I completed two BScs, in Mathematics and Biomedical Sciences, and a MSc in Cognitive Neuroscience at the Radboud University Nijmegen, in the Nethderlands. During these programs, I did courses and conducted research on machine learning and computational neuroscience. I am proficient in several programming languages (Python, Matlab, R) and applied them to set up my experiments and analyze their results. During my thesis research, and my later work as research assistant at the Donders Centre for Cognitive Neuroimaging and the Behavioral Science Institute of the Radboud University, I gained experience with conducting experiments (including MRI, EEG, physiology and pupil recordings), as well as with analyzing experimental results.
During my time in this lab, I aim to use computational modeling on neuroimaging and behavioral data to improve classification of disorders. To achieve this, I will use different model frameworks (e.g. the reinforcement meta-learner and active inference) to model the differences between healthy people, and patients suffering from depression.
I aim to develop a script that uses model inversion of these different model frameworks on the behavioral data of a participant performing a decision-making task, in order to determine the model parameters for this specific participant. I will verify this data, and investigate how these parameters allow for differentiation between healthy participants and participants suffering from depression.