Hypersynchronization has been proposed as a synaptic dysfunction biomarker in the Alzheimer's disease continuum, reflecting the alteration of the excitation/inhibition balance. While animal models have verified this idea extensively, there is still no clear evidence in humans. Here we test this hypothesis, evaluating the risk of conversion from mild cognitive impairment (MCI) to Alzheimer's disease in a longitudinal study. We compared the functional resting state eyes-closed magnetoencephalographic networks of 54 patients with MCI who were followed-up every 6 months. According to their clinical outcome, they were split into: (i) the 'progressive' MCI (n = 27) group; and (ii) the 'stable' MCI group (n = 27). They did not differ in gender or educational level. For all participants, two magnetoencephalographic recordings were acquired. Functional connectivity was evaluated using the phase locking value. To extract the functional connectivity network with significant changes between both magnetoencephalographic recordings, we evaluated the functional connectivity ratio, defined as functional connectivity post-/pre-condition, in a network-based statistical model with an ANCOVA test with age as covariate. Two significant networks were found in the theta and beta bands, involving fronto-temporal and fronto-occipital connections, and showing a diminished functional connectivity ratio in the progressive MCI group. These topologies were then evaluated at each condition showing that at baseline, patients with progressive MCI showed higher synchronization than patients with stable MCI, while in the post-condition this pattern was reversed. These results may be influenced by two main factors in the post-condition: the increased synchrony in the stable MCI patients and the network failure in the progressive MCI patients. These findings may be explained as an 'X' form model where the hypersynchrony predicts conversion, leading subsequently to a network breakdown in progressive MCI. Patients with stable MCI showed an opposite phenomenon, which could indicate that they were a step beyond in the Alzheimer's disease continuum. This model would be able to predict the risk for the conversion to dementia in MCI patients.

中文翻译：

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轻度认知障碍中的超同步：“ X”模型。

已经提出超同步化是阿尔茨海默氏病连续体中的突触功能障碍生物标志物，反映了兴奋/抑制平衡的改变。尽管动物模型已广泛验证了这一想法，但人类仍没有明确的证据。在这里，我们通过纵向研究来验证这一假设，评估从轻度认知障碍（MCI）转化为阿尔茨海默氏病的风险。我们比较了每6个月随访的54例MCI患者的功能性休息状态闭眼式磁脑图网络。根据他们的临床结果，将他们分为：（i）“进行性” MCI（n = 27）组；（ii）“稳定的” MCI组（n = 27）。他们的性别或受教育程度没有差异。对于所有参与者，获得了两次脑磁图记录。使用锁相值评估功能连接性。为了提取两个脑磁图记录之间有显着变化的功能连接网络，我们在具有年龄作为协变量的ANCOVA测试的基于网络的统计模型中评估了功能连接率，定义为功能连接后/前提。在θ和β带中发现了两个重要的网络，涉及额颞叶和额枕连接，并且在进行性MCI组中显示出功能连接率降低。然后，在每种情况下对这些拓扑进行评估，结果表明，在基线时，进行性MCI的患者比稳定MCI的患者显示出更高的同步性 而在后置条件下，这种模式被颠倒了。这些结果可能受到两个主要因素的影响：稳定MCI患者的同步性增加和进行性MCI患者的网络衰竭。这些发现可以解释为“ X”形式的模型，其中超同步会预测转换，从而导致渐进式MCI中的网络崩溃。MCI稳定的患者表现出相反的现象，这可能表明他们已经超越了阿尔茨海默氏病的病程。该模型将能够预测MCI患者转化为痴呆症的风险。这些发现可以解释为“ X”形式的模型，其中超同步会预测转换，从而导致渐进式MCI中的网络崩溃。MCI稳定的患者表现出相反的现象，这可能表明他们已经超越了阿尔茨海默氏病的病程。该模型将能够预测MCI患者转化为痴呆症的风险。这些发现可以解释为“ X”形式的模型，其中超同步会预测转换，随后导致渐进式MCI中的网络崩溃。MCI稳定的患者表现出相反的现象，这可能表明他们已经超越了阿尔茨海默氏病的病程。该模型将能够预测MCI患者转化为痴呆症的风险。