Multitaper estimates of phase-amplitude coupling.

Abstract

Phase-amplitude coupling (PAC) is the association of the amplitude of a high-frequency oscillation with the phase of a low-frequency oscillation. In neuroscience, this relationship provides a mechanism by which neural activity might be coordinated between distant regions. The dangers and pitfalls of assessing PAC with commonly used statistical measures have been well-documented. The limitations of these measures include: (1) response to non-oscillatory, high-frequency, broad-band activity, (2) response to high-frequency components of the low-frequency oscillation, (3) adhoc selection of analysis frequency-intervals, and (4) reliance upon data shuffling to assess statistical significance.<i>Objective.</i>To address issues (1)-(4) by introducing a nonparametric multitaper estimator of PAC.<i>Approach.</i>In this work, a multitaper PAC estimator is proposed that addresses these issues. Specifically, issue (1) is addressed by replacing the analytic signal envelope estimator computed using the Hilbert transform with a multitaper estimator that down-weights non-sinusoidal activity using a classical, multitaper super-resolution technique. Issue (2) is addressed by replacing coherence between the low-frequency and high-frequency components in a standard PAC estimator with multitaper partial coherence, while issue (3) is addressed with a physical argument regarding meaningful neural oscillation. Finally, asymptotic statistical assessment of the multitaper estimator is introduced to address issue (4).<i>Main results.</i>Multitaper estimates of PAC are introduced. Their efficacy is demonstrated in simulation and on human intracranial recordings obtained from epileptic patients.<i>Significance.</i>This work facilitates a more informative statistical assessment of PAC, a phenomena exhibited by many neural systems, and provides a basis upon which further nonparametric multitaper-related methods can be developed.