Trial-level ERPs predicted behavioral responses during self-referential processing in late childhood.

Pan Liu, Xiao Yang, Jaron X Y Tan
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Abstract

Self-referential information is uniquely salient and preferentially processed even in children. The literature has used the self-referent encoding task (SRET) combined with event-related potentials (ERPs) to study self-referential processing and its associations with youth psychopathology. However, it is unclear how the ERP and behavioral indices of SRET are associated with each other, although this knowledge can promote our mechanistic understanding of this construct and its role in psychopathology. We examined this question in 115 9- to 12-year-old children, a critical period for the development of self-related concepts. By applying a multilevel modeling approach to the trial-level data of SRET, we disaggregated the between- and within-person variability and observed within-person, but not between-person, effects of the P2 and late positive potential (LPP) on behavioral responses: a larger P2 on a given trial predicted a faster response in this trial; a larger LPP on a given trial predicted a higher likelihood of endorsing the word of this trial. We provided novel evidence on how the within-person variability of the ERPs predicted the overt responses of the SRET in children. These findings inform our mechanistic knowledge of self-referential processing and shed light on a better understanding of the role of self-referential processing in the development of psychopathology.

试验水平的 ERP 预测了儿童晚期自我参照加工过程中的行为反应。
即使在儿童身上,自我参照信息也具有独特的显著性和优先处理性。有文献利用自我参照编码任务(SRET)结合事件相关电位(ERPs)来研究自我参照加工及其与青少年心理病理学的关联。然而,目前还不清楚自我参照编码任务的ERP和行为指数是如何相互关联的,尽管这一知识可以促进我们对这一结构及其在精神病理学中的作用的机制性理解。我们在 115 名 9 至 12 岁儿童中研究了这一问题,他们正是自我相关概念发展的关键时期。通过对 SRET 的试验级数据应用多层次建模方法,我们分解了人与人之间和人与人之间的变异性,并观察到 P2 和晚期正电位(LPP)对行为反应的人内效应,而非人与人之间的效应:在给定试验中,P2 越大,则预测在该试验中反应越快;在给定试验中,LPP 越大,则预测在该试验中赞同单词的可能性越高。我们提供了新的证据,说明ERPs 的人内变异如何预测儿童 SRET 的公开反应。这些发现为我们提供了自我参照加工的机制知识,有助于我们更好地理解自我参照加工在精神病理学发展中的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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