The current study compared sex differences in the brain examining gray matter volume in two independent cohorts. We found a high reproducibility of effects between cohorts and therefore pooled the data for a unified analysis, which resulted in a well-powered sample (n = 2,838). Since this study did not directly measure associations between brain structure and behavior interpretations drawn between brain structure and behavioral implications are speculative.

Correspondence with previous findings

In our study, the most compelling differences between cortical GMV of men and women laid in the larger prefrontal GMV in women and larger anterior-medial temporal GMV in men. This confirms results of Chen and colleagues7 describing regional GMV differences in an cohort of 411 middle-aged healthy participants (44–48 years) with men > women in midbrain, left inferior temporal gyrus, right occipital lingual gyrus, right middle temporal gyrus, and both cerebellar hemispheres and women > men in dorsal anterior, posterior and ventral cingulate cortices, and right inferior parietal lobule. In addition, the present study largely confirmed the meta-analytic findings by Ruigrok and colleagues2. That is, we detected larger GMV in women in the inferior and middle frontal gyrus, the ACC, the right OFC, the right insula, the lateral occipital cortex, the Heschl gyrus, the thalamus, the precuneus, but not in the planum temporale/Wernicke’s area.

GMV-differences in subcortical structures (parahippocampus, hippocampus, thalamus)

For the parahippocampus, Ruigrok and colleagues2 reported larger GMV posteriorly in women, and larger GMV anteriorly in men. Interestingly, the parahippocampus showed the strongest sex effect (men > women) in the present study and we did not observe any effect for women > men in this area. For the parahippocampal gyrus, Ritchie and colleagues5 reported that females showed relatively higher thickness but males showed relatively higher volume and surface area.

In the current study, the GMV in the anterior-inferior hippocampus was larger in men than in women. However, testing the interaction of age and sex, this held true only for the younger part of the sample (median split, (<53 years), but not for the older (≥53 years). In contrast, older women showed increased left posterior-superior hippocampal GMV compared to older men. It might well be the case that for women hormonal changes after menopause modulate these specific hippocampal GMV differences in comparison to men11. Additional information on this effect is provided in the Supplement. In accordance with our study (but measured for the complete structure volume), Ritchie and colleagues5 (mean age 62 years) reported no sex differences in hippocampal volume after correction for total brain volume. Our results are also corroborated by the meta-analysis of Ruigrok et al.2, showing increased hippocampal volume bilaterally for men.

We found larger GMV of the thalamus in men compared to women in contrast to Ruigrok and colleagues2 (increased thalamic GMV in females), except for the left thalamus, where we found a larger GMV for the posterior part in women. This demonstrates the strength of a voxelwise analysis enabling a more detailed analysis of subregions.

Larger GMV in men in motor areas

For men compared to women, we observed larger GMV in the putamen, the premotor cortex (BA6), and the anterior cerebellum (i.e., structures involved in motor function). Ruigrok et al.2 likewise found larger GMV in men in the bilateral putamen, bilateral cerebellum and the left precentral gyrus. Larger GMV in motor areas in men may arise during the phases when testosterone in boys and estradiol in girls are causing the greatest modulation of the brain8.

Larger GMV in women in prefrontal areas

Increased GMV in women’s prefrontal areas has been reported in a number of smaller studies and was therefore the most prominent result in the large meta-analysis by Ruigrok et al.2. The present study confirms these results with women demonstrating larger GMV in bilateral dorso- and ventrolateral prefrontal cortices, the frontal pole, and the medial orbitofrontal cortex. In contrast to Ritchie et al.5, who were speculating about the functional meaning of higher prefrontal GMV in men as “regions that showed the largest effects were broadly areas involved in the hypothesized intelligence-related circuit in the “P-FIT” model“, we demonstrated the contrary with females showing larger GMV in the same areas. Although our study did not measure cognitive or behavioral data, and is thus not able to draw conclusions about cognitive functioning and brain structure, we would like to point out that increased GMV is usually associated with a better functioning in the cognitive domain12. Prefrontal areas with larger GMV in women are functionally important for executive functioning13, such as planning, working memory, inhibition, mental flexibility as well as the initiation and monitoring of action, but also for emotional control, moral considerations14 and processing of language15.

Do differences between men and women do not allow for individual assignment?

Although these sex differences have been robustly observed in different cohorts, a relevance for an individual is rather small: Joel and colleagues demonstrated that there is a considerable overlap between the features of brain form between males and females and that these features are internally inconsistent1, even when considering only those showing the largest sex differences. In response to the Joel et al.1 study, Chekroud et al.16 used a multivoxel pattern analysis to distinguish male and female brains by structural differences. They found a classification accuracy of 93–95% and concluded that sex can be reliably predicted by brain structure when considering the brain mosaic as a whole.

Limitations

Brain structural differences between men and women are the result of complex biological and environmental influences and the underlying neural mechanisms a matter of ongoing discussion. Additionally, no complete understanding exists whether more GMV is associated with improved function, even if most studies comparing experts and non-experts or longitudinal studies applying training paradigms demonstrated specifically increased GMV in those areas functionally representing improved performance17,18,19. However, these associations are poorly understood and a matter of ongoing discussions20.

Furthermore, while cognitive function is associated with GMV, it has also been linked to white matter and structural connectivity between different brain regions21. Thus, gray matter may explain some, but not all of the differences. In addition, sex-specific incidence of pathologies may have an impact on differences in GMV between men and women. In the current study, all pathologic brain scans had been excluded in this sample, as described in the Methods.

Finally, different measuring techniques of GMV do only partially provide comparable results. A major drawback of voxel-based measurements is that they combine cortical thickness and surface area into one single measurement. It has been demonstrated that vertex-based measures (cortical thickness, surface area) are more or less independent of each other22. A global or local change of these measures in different directions (e.g. increase of cortical thickness, decrease of surface area) wouldn’t necessarily be visible in voxel-based morphometry, and this may be one principal explanation for the differences between vertex- and voxel-based measures.