Although stress can be considered as an ongoing process that helps an organism to cope with present and future challenges, when it is too intense or uncontrollable, it can lead to adverse consequences for physical and mental health. Social stress specifically, is a highly prevalent traumatic experience, present in multiple contexts, such as war, bullying and interpersonal violence, and it has been linked with increased risk for major depression and anxiety disorders. Nevertheless, not all individuals exposed to strong stressful events develop psychopathology, with the mechanisms of resilience and vulnerability being still under investigation. During this talk, I will identify key gaps in our knowledge about stress vulnerability and I will present our recent data from our contextual fear learning protocol based on social defeat stress in mice.

We solicit applications for a PhD position to develop machine learning techniques for personalized prediction of psychopathology. The position will be part of a large new center aiming to develop a novel dynamic network approach of mental health. This center, the 'LOEWE center DYNAMIC', brings together scientists from a range of disciplines, including psychology, psychiatry, computer science and machine learning, with a shared goal of advancing our understanding of mental disorders and developing new treatment options. The center’s research focuses on the application of dynamic network models at various levels (neurobiological, psychological and psychopathological) to mental disorder research. It brings together researchers from the Universities of Marburg, Giessen, Frankfurt and Darmstadt, as well as the Leibniz Institute for Research and Information in Education DIPF and the Ernst Strüngmann Institute for Neurosciences ESI. The respective university hospitals and the psychotherapy outpatient clinics of the psychological university institutes are also involved, facilitating the rapid transfer of research results into practice. The present opening will be associated with the Department of Computer Science at the University of Frankfurt. The objective of the project is to develop a personalized prediction model for changes in psychopathology (new depressive episodes), behavioral patterns and biological parameters. Many mental illnesses are characterized by changes in the network structure of the brain that affect observable patterns of activity or behavior in the future. Early detection and especially prediction of changes in behavioral parameters, psychopathology and biomarkers could enable targeted, personalized interventions to offer special (additional, more specific) therapies to patients with poor prognosis. The objective of this project is to develop methods for the early and reliable detection and prediction of changes in multimodal data.

Rhythmic changes in sex hormone levels across the ovarian cycle exert powerful effects on the brain and behavior, and confer female-specific risks for neuropsychiatric conditions. In this talk, Dr. Kundakovic will discuss the role of fluctuating ovarian hormones as a critical biological factor contributing to the increased depression and anxiety risk in women. Cycling ovarian hormones drive brain and behavioral plasticity in both humans and rodents, and the talk will focus on animal studies in Dr. Kundakovic’s lab that are revealing the molecular and receptor mechanisms that underlie this female-specific brain dynamic. She will highlight the lab’s discovery of sex hormone-driven epigenetic mechanisms, namely chromatin accessibility and 3D genome changes, that dynamically regulate neuronal gene expression and brain plasticity but may also prime the (epi)genome for psychopathology. She will then describe functional studies, including hormone replacement experiments and the overexpression of an estrous cycle stage-dependent transcription factor, which provide the causal link(s) between hormone-driven chromatin dynamics and sex-specific anxiety behavior. Dr. Kundakovic will also highlight an unconventional role that chromatin dynamics may have in regulating neuronal function across the ovarian cycle, including in sex hormone-driven X chromosome plasticity and hormonally-induced epigenetic priming. In summary, these studies provide a molecular framework to understand ovarian hormone-driven brain plasticity and increased female risk for anxiety and depression, opening new avenues for sex- and gender-informed treatments for brain disorders.

Mental Health problems among youth constitutes an area of significant social, educational, clinical, policy and public health concern. Understanding processes and mechanisms that underlie the development of mental health problems during childhood and adolescence requires theoretical and methodological integration across multiple scientific domains, including developmental science, neuroscience, genetics, education and prevention science. The primary focus of this presentation is to examine the relative role of genetic and family environmental influences on children’s emotional and behavioural development. Specifically, a complementary array of genetically sensitive and longitudinal research designs will be employed to examine the role of early environmental adversity (e.g. inter-parental conflict, negative parenting practices) relative to inherited factors in accounting for individual differences in children’s symptoms of psychopathology (e.g. depression, aggression, ADHD ). Examples of recent applications of this research to the development of evidence-based intervention programmes aimed at reducing psychopathology in the context of high-risk family settings will also be presented.