Subthalamic low beta bursts differ in Parkinson's disease phenotypes

Area of Science:

• Neuroscience
• Computational Neuroscience
• Biomedical Engineering

Background:

• Parkinson's disease (PD) is clinically classified into tremor-dominant (TD) and postural-instability and gait disorder (PIGD) motor phenotypes.
• The underlying electrophysiological differences, particularly in subthalamic nucleus local field potentials (STN-LFP), between these PD phenotypes are not fully understood.

Purpose of the Study:

• To investigate the dynamical aspects of STN-LFP.
• To identify neural correlates distinguishing TD and PIGD phenotypes in Parkinson's disease.
• To characterize beta oscillation dynamics in relation to motor symptoms.

Main Methods:

• Analysis of STN-LFP data from 35 Parkinson's disease patients (15 TD, 20 PIGD) using continuous wavelet transform.
• Application of machine-learning-based methods to characterize beta burst parameters (probability, duration) across phenotypes.
• Definition of optimal burst thresholds and analysis of burst intervals.

Main Results:

• Low-frequency (13-22 Hz) beta burst probability was the most accurate predictor of PD phenotypes (75% accuracy).
• PIGD patients showed significantly longer average beta burst durations (p=0.018), while TD patients exhibited higher burst probability (p=0.014).
• Significant interaction between burst length categories (<400 ms vs. >400 ms) and PD phenotypes was observed (p<0.050). Long burst durations correlated with rigidity-bradykinesia scores (p=0.029), and short burst probability correlated with tremor scores (p=0.038).

Conclusions:

• Subthalamic low-frequency beta burst dynamics differ significantly between TD and PIGD phenotypes.
• These distinct beta burst characteristics correlate with specific motor symptoms in Parkinson's disease.
• The findings enhance the electrophysiological characterization of PD phenotypes and suggest potential criteria for adaptive deep brain stimulation.