IEEE Trans Neural Syst Rehabil Eng. 2014 Mar;22(2):212-21. doi: 10.1109/TNSRE.2013.2289899.
Synchronization behavior of electroencephalographic (EEG) signals is important for decoding information processing in the human brain. Modern multichannel EEG allows a transition from traditional measurements of synchronization in pairs of EEG signals to whole-brain synchronization maps. The latter can be based on bivariate measures (BM) via averaging over pair-wise values or, alternatively, on multivariate measures (MM), which directly ascribe a single value to the synchronization in a group. In order to compare BM versus MM, we applied nine different estimators to simulated multivariate time series with known parameters and to real EEGs.We found widespread correlations between BM and MM, which were almost frequency-independent for all the measures except coherence. The analysis of the behavior of synchronization measures in simulated settings with variable coupling strength, connection probability, and parameter mismatch showed that some of them, including S-estimator, S-Renyi, omega, and coherence, aremore sensitive to linear interdependences,while others, like mutual information and phase locking value, are more responsive to nonlinear effects. Onemust consider these properties together with the fact thatMM are computationally less expensive and, therefore, more efficient for the large-scale data sets than BM while choosing a synchronization measure for EEG analysis.
脑电（EEG）信号的同步行为对于解码人类大脑中的信息处理非常重要。现代多通道 EEG 允许从 EEG 信号对的传统同步测量过渡到全脑同步图。后者可以基于二元测量（BM）通过对两两值进行平均，或者直接基于多元测量（MM），将单个值直接归因于组内的同步。为了比较 BM 与 MM，我们将九种不同的估计器应用于具有已知参数的模拟多元时间序列和真实 EEG。我们发现 BM 和 MM 之间存在广泛的相关性，除了相干性之外，所有这些相关性几乎与频率无关。对具有可变耦合强度、连接概率和参数失配的模拟环境中同步测量行为的分析表明，其中一些测量值，包括 S 估计器、S-Renyi、omega 和相干性，对线性相关性更敏感，而其他测量值，如互信息和相位锁定值，对非线性效应更敏感。在为 EEG 分析选择同步测量值时，必须考虑到这些特性，以及 MM 计算成本更低的事实，因此对于大规模数据集来说比 BM 更有效。
