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睡眠剥夺期间情绪恶化的易感性受三重网络模型的白质致密性影响。

Vulnerability to mood degradation during sleep deprivation is influenced by white-matter compactness of the triple-network model.

机构信息

Social, Cognitive and Affective Neuroscience Laboratory, Department of Psychiatry, College of Medicine, University of Arizona, Tucson, AZ, USA.

Social, Cognitive and Affective Neuroscience Laboratory, Department of Psychiatry, College of Medicine, University of Arizona, Tucson, AZ, USA.

出版信息

Neuroimage. 2019 Nov 15;202:116123. doi: 10.1016/j.neuroimage.2019.116123. Epub 2019 Aug 25.

Abstract

Sleep deprivation (SD) is often associated with significant shifts in mood state relative to baseline functioning. Prior work suggests that there are consistent trait-like differences among individuals in the degree to which their mood and performances are affected by sleep loss. The goal of this study was to determine the extent to which trait-like individual differences in vulnerability/resistance to mood degradation during a night of SD are dependent upon region-specific white and grey matter (WM/GM) characteristics of a triple-network model, including the default-mode network (DMN), control-execution network (CEN) and salience network (SN). Diffusion-weighted and anatomical brain data were collected from 45 healthy individuals several days prior to a 28-h overnight SD protocol. During SD, a visual analog mood scale was administered every hour from 19:15 (time point1; TP1) to 11:15 (TP17) the following morning to measure two positive and six negative mood states. Four core regions within the DMN, five within the CEN, and seven within the SN were used as regions of interest (ROIs). An index of mood resistance (IMR) was defined as the averaged differences between positive and negative mood states over 12 TPs (TP5 to TP16) relative to baseline (TP1 to TP4). For each ROI, characteristics of WM - quantitative anisotropy (QA) and mean curvature index (WM-MCI), and GM - cortical volume (CV) and GM-MCI were estimated, and used to predict IMR. WM characteristics, particularly QA, of all of regions within the DMN, and most of the regions within the CEN and SN predicted IMR during SD. In contrast, most ROIs did not show significant association between IMR and any of the GM characteristics (CV and MCI) or WM MCI. Our findings suggest that greater resilience to mood degradation induced by total SD appears to be associated with more compact axonal pathways within the DMN, CEN and SN.

摘要

睡眠剥夺(SD)常与情绪状态相对于基线功能的显著变化有关。先前的研究表明,个体在睡眠剥夺时情绪和表现受到影响的程度存在一致的特质差异。本研究的目的是确定在一夜 SD 期间,对情绪恶化的易感性/抵抗力的个体差异在多大程度上取决于三重网络模型的区域特异性白质和灰质(WM/GM)特征,包括默认模式网络(DMN)、控制执行网络(CEN)和突显网络(SN)。在 28 小时的 overnight SD 方案之前的几天,从 45 名健康个体中收集了扩散加权和解剖学脑数据。在 SD 期间,从 19:15(时间点 1;TP1)到第二天早上 11:15(TP17),每小时通过视觉模拟情绪量表来测量两种积极情绪和六种消极情绪,以评估情绪状态。DMN 中的四个核心区域、CEN 中的五个区域和 SN 中的七个区域被用作感兴趣区域(ROI)。情绪抵抗指数(IMR)定义为相对于基线(TP1 到 TP4),在 12 个 TP(TP5 到 TP16)上正性和负性情绪状态之间的平均差异。对于每个 ROI,WM - 各向异性分数(QA)和平均曲率指数(WM-MCI)、GM - 皮质体积(CV)和 GM-MCI 的特征进行了估计,并用于预测 IMR。DMN 中所有区域的 WM 特征,特别是 QA,以及 CEN 和 SN 中的大多数区域的 WM 特征,都可以预测 SD 期间的 IMR。相比之下,大多数 ROI 没有显示 IMR 与 GM 特征(CV 和 MCI)或 WM MCI 之间的显著关联。我们的研究结果表明,对总 SD 引起的情绪恶化的更强抵抗力似乎与 DMN、CEN 和 SN 中的更紧凑的轴突通路有关。

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