爆裂
丘脑底核
神经科学
脑深部刺激
BETA(编程语言)
局部场电位
帕金森病
心理学
听力学
医学
疾病
内科学
计算机科学
程序设计语言
作者
Arnaldo Fim Neto,Júlia Baldi de Luccas,Bruno Leonardo Bianqueti,Luiz Ricardo da Silva,Tiago P. Almeida,André K. Takahata,Manoel Jacobsen Teixeira,Eberval Gadelha Figueiredo,Slawomir J. Nasuto,Maria Sheila Guimarães Rocha,Diogo C. Soriano,Fábio Godinho
标识
DOI:10.1016/j.clinph.2022.05.013
摘要
Parkinson's disease (PD) patients may be categorized into tremor-dominant (TD) and postural-instability and gait disorder (PIGD) motor phenotypes, but the dynamical aspects of subthalamic nucleus local field potentials (STN-LFP) and the neural correlates of this phenotypical classification remain unclear.35 STN-LFP (20 PIGD and 15 TD) were investigated through continuous wavelet transform and machine-learning-based methods. The beta oscillation - the main band associated with motor impairment in PD - dynamics was characterized through beta burst parameters across phenotypes and burst intervals under specific proposed criteria for optimal burst threshold definition.Low-frequency (13-22 Hz) beta burst probability was the best predictor for PD phenotypes (75% accuracy). PIGD patients presented higher average burst duration (p = 0.018), while TD patients exhibited higher burst probability (p = 0.014). Categorization into shorter and longer than 400 ms bursts led to significant interaction between burst length categories and the phenotypes (p < 0.050) as revealed by mixed-effects models. Long burst durations and short bursts probability positively correlated, respectively, with rigidity-bradykinesia (p = 0.029) and tremor (p = 0.038) scores.Subthalamic low-frequency beta bursts differed between TD and PIGD phenotypes and correlated with motor symptoms.These findings improve the PD phenotypes' electrophysiological characterization and may define new criteria for adaptive deep brain stimulation.
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