Cheng Ning, Li Qun, Xu Xiaxia, Zhang Tao
College of Life Sciences and Key Laboratory of Bioactive Materials Ministry of Education, Nankai University, Tianjin, PR China.
College of Mathematics, Nankai University, 300071, Tianjin, PR China.
PLoS One. 2016 Oct 4;11(10):e0163940. doi: 10.1371/journal.pone.0163940. eCollection 2016.
Neuronal information can be coded in different temporal and spatial scales. Cross-frequency coupling of neuronal oscillations, especially phase-amplitude coupling (PAC), plays a critical functional role in neuronal communication and large scale neuronal encoding. Several approaches have been developed to assess PAC intensity. It is generally agreed that the PAC intensity relates to the uneven distribution of the fast oscillation amplitude conditioned on the slow oscillation phase. However, it is still not clear what the PAC intensity exactly means. In the present study, it was found that there were three types of interferential signals taking part in PAC phenomenon. Based on the classification of interferential signals, the conception of PAC intensity is theoretically annotated as the proportion of slow or fast oscillation that is involved in a related PAC phenomenon. In order to make sure that the annotation is proper to some content, simulation data are constructed and then analyzed by three PAC approaches. These approaches are the mean vector length (MVL), the modulation index (MI), and a new permutation mutual information (PMI) method in which the permutation entropy and the information theory are applied. Results show positive correlations between PAC values derived from all three methods and the suggested intensity. Finally, the amplitude distributions, i.e. the phase-amplitude plots, obtained from different PAC intensities show that the annotation proposed in the study is in line with the previous understandings.
神经元信息可以在不同的时间和空间尺度上进行编码。神经元振荡的交叉频率耦合，尤其是相位-幅度耦合（PAC），在神经元通信和大规模神经元编码中发挥着关键的功能作用。已经开发了几种方法来评估PAC强度。人们普遍认为，PAC强度与以慢振荡相位为条件的快振荡幅度的不均匀分布有关。然而，PAC强度到底意味着什么仍然不清楚。在本研究中，发现有三种类型的干扰信号参与了PAC现象。基于干扰信号的分类，PAC强度的概念在理论上被诠释为参与相关PAC现象的慢振荡或快振荡的比例。为了确保这种诠释适用于某些内容，构建了模拟数据，然后用三种PAC方法进行分析。这些方法是平均向量长度（MVL）、调制指数（MI）和一种应用了排列熵和信息论的新的排列互信息（PMI）方法。结果表明，从所有三种方法得出的PAC值与所提出的强度之间存在正相关。最后，从不同PAC强度获得的幅度分布，即相位-幅度图，表明该研究中提出的诠释与先前的理解一致。
