Just like a circus: the public consumption of sex differences

Behavioral neuroscience's inevitable SABV growing pains

The field of rodent behavioral neuroscience is undergoing two major sea changes: an ever-growing technological revolution, and worldwide calls to consider sex as a biological variable (SABV) in experimental design. Both have enormous potential to improve the precision and rigor with which the brain can be studied, but the convergence of these shifts in scientific practice has exposed critical limitations in classic and widely used behavioral paradigms. While our tools have advanced, our behavioral metrics - mostly developed in males and often allowing for only binary outcomes - have not. This opinion article explores how this disconnect has presented challenges for the accurate depiction and interpretation of sex differences in brain function, arguing for the expansion of current behavioral constructs to better account for behavioral diversity.

Remembering the null hypothesis when searching for brain sex differences

Human brain sex differences have fascinated scholars for centuries and become a key focus of neuroscientists since the dawn of MRI. We recently published a major review in Neuroscience and Biobehavioral Reviews showing that most male-female brain differences in humans are small and few have been reliably replicated. Although widely cited, this work was the target of a critical Commentary by DeCasien et al. (Biol Sex Differ 13:43, 2022). In this response, I update our findings and confirm the small effect sizes and pronounced scatter across recent large neuroimaging studies of human sex/gender difference. Based on the sum of data, neuroscientists would be well-advised to take the null hypothesis seriously: that men and women's brains are fundamentally similar, or "monomorphic". This perspective has important implications for how we study the genesis of behavioral and neuropsychiatric gender disparities.

Best practices to promote rigor and reproducibility in the era of sex-inclusive research

To enhance inclusivity and rigor, many funding agencies and journals now mandate the inclusion of females as well as males in biomedical studies. These mandates have enhanced generalizability and created unprecedented opportunities to discover sex differences. However, education in sound methods to consider sex as a subgroup category has lagged behind, resulting in a problematic literature in which study designs, analyses, and interpretations of results are often flawed. Here, we outline best practices for complying with sex-inclusive mandates, both for studies in which sex differences are a primary focus and for those in which they are not. Our recommendations are organized within the "4 Cs of Studying Sex to Strengthen Science: Consideration, Collection, Characterization and Communication," a framework developed by the Office of Research on Women's Health at the National Institutes of Health in the United States. Following these guidelines should help researchers include females and males in their studies while at the same time upholding high standards of rigor.

Deconstructing sex: Strategies for undoing binary thinking in neuroendocrinology and behavior

The scientific community widely recognizes that "sex" is a complex category composed of multiple physiologies. Yet in practice, basic scientific research often treats "sex" as a single, internally consistent, and often binary variable. This practice occludes important physiological factors and processes, and thus limits the scientific value of our findings. In human-oriented biomedical research, the use of simplistic (and often binary) models of sex ignores the existence of intersex, trans, non-binary, and gender non-conforming people and contributes to a medical paradigm that neglects their needs and interests. More broadly, our collective reliance on these models legitimizes a false paradigm of human biology that undergirds harmful medical practices and anti-trans political movements. Herein, we continue the conversations begun at the SBN 2022 Symposium on Hormones and Trans Health, providing guiding questions to help scientists deconstruct and rethink the use of "sex" across the stages of the scientific method. We offer these as a step toward a scientific paradigm that more accurately recognizes and represents sexed physiologies as multiple, interacting, variable, and unbounded by gendered preconceptions. We hope this paper will serve as a useful resource for scientists who seek a new paradigm for researching and understanding sexed physiologies that improves our science, widens the applicability of our findings, and deters the misuse of our research against marginalized groups.

Why and How to Account for Sex and Gender in Brain and Behavioral Research

Long overlooked in neuroscience research, sex and gender are increasingly included as key variables potentially impacting all levels of neurobehavioral analysis. Still, many neuroscientists do not understand the difference between the terms "sex" and "gender," the complexity and nuance of each, or how to best include them as variables in research designs. This TechSights article outlines rationales for considering the influence of sex and gender across taxa, and provides technical guidance for strengthening the rigor and reproducibility of such analyses. This guidance includes the use of appropriate statistical methods for comparing groups as well as controls for key covariates of sex (e.g., total intracranial volume) and gender (e.g., income, caregiver stress, bias). We also recommend approaches for interpreting and communicating sex- and gender-related findings about the brain, which have often been misconstrued by neuroscientists and the lay public alike.

