Topology of Functional Connectivity and Hub Dynamics in the Beta Band As Temporal Prior for Natural Vision in the Human Brain
Topology of Functional Connectivity and Hub Dynamics in the Beta Band As Temporal Prior for Natural Vision in the Human Brain
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DOI：
10.1523/jneurosci.1089-17.2018
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发表时间：
2018-04-11
影响因子：
5.3
通讯作者：
Della Penna, Stefania
中科院分区：
文献类型：
--
作者：
Betti, Viviana;Corbetta, Maurizio;Della Penna, Stefania
网络中心代表跨许多不同节点和系统的信息集成的汇聚点。尽管人们对人脑中枢区域的拓扑结构了解很多，但对其时间动态知之甚少。在这里，我们检查在没有任务（休息）的情况下或在观察自然或合成视觉刺激期间测量时中心区域的静态和动态中心性。我们在人类（男女）中使用脑磁图（MEG）来测量三种情况下α和β带有限功率（BLP）的静态和瞬态区域和网络级交互：视觉固定（休息）、观看电影剪辑（自然视觉）和同一剪辑的时间扰乱版本（扰乱视觉）。与休息相比，我们在两种电影条件下观察到 alpha-BLP 连接性均大幅下降。此外，这两种电影条件都会导致阿尔法波段的连接发生重大重组，尤其是网络之间的连接。相比之下，休息和自然视觉之间的 beta-BLP 连接性非常相似。不仅拓扑没有改变，而且自然视觉期间核心网络中集线器的联合动态可以通过静息状态下的类似波动来预测。我们通过暗示β带高阶区域中发生的缓慢变化的积分波动可能是预测和预测视觉环境缓慢变化的时间模式的机制来解释这些发现。
Networks hubs represent points of convergence for the integration of information across many different nodes and systems. Although a great deal is known on the topology of hub regions in the human brain, little is known about their temporal dynamics. Here, we examine the static and dynamic centrality of hub regions when measured in the absence of a task (rest) or during the observation of natural or synthetic visual stimuli. We used Magnetoencephalography (MEG) in humans (both sexes) to measure static and transient regional and network-level interaction in alpha-and beta-band limited power (BLP) in three conditions: visual fixation (rest), viewing of movie clips (natural vision), and time-scrambled versions of the same clips (scrambled vision). Compared with rest, we observed in both movie conditions a robust decrement of alpha-BLP connectivity. Moreover, both movie conditions caused a significant reorganization of connections in the alpha band, especially between networks. In contrast, beta-BLP connectivity was remarkably similar between rest and natural vision. Not only the topology did not change, but the joint dynamics of hubs in a core network during natural vision was predicted by similar fluctuations in the resting state. We interpret these findings by suggesting that slow-varying fluctuations of integration occurring in higher-order regions in the beta band may be a mechanism to anticipate and predict slow-varying temporal patterns of the visual environment.