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.