Readers scrutinize lexical familiarity only in the absence of expectations: Evidence from lexicality effects on event-related potentials

IF 2.1 2区 心理学 Q1 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY
Neslihan Caliskan, Sara Milligan, Elizabeth R. Schotter
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引用次数: 0

Abstract

Readers generate predictions about the meaning of upcoming words while reading constraining sentences. These predictions feed down to predictions about orthographic form. For example, orthographic neighbors of predicted words yield reduced N400 amplitudes compared to non-neighbors regardless of lexical status (Laszlo & Federmeier, 2009). We investigated whether readers are sensitive to lexicality in low constraint sentences when they must scrutinize the perceptual input more closely for word recognition. In a replication and extension of Laszlo and Federmeier (2009), we observed similar patterns as the original study in high constraint sentences, but found a lexicality effect in low constraint sentences that was not present when the sentence was highly constraining. This suggests that, in the absence of strong expectations, readers adopt a different reading strategy to scrutinize the structure of words more in depth to make sense of what they have read compared to when they encounter a supportive sentence context.

读者只有在没有预期的情况下才会仔细检查词汇熟悉度:来自词汇对事件相关电位影响的证据
读者在阅读限制性句子时,会对即将出现的单词的含义做出预测。这些预测可以归结为对正字法形式的预测。例如,与非邻居相比,无论词汇状态如何,预测单词的正字法邻居产生的N400振幅都会降低(Laszlo&;Federmeier,2009)。我们调查了当读者必须更仔细地检查感知输入以进行单词识别时,他们是否对低约束句子中的词汇性敏感。在Laszlo和Federmeier(2009)的复制和扩展中,我们在高约束句中观察到了与原始研究相似的模式,但在低约束句中发现了词汇效应,而当句子高度约束时,这种效应并不存在。这表明,在没有强烈期望的情况下,与遇到支持性的句子上下文相比,读者会采取不同的阅读策略,更深入地审视单词的结构,以理解他们所读的内容。
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来源期刊
Brain and Language
Brain and Language 医学-神经科学
CiteScore
4.50
自引率
8.00%
发文量
82
审稿时长
20.5 weeks
期刊介绍: An interdisciplinary journal, Brain and Language publishes articles that elucidate the complex relationships among language, brain, and behavior. The journal covers the large variety of modern techniques in cognitive neuroscience, including functional and structural brain imaging, electrophysiology, cellular and molecular neurobiology, genetics, lesion-based approaches, and computational modeling. All articles must relate to human language and be relevant to the understanding of its neurobiological and neurocognitive bases. Published articles in the journal are expected to have significant theoretical novelty and/or practical implications, and use perspectives and methods from psychology, linguistics, and neuroscience along with brain data and brain measures.
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