A Time-frequency Based Multivariate Phase-amplitude Coupling Measure

Interaction of neuronal oscillations across different frequency bands plays an important role in perception, attention, and memory. One particular form of interaction is the modulation of the amplitude of high-frequency oscillations by the phase of low-frequency oscillations, known as phase-amplitude coupling (PAC). Current methods for quantifying PAC mostly rely on Hilbert transform which assumes that brain activity is stationary and narrowband. Moreover, these methods are limited to quantifying bivariate PAC and cannot capture multivariate cross-frequency coupling between different brain regions. This paper presents a new complex time-frequency based high resolution PAC measure and its extension to the multivariate case using PARAFAC (Parallel Factor) model. The proposed approach is evaluated on both simulated and real electroencephalogram (EEG) data.