Abstract
Findings of average differences between females and males in the structure of specific brain regions are often interpreted as indicating that the typical male brain is different from the typical female brain. An alternative interpretation is that the brain types typical of females are also typical of males, and sex differences exist only in the frequency of rare brain types. Here we contrasted the two hypotheses by analyzing the structure of 2176 human brains using three analytical approaches. An anomaly detection analysis showed that brains from females are almost as likely to be classified as “normal male brains,” as brains from males are, and vice versa. Unsupervised clustering algorithms revealed that common brain “types” are similarly common in females and in males and that a male and a female are almost as likely to have the same brain “type” as two females or two males are. Large sex differences were found only in the frequency of some rare brain “types.” Last, supervised clustering algorithms revealed that the brain “type(s)” typical of one sex category in one sample could be typical of the other sex category in another sample. The present findings demonstrate that even when similarity and difference are defined mathematically, ignoring biological or functional relevance, sex category (i.e., whether one is female or male), is not a major predictor of the variability of human brain structure. Rather, the brain types typical of females are also typical of males, and vice versa, and large sex differences are found only in the prevalence of some rare brain types. We discuss the implications of these findings to studies of the structure and function of the human brain.
Highlights
Findings of average differences between females and males in the structure and function of specific brain regions as well as evidence from in vitro and in vivo studies that sex can affect the structure and function of brain cells are often interpreted as indicating that the typical male brain is different from the typical female brain (e.g., Baron-Cohen, 2002; Ingalhalikar et al, 2014; Larson et al, 2015; Sex and Typical Human BrainsEcker et al, 2017; Wierenga et al, 2017)
The less extreme interpretation, which is more common in scientific publications and which is the one challenged in the present study, is that there is overlap between females and males in brain structure, the typical female brain differs from the typical male brain
They support the claim that the types of brain typical of females are typical of males, and that large sex differences exist in the prevalence of some rare brain types (Joel, 2011, 2012; Joel et al, 2015; Joel and Fausto-Sterling, 2016)
Summary
Findings of average differences between females and males in the structure and function of specific brain regions as well as evidence from in vitro and in vivo studies that sex can affect the structure and function of brain cells are often interpreted as indicating that the typical male brain is different from the typical female brain (e.g., Baron-Cohen, 2002; Ingalhalikar et al, 2014; Larson et al, 2015; Sex and Typical Human BrainsEcker et al, 2017; Wierenga et al, 2017). The less extreme interpretation, which is more common in scientific publications and which is the one challenged in the present study, is that there is overlap between females and males in brain structure, the typical female brain differs from the typical male brain This is evident in describing average group-level differences between females and males as if they were characteristics of females and males, or in assuming that human brains are aligned along a continuum between a typical male brain and a typical female brain. The former is evident in statements such as: “During developmental periods, male brains tend to be structured to facilitate withinlobe and within-hemisphere connectivity . The latter may be seen in the description of the aim of a recent study: “to examine the probability of autism spectrum disorder along a normative phenotypic axis ranging from the characteristic female to male brain phenotype” (Ecker et al, 2017, p. 330)
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