Dr Horn is a medical scientist with training in neuroimaging, movement disorders, software development and both invasive and noninvasive brain stimulation and the group leader of the Network Stimulation Laboratory at Brigham & Women’s Hospital, Massachusetts General Hospital Boston and Charité – University Medicine Berlin. His main interest and research focus lies in the development and improvement of methods to analyze brain stimulation sites to study network interactions of neuromodulation in the human brain. He is also the host of a podcast focusing on brain stimulation.

In the interview with Dr Horn we explore how the impact of deep brain stimulation on the connectome can be studied, and how it can be used to improve patients lives. “In contrast to many other neuroimaging domains, there is a more or less direct translation [..] to clinical practice”, says Dr Horn, and explains how for example networks that have been identified via DBS can later be targeted with noninvasive stimulation methods such as multifocal transcranial direct current stimulation (tDCS), for example to improve patients’ conditions in movement disorders such as Parkinson's disease. Among many other things, Dr Horn also lets us in on an informally ongoing challenge at Harvard University whether structural or functional measures provide better predictions for DBS outcomes. He explains why his lab has gradually shifted away from using patient specific connectivity data to precise normative connectomes for studying which brain networks should optimally be modulated for maximal effects.

In his keynote at OHBM 2023, Dr Horn will give us a tour through his findings from years of work studying the effects of deep brain stimulation on the connectome across different disorders, ranging across neurological, neuropsychiatric and psychiatric diseases. He will illustrate how his findings can be transferred across disorders to inform one another and how they can be further used to inform neurocognitive effects and behaviors such as risk-taking and impulsivity.