University of New Mexico, Department of Psychology, USA.
University of New Mexico, Department of Computer Science, USA.
Clin Neurophysiol. 2018 Feb;129(2):409-418. doi: 10.1016/j.clinph.2017.11.023. Epub 2017 Dec 13.
We aimed to test if EEG responses to novel events reliably dissociated individuals with Parkinson's disease and controls, and if this dissociation was sensitive and specific enough to be a candidate biomarker of cognitive dysfunction in Parkinson's disease.
Participants included N = 25 individuals with Parkinson's disease and an equal number of well-matched controls. EEG was recorded during a three-stimulus auditory oddball paradigm both ON and OFF medication.
While control participants showed reliable EEG habituation to novel events over time, individuals with Parkinson's did not. In the OFF condition, individual differences in habituation correlated with years since diagnosis. Pattern classifiers achieved high sensitivity and specificity in discriminating patients from controls, with a maximum accuracy of 82%. Most importantly, the confidence of the classifier was related to years since diagnosis, and this correlation increased as the time course of differential habituation increasingly distinguished the groups.
These findings identify systemic alteration in an obligatory neural mechanism that may contribute to higher-level cognitive dysfunction in Parkinson's disease.
These findings suggest that EEG responses to novel events in this rapid, simple, and inexpensive test have tremendous promise for tracking individual trajectories of cognitive dysfunction in Parkinson's disease.
我们旨在测试 EEG 对新事件的反应是否能可靠地区分帕金森病患者和对照组,如果这种区分具有足够的敏感性和特异性,可以作为帕金森病认知功能障碍的候选生物标志物。
参与者包括 25 名帕金森病患者和数量相等的匹配对照组。在药物治疗和非药物治疗两种状态下,参与者接受了三刺激听觉Oddball 范式的 EEG 记录。
虽然对照组参与者的 EEG 随着时间的推移对新事件表现出可靠的习惯化,但帕金森病患者则没有。在非药物治疗状态下,习惯化的个体差异与诊断后的时间有关。模式分类器在区分患者和对照组方面具有很高的灵敏度和特异性,最大准确率为 82%。最重要的是,分类器的置信度与诊断后的时间有关,并且这种相关性随着差异习惯化的时间进程越来越能区分两组而增加。
这些发现表明,在这种快速、简单和廉价的测试中,对新事件的 EEG 反应可能与帕金森病的高级认知功能障碍有关。
这些发现表明,这种快速、简单和廉价测试中对新事件的 EEG 反应在跟踪帕金森病患者认知功能障碍的个体轨迹方面具有巨大的潜力。