Neural correlates and functional benefits of continuous vs. categorical listening

About This Grant

Project Summary/Abstract Successful speech perception requires that listeners map continuous changes in the acoustic signal into discrete phonetic units (categorize) while “tuning out” background noise. Listeners could use two opposing listening strategies to accomplish these tasks: a gradient/continuous strategy that linearly maps acoustics to perception and retains all signal details or a categorical/discrete strategy that warps acoustics into phonetic categories and discards perceptually irrelevant features. Theoretically, either strategy could benefit speech-in-noise (SIN) perception: gradient listening could offer flexibility for optimal cue-weighting in noise, whereas abstract phonetic categories formed by discrete listening could be more resilient to degradation. Combining behavioral tasks designed to evaluate listening strategy (phoneme labeling) with temporally sensitive electrophysiological measures (EEG) of brainstem and cortical function, this project will evaluate how the brain’s encoding of speech reflects gradient vs. discrete modes of hearing at the individual level, and in turn, might predict SIN abilities. Our innovative EEG paradigms include the simultaneous recording of frequency-following responses (FFRs) and event-related potentials (ERPs) to assess how different levels of the auditory system (brainstem + cortex) scale with perceptual abilities and reflect listening strategy between (Aim 1) and within (Aim 2) individuals. Our central hypothesis is that listening strategy is directly related to figure-ground perception and may account for substantial unrecognized variation in SIN outcomes, providing a fresh mechanistic view of degraded speech perception. The proposed predoctoral work will be pursued in a highly productive and interdisciplinary research environment at Indiana University in the Auditory Cognitive Neuroscience Lab (ACNL) under the primary mentorship of Dr. Gavin Bidelman. The ACNL specializes in auditory/speech perception, neurophysiology (brainstem and cortical EEG), and computational modeling. This environment is well-suited to the PI’s goals for training in brain imaging, advanced computational and statistical analysis of multichannel EEG data, and professional and career development. Primary training in human neuroimaging and auditory neuroscience will be complemented by interdisciplinary training in behavior and speech perception with Co-Sponsor Dr. Tessa Bent, a leading expert on indexical and cognitive factors in speech and individual differences in speech perception. In addition to these research experiences, the fellowship training plan includes opportunities for career development, incorporating milestones in scientific dissemination (conference presentations, publications), seminars and workshops in professional development (e.g., grantsmanship), and formal coursework to support the PI’s training in theoretical and empirical issues in auditory cognitive neuroscience. Collectively, this F31 will provide the PI with crucial tools and experience to propel her into a successful career in auditory neuroscience and becoming a tenure-track academic researcher.