用脑电波连接度区分帕金森患者与健康人，比行为表现更准。
EEG-estimated functional connectivity, and not behavior, differentiates Parkinson's patients from health controls during the Simon conflict task
- 基于δ/θ频段脑电振荡估算功能连接度
- 连接度差异区分帕金森病与健康人，优于行为或时序特征
- 适合早期诊断与治疗效果评估研究者参考
神经生物标志物对神经与精神疾病研究具有重要意义，可反映疾病状态或治疗效果，甚至在症状或行为变化前就显现。本研究探讨脑电图估算的功能连接（FC）作为帕金森病（PD）的生物标志物。具体分析在西蒙冲突任务中，通过神经振荡介导的FC。该任务诱发感觉-运动冲突，预期帕金森患者与健康对照（HC）存在行为差异。除了空间聚焦的FC方法，还考察了对神经活动动态变化更敏感的时序特征。结果发现，由δ（1–4Hz）和θ（4–7Hz）振荡估算的空间功能连接模式，在区分PD患者与健康对照方面显著优于时序特征或行为表现。研究证实，特定频段的功能连接能有效揭示全脑功能差异，可作为区分正常与病变脑功能的生物标志物。
原文摘要 · Abstract (English)
Neural biomarkers that can classify or predict disease are of broad interest to the neurological and psychiatric communities. Such biomarkers can be informative of disease state or treatment efficacy, even before there are changes in symptoms and/or behavior. This work investigates EEG-estimated functional connectivity (FC) as a Parkinson's Disease (PD) biomarker. Specifically, we investigate FC mediated via neural oscillations and consider such activity during the Simons conflict task. This task yields sensory-motor conflict, and one might expect differences in behavior between PD patients and healthy controls (HCs). In addition to considering spatially focused approaches, such as FC, as a biomarker, we also consider temporal biomarkers, which are more sensitive to ongoing changes in neural activity. We find that FC, estimated from delta (1-4Hz) and theta (4-7Hz) oscillations, yields spatial FC patterns significantly better at distinguishing PD from HC than temporal features or behavior. This study reinforces that FC in spectral bands is informative of differences in brain-wide processes and can serve as a biomarker distinguishing normal brain function from that seen in disease.
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