Center for Mind/Brain Sciences, University of Trento, Trento, 38068, Italy.
Department of Psychology, Boston College, Boston, 02467, USA.
Sci Rep. 2020 Jun 2;10(1):8931. doi: 10.1038/s41598-020-65906-0.
How semantic representations are manifest over the brain remains a topic of active debate. A semantic representation may be determined by specific semantic features (e.g. sensorimotor information), or may abstract away from specific features and represent generalized semantic characteristics (general semantic representation). Here we tested whether nodes of the semantic system code for a general semantic representation and/or possess representational spaces linked to particular semantic features. In an fMRI study, eighteen participants performed a typicality judgment task with written words drawn from sixteen different categories. Multivariate pattern analysis (MVPA) and representational similarity analysis (RSA) were adopted to investigate the sensitivity of the brain regions to semantic content and the type of semantic representation coded (general or feature-based). We replicated previous findings of sensitivity to general semantic similarity in posterior middle/inferior temporal gyrus (pMTG/ITG) and precuneus (PC) and additionally observed general semantic representations in ventromedial prefrontal cortex (PFC). Finally, two brain regions of the semantic network were sensitive to semantic features: the left pMTG/ITG was sensitive to haptic perception and the left ventral temporal cortex (VTC) to size. This finding supports the involvement of both general semantic representation and feature-based representations in the brain's semantic system.
语义表示如何在大脑中表现出来仍然是一个活跃的辩论话题。语义表示可能取决于特定的语义特征（例如感觉运动信息），也可能抽象出特定的特征并表示广义的语义特征（一般语义表示）。在这里，我们测试了语义系统的节点是否编码了一般语义表示，以及是否具有与特定语义特征相关的表示空间。在一项 fMRI 研究中，18 名参与者使用 16 个不同类别中的书面单词进行典型性判断任务。多变量模式分析 (MVPA) 和表示相似性分析 (RSA) 用于研究大脑区域对语义内容的敏感性以及编码的语义表示类型（一般或基于特征）。我们复制了先前在后中部/下颞叶回（pMTG/ITG）和顶下小叶（PC）中对一般语义相似性敏感的发现，并在腹内侧前额叶皮层（PFC）中观察到一般语义表示。最后，语义网络中的两个大脑区域对语义特征敏感：左侧 pMTG/ITG 对触觉感知敏感，左侧腹侧颞叶皮层（VTC）对大小敏感。这一发现支持了大脑语义系统中一般语义表示和基于特征的表示的参与。
