Local Field Potential-Guided Contact Selection Using Chronically Implanted Sensing Devices for Deep Brain Stimulation...

Area of Science:

• Neuroscience
• Biomedical Engineering
• Neurology

Background:

• Local field potential (LFP) activity in the subthalamic nucleus (STN) is a potential biomarker for guiding deep brain stimulation (DBS) in Parkinson's disease (PD).
• Current DBS technology allows for chronic LFP recordings, but a validated algorithm for automated contact selection is still needed.

Purpose of the Study:

• To evaluate a fully automated algorithm for STN-DBS contact selection based on beta-band LFP activity.
• To compare the clinical efficacy of algorithm-selected contacts with standard clinical practice.

Main Methods:

• Recorded LFPs from 14 hemispheres in seven PD patients with newly implanted directional STN DBS leads.
• Developed an algorithm to identify effective monopolar contacts by analyzing weighted average bipolar recordings for elevated beta-band activity.
• Projected recording sites to MNI standard space to assess anatomical feasibility within the STN.

Main Results:

• The algorithm identified stimulation levels and directional contacts with the highest beta activity.
• The mean clinical efficacy of contacts selected by the algorithm was not statistically different from those selected through standard clinical routine.
• Feasibility analysis confirmed the algorithm's potential application within the anatomical boundaries of the STN.

Conclusions:

• The proposed automated algorithm is a viable first step for LFP-based contact selection in STN-DBS for PD using chronically implanted devices.
• This approach holds promise for optimizing DBS therapy by leveraging real-time neural recordings.