Breaking the binary: Gender versus sex analysis in human brain imaging

Personality assessment inventory sex differences in people with epileptic and functional seizures

OBJECTIVE

Previous research has shown that the Personality Assessment Inventory (PAI) is useful in differentiating individuals with functional seizures (FS) from those with epileptic seizures (ES). In these two groups, sex differences in PAI validity and clinical subscales have not been investigated. Elucidating sex differences could improve the understanding of how males and females experience FS or ES and may improve differential diagnosis and treatment planning.

METHOD

We examined sex differences across PAI scales, subscales, and validity profiles amongst adults with FS (n = 62) and ES (n = 55). Participants were evaluated and classified at the Johns Hopkins Hospital Epilepsy Monitoring Unit based on continuous video electroencephalography (cEEG) confirmed diagnoses. Among valid profiles, we conducted the following analyses: calculation of odds ratios (OR) and associated confidence intervals (CI) for each clinical, treatment, and interpersonal scale; logistic regression models to examine whether diagnostic status could be predicted by PAI scale elevations and sex; positive predictive values (PPV) and negative predictive values (NPV) to understand the diagnostic utility of scale and subscale elevations; and receiver operating characteristic (ROC) curves to determine the area under the curve (AUC) and identify PAI scales with the greatest capacity to distinguish FS presence/absence.

RESULTS

There were no significant differences in validity scales between FS and ES groups, both in the combined sample and when stratifying by sex (p's > 0.05). On a clinical scale level, FS females produced higher elevations on stress (STR) and somatic complaints (SOM) (OR = 4.17, OR = 6.95, p's < 0.05), and FS males reported higher anxiety (ANX), anxiety-related disorders (ARD), and non-support (NON) (OR = 8.0, OR = 11.25, OR = 15.2, p's < 0.05) than sex-matched ES patients. On a subscale level, FS females were more likely than ES females to have clinically elevated conversion (SOM-C) and somatization (SOM-S) scales (OR = 4.72, OR = 5.78, p's < 0.05), and FS males were more likely than ES males to report clinically elevated SOM-C, physiological anxiety (ANX-P), and trauma-related distress (ARD-T) (OR = 10.53, OR = 9.52, OR = 9.52, p's < 0.05). ROC findings revealed that SOM-C (AUC = 0.72) and ANX-P (AUC = 0.78) had the greatest AUCs for FS females and males, respectively. In the combined sex sample, FS patients were more likely than ES patients to endorse mildly elevated paranoia (PAR) and STR and clinically elevated SOM, depression (DEP), and ARD (ORs = 4.86, 3.52, 5.10, 3.01, 4.38, respectively, p's < 0.05); when entering these scales in a logistic regression model, SOM was the best predictor of FS. However, overall classification rates did not exceed 80 % (PPV = 75.5 %, NPV = 65.5 %). Among subscales, the combined-sex FS cohort was more likely to endorse elevations on SOM-C, SOM-S, ANX-P, and ARD-T than the ES cohort (ORs = 5.24, 3.82, 4.38, 4.38, respectively, p's < 0.05); when entering these scales in a logistic regression model, SOM-C was the best predictor of FS. Within the combined sex sample, SOM-C and STR had the highest AUCs (0.70 and 0.68, respectively).

CONCLUSIONS

Our findings indicate that males and females with FS are both more likely than those with ES to endorse higher conversion symptoms but otherwise have different characteristics. These differences might influence predisposition to the development of FS or perpetuation of symptoms and could be useful in determining optimal treatment approaches.

"Precision Medicine" and the Failed Search for Binary Brain Sex Differences to Address Gender Behavioral Health Disparities

