Olbrich Sebastian, van Dinteren Rik, Arns Martijn
Neuropsychobiology. 2015;72(3-4):229-40. doi: 10.1159/000437435. Epub 2016 Feb 23.
Personalized medicine in psychiatry is in need of biomarkers that resemble central nervous system function at the level of neuronal activity. Electroencephalography (EEG) during sleep or resting-state conditions and event-related potentials (ERPs) have not only been used to discriminate patients from healthy subjects, but also for the prediction of treatment outcome in various psychiatric diseases, yielding information about tailored therapy approaches for an individual. This review focuses on baseline EEG markers for two psychiatric conditions, namely major depressive disorder and attention deficit hyperactivity disorder. It covers potential biomarkers from EEG sleep research and vigilance regulation, paroxysmal EEG patterns and epileptiform discharges, quantitative EEG features within the EEG main frequency bands, connectivity markers and ERP components that might help to identify favourable treatment outcome. Further, the various markers are discussed in the context of their potential clinical value and as research domain criteria, before giving an outline for future studies that are needed to pave the way to an electrophysiological biomarker-based personalized medicine.
精神病学中的个性化医疗需要能够在神经元活动水平上反映中枢神经系统功能的生物标志物。睡眠或静息状态下的脑电图(EEG)以及事件相关电位(ERP)不仅被用于区分患者与健康受试者,还用于预测各种精神疾病的治疗结果,从而为个体提供量身定制的治疗方法相关信息。本综述聚焦于两种精神疾病,即重度抑郁症和注意力缺陷多动障碍的基线EEG标志物。它涵盖了来自EEG睡眠研究和警觉调节、阵发性EEG模式和癫痫样放电、EEG主要频段内的定量EEG特征、连接性标志物以及可能有助于识别良好治疗结果的ERP成分等潜在生物标志物。此外,在为基于电生理生物标志物的个性化医疗铺平道路所需的未来研究勾勒轮廓之前,将在其潜在临床价值和作为研究领域标准的背景下讨论各种标志物。