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  1. Billings CJ, Grush LD, Maamor N
    Physiol Rep, 2017 Nov;5(20).
    PMID: 29051305 DOI: 10.14814/phy2.13464
    The effects of background noise on speech-evoked cortical auditory evoked potentials (CAEPs) can provide insight into the physiology of the auditory system. The purpose of this study was to determine background noise effects on neural coding of different phonemes within a syllable. CAEPs were recorded from 15 young normal-hearing adults in response to speech signals /s/, /ɑ/, and /sɑ/. Signals were presented at varying signal-to-noise ratios (SNRs). The effects of SNR and context (in isolation or within syllable) were analyzed for both phonemes. For all three stimuli, latencies generally decreased and amplitudes generally increased as SNR improved, and context effects were not present; however, the amplitude of the /ɑ/ response was the exception, showing no SNR effect and a significant context effect. Differential coding of /s/ and /ɑ/ likely result from level and timing differences. Neural refractoriness may result in the lack of a robust SNR effect on amplitude in the syllable context. The stable amplitude across SNRs in response to the vowel in /sɑ/ suggests the combined effects of (1) acoustic characteristics of the syllable and noise at poor SNRs and (2) refractory effects resulting from phoneme timing at good SNRs. Results provide insights into the coding of multiple-onset speech syllables in varying levels of background noise and, together with behavioral measures, may help to improve our understanding of speech-perception-in-noise difficulties.
    Matched MeSH terms: Refractory Period, Electrophysiological*
  2. Zilany MS, Bruce IC, Carney LH
    J Acoust Soc Am, 2014 Jan;135(1):283-6.
    PMID: 24437768 DOI: 10.1121/1.4837815
    A phenomenological model of the auditory periphery in cats was previously developed by Zilany and colleagues [J. Acoust. Soc. Am. 126, 2390-2412 (2009)] to examine the detailed transformation of acoustic signals into the auditory-nerve representation. In this paper, a few issues arising from the responses of the previous version have been addressed. The parameters of the synapse model have been readjusted to better simulate reported physiological discharge rates at saturation for higher characteristic frequencies [Liberman, J. Acoust. Soc. Am. 63, 442-455 (1978)]. This modification also corrects the responses of higher-characteristic frequency (CF) model fibers to low-frequency tones that were erroneously much higher than the responses of low-CF model fibers in the previous version. In addition, an analytical method has been implemented to compute the mean discharge rate and variance from the model's synapse output that takes into account the effects of absolute refractoriness.
    Matched MeSH terms: Refractory Period, Electrophysiological
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