Reporting and misreporting of sex differences in the biological sciences

As part of an initiative to improve rigor and reproducibility in biomedical research, the U.S. National Institutes of Health now requires the consideration of sex as a biological variable in preclinical studies. This new policy has been interpreted by some as a call to compare males and females with each other. Researchers testing for sex differences may not be trained to do so, however, increasing risk for misinterpretation of results. Using a list of recently published articles curated by Woitowich et al. (eLife, 2020; 9:e56344), we examined reports of sex differences and non-differences across nine biological disciplines. Sex differences were claimed in the majority of the 147 articles we analyzed; however, statistical evidence supporting those differences was often missing. For example, when a sex-specific effect of a manipulation was claimed, authors usually had not tested statistically whether females and males responded differently. Thus, sex-specific effects may be over-reported. In contrast, we also encountered practices that could mask sex differences, such as pooling the sexes without first testing for a difference. Our findings support the need for continuing efforts to train researchers how to test for and report sex differences in order to promote rigor and reproducibility in biomedical research.

Biomedical research has a long history of including only men or male laboratory animals in studies. To address this disparity, the United States National Institutes of Health (NIH) rolled out a policy in 2016 called Sex as a Biological Variable (or SABV). The policy requires researchers funded by the NIH to include males and females in every experiment unless there is a strong justification not to, such as studies of ovarian cancer. Since then, the number of research papers including both sexes has continued to grow.

Although the NIH does not require investigators to compare males and females, many researchers have interpreted the SABV policy as a call to do so. This has led to reports of sex differences that would otherwise have been unrecognized or ignored. However, researchers may not be trained on how best to test for sex differences in their data, and if the data are not analyzed appropriately this may lead to misleading interpretations.

Here, Garcia-Sifuentes and Maney have examined the methods of 147 papers published in 2019 that included both males and females. They discovered that more than half of these studies had reported sex differences, but these claims were not always backed by statistical evidence. Indeed, in a large majority (more than 70%) of the papers describing differences in how males and females responded to a treatment, the impact of the treatment was not actually statistically compared between the sexes. This suggests that sex-specific effects may be over-reported. In contrast, Garcia-Sifuentes and Maney also encountered instances where an effect may have been masked due to data from males and females being pooled together without testing for a difference first.

These findings reveal how easy it is to draw misleading conclusions from sex-based data. Garcia-Sifuentes and Maney hope their work raises awareness of this issue and encourages the development of more training materials for researchers.

Can Open Science be a Tool to Dismantle Claims of Hardwired Brain Sex Differences? Opportunities and Challenges for Feminist Researchers

Feminist scholars have long been concerned with claims of hardwired brain sex differences emanating from neuroscience and evolutionary psychology. Past criticisms of these claims have rightfully questioned the impact of this research on gender equality, pointing out how findings can be used to vindicate gender stereotypes. In this article, we appraise the brain sex differences literature through the lens of open science, a movement aimed at improving the robustness and reliability of science. In this discussion, we offer a feminist evaluation of the strategies (e.g., pre-registration, data sharing, and accountability) provided by open science, and we question whether these may be the novel and disruptive tools needed to dismantle claims about hardwired brain sex differences. We suggest that open science strategies can be useful in challenging some of these claims, and we note that promising initiatives are already being developed in neuroscience and allied fields. We end by acknowledging the distinct challenges that feminist researchers wishing to engage in open science face, particularly in the context of limited diversity. We conclude that open science presents considerable opportunity for feminist researchers, and that it will be crucial for feminists to be involved in shaping the future of this movement.

