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功能脑网络揭示了认知储备的存在以及网络拓扑结构和动态之间的相互作用。

Functional brain networks reveal the existence of cognitive reserve and the interplay between network topology and dynamics.

机构信息

INSERM U-1127, Institut du Cerveau et de la Moelle Épinière (ICM), Hôpital Pitié Salpêtrière, Paris, France.

GISC & Laboratory of Biological Networks, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain.

出版信息

Sci Rep. 2018 Jul 12;8(1):10525. doi: 10.1038/s41598-018-28747-6.

Abstract

We investigated how the organization of functional brain networks was related to cognitive reserve (CR) during a memory task in healthy aging. We obtained the magnetoencephalographic functional networks of 20 elders with a high or low CR level to analyse the differences at network features. We reported a negative correlation between synchronization of the whole network and CR, and observed differences both at the node and at the network level in: the average shortest path and the network outreach. Individuals with high CR required functional networks with lower links to successfully carry out the memory task. These results may indicate that those individuals with low CR level exhibited a dual pattern of compensation and network impairment, since their functioning was more energetically costly to perform the task as the high CR group. Additionally, we evaluated how the dynamical properties of the different brain regions were correlated to the network parameters obtaining that entropy was positively correlated with the strength and clustering coefficient, while complexity behaved conversely. Consequently, highly connected nodes of the functional networks showed a more stochastic and less complex signal. We consider that network approach may be a relevant tool to better understand brain functioning in aging.

摘要

我们研究了在健康老年人的记忆任务中,大脑功能网络的组织与认知储备(CR)之间的关系。我们获取了 20 名认知储备水平高或低的老年人的脑磁图功能网络,以分析网络特征的差异。我们报告了整个网络同步与 CR 之间呈负相关,并且在节点和网络水平上都观察到了差异:平均最短路径和网络扩展性。具有高 CR 的个体需要具有较低链接的功能网络才能成功执行记忆任务。这些结果可能表明,那些 CR 水平较低的个体表现出了补偿和网络损伤的双重模式,因为他们的功能需要更多的能量来完成任务,而高 CR 组则不需要。此外,我们评估了不同脑区的动力学特性与网络参数之间的相关性,发现熵与强度和聚类系数呈正相关,而复杂度则相反。因此,功能网络的高连接节点表现出更随机和更不复杂的信号。我们认为,网络方法可能是更好地理解衰老过程中大脑功能的一个相关工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4caa/6043549/beec68b8b6f3/41598_2018_28747_Fig1_HTML.jpg

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