Structural differences between male and female brains

The link between structural brain asymmetry and the dimensions of the corpus callosum: A systematic review

Cerebral asymmetry is a defining feature of the human brain, but some controversy exists with respect to the relationship between structural brain asymmetry and the dimensions of the corpus callosum, the brain's major inter-hemispheric commissure. On the one hand, more asymmetric brains might house a proportionally smaller corpus callosum (negative link), potentially due to intra-hemispheric connections dominating over inter-hemispheric connections. On the other hand, asymmetric brains may contain a proportionately larger corpus callosum (positive link), to facilitate a possibly enhanced demand of interhemispheric communication, either through excitatory or inhibitory channels. The scientific literature on this topic is relatively sparse, but we have identified 13 studies that directly assess the relationship between structural asymmetries and callosal morphology. The studies suggest a multitude of effects on the global, regional, and local levels, where findings range from negative links, to positive links, to no links whatsoever. These links are systematically summarized, detailed, and discussed in the present review. Discrepancies between study outcomes might arise from the application of different morphometric approaches, the differential treatment of possible confounds, as well as the size and characteristics of the study sample.

Brain functional connectivity, but not neuroanatomy, captures the interrelationship between sex and gender in preadolescents

Understanding sex differences in the adolescent brain is crucial, as these differences are linked to neurological and psychiatric conditions that vary between males and females. Predicting sex from adolescent brain data may offer valuable insights into how these variations shape neurodevelopment. Recently, attention has shifted toward exploring socially-identified gender, distinct from sex assigned at birth, recognizing its additional explanatory power. This study evaluates whether resting-state functional connectivity (rsFC) or cortical thickness more effectively predicts sex and sex/gender alignment (the congruence between sex and gender) and investigates their interrelationship in preadolescents. Using data from the Adolescent Brain Cognitive Development (ABCD) Study, we employed machine learning to predict both sex (assigned at birth) and sex/gender alignment from rsFC and cortical thickness. rsFC predicted sex with significantly higher accuracy (86%) than cortical thickness (75%) and combining both did not improve the rsFC model's accuracy. Brain regions most effective in predicting sex belonged to association (default mode, dorsal attention, and parietal memory) and visual (visual and medial visual) networks. The rsFC sex classifier trained on sex/gender aligned youth was significantly more effective in classifying unseen youth with sex/gender alignment than in classifying unseen youth with sex/gender unalignment. In females, the degree to which their brains' rsFC matched a sex profile (female or male), was positively associated with the degree of sex/gender alignment. Lastly, neither rsFC nor cortical thickness predicted sex/gender alignment. These findings highlight rsFC's predictive power in capturing the relationship between sex and gender and the complexity of the interplay between sex, gender, and the brain's functional connectivity and neuroanatomy.

Effects of Congenital Adrenal Hyperplasia (CAH) and Biological Sex on Brain Size

Congenital Adrenal Hyperplasia (CAH) has been reported to involve structural alterations in some brain regions. However, it remains to be established whether there is also an impact on the size of the brain as a whole. Here, we compiled the largest CAH sample to date (n = 53), matched pair-wise to a control group (n = 53) on sex, age, and verbal intelligence. Using T1-weighted brain scans, we calculated intracranial volume (ICV) as well as total brain volume (TBV), which are both common estimates for brain size. The statistical analysis was performed using a general linear model assessing the effects of CAH (CAH vs. controls), sex (women vs. men), and any CAH-by-sex interaction. The outcomes were comparable for ICV and TBV, i.e., there was no significant main effect of CAH and no significant CAH-by-sex interaction. However, there was a significant main effect of sex, with larger ICVs and TBVs in men than in women. Our findings contribute to an understudied field of research exploring brain anatomy in CAH. In contrast to some existing studies suggesting a smaller brain size in CAH, we did not observe such an effect. In other words, ICV and TBV in women and men with CAH did not differ significantly from those in controls. Notwithstanding, we observed the well-known sex difference in brain size (12.69% for ICV and 12.50% for TBV), with larger volumes in men than in women, which is in agreement with the existing literature.

Sex differences in patterns of white matter neuroplasticity after balance training in young adults

Introduction

In past work we demonstrated different patterns of white matter (WM) plasticity in females versus males associated with learning a lab-based unilateral motor skill. However, this work was completed in neurologically intact older adults. The current manuscript sought to replicate and expand upon these WM findings in two ways: (1) we investigated biological sex differences in neurologically intact young adults, and (2) participants learned a dynamic full-body balance task.

