Toward a proper estimation of phase-amplitude coupling in neural oscillations.
BACKGROUND
The phase-amplitude coupling (PAC) between distinct neural oscillations is critical to brain functions that include cross-scale organization, selection of attention, routing the flow of information through neural circuits, memory processing and information coding. Several methods for PAC estimation have been proposed but the limitations of PAC estimation as well as the assumptions about the data for accurate PAC estimation are unclear.


METHODS
We define boundary conditions for standard PAC algorithms and propose "oscillation-triggered coupling" (OTC), a parameter-free, data-driven algorithm for unbiased estimation of PAC. OTC establishes a unified framework that treats individual oscillations as discrete events for estimating PAC from a set of oscillations and for characterizing events from time windows as short as a single modulating oscillation.


RESULTS
For accurate PAC estimation, standard PAC algorithms require amplitude filters with a bandwidth at least twice the modulatory frequency. The phase filters must be moderately narrow-band, especially when the modulatory rhythm is non-sinusoidal. The minimally appropriate analysis window is ∼10s. We then demonstrate that OTC can characterize PAC by treating neural oscillations as discrete events rather than continuous phase and amplitude time series.


METHODS
These findings show that in addition to providing the same information about PAC as the standard approach, OTC facilitates characterization of single oscillations and their sequences, in addition to explaining the role of individual oscillations in generating PAC patterns.


CONCLUSIONS
OTC allows PAC analysis at the level of individual oscillations and therefore enables investigation of PAC at the time scales of cognitive phenomena.
SUNY Downstate and NYU Polytechnic School of Engineering, Joint Graduate Program in Biomedical Engineering, 450 Clarkson Avenue, Brooklyn, NY, USA.
Dino
D
Dvorak
The Robert F. Furchgott Center for Neural and Behavioral Science, Department of Physiology and Pharmacology, SUNY Downstate Medical Center, 450 Clarkson Avenue, Brooklyn, NY, USA; Center for Neural Science, New York University, 4 Washington Place, New York, NY, USA. Electronic address: afenton@nyu.edu.
André A
AA
Fenton
D000465:Algorithms; D000818:Animals; D001921:Brain / Q000502:physiology*; D004594:Electrophysiology / Q000379:methods*; D008297:Male; D051379:Mice; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D051381:Rats; D012815:Signal Processing, Computer-Assisted
Coupling; Event; Gamma; Modulation; Oscillation; PAC; Theta