Master Thesis: A computational model of Deep Brain Stimulation

Background

Deep Brain Stimulation (DBS) is an effective clinical treatment for movement disorders, such as Parkinson’s disease and is actively investigated for treatment of several neurological dysfunctions such as mood or memory disorders. 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 DBS. Computational modeling of DBS has recently emerged as a powerful tool for investigating both theoretical mechanisms and techniques to optimize the clinical application of the technology. Much of the field has focused on patient-specific DBS models, which had a great impact on surgical targeting and stimulation parameter selection.

Aim 

The successful student is asked to develop a patient-specific 3D Finite Element Method (FEM) model of the human brain and evaluate the effects of stimulation parameter selection on the electric field generated by DBS. 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.

Data

Literature

Literature recommendations are provided during the meetings. The candidate is further encouraged to research relevant publications on this topic.

Examination

Final presentation and final report/thesis

Contact

Dr. Andreas Rowald
Research Group Leader
Henkestraße 91, Haus 7, 1. OG
91052 Erlangen
Germany
📞+49 9131 85-23604
✉andreas.rowald@fau.de

Category: SS2022, Student Projects, Work or Study with us Archive