Untangling cross-frequency coupling in neuroscience

TL;DR

This paper critically examines cross-frequency coupling (CFC) analysis in neuroscience, highlighting fundamental issues and providing practical recommendations to improve interpretability and avoid common errors in understanding neural interactions.

Contribution

It offers a structured overview of current and potential approaches to analyze CFC, emphasizing biophysical interpretability and practical guidelines for researchers.

Findings

Spectral correlations can mimic CFC without true neural interactions

Common non-stationarities can lead to false CFC detection

Practical recommendations improve analysis reliability

Abstract

Cross-frequency coupling (CFC) has been proposed to coordinate neural dynamics across spatial and temporal scales. Despite its potential relevance for understanding healthy and pathological brain function, the standard CFC analysis and physiological interpretation come with fundamental problems. For example, apparent CFC can appear because of spectral correlations due to common non-stationarities that may arise in the total absence of interactions between neural frequency components. To provide a road map towards an improved mechanistic understanding of CFC, we organize the available and potential novel statistical/modeling approaches according to their biophysical interpretability. While we do not provide solutions for all the problems described, we provide a list of practical recommendations to avoid common errors and to enhance the interpretability of CFC analysis.