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Love thy neighbor: Facilitation and inhibition in the competition between parallel predictions
Cognition ( IF 2.8 ) Pub Date : 2020-11-16 , DOI: 10.1016/j.cognition.2020.104509
Tal Ness 1 , Aya Meltzer-Asscher 2
Affiliation  

Ample evidence suggests that during word recognition and production, simultaneously activated lexical and sublexical representations interact, demonstrating varied patterns of facilitation and inhibition in various tasks and measures. A separate line of research has led to a growing consensus that prediction during sentence processing involves activating multiple possible predictions. However, very little is known about the nature of the interactions between parallel predictions. The current study employed a speeded cloze task to probe competition between simultaneously activated predictions. We focused on the modal response (the most probable completion for a sentence) and its strongest competitor (the second most probable completion). Examining production latencies of the modal response, the results showed an interaction between competitor strength and the semantic relatedness between the competitor and the modal: when the two were related, the stronger the competitor was, the more it facilitated production; however, when the two were unrelated, the stronger the competitor was, the more inhibition it caused. These results contrast with the pattern observed for the influences of near and distant semantic neighbors on word recognition and production. However, we show that when the different nature of the tasks is taken into consideration, these patterns of interaction between parallel predictions can be accounted for by the interactive activation and competition (IAC) model used to account for previous neighborhood effects (Chen & Mirman, 2012).



中文翻译:

爱你的邻居:在平行预测之间的竞争中的促进和抑制

大量证据表明,在单词识别和生成过程中,同时激活的词汇和次词汇表示形式会相互作用,这表明在各种任务和措施中促进和抑制的变化形式。一项单独的研究导致越来越多的共识,即句子处理过程中的预测涉及激活多个可能的预测。但是,关于并行预测之间相互作用的性质了解甚少。当前的研究采用了加速的结束任务来探测同时激活的预测之间的竞争。我们关注模式响应(一个句子中最可能的完成)及其最强的竞争对手(第二个最可能的完成)。检查模态响应的生产延迟,结果表明,竞争者的力量与竞争者与情态之间的语义相关性之间存在相互作用:当两者相互关联时,竞争者越强大,就越有利于生产。但是,当两者不相关时,竞争者越强大,所造成的抑制就越大。这些结果与观察到的模式对近距离和远距离语义邻居对单词识别和产生的影响形成对比。但是,我们表明,当考虑到任务的不同性质时,可以通过用于解释先前邻域效应的互动激活和竞争(IAC)模型来解释并行预测之间的这些交互方式(Chen和Mirman, 2012)。当两者相关时,竞争者越强大,就越有利于生产。但是,当两者不相关时,竞争者越强大,所造成的抑制就越大。这些结果与观察到的模式对近距离和远距离语义邻居对单词识别和产生的影响形成对比。但是,我们表明,当考虑到任务的不同性质时,可以通过用于解释先前邻域效应的互动激活和竞争(IAC)模型来解释并行预测之间的这些交互方式(Chen和Mirman, 2012)。当两者相关时,竞争者越强大,就越有利于生产。但是,当两者不相关时,竞争者越强大,所造成的抑制就越大。这些结果与观察到的模式对近距离和远距离语义邻居对单词识别和产生的影响形成对比。但是,我们表明,当考虑到任务的不同性质时,可以通过用于解释先前邻域效应的互动激活和竞争(IAC)模型来解释并行预测之间的这些交互方式(Chen和Mirman, 2012)。这些结果与观察到的模式对近距离和远距离语义邻居对单词识别和产生的影响形成对比。但是,我们表明,当考虑到任务的不同性质时,可以通过用于解释先前邻域效应的互动激活和竞争(IAC)模型来解释并行预测之间的这些交互方式(Chen和Mirman, 2012)。这些结果与观察到的模式对近距离和远距离语义邻居对单词识别和产生的影响形成对比。但是,我们表明,当考虑到任务的不同性质时,可以通过用于解释先前邻域效应的互动激活和竞争(IAC)模型来解释并行预测之间的这些交互方式(Chen和Mirman, 2012)。

更新日期:2020-11-17
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