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基于分割的语义网络解剖模型。

Parcellation-based anatomic model of the semantic network.

机构信息

Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.

Department of Neurosurgery, Prince of Wales Private Hospital, Sydney, NSW, Australia.

出版信息

Brain Behav. 2021 Apr;11(4):e02065. doi: 10.1002/brb3.2065. Epub 2021 Feb 18.

Abstract

INTRODUCTION

The semantic network is an important mediator of language, enabling both speech production and the comprehension of multimodal stimuli. A major challenge in the field of neurosurgery is preventing semantic deficits. Multiple cortical areas have been linked to semantic processing, though knowledge of network connectivity has lacked anatomic specificity. Using attentional task-based fMRI studies, we built a neuroanatomical model of this network.

METHODS

One hundred and fifty-five task-based fMRI studies related to categorization of visual words and objects, and auditory words and stories were used to generate an activation likelihood estimation (ALE). Cortical parcellations overlapping the ALE were used to construct a preliminary model of the semantic network based on the cortical parcellation scheme previously published under the Human Connectome Project. Deterministic fiber tractography was performed on 25 randomly chosen subjects from the Human Connectome Project, to determine the connectivity of the cortical parcellations comprising the network.

RESULTS

The ALE analysis demonstrated fourteen left hemisphere cortical regions to be a part of the semantic network: 44, 45, 55b, IFJa, 8C, p32pr, SFL, SCEF, 8BM, STSdp, STSvp, TE1p, PHT, and PBelt. These regions showed consistent interconnections between parcellations. Notably, the anterior temporal pole, a region often implicated in semantic function, was absent from our model.

CONCLUSIONS

We describe a preliminary cortical model for the underlying structural connectivity of the semantic network. Future studies will further characterize the neurotractographic details of the semantic network in the context of medical application.

摘要

简介

语义网络是语言的重要中介,使言语产生和多模态刺激的理解成为可能。神经外科领域的一个主要挑战是防止语义缺陷。已有多个皮质区域与语义处理有关,但对网络连接的了解缺乏解剖特异性。我们使用基于注意力的 fMRI 研究构建了该网络的神经解剖模型。

方法

使用与视觉词和物体、听觉词和故事分类相关的 155 项基于任务的 fMRI 研究来生成激活似然估计(ALE)。重叠 ALE 的皮质分割被用于根据先前在人类连接组计划下发表的皮质分割方案构建语义网络的初步模型。对人类连接组计划中的 25 名随机选择的受试者进行确定性纤维束追踪,以确定构成网络的皮质分割的连通性。

结果

ALE 分析表明,左半球的 14 个皮质区域是语义网络的一部分:44、45、55b、IFJa、8C、p32pr、SFL、SCEF、8BM、STSdp、STSvp、TE1p、PHT 和 PBelt。这些区域显示出皮质分割之间的一致连接。值得注意的是,我们的模型中没有包括常与语义功能有关的前颞极区域。

结论

我们描述了语义网络基础结构连接的初步皮质模型。未来的研究将进一步描述语义网络的神经追踪细节,以便在医学应用中使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c10/8035438/8ad775dde1f0/BRB3-11-e02065-g006.jpg

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