Beyond sex differences and a male-female continuum: Mosaic brains in a multidimensional space

In the last two decades, the 60 years old view that in utero exposure to testosterone irreversibly masculinizes the brain of males away from a default female form has been replaced by a complex scenario according to which sex affects the brains of both females and males via multiple mechanisms, which are susceptible to internal and external factors. These observations led to the "mosaic" hypothesis-the expectation that the degree of "maleness"/"femaleness" of different features within a single brain would not be internally consistent. Following a short review of the animal studies providing the basis of the mosaic hypothesis, I describe three studies conducted in humans that assessed internal consistency in regional volume, cortical thickness, and connectivity as revealed by magnetic resonance imaging (MRI); in neuronal numbers in the postmortem hypothalamus; and in changes in regional volume and cortical thickness (assessed with MRI) following exposure to extreme real-life stress. The conclusion from these studies, that human brains are largely composed of unique mosaics of female-typical and male-typical features, was supported by recent findings that the brain "types" typical of women are also typical of men, and vice versa. Lastly, I discuss criticism of the mosaic hypothesis and suggest replacing the framework of a male-female continuum with thinking about mosaic brains residing in a multidimensional space.

Sex Matters: A Multivariate Pattern Analysis of Sex- and Gender-Related Neuroanatomical Differences in Cis- and Transgender Individuals Using Structural Magnetic Resonance Imaging

Univariate analyses of structural neuroimaging data have produced heterogeneous results regarding anatomical sex- and gender-related differences. The current study aimed at delineating and cross-validating brain volumetric surrogates of sex and gender by comparing the structural magnetic resonance imaging data of cis- and transgender subjects using multivariate pattern analysis. Gray matter (GM) tissue maps of 29 transgender men, 23 transgender women, 35 cisgender women, and 34 cisgender men were created using voxel-based morphometry and analyzed using support vector classification. Generalizability of the models was estimated using repeated nested cross-validation. For external validation, significant models were applied to hormone-treated transgender subjects (n = 32) and individuals diagnosed with depression (n = 27). Sex was identified with a balanced accuracy (BAC) of 82.6% (false discovery rate [pFDR] < 0.001) in cisgender, but only with 67.5% (pFDR = 0.04) in transgender participants indicating differences in the neuroanatomical patterns associated with sex in transgender despite the major effect of sex on GM volume irrespective of the self-identification as a woman or man. Gender identity and gender incongruence could not be reliably identified (all pFDR > 0.05). The neuroanatomical signature of sex in cisgender did not interact with depressive features (BAC = 74.7%) but was affected by hormone therapy when applied in transgender women (P < 0.001).

How hype and hyperbole distort the neuroscience of sex differences

Mind your language! This Perspective article points out that the source of misreporting in the field of sex/gender differences can often be found in the unjustified overstatements used by researchers themselves in reporting their findings; caution is needed when addressing differences between human beings, and hype and hyperbole should be avoided.

Dump the "dimorphism": Comprehensive synthesis of human brain studies reveals few male-female differences beyond size

With the explosion of neuroimaging, differences between male and female brains have been exhaustively analyzed. Here we synthesize three decades of human MRI and postmortem data, emphasizing meta-analyses and other large studies, which collectively reveal few reliable sex/gender differences and a history of unreplicated claims. Males' brains are larger than females' from birth, stabilizing around 11 % in adults. This size difference accounts for other reproducible findings: higher white/gray matter ratio, intra- versus interhemispheric connectivity, and regional cortical and subcortical volumes in males. But when structural and lateralization differences are present independent of size, sex/gender explains only about 1% of total variance. Connectome differences and multivariate sex/gender prediction are largely based on brain size, and perform poorly across diverse populations. Task-based fMRI has especially failed to find reproducible activation differences between men and women in verbal, spatial or emotion processing due to high rates of false discovery. Overall, male/female brain differences appear trivial and population-specific. The human brain is not "sexually dimorphic."

Beyond the binary: Rethinking sex and the brain

The paper reviews the relations between sex and brain in light of the binary conceptualization of these relations and the challenges posed to it by the 'mosaic' hypothesis. Recent formulations of the binary framework range from arguing that the typical male brain is different from the typical female brain to claiming that brains are typically male or female because brain structure can be used to predict the sex category (female/male) of the brain's owner. These formulations are challenged by evidence that sex effects on the brain may be opposite under different conditions, that human brains are comprised of mosaics of female-typical and male-typical features, and that sex category explains only a small part of the variability in human brain structure. These findings led to a new, non-binary, framework, according to which mosaic brains reside in a multi-dimensional space that cannot meaningfully be reduced to a male-female continuum or to a binary variable. This framework may also apply to sex-related variables and has implications for research.