Methods

24 participants (14 female, 10 male) participated in the balance training intervention, and 28 were matched controls (16 female, 12 male). Correlational tractography was used to analyze changes in WM from pre- to post-training.

Results

Both females and males demonstrated skill acquisition, yet there were significant differences in measures of WM between females and males. These data support a growing body of evidence suggesting that females exhibit increased WM neuroplasticity changes relative to males despite comparable changes in motor behavior (e.g., balance).

Discussion

The biological sex differences reported here may represent an important factor to consider in both basic research (e.g., collapsing across females and males) as well as future clinical studies of neuroplasticity associated with motor function (e.g., tailored rehabilitation approaches).

Effects of gender-affirming hormone therapy on gray matter density, microstructure and monoamine oxidase A levels in transgender subjects

MAO-A catalyzes the oxidative degradation of monoamines and is thus implicated in sex-specific neuroplastic processes that influence gray matter (GM) density (GMD) and microstructure (GMM). Given the exact monitoring of plasma hormone levels and sex steroid intake, transgender individuals undergoing gender-affirming hormone therapy (GHT) represent a valuable cohort to potentially investigate sex steroid-induced changes of GM and concomitant MAO-A density. Here, we investigated the effects of GHT over a median time period of 4.5 months on GMD and GMM as well as MAO-A distribution volume. To this end, 20 cisgender women, 11 cisgender men, 20 transgender women and 10 transgender men underwent two MRI scans in a longitudinal design. PET scans using [11C]harmine were performed before each MRI session in a subset of 35 individuals. GM changes determined by diffusion weighted imaging (DWI) metrics for GMM and voxel based morphometry (VBM) for GMD were estimated using repeated measures ANOVA. Regions showing significant changes of both GMM and GMD were used for the subsequent analysis of MAO-A density. These involved the fusiform gyrus, rolandic operculum, inferior occipital cortex, middle and anterior cingulum, bilateral insula, cerebellum and the lingual gyrus (post-hoc tests: pFWE+Bonferroni < 0.025). In terms of MAO-A distribution volume, no significant effects were found. Additionally, the sexual desire inventory (SDI) was applied to assess GHT-induced changes in sexual desire, showing an increase of SDI scores among transgender men. Changes in the GMD of the bilateral insula showed a moderate correlation to SDI scores (rho = - 0.62, pBonferroni = 0.047). The present results are indicative of a reliable influence of gender-affirming hormone therapy on 1) GMD and GMM following an interregional pattern and 2) sexual desire specifically among transgender men.

Cortical gyrification in women and men and the (missing) link to prenatal androgens

Previous studies have reported sex differences in cortical gyrification. Since most cortical folding is principally defined in utero, sex chromosomes as well as gonadal hormones are likely to influence sex-specific aspects of local gyrification. Classic congenital adrenal hyperplasia (CAH) causes high levels of androgens during gestation in females, whereas levels in males are largely within the typical male range. Therefore, CAH provides an opportunity to study the possible effects of prenatal androgens on cortical gyrification. Here, we examined the vertex-wise absolute mean curvature-a common estimate for cortical gyrification-in individuals with CAH (33 women and 20 men) and pair-wise matched controls (33 women and 20 men). There was no significant main effect of CAH and no significant CAH-by-sex interaction. However, there was a significant main effect of sex in five cortical regions, where gyrification was increased in women compared to men. These regions were located on the lateral surface of the brain, specifically left middle frontal (rostral and caudal), right inferior frontal, left inferior parietal, and right occipital. There was no cortical region where gyrification was increased in men compared to women. Our findings do not only confirm prior reports of increased cortical gyrification in female brains but also suggest that cortical gyrification is not significantly affected by prenatal androgen exposure. Instead, cortical gyrification might be determined by sex chromosomes either directly or indirectly-the latter potentially by affecting the underlying architecture of the cortex or the size of the intracranial cavity, which is smaller in women.

