Electrophysiology and Perception of Speech in Noise in Older Listeners: Effects of Hearing Impairment and Age. Issue 6 (November 2015)

• Record Type: Journal Article
• Authors: Billings, Curtis J.; Penman, Tina M.; McMillan, Garnett P.; Ellis, Emily M.
• Is Part Of: Ear and hearing. Volume 36:Issue 6(2015:Nov./Dec.)
• Publication Date: 2015-11
• Subjects: Background noise -- Cortical auditory evoked potentials -- Event-related potentials -- N1 -- Perception in noise -- Prediction -- Psychometric function -- Signals in noise -- Signal-to-noise ratio; Hearing disorders -- Periodicals; Audiology -- Periodicals; 612.85
• DOI: 10.1097/AUD.0000000000000191
• Languages: English
• ISSNs: 0196-0202

Abstract

Abstract : Objectives: Speech perception in background noise is difficult for many individuals, and there is considerable performance variability across listeners. The combination of physiological and behavioral measures may help to understand sources of this variability for individuals and groups and prove useful clinically with hard-to-test populations. The purpose of this study was threefold: (1) determine the effect of signal-to-noise ratio (SNR) and signal level on cortical auditory evoked potentials (CAEPs) and sentence-level perception in older normal-hearing (ONH) and older hearing-impaired (OHI) individuals, (2) determine the effects of hearing impairment and age on CAEPs and perception, and (3) explore how well CAEPs correlate with and predict speech perception in noise. Design: Two groups of older participants (15 ONH and 15 OHI) were tested using speech-in-noise stimuli to measure CAEPs and sentence-level perception of speech. The syllable /ba/, used to evoke CAEPs, and sentences were presented in speech-spectrum background noise at four signal levels (50, 60, 70, and 80 dB SPL) and up to seven SNRs (−10, −5, 0, 5, 15, 25, and 35 dB). These data were compared between groups to reveal the hearing impairment effect and then combined with previously published data for 15 young normal-hearing individuals to determine the aging effect. Results: Robust effects of SNR were found for perception and CAEPs. Small but significant effects of signal level were found for perception, primarily at poor SNRs and high signal levels, and in some limited instances for CAEPs. Significant effects of age were seen for both CAEPs and perception, while hearing impairment effects were only found with perception measures. CAEPs correlate well with perception and can predict SNR50s to within 2 dB for ONH. However, prediction error is much larger for OHI and varies widely (from 6 to 12 dB) depending on the model that was used for prediction. Conclusions: When background noise is present, SNR dominates both perception-in-noise testing and cortical electrophysiological testing, with smaller and sometimes significant contributions from signal level. A mismatch between behavioral and electrophysiological results was found (hearing impairment effects were primarily only seen for behavioral data), illustrating the possible contributions of higher order cognitive processes on behavior. It is interesting that the hearing impairment effect size was more than five times larger than the aging effect size for CAEPs and perception. Sentence-level perception can be predicted well in normal-hearing individuals; however, additional research is needed to explore improved prediction methods for older individuals with hearing impairment. Abstract : Understanding speech in background noise is especially difficult for older individuals and individuals with hearing loss. Both electrophysiological and behavioral measures were used to understand the contribution of signal-to-noise ratio (SNR), signal level, aging, and hearing impairment to electrophysiology and perception in noise. In addition, we explored the correlation strength and prediction accuracy between electrophysiology and behavior. It was found that SNR dominates responses. Hearing impairment effect sizes are many times larger than aging effect sizes. Electrophysiology correlates well with behavior and could be used to predict behavior in certain populations.Supplemental Digital Content is available in the text.