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Event-related potentials support a dual process account of the Embedded Chinese Character Task

机译:事件相关的潜力支持嵌入式汉字任务的双程处理帐户

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Tests of the principles of dual process theory are typically conducted in the reasoning and judgement/decision-making literature. The present study explores dual process explanations with a new paradigm – the Embedded Chinese Character Task (ECCT). The beauty of this task is that it allows the contrast of automatic and deliberate processes without the potential for conflict. We used event-related potentials (ERPs) and behavioral measures to investigate the time course of automatic (Type 1) and deliberative (Type 2) processes on the ECCT. Thus we explored whether there were differences in processing speed in neural activation. The ECCT requires the extraction of one Chinese character from another, which requires either an automatic strategy reliant on knowledge of Chinese character formation and meaning (based on theradical), or a deliberative strategy using the shape of the components of the character (based on thestroke). Participants judged whether character elements were included or excluded in test characters. Faster response time were observed when judging 'inclusion relations' on automatic problems supporting the proposal that they required a Type 1 process. In line with the behavioral results, the hypothesized faster automatic process showed the rapid differentiation of N2 and P3b components between inclusion and exclusion responses, while no difference was shown for deliberative problems. Thus, neural differences in processing were shown between automatic and deliberate problems, and automatic processing was faster than deliberate processing.
机译:通常在推理和判断/决策文献中进行双流程理论原则的测试。本研究探讨了具有新范式的双程解释 - 嵌入式汉字任务(ecct)。这项任务的美丽是它允许自动和刻意流程对比,而无需冲突潜力。我们使用了与事件相关的潜力(ERP)和行为措施来调查ECCT上的自动(类型1)和审议(类型2)过程的时间过程。因此,我们探讨了神经激活中的处理速度是否存在差异。 ecct要求从另一个中提取一个汉字,这需要自动策略依赖于汉字形成和意义的知识(基于Theradical),或使用角色组件的形状的审议策略(基于Thestroke )。参与者判断是否包含字符元素或以测试字符排除。当判断“包含关系”时,在支持提案的自动问题上观察到更快的响应时间。符合行为结果,假设更快的自动过程显示夹杂物和排除响应之间的N2和P3B部件的快速分化,同时显示出用于审议问题的差异。因此,在自动和刻意的问题之间显示了处理的神经差异,并且自动处理比刻意处理更快。

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