Meet the Researcher
Jacie R. McHaney, PhD., earned my doctorate from the University of Pittsburgh in Communication Sciences and Disorders, where she trained in auditory neuroscience. She is now an Assistant Professor at The University of Texas at Austin. McHaney is a recipient of a 2027 Elizabeth M. Keithley, Ph.D. Early Stage Investigator Award.
This project grew out of a question that emerged directly from my own prior research. In earlier work, my colleagues and I found that as people age, the brain’s representation of speech sounds becomes “fuzzier,” or less precise, even when listening in easy, quiet conditions. That finding led to an obvious next question to ask if there is anything we can do to sharpen those neural representations back up. Hearing aids seemed like a natural place to look. They are designed to restore audibility, but I wanted to know whether their specific signal-processing algorithms could also improve the clarity of speech encoding in the brain itself, not just make the sounds louder. This project tests whether certain hearing aid parameters sharpen cortical speech encoding, and whether sharpening relates to how well people actually understand speech and how good it sounds to them.
I was a first-generation college student, so truthfully I did not grasp that a career as a scientist, or even helping with research in college was possible. I had a professor in college encourage the class to get involved with research and how it could lead to an eventual Ph.D. and a career. I never imagined that this path was a possibility for me. I had really incredible mentors in college and grad school, whom without, I would not be where I am today. The rest is history! That experience really shapes how I approach mentoring and teaching the next generation of scientists.
Early in my research career, I assisted with a large study on speech perception in noise challenges in older adults, which really sparked my interest in hearing loss and age-related changes. I was really moved by the participants’ desires to learn what they could do to improve their communication for daily tasks as simple as hearing their grandchildren talk. Ever since, my research has focused on speech perception challenges and the impacts of hearing loss, aging, and cognition.
If I had not become a researcher, I likely would have pursued medical school, but as a kid, I was set on becoming an FBI agent! In my spare time, I love to be outdoors. I’ll often set up my laptop on a patio and work outside for the day. If I’m not working outside, I’m doing other kinds of “work” outside, like gardening, landscaping, hiking, skiing, camping, etc. I am always amazed at the silence of the outdoors compared with the bustling cities, which reminds me how loud our environments can be on a daily basis. I have two small children at home—a 1-year-old and a kindergartener. It’s been so fun observing my children learn about their world through sound!
Right now, I am just getting started building my research lab at The University of Texas at Austin. Over the next five to 10 years, I hope to have a fully developed lab studying the neural mechanisms speech processing and to have begun translating our research findings into the clinic to work with real patients on their listening outcomes.
The Research
The University of Texas at Austin
Neural and cognitive mechanisms of hearing aid signal processing
Millions of adults with hearing loss rely on hearing aids, yet many still struggle to follow conversations, especially in noisy, everyday settings. Even when a hearing aid makes sounds loud enough to hear, understanding speech clearly is a different challenge. This often means extra mental effort just to keep up, along with sound that doesn't feel quite right. Current methods for testing hearing aid fit and satisfaction mostly ask, “Can you hear this?” or “Can you repeat this word?” These methods do not show what is happening in the brain as it processes speech through a hearing aid’s processing. This research project aims to close that gap. We will study how a hearing aid’s internal processing affects the brain’s ability to recognize individual speech sounds (i.e., phonemes) in real time. We will use electroencephalography (EEG) to track brain responses while people listen to naturalistic speech through different hearing aid processing parameters. Additionally, we will measure pupil sizes during listening, which subtly changes based on how hard someone has to focus on listening, providing a window into listening effort. Participants will also report how well they understood the speech and their perceived quality of the speech. By testing different hearing aid processing settings in a controlled environment, we can examine which processing parameters help the brain encode speech clearly, which ones ease listening effort, and which do both. The findings from this study could reveal specific, measurable brain and effort signals that explain why some hearing aid settings work better than others, rather than solely depending on yes-or-no hearing tests. These insights could guide the design of “smarter” hearing aids that don’t just make sound louder, but also make listening easier and communication clearer for millions of people.
Long-term goal of research: This project aims to change how hearing aids are fitted. Current approaches mostly test whether sounds are loud enough to hear. As a result, many individuals with hearing loss continue to experience listening fatigue, poor sound quality, and suboptimal benefit from amplification. This research works toward fittings guided by what’s actually happening at the neural level to determine how clearly speech sounds are processed, and how much effort listening takes, so hearing aids can be tuned to how people experience sound, not just whether they can detect it. In the future, this could give clinicians new tools to complement standard hearing tests that can help fine-tune hearing aids for each person's brain and listening needs. This could mean less listening fatigue, better sound quality, and hearing aids that optimize for real-world settings.