.3%) and cerebral white matter in the left hemisphere (57.4%). Environmental factors explained most of the variance in TEs (C = 61.6%, E = 15.1%), PTSDsx (residual-C = 18.4%, residual-E = 21.8%), right lateral ventricle (C = 15.2%, E = 43.1%) and six of the nine EN-identified cortical ROIs (C = 4.0-13.6%, E = 56.7-74.8%). There is negligible evidence that the volumes of brain ROIs are associated with the indirect effects of TEs on PTSDsx at this age. Overall, environmental factors accounted for more of the variation in TEs and PTSDsx. Whereas additive genetic factors accounted for most of the variability in the volumes of a minority of cortical and in most of subcortical ROIs.

Genetic Influences on Longitudinal Trajectories of Cortical Thickness and Surface Area during the First 2 Years of Life

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.

A simple permutation-based test of intermodal correspondence

Many key findings in neuroimaging studies involve similarities between brain maps, but statistical methods used to measure these findings have varied. Current state-of-the-art methods involve comparing observed group-level brain maps (after averaging intensities at each image location across multiple subjects) against spatial null models of these group-level maps. However, these methods typically make strong and potentially unrealistic statistical assumptions, such as covariance stationarity. To address these issues, in this article we propose using subject-level data and a classical permutation testing framework to test and assess similarities between brain maps. Our method is comparable to traditional permutation tests in that it involves randomly permuting subjects to generate a null distribution of intermodal correspondence statistics, which we compare to an observed statistic to estimate a p-value. We apply and compare our method in simulated and real neuroimaging data from the Philadelphia Neurodevelopmental Cohort. We show that our method performs well for detecting relationships between modalities known to be strongly related (cortical thickness and sulcal depth), and it is conservative when an association would not be expected (cortical thickness and activation on the n-back working memory task). Notably, our method is the most flexible and reliable for localizing intermodal relationships within subregions of the brain and allows for generalizable statistical inference.

Twin studies to GWAS: there and back again

The field of human behavioral genetics has come full circle. It began by using twin/family studies to estimate the relative importance of genetic and environmental influences. As large-scale genotyping became cost-effective, genome-wide association studies (GWASs) yielded insights about the nature of genetic influences and new methods that use GWAS data to estimate heritability and genetic correlations invigorated the field. Yet these newer GWAS methods have not replaced twin/family studies. In this review, we discuss the strengths and weaknesses of the two approaches with respect to characterizing genetic and environmental influences, measurement of behavioral phenotypes, and evaluation of causal models, with a particular focus on cognitive neuroscience. This discussion highlights how twin/family studies and GWAS complement and mutually reinforce one another.

X-chromosome influences on neuroanatomical variation in humans

The X-chromosome has long been hypothesized to have a disproportionate influence on the brain based on its enrichment for genes that are expressed in the brain and associated with intellectual disability. Here, we verify this hypothesis through partitioned heritability analysis of X-chromosome influences (XIs) on human brain anatomy in 32,256 individuals from the UK Biobank. We first establish evidence for dosage compensation in XIs on brain anatomy-reflecting larger XIs in males compared to females, which correlate with regional sex-biases in neuroanatomical variance. XIs are significantly larger than would be predicted from X-chromosome size for the relative surface area of cortical systems supporting attention, decision-making and motor control. Follow-up association analyses implicate X-linked genes with pleiotropic effects on cognition. Our study reveals a privileged role for the X-chromosome in human neurodevelopment and urges greater inclusion of this chromosome in future genome-wide association studies.

Distinct Regionalization Patterns of Cortical Morphology are Associated with Cognitive Performance Across Different Domains

Cognitive performance in children is predictive of academic and social outcomes; therefore, understanding neurobiological mechanisms underlying individual differences in cognition during development may be important for improving quality of life. The belief that a single, psychological construct underlies many cognitive processes is pervasive throughout society. However, it is unclear if there is a consistent neural substrate underlying many cognitive processes. Here, we show that a distributed configuration of cortical surface area and apparent thickness, when controlling for global imaging measures, is differentially associated with cognitive performance on different types of tasks in a large sample (N = 10 145) of 9-11-year-old children from the Adolescent Brain and Cognitive DevelopmentSM (ABCD) study. The minimal overlap in these regionalization patterns of association has implications for competing theories about developing intellectual functions. Surprisingly, not controlling for sociodemographic factors increased the similarity between these regionalization patterns. This highlights the importance of understanding the shared variance between sociodemographic factors, cognition and brain structure, particularly with a population-based sample such as ABCD.

