Auditory grouping ability predicts speech-in-noise performance in cochlear implants

Objectives Cochlear implant (CI) users exhibit a large variance in understanding speech in noise (SiN). Past works in CI users found that spectral and temporal resolutions correlate with the SiN ability, but a large portion of variance has been remaining unexplained. Our group’s recent work on normal-hearing listeners showed that the ability of grouping temporally coherent tones in a complex auditory scene predicts SiN ability, highlighting a central mechanism of auditory scene analysis that contributes to SiN. The current study examined whether the auditory grouping ability contributes to SiN understanding in CI users as well. Design 47 post-lingually deafened CI users performed multiple tasks including sentence-in-noise understanding, spectral ripple discrimination, temporal modulation detection, and stochastic figure-ground task in which listeners detect temporally coherent tone pips in the cloud of many tone pips that rise at random times at random frequencies. Accuracies from the latter three tasks were used as predictor variables while the sentence-in-noise performance was used as the dependent variable in a multiple linear regression analysis. Results No co-linearity was found between any predictor variables. All the three predictors exhibited significant contribution in the multiple linear regression model, indicating that the ability to detect temporal coherence in a complex auditory scene explains a further amount of variance in CI users’ SiN performance that was not explained by spectral and temporal resolution. Conclusions This result indicates that the across-frequency comparison builds an important auditory cognitive mechanism in CI users’ SiN understanding. Clinically, this result proposes a novel paradigm to reveal a source of SiN difficulty in CI users and a potential rehabilitative strategy.