Olejarczyk Elzbieta, Marzetti Laura, Pizzella Vittorio, Zappasodi Filippo
Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland.
J Neural Eng. 2017 Jun;14(3):036017. doi: 10.1088/1741-2552/aa6401. Epub 2017 Apr 5.
In the present work, a nonlinear measure (transfer entropy, TE) was used in a multivariate approach for the analysis of effective connectivity in high density resting state EEG data in eyes open and eyes closed. Advantages of the multivariate approach in comparison to the bivariate one were tested. Moreover, the multivariate TE was compared to an effective linear measure, i.e. directed transfer function (DTF). Finally, the existence of a relationship between the information transfer and the level of brain synchronization as measured by phase synchronization value (PLV) was investigated.
The comparison between the connectivity measures, i.e. bivariate versus multivariate TE, TE versus DTF, TE versus PLV, was performed by means of statistical analysis of indexes based on graph theory.
The multivariate approach is less sensitive to false indirect connections with respect to the bivariate estimates. The multivariate TE differentiated better between eyes closed and eyes open conditions compared to DTF. Moreover, the multivariate TE evidenced non-linear phenomena in information transfer, which are not evidenced by the use of DTF. We also showed that the target of information flow, in particular the frontal region, is an area of greater brain synchronization.
Comparison of different connectivity analysis methods pointed to the advantages of nonlinear methods, and indicated a relationship existing between the flow of information and the level of synchronization of the brain.
在本研究中，一种非线性测量方法（转移熵，TE）被用于多变量分析，以研究睁眼和闭眼状态下高密度静息态脑电图数据中的有效连接性。测试了多变量方法相对于双变量方法的优势。此外，将多变量TE与一种有效的线性测量方法，即定向传递函数（DTF）进行了比较。最后，研究了信息传递与通过相位同步值（PLV）测量的脑同步水平之间的关系。
通过基于图论的指标统计分析，对连接性测量方法进行比较，即双变量与多变量TE、TE与DTF、TE与PLV。
与双变量估计相比，多变量方法对错误的间接连接不太敏感。与DTF相比，多变量TE在区分闭眼和睁眼状态方面表现更好。此外，多变量TE证明了信息传递中的非线性现象，而DTF的使用并未证明这些现象。我们还表明，信息流的目标，特别是额叶区域，是脑同步程度更高的区域。
不同连接性分析方法的比较指出了非线性方法的优势，并表明了信息流动与脑同步水平之间存在的关系。