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.

Brain structural trajectories in youth at familial risk for schizophrenia or bipolar disorder according to development of psychosis spectrum symptoms

BACKGROUND

The evaluation of child and adolescent offspring of patients with schizophrenia (SzO) or bipolar disorder (BpO) may help understand changes taking place in the brain in individuals at heightened risk for disease during a key developmental period.

METHODS

One hundred twenty-eight individuals (33 SzO and 46 BpO, considered jointly as 'Familial High Risk' (FHR), and 49 controls) aged 6-17 years underwent clinical, cognitive and neuroimaging assessment at baseline, 2- and 4-year follow-up. Twenty FHR participants (11 SzO and 9 BpO) developed psychotic spectrum symptoms during follow-up, while 59 FHR participants did not. Magnetic resonance imaging was performed on a 3Tesla scanner; cortical surface reconstruction was applied to measure cortical thickness, surface area and grey matter volume.

RESULTS

FHR participants who developed psychotic spectrum symptoms over time showed greater time-related mean cortical thinning than those who did not and than controls. By subgroups, this effect was present in both BpO and SzO in the occipital cortex. At baseline, FHR participants who developed psychotic spectrum symptoms over time had smaller total surface area and grey matter volume than those who did not and than controls. Over time, all FHR participants showed less longitudinal decrease in surface area than controls. In those who developed psychotic spectrum symptoms over time, this effect was driven by BpO, while in those who did not, this was due to SzO, who also showed less grey matter volume reduction.

CONCLUSION

The emergence of psychotic spectrum symptoms in FHR was indexed by smaller cross-sectional surface area and progressive cortical thinning. Relative preservation of surface area over time may signal different processes according to familial risk. These findings lay the foundation for future studies aimed at stratification of FHR youth.

The neural basis of intelligence in fine-grained cortical topographies

Intelligent thought is the product of efficient neural information processing, which is embedded in fine-grained, topographically organized population responses and supported by fine-grained patterns of connectivity among cortical fields. Previous work on the neural basis of intelligence, however, has focused on coarse-grained features of brain anatomy and function because cortical topographies are highly idiosyncratic at a finer scale, obscuring individual differences in fine-grained connectivity patterns. We used a computational algorithm, hyperalignment, to resolve these topographic idiosyncrasies and found that predictions of general intelligence based on fine-grained (vertex-by-vertex) connectivity patterns were markedly stronger than predictions based on coarse-grained (region-by-region) patterns. Intelligence was best predicted by fine-grained connectivity in the default and frontoparietal cortical systems, both of which are associated with self-generated thought. Previous work overlooked fine-grained architecture because existing methods could not resolve idiosyncratic topographies, preventing investigation where the keys to the neural basis of intelligence are more likely to be found.

The Heritability of Cortical Folding: Evidence from the Human Connectome Project

The mechanisms underlying cortical folding are incompletely understood. Prior studies have suggested that individual differences in sulcal depth are genetically mediated, with deeper and ontologically older sulci more heritable than others. In this study, we examine FreeSurfer-derived estimates of average convexity and mean curvature as proxy measures of cortical folding patterns using a large (N = 1096) genetically informative young adult subsample of the Human Connectome Project. Both measures were significantly heritable near major sulci and primary fissures, where approximately half of individual differences could be attributed to genetic factors. Genetic influences near higher order gyri and sulci were substantially lower and largely nonsignificant. Spatial permutation analysis found that heritability patterns were significantly anticorrelated to maps of evolutionary and neurodevelopmental expansion. We also found strong phenotypic correlations between average convexity, curvature, and several common surface metrics (cortical thickness, surface area, and cortical myelination). However, quantitative genetic models suggest that correlations between these metrics are largely driven by nongenetic factors. These findings not only further our understanding of the neurobiology of gyrification, but have pragmatic implications for the interpretation of heritability maps based on automated surface-based measurements.

