Project Summary/Abstract
Robust perception requires listeners organize incoming stimuli into meaningful perceptual groups to make
sense of their environment. This many-to-one mapping problem is known as categorical perception (CP).
Surprisingly, despite decades of behavioral research, when and where categorization occurs in the brain and
how categories are shaped by experience (e.g., learning) are not well understood. By combining temporally
sensitive EEG measurements with state-of-the-art source analysis and functional connectivity techniques, this
project will characterize the neural correlates of successful category learning (Aim 1) during short-term
auditory identification training. We then evaluate neural differences within the brain’s auditory-linguistic
pathways that distinguish good vs. poor learners (Aim 2), testing bottom-up vs. top-down predictions of the
reverse hierarchy theory (RHT). Analyses will identify different “neural strategies” that illustrate individual
differences in learning performance and determine whether stronger feedforward or feedback cortical
processing leads to more successful categorization after training. Understanding the unique neural
mechanisms supporting sound categorization and auditory learning may help individualize future rehabilitative
or personalized training programs (e.g., second language learning), thereby maximizing therapeutic and/or
educational benefits for receptive hearing abilities.
The proposed predoctoral work will be conducted in a highly productive and interdisciplinary training
environment at the University of Memphis that is well-suited to support the PI in achieving the training plan
goals. Under the guidance of Dr. Gavin Bidelman, the research will be primarily conducted in the Auditory
Cognitive Neuroscience Laboratory (ACNL), which specializes in auditory perception-cognition,
neurophysiology (via multichannel EEG/ERP analysis), speech/music perception, and computational modeling.
To achieve the research objectives, this F31 includes training in advanced source analysis and functional
connectivity techniques via dedicated one-on-one mentorship with the faculty Sponsor. Primary training in
human neuroimaging and speech-hearing science will be complemented by interdisciplinary training in
cognitive psychology and modeling of behavioral learning data with Co-Sponsor Dr. Philip Pavlik, a leading
expert on knowledge acquisition and the dynamics of human learning. 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 and the speech-hearing sciences. This
fellowship will provide the PI invaluable scientific training, mentorship, and professional development that will
ultimately help launch her career toward becoming a tenure-track academic researcher.