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回顾之前的实证研究CS,似乎重要给ERP的主要组件的概述和讨论ERP技术的基础,因为它将进一步理解语言的转换过程。在本小节中,我将主要遵循的一个很好的描述基本原理及应用提供的epr van地狱& Witteman(2009)。首先,大脑细胞产生电活动。这个活动的变化可以通过测量电极放置在头皮上的关键职位。如上所述的研究(2009:55),电压随时间变化的记录称为脑电图(EEG)。这些电压变化构成了ERP信号,反映大脑活动寿命及其外部事件,如刺激词。因此,ERP技术的优点是,它提供了一个学习任务相关的神经活动的发音。

ERP信号包括积极的和消极的山峰,或组件。有两种类型的组件:外生,所引起的刺激的物理特征和发生早期,即在100毫秒内刺激出现,b)内生,反映了认知方面的语言处理和发生至少100 ms刺激后发病。


Before reviewing the empirical studies on CS, it seems important to give an overview of the main ERP components and discuss the basics of the ERP technique as it will further the understanding of the language switching process. In this section I will mainly follow an excellent description of basic principles and applications of EPRs provided by van Hell & Witteman (2009).To start with, brain cells produce electrical activity. The variation of this activity can be measured by electrodes placed in key positions on the scalp. As stated by the researches (2009: 55), the recording of voltage variations over time is called Electroencephalogram (EEG).These voltage changes make up the ERP signal and reflect brain activity which is time-locked to an external event, e.g. a stimulus word. Therefore, the advantage of the ERP technique is that it provides a study of task-related neural activity millisecond-by-millisecond.

ERP signal consists of positive and negative peaks, or components. There are two types of components: a) exogenous, that are caused by the physical characteristics of the stimulus and occur early, i.e. within 100 ms within stimulus onset, and b) endogenous, that reflect cognitive aspects of language processing and occur at least 100 ms post stimulus onset.