Neural and Hormonal Correlates of Sexual Arousal in Transgender Persons

Gender Dysphoria and Sexual Euphoria: A Bayesian Perspective on the Influence of Gender-Affirming Hormone Therapy on Sexual Arousal

Self-reported sexual orientation of transgender individuals occasionally changes over transition. Using functional magnetic resonance imaging, we tested the hypothesis that neural and behavioral patterns of sexual arousal in transgender individuals would shift from the assigned to the experienced gender (e.g., trans women's responses becoming more dissimilar to those of cis men and more similar to those of cis women). To this aim, trans women (N = 12) and trans men (N = 20) as well as cisgender women (N = 24) and cisgender men (N = 14) rated visual stimuli showing male-female, female-female or male-male intercourse for sexual arousal before and after four months of gender-affirming hormone therapy. A Bayesian framework allowed us to incorporate previous behavioral findings. The hypothesized changes could indeed be observed in the behavioral responses with the strongest results for trans men and female-female scenes. Activation of the ventral striatum supported our hypothesis only for female-female scenes in trans women. The respective application or depletion of androgens in trans men and trans women might partly explain this observation. The prominent role of female-female stimuli might be based on the differential responses they elicit in cis women and men or, in theory, the controversial concept of autogynephilia. We show that correlates of sexual arousal in transgender individuals might change in the direction of the experienced gender. Future investigations should elucidate the mechanistic role of sex hormones and the cause of the differential neural and behavioral findings.The study was registered at ClinicalTrials.gov (NCT02715232), March 22, 2016.

Deep Learning in the Identification of Electroencephalogram Sources Associated with Sexual Orientation

INTRODUCTION

It is unclear if sexual orientation is a biological trait that has neurofunctional footprints. With deep learning, the power to classify biological datasets without an a priori selection of features has increased by magnitudes. The aim of this study was to correctly classify resting-state electroencephalogram (EEG) data from males with different sexual orientation using deep learning and to explore techniques to identify the learned distinguishing features.

METHODS

Three cohorts (homosexual men, heterosexual men, and a mixed sex cohort), one pretrained network on sex classification, and one newly trained network for sexual orientation classification were used to classify sex. Further, Grad-CAM methodology and source localization were used to identify the spatiotemporal patterns that were used for differentiation by the networks.

RESULTS

Using a pretrained network for classification of males and females, no differences existed between classification of homosexual and heterosexual males. The newly trained network was able, however, to correctly classify the cohorts with a total accuracy of 83%. The retrograde activation using Grad-CAM technology yielded distinctive functional EEG patterns in the Brodmann area 40 and 1 when combined with Fourier analysis and a source localization.

DISCUSSION

This study shows that electrophysiological trait markers of male sexual orientation can be identified using deep learning. These patterns are different from the differentiating signatures of males and females in a resting-state EEG.

Inter-Network Brain Functional Connectivity in Adolescents Assigned Female at Birth Who Experience Gender Dysphoria

Gender dysphoria (GD) is characterized by distress due to an incongruence between experienced gender and sex assigned at birth. Brain functional connectivity in adolescents who experience GD may be associated with experienced gender (vs. assigned sex) and/or brain networks implicated in own-body perception. Furthermore, sexual orientation may be related to brain functional organization given commonalities in developmental mechanisms proposed to underpin GD and same-sex attractions. Here, we applied group independent component analysis to resting-state functional magnetic resonance imaging (rs-fMRI) BOLD timeseries data to estimate inter-network (i.e., between independent components) timeseries correlations, representing functional connectivity, in 17 GD adolescents assigned female at birth (AFAB) not receiving gender-affirming hormone therapy, 17 cisgender girls, and 15 cisgender boys (ages 12-17 years). Sexual orientation was represented by degree of androphilia-gynephilia and sexual attractions strength. Multivariate partial least squares analyses found that functional connectivity differed among cisgender boys, cisgender girls, and GD AFAB, with the largest difference between cisgender boys and GD AFAB. Regarding sexual orientation and age, the brain's intrinsic functional organization of GD AFAB was both similar to and different from cisgender girls, and both differed from cisgender boys. The pattern of group differences and the networks involved aligned with the hypothesis that brain functional organization is different among GD AFAB (vs. cisgender) adolescents, and certain aspects of this organization relate to brain areas implicated in own-body perception and self-referential thinking. Overall, brain functional organization of GD AFAB was generally more similar to that of cisgender girls than cisgender boys.