Multivariate analyses allow assessment of the degree to which the same genetic or environmental factors contribute to multiple neuroanatomic structures. Like the univariate variables, these interstructure correlations can be parceled into relationships of either genetic or environmental origin. This knowledge is vitally important for interpretation of most of the twin data, including understanding the impact of genes that may affect distributed neural networks, as well as interventions that may have global brain impacts. Shared effects account for more of the variance than structure-specific effects, with a single genetic factor accounting for 60% of variability in cortical thickness (Schmitt et al., 2007). Six factors account for 58% of the remaining variance, with five groups of structures strongly influenced by the same underlying genetic factors. These findings are consistent with the radial unit hypothesis of neocortical expansion proposed by Rakic (Rakic, 1995) and with hypotheses that global, genetically mediated differences in cell division were the driving force behind interspecies differences in total brain volume (Darlington et al., 1999; Finlay and Darlington, 1995; Fishell, 1997). Expanding the entire brain when only specific functions
