Abstract
Phase-amplitude coupling (PAC) is proposed to play an essential role in coordinating the processing of information on local and global scales. In recent years, the methods able to reveal trustworthy PAC has gained considerable interest. However, the intrinsic features of some signals can lead to the identification of spurious or waveform-dependent coupling. This prompted us to develop an easily accessible tool that could be used to differentiate spurious from authentic PAC. Here, we propose a new tool for more reliable detection of PAC named the Extended Modulation Index (eMI) based on the classical Modulation Index measure of coupling. eMI is suitable both for continuous and epoched data and allows estimation of the statistical significance of each pair of frequencies for phase and for amplitude in the whole comodulogram in the framework of extreme value statistics. We compared eMI with the reference PAC measures—direct PAC estimator (a modification of Mean Vector Length) and standard Modulation Index. All three methods were tested using computer-simulated data and actual local field potential recordings from freely moving rats. All methods exhibited similar properties in terms of sensitivity and specificity of PAC detection. eMI proved to be more selective in the dimension of frequency for phase. One of the novelty’s offered by eMI is a heuristic algorithm for classification of PAC as Reliable or Ambiguous. It relies on analysis of the relation between the spectral properties of the signal and the detected coupling. Moreover, eMI generates visualizations that support further evaluation of the coupling properties. It also introduces the concept of the polar phase-histogram to study phase relations of coupled slow and fast oscillations. We discuss the extent to which eMI addresses the known problems of interpreting PAC. The Matlab® toolbox implementing eMI framework, and the two reference PAC estimators is freely available as EEGLAB plugin at https://github.com/GabrielaJurkiewicz/ePAC.
Highlights
Neuronal activity manifests itself, among others, in the form of periodic voltage fluctuations, which can be recorded as rhythms in electroencephalograms (EEG) and electrocorticograms (ECoG)
To address the problem of interpreting Phase-amplitude coupling (PAC) and combine most of Aru et al (2015) recommendations, we propose a comprehensive framework for analyzing this type of cross-frequency coupling (CFC), which we have named the Extended Modulation Index
There are two widely used methods: direct PAC estimator (Ozkurt and Schnitzler 2011), and Modulation Index (MI) (Tort et al 2010), which will serve as reference methods, and the method we propose here – Extended Modulation Index (eMI)
Summary
Among others, in the form of periodic voltage fluctuations, which can be recorded as rhythms in electroencephalograms (EEG) and electrocorticograms (ECoG). Brain rhythms are studied in discrete frequency bands, which often are attributed to distinct physiological functions (Buzsaki and Draguhn 2004; Wang 2010). Phase-amplitude coupling (PAC) is a particular type of cross-frequency coupling (CFC). Previous studies have reported PAC between the phase of a low-frequency oscillation and the amplitude of high-frequency oscillations in local field potentials (LFP) in rats (Lisman and Idiart 1995; Bragin et al 1995; Tort et al 2008) and in ECoG and EEG in humans (Canolty et al 2006; Axmacher et al 2010; Koster et al 2014; Demiralp et al 2007). There is a growing interest in understanding patterns of CFC since they may be relevant for diagnosing and eventually treating various disorders or in designing preventive strategies (Zhang et al 2016; Berman et al 2015; de Hemptinne et al 2013; Koutsoukos et al 2013)
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