EEG-Based DBS Programming in Parkinson’s Disease

Mar 13, 2026

EEG-Based Algorithm Predicts Optimal DBS Contacts in Parkinson’s Disease

At the DGKN Annual Meeting 2026, several members of the ReTune consortium contributed to the scientific program. Prof. Andrea Kühn and Prof. Jens Volkmann, spokesperson and deputy spokesperson of the ReTune consortium, delivered keynote lectures highlighting advances in neuromodulation and movement disorders. In addition, Dr. Bahne Bahners presented a novel EEG-based method to support the programming of deep brain stimulation (DBS) in Parkinson’s disease.

Moving beyond trial and error in DBS programming

Identifying effective stimulation settings for DBS remains a time intensive process in routine care. Initial programming sessions can take up to two hours and often require multiple follow-up visits. This iterative trial and error approach reflects the lack of objective biomarkers to guide parameter selection. Dr. Bahners’ work aims to overcome this limitation by introducing a data driven method based on electroencephalography (EEG). Specifically, the study investigates whether a dry EEG system, which can be applied more quickly than conventional gel-based setups, can be used to predict clinically optimal stimulation contacts.

Decoding brain responses to stimulation

The approach focuses on DBS evoked potentials, that is, the brain’s electrophysiological response to stimulation pulses delivered to the subthalamic nucleus. These signals were recorded using EEG and analyzed to identify patterns associated with clinical outcomes. The algorithm was developed in a cohort of 30 patients with Parkinson’s disease and subsequently evaluated in a prospective cohort of 11 additional patients. The results show that specific features of the evoked brain response explain a substantial portion of the variability in patient outcomes. Importantly, the model was able to predict the optimal stimulation contact in previously unseen patients, highlighting its potential for real world application.

Toward faster and more objective DBS programming

By linking stimulation induced brain responses to clinical efficacy, the method provides a principled framework for selecting stimulation parameters. This could significantly reduce programming time and improve consistency across clinical settings. The use of dry EEG is particularly relevant for translation into practice, as it enables faster setup and more flexible use in clinical environments compared to traditional systems. International collaboration and ReTune integration

The data analysis was conducted during Dr. Bahners’ research stay in the laboratory of Prof. Andreas Horn at Brigham and Women’s Hospital, Harvard Medical School in Boston. The study emerged from a collaborative effort between multiple ReTune groups in Berlin and partners in Düsseldorf, reflecting the consortium’s strong integration of computational and clinical expertise. The findings align closely with ReTune’s goal of biomarker driven and personalized neuromodulation strategies, particularly in the context of adaptive and data guided DBS.

Outlook

The presented work provides a proof of concept for EEG based guidance of DBS programming. Future studies will be required to validate the approach in larger cohorts and to integrate it into clinical workflows. If successful, such tools could represent an important step toward more efficient and individualized treatment for people with Parkinson’s disease.