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用于驾驶困倦评估的频间拓扑和动态高阶功能连接。

Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2019 Mar;27(3):358-367. doi: 10.1109/TNSRE.2019.2893949. Epub 2019 Jan 21.

Abstract

Previous studies exploring driving drowsiness utilized spectral power and functional connectivity without considering between-frequency and more complex synchronizations. To complement such lacks, we explored inter-regional synchronizations based on the topographical and dynamic properties between frequency bands using high-order functional connectivity (HOFC) and envelope correlation. We proposed the dynamic interactions of HOFC, associated-HOFC, and a global metric measuring the aggregated effect of the functional connectivity. The EEG dataset was collected from 30 healthy subjects, undergoing two driving sessions. The two-session setting was employed for evaluating the metric reliability across sessions. Based on the results, we observed reliably significant metric changes, mainly involving the alpha band. In HOFC , HOFC , associated- HOFC , and associated- HOFC , the connection-level metrics in frontal-central, central-central, and central-parietal/occipital areas were significantly increased, indicating a dominance in the central region. Similar results were also obtained in the HOFC and aHOFC . For dynamic-low-order-FC and dynamic-HOFC, the global metrics revealed a reliably significant increment in the alpha, theta-alpha, and alpha-beta bands. Modularity indexes of associated- HOFC and associated- HOFC also exhibited reliably significant differences. This paper demonstrated that within-band and between-frequency topographical and dynamic FC can provide complementary information to the traditional individual-band LOFC for assessing driving drowsiness.

摘要

先前研究探索驾驶困倦主要利用频谱功率和功能连接,但未考虑到不同频率之间以及更复杂的同步。为了弥补这些不足,我们探索了基于频带之间拓扑和动态特性的区域间同步,使用了高阶功能连接(HOFC)和包络相关。我们提出了 HOFC、相关-HOFC 和一个全局指标的动态相互作用,该全局指标用于测量功能连接的综合效应。该 EEG 数据集是从 30 名健康受试者中收集的,他们进行了两次驾驶测试。采用两阶段设置是为了评估跨阶段的度量可靠性。基于结果,我们观察到了可靠的显著度量变化,主要涉及阿尔法频段。在 HOFC、HOFC、相关-HOFC 和相关-HOFC 中,额中央、中央中央和中央顶枕/枕叶区域的连接水平指标显著增加,表明中央区域占主导地位。在 HOFC 和 aHOFC 中也得到了类似的结果。对于动态低阶-FC 和动态-HOFC,全局指标显示在阿尔法、theta-alpha 和 alpha-beta 频段可靠地显著增加。相关-HOFC 和相关-HOFC 的模块性指数也表现出可靠的显著差异。本文表明,频带内和频带间的拓扑和动态 FC 可以为评估驾驶困倦的传统单频带 LOFC 提供补充信息。

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