A statistical framework to assess cross-frequency coupling while accounting for confounding analysis effects.

Jessica K Nadalin,Meng-Chen Lo,Alik S Widge,Sydney S Cash,Louis-Emmanuel Martinet,Ethan B Blackwood,Uri T Eden,Mark A Kramer

doi:10.7554/elife.44287

Jessica K Nadalin, Meng-Chen Lo + Show 6 more

Open Access

https://doi.org/10.7554/elife.44287

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Abstract

Cross frequency coupling (CFC) is emerging as a fundamental feature of brain activity, correlated with brain function and dysfunction. Many different types of CFC have been identified through application of numerous data analysis methods, each developed to characterize a specific CFC type. Choosing an inappropriate method weakens statistical power and introduces opportunities for confounding effects. To address this, we propose a statistical modeling framework to estimate high frequency amplitude as a function of both the low frequency amplitude and low frequency phase; the result is a measure of phase-amplitude coupling that accounts for changes in the low frequency amplitude. We show in simulations that the proposed method successfully detects CFC between the low frequency phase or amplitude and the high frequency amplitude, and outperforms an existing method in biologically-motivated examples. Applying the method to in vivo data, we illustrate examples of CFC during a seizure and in response to electrical stimuli.

Highlights

Brain rhythms - as recorded in the local field potential (LFP) or scalp electroencephalogram (EEG) are believed to play a critical role in coordinating brain networks
We show that the statistics RPAC and RAAC accurately detect different types of cross-frequency coupling, increase with the intensity of coupling, and detect weak phase-amplitude coupling (PAC) coupled to the low frequency amplitude
We show that the proposed method is less sensitive to changes in low frequency power, and outperforms an existing PAC measure that lacks dependence on the low frequency amplitude

Summary

Introduction

Brain rhythms - as recorded in the local field potential (LFP) or scalp electroencephalogram (EEG) are believed to play a critical role in coordinating brain networks. The phase of low frequency rhythms has been shown to modulate and coordinate neural spiking (Vinck et al, 2010; Hyafil et al, 2015b; Fries et al, 2007) via local circuit mechanisms that provide discrete windows of increased excitability. This interaction, in which fast activity is coupled to slower rhythms, is a common type of cross-frequency coupling (CFC). This particular type of CFC has been shown to carry behaviorally relevant information

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