Project description:Gyrification is a fundamental property of the human cortex that is increasingly studied by basic and clinical neuroscience. However, it remains unclear if and how the global architecture of cortical folding varies with 3 interwoven sources of anatomical variation: brain size, sex, and sex chromosome dosage (SCD). Here, for 375 individuals spanning 7 karyotype groups (XX, XY, XXX, XYY, XXY, XXYY, XXXXY), we use structural neuroimaging to measure a global sulcation index (SI, total sulcal/cortical hull area) and both determinants of sulcal area: total sulcal length and mean sulcal depth. We detail large and patterned effects of sex and SCD across all folding metrics, but show that these effects are in fact largely consistent with the normative scaling of cortical folding in health: larger human brains have disproportionately high SI due to a relative expansion of sulcal area versus hull area, which arises because disproportionate sulcal lengthening overcomes a lack of proportionate sulcal deepening. Accounting for these normative allometries reveals 1) brain size-independent sulcal lengthening in males versus females, and 2) insensitivity of overall folding architecture to SCD. Our methodology and findings provide a novel context for future studies of human cortical folding in health and disease.
Project description:Recent progress in deciphering mechanisms of human brain cortical folding leave unexplained whether spatially patterned genetic influences contribute to this folding. High-resolution in vivo brain MRI can be used to estimate genetic correlations (covariability due to shared genetic factors) in interregional cortical thickness, and biomechanical studies predict an influence of cortical thickness on folding patterns. However, progress has been hampered because shared genetic influences related to folding patterns likely operate at a scale that is much more local (<1 cm) than that addressed in prior imaging studies. Here, we develop methodological approaches to examine local genetic influences on cortical thickness and apply these methods to two large, independent samples. We find that such influences are markedly heterogeneous in strength, and in some cortical areas are notably stronger in specific orientations relative to gyri or sulci. The overall, phenotypic local correlation has a significant basis in shared genetic factors and is highly symmetric between left and right cortical hemispheres. Furthermore, the degree of local cortical folding relates systematically with the strength of local correlations, which tends to be higher in gyral crests and lower in sulcal fundi. The relationship between folding and local correlations is stronger in primary sensorimotor areas and weaker in association areas such as prefrontal cortex, consistent with reduced genetic constraints on the structural topology of association cortex. Collectively, our results suggest that patterned genetic influences on cortical thickness, measurable at the scale of in vivo MRI, may be a causal factor in the development of cortical folding.
Project description:The folding of the cortex in mammalian brains across species has recently been shown to follow a universal scaling law that can be derived from a simple physics model. However, it was yet to be determined whether this law also applies to the morphological diversity of different individuals in a single species, in particular with respect to factors, such as age, sex, and disease. To this end, we derived and investigated the cortical morphology from magnetic resonance images (MRIs) of over 1,000 healthy human subjects from three independent public databases. Our results show that all three MRI datasets follow the scaling law obtained from the comparative neuroanatomical data, which strengthens the case for the existence of a common mechanism for cortical folding. Additionally, for comparable age groups, both male and female brains scale in exactly the same way, despite systematic differences in size and folding. Furthermore, age introduces a systematic shift in the offset of the scaling law. In the model, this shift can be interpreted as changes in the mechanical forces acting on the cortex. We also applied this analysis to a dataset derived from comparable cohorts of Alzheimer's disease patients and healthy subjects of similar age. We show a systematically lower offset and a possible change in the exponent for Alzheimer's disease subjects compared with the control cohort. Finally, we discuss implications of the changes in offset and exponent in the data and relate it to existing literature. We, thus, provide a possible mechanistic link between previously independent observations.
Project description:The brain's mature functional network architecture has been extensively studied but the early emergence of the brain's network organization remains largely unknown. In this study, leveraging a large sample (143 subjects) with longitudinal rsfMRI scans (333 datasets), we aimed to characterize the important developmental process of the brain's functional network architecture during the first 2 years of life. Based on spatial independent component analysis and longitudinal linear mixed effect modeling, our results unveiled the detailed topology and growth trajectories of nine cortical functional networks. Within networks, our findings clearly separated the brains networks into two categories: primary networks were topologically adult-like in neonates while higher-order networks were topologically incomplete and isolated in neonates but demonstrated consistent synchronization during the first 2 years of life (connectivity increases 0.13-0.35). Between networks, our results demonstrated both network-level connectivity decreases (-0.02 to -0.64) and increases (0.05-0.18) but decreasing connections (n = 14) dominated increasing ones (n = 5). Finally, significant sex differences were observed with boys demonstrating faster network-level connectivity increases among the two frontoparietal networks (growth rate was 1.63e-4 per day for girls and 2.69e-4 per day for boys, p < 1e-4). Overall, our study delineated the development of the whole brain functional architecture during the first 2 years of life featuring significant changes of both within- and between-network interactions.
