Transition in Transgender: Therapy induced changes in brain and behavior

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Transgender individuals are in discomfort with their biological sex and wish to live and be accepted as a member of the other sex. In the last few years the public and media have become more aware of transgender issues. The number of those affected is higher than previously thought, and they often face severe discrimination and are at risk for poor mental and physical health. Many transgender individuals request for cross-sex hormonal treatment and gender confirmation surgery.In recent years, a growing number of neuroimaging studies have inquired into structural and functional correlates of transgender, reporting signs of feminisation in transwomen, and signs of masculinisation in transmen in several sexually dimorphic brain structures as well as functional processes. However, evidence is still sparse especially concerning plastic brain changes in structure and function in the course of hormonal therapy. Furthermore, most studies are confronted with several methodological problems, such as small sample sizes, the lack of adequate control groups as well as no direct comparison between transmen and transwomen, just to name a few.This project hence follows a longitudinal approach to quantify the effects of cross-hormone therapy on brain and behavior, measuring brain structure, as well as brain function over a time period of 6 months following hormone therapy. Next to psychopathological assessments and questionnaire data on stress, emotion and subjective well-being as well as quality of life, we intend to measure behavioral and neural correlates in two paradigms assessing voice gender and face gender perception, continuing but also expanding our preceding data, to characterize basic gender and self-related auditory and visual processes. Furthermore, we will test the hypothesis of a neurobiological gender continuum within the human brain, questioning the validity of a binary gender conceptualization. Based on functional connectivity and questionnaire data we will apply data-based machine learning algorithms naive to the assignment of each participant to his/her gender/sex to classify the subjectively experienced, psychological gender, irrespective of the biological sex. Since we successfully applied this to our already existing data set, we strive for a cross validation of our findings in a new sample. With the longitudinal data we will further test the hypothesis, that hormonal treatment may lead to a reduction in classification accuracy due to therapy-induced changes in direction of their aspired gender identity. We hope, that such precise bio-behavioral markers for gender identity might add clinically and societally relevant knowledge in the field of transgender.