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Compression and amplification algorithms in hearing aids impair the selectivity of neural responses to speech

Nature Biomedical Engineering volume 6, pages 717–730 (2022)Cite this article

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A Publisher Correction to this article was published on 05 January 2022

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Abstract

In quiet environments, hearing aids improve the perception of low-intensity sounds. However, for high-intensity sounds in background noise, the aids often fail to provide a benefit to the wearer. Here, using large-scale single-neuron recordings from hearing-impaired gerbils—an established animal model of human hearing—we show that hearing aids restore the sensitivity of neural responses to speech, but not their selectivity. Rather than reflecting a deficit in supra-threshold auditory processing, the low selectivity is a consequence of hearing-aid compression (which decreases the spectral and temporal contrasts of incoming sound) and amplification (which distorts neural responses, regardless of whether hearing is impaired). Processing strategies that avoid the trade-off between neural sensitivity and selectivity should improve the performance of hearing aids.

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Fig. 1: Large-scale recordings of neural activity from the IC with normal hearing and mild-to-moderate hearing loss.
Fig. 2: Single-trial responses to speech can be classified with high accuracy.
Fig. 3: Hearing aids restore speech audibility but not consonant identification.
Fig. 4: Hearing aids fail to restore the selectivity of neural responses to speech.
Fig. 5: Hearing aids restore the selectivity of neural responses to tones.
Fig. 6: Hearing aid compression decreases the selectivity of neural responses to speech.
Fig. 7: Amplification decreases consonant identification even with normal hearing.

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Data availability

Recordings of consonant–vowel syllables are available from the Linguistic Data Consortium (catalogue number: LDC2015S12). Recordings of continuous speech are available from the UCL Scribe database (https://www.phon.ucl.ac.uk/resource/scribe). The database of neural recordings that were analysed in this study is too large to be publicly shared, but is available from the corresponding author on reasonable request.

Code availability

The custom MATLAB code used in this study is available at GitHub (https://github.com/nicklesica/neuro).

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Acknowledgements

We thank J. Linden, S. Rosen, D. Fitzpatrick, B. Moore, J. Alexander, M. Huckvale, K. Harris, G. Huang, T. Keck and R. Beutelmann for their advice. This work was supported by a Wellcome Trust Senior Research Fellowship (200942/Z/16/Z).

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  1. These authors contributed equally: Alex G. Armstrong, Chi Chung Lam, Shievanie Sabesan.

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  1. Ear Institute, University College London, London, UK

    Alex G. Armstrong, Chi Chung Lam, Shievanie Sabesan & Nicholas A. Lesica

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Contributions

N.A.L. and C.C.L. conceived and designed the experiments. N.A.L., C.C.L., A.G.A. and S.S. performed the experiments. N.A.L. analysed the data and wrote the paper.

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Correspondence to Nicholas A. Lesica.

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Competing interests

N.A.L. is a co-founder of Perceptual Technologies Ltd. A.G.A., C.C.L. and S.S. declare no competing interests.

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Armstrong, A.G., Lam, C.C., Sabesan, S. et al. Compression and amplification algorithms in hearing aids impair the selectivity of neural responses to speech. Nat. Biomed. Eng 6, 717–730 (2022). https://doi.org/10.1038/s41551-021-00707-y

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