名词
动词
单变量
心理学
语言学
功能磁共振成像
代表(政治)
认知
认知心理学
计算机科学
人工智能
多元统计
哲学
神经科学
政治
政治学
法学
机器学习
作者
Wenjia Zhang,Xuemei Chen,Suiping Wang
标识
DOI:10.1093/cercor/bhae242
摘要
Nouns and verbs are fundamental grammatical building blocks of languages. A key question is whether and where the noun-verb division was represented in the brain. Previous studies mainly used univariate analyses to examine this issue. However, the interpretation of activated brain regions in univariate analyses may be confounded with general cognitive processing and/or confounding variables. We addressed these limitations by using partial representation similarity analysis (RSA) of Chinese nouns and verbs with different levels of imageability. Participants were asked to complete the 1-back grammatical class probe (GCP; an explicit measure) and the 1-back word probe (WP; an implicit measure) tasks while undergoing functional magnetic resonance imaging. RSA results showed that the activation pattern in the left posterior middle temporal gyrus (LpMTG) was significantly correlated with the grammatical class representational dissimilarity matrix in the GCP task after eliminating the potential confounding variables. Moreover, the LpMTG did not overlap with the frontal-parietal regions that were activated by verbs vs. nouns or the task effect (CRP vs. WP) in univariate analyses. These results highlight the role of LpMTG in distinguishing nouns from verbs rather than general cognitive processing.
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