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

Alex G ArmstrongChi Chung LamShievanie SabesanNicholas A Lesica
Published in: Nature biomedical engineering (2021)
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.
Keyphrases
  • hearing loss
  • high intensity
  • antiretroviral therapy
  • machine learning
  • computed tomography
  • deep learning
  • resistance training
  • magnetic resonance imaging
  • air pollution
  • working memory
  • structural basis