Evaluation of Phase-Amplitude Coupling in Resting State Magnetoencephalographic Signals: Effect of Surrogates and Evaluation Approach

Abstract

Phase-amplitude coupling (PAC) plays an important role in neural communication and computation. Interestingly, recent studies have indicated the presence of ubiquitous PAC phenomenon even during the resting state. Despite the importance of PAC phenomenon, estimation of significant physiological PAC is challenging because of the lack of appropriate surrogate measures to control false positives caused by non-physiological PAC. Therefore, in the present study, we evaluated PAC phenomenon during resting-state magnetoencephalography (MEG) signal and considered various surrogate measures and computational approaches widely used in the literature in addition to proposing new ones. We evaluated PAC phenomenon over the entire length of the MEG signal and for multiple shorter time segments. The results indicate that the extent of PAC phenomenon mainly depends on the surrogate measures and PAC computational methods used, as well as the evaluation approach. After a careful and critical evaluation, we found that resting-state MEG signals failed to exhibit ubiquitous PAC phenomenon, contrary to what has been suggested previously.

Developmental Changes in EEG Phase Amplitude Coupling and Phase Preference over the First Three Years After Birth

“…Here, we demonstrate the typical development of PAC from 3 months through 3 years of age. This PAC occurs most prominently between alpha-beta and gamma, largely consistent with several reports of alpha-gamma PAC in resting state recordings (Roux et al, 2013;Berman et al, 2015;Gohel et al, 2016), but is also present between theta and beta, theta and gamma, and alpha and beta. We observe PAC broadly across the scalp, suggesting a relatively ubiquitous presence of cross-frequency coupling.…”

Anterior Thalamic High Frequency Band Activity Is Coupled with Theta Oscillations at Rest

“…A distribution against which to test the statistical significance of the MI for each channel was generated by dividing the signal into two sections and swapping amplitude and phase blocks in order to preserve the statistical properties of the data in the surrogates (Canolty et al, 2006; Foster and Parvizi, 2012; Aru et al, 2015; Gohel et al, 2016). …”

“…An MI greater than zero indicates a tendency for amplitude in the high frequency signal to peak at a particular point in the phase cycle of the low frequency signal (Onslow et al, 2011 ). A distribution against which to test the statistical significance of the MI for each channel was generated by dividing the signal into two sections and swapping amplitude and phase blocks in order to preserve the statistical properties of the data in the surrogates (Canolty et al, 2006 ; Foster and Parvizi, 2012 ; Aru et al, 2015 ; Gohel et al, 2016 ).…”

Commentary: Evaluation of Phase-Amplitude Coupling in Resting State Magnetoencephalographic Signals: Effect of Surrogates and Evaluation Approach

“…Using Human Connectome Project (HCP) data, Gohel et al ( 2016 ) (GEA) recently reported that “resting-state MEG signals failed to exhibit ubiquitous phase-amplitude coupling (PAC) phenomenon, contrary to what has been suggested” by Florin and Baillet ( 2015 ) (FB). GEA argued that the original PAC findings by FB were driven by false positives resulting from the use of inappropriate methods.…”

“…In this commentary, we first correct GEA's mischaracterization of the approach actually used by FB. We then investigated the PAC computations in Gohel et al ( 2016 ) (GEA) and demonstrate that with FB's approach, it is actually possible to detect PAC in the Human Connectome Project (HCP) resting-state data. Finally, when making the data processing as similar as possible to GEA we still found significant PAC across large portions of the brain.…”