Department of Medicine, Surgery and Health Sciences, Neurology Unit, Cattinara University Hospital ASUGI, University of Trieste, Trieste, Italy.
Neurology Unit, Hospital of Gorizia, ASUGI, Gorizia, Italy.
Brain Topogr. 2024 Nov;37(6):1203-1216. doi: 10.1007/s10548-024-01053-3. Epub 2024 Jun 7.
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.
疲劳影响大约 80%的多发性硬化症患者(PwMS),并可能影响日常生活的多个领域。然而,多发性硬化症疲劳的神经基础仍不完全清楚。我们的研究目的是使用 EEG 微状态方法和频谱分解来研究与 PwMS 疲劳相关的自发大规模网络功能。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)。所有参与者均接受了改良疲劳影响量表(MFIS)和 15 分钟静息状态高密度 EEG 记录的评估。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状态;还分析了与临床和行为疲劳评分的相关性。微状态分析显示了六个跨组频率模板。我们发现,在 F-MS 中,与突显网络相关的宽带和β频段的微状态 F 显著减少。此外,与视觉网络相关的微状态 B 在宽带和β频段中,疲劳患者的出现明显高于健康受试者。多元线性回归显示,高认知疲劳与δ波段微状态 B 和β波段微状态 F 的增加和减少分别相关。另一方面,较高的身体疲劳与β波段微状态 F 的发生频率较低相关。目前的研究结果表明,在多发性硬化症中,更高水平的疲劳可能与突显网络和视觉网络的适应不良功能有关。