Oyrgen/University of Melbourne
The overall aim of my research is to investigate quantifications of the biological age to better understand the complex interplay between mental health and aging. During my PhD, I focused on the development of machine learning models using neuroimaging data from large-scale population cohorts and global consortia, and the application of these models to (clinical) datasets to identify contributing factors to biological aging. Recently, I was awarded with a Rubicon grant from the Dutch NWO to continue this line of research at the University of Melbourne as a Postdoctoral Research Fellow. Here, I will extend our work to young persons and evaluate whether abnormal age-related neurodevelopmental deviations predict functioning, disease severity, and treatment response. This ongoing work is a collaborative effort between, amongst others, researchers involved in the ENIGMA consortium.
neuroimaging, brain age, machine learning, mental health, ENIGMA