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白质在枢纽-辐辏语义表象中的基础作用:来自语义性痴呆的证据。

White matter basis for the hub-and-spoke semantic representation: evidence from semantic dementia.

机构信息

State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.

College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China.

出版信息

Brain. 2020 Apr 1;143(4):1206-1219. doi: 10.1093/brain/awaa057.

Abstract

The hub-and-spoke semantic representation theory posits that semantic knowledge is processed in a neural network, which contains an amodal hub, the sensorimotor modality-specific regions, and the connections between them. The exact neural basis of the hub, regions and connectivity remains unclear. Semantic dementia could be an ideal lesion model to construct the semantic network as this disease presents both amodal and modality-specific semantic processing (e.g. colour) deficits. The goal of the present study was to identify, using an unbiased data-driven approach, the semantic hub and its general and modality-specific semantic white matter connections by investigating the relationship between the lesion degree of the network and the severity of semantic deficits in 33 patients with semantic dementia. Data of diffusion-weighted imaging and behavioural performance in processing knowledge of general semantic and six sensorimotor modalities (i.e. object form, colour, motion, sound, manipulation and function) were collected from each subject. Specifically, to identify the semantic hub, we mapped the white matter nodal degree value (a graph theoretical index) of the 90 regions in the automated anatomical labelling atlas with the general semantic abilities of the patients. Of the regions, only the left fusiform gyrus was identified as the hub because its structural connectivity strength (i.e. nodal degree value) could significantly predict the general semantic processing of the patients. To identify the general and modality-specific semantic connections of the semantic hub, we separately correlated the white matter integrity values of each tract connected with the left fusiform gyrus, with the performance for general semantic processing and each of six semantic modality processing. The results showed that the hub region worked in concert with nine other regions in the semantic memory network for general semantic processing. Moreover, the connection between the hub and the left calcarine was associated with colour-specific semantic processing. The observed effects could not be accounted for by potential confounding variables (e.g. total grey matter volume, regional grey matter volume and performance on non-semantic control tasks). Our findings refine the neuroanatomical structure of the semantic network and underline the critical role of the left fusiform gyrus and its connectivity in the network.

摘要

枢纽-辐条语义表示理论认为,语义知识在神经网络中进行处理,该网络包含一个无模态枢纽、感觉运动模态特异性区域以及它们之间的连接。枢纽、区域和连接的确切神经基础仍不清楚。语义痴呆症可能是构建语义网络的理想病变模型,因为这种疾病既有非模态的,也有模态特异性的语义处理(例如颜色)缺陷。本研究的目的是通过研究 33 名语义痴呆症患者的网络病变程度与语义缺陷严重程度之间的关系,使用无偏的基于数据驱动的方法来确定语义枢纽及其一般和模态特异性语义白质连接。从每个受试者中收集了扩散加权成像和处理一般语义和六个感觉运动模态(即物体形状、颜色、运动、声音、操作和功能)知识的行为表现的数据。具体来说,为了确定语义枢纽,我们将自动解剖学实验室图谱中 90 个区域的白质节段度值(图论指标)与患者的一般语义能力进行了映射。在这些区域中,只有左侧梭状回被确定为枢纽,因为其结构连接强度(即节点度值)可以显著预测患者的一般语义处理能力。为了确定语义枢纽的一般和模态特异性语义连接,我们分别将与左侧梭状回相连的每个束的白质完整性值与一般语义处理以及六个语义模态处理的表现进行了相关分析。结果表明,枢纽区域与语义记忆网络中的其他九个区域协同工作,用于一般语义处理。此外,枢纽与左侧距状回之间的连接与颜色特异性语义处理有关。观察到的效应不能用潜在的混杂变量(例如总灰质体积、区域灰质体积和非语义控制任务的表现)来解释。我们的发现细化了语义网络的神经解剖结构,并强调了左侧梭状回及其连接在网络中的关键作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe2f/7191302/4725bcbe2b95/awaa057f1.jpg

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