Human brain imaging took off in the 1980s and has since flooded the zone in the analysis of gender differences in behavior and mental health. Couched in the aims of "precision medicine," the vast majority of this research has taken a binary approach, dividing participants according to the M/F box at intake and asserting that the sex differences found in neuroimaging will lead to important advances for treating neuropsychiatric disorders. However, the actual findings from this 40-year project have not lived up to its promise, in part because of the over-binarization of sex and general ignorance of gender as a complex variable influencing human behavior and brain function. This paper reviews the history of failed claims about male-female brain difference in the modern era, illuminates the deep-pocketed incentives driving such research, and examines the limitations of this binary approach for understanding gender-related behavior and health disparities. It then considers more recent efforts to "break the binary" by using measures of "gender" in addition to "sex" as an independent variable in brain imaging studies. Given the multidimensional nature of gender-as identity, expression, roles and relations-this is challenging to implement, with initial efforts producing little of substance. Better approaches to addressing male-female disparities in brain health will require focusing on specific behaviors (e.g., anxiety, risk-taking, verbal memory, spatial navigation) and specific components of sex and gender (e.g., body size, hormone levels, gene expression, caregiver role, financial independence, discrimination) when seeking brain-behavior correlates in a diverse population.

Sex/gender differences in hemispheric asymmetries

This chapter will critically review evidence across 40 years of research, covering both early and contemporary studies that have investigated sex/gender differences in hemispheric asymmetries, including both structural and functional asymmetries. We argue that small sex/gender differences in hemispheric asymmetry reliably exist, but there is significant overlap between the sexes and considerable within-sex variation. Furthermore, we argue that research to date is limited in its consideration of sex/gender-related factors, such as sex hormones and gender roles. Moreover, we highlight a critical limitation stemming from the lack of universal agreement on the definitions of "sex" and "gender," resulting in the majority of studies interested in sex/gender differences in hemispheric asymmetry involving the separation of participants into dichotomous male/female groups based solely on self-identified sex. Future research involving sex/gender should adopt a biopsychosocial approach whenever possible, to ensure that nonbinary psychologic, biologic, and environmental/social factors related to sex/gender, and their interactions, are routinely accounted for. Finally, we argue that while the human brain is not sexually dimorphic, sex/gender differences in the brain are not trivial and likely have several clinically relevant implications, including for the development of stratified treatment approaches for both neurologic and psychiatric patient populations.

Is Being Male a Marker of Aggression? Evidence for the Decoupling of Sex and Gender Role Orientation

OBJECTIVES

This study explores whether sex differences in reactive aggression (RA) and proactive aggression (PA) are attributable to sex, gender role orientation, or their interaction and explores the neuroanatomical characteristics of these sex differences.

METHODS

In a sample of 108 males and 126 females, we examined the sex-by-gender role orientation interaction on RA, PA, and brain gray matter volume (GMV). Then, we explored the relationship between aggression and regional GMV.

RESULTS

When the effects of sex and gender role orientation on aggression were disentangled, there were no sex differences in RA, regardless of gender role orientation. However, sex differences (male > female) in PA were observed within the masculine group but not within the feminine group. Brain imaging results revealed sex differences (male > female) on the right inferior frontal gyrus GMV, a region involved in cognitive control, within the masculine group. Moreover, a negative association between PA and the right inferior frontal gyrus GMV was observed in masculine females rather than masculine males.

CONCLUSIONS

These findings indicate that gender role orientation has a more significant effect on aggression than sex, particularly with regard to PA, and hint that the goal of cognitive control involved in displaying PA differs in masculine males and masculine females.

Hypothalamus Connectivity in Adolescent Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Adolescent Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a disabling illness of unknown etiology. Increasing evidence suggests hypothalamic involvement in ME/CFS pathophysiology, which has rarely been explored using magnetic resonance imaging (MRI) in the condition. This work aimed to use MRI to examine hypothalamus connectivity in adolescents with ME/CFS and explore how this relates to fatigue severity and illness duration. 25 adolescents with ME/CFS and 23 healthy controls completed a neuroimaging protocol consisting of structural and multishell diffusion-weighted imaging sequences, in addition to the PedsQL Multidimensional Fatigue Scale to assess fatigue severity. Information about illness duration was acquired at diagnosis. Preprocessing and streamlines tractography was performed using QSIPrep combined with a custom parcellation scheme to create structural networks. The number (degree) and weight (strength) of connections between lateralized hypothalamus regions and cortical and subcortical nodes were extracted, and relationships between connectivity measures, fatigue severity, and illness duration were performed using Bayesian regression models. We observed weak-to-moderate evidence of increased degree, but not strength, of connections from the bilateral anterior-inferior (left: pd [%] = 99.18, median [95% CI] = -22.68[-40.96 to 4.45]; right: pd [%] = 99.86, median [95% CI] = -23.35[-38.47 to 8.20]), left anterior-superior (pd [%] = 99.33, median [95% CI] = -18.83[-33.45 to 4.07]) and total left hypothalamus (pd [%] = 99.44, median [95% CI] = -47.18[-83.74 to 11.03]) in the ME/CFS group compared with controls. Conversely, bilateral posterior hypothalamus degree decreased with increasing ME/CFS illness duration (left: pd [%] = 98.13, median [95% CI]: -0.47[-0.89 to 0.03]; right: pd [%] = 98.50, median [95% CI]:-0.43[-0.82 to 0.05]). Finally, a weak relationship between right intermediate hypothalamus connectivity strength and fatigue severity was identified in the ME/CFS group (pd [%] = 99.35, median [95% CI] = -0.28[-0.51 to 0.06]), which was absent in controls. These findings suggest changes in hypothalamus connectivity may occur in adolescents with ME/CFS, warranting further investigation.

