Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
Department of Neuropsychology and Rehabilitation Psychology, Radboud University Medical Center, Nijmegen, the Netherlands; Center for Cognition, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Kapittelweg 29, 6525 EN Nijmegen, the Netherlands; Vincent van Gogh Institute for Psychiatry, Venray, the Netherlands.
Clin Neurophysiol. 2020 Aug;131(8):1886-1895. doi: 10.1016/j.clinph.2020.05.014. Epub 2020 May 29.
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.
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.
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.
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.
EEG network analysis has potential to help understand brain related DM1 phenotypes.
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.
在常染色体显性、多系统、慢性进行性疾病 1 型肌强直性营养不良（DM1）中，认知缺陷可能源于功能脑网络的破坏。我们旨在使用 DM1 患者和匹配的未受影响对照者的静息状态脑电图（EEG）记录的网络分析，来研究大脑功能网络中网络组织的变化，并探讨其与认知缺陷的相关性。
在这项横断面研究中，28 名经基因证实的 DM1 成年患者和 26 名年龄、性别和教育程度匹配的未受影响的对照者接受了静息状态 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 频率依赖性功能连接。应用图论的概念来描述功能脑网络，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与神经心理学测试之间的相关性，这些测试在组间存在统计学差异。
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 频段更高（0.141[0.050]比 0.125[0.018]，p=0.029），而在较高的 alpha 频段较低（0.154[0.048]比 0.182[0.073]，p=0.038）。DM1 患者的功能 MST 构建网络在 delta（p=0.009）、theta（p=0.009）、较低的 alpha（p=0.036）和较高的 alpha（p=0.008）频段与健康对照组有明显差异。在评估局部 MST 网络指标时，观察到趋势是在 theta 频段具有更高的全局整合，而在较高的 alpha 频段具有较低的全局整合。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 alpha 频段的全局中位数 PLI 相关；Stroop 干扰测试与该频段的介数中心性相关。
这项研究支持这样一种假设，即 DM1 中的大脑变化导致功能网络组织的破坏，这可以通过基于 EEG 的网络进行建模。进一步的研究可能有助于揭示与 DM1 相关的临床大脑症状的关系。
EEG 网络分析有可能帮助我们理解与 DM1 相关的大脑表型。
这项工作得到了欧洲社区第七框架计划（FP7/2007-2013）的支持，该计划通过协议 n°305697（OPTIMISTIC）和 Marigold 基金会拨款。