Morphological changes in the cerebellum during aging: evidence from convolutional neural networks and shape analysis

The morphology and function of the cerebellum are associated with various developmental disorders and healthy aging. Changes in cerebellar morphology during the aging process have been extensively investigated, with most studies focusing on changes in cerebellar regional volume. The volumetric method has been used to quantitatively demonstrate the decrease in the cerebellar volume with age, but it has certain limitations in visually presenting the morphological changes of cerebellar atrophy from a three-dimensional perspective. Thus, we comprehensively described cerebellar morphological changes during aging through volume measurements of subregions and shape analysis. This study included 553 healthy participants aged 20-80 years. A novel cerebellar localized segmentation algorithm based on convolutional neural networks was utilized to analyze the volume of subregions, followed by shape analysis for localized atrophy assessment based on the cerebellar thickness. The results indicated that out of the 28 subregions in the absolute volume of the cerebellum, 15 exhibited significant aging trends, and 16 exhibited significant sex differences. Regarding the analysis of relative volume, only 11 out of the 28 subregions of the cerebellum exhibited significant aging trends, and 4 exhibited significant sex differences. The results of the shape analysis revealed region-specific atrophy of the cerebellum with increasing age. Regions displaying more significant atrophy were predominantly located in the vermis, the lateral portions of bilateral cerebellar hemispheres, lobules I-III, and the medial portions of the posterior lobe. This atrophy differed between sexes. Men exhibited slightly more severe atrophy than women in most of the cerebellar regions. Our study provides a comprehensive perspective for observing cerebellar atrophy during the aging process.

Functional and structural reorganization in brain tumors: a machine learning approach using desynchronized functional oscillations

Neuroimaging studies have allowed for non-invasive mapping of brain networks in brain tumors. Although tumor core and edema are easily identifiable using standard MRI acquisitions, imaging studies often neglect signals, structures, and functions within their presence. Therefore, both functional and diffusion signals, as well as their relationship with global patterns of connectivity reorganization, are poorly understood. Here, we explore the functional activity and the structure of white matter fibers considering the contribution of the whole tumor in a surgical context. First, we find intertwined alterations in the frequency domain of local and spatially distributed resting-state functional signals, potentially arising within the tumor. Second, we propose a fiber tracking pipeline capable of using anatomical information while still reconstructing bundles in tumoral and peritumoral tissue. Finally, using machine learning and healthy anatomical information, we predict structural rearrangement after surgery given the preoperative brain network. The generative model also disentangles complex patterns of connectivity reorganization for different types of tumors. Overall, we show the importance of carefully designing studies including MR signals within damaged brain tissues, as they exhibit and relate to non-trivial patterns of both structural and functional (dis-)connections or activity.

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.

Investigating female versus male differences in white matter neuroplasticity associated with complex visuo-motor learning

Magnetic resonance imaging (MRI) has increasingly been used to characterize structure-function relationships during white matter neuroplasticity. Biological sex differences may be an important factor that affects patterns of neuroplasticity, and therefore impacts learning and rehabilitation. The current study examined a participant cohort before and after visuo-motor training to characterize sex differences in microstructural measures. The participants (N = 27) completed a 10-session (4 week) complex visuo-motor training task with their non-dominant hand. All participants significantly improved movement speed and their movement speed variability over the training period. White matter neuroplasticity in females and males was examined using fractional anisotropy (FA) and myelin water fraction (MWF) along the cortico-spinal tract (CST) and the corpus callosum (CC). FA values showed significant differences in the middle portion of the CST tract (nodes 38-51) across the training period. MWF showed a similar cluster in the inferior portion of the tract (nodes 18-29) but did not reach significance. Additionally, at baseline, males showed significantly higher levels of MWF measures in the middle body of the CC. Combining data from females and males would have resulted in reduced sensitivity, making it harder to detect differences in neuroplasticity. These findings offer initial insights into possible female versus male differences in white matter neuroplasticity during motor learning. This warrants investigations into specific patterns of white matter neuroplasticity for females versus males across the lifespan. Understanding biological sex-specific differences in white matter neuroplasticity may have significant implications for the interpretation of change associated with learning or rehabilitation.

Deep learning models reveal replicable, generalizable, and behaviorally relevant sex differences in human functional brain organization

Sex plays a crucial role in human brain development, aging, and the manifestation of psychiatric and neurological disorders. However, our understanding of sex differences in human functional brain organization and their behavioral consequences has been hindered by inconsistent findings and a lack of replication. Here, we address these challenges using a spatiotemporal deep neural network (stDNN) model to uncover latent functional brain dynamics that distinguish male and female brains. Our stDNN model accurately differentiated male and female brains, demonstrating consistently high cross-validation accuracy (>90%), replicability, and generalizability across multisession data from the same individuals and three independent cohorts (N ~ 1,500 young adults aged 20 to 35). Explainable AI (XAI) analysis revealed that brain features associated with the default mode network, striatum, and limbic network consistently exhibited significant sex differences (effect sizes > 1.5) across sessions and independent cohorts. Furthermore, XAI-derived brain features accurately predicted sex-specific cognitive profiles, a finding that was also independently replicated. Our results demonstrate that sex differences in functional brain dynamics are not only highly replicable and generalizable but also behaviorally relevant, challenging the notion of a continuum in male-female brain organization. Our findings underscore the crucial role of sex as a biological determinant in human brain organization, have significant implications for developing personalized sex-specific biomarkers in psychiatric and neurological disorders, and provide innovative AI-based computational tools for future research.

