On 13 August, Torge Worbs will defend his PhD thesis entitled "Integrating Personalized Electric Field Simulations with Detailed Neural Modeling for Dose Control of Transcranial Magnetic Brain Stimulation"

Time: 15:00-18:00

Place: Bldg. 341, auditorium 22 & Zoom:

https://dtudk.zoom.us/meeting/register/nwAdK6GGRt2osVw5C63CXw

Please be aware that the PhD defence may be recorded - This will also be informed at the beginning of the PhD defence.

Supervisor: Professor Axel Thielscher

Co-supervisor: Professor Kristoffer Hougaard Madsen

Assessment committee:

Associate Professor Sanne Simone Kaalund, DTU Professor Andreas Vlachos, University of Freiburg Professor Peter Jedlicka, University of Giessen

Chairperson:

Associate Professor Jens Hjotkjær, DTU

Abstract:

Transcranial magnetic stimulation (TMS) is a non-invasive method for stimulating the brain. A current flow through a magnetic coil placed on the scalp generates brief, rapidly changing magnetic fields, which painlessly pass through the skull and, in turn, induce an electric field in the brain tissue. This electric field drives small currents that can activate neurons and influence brain activity. TMS is widely used in neuroscience research and is an approved treatment for several psychiatric disorders, including depression and obsessive–compulsive disorder. However, despite its clinical success, it is still not well understood how neurons are activated by TMS and why treatment effects differ between individuals.

This PhD project addresses these questions by developing new computational models that link brain-scale stimulation with the behavior of individual neurons. First, it introduces a framework for modeling deformable TMS coils and shows that realistic coil shapes and placements can lead to substantial differences in the induced electric fields across individuals, even with standard clinical coils. Second, the work combines highly detailed reconstructions of human neurons from electron microscopy data with biologically informed simplified models to identify the most likely neural targets of TMS. Contrary to earlier assumptions, the results suggest that the most sensitive site is a sharp bend in nerve fibers where gray matter transitions into superficial white matter, rather than the ends of axons. Finally, the thesis develops fast surrogate models that can predict neural activation accurately while reducing computational cost.

Overall, this work provides a clearer and more realistic understanding of how TMS interacts with the human brain. The methods developed here support more precise and efficient stimulation planning and open the door to future applications such as personalized therapies, improved dosing strategies, and studies of long-term brain network effects and plasticity.