Imaging studies of cerebral volumes often adjust for factors such as age that may confound between-subject comparisons. However the use of nuisance covariates in imaging studies is inconsistent, which can make interpreting results across studies difficult. Using magnetic resonance images of 78 healthy controls we assessed the effects of age, gender, head size and scanner upgrade on region of interest (ROI) volumetry, cortical thickness and voxel-based morphometric (VBM) measures. We found numerous significant associations between these variables and volumetric measures: cerebral volumes and cortical thicknesses decreased with increasing age, men had larger volumes and smaller thicknesses than women, and increasing head size was associated with larger volumes. The relationships between most ROIs and head size volumes were non-linear. With age, gender, head size and upgrade in one model we found that volumes and thicknesses decreased with increasing age, women had larger volumes than men (VBM, whole-brain and white matter volumes), increasing head size was associated with larger volumes but not cortical thickness, and scanner upgrade had an effect on thickness and some volume measures. The effects of gender on cortical thickness when adjusting for head size, age and upgrade showed some non-significant effect (women>men), whereas the independent effect of head size showed little pattern. We conclude that age and head size should be considered in ROI volume studies, age, gender and upgrade should be considered for cortical thickness studies and all variables require consideration for VBM analyses. Division of all volumes by head size is unlikely to be adequate owing to their non-proportional relationship.
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Whereas a categorical difference in the genitals has always been acknowledged, the question of how far these categories extend into human biology is still not resolved. Documented sex/gender differences in the brain are often taken as support of a sexually dimorphic view of human brains ("female brain" or "male brain"). However, such a distinction would be possible only if sex/gender differences in brain features were highly dimorphic (i.e., little overlap between the forms of these features in males and females) and internally consistent (i.e., a brain has only "male" or only "female" features). Here, analysis of MRIs of more than 1,400 human brains from four datasets reveals extensive overlap between the distributions of females and males for all gray matter, white matter, and connections assessed. Moreover, analyses of internal consistency reveal that brains with features that are consistently at one end of the "maleness-femaleness" continuum are rare. Rather, most brains are comprised of unique "mosaics" of features, some more common in females compared with males, some more common in males compared with females, and some common in both females and males. Our findings are robust across sample, age, type of MRI, and method of analysis. These findings are corroborated by a similar analysis of personality traits, attitudes, interests, and behaviors of more than 5,500 individuals, which reveals that internal consistency is extremely rare. Our study demonstrates that, although there are sex/gender differences in the brain, human brains do not belong to one of two distinct categories: male brain/female brain.