Project description:The thickness of the cerebral cortical sheet and its surface area are highly heritable traits thought to have largely distinct polygenic architectures. Despite large-scale efforts, the majority of their genetic determinants remain unknown. Our ability to identify causal genetic variants can be improved by employing brain measures that better map onto the biology we seek to understand. Such measures may have fewer variants but with larger effects, that is, lower polygenicity and higher discoverability. Using Gaussian mixture modeling, we estimated the number of causal variants shared between mean cortical thickness and total surface area, as well as the polygenicity and discoverability of regional measures. We made use of UK Biobank data from 30 880 healthy White European individuals (mean age 64.3, standard deviation 7.5, 52.1% female). We found large genetic overlap between total surface area and mean thickness, sharing 4016 out of 7941 causal variants. Regional surface area was more discoverable (P = 2.6 × 10-6) and less polygenic (P = 0.004) than regional thickness measures. These findings may serve as a roadmap for improved future GWAS studies; knowledge of which measures are most discoverable may be used to boost identification of genetic predictors and thereby gain a better understanding of brain morphology.
Project description:We evaluated 22 measures of cortical folding, 20 derived from local curvature (curvature-based measures) and two based on other features (sulcal depth and gyrification index), for their capacity to distinguish between normal and aberrant cortical development. Cortical surfaces were reconstructed from 12 term-born control and 63 prematurely-born infants. Preterm infants underwent 2-4 MR imaging sessions between 27 and 42weeks postmenstrual age (PMA). Term infants underwent a single MR imaging session during the first postnatal week. Preterm infants were divided into two groups. One group (38 infants) had no/minimal abnormalities on qualitative assessment of conventional MR images. The second group (25 infants) consisted of infants with injury on conventional MRI at term equivalent PMA. For both preterm infant groups, all folding measures increased or decreased monotonically with increasing PMA, but only sulcal depth and gyrification index differentiated preterm infants with brain injury from those without. We also compared scans obtained at term equivalent PMA (36-42weeks) for all three groups. No curvature-based measured distinguished between the groups, whereas sulcal depth distinguished term control from injured preterm infants and gyrification index distinguished all three groups. When incorporating total cerebral volume into the statistical model, sulcal depth no longer distinguished between the groups, though gyrification index distinguished between all three groups and positive shape index distinguished between the term control and uninjured preterm groups. We also analyzed folding measures averaged over brain lobes separately. These results demonstrated similar patterns to those obtained from the whole brain analyses. Overall, though the curvature-based measures changed during this period of rapid cerebral development, they were not sensitive for detecting the differences in folding associated with brain injury and/or preterm birth. In contrast, gyrification index was effective in differentiating these groups.
Project description: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.
Project description:Folding of the primate brain cortex allows for improved neural processing power by increasing cortical surface area for the allocation of neurons. The arrangement of folds (sulci) and ridges (gyri) across the cerebral cortex is thought to reflect the underlying neural network. Gyrification, an adaptive trait with a unique evolutionary history, is affected by genetic factors different from those affecting brain volume. Using a large pedigreed population of ?1000 Papio baboons, we address critical questions about the genetic architecture of primate brain folding, the interplay between genetics, brain anatomy, development, patterns of cortical-cortical connectivity, and gyrification's potential for future evolution. Through Mantel testing and cluster analyses, we find that the baboon cortex is quite evolvable, with high integration between the genotype and phenotype. We further find significantly similar partitioning of variation between cortical development, anatomy, and connectivity, supporting the predictions of tension-based models for sulcal development. We identify a significant, moderate degree of genetic control over variation in sulcal length, with gyrus-shape features being more susceptible to environmental effects. Finally, through QTL mapping, we identify novel chromosomal regions affecting variation in brain folding. The most significant QTL contain compelling candidate genes, including gene clusters associated with Williams and Down syndromes. The QTL distribution suggests a complex genetic architecture for gyrification with both polygeny and pleiotropy. Our results provide a solid preliminary characterization of the genetic basis of primate brain folding, a unique and biomedically relevant phenotype with significant implications in primate brain evolution.
Project description:The developmental principles that establish the columnar edifice of the cerebral cortex underlie its evolution and dictate its physiological operations and cognitive capacity. This article contrasts the initial discoveries made by Ramón y Cajal and his contemporaries, based on the ingenious interpretation of neuronal shapes and their relationships using the Golgi method, with new insights based on the application of the most advanced methods of molecular biology and genetics. We can now propose a realistic model of how the sequence of gene expression, cascade of multiple molecular pathways and cell-cell interactions establish the number of neurons, guide their migration and allocation into proper regions and determine their differentiation into specific phenotypes that establish specific synaptic connections. The findings obtained from different levels of analyses sustain the radial unit hypothesis as a useful framework for understanding the mechanisms of cortical development and its evolution as an organ of thought.
Project description:Different cortical regions vary systematically in their morphology. Here we investigate if the scaling law of cortical morphology, which was previously demonstrated across both human subjects and mammalian species, still holds within a single cortex across different brain regions. By topologically correcting for regional curvature, we could analyse how different morphological parameters co-vary within single cortices. We show in over 1500 healthy individuals that, despite their morphological diversity, regions of the same cortex obey the same universal scaling law, and age morphologically at similar rates. In Alzheimer's disease, we observe a premature ageing in the morphological parameters that was nevertheless consistent with the scaling law. The premature ageing effect was most dramatic in the temporal lobe. Thus, while morphology can vary substantially across cortical regions, subjects, and species, it always does so in accordance with a common scaling law, suggesting that the underlying processes driving cortical gyrification are universal.