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基于功能和解剖连接的人脑扣带回皮层分区。

Functional and anatomical connectivity-based parcellation of human cingulate cortex.

机构信息

Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.

出版信息

Brain Behav. 2018 Aug;8(8):e01070. doi: 10.1002/brb3.1070. Epub 2018 Jul 24.

Abstract

INTRODUCTION

Human cingulate cortex (CC) has been implicated in many functions, which is highly suggestive of the existence of functional subregions.

METHODS

In this study, we used resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) to parcellate the human cingulate cortex (CC) based on resting-state functional connectivity (rsFC) patterns and anatomical connectivity (AC) patterns, to analyze the rsFC patterns and the AC patterns of different subregions, and to recognize whether the parcellation results obtained by the two different methods were consistent.

RESULTS

The CC was divided into six functional subregions, including the anterior cingulate cortex, dorsal anterior midcingulate cortex, ventral anterior midcingulate cortex, posterior midcingulate cortex, dorsal posterior cingulate cortex, and ventral posterior cingulate cortex. The CC was also divided into ten anatomical subregions, termed Subregion 1 (S1) to Subregion 10 (S10). Each subregion showed specific connectivity patterns, although the functional subregions and the anatomical subregions were internally consistent.

CONCLUSIONS

Using different model MRI images, we established a parcellation scheme, which is internally consistent for the human CC, which may provide an in vivo guide for subregion-level studies and improve our understanding of this brain area at subregional levels.

摘要

简介

人类扣带回(CC)被认为参与了许多功能,这强烈提示其存在功能亚区。

方法

在这项研究中,我们使用静息态功能磁共振成像(rs-fMRI)和弥散张量成像(DTI),基于静息态功能连接(rsFC)模式和解剖连接(AC)模式对人类扣带回(CC)进行分区,分析不同子区域的 rsFC 模式和 AC 模式,并识别两种不同方法得到的分区结果是否一致。

结果

CC 被分为六个功能亚区,包括前扣带皮层、背侧前扣带中皮质、腹侧前扣带中皮质、后扣带中皮质、背侧后扣带皮质和腹侧后扣带皮质。CC 还被分为十个解剖亚区,分别命名为 Subregion 1(S1)到 Subregion 10(S10)。每个亚区都表现出特定的连接模式,尽管功能亚区和解剖亚区在内部是一致的。

结论

使用不同的模型 MRI 图像,我们建立了一个内部一致的人类 CC 分区方案,这可能为亚区水平的研究提供活体指导,并提高我们对该脑区亚区水平的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ecf/6085915/46e0c515625a/BRB3-8-e01070-g001.jpg

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