Here we have demonstrated the importance of considering trajectories rather than group averages across broad age spans in investigations of brain sexual dimorphism. The finding that sex differences were age-dependent may partially account for discrepant findings of sexual dimorphism in the literature.
Previous work comparing brain growth patterns between males and females has been sparse and limited by small sample sizes or cross-sectional designs. In a cross-sectional sample of 118 healthy children and adolescents growth rates were faster in males than females for total gray and white matter volumes and the area of the corpus callosum (De Bellis et al., 2001
). In this study, however, a linear model was used to describe changes with age, limiting the ability to detect more complex interactions.
The one currently available longitudinal study is based on an earlier sample from the same population reported here(Giedd et al., 1999
). This study was the first to show that brain development follows a nonlinear trajectory, but did not find significant interactions of sex with age. Additionally, the age at which peak volume is reached is somewhat different between the two studies. For example, frontal gray matter volume peaks in the earlier study at 11 years in females and 12.1 in males, while in the current study frontal gray matter peaks at 10.5 and 11.5 for females and males, respectively. The differences in findings are likely related to the pronounced increase in sample size and numbers of longitudinal scans in the current study (145 children and adolescents contributing 243 scans in the previous study, versus 387 subjects contributing 829 scans in the current report), and to the difference in models for longitudinal changes; the previous study was constrained to linear and quadratic models, while many of the structures in the present report are best described by a cubic model. These differences highlight the need for large longitudinal samples to describe the complex developmental changes occurring over this age range.
The proper interpretation of sex differences in brain morphometry given the overall larger brain size in males has been a much-debated issue. Several studies in adults have reported that if total brain size is taken into account, female brains have proportionately more gray matter. It is not clear to what extent these proportional differences are related to scaling issues. It has been proposed that white matter will increase more quickly than gray matter with increasing brain volume, due to the greater volume required by axons associated with a given surface area as they lengthen to cover longer distances between brain regions(Prothero, 1997
). Luders et al. found that sex did not contribute significantly to explaining proportional differences between male and female adults, and that brain size itself was the strongest predictor, supporting the potential relevance of scaling factors (Luders et al., 2002
). Studies across species of widely varying brain sizes have tended to confirm this empirically, finding that the relationship of gray and white matter volumes is exponential rather than linear(Prothero, 1997
; Zhang and Sejnowski, 2000
Our findings here of proportionately greater frontal gray matter in females is consistent with this, although the question remains as to which factors contribute to the larger brain size in males. Male/female brain size differences are often attributed to the greater average height of males (Dekaban and Sadowsky, 1978
; Fausto-Sterling, 1992
). However, this is clearly not the case for pediatric populations, where data from the Center for Disease Control’s National Center for Health Statistics indicate average height for girls is larger from ages 10 to 13.5 and cumulative mean height across the first 15 years of life for boys and girls are within 1% of each other (Kuczmarski et al., 2002
). The decreasing brain volume and increasing height after age 12 further suggest a decoupling of these parameters.
The observation that gray matter volumes peak approximately one to two years earlier in females than males, corresponding to the average age difference at puberty, is suggestive that the switch from progressively increasing to decreasing gray matter volume is associated with pubertal maturation. In this study we did not have pubertal measures and could not examine this relationship directly. There has been debate whether sex hormones serve primarily to activate brain structures formed in earlier stages of development, or if they also have a direct effect on brain structure. Work in rodent models has shown that exposure to pubertal hormones during adolescence has effects on behaviour which persist after the hormones are removed, supporting a long-term effect which could be related to changes in brain structure(Schulz and Sisk, 2006
; Sisk and Foster, 2004
). It has also been shown that administration of hormones before adolescence does not result in the same behavioural changes as when given during adolescence (Meek et al., 1997
), implying that pubertal effects are dependent on interactions with other brain developmental processes. Disentangling the effects of puberty from those associated with chronological age is a difficult task, particularly in humans where direct manipulation of endocrine exposure in healthy adolescents is not ethically feasible. An additional complication is that puberty itself is not an easily measurable process. Different physiologic systems become sexually mature at different rates, and the effect of endocrine factors during puberty is strongly influenced by the timing as well as the magnitude of fluctuating levels, making an accurate description of an adolescent’s degree of physical maturation less than straightforward. Such work is necessary, however, in order to better understand the developmental pathways responsible for the increasing risk of most psychiatric disorders during this period, and the origin of sex-specific differences in symptoms which arise during adolescence in conditions such as Major Depressive Disorder (Dahl, 2004
; Kessler et al., 2005
; Steinberg et al., 2006
Differences in brain size between males and females should not be interpreted as implying any sort of functional advantage or disadvantage. Size/function relationships are complicated by the inverted U shape of developmental trajectories and by the myriad of factors contributing to structure size, including the number and size of neurons and glial cells, packing density, vascularity, and matrix composition. However, an understanding of the sexual dimorphism of brain development, and the factors that influence these trajectories, may have important implications for the field of developmental neuropsychiatry where nearly all of the disorders have different ages of onset, prevalence, and symptomatology between boys and girls.