Due to my background in math and physics I am really interested in the link between applied science and neurocognitive methods. Especially the field of brain computer interfaces (BCI) and neurofeedback (NFB) provides such combinations and research in this area is of great importance, e.g. in combination with motor imagery (MI) to support neurorehabilitation. In general, MI NFB can be beneficial for all neurocognitive disorders affecting the motor areas, e.g. Parkinsons’s disease (PD).
A promising tool for MI NFB is functional Near Infrared Spectroscopy (fNIRS). However, research in the field of fNIRS-based motor imagery NFB is still lacking. Therefore, the aim of my PhD project is the development of a MI NFB protocol in combination with fNIRS, considering advanced methods from the field of mathematics and computer science (e.g., machine learning) to accomplish this goal. In the long term, this protocol should be applied in order to alleviate motor symptoms in patients with PD, preferably in a mobile setup usable at home.

Furthermore, I am interested in finding an adequate method (e.g., classification) to detect movement in electromyography (EMG) data. This is of particular interest for our group both as a control variable in MI when analysing data of healthy subjects and to detect minute movements in patients (e.g., after stroke) after MI NFB training.

Since May 2018
PhD student, Neuropsychology Lab, Department of Psychology, Carl von Ossietzky University Oldenburg, Germany

May 2018
M.Sc. Neurocognitive Psychology, Carl von Ossietzky University Oldenburg, Germany

September 2015
B. Sc. Naturwissenschaften i. d. Informationsgesellschaft (main focus on mathematics/physics), Technical University Berlin, Germany