Modulation Spectra Capture EEG Responses to Speech Signals and Drive Distinct Temporal Response Functions.

Speech signals have a unique shape of long-term modulation spectrum that is distinct from environmental noise, music, and non-speech vocalizations. Does the human auditory system adapt to the speech long-term modulation spectrum and efficiently extract critical information from speech signals? To answer this question, we tested whether neural responses to speech signals can be captured by specific modulation spectra of non-speech acoustic stimuli. We generated amplitude modulated (AM) noise with the speech modulation spectrum and 1/f modulation spectra of different exponents to imitate temporal dynamics of different natural sounds. We presented these AM stimuli and a 10-min piece of natural speech to 19 human participants undergoing electroencephalography (EEG) recording. We derived temporal response functions (TRFs) to the AM stimuli of different spectrum shapes and found distinct neural dynamics for each type of TRFs. We then used the TRFs of AM stimuli to predict neural responses to the speech signals, and found that (1) the TRFs of AM modulation spectra of exponents 1, 1.5, and 2 preferably captured EEG responses to speech signals in the δ band and (2) the θ neural band of speech neural responses can be captured by the AM stimuli of an exponent of 0.75. Our results suggest that the human auditory system shows specificity to the long-term modulation spectrum and is equipped with characteristic neural algorithms tailored to extract critical acoustic information from speech signals.

Theta and Gamma Bands Encode Acoustic Dynamics over Wide-Ranging Timescales.

Natural sounds contain acoustic dynamics ranging from tens to hundreds of milliseconds. How does the human auditory system encode acoustic information over wide-ranging timescales to achieve sound recognition? Previous work (Teng et al. 2017) demonstrated a temporal coding preference for the theta and gamma ranges, but it remains unclear how acoustic dynamics between these two ranges are coded. Here, we generated artificial sounds with temporal structures over timescales from ~200 to ~30 ms and investigated temporal coding on different timescales. Participants discriminated sounds with temporal structures at different timescales while undergoing magnetoencephalography recording. Although considerable intertrial phase coherence can be induced by acoustic dynamics of all the timescales, classification analyses reveal that the acoustic information of all timescales is preferentially differentiated through the theta and gamma bands, but not through the alpha and beta bands; stimulus reconstruction shows that the acoustic dynamics in the theta and gamma ranges are preferentially coded. We demonstrate that the theta and gamma bands show the generality of temporal coding with comparable capacity. Our findings provide a novel perspective-acoustic information of all timescales is discretised into two discrete temporal chunks for further perceptual analysis.

Theta band oscillations reflect more than entrainment: behavioral and neural evidence demonstrates an active chunking process.

Parsing continuous acoustic streams into perceptual units is fundamental to auditory perception. Previous studies have uncovered a cortical entrainment mechanism in the delta and theta bands (~1-8 Hz) that correlates with formation of perceptual units in speech, music, and other quasi-rhythmic stimuli. Whether cortical oscillations in the delta-theta bands are passively entrained by regular acoustic patterns or play an active role in parsing the acoustic stream is debated. Here, we investigate cortical oscillations using novel stimuli with 1/f modulation spectra. These 1/f signals have no rhythmic structure but contain information over many timescales because of their broadband modulation characteristics. We chose 1/f modulation spectra with varying exponents of f, which simulate the dynamics of environmental noise, speech, vocalizations, and music. While undergoing magnetoencephalography (MEG) recording, participants listened to 1/f stimuli and detected embedded target tones. Tone detection performance varied across stimuli of different exponents and can be explained by local signal-to-noise ratio computed using a temporal window around 200 ms. Furthermore, theta band oscillations, surprisingly, were observed for all stimuli, but robust phase coherence was preferentially displayed by stimuli with exponents 1 and 1.5. We constructed an auditory processing model to quantify acoustic information on various timescales and correlated the model outputs with the neural results. We show that cortical oscillations reflect a chunking of segments, > 200 ms. These results suggest an active auditory segmentation mechanism, complementary to entrainment, operating on a timescale of ~200 ms to organize acoustic information.

Concurrent temporal channels for auditory processing: Oscillatory neural entrainment reveals segregation of function at different scales.

Natural sounds convey perceptually relevant information over multiple timescales, and the necessary extraction of multi-timescale information requires the auditory system to work over distinct ranges. The simplest hypothesis suggests that temporal modulations are encoded in an equivalent manner within a reasonable intermediate range. We show that the human auditory system selectively and preferentially tracks acoustic dynamics concurrently at 2 timescales corresponding to the neurophysiological theta band (4-7 Hz) and gamma band ranges (31-45 Hz) but, contrary to expectation, not at the timescale corresponding to alpha (8-12 Hz), which has also been found to be related to auditory perception. Listeners heard synthetic acoustic stimuli with temporally modulated structures at 3 timescales (approximately 190-, approximately 100-, and approximately 30-ms modulation periods) and identified the stimuli while undergoing magnetoencephalography recording. There was strong intertrial phase coherence in the theta band for stimuli of all modulation rates and in the gamma band for stimuli with corresponding modulation rates. The alpha band did not respond in a similar manner. Classification analyses also revealed that oscillatory phase reliably tracked temporal dynamics but not equivalently across rates. Finally, mutual information analyses quantifying the relation between phase and cochlear-scaled correlations also showed preferential processing in 2 distinct regimes, with the alpha range again yielding different patterns. The results support the hypothesis that the human auditory system employs (at least) a 2-timescale processing mode, in which lower and higher perceptual sampling scales are segregated by an intermediate temporal regime in the alpha band that likely reflects different underlying computations.

Adding irrelevant information to the content prime reduces the prime-induced unmasking effect on speech recognition.

Presenting the early part of a nonsense sentence in quiet improves recognition of the last keyword of the sentence in a masker, especially a speech masker. This priming effect depends on higher-order processing of the prime information during target-masker segregation. This study investigated whether introducing irrelevant content information into the prime reduces the priming effect. The results showed that presenting the first four syllables (not including the second and third keywords) of the three-keyword target sentence in quiet significantly improved recognition of the second and third keywords in a two-talker-speech masker but not a noise masker, relative to the no-priming condition. Increasing the prime content from four to eight syllables (including the first and second keywords of the target sentence) further improved recognition of the third keyword in either the noise or speech masker. However, if the last four syllables of the eight-syllable prime were replaced by four irrelevant syllables (which did not occur in the target sentence), all the prime-induced speech-recognition improvements disappeared. Thus, knowing the early part of the target sentence mainly reduces informational masking of target speech, possibly by helping listeners attend to the target speech. Increasing the informative content of the prime further improves target-speech recognition probably by reducing the processing load. The reduction of the priming effect by adding irrelevant information to the prime is not due to introducing additional masking of the target speech.