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Predicting Perception in Noise Using Cortical Auditory Evoked Potentials

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Abstract

Speech perception in background noise is a common challenge across individuals and health conditions (e.g., hearing impairment, aging, etc.). Both behavioral and physiological measures have been used to understand the important factors that contribute to perception-in-noise abilities. The addition of a physiological measure provides additional information about signal-in-noise encoding in the auditory system and may be useful in clarifying some of the variability in perception-in-noise abilities across individuals. Fifteen young normal-hearing individuals were tested using both electrophysiology and behavioral methods as a means to determine (1) the effects of signal-to-noise ratio (SNR) and signal level and (2) how well cortical auditory evoked potentials (CAEPs) can predict perception in noise. Three correlation/regression approaches were used to determine how well CAEPs predicted behavior. Main effects of SNR were found for both electrophysiology and speech perception measures, while signal level effects were found generally only for speech testing. These results demonstrate that when signals are presented in noise, sensitivity to SNR cues obscures any encoding of signal level cues. Electrophysiology and behavioral measures were strongly correlated. The best physiological predictors (e.g., latency, amplitude, and area of CAEP waves) of behavior (SNR at which 50 % of the sentence is understood) were N1 latency and N1 amplitude measures. In addition, behavior was best predicted by the 70-dB signal/5-dB SNR CAEP condition. It will be important in future studies to determine the relationship of electrophysiology and behavior in populations who experience difficulty understanding speech in noise such as those with hearing impairment or age-related deficits.

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Abbreviations

SPL:

Sound pressure level

HL:

Hearing level

dB:

Decibel

SNR:

Signal-to-noise ratio

CAEPs:

Cortical auditory evoked potentials

ANOVA:

Analysis of variance

LOOCV:

Leave-one-out cross-validation

PLS:

Partial least squares

RMSPE:

Root-mean-square prediction error

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Acknowledgments

We wish to thank Drs. Marjorie Leek, Robert Burkard, and Kelly Tremblay for the comments on the design of this experiment and earlier versions of this manuscript. This work was supported by a grant from the National Institute on Deafness and Other Communication Disorders (R03DC10914) and career development awards from the VA Rehabilitation Research and Development Service (C4844C and C8006W).

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Authors and Affiliations

  1. National Center for Rehabilitative Auditory Research, Portland VA Medical Center, 3710 SW U.S. Veterans Hospital Rd (NCRAR), Portland, OR, 97239, USA

    Curtis J. Billings, Garnett P. McMillan, Tina M. Penman & Sun Mi Gille

  2. Department of Otolaryngology, Oregon Health & Science University, Portland, OR, 97239, USA

    Curtis J. Billings

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  1. Curtis J. Billings
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  2. Garnett P. McMillan
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  3. Tina M. Penman
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  4. Sun Mi Gille
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Correspondence to Curtis J. Billings.

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Billings, C.J., McMillan, G.P., Penman, T.M. et al. Predicting Perception in Noise Using Cortical Auditory Evoked Potentials. JARO 14, 891–903 (2013). https://doi.org/10.1007/s10162-013-0415-y

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  • DOI: https://doi.org/10.1007/s10162-013-0415-y

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