title: A Precise Annotation of Phase-Amplitude Coupling Intensity.
abstract: 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.
authors.affiliation: College of Life Sciences and Key Laboratory of Bioactive Materials Ministry of Education, Nankai University, Tianjin, PR China.
authors.forename: Ning
authors.initials: N
authors.lastname: Cheng
authors.affiliation: 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.
authors.forename: Qun
authors.initials: Q
authors.lastname: Li
authors.affiliation: College of Life Sciences and Key Laboratory of Bioactive Materials Ministry of Education, Nankai University, Tianjin, PR China.
authors.forename: Xiaxia
authors.initials: X
authors.lastname: Xu
authors.affiliation: College of Life Sciences and Key Laboratory of Bioactive Materials Ministry of Education, Nankai University, Tianjin, PR China.
authors.forename: Tao
authors.initials: T
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008959:Models, Neurological; D012815:Signal Processing, Computer-Assisted