Article
Cortical temporal mismatch compensation in bimodal cochlear implant users: Selective attention decoding and pupillometry study
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Authors
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Hanna Dolhopiatenko
- Medizinische Hochschule Hannover, Hannover, Deutschland
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Waldo Nogueira
- Medizinische Hochschule Hannover, Hannover, Deutschland
| Published: | March 18, 2025 |
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Outline
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Bimodal cochlear implant (CI) users combine electrical stimulation from a cochlear implant in one ear with acoustic stimulation through either normal hearing or a hearing aid in the opposite ear. While this bimodal stimulation typically improves speech perception, the degree of improvement varies significantly and can sometimes result in interference effects. This variability is associated with the integration of electric and acoustic signals, which can be influenced by several factors, including temporal mismatch between the two sides.
In previous work, we utilized cortical auditory evoked potentials (CAEPs) to estimate temporal mismatch between the CI and acoustic side (AS), based on differences in N1 latencies when listening with the CI alone and the AS alone (Dolhopiatenko et al., 2023). Building on this approach, the present study estimates temporal mismatch and investigates the impact of compensating for this mismatch on speech perception.
In addition to traditional behavioral measures of speech understanding, this study employs selective attention decoding, which has been shown to be feasible in bimodal CI users despite the presence of electrical artifacts from the CI (Dolhopiatenko and Nogueira, 2023). Unlike behavioral performance, selective attention decoding reflects not only speech intelligibility but also the allocation of cognitive resources to segregate speech streams such as attentional listening. Therefore, it may provide a more sensitive measure of the effects of temporal mismatch. Moreover, this study explores whether temporal mismatch compensation reduces listening effort, which is assessed via pupillometry. Changes in pupil dilation serve as an indicator of cognitive load during listening tasks.
This study underscores the utility of CAEPs in estimating temporal mismatch in bimodal CI users and demonstrates that compensating for this mismatch influences speech perception, as reflected by selective attention decoding and pupillometry, although no significant effect was observed in behavioral speech understanding.
