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The N400 ERP component reflects an error-based implicit learning signal during language comprehension
European Journal of Neuroscience ( IF 2.7 ) Pub Date : 2021-09-17 , DOI: 10.1111/ejn.15462
Alice Hodapp 1 , Milena Rabovsky 1
Affiliation  

The functional significance of the N400 evoked-response component is still actively debated. An increasing amount of theoretical and computational modelling work is built on the interpretation of the N400 as a prediction error. In neural network modelling work, it was proposed that the N400 component can be interpreted as the change in a probabilistic representation of meaning that drives the continuous adaptation of an internal model of the statistics of the environment. These results imply that increased N400 amplitudes should correspond to greater adaptation, which can be measured via implicit memory. To investigate this model derived hypothesis, the current study manipulated expectancy in a sentence reading task to influence N400 amplitudes and subsequently presented the previously expected vs. unexpected words in a perceptual identification task to measure implicit memory. As predicted, reaction times in the perceptual identification task were significantly faster for previously unexpected words that induced larger N400 amplitudes in the previous sentence reading task. Additionally, it could be demonstrated that this adaptation seems to specifically depend on the process underlying N400 amplitudes, as participants with larger N400 differences during sentence reading also exhibited a larger implicit memory benefit in the perceptual identification task. These findings support the interpretation of the N400 as an implicit learning signal driving adaptation in language processing.

中文翻译:

N400 ERP 组件反映了语言理解过程中基于错误的隐式学习信号

N400 诱发反应成分的功能意义仍在争论中。越来越多的理论和计算建模工作建立在将 N400 解释为预测误差的基础上。在神经网络建模工作中,有人提出 N400 组件可以解释为意义的概率表示的变化,它推动了环境统计的内部模型的不断适应。这些结果意味着增加的 N400 振幅应该对应于更大的适应,这可以通过内隐记忆来测量。为了研究这个模型衍生的假设,当前的研究操纵了句子阅读任务中的期望值来影响 N400 振幅,随后呈现了先前预期与 在感知识别任务中测量内隐记忆中的意外单词。正如预测的那样,对于先前意外的单词,感知识别任务中的反应时间明显更快,这些单词在之前的句子阅读任务中引起了更大的 N400 振幅。此外,可以证明这种适应似乎特别依赖于 N400 振幅的基础过程,因为在句子阅读期间具有较大 N400 差异的参与者在感知识别任务中也表现出更大的内隐记忆益处。这些发现支持将 N400 解释为内隐学习信号驱动语言处理中的适应。感知识别任务中的反应时间对于先前意外的单词明显更快,这些单词在之前的句子阅读任务中引起了更大的 N400 振幅。此外,可以证明这种适应似乎特别依赖于 N400 振幅的基础过程,因为在句子阅读期间具有较大 N400 差异的参与者在感知识别任务中也表现出更大的内隐记忆益处。这些发现支持将 N400 解释为内隐学习信号驱动语言处理中的适应。感知识别任务中的反应时间对于先前意外的单词明显更快,这些单词在之前的句子阅读任务中引起了更大的 N400 振幅。此外,可以证明这种适应似乎特别依赖于 N400 振幅的基础过程,因为在句子阅读期间具有较大 N400 差异的参与者在感知识别任务中也表现出更大的内隐记忆益处。这些发现支持将 N400 解释为内隐学习信号驱动语言处理中的适应。因为在句子阅读期间具有较大 N400 差异的参与者在知觉识别任务中也表现出更大的内隐记忆益处。这些发现支持将 N400 解释为内隐学习信号驱动语言处理中的适应。因为在句子阅读期间具有较大 N400 差异的参与者在知觉识别任务中也表现出更大的内隐记忆益处。这些发现支持将 N400 解释为内隐学习信号驱动语言处理中的适应。
更新日期:2021-11-10
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