Document Type

Dissertation

Date of Award

5-31-2021

Degree Name

Doctor of Philosophy in Biomedical Engineering - (Ph.D.)

Department

Biomedical Engineering

First Advisor

Antje Ihlefeld

Second Advisor

Sergei Adamovich

Third Advisor

Tara L. Alvarez

Fourth Advisor

Carrie Esopenko

Fifth Advisor

Jorge M. Serrador

Abstract

Resolving complicated auditory scenes is crucial for daily communication where background sound is often present. However, most hearing aid (HA) and cochlear implant (CI) users have difficulties understanding speech when competing sound sources are present, resulting in reduced job opportunities and increased risk for social isolation. Perceptual interference from background sound is called auditory masking. At least two distinct masking phenomena exist, called energetic and informational masking (EM and IM).

In the first masking phenomenon, EM, target and masker energies coincide at the same time and frequency. Computational and physiological models of cochlear auditory processing can reliably predict listeners' performances in EM situations, demonstrating that EM is primarily caused by peripheral processes. Therefore, even ideal HA or CI device could not restore information that is energetically masked at the cochlea. In contrast, the second masking phenomenon, informational masking (IM), occurs when target-like sound is in the background, even when cochlear models do not predict much interference. Because IM is thought to arise from central interference downstream from the cochlea, HA or CI devices could be designed to overcome IM. However, the mechanisms underlying IM are currently not understood. Tools that objectively predict and compensate for an individual's susceptibility to IM do not currently exist in clinical practice. Thus, there is a timely need to elucidate the mechanisms underlying IM and to develop safe, quiet and inexpensive brain imaging tools that could guide the fitting of HA and CI devices.

In this dissertation, psychometrical testing is combined with functional near-infrared spectroscopy (fNIRS) as a brain imaging tool to objectively measure the listeners' susceptibility to IM. Chapter 1 reviews the literature. Using psychometric testing, Chapter 2 then demonstrates that susceptibility to IM negatively correlates with susceptibility to crowding in vision, a superficially similar and better-understood phenomenon. Domain-general selective attention, motivation, effort, or vigilance would have predicted a positive association between the two phenomena. Thus, Chapter 2 demonstrates that additional central processing must underly IM. In search for neural correlates of IM mechanisms, three fNIRS experiments are then conducted. Chapter 3, establishes fNIRS as a viable objective measure for sensing whether a normally hearing listener actively listens to an auditory scene vs. passively hears sound. Extending this method, Chapter 4 shows that listening with IM interference causes auditory-task evoked hemodynamic responses near auditory regions in the lateral frontal cortex and superior temporal gyrus, bilaterally. However, only the hemodynamic responses near the superior temporal gyrus predict individuals' susceptibility to IM (R2 = 20-43%). Using machine learning techniques, Chapter 5 confirms robust test-retest reliability of the fNIRS protocols used in Chapters 3 and 4. Chapter 6 summarized and discusses the results of this dissertation.

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