? PROJECT 4 A major issue in hearing loss is variability. Hearing impaired (HI) listeners with similar profiles often show different outcomes. Correlational studies show that signal quality (audibility, frequency separation) is related to outcomes. However, equally important are factors like device experience, cognition and brain function. It is unclear how these adaptations, cognitive resources, or brain areas improve perception. This project tackles this by leveraging mechanisms and measures from cognitive science that describe how sound is mapped to meaning, focusing on the issue of time. Since speech unfolds over time, there are ambiguous periods when the input is compatible with many words. For example, at the onset of butter, the signal could match bump, but and buck. Normal hearing (NH) listeners manage this ambiguity by immediately activating multiple words which compete dynamically over time. For HI listeners, this natural ambiguity may be more problematic and managed differently. We assess the dynamics of word recognition with an eye-tracking paradigm that traces how this competition unfolds over several hundred milliseconds. Prior work suggests cochlear implant (CI) users tune these dynamics differently than NH listeners; these differences are correlated with outcomes and may help cope with poor input. This project asks why these competition processes differ in HI listeners. Are such differences a poor version of typical language processing imposed by degraded input? Or are they a compensatory adaptation for coping with uncertainty? To answer this question in a way that translates to the real-world, Aim 1 moves beyond isolated words to examine sentences, where factors like semantics constrain this competition.
Aim 2 uses a longitudinal study to link differences in competition to peripheral auditory function (Project 2), listening effort (Project 1) and cortical processing (Project 3);
and Aim 3 complements this with laboratory studies of adaption.
Aim 4 examines how HI listeners fuse information from different types of input, for example, from aided acoustic hearing and a CI.
All aims leverage natural variation in multiple types of HI listeners (standard CIs, acoustic+electric CI configurations, and hearing aids) to investigate how differences in the peripheral input impact the mechanisms of language processing.
? PROJECT 4 We seek a better understanding of the cognitive mechanisms by which hearing impaired listeners (including cochlear implant and hearing aid users) map the auditory signal to meaning, and how these mechanisms adapt to compensate for poor input. This will improve cochlear implantation criteria, outcome measures, post- remediation therapies, and signal processing strategies in cochlear implants and hearing aids.
|McMurray, Bob; Farris-Trimble, Ashley; Rigler, Hannah (2017) Waiting for lexical access: Cochlear implants or severely degraded input lead listeners to process speech less incrementally. Cognition 169:147-164|
|Tejani, Viral D; Abbas, Paul J; Brown, Carolyn J (2017) Relationship Between Peripheral and Psychophysical Measures of Amplitude Modulation Detection in Cochlear Implant Users. Ear Hear 38:e268-e284|
|Guo, Ling-Yu; Spencer, Linda J (2017) Development of Grammatical Accuracy in English-Speaking Children With Cochlear Implants: A Longitudinal Study. J Speech Lang Hear Res 60:1062-1075|
|Abbas, Paul J; Tejani, Viral D; Scheperle, Rachel A et al. (2017) Using Neural Response Telemetry to Monitor Physiological Responses to Acoustic Stimulation in Hybrid Cochlear Implant Users. Ear Hear 38:409-425|
|Shearer, A Eliot; Eppsteiner, Robert W; Frees, Kathy et al. (2017) Genetic variants in the peripheral auditory system significantly affect adult cochlear implant performance. Hear Res 348:138-142|
|Sjoberg, Kristin M; Driscoll, Virginia D; Gfeller, Kate et al. (2017) The impact of electric hearing on children's timbre and pitch perception and talker discrimination. Cochlear Implants Int 18:36-48|
|Samuelson, Larissa K; McMurray, Bob (2017) What does it take to learn a word? Wiley Interdiscip Rev Cogn Sci 8:|
|Oleson, Jacob J; Cavanaugh, Joseph E; McMurray, Bob et al. (2017) Detecting time-specific differences between temporal nonlinear curves: Analyzing data from the visual world paradigm. Stat Methods Med Res 26:2708-2725|
|Scheperle, Rachel A; Tejani, Viral D; Omtvedt, Julia K et al. (2017) Delayed changes in auditory status in cochlear implant users with preserved acoustic hearing. Hear Res 350:45-57|
|Brown, Carolyn J; Jeon, Eun-Kyung; Driscoll, Virginia et al. (2017) Effects of Long-Term Musical Training on Cortical Auditory Evoked Potentials. Ear Hear 38:e74-e84|
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