Phase Alignment of Low-Frequency Neural Activity to the Amplitude Envelope of Speech Reflects Evoked Responses to Acoustic Edges, Not Oscillatory Entrainment

Abstract

The amplitude envelope of speech is crucial for accurate comprehension. Considered a key stage in speech processing, the phase of neural activity in the theta-delta bands (1 - 10 Hz) tracks the phase of the speech amplitude envelope during listening. However, the mechanisms underlying this envelope representation have been heavily debated. A dominant model posits that envelope tracking reflects entrainment of endogenous low-frequency oscillations to the speech envelope. Alternatively, envelope tracking reflects a series of evoked responses to acoustic landmarks within the envelope. It has proven challenging to distinguish these two mechanisms. To address this, we recorded magnetoencephalography while participants (n=12, 6 female) listened to natural speech, and compared the neural phase patterns to the predictions of two computational models: An oscillatory entrainment model and a model of evoked responses to peaks in the rate of envelope change. Critically, we also presented speech at slowed rates, where the spectro-temporal predictions of the two models diverge. Our analyses revealed transient theta phase-locking in regular speech, as predicted by both models. However, for slow speech we found transient theta and delta phase-locking, a pattern that was fully compatible with the evoked response model but could not be explained by the oscillatory entrainment model. Furthermore, encoding of acoustic edge magnitudes was invariant to contextual speech rate, demonstrating speech rate normalization of acoustic edge representations. Taken together, our results suggest that neural phase locking to the speech envelope is more likely to reflect discrete representation of transient information rather than oscillatory entrainment.Significance statement:Oganian and colleagues probe a highly debated topic in speech perception – the neural mechanisms underlying the cortical representation of the temporal envelope of speech. It is well established that the slow intensity profile of the speech signal, its envelope, elicits a robust brain response that “tracks” these envelope fluctuations. The oscillatory entrainment model posits that envelope tracking reflects phase alignment of endogenous neural oscillations. Here the authors provide evidence for a distinct mechanism. They show that neural speech envelope tracking arises from transient evoked neural responses to rapid increases in the speech envelope. Explicit computational modeling provides direct and compelling evidence that evoked responses are the primary mechanism underlying cortical speech envelope representations, with no evidence for oscillatory entrainment.

Effects of Stimulus Rate and Periodicity on Auditory Cortical Entrainment to Continuous Sounds

“…Indeed, there is some evidence that auditory cortical entrainment is enhanced for intelligible signals which might explain the larger PLV we see for the syllable train relative to click stimuli ( Xu et al, 2023 ). Moreover, token duration seems to play a less prominent role in the strength of cortical entrainment since tracking is dominated by locking to an acoustic signal's edge landmarks rather than its nucleus, per se ( Oganian and Chang, 2019 ; Oganian et al, 2023 ).…”

High-resolution neural recordings improve the accuracy of speech decoding

“…9 ). LFS were associated with the temporal structure of speech (prosodics and syllabic information) 52 – 55 , and the lack of performance improvements may be attributed to the stimuli design of single non-word speech tokens, compared to naturalistic stimuli with varying syllabic/prosodic information.…”

Neural tracking of continuous acoustics: properties, speech‐specificity and open questions

“…In speech research, early studies reported speech-aligned neural activity on the syllable level (Ahissar et al, 2001;Luo & Poeppel, 2007;Peelle et al, 2013). Although this effect seems to include responses to sharp acoustic onsets (Doelling et al, 2014;Oganian et al, 2023), other research found that neural dynamics can track various structural or 'higher-level' features of speech (for reviews, see Ding & Simon, 2014;Zoefel & VanRullen, 2015a). Later, Ding et al (2016) showed that, only when participants comprehend speech and are therefore able to parse it into various linguistic elements (e.g.…”