Effects of different intracranial volume correction methods on univariate sex differences in grey matter volume and multivariate sex prediction

Sex differences in 116 local gray matter volumes (GMVOL) were assessed in 444 males and 444 females without correcting for total intracranial volume (TIV) or after adjusting the data with the scaling, proportions, power-corrected proportions (PCP), and residuals methods. The results confirmed that only the residuals and PCP methods completely eliminate TIV-variation and result in sex-differences that are "small" (∣d∣ < 0.3). Moreover, as assessed using a totally independent sample, sex differences in PCP and residuals adjusted-data showed higher replicability ([Formula: see text] 93%) than scaling and proportions adjusted-data [Formula: see text] 68%) or raw data ([Formula: see text] 45%). The replicated effects were meta-analyzed together and confirmed that, when TIV-variation is adequately controlled, volumetric sex differences become "small" (∣d∣ < 0.3 in all cases). Finally, we assessed the utility of TIV-corrected/ TIV-uncorrected GMVOL features in predicting individuals' sex with 12 different machine learning classifiers. Sex could be reliably predicted (> 80%) when using raw local GMVOL, but also when using scaling or proportions adjusted-data or TIV as a single predictor. Conversely, after properly controlling TIV variation with the PCP and residuals' methods, prediction accuracy dropped to [Formula: see text] 60%. It is concluded that gross morphological differences account for most of the univariate and multivariate sex differences in GMVOL.

The Complex Relationships between Sex and the Brain

In the past decennia, our understanding of the sexual differentiation of the mammalian brain has dramatically changed. The simple model according to which testosterone masculinizes the brain of males away from a default female form, was replaced with a complex scenario, according to which sex effects on the brain of both females and males are exerted by genetic, hormonal, and environmental factors. These factors act via multiple partly independent mechanisms that may vary according to internal and external factors. These observations led to the "mosaic" hypothesis-the expectation of high variability in the degree of "maleness"/"femaleness" of different features within a single brain. Here, we briefly review animal data that form the basis of current understanding of sexual differentiation; present, in this context, the results of co-analyses of human brain measures obtained by magnetic resonance imaging or postmortem; discuss criticisms and controversies of the mosaic hypothesis and implications for research; and conclude that co-analysis of several (preferably, many) features and going back from the group level to that of the individual would advance our understanding of the relations between sex and the brain in health and disease.

Sex differences in gray matter volume: how many and how large are they really?

Background

Studies assessing volumetric sex differences have provided contradictory results. Total intracranial volume (TIV) is a major confounding factor when estimating local volumes of interest (VOIs). We investigated how the number, size, and direction of sex differences in gray matter volume (GMv) vary depending on how TIV variation is statistically handled.

Methods

Sex differences in the GMv of 116 VOIs were assessed in 356 participants (171 females) without correcting for TIV variation or after adjusting the data with 5 different methods (VBM8 non-linear-only modulation, proportions, power-corrected-proportions, covariation, and the residuals method). The outcomes obtained with these procedures were compared to each other and to those obtained in three criterial subsamples, one comparing female-male pairs matched on their TIV and two others comparing groups of either females or males with large/small TIVs. Linear regression was used to quantify TIV effects on raw GMv and the efficacy of each method in controlling for them.

Results

Males had larger raw GMv than females in all brain areas, but these differences were driven by direct TIV-VOIs relationships and more closely resembled the differences observed between individuals with large/small TIVs of sex-specific subsamples than the sex differences observed in the TIV-matched subsample. All TIV-adjustment methods reduced the number of sex differences but their results were very different. The VBM8- and the proportions-adjustment methods inverted TIV-VOIs relationships and resulted in larger adjusted volumes in females, promoting sex differences largely attributable to TIV variation and very distinct from those observed in the TIV-matched subsample. The other three methods provided results unrelated to TIV and very similar to those of the TIV-matched subsample. In these datasets, sex differences were bidirectional and achieved satisfactory replication rates in 19 VOIs, but they were “small” (d < ∣0.38∣) and most of them faded away after correcting for multiple comparisons.

Conclusions

There is not just one answer to the question of how many and how large the sex differences in GMv are, but not all the possible answers are equally valid. When TIV effects are ruled out using appropriate adjustment methods, few sex differences (if any) remain statistically significant, and their size is quite reduced.

