# Neural Dynamics Underlying the Emergence of Auditory Categorization and Learning

> **NIH NIH R01** · UNIVERSITY OF MEMPHIS · 2021 · $353,516

## Abstract

Project Summary
 Successful perception of the world requires that the human brain assemble diverse sensory information
into common, well-formed groupings, a process known as categorical perception (CP). At its core, CP is known
as the “invariance-” or “many-to-one mapping” problem: an infinite collection of sensory features must be
converted into a finite, invariant perceptual space to be acted upon by the perceptual system. Categorization
manