Form-to-expectation matching effects on first-pass eye movement measures during reading.
Form-to-expectation matching effects on first-pass eye movement measures during reading.
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阅读过程中形式与期望匹配对首次眼动测量的影响。
DOI：
10.1037/xhp0000054
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Tanenhaus,MichaelK
中科院分区：
文献类型：
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作者：
Farmer,ThomasA;Yan,Shaorong;Bicknell,Klinton;Tanenhaus,MichaelK
最近的脑电图/脑磁图（EEG/MEG）研究表明，当上下文信息高度预测语言信号的某些属性时，从上下文生成的期望可以转化为对可能出现在展开信号的后续部分中的基于物理形式的属性的令人惊讶的低水平估计。然而，在自然阅读过程中是否会产生和评估基于形式的期望仍不清楚。我们监测了参与者在名词预测环境中阅读语音上典型和非典型名词时的眼球运动（实验1），结果表明，当强烈期望一个名词时，对于具有类别典型形式特征的名词，首次眼球运动测量的注视持续时间（包括首次注视持续时间、凝视持续时间和过去时间）较短。在实验 2 和 3 中，典型和非典型名词被放置在规范化的句子上下文中，以创建对名词的可变强度的期望。情境和典型性在凝视持续时间内显着相互作用。这些结果表明，在阅读过程中，从更高级别的基于类别的期望翻译而来的基于形式的期望可以促进上下文中单词的处理，并且它们对词汇处理的影响根据类别期望的强度进行分级。
Recent Electroencephalography/Magnetoencephalography (EEG/MEG) studies suggest that when contextual information is highly predictive of some property of a linguistic signal, expectations generated from context can be translated into surprisingly low-level estimates of the physical form-based properties likely to occur in subsequent portions of the unfolding signal. Whether form-based expectations are generated and assessed during natural reading, however, remains unclear. We monitored eye movements while participants read phonologically typical and atypical nouns in noun-predictive contexts (Experiment 1), demonstrating that when a noun is strongly expected, fixation durations on first-pass eye movement measures, including first fixation duration, gaze duration, and go-past times, are shorter for nouns with category typical form-based features. In Experiments 2 and 3, typical and atypical nouns were placed in sentential contexts normed to create expectations of variable strength for a noun. Context and typicality interacted significantly at gaze duration. These results suggest that during reading, form-based expectations that are translated from higher-level category-based expectancies can facilitate the processing of a word in context, and that their effect on lexical processing is graded based on the strength of category expectancy.