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.
Learning to map sounds to meaning (categorize) is fundamental to speech and language acquisition, but what makes an individual successful in auditory learning is not well understood. By measuring neuroelectric signals via scalp-recorded electroencephalography (EEG) during training tasks, this research will assess where and when in the brain successful category learning occurs. These results will reveal how individual differences in neural function contribute to behavioral learning and may inform future brain-based interventions in educational, therapeutic, and/or rehabilitative applications.
