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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

The role of genetics in driving intracortical relationships is an important question that has rarely been studied in humans. In particular, there are no extant high-resolution imaging studies on genetic covariance. In this article, we describe a novel method that combines classical quantitative genetic methodologies for variance decomposition with recently developed semi-multivariate algorithms for high-resolution measurement of phenotypic covariance. Using these tools, we produced correlational maps of genetic and environmental (i.e. nongenetic) relationships between several regions of interest and the cortical surface in a large pediatric sample of 600 twins, siblings, and singletons. These analyses demonstrated high, fairly uniform, statistically significant genetic correlations between the entire cortex and global mean cortical thickness. In agreement with prior reports on phenotypic covariance using similar methods, we found that mean cortical thickness was most strongly correlated with association cortices. However, the present study suggests that genetics plays a large role in global brain patterning of cortical thickness in this manner. Further, using specific gyri with known high heritabilities as seed regions, we found a consistent pattern of high bilateral genetic correlations between structural homologues, with environmental correlations more restricted to the same hemisphere as the seed region, suggesting that interhemispheric covariance is largely genetically mediated. These findings are consistent with the limited existing knowledge on the genetics of cortical variability as well as our prior multivariate studies on cortical gyri.

An important component of brain mapping is an understanding of the relationships between neuroanatomic structures, as well as the nature of shared causal factors. Prior twin studies have demonstrated that much of individual differences in human anatomy are caused by genetic differences, but information is limited on whether different structures share common genetic factors. We performed a multivariate statistical genetic analysis on volumetric MRI measures (cerebrum, cerebellum, lateral ventricles, corpus callosum, thalamus, and basal ganglia) from a pediatric sample of 326 twins and 158 singletons. Our results suggest that the great majority of variability in cerebrum, cerebellum, thalamus and basal ganglia is determined by a single genetic factor. Though most (75%) of the variability in corpus callosum was explained by additive genetic effects these were largely independent of other structures. We also observed relatively small but significant environmental effects common to multiple neuroanatomic regions, particularly between thalamus, basal ganglia, and lateral ventricles. These findings are concordant with prior volumetric twin studies and support radial models of brain evolution.

Williams syndrome (WS), a neurogenetic developmental disorder, is characterized by a rare fractionation of higher cortical functioning: selective preservation of certain complex faculties (language, music, face processing, and sociability) in contrast to marked and severe deficits in nearly every other cognitive domain (reasoning, spatial ability, motor coordination, arithmetic, problem solving). WS people are also known to suffer from hyperacusis and to experience heightened emotional reactions to music and certain classes of noise. We used functional magnetic resonance imaging to examine the neural basis of auditory processing of music and noise in WS patients and age-matched controls and found strikingly different patterns of neural organization between the groups. Those regions supporting music and noise processing in normal subjects were found not to be consistently activated in the WS participants (e.g., superior temporal and middle temporal gyri). Instead, the WS participants showed significantly reduced activation in the temporal lobes coupled with significantly greater activation in the right amygdala. In addition, WS participants (but not controls) showed a widely distributed network of activation in cortical and subcortical structures, including the brain stem, during music processing. Taken together with previous ERP and cytoarchitectonic studies, this first published report of WS using fMRI provides additional evidence of a different neurofunctional organization in WS people than normal people, which may help to explain their atypical reactions to sound. These results constitute an important first step in drawing out the links between genes, brain, cognition, and behavior in Williams syndrome.