Objective: To assess whether using high frequency oscillations (HFO; 150-350 Hz) or beta band oscillations (13-30 Hz) can objectively differentiate the external from the internal segment of the globus pallidus (GPe from GPi) during DBS lead placement surgery in Parkinson’s disease (PD) patients.
Background: The GPi is an effective DBS target for improving motor signs in PD. Localizing the sensorimotor region of GPi using microelectrode recordings (MER) can, however, be difficult due to ambiguity in neural activity between GPe and GPi. Beta band (13-30 Hz) oscillations are an established biomarker associated with PD and have successfully been used to identify the borders of the subthalamic nucleus (STN). Identifying the borders of GPi, however, has been more challenging. Recently, HFOs have been indicated as a potential biomarker in the GPi of PD patients but their utility in identifying the borders of GPi has not been thoroughly studied.
Method: We recorded LFP activity from 3 microelectrodes simultaneously in 34 PD patients (45 nuclei) in the off-medication state undergoing implantation of DBS leads. MER tracks started 15 mm above the targeted ventral border of GPi. Dorsal/ventral borders of GPi were determined from MER by an electrophysiologist with expertise in mapping the GPi/GPe in PD patients. Peak power of the HFO center frequency was extracted from microelectrode LFPs using the FOOOF method and peak beta power using the empirical mode decomposition method.
Results: Mean peak power of HFOs inside GPi was significantly higher compared to those outside (p<0.01) while mean peak power of beta failed to reach significance. A generalized linear mixed-effects model analysis showed HFO peak power alone, as well as in combination with beta power, was a significant predictor for distinguishing neural activity inside GPi compared to outside of GPi, while beta band power alone was not.
Conclusion: These data provide evidence that peak HFO power outperformed beta power for discriminating GPi from GPe in PD patients, providing compelling support for the incorporation of HFOs into automated GPi detection software for PD patients. Additionally, these data support further exploration into the pathophysiological relevance of HFOs in the GPi in PD and how these signals may inform DBS programming or biomarker-based adaptive stimulation.
To cite this abstract in AMA style:
J. Aman, K. O'Neill, S. Safo, M. Hill, S. Alberico, R. Cole, L. Johnson, J. Wang, K. Domingo, L. de Almeida, S. Cooper, D. Darrow, R. Mcgovern Iii, M. Park, L. Eberly, J. Vitek. Synchronized High Frequency Neural Oscillations as a Biomarker for Differentiating the Internal from the External Segment of the Globus Pallidus in Parkinson’s Disease [abstract]. Mov Disord. 2025; 40 (suppl 1). https://www.mdsabstracts.org/abstract/synchronized-high-frequency-neural-oscillations-as-a-biomarker-for-differentiating-the-internal-from-the-external-segment-of-the-globus-pallidus-in-parkinsons-disease/. Accessed October 5, 2025.« Back to 2025 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/synchronized-high-frequency-neural-oscillations-as-a-biomarker-for-differentiating-the-internal-from-the-external-segment-of-the-globus-pallidus-in-parkinsons-disease/