Master Thesis: A computational model of transcutaneous Vagus Nerve Stimulation
Vagus Nerve Stimulation (VNS) is an effective clinical treatment for many neurological disorders, including epilepsy, depression and pain. However, the mechanisms of action between the applied electric fields and the underlying neural circuits remain largely enigmatic, limiting both the clinical efficacy as well as the pace of translational research of VNS. Computational modeling of VNS has recently emerged as a powerful tool for investigating both theoretical mechanisms and techniques to optimize the clinical application of the technology. Thus far VNS modeling has focused on invasive VNS, with only minimal focus on non-invasive VNS.
The successful student is asked to develop a patient-specific 3D Finite Element Method (FEM) model of the vagus nerve and its surrounding and evaluate the effects of stimulation parameter selection on the electric field generated by transcutaneous VNS. The student is asked to couple the results of the FEM analysis with compartmental cable models of the axon, assess the outcomes of stimulation parameter selection of various neural substrates and optimise stimulation parameters accordingly.
|Project type||Master thesis|
|Period||Summer term 2022|
|Presence time||Virtual and/or at the Chair of Digital Health|
|Useful knowledge||Finite Element Method, Compartmental Cable Models, Programming, Neuroscience|
|Work distribution||50 % modeling and 50 % programming|
|Registration||E-mail to Dr. Andreas Rowald|
Literature recommendations are provided during the meetings. The candidate is further encouraged to research relevant publications on this topic.
Final presentation and final report/thesis