Insights into Sex and Gender Differences in Brain and Psychopathologies Using Big Data

The societal implication of sex and gender (SG) differences in brain are profound, as they influence brain development, behavior, and importantly, the presentation, prevalence, and therapeutic response to diseases. Technological advances have enabled speed up identification and characterization of SG differences during development and in psychopathologies. The main aim of this review is to elaborate on new technological advancements, such as genomics, imaging, and emerging biobanks, coupled with bioinformatics analyses of data generated from these technologies have facilitated the identification and characterization of SG differences in the human brain through development and psychopathologies. First, a brief explanation of SG concepts is provided, along with a developmental and evolutionary context. We then describe physiological SG differences in brain activity and function, and in psychopathologies identified through imaging techniques. We further provide an overview of insights into SG differences using genomics, specifically taking advantage of large cohorts and biobanks. We finally emphasize how bioinformatics analyses of big data generated by emerging technologies provides new opportunities to reduce SG disparities in health outcomes, including major challenges.

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impact, however, has been limited due to small sample sizes and methodological variability in addition to intrinsic limitations of the method itself such as its sensitivity to motion. The lack of standardization from a data acquisition and data processing perspective makes it difficult to pool multiple studies and/or conduct multisite studies that are necessary for supporting clinically relevant findings. Based on the experience of the ENIGMA MRS work group and a review of the literature, this manuscript provides an overview of the current state of MRS data harmonization. Key factors that need to be taken into consideration when conducting both retrospective and prospective studies are described. These include (1) MRS acquisition issues such as pulse sequence, RF and B0 calibrations, echo time, and SNR; (2) data processing issues such as pre-processing steps, modeling, and quantitation; and (3) biological factors such as voxel location, age, sex, and pathology. Various approaches to MRS data harmonization are then described including meta-analysis, mega-analysis, linear modeling, ComBat and artificial intelligence approaches. The goal is to provide both novice and experienced readers with the necessary knowledge for conducting MRS data harmonization studies.

Age-associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood: A UK Biobank imaging study

Cortical morphology changes with ageing and age-related neurodegenerative diseases. Previous studies suggest that the age effect is more pronounced in the frontal lobe. However, our knowledge of structural complexity changes in male and female brains is still limited. We measured cortical ribbon complexity through fractal dimension (FD) analysis at the hemisphere and lobe level in 7010 individuals from the UK Biobank imaging cohort to study age-related sex differences (3332 males, age ranged 45-79 years). FD decreases significantly with age and sexual dimorphism exists. With correction for brain size, females showed higher complexity in the left hemisphere and left and right parietal lobes whereas males showed higher complexity in the right temporal and left and right occipital lobes. A nonlinear age effect was observed in the left and right frontal, and right temporal lobes. Differential patterns of age effects were observed in both sexes with relatively more age-affected regions in males. Significantly higher rightward asymmetries at hemisphere, frontal, parietal, and occipital lobe level and higher leftward asymmetry in temporal lobe were observed. There was no age-by-sex-by asymmetry interaction in any region. When controlling for brain size, the leftward hemispheric, and temporal lobe asymmetry decreased with age. Males had significantly lower asymmetry between hemispheres and higher asymmetry in the parietal and occipital lobes than females. This work provides distinct patterns of age-related sex and asymmetry differences that can aid in the future development of sex-specific models of the normal brain to ascribe cognitive functional significance of these patterns in ageing.

The Neuroanatomy of Pregnancy and Postpartum

Pregnancy and giving birth are exceptional states in a woman's life for many reasons. While the effects of pregnancy and childbirth on the female body are obvious, less is known about their impact on the female brain, especially in humans. The scientific literature is still sparse but we have identified 12 longitudinal neuroimaging studies conducted in women whose brains were scanned before pregnancy, during pregnancy, and/or after giving birth. This review summarizes and discusses the reported neuroanatomical changes during pregnancy, postpartum, and beyond. Some studies suggest that pregnancy is mainly associated with tissue decreases, and a few studies suggest that this tissue loss is mostly permanent. In contrast, the majority of studies seems to indicate that the postpartum period is accompanied by substantial tissue increases throughout the entire brain. Future research is clearly warranted to replicate and extend the current findings, while addressing various limitations and shortcomings of existing studies.

