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Modeling affirmative and negated action processing in the brain with lexical and compositional semantic models

机译:用词汇和成分语义模型对大脑中肯定和否定的动作处理进行建模

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Recent work shows that distributional semantic models can be used to decode patterns of brain activity associated with individual words and sentence meanings. However, it is yet unclear to what extent such models can be used to study and decode fMRI patterns associated with specific aspects of semantic composition such as the negation function. In this paper, we apply lexical and compositional semantic models to decode fMRI patterns associated with negated and affirmative sentences containing hand-action verbs. Our results show reduced decoding (correlation) of sentences where the verb is in the negated context, as compared to the affirmative one, within brain regions implicated in action-semantic processing. This supports behavioral and brain imaging studies, suggesting that negation involves reduced access to aspects of the affirmative mental representation. The results pave the way for testing alternate semantic models of negation against human semantic processing in the brain.
机译:最近的工作表明,分布语义模型可用于解码与单个单词和句子含义相关的大脑活动模式。然而,目前尚不清楚这种模型在多大程度上可用于研究和解码与诸如否定功能之类的语义成分的特定方面相关联的fMRI模式。在本文中,我们应用词法和成分语义模型来解码与包含手部动词的否定和肯定句相关的fMRI模式。我们的研究结果表明,与肯定动词相比,动词处于否定语境的句子在与动作语义处理有关的大脑区域内的解码(相关性)降低。这支持了行为和大脑影像学研究,表明否定会减少人们对肯定性精神表征各个方面的访问。结果为测试针对大脑的人类语义处理的否定替代语义模型铺平了道路。

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