Sex chromosome aneuploidy alters the relationship between neuroanatomy and cognition

Sex chromosome aneuploidy (SCA) increases the risk for cognitive deficits, and confers changes in regional cortical thickness (CT) and surface area (SA). Neuroanatomical correlates of inter-individual variation in cognitive ability have been described in health, but are not well-characterized in SCA. Here, we modeled relationships between general cognitive ability (estimated using full-scale IQ [FSIQ] from Wechsler scales) and regional estimates of SA and CT (from structural MRI scans) in both aneuploid (28 XXX, 55 XXY, 22 XYY, 19 XXYY) and typically-developing euploid (79 XX, 85 XY) individuals. Results indicated widespread decoupling of normative anatomical-cognitive relationships in SCA: we found five regions where SCA significantly altered SA-FSIQ relationships, and five regions where SCA significantly altered CT-FSIQ relationships. The majority of areas were characterized by the presence of positive anatomy-IQ relationships in health, but no or slightly negative anatomy-IQ relationships in SCA. Disrupted anatomical-cognitive relationships generalized from the full cohort to karyotypically defined subcohorts (i.e., XX-XXX; XY-XYY; XY-XXY), demonstrating continuity across multiple supernumerary SCA conditions. As the first direct evidence of altered regional neuroanatomical-cognitive relationships in supernumerary SCA, our findings shed light on potential genetic and structural correlates of the cognitive phenotype in SCA, and may have implications for other neurogenetic disorders.

Genetic and Environmental Influences on Lobar Brain Structures in Twins With Autism

This investigation examined whether the variation of cerebral structure is associated with genetic or environmental factors in children with autism spectrum disorder (ASD) compared with typically developing (TD) controls. T1-weighted magnetic resonance imaging scans were obtained from twin pairs (aged 6-15 years) in which at least one twin was diagnosed with ASD or both were TD. Good quality data were available from 30 ASD, 18 discordant, and 34 TD pairs (n = 164). Structural measures (volume, cortical thickness, and surface area) were generated with FreeSurfer, and ACE modeling was completed. Lobar structures were primarily genetically mediated in TD twins (a2 = 0.60-0.89), except thickness of the temporal (a2 = 0.33 [0.04, 0.63]) and occipital lobes (c2 = 0.61 [0.45, 0.77]). Lobar structures were also predominantly genetically mediated in twins with ASD (a2 = 0.70-1.00); however, thickness of the frontal (c2 = 0.81 [0.71, 0.92]), temporal (c2 = 0.77 [0.60, 0.93]), and parietal lobes (c2 = 0.87 [0.77, 0.97]), and frontal gray matter (GM) volume (c2 = 0.79 [0.63, 0.95]), were associated with environmental factors. Conversely, occipital thickness (a2 = 0.93 [0.75, 1.11]) did not exhibit the environmental contributions that were found in controls. Differences in GM volume were associated with social communication impairments for the frontal (r = 0.52 [0.18, 0.75]), temporal (r = 0.61 [0.30, 0.80]), and parietal lobes (r = 0.53 [0.19, 0.76]). To our knowledge, this is the first investigation to suggest that environmental factors influence GM to a larger extent in children with ASD, especially in the frontal lobe.

The genetics of cortical myelination in young adults and its relationships to cerebral surface area, cortical thickness, and intelligence: A magnetic resonance imaging study of twins and families

The cerebral cortex contains a significant quantity of intracortical myelin, but the genetics of cortical myelination (CM) in humans is not well understood. Relatively novel MRI-derived measures now enable the investigation of cortical myelination in large samples. In this study, we use a genetically-informative neuroimaging sample of 1096 young adult subjects from the Human Connectome Project in order to investigate genetic and environmental variation in CM and its relationships with cerebral surface area (SA) and cortical thickness (CT). We found that genetic factors account for approximately 50% of the observed individual differences in mean cortical myelin, 75% of the variation in total SA, and 85% of the variance in global mean CT. Although significant genetic influences were found throughout the cortex, both CM and SA demonstrated a posterior predominance, with disproportionately strong effects in the parietal and occipital lobes and significantly overlapping heritability maps (p < 0.001). Yet despite showing similar spatial heritability patterns, we found evidence that CM is genetically independent from SA at both global and vertex levels; genetically-mediated relationships between CM and CT were similarly small in magnitude. We also found small but statistically significant genetic associations between NIH Toolbox Total Cognition score and CM in the temporal lobe and insula. SA-cognition and CT-cognition correlations were less widespread compared to CM and both patterns were similar to those reported in prior studies.