AbstractGiven the huge symptom diversity and complexity of mental disorders, an individual approach is the most promising avenue for clinical transfer and the establishment of personalized psychiatry. However, due to technical limitations, knowledge about the neurobiological basis of mental illnesses has, to date, mainly been based on findings resulting from evaluations of average data from certain diagnostic groups. We postulate that this could change substantially through the use of the emerging ultra-high-field MRI (UHF-MRI) technology. The main advantages of UHF-MRI include high signal-to-noise ratio, resulting in higher spatial resolution and contrast and enabling individual examinations of single subjects. Thus, we used this technology to assess changes in the properties of resting-state networks over the course of therapy in a naturalistic study of two depressed patients. Significant changes in several network property measures were found in regions corresponding to prior knowledge from group-level studies. Moreover, relevant parameters were already significantly divergent in both patients at baseline. In summary, we demonstrate the feasibility of UHF-MRI for capturing individual neurobiological correlates of mental diseases. These could serve as a tool for therapy monitoring and pave the way for a truly individualized and predictive clinical approach in psychiatric care.