Assessment of cross-frequency coupling with confidence using generalized linear models

Background: Brain voltage activity displays distinct neuronal rhythms spanning a wide frequency range. How rhythms of different frequency interact - and the function of these interactions - remains an active area of research. Many methods have been proposed to assess the interactions between different frequency rhythms, in particular measures that characterize the relationship between the phase of a low frequency rhythm and the amplitude envelope of a high frequency rhythm. However, an optimal analysis method to assess this cross-frequency coupling (CFC) does not yet exist. New method: Here we describe a new procedure to assess CFC that utilizes the generalized linear modeling (GLM) framework. Results: We illustrate the utility of this procedure in three synthetic examples. The proposed GLM-CFC procedure allows a rapid and principled assessment of CFC with confidence bounds, scales with the intensity of the CFC, and accurately detects biphasic coupling. Comparison with existing methods: Compared to existing methods, the proposed GLM-CFC procedure is easily interpretable, possesses confidence intervals that are easy and efficient to compute, and accurately detects biphasic coupling. Conclusions: The GLM-CFC statistic provides a method for accurate and statistically rigorous assessment of CFC. (C) 2013 Elsevier B.V. All rights reserved.