Frequency modulation entrains slow neural oscillations and optimizes human listening behavior

Abstract

The human ability to continuously track dynamic environmental stimuli, in particular speech, is proposed to profit from "entrainment" of endogenous neural oscillations, which involves phase reorganization such that "optimal" phase comes into line with temporally expected critical events, resulting in improved processing. The current experiment goes beyond previous work in this domain by addressing two thus far unanswered questions. First, how general is neural entrainment to environmental rhythms: Can neural oscillations be entrained by temporal dynamics of ongoing rhythmic stimuli without abrupt onsets? Second, does neural entrainment optimize performance of the perceptual system: Does human auditory perception benefit from neural phase reorganization? In a human electroencephalography study, listeners detected short gaps distributed uniformly with respect to the phase angle of a 3-Hz frequency-modulated stimulus. Listeners' ability to detect gaps in the frequency-modulated sound was not uniformly distributed in time, but clustered in certain preferred phases of the modulation. Moreover, the optimal stimulus phase was individually determined by the neural delta oscillation entrained by the stimulus. Finally, delta phase predicted behavior better than stimulus phase or the event-related potential after the gap. This study demonstrates behavioral benefits of phase realignment in response to frequency-modulated auditory stimuli, overall suggesting that frequency fluctuations in natural environmental input provide a pacing signal for endogenous neural oscillations, thereby influencing perceptual processing.

Fig. 1.

(A) FM stimuli for the EEG experiment. Periodicity was conveyed without fluctuations in amplitude (Top), but instead only by fluctuations in frequency (Middle). Listeners detected short silent gaps (Bottom Left) that were distributed uniformly around the 3-Hz FM cycle (Bottom Right); 2, 3, or 4 gaps were present in each 10-s stimulus. (B) Predicted neural and behavioral effects of entrainment to the FM stimulus. At stimulus onset (Top), the phase of the ongoing delta oscillation was predicted to reset to bring the neuronal oscillation into line with the driving stimulus (Middle), thereby modulating the excitation–inhibition cycle of the delta oscillation (Bottom Left). For this reason, gap detection hit rates were expected to be modulated by stimulus phase (Bottom Right).

Fig. 2.

(A) Amplitude spectrum from fast Fourier transform (FFT) of time-domain EEG signal. Amplitude in the 3-Hz and 6-Hz frequency bins was significantly larger than in the neighboring bins. Red solid line indicates the group average spectrum, gray lines show single participants’ spectra, averaged over all electrodes. (B) ITPC shown over time (Left), and averaged over time (Right), again averaged over all electrodes. The red bar indicates the frequency region in which phase coherence was significantly greater than baseline. Inset shows the topography for the significant frequency region, averaged over time; the color scale is the same as for the time-frequency representation of ITPC.

Fig. 3.

(A) Hit rates (red) as a function of 3-Hz stimulus phase (black) for each individual listener. Two cycles of both stimulus and data have been concatenated for illustration purposes. Circular-linear correlations between stimulus phase and hit rates were significant across listeners (P < 0.001). (B) Grand average of the z-transformed individual data in A. Across listeners, there was no consistent relation between gap detection (grand average hit rate, red) and the stimulus phase (black), ruling out acoustic explanations for the observed effect.

Fig. 4.

Single trials were sorted according to the instantaneous phase of the neural delta oscillation at electrode Cz (A) at the time of gap occurrence (from –π to π). Sorting single-trial stimulus phase (B) by applying the same permutation vector revealed that stimulus phase was not consistently related to neural delta phase across listeners. However, hit rate (C) and ERPs (D–F) were. Hit rate (C), N1 amplitude (E), and P2 amplitude (F) were significantly correlated with neural delta phase (P < 0.001). Moreover, optimal neural delta phase for hit rate (G), N1 amplitude (H), and P2 amplitude (I) was consistent across listeners (P < 0.02). Note: this figure shows all trials for all listeners (fixed-effects), whereas all statistics reported took into account the between-subjects variance (random effects).

Fig. 5.

A schematic depicting the reconstruction of individual stimulus–behavior lags (C) from stimulus–brain lags (A) and brain–behavior lags (B). For each listener, stimulus–brain lags were estimated from a cross-correlation analysis, whereas stimulus–behavior and brain–behavior relations were taken from analyses estimating optimal phase from hit rate data. Then, brain–behavior lags and stimulus–brain lags in radians were summed, and this sum was correlated with stimulus–behavior lags (P = 0.03). This relationship confirmed that variability in stimulus–behavior relations is well explained by the intervening brain oscillation phase lag.