Laboratory of Clinical Biochemistry and Molecular Biology, University of Pisa, Pisa, Italy; Molecular Mind Lab, IMT School for Advanced Studies Lucca, Lucca 55100, Italy.
Laboratory of Clinical Biochemistry and Molecular Biology, University of Pisa, Pisa, Italy; Molecular Mind Lab, IMT School for Advanced Studies Lucca, Lucca 55100, Italy.
Neuropsychologia. 2017 Oct;105:39-49. doi: 10.1016/j.neuropsychologia.2017.05.001. Epub 2017 May 3.
The organization of semantic information in the brain has been mainly explored through category-based models, on the assumption that categories broadly reflect the organization of conceptual knowledge. However, the analysis of concepts as individual entities, rather than as items belonging to distinct superordinate categories, may represent a significant advancement in the comprehension of how conceptual knowledge is encoded in the human brain. Here, we studied the individual representation of thirty concrete nouns from six different categories, across different sensory modalities (i.e., auditory and visual) and groups (i.e., sighted and congenitally blind individuals) in a core hub of the semantic network, the left angular gyrus, and in its neighboring regions within the lateral parietal cortex. Four models based on either perceptual or semantic features at different levels of complexity (i.e., low- or high-level) were used to predict fMRI brain activity using representational similarity encoding analysis. When controlling for the superordinate component, high-level models based on semantic and shape information led to significant encoding accuracies in the intraparietal sulcus only. This region is involved in feature binding and combination of concepts across multiple sensory modalities, suggesting its role in high-level representation of conceptual knowledge. Moreover, when the information regarding superordinate categories is retained, a large extent of parietal cortex is engaged. This result indicates the need to control for the coarse-level categorial organization when performing studies on higher-level processes related to the retrieval of semantic information.
大脑中语义信息的组织主要是通过基于类别(category-based)的模型来探索的,这些模型假设类别广泛反映了概念知识的组织。然而,将概念分析为单个实体,而不是作为属于不同上位类别(superordinate category)的项目,可能代表了在理解人类大脑中概念知识是如何编码的方面的重大进展。在这里,我们在语义网络的核心枢纽——左侧角回(left angular gyrus)及其外侧顶叶皮层(lateral parietal cortex)的邻近区域,研究了来自六个不同类别(即听觉和视觉)和两个群体(即有视力者和先天性盲人)的三十个具体名词的个体表示。我们使用了四种基于不同复杂程度(即低水平或高水平)的感知或语义特征的模型,通过代表性相似性编码分析(representational similarity encoding analysis)来预测 fMRI 大脑活动。在控制上位成分的情况下,基于语义和形状信息的高水平模型仅在顶内沟(intraparietal sulcus)中导致了显著的编码准确性。该区域涉及多个感觉模态的特征绑定和概念组合,表明其在概念知识的高级表示中的作用。此外,当保留关于上位类别的信息时,大量顶叶皮层被激活。这一结果表明,在进行与语义信息检索相关的高级过程研究时,需要控制粗粒度的类别组织。