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脑白质疏松症患者因认知负荷不同导致突显网络、中央执行网络和默认模式网络的异常交互。

Abnormal Interactions of the Salience Network, Central Executive Network, and Default-Mode Network in Patients With Different Cognitive Impairment Loads Caused by Leukoaraiosis.

机构信息

Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

Department of Rehabilitation Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

出版信息

Front Neural Circuits. 2019 Jun 18;13:42. doi: 10.3389/fncir.2019.00042. eCollection 2019.

Abstract

Leukoaraiosis (LA) is associated with cognitive impairment in the older people which can be demonstrated in functional connectivity (FC) based on resting-state functional magnetic resonance imaging (rs-fMRI). This study is to explore the FC changes in LA patients with different cognitive status by three network models. Fifty-three patients with LA were divided into three groups: the normal cognition (LA-NC; = 14, six males), mild cognitive impairment (LA-MCI; = 27, 13 males), and vascular dementia (LA-VD; = 12, six males), according to the Mini Mental State Exam (MMSE) and Clinical Dementia Rating (CDR). The three groups and 30 matched healthy controls (HCs; 11 males) underwent rs-fMRI. The data of rs-fMRI were analyzed by independent components analysis (ICA) and region of interest (ROI) analysis by the REST toolbox. Then the FC was respectively analyzed by the default-mode network (DMN), salience networks (SNs) and the central executive network (CEN) with their results compared among the different groups. For inter-brain network analysis, there were negative FC between the SN and DMN in LA groups, and the FC decreased when compared with HC group. While there were enhanced inter-brain network FC between the SN and CEN as well as within the SN. The FC in patients with LA can be detected by different network models of rs-fMRI. The multi-model analysis is helpful for the further understanding of the cognitive changes in those patients.

摘要

脑白质疏松症(LA)与老年人的认知功能障碍有关,在基于静息态功能磁共振成像(rs-fMRI)的功能连接(FC)中可以得到证明。本研究旨在通过三种网络模型探索不同认知状态下 LA 患者的 FC 变化。将 53 名 LA 患者根据简易精神状态检查(MMSE)和临床痴呆评定量表(CDR)分为三组:正常认知(LA-NC; = 14,6 名男性)、轻度认知障碍(LA-MCI; = 27,13 名男性)和血管性痴呆(LA-VD; = 12,6 名男性)。三组和 30 名匹配的健康对照组(HCs;11 名男性)接受 rs-fMRI。rs-fMRI 数据采用独立成分分析(ICA)和 REST 工具包的感兴趣区(ROI)分析进行分析。然后,采用默认模式网络(DMN)、突显网络(SNs)和中央执行网络(CEN)分别对 FC 进行分析,并比较不同组之间的结果。对于脑间网络分析,LA 组的 SN 与 DMN 之间存在负 FC,与 HC 组相比,FC 降低。而 SN 与 CEN 之间以及 SN 内部的脑间网络 FC 增强。rs-fMRI 不同网络模型可检测 LA 患者的 FC。多模型分析有助于进一步了解这些患者的认知变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f895/6592158/3532468a76c1/fncir-13-00042-g0001.jpg

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