How sex and gender shape functional brain networks

Sex and gender differences exist in the prevalence and clinical manifestation of common brain disorders. Identifying their neural correlates may help improve clinical care.

Relationships between Grey Matter Volume in the Bilateral Superior Frontal Gyrus and Reactive Aggression Varied by Level of Traditional Masculinity

Although previous behavioral studies have associated reactive aggression (RA) and proactive aggression (PA) with traditional masculinity, further investigation is needed into the traditional masculinity-linked neuroanatomical characteristics of RA and PA. This study analyzed the traditional masculinity-by-aggression interaction in 705 participants (350 men) by measuring grey matter volume (GMV). We have expanded on previous studies and found that traditional masculinity was not associated with RA and PA when not controlled for traditional femininity. However, the association appeared when controlling for it. Furthermore, we found significant traditional masculinity-by-RA interactions on the GMV in the bilateral superior frontal gyrus, a region known to be involved in cognitive control. When traditional masculinity scores were 1 standard deviation above the mean, there was a positive correlation between RA and the GMV in the bilateral superior frontal gyrus. Conversely, when traditional masculinity scores were 1 standard deviation below the mean, there was a negative correlation between RA and the GMV in the region. However, no traditional masculinity-linked neuroanatomical characteristics of PA were found. The results indicated that individuals with high/low traditional masculinity perceived RA as a different outcome (gain or loss) of self-control. The results supported an opportunity to develop prevention or intervention strategies for RA.

Sex, gender diversity, and brain structure in early adolescence

There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Sex versus gender associations with brain structure

In contrast to sex (a biological distinction), little is known about the associations between gender (a societal construct) and brain structure in the general population. In response to this knowledge gap, we examined the associations of sex vs. gender with FreeSurfer-generated cortical thickness and proportion-adjusted subcortical brain volume regions-of-interest (ROIs) in healthy adults (n = 88) screened for general medical conditions, mental illness, substance abuse, and intracranial pathologies. Gender role endorsement was assessed using the well-established and validated Bem Sex Role Inventory. For our main objectives, we calculated a continuum score as a composite measure of gender. For our secondary objectives, we examined sex-specific associations of the masculine vs. feminine gender role endorsement domains with brain structural outcomes. We found that female sex, independent of continuum scores, was associated with larger proportion-adjusted volumes for the basal ganglia, hippocampus, and ventral diencephalon. Higher continuum scores, independent of sex, were associated with thicker cortical thickness for the left and right superior frontal cortex, caudal and rostral middle frontal cortex, and right pars orbitalis. Female sex and higher continuum scores were independently associated with larger corpus callosum volumes. Post-hoc testing showed sex-specific associations between higher femininity scores and thicker prefrontal cortical thickness for the ROIs in females, but not in males. In conclusion, sex and gender showed semi-independent associations with brain structure in a general population sample. Our research supports the disaggregation of sex and gender to provide a more nuanced perspective on brain structural differences between men and women.

