This project will establish how attention influences physiological responses from the inner ear (i.e., cochlea) when listening to speech in noisy backgrounds. Human participants will actively listen to speech from a target talker while ignoring the speech from talkers who serve as distractors. Inner ear responses will be obtained using a custom-made sensor while participants complete the listening task. We hypothesize that inner ear responses will be larger for the target speech compared to the distracting speech, consistent with attention-driven control of the cochlea. Results from this study will improve our understanding of how humans are able to understand speech in noisy backgrounds and provide directions for improving this ability in adults with hearing loss.
Student research assistants will participate in the design, execution, analysis, and publication of research. Primarily responsibilities will include running and documenting data collection sessions, summarizing data collected in tables and figures, summarizing research findings in reports written to the lab manager, and reviewing/discussing pertinent literature on the project. Data collection for evoked potentials experiments will involve measuring electrical potentials from the brain and the cochlea in human participants via passive electrodes placed on the high-forehead and eardrum. Data collection for perceptual experiments will involve working with a customized graphical user interface in Matlab to quantify the sensitivity of human participants to specific features of sound.
Student Learning Outcomes and Benefits
At the completion of this research experience, the student will:
- understand neural mechanisms underlying auditory perception
- understand the anatomy and physiology of auditory reflexes
- understand principles of auditory evoked responses
- understand how to measure and quantify auditory perception
- master techniques for measuring auditory evoked potentials
- masker techniques for measuring auditory perception
- gain or improve on a working knowledge of Matlab programming
- gain or improve on the analysis of electrical and acoustic signals in time and frequency domains
- deepen skills on critically evaluating research
The long-term goal of my research is to understand how the auditory system and brain process sound in noisy backgrounds to achieve robust speech understanding. My current projects center on the hypothesis that efferent feedback automatically calibrates the auditory system to the ever-changing acoustic soundscape. This hypothesis predicts that individuals with cochlear hearing impairment suffer from an inability to adapt to new acoustic environments, since loss of outer hair cell (OHC) function is expected to negatively influence an important efferent subsystem called the medial olivocochlear (MOC) reflex. Despite physiological evidence linking MOC activity to improved signal-to-noise ratios, behavioral studies in humans have yet to provide compelling results to support this claim. This lack of evidence provides the impetus for my recent research interests and activities.
My teaching philosophy is summarized in three statements: 1) be a chef, not a cook!, 2) understand the graphs, and 3) rise to the challenge.
Be a chef, not a cook!: I found the major difference between student "chefs" and "cooks" is the ability to master concepts rather than master facts. I teach concepts in hearing science by packaging them into a model or framework. I introduce and develop these models through examples, figures, drawings, formulas, and succinct summary statements.
Understand the graphs: Data is at the heart of the concepts and models in hearing science. Analyzing a graph is an essential skill for learning new ideas and refining the models and frameworks that drive research.
Rise to the challenge: I believe the rigor and quality of education is substantially increased when instructors facilitate in-depth learning and "raise the bar" on academic performance in these areas. My experience is that students will rise to the instructor's expectations if the appropriate support structure is in place. I challenge students with advanced topics in acoustic impedance, signals and systems, Fourier analysis, cochlear physiology, models of the auditory periphery, and psychophysical models of auditory perception. I support students with these challenges by carefully designing assignments, being responsive to email and face-to-face communication, and facilitating interaction with other research assistants. Students in my lab benefit from mentoring activities such as guided literature reviews, impromptu whiteboard discussions, mini-teaching/discussion sessions during lab meetings, and brainstorming sessions about research and how to improve the lab where students are full and valued participants.