École Doctorale Cerveau-Cognition-Comportement, Université Pierre et Marie Curie - Paris 6, 75005 Paris, France; Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale, U992, F-91191 Gif/Yvette, France; Center for Mind/Brain Sciences, University of Trento, 38068 Rovereto, Italy.
Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale, U992, F-91191 Gif/Yvette, France; Center for Mind/Brain Sciences, University of Trento, 38068 Rovereto, Italy.
Neuropsychologia. 2017 Oct;105:4-17. doi: 10.1016/j.neuropsychologia.2017.06.026. Epub 2017 Jun 23.
We live our lives surrounded by symbols (e.g., road signs, logos, but especially words and numbers), and throughout our life we use them to evoke, communicate and reflect upon ideas and things that are not currently present to our senses. Symbols are represented in our brains at different levels of complexity: at the first and most simple level, as physical entities, in the corresponding primary and secondary sensory cortices. The crucial property of symbols, however, is that, despite the simplicity of their surface forms, they have the power of evoking higher order multifaceted representations that are implemented in distributed neural networks spanning a large portion of the cortex. The rich internal states that reflect our knowledge of the meaning of symbols are what we call semantic representations. In this review paper, we summarize our current knowledge of both the cognitive and neural substrates of semantic representations, focusing on concrete words (i.e., nouns or verbs referring to concrete objects and actions), which, together with numbers, are the most-studied and well defined classes of symbols. Following a systematic descriptive approach, we will organize this literature review around two key questions: what is the content of semantic representations? And, how are semantic representations implemented in the brain, in terms of localization and dynamics? While highlighting the main current opposing perspectives on these topics, we propose that a fruitful way to make substantial progress in this domain would be to adopt a geometrical view of semantic representations as points in high dimensional space, and to operationally partition the space of concrete word meaning into motor-perceptual and conceptual dimensions. By giving concrete examples of the kinds of research that can be done within this perspective, we illustrate how we believe this framework will foster theoretical speculations as well as empirical research.
我们的生活被符号所包围（例如路标、商标，但尤其是文字和数字），在我们的一生中，我们用它们来唤起、交流和反思那些当前不在我们感官范围内的想法和事物。符号在我们的大脑中以不同的复杂程度呈现：在第一级和最基本的水平上，作为物理实体，存在于相应的初级和次级感觉皮层中。然而，符号的关键特性是，尽管它们的表面形式简单，但它们具有唤起更高阶、多面向的表示的能力，这些表示是在分布于大脑很大一部分的神经网络中实现的。反映我们对符号含义的知识的丰富内部状态就是我们所说的语义表示。在这篇综述文章中，我们总结了当前关于语义表示的认知和神经基础的知识，重点是具体的词（即指具体物体和动作的名词或动词），这些词与数字一起，是研究最多、定义最明确的符号类别。我们将采用系统的描述性方法，围绕两个关键问题组织这篇文献综述：语义表示的内容是什么？以及，从定位和动态的角度来看，语义表示是如何在大脑中实现的？在强调这些主题的主要当前对立观点的同时，我们提出，采用语义表示作为高维空间中的点的几何观点，并将具体单词的意义空间操作地划分为运动感知和概念维度，是在这一领域取得实质性进展的一种富有成效的方法。通过给出在这种观点下可以进行的研究类型的具体示例，我们说明了我们如何相信这个框架将促进理论推测以及实证研究。
