Department of Occupational Therapy, Creighton University, Omaha, NE 68178, USA.
Eur J Neurosci. 2010 Oct;32(8):1388-96. doi: 10.1111/j.1460-9568.2010.07384.x. Epub 2010 Sep 16.
Recent studies have investigated the relationship between psychological symptoms and personality traits and error monitoring measured by error-related negativity (ERN) and error positivity (Pe) event-related potential (ERP) components, yet there remains a paucity of studies examining the collective simultaneous effects of psychological symptoms and personality traits on error monitoring. This present study, therefore, examined whether measures of hyperactivity-impulsivity, depression, anxiety and antisocial personality characteristics could collectively account for significant interindividual variability of both ERN and Pe amplitudes, in 29 healthy adults with no known disorders, ages 18-30 years. The bivariate zero-order correlation analyses found that only the anxiety measure was significantly related to both ERN and Pe amplitudes. However, multiple regression analyses that included all four characteristic measures while controlling for number of segments in the ERP average revealed that both depression and antisocial personality characteristics were significant predictors for the ERN amplitudes whereas antisocial personality was the only significant predictor for the Pe amplitude. These findings suggest that psychological symptoms and personality traits are associated with individual variations in error monitoring in healthy adults, and future studies should consider these variables when comparing group difference in error monitoring between adults with and without disabilities.
最近的研究调查了心理症状和人格特质与错误监测之间的关系,错误监测通过错误相关负波(ERN)和错误正波(Pe)事件相关电位(ERP)成分来衡量,然而,关于心理症状和人格特质对错误监测的综合影响的研究仍然很少。因此,本研究在 29 名年龄在 18 至 30 岁之间、无已知障碍的健康成年人中,检验了多动冲动、抑郁、焦虑和反社会人格特征的测量值是否可以共同解释 ERN 和 Pe 振幅的个体间显著差异。双变量零阶相关分析发现,只有焦虑测量值与 ERN 和 Pe 振幅均显著相关。然而,包括所有四个特征测量值并控制 ERP 平均值中的段数的多元回归分析表明,抑郁和反社会人格特征均是 ERN 振幅的显著预测因子,而反社会人格是 Pe 振幅的唯一显著预测因子。这些发现表明,心理症状和人格特质与健康成年人的错误监测个体差异有关,未来的研究在比较残疾和非残疾成年人之间的错误监测组间差异时,应该考虑这些变量。