Volume 16 Supplement 1
An information theoretic measure of cross-frequency coupling
© Ardila-Jimenez et al. 2015
Published: 18 December 2015
The coupling of neuronal oscillations between cortical areas has been proposed both as a mechanism for top-down and bottom-up signaling in the brain. These interactions may facilitate the coordination of both local and distributed networks across different time scales. However, we are still exploring what the best method is to quantify them. Of particular interest has been the role of phase-amplitude cross-frequency coupling (CFC), and a variety of methods to analyze this have been proposed . Thus far none of these stands out as an ideal measure. We propose the use of Mutual Information to quantify CFC. We test the performance of this method against two other approaches: the Mean Vector Length, and the Envelope to Signal Correlation. Finally we apply this method to data recorded from the mouse early visual system.
The ability of Mutual Information to measure the amount of common information shared by the two systems, while capturing both linear and nonlinear relationships, makes it a suitable candidate as a measure of cross-frequency interactions. The resulting value is measured in an absolute scale which provides a framework for comparison across studies. A number of methods have been proposed for measuring CFC each with its own benefits and caveats.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.