Disruption of Functional Brain Networks in Alzheimer's Disease: What Can We Learn from Graph Spectral Analysis of Resting-State Magnetoencephalography?
Disruption of Functional Brain Networks in Alzheimer's Disease: What Can We Learn from Graph Spectral Analysis of Resting-State Magnetoencephalography?
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DOI：
10.1089/brain.2011.0043
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发表时间：
2012-04-01
影响因子：
3.4
通讯作者：
Stam, Cornelis J.
中科院分区：
文献类型：
--
作者：
de Haan, Willem;van der Flier, Wiesje M.;Stam, Cornelis J.
阿尔茨海默病（AD）患者的大脑结构和功能网络组织受到干扰。然而，目前许多网络分析方法都需要先验假设和方法选择，从而影响结果和解释。图谱分析（GSA）是一种描述网络属性的更直接的代数方法，可能会带来更可靠的结果。在本研究中，GSA 被应用于脑磁图（MEG）数据，以探索 AD 的功能网络完整性。研究人员对 18 名阿尔茨海默病患者（67 岁 +/- 9 岁，6 名女性）和 18 名健康对照者（66 岁 +/- 9 岁，11 名女性）进行了传感器级静息态 MEG 分析。根据使用同步可能性进行的功能连通性分析构建了加权无向图，并以网络连通性、同步性和节点中心性为重点进行了 GSA 分析。主要结果是网络连通性的全面丧失和大多数频段同步性的改变。特征向量中心性映射证实了顶叶区的枢纽地位，并证明了AD患者左颞区θ波段的低中心性与迷你精神状态检查（全球认知功能测试）得分密切相关（r = 0.67，p = 0.001）。综上所述，GSA 是一种理论上可靠的方法，能够检测出注意力缺失症患者功能网络拓扑结构的破坏。除了之前报道的整体连通性损失和顶叶区枢纽状态外，我们还发现 AD 患者的网络同步性受损以及与临床相关的左颞中心性损失。我们的研究结果表明，GSA对于研究AD患者大脑网络拓扑结构和动态变化很有价值。
In Alzheimer's disease (AD), structural and functional brain network organization is disturbed. However, many of the present network analysis measures require a priori assumptions and methodological choices that influence outcomes and interpretations. Graph spectral analysis (GSA) is a more direct algebraic method that describes network properties, which might lead to more reliable results. In this study, GSA was applied to magnetoencephalography (MEG) data to explore functional network integrity in AD. Sensor-level resting-state MEG was performed in 18 Alzheimer patients (age 67 +/- 9, 6 women) and 18 healthy controls (age 66 +/- 9, 11 women). Weighted, undirected graphs were constructed based on functional connectivity analysis using the Synchronization likelihood, and GSA was performed with a focus on network connectivity, synchronizability, and node centrality. The main outcomes were a global loss of network connectivity and altered synchronizability in most frequency bands. Eigenvector centrality mapping confirmed the hub status of the parietal areas, and demonstrated a low centrality of the left temporal region in the theta band in AD patients that was strongly related to the mini mental state examination (global cognitive function test) score (r = 0.67, p = 0.001). Summarizing, GSA is a theoretically solid approach that is able to detect the disruption of functional network topology in AD. In addition to the previously reported overall connectivity losses and parietal area hub status, impaired network synchronizability and a clinically relevant left temporal centrality loss were found in AD patients. Our findings imply that GSA is valuable for the purpose of studying altered brain network topology and dynamics in AD.