Investigating brain networks affected by different TMS approaches in psychiatric diseases

Psychiatric disorders like depression are increasingly viewed as disorders of brain networks. In healthy individuals, there is a balance between some of the most crucial networks of the brain, however, in disorders like depression and obsessive-compulsive disorder, this balance is disrupted, leading to very different sets of symptoms like anhedonia and anxiousness.

The most common treatment option for major depressive disorder is anti-depressant medication. Anti-depressant medication can cause severe side effects, furthermore, not all patients respond to medication-based treatment. In this project, we assess an alternative, less invasive treatment approach that has gained increased use in recent years – namely transcranial magnetic stimulation (TMS).

Although treatment methods involving TMS are constantly developing, there is still great variability in response to treatment. Additionally, exactly how TMS provokes its therapeutic effect is not fully understood. There are still numerous unresolved questions, such as where to stimulate, how to time the stimulation, how strongly to stimulate, and so on. Carrying out experiments in clinical populations to test all these different variables one at a time is not feasible.

Luckily, the whole process of improving treatment approaches can be speeded up by simulation studies utilizing preexisting datasets. In this PhD project, we aim to get closer to answering these questions on where and how to stimulate the brain for more effective treatment of psychiatric disorders by combining realistic electric-field modeling with different MRI modalities. By assessing, which brain networks are targeted by different TMS coils and coil placements, this project can lead to discoveries for improving future TMS protocols and thus serve as an important prior step to conducting therapeutical interventional studies.