Fayed Rassoulou

All Publications

• Electrophysiological signatures predict the therapeutic window of deep brain stimulation electrode contacts. NPJ digital medicine Rassoulou, F., Sharma, A., Steina, A., Butz, M., Hartmann, C. J., Bahners, B. H., Vesper, J., Schnitzler, A., Hirschmann, J. 2025; 8 (1): 635

  Abstract

  Deep brain stimulation (DBS) is an effective treatment for Parkinson's disease. Identifying the optimal parameters is a complex task. Here, we investigated whether electrophysiology, combined with machine learning, can support contact selection. We applied tree learning to resting-state magnetoencephalographic and local field potential recordings from the subthalamic nucleus (STN). STN power and STN-cortex coherence in various frequency bands served to predict the therapeutic window. The model successfully predicted therapeutic windows in the original (r = 0.45, p < 0.001, N = 45) and in an independent cohort (r = 0.30, p < 0.001, N = 8). It relied mostly on fast (>35 Hz) subthalamic activity and on STN-cortex coherence in several bands. Furthermore, it was able to order contacts such that the optimal contact can be found faster. Our study demonstrates the feasibility of predicting therapeutic windows from electrophysiological features and could contribute to automated contact selection in the future.

  View details for DOI 10.1038/s41746-025-02089-w

  View details for PubMedID 41162751

  View details for PubMedCentralID PMC12572235

• The deep brain stimulation response network in Parkinson's disease operates in the high beta band. Brain : a journal of neurology Bahners, B. H., Goede, L. L., Zvarova, P., Meyer, G. M., Butenko, K., Lofredi, R., Rajamani, N., Schaper, F. L., Neudorfer, C., Hollunder, B., Pijar, J., Madan, S., Hart, L. A., Sure, M., Steina, A., Rassoulou, F., Hartmann, C. J., Butz, M., Hirschmann, J., Vesper, J., Faust, K., Schneider, G. H., Sander, T. H., Neumann, W. J., Fox, M. D., Miller, K. J., Schnitzler, A., Kühn, A. A., Florin, E., Horn, A. 2026; 149 (7): 2395-2408

  Abstract

  Deep brain stimulation (DBS) of the subthalamic nucleus improves motor symptoms in patients with Parkinson's disease. Using functional MRI, optimal DBS response networks have been characterized. However, neural activity associated with Parkinsonian symptoms is magnitudes faster than what can be resolved by this method. Although both spatial and temporal domains of these networks appear crucial, no single study has yet investigated both domains simultaneously. Here, we aimed at closing this gap by analysing electrophysiological data from a total of n = 127 hemispheres. Using subthalamic local field potentials that were recorded concurrently alongside whole-brain magnetoencephalography in a multi-centre cohort of patients who underwent subthalamic DBS for the treatment of Parkinson's disease (n = 100 hemispheres), we analysed the DBS response network in both spatial and temporal domains. In every cortical vertex, cortico-subthalamic coupling was correlated with stimulation outcomes. This network spatially resembled functional MRI-based findings (R = 0.40, P = 0.039) and explained significant amounts of variance in clinical outcomes (βstd = 0.30, P = 0.002), whereas theta-alpha and low beta coupling did not show significant associations with DBS response (theta-alpha: βstd = -0.02, P = 0.805; low beta: βstd = -0.08, P = 0.426). The 'optimal' high beta coupling map was robust when subjected to various cross-validation designs (10-fold cross-validation: R = 0.29, P = 0.009; split-half design: R = 0.31, P = 0.026) and was able to predict outcomes across DBS centres [R = 0.74; P(1) = 8.9 × 10-5]. We identified a DBS response network that resembles the previously defined MRI network and operates in the high beta band. Maximal connectivity to this network was associated with optimal DBS outcomes and was able to cross-predict clinical improvements across DBS surgeons and centres.

  View details for DOI 10.1093/brain/awaf445

  View details for PubMedID 41645667

  View details for PubMedCentralID PMC13337225

• Exploring the electrophysiology of Parkinson's disease with magnetoencephalography and deep brain recordings. Scientific data Rassoulou, F., Steina, A., Hartmann, C. J., Vesper, J., Butz, M., Schnitzler, A., Hirschmann, J. 2024; 11 (1): 889

  Abstract

  Aberrant information processing in the basal ganglia and connected cortical areas are key to many neurological movement disorders such as Parkinson's disease. Investigating the electrophysiology of this system is difficult in humans because non-invasive methods, such as electroencephalography or magnetoencephalography, have limited sensitivity to deep brain areas. Recordings from electrodes implanted for therapeutic deep brain stimulation, in contrast, provide clear deep brain signals but are not suited for studying cortical activity. Therefore, we combine magnetoencephalography and local field potential recordings from deep brain stimulation electrodes in individuals with Parkinson's disease. Here, we make these data available, inviting a broader scientific community to explore the dynamics of neural activity in the subthalamic nucleus and its functional connectivity to cortex. The dataset encompasses resting-state recordings, plus two motor tasks: static forearm extension and self-paced repetitive fist clenching. Most patients were recorded both in the medicated and the unmedicated state. Along with the raw data, we provide metadata on channels, events and scripts for pre-processing to help interested researchers get started.

  View details for DOI 10.1038/s41597-024-03768-1

  View details for PubMedID 39147788

  View details for PubMedCentralID PMC11327342