We offer a dynamic multiscale modeling perspective on deep brain stimulation (DBS) to investigate its mechanisms, thereby creating new testable hypotheses, and providing an in silico testing ground for novel stimulation paradigms using The Virtual Brain (TVB).

We plan to continue to enhance our developed and tested Virtual DBS model based on brain network modeling using our newly developed advanced parameter learning methods for the DBS optimization.

We also aim to tackle the same optimization problem from a theoretical perspective applying methods from network and control theory. We plan to perform a first prospective pilot study of testing the simulation-assisted TVB-based electrode settings as a steppingstone toward bringing Virtual DBS modeling into clinical practice.