Cortical auditory responses index the contributions of different RMS-level-dependent segments to speech...

Previous behavioral and neurophysiological studies indicated that the use of an appropriate segmentation method to parse speech streams into meaningful chunks is of vital importance for the examination of sentence perception and intelligibility. Researchers have recently proposed speech segmentation methods employing the relative root-mean-square (RMS) intensity to separate sentences into segments with distinct intelligibility information. However, the effects of different RMS-level segments containing distinct intelligibility information on neural oscillations are not clear. Using scalp-recorded electroencephalography (EEG) data, we investigated the hypothesis that perceptual responses to different RMS-level-dependent speech segments would have distinct EEG characteristics derived from the power values at each frequency band and the relationship between acoustics and neural oscillations at different response time and spatial distribution. We analyzed the EEG power and synchronized neural oscillations corresponding to auditory temporal fluctuations when subjects listened to Mandarin sentences with only high-RMS-level segments and only middle-RMS-level segments preserved, respectively. The results showed significantly stronger EEG spectral power in the delta and theta bands for high-RMS-level stimuli compared with middle-RMS-level stimuli, indicating that the former carry more speech-parsing information at the syllabic level. Differences in neural synchronization were also found between the high- and middle-RMS-level stimuli, allowing for the derivation of intelligibility indices for cortical responses corresponding to different RMS-level segments. These findings suggest that both high- and middle-RMS-level segments drive delta and theta rhythms to track stimuli, and that neural oscillations employ different tracking patterns for these two segment types during auditory sentence processing. Moreover, they suggest that neural oscillations can serve as effective indices for the identification of reliable intelligibility factors in RMS-level-dependent stimuli.