Sara Baldini, Arianna Sartori, Lucrezia Rossi, Anna Favero, Fulvio Pasquin, Alessandro Dinoto, Alessio Bratina, Antonio Bosco, Paolo Manganotti
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引用次数: 0
Abstract
Fatigue affects approximately 80% of people with Multiple Sclerosis (PwMS) and can impact several domains of daily life. However, the neural underpinnings of fatigue in MS are still not completely clear. The aim of our study was to investigate the spontaneous large-scale networks functioning associated with fatigue in PwMS using the EEG microstate approach with a spectral decomposition. Forty-three relapsing-remitting MS patients and twenty-four healthy controls (HCs) were recruited. All participants underwent an administration of Modified Fatigue Impact scale (MFIS) and a 15-min resting-state high-density EEG recording. We compared the microstates of healthy subjects, fatigued (F-MS) and non-fatigued (nF-MS) patients with MS; correlations with clinical and behavioral fatigue scores were also analyzed. Microstates analysis showed six templates across groups and frequencies. We found that in the F-MS emerged a significant decrease of microstate F, associated to the salience network, in the broadband and in the beta band. Moreover, the microstate B, associated to the visual network, showed a significant increase in fatigued patients than healthy subjects in broadband and beta bands. The multiple linear regression showed that the high cognitive fatigue was predicted by both an increase and decrease, respectively, in delta band microstate B and beta band microstate F. On the other hand, higher physical fatigue was predicted with lower occurrence microstate F in beta band. The current findings suggest that in MS the higher level of fatigue might be related to a maladaptive functioning of the salience and visual network.
约有 80% 的多发性硬化症(PwMS)患者会感到疲劳,并对日常生活的多个领域产生影响。然而,多发性硬化症患者疲劳的神经基础仍不完全清楚。我们研究的目的是利用频谱分解的脑电图微状态方法,研究与多发性硬化症患者疲劳相关的自发大规模网络功能。我们招募了 43 名复发缓解型多发性硬化症患者和 24 名健康对照者(HCs)。所有参与者都接受了改良疲劳影响量表(MFIS)和 15 分钟静息态高密度脑电图记录。我们比较了健康受试者、疲劳(F-MS)和非疲劳(nF-MS)多发性硬化症患者的微观状态,并分析了与临床和行为疲劳评分的相关性。微观状态分析显示,在不同组别和频率中存在六种模板。我们发现,在 F-MS 中,与突出网络相关的微状态 F 在宽带和贝塔波段出现了显著下降。此外,与视觉网络相关的微状态 B 在宽带和贝塔波段显示疲劳患者比健康受试者明显增加。多元线性回归结果表明,认知疲劳程度越高,德尔塔波段微状态 B 和贝塔波段微状态 F 的增加和减少幅度就越大。目前的研究结果表明,多发性硬化症患者较高程度的疲劳可能与突出和视觉网络的不适应功能有关。
期刊介绍:
Brain Topography publishes clinical and basic research on cognitive neuroscience and functional neurophysiology using the full range of imaging techniques including EEG, MEG, fMRI, TMS, diffusion imaging, spectroscopy, intracranial recordings, lesion studies, and related methods. Submissions combining multiple techniques are particularly encouraged, as well as reports of new and innovative methodologies.