Sex and Gender in Population Neuroscience

To understand psychiatric and neurological disorders and the structural and functional properties of the human brain, it is essential to consider the roles of sex and gender. In this chapter, I first define sex and gender and describe studies of sex differences in non-human animals. In humans, I describe the sex differences in behavioral and clinical phenotypes and neuroimaging-derived phenotypes, including whole-brain measures, regional subcortical and cortical measures, and structural and functional connectivity. Although structural whole-brain sex differences are large, regional effects (adjusting for whole-brain volumes) are typically much smaller and often fail to replicate. Nevertheless, while an individual neuroimaging feature may have a small effect size, aggregating them in a "maleness/femaleness" score or machine learning multivariate paradigm may prove to be predictive and informative of sex- and gender-related traits. Finally, I conclude by summarizing emerging investigations of gender norms and gender identity and provide methodological recommendations to incorporate sex and gender in population neuroscience research.

A systematic review of sex/gender differences in the multi-dimensional neurobiological mechanisms in addiction and their relevance to impulsivity

Purpose of Review

Addiction may be characterized along three functional domains: Approach Behavior, Executive Function, and Negative Emotionality. Constructs underlying impulsivity thought to be relevant in addiction map on to these three functional domains. The purpose of the present review was to evaluate the extant research regarding sex/gender differences in the multi-dimensional domains of addiction using human neuroimaging and discuss their relevance to impulsivity.

Recent Findings

Few papers over the past two decades have used human neuroimaging to test sex/gender differences in addiction. There is therefore a significant gap in the literature regarding sex/gender differences in the neurobiological mechanisms driving the multi-dimensionality of addiction and their implications to impulsivity.

Summary

Of the 34 reviewed papers, the orbitofrontal cortex/ventromedial prefrontal cortex (OFC/vmPFC) was the most frequently reported brain region to evidence a sex/gender difference during fMRI tasks probing Approach Behavior and Negative Emotionality. This finding suggests potential sex/gender-specific patterns of subjective valuation in substance misuse, driven by OFC/vmPFC dysregulation.

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.

Sex, gender diversity, and brain structure in children ages 9 to 11 years old

There remains little consensus about the relationship between sex and brain structure, particularly in childhood. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest - many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years-old (N=7693). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. The model with sex, but not gender diversity, was the best-fitting model in 75% of gray matter regions and 79% of white matter regions examined. The addition of gender to the sex model explained significantly more variance than sex alone with regard to bilateral cerebellum volume, left precentral cortical thickness, as well as gyrification in the right superior frontal gyrus, right parahippocampal gyrus, and several regions in the left parietal lobe. For mean diffusivity in the left uncinate fasciculus, the model with sex, gender, and their interaction captured the most variance. Nonetheless, the magnitude of variance accounted for by sex was small in all cases and felt-gender score was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years-old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Comprehensive evaluation of harmonization on functional brain imaging for multisite data-fusion

To embrace big-data neuroimaging, harmonizing the site effect in resting-state functional magnetic resonance imaging (R-fMRI) data fusion is a fundamental challenge. A comprehensive evaluation of potentially effective harmonization strategies, particularly with specifically collected data, has been scarce, especially for R-fMRI metrics. Here, we comprehensively assess harmonization strategies from multiple perspectives, including tests on residual site effect, individual identification, test-retest reliability, and replicability of group-level statistical results, on widely used R-fMRI metrics across various datasets, including data obtained from participants with repetitive measures at different scanners. For individual identifiability (i.e., whether the same subject could be identified across R-fMRI data scanned across different sites), we found that, while most methods decreased site effects, the Subsampling Maximum-mean-distance based distribution shift correction Algorithm (SMA) and parametric unadjusted CovBat outperformed linear regression models, linear mixed models, ComBat series and invariant conditional variational auto-encoder in clustering accuracy. Test-retest reliability was better for SMA and parametric adjusted CovBat than unadjusted ComBat series and parametric unadjusted CovBat in the number of overlapped voxels. At the same time, SMA was superior to the latter in replicability in terms of the Dice coefficient and the scale of brain areas showing sex differences reproducibly observed across datasets. Furthermore, SMA better detected reproducible sex differences of ALFF under the site-sex confounded situation. Moreover, we designed experiments to identify the best target site features to optimize SMA identifiability, test-retest reliability, and stability. We noted both sample size and distribution of the target site matter and introduced a heuristic formula for selecting the target site. In addition to providing practical guidelines, this work can inform continuing improvements and innovations in harmonizing methodologies for big R-fMRI data.