Understanding the mechanisms underlying cross-frequency coupling (CFC) in the brain is essential for decoding the coordination of neural populations during complex perceptual processes. In this study, we present a biophysically inspired method to apply the Qin’s oscillator model to simulate phase-amplitude coupling (PAC) across multiple frequency bands. Our framework incorporates coupled nonlinear oscillators with tunable intrinsic growth rates ( \(\delta \) ) and angular frequency ( \(\omega \) ), enabling dynamic interactions between low- and high-frequency components that emulate nonlinear modulation patterns in cortical networks. We validate the model by comparing its output with PAC patterns derived from electroencephalography (EEG) recordings during an audiovisual bistable perception task. Utilizing a standardized PAC analysis pipeline, we demonstrate that the simulated data replicates critical features of empirical EEG signals, including frequency-specific PAC and multi-peak coupling structures. The results demonstrate that the difference between the excitability parameters of interacting oscillators significantly modulated the strength of PAC. Smaller \(\delta \) differences enhance PAC magnitude and induce broader spectral coupling, whereas larger asymmetries attenuate PAC and constrain its bandwidth. These findings suggest that intrinsic excitability matching between neuronal populations play an important role in cross-frequency coordination. Overall, this study offers a biologically plausible framework for understanding the computational origins of CFC during audiovisual integration.