Electronic supplementary material

The online version of this article (10.1186/s13293-019-0245-7) contains supplementary material, which is available to authorized users.

Potential Reporting Bias in Neuroimaging Studies of Sex Differences

Numerous functional magnetic resonance imaging (fMRI) studies have reported sex differences. To empirically evaluate for evidence of excessive significance bias in this literature, we searched for published fMRI studies of human brain to evaluate sex differences, regardless of the topic investigated, in Medline and Scopus over 10 years. We analyzed the prevalence of conclusions in favor of sex differences and the correlation between study sample sizes and number of significant foci identified. In the absence of bias, larger studies (better powered) should identify a larger number of significant foci. Across 179 papers, median sample size was n = 32 (interquartile range 23-47.5). A median of 5 foci related to sex differences were reported (interquartile range, 2-9.5). Few articles (n = 2) had titles focused on no differences or on similarities (n = 3) between sexes. Overall, 158 papers (88%) reached "positive" conclusions in their abstract and presented some foci related to sex differences. There was no statistically significant relationship between sample size and the number of foci (-0.048% increase for every 10 participants, p = 0.63). The extremely high prevalence of "positive" results and the lack of the expected relationship between sample size and the number of discovered foci reflect probable reporting bias and excess significance bias in this literature.

Sex in Context: Limitations of Animal Studies for Addressing Human Sex/Gender Neurobehavioral Health Disparities

Many brain and behavioral disorders differentially affect men and women. The new National Institutes of Health requirement to include both male and female animals in preclinical studies aims to address such health disparities, but we argue that the mandate is not the best solution to this problem. Sex differences are highly species-specific, tied to the mating system and social ecology of a given species or even strain of animal. In many cases, animals poorly replicate male-female differences in brain-related human diseases. Sex/gender disparities in human health have a strong sociocultural component that is intimately entangled with biological sex and challenging to model in animals. We support research that investigates sex-related variables in hypothesis-driven studies of animal brains and behavior. However, institutional policies that require sex analysis and give it special salience over other sources of biological variance can distort research. We caution that the costly imposition of sex analysis on nearly all animal research entrenches the presumption that human brain and behavioral differences are largely biological in origin and overlooks the potentially more powerful social, psychological, and cultural contributors to male-female neurobehavioral health gaps.

Perils and pitfalls of reporting sex differences

The idea of sex differences in the brain both fascinates and inflames the public. As a result, the communication and public discussion of new findings is particularly vulnerable to logical leaps and pseudoscience. A new US National Institutes of Health policy to consider both sexes in almost all preclinical research will increase the number of reported sex differences and thus the risk that research in this important area will be misinterpreted and misrepresented. In this article, I consider ways in which we might reduce that risk, for example, by (i) employing statistical tests that reveal the extent to which sex explains variation, rather than whether or not the sexes 'differ', (ii) properly characterizing the frequency distributions of scores or dependent measures, which nearly always overlap, and (iii) avoiding speculative functional or evolutionary explanations for sex-based variation, which usually invoke logical fallacies and perpetuate sex stereotypes. Ultimately, the factor of sex should be viewed as an imperfect, temporary proxy for yet-unknown factors, such as hormones or sex-linked genes, that explain variation better than sex. As scientists, we should be interested in discovering and understanding the true sources of variation, which will be more informative in the development of clinical treatments.

Multifaceted origins of sex differences in the brain

Studies of sex differences in the brain range from reductionistic cell and molecular analyses in animal models to functional imaging in awake human subjects, with many other levels in between. Interpretations and conclusions about the importance of particular differences often vary with differing levels of analyses and can lead to discord and dissent. In the past two decades, the range of neurobiological, psychological and psychiatric endpoints found to differ between males and females has expanded beyond reproduction into every aspect of the healthy and diseased brain, and thereby demands our attention. A greater understanding of all aspects of neural functioning will only be achieved by incorporating sex as a biological variable. The goal of this review is to highlight the current state of the art of the discipline of sex differences research with an emphasis on the brain and to contextualize the articles appearing in the accompanying special issue.

Sex beyond the genitalia: The human brain mosaic

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.