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Differential contributions of subthalamic beta rhythms and 1/f broadband activity to motor symptoms in Parkinson’s disease

机译:丘脑下β节律和1 / f宽带活动对帕金森病运动症状的不同贡献

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摘要

Excessive beta oscillatory activity in the subthalamic nucleus (STN) is linked to Parkinson’s Disease (PD) motor symptoms. However, previous works have been inconsistent regarding the functional role of beta activity in untreated Parkinsonian states, questioning such role. We hypothesized that this inconsistency is due to the influence of electrophysiological broadband activity —a neurophysiological indicator of synaptic excitation/inhibition ratio— that could confound measurements of beta activity in STN recordings. Here we propose a data-driven, automatic and individualized mathematical model that disentangles beta activity and 1/f broadband activity in the STN power spectrum, and investigate the link between these individual components and motor symptoms in thirteen Parkinsonian patients. We show, using both modeled and actual data, how beta oscillatory activity significantly correlates with motor symptoms (bradykinesia and rigidity) only when broadband activity is not considered in the biomarker estimations, providing solid evidence that oscillatory beta activity does correlate with motor symptoms in untreated PD states as well as the significant impact of broadband activity. These findings emphasize the importance of data-driven models and the identification of better biomarkers for characterizing symptom severity and closed-loop applications.
机译:丘脑底核(STN)中过度的β振荡活动与帕金森氏病(PD)运动症状有关。但是,先前的研究在未治疗的帕金森病州中关于β活性的功能作用一直不一致,对此作用提出了质疑。我们假设这种不一致是由于电生理宽带活动(一种突触兴奋/抑制比的神经生理指标)的影响所致,它可能混淆STN记录中β活性的测量。在这里,我们提出了一个数据驱动的,自动的,个性化的数学模型,该模型可以解开STN功率谱中的β活性和1 / f宽带活性,并研究13名帕金森病患者中这些个体成分与运动症状之间的联系。我们显示,使用模型数据和实际数据,仅当在生物标志物估计中未考虑宽带活动时,β振荡活动才与运动症状(运动迟缓和僵硬)显着相关,从而提供了有力的证据表明未经治疗的振荡性β活动确实与运动症状相关PD状态以及宽带活动的重大影响。这些发现强调了数据驱动模型和鉴定更好的生物标志物以表征症状严重程度和闭环应用的重要性。

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