Phase-amplitude coupling (PAC) between the phase of low-frequency oscillations and the power of high-frequency activity plays a functional role in neuronal computation and information transfer. Traditional Hilbert transform-based PAC methods assume that neuronal activity is narrowband, sinusoidal, and sustained. However, natural neuronal signals often violate these three assumptions, creating a potential confound for the interpretation of PAC results. In this study, we present a new method, called Tau-Modulation, that does not require these assumptions to be met. We use this method to identify task-relevant neuronal networks in human electrocorticographic signals. Our results show that Tau-Modulation can identify these networks and characterize the strength and frequency of wideband low-frequency coupling with broadband gamma activity. Thus, Tau-Modulation might provide for a robust approach to analyzing neuronal signals and pave the way for new insights on brain functions.