The Deep Brain Stimulation Response Network in Parkinson's Disease Operates in the High Beta Band

Area of Science:

• Neuroscience
• Neurology
• Biomedical Engineering

Background:

• Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a key treatment for Parkinson's disease motor symptoms.
• Previous research using fMRI identified optimal DBS response networks but lacked the temporal resolution to capture fast neural activity.
• Investigating both spatial and temporal domains of DBS networks is crucial for understanding treatment efficacy.

Purpose of the Study:

• To simultaneously investigate the spatial and temporal domains of subthalamic nucleus DBS response networks.
• To identify neural activity patterns associated with optimal DBS outcomes in Parkinson's disease.
• To validate findings across multiple centers and surgical teams.

Main Methods:

• Concurrent recording of subthalamic local field potentials and whole-brain magnetoencephalography in 100 Parkinson's disease hemispheres undergoing STN-DBS.
• Correlation analysis of cortico-subthalamic coupling with stimulation outcomes across different frequency bands (theta-alpha, low beta, high beta).
• Cross-validation and multi-center prediction to assess the robustness and generalizability of identified networks.

Main Results:

• A DBS response network was identified, spatially resembling fMRI-defined networks and significantly predicting clinical outcomes (β = 0.30, P = 0.002).
• High-beta band cortico-subthalamic coupling was strongly associated with optimal DBS outcomes.
• Theta-alpha and low beta coupling showed no significant association with DBS response.
• The identified high-beta network demonstrated robustness through cross-validation and predictive power across centers (R = 0.74, P = 8.9e-5).

Conclusions:

• A DBS response network operating in the high-beta frequency band was identified, complementing prior fMRI findings.
• Maximal connectivity within this high-beta network is associated with optimal clinical improvement in Parkinson's disease patients.
• This network serves as a reliable predictor of DBS treatment outcomes across different surgical settings.