Sexual dimorphism of brain developmental trajectories during childhood and adolescence

Abstract

Human total brain size is consistently reported to be ~8-10% larger in males, although consensus on regionally-specific differences is weak. Here, in the largest longitudinal pediatric neuroimaging study reported to date (829 scans from 387 subjects, ages 3 to 27 years), we demonstrate the importance of examining size-by-age trajectories of brain development rather than group averages across broad age ranges when assessing sexual dimorphism. Using magnetic resonance imaging (MRI) we found robust male/female differences in the shapes of trajectories with total cerebral volume peaking at age 10.5 in females and 14.5 in males. White matter increases throughout this 24 year period with males having a steeper rate of increase during adolescence. Both cortical and subcortical gray matter trajectories follow an inverted U shaped path with peak sizes 1 to 2 years earlier in females. These sexually dimorphic trajectories confirm the importance of longitudinal data in studies of brain development and underline the need to consider sex matching in studies of brain development.

Brain SCALE: Brain Structure and Cognition: an Adolescent Longitudinal Twin Study into the Genetic Etiology of Individual Differences

“…The relatively large increase in cerebellar volume observed between age 9 and 12 is consistent with previous findings that the cerebellum is maturing at a later age than the cerebrum (Lenroot et al, 2007;Tiemeier et al, 2010). It can also be speculated that, in this sample, the relatively large increase in cerebellar volume that was found at age 9 is partly the result of compensating for the effect of preterm birth.…”

Differences in genetic and environmental influences on the human cerebral cortex associated with development during childhood and adolescence

“…The model also contained parameters to account for the effects of age and sex on mean cortical thickness, which were estimated concurrently with the variance components. Sex effects were estimated using a linear model, and age was estimated using a cubic model based on prior evidence of age interactions with cortical thickness [Lenroot et al, 2005]. Optimum model fit was determined using maximum likelihood [Edwards, 1972], which produces unbiased parameter estimates and allows the identification of statistically significant parameters in the model [Neale and Miller, 1997].…”

A social neuroscience perspective on adolescent risk-taking

“…Unlike the synaptic pruning of the prefrontal areas, which takes place early adolescence, myelination is ongoing well into the second decade of life and perhaps beyond (Lenroot, Gogtay, Greenstein, Wells, Wallace, Clasen, et al, 2007). Improved connectivity within the prefrontal cortex should be associated with subsequent improvements in higher-order functions subserved by multiple prefrontal areas, including many aspects of executive function, such as response inhibition, planning ahead, weighing risks and rewards, and the simultaneous consideration of multiple sources of information.…”