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Multitaper Estimates of Phase-Amplitude Coupling
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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 phase-amplitude coupling with existing statistical measures have been well-documented. The limitations of these measures include: (i) response to non-oscillatory, high-frequency, broad-band activity, (ii) response to high-frequency components of the low-frequency oscillation, (iii) adhoc selection of analysis frequency-intervals, and (iv) reliance upon data shuffling to assess statistical significance. In this work, a multitaper phase-amplitude coupling estimator is proposed that addresses issues (i)-(iv) above. Specifically, issue (i) 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 (ii) is addressed by replacing coherence between the low-frequency and high-frequency components in a standard PAC estimator with multitaper partial coherence, while issue (iii) is addressed with a physical argument regarding meaningful neural oscillation. Finally, asymptotic statistical assessment of the multitaper estimator is introduced to address issue (iv).
Title: Multitaper Estimates of Phase-Amplitude Coupling
Description:
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 phase-amplitude coupling with existing statistical measures have been well-documented.
The limitations of these measures include: (i) response to non-oscillatory, high-frequency, broad-band activity, (ii) response to high-frequency components of the low-frequency oscillation, (iii) adhoc selection of analysis frequency-intervals, and (iv) reliance upon data shuffling to assess statistical significance.
In this work, a multitaper phase-amplitude coupling estimator is proposed that addresses issues (i)-(iv) above.
Specifically, issue (i) 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 (ii) is addressed by replacing coherence between the low-frequency and high-frequency components in a standard PAC estimator with multitaper partial coherence, while issue (iii) is addressed with a physical argument regarding meaningful neural oscillation.
Finally, asymptotic statistical assessment of the multitaper estimator is introduced to address issue (iv).
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