OBJECTIVE In the autosomal dominant, multisystem, chronic progressive disease myotonic dystrophy type 1 (DM1), cognitive deficits may originate from disrupted functional brain networks. We aimed to use network analysis of resting-state electro-encephalography (EEG) recordings of patients with DM1 and matched unaffected controls to investigate changes in network organization in large-scale functional brain networks and correlations with cognitive deficits. METHODS In this cross-sectional study, 28 adult patients with genetically confirmed DM1 and 26 age-, sex- and education-matched unaffected controls underwent resting-state EEG and neuropsychological assessment. We calculated the Phase Lag Index (PLI) to determine EEG frequency-dependent functional connectivity between brain regions. Functional brain networks were characterized by applying concepts from graph theory and compared between-groups. Network topology was evaluated using the minimum spanning tree (MST). We evaluated correlations between network metrics and neuropsychological tests that showed statistically significant between-group differences. RESULTS Functional connectivity estimated as whole-brain median PLI for DM1 patients versus healthy controls was higher in theta band (0.141 [0.050] versus 0.125 [0.018], p = 0.029), and lower in the upper alpha band (0.154 [0.048] versus 0.182 [0.073], p = 0.038), respectively. Functional MST-constructed networks in DM1 patients were significantly dissimilar from healthy controls in the delta, (p = 0.009); theta, (p = 0.009); lower alpha, (p = 0.036); and upper alpha, (p = 0.008) bands. In evaluation of local MST network measures, trends toward networks with higher global integration in the theta band and lower global integration in the upper alpha band were observed. Compared to unaffected controls, DM1 patients performed worse on tests of attention, motor function, executive function and visuospatial memory. Visuospatial memory correlated with the global median PLI in the upper alpha band; the Stroop interference test correlated with betweenness centrality in this band. CONCLUSION This study supports the hypothesis that brain changes in DM1 give rise to disrupted functional network organization, as modelled with EEG-based networks. Further study may help unravel the relations with clinical brain-related DM1 symptoms. SIGNIFICANCE EEG network analysis has potential to help understand brain related DM1 phenotypes. FUNDING This work was supported by the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 305697 (OPTIMISTIC) and the Marigold Foundation.

中文翻译：

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肌强直性营养不良1型基于脑电图的功能性脑网络的表征

目的 在常染色体显性遗传、多系统、慢性进行性疾病肌强直性营养不良 1 型 (DM1) 中，认知缺陷可能源于功能性脑网络中断。我们旨在使用 DM1 患者和匹配的未受影响对照的静息状态脑电图 (EEG) 记录的网络分析来研究大规模功能性大脑网络中网络组织的变化以及与认知缺陷的相关性。方法 在这项横断面研究中，28 名经基因证实为 DM1 的成年患者和 26 名年龄、性别和教育匹配的未受影响对照接受静息态 EEG 和神经心理学评估。我们计算了相位滞后指数 (PLI)，以确定大脑区域之间的 EEG 频率相关功能连接。功能性大脑网络的特点是应用图论中的概念并在组间进行比较。使用最小生成树 (MST) 评估网络拓扑。我们评估了网络指标和神经心理学测试之间的相关性，这些测试显示出统计学上显着的组间差异。结果 DM1 患者与健康对照组的全脑中位数 PLI 估计的功能连接在 theta 波段较高（0.141 [0.050] 与 0.125 [0.018]，p = 0.029），而在上α 波段（0.154 [0.048] 与0.182 [0.073]，p = 0.038)，分别。DM1 患者中功能性 MST 构建的网络与三角洲中的健康对照显着不同（p = 0.009）；θ，（p = 0.009）；下阿尔法，（p = 0.036）；和上阿尔法 (p = 0.008) 波段。在评估本地 MST 网络措施时，观察到了在 theta 波段具有更高全局集成度和在上 alpha 波段具有更低全局集成度的网络趋势。与未受影响的对照组相比，DM1 患者在注意力、运动功能、执行功能和视觉空间记忆测试中表现更差。视觉空间记忆与上阿尔法波段的全球中位数 PLI 相关；Stroop 干扰测试与该频段的介数中心性相关。结论 本研究支持以下假设，即 DM1 中的大脑变化会导致功能网络组织中断，这与基于 EEG 的网络建模相同。进一步的研究可能有助于阐明与临床脑相关 DM1 症状的关系。意义 EEG 网络分析有可能帮助了解与大脑相关的 DM1 表型。