The Impact of Gender-affirming Hormone Therapy on Anatomic Structures of the Brain Among Transgender Individuals

Despite the growing numbers of individuals who identify as transgender, this population continues to face worse mental health outcomes compared with the general population. Transgender individuals attempt suicide at a rate that is almost 9 times that of the general population. Few studies have reported on the positive effect of gender-affirming hormone therapy on mental health outcomes in transgender individuals. It is likely that this effect is due in part to the physiological responses that occur as a result of hormone therapy that mitigate incongruencies between one's gender identity and assigned sex. To our knowledge, only limited studies have shown a connection between gender-affirming hormone therapy, its effect on the brain's structure, and long-term effects that this may have on mental health outcomes. The authors propose that, in addition to the physiological responses that occur as a direct result of hormone therapy and the validation that results from receiving gender-affirming medical care, mental health outcomes in transgender individuals may also improve due to the role that hormone therapy plays in altering the brain's structure, possibly shaping the brain to become more like that of the gender with which an individual identifies. In this article, the authors review the current literature on the effects that gender-affirming hormone therapy has on mental health outcomes and anatomic structures of the brain in transgender individuals.

Mate Choice, Sex Roles and Sexual Cognition: Neuronal Prerequisites Supporting Cognitive Mate Choice

Across taxa, mate choice is a highly selective process involving both intra- and intersexual selection processes aiming to pass on one’s genes, making mate choice a pivotal tool of sexual selection. Individuals adapt mate choice behavior dynamically in response to environmental and social changes. These changes are perceived sensorily and integrated on a neuronal level, which ultimately leads to an adequate behavioral response. Along with perception and prior to an appropriate behavioral response, the choosing sex has (1) to recognize and discriminate between the prospective mates and (2) to be able to assess and compare their performance in order to make an informed decision. To do so, cognitive processes allow for the simultaneous processing of multiple information from the (in-) animate environment as well as from a variety of both sexual and social (but non-sexual) conspecific cues. Although many behavioral aspects of cognition on one side and of mate choice displays on the other are well understood, the interplay of neuronal mechanisms governing both determinants, i.e., governing cognitive mate choice have been described only vaguely. This review aimed to throw a spotlight on neuronal prerequisites, networks and processes supporting the interaction between mate choice, sex roles and sexual cognition, hence, supporting cognitive mate choice. How does neuronal activity differ between males and females regarding social cognition? Does sex or the respective sex role within the prevailing mating system mirror at a neuronal level? How does cognitive competence affect mate choice? Conversely, how does mate choice affect the cognitive abilities of both sexes? Benefitting from studies using different neuroanatomical techniques such as neuronal activity markers, differential coexpression or candidate gene analyses, modulatory effects of neurotransmitters and hormones, or imaging techniques such as fMRI, there is ample evidence pointing to a reflection of sex and the respective sex role at the neuronal level, at least in individual brain regions. Moreover, this review aims to summarize evidence for cognitive abilities influencing mate choice and vice versa. At the same time, new questions arise centering the complex relationship between neurobiology, cognition and mate choice, which we will perhaps be able to answer with new experimental techniques.

Development of sex differences in the human brain

Sex differences in brain anatomy have been described from early childhood through late adulthood, but without any clear consensus among studies. Here, we applied a machine learning approach to estimate 'Brain Sex' using a continuous (rather than binary) classifier in 162 boys and 185 girls aged between 5 and 18 years. Changes in the estimated sex differences over time at different age groups were subsequently calculated using a sliding window approach. We hypothesized that males and females would differ in brain structure already during childhood, but that these differences will become even more pronounced with increasing age, particularly during adolescence. Overall, the classifier achieved a good performance, with an accuracy of 80.4% and an AUC of 0.897 across all age groups. Assessing changes in the estimated sex with age revealed a growing difference between the sexes with increasing age. That is, the very large effect size of d = 1.2 which was already evident during childhood increased even further from age 11 onward, and eventually reached an effect size of d = 1.6 at age 17. Altogether these findings suggest a systematic sex difference in brain structure already during childhood, and a subsequent increase of this difference during adolescence.