Basque Center on Cognition, Brain and Language, San Sebastian, Spain.
Basque Center on Cognition, Brain and Language, San Sebastian, Spain; Ikerbasque, Basque Foundation for Science, Bilbao, Spain; University of the Basque Country, Bilbao, Spain.
Neuropsychologia. 2021 Mar 12;153:107740. doi: 10.1016/j.neuropsychologia.2020.107740. Epub 2020 Dec 31.
The neurocognitive mechanisms that support the generalization of semantic representations across different languages remain to be determined. Current psycholinguistic models propose that semantic representations are likely to overlap across languages, although there is evidence also to the contrary. Neuroimaging studies observed that brain activity patterns associated with the meaning of words may be similar across languages. However, the factors that mediate cross-language generalization of semantic representations are not known. We here identify a key factor: the depth of processing. Human participants were asked to process visual words as they underwent functional MRI. We found that, during shallow processing, multivariate pattern classifiers could decode the word semantic category within each language in putative substrates of the semantic network, but there was no evidence of cross-language generalization in the shallow processing context. By contrast, when the depth of processing was higher, significant cross-language generalization was observed in several regions, including inferior parietal, ventromedial, lateral temporal, and inferior frontal cortex. These results are in keeping with distributed-only views of semantic processing and favour models based on multiple semantic hubs. The results also have ramifications for existing psycholinguistic models of word processing such as the BIA+, which by default assumes non-selective access to both native and second languages.
支持语义表示在不同语言之间泛化的神经认知机制仍有待确定。目前的心理语言学模型提出，语义表示可能在不同语言之间存在重叠，尽管也有相反的证据。神经影像学研究观察到，与单词意义相关的大脑活动模式可能在不同语言中相似。然而，介导语义表示跨语言泛化的因素尚不清楚。我们在这里确定了一个关键因素：加工深度。人类参与者在接受功能磁共振成像时被要求处理视觉单词。我们发现，在浅层处理过程中，多元模式分类器可以在语义网络的假定底物中对每个语言中的单词语义类别进行解码，但在浅层处理环境中没有跨语言泛化的证据。相比之下，当处理深度增加时，在几个区域观察到了显著的跨语言泛化，包括下顶叶、腹内侧、外侧颞叶和下额叶皮层。这些结果与语义处理的分布式观点一致，并支持基于多个语义枢纽的模型。这些结果对于现有的心理语言学单词处理模型（如 BIA+）也有影响，该模型默认假设对母语和第二语言都有非选择性的访问。
