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一项关于大脑默认模式网络的个体内可靠性的研究。

A study of within-subject reliability of the brain's default-mode network.

机构信息

Department of Neuroscience, University of Sheffield, Royal Hallamshire Hospital, Beech Hill Road, N Floor, Room N133, Sheffield, S10 2RX, UK.

Faculty of Earth and Life Sciences, VU University Amsterdam, Amsterdam, The Netherlands.

出版信息

MAGMA. 2019 Jun;32(3):391-405. doi: 10.1007/s10334-018-00732-0. Epub 2019 Feb 7.

Abstract

OBJECTIVE

Resting-state functional magnetic resonance imaging (fMRI) is promising for Alzheimer's disease (AD). This study aimed to examine short-term reliability of the default-mode network (DMN), one of the main haemodynamic patterns of the brain.

MATERIALS AND METHODS

Using a 1.5 T Philips Achieva scanner, two consecutive resting-state fMRI runs were acquired on 69 healthy adults, 62 patients with mild cognitive impairment (MCI) due to AD, and 28 patients with AD dementia. The anterior and posterior DMN and, as control, the visual-processing network (VPN) were computed using two different methodologies: connectivity of predetermined seeds (theory-driven) and dual regression (data-driven). Divergence and convergence in network strength and topography were calculated with paired t tests, global correlation coefficients, voxel-based correlation maps, and indices of reliability.

RESULTS

No topographical differences were found in any of the networks. High correlations and reliability were found in the posterior DMN of healthy adults and MCI patients. Lower reliability was found in the anterior DMN and in the VPN, and in the posterior DMN of dementia patients.

DISCUSSION

Strength and topography of the posterior DMN appear relatively stable and reliable over a short-term period of acquisition but with some degree of variability across clinical samples.

摘要

目的

静息态功能磁共振成像(fMRI)有望用于阿尔茨海默病(AD)的研究。本研究旨在探讨脑主要血流动力学模式之一的默认模式网络(DMN)的短期可靠性。

材料和方法

使用 1.5T 飞利浦 Achieva 扫描仪,对 69 名健康成年人、62 名 AD 导致的轻度认知障碍(MCI)患者和 28 名 AD 痴呆患者进行了两次连续的静息态 fMRI 扫描。使用两种不同的方法计算了前、后 DMN 以及作为对照的视觉处理网络(VPN):预定种子的连接性(理论驱动)和双回归(数据驱动)。使用配对 t 检验、全局相关系数、体素相关图和可靠性指标来计算网络强度和拓扑结构的离散度和收敛度。

结果

在任何网络中都没有发现拓扑差异。健康成年人和 MCI 患者的后 DMN 具有较高的相关性和可靠性。在前 DMN 和 VPN 以及痴呆患者的后 DMN 中,可靠性较低。

讨论

在后 DMN 的强度和拓扑结构在短期内采集时表现出相对稳定和可靠,但在不同的临床样本中存在一定程度的可变性。

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