Local Field Potentials Predict Motor Performance in Deep Brain Stimulation for Parkinson's Disease

Area of Science:

• Neuroscience
• Biomedical Engineering
• Neurology

Background:

• Deep brain stimulation (DBS) is a key treatment for Parkinson's disease (PD).
• Programming DBS with segmented electrodes presents clinical challenges.
• Novel sensing neurostimulators offer potential for improved programming.

Purpose of the Study:

• Investigate local field potentials (LFPs) and their modulation by DBS.
• Assess electrophysiological biomarkers for facilitating clinical programming in PD patients.
• Evaluate sensing-enabled neurostimulators in chronically implanted patients.

Main Methods:

• Included 16 PD patients (31 hemispheres) with subthalamic nucleus DBS and sensing neurostimulators.
• Recorded LFPs 3 months post-surgery after medication withdrawal.
• Acquired LFPs during OFF stimulation and monopolar review of directional/ring contacts.
• Computed directional and stimulation-induced beta power suppression.
• Correlated motor performance with electrophysiological data and electrode placement.

Main Results:

• Stronger beta power suppression correlated with better motor performance at higher stimulation amplitudes.
• Directional beta power and stimulation-induced suppression predicted motor performance across contacts.
• Beta power suppression within hemispheres was superior to directional beta power for identifying optimal contacts.
• Clinically activated contacts showed stronger beta power suppression than non-activated ones.

Conclusions:

• Stimulation-induced beta power suppression is more effective than directional beta power for selecting optimal DBS contacts.
• Electrophysiological biomarkers can guide the programming of directional DBS systems in PD.
• This approach may enhance therapeutic outcomes for Parkinson's disease patients.