Speech-in-noise intelligibility difficulties with age: the role of cochlear synaptopathy

2020 
Damage to auditory-nerve-fiber synapses (i.e. cochlear synaptopathy) degrades the neural coding of sound and is predicted to impair sound perception in noisy listening environments. However, establishing a causal relationship between synaptopathy and speech intelligibility is difficult because we have no direct access to synapse counts in humans. Hence, we rely on the quality of noninvasive auditory-evoked potential (AEP) markers developed in rodent studies of histologically-verified synaptopathy. However, there are a number of reasons which render the interpretation of these markers in humans difficult. To bridge this translational gap, we apply a multi-method approach to enable a meaningful interpretation of the relationship between the histopathology of sensorineural hearing loss (SNHL) and speech perception. We first selected a synaptopathy-sensitive AEP marker and verified its sensitivity (i) in an animal model using a Kainic-acid induced synaptopathy, and (ii), via auditory model simulations which connect the histopathology of SNHL to the source generators of AEPs. Secondly, we restricted the frequency content of the speech-material to ensure that both AEP and speech metrics targeted similar cochlear frequency regions and associated auditory coding mechanisms. Following this approach, we studied the relative contribution of AEP markers of synaptopathy and hearing sensitivity to speech recognition thresholds in 44 listeners (24 women) of different ages and SNHL profiles. Our analysis shows that synaptopathy plays an important role for speech intelligibility in noise, but that outer-hair-cell integrity predicts performance in the absence of noise. Our results corroborate conclusions from animal studies regarding the prevalence of age-related synaptopathy, and its occurrence before outer-hair-cell loss damage.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    109
    References
    2
    Citations
    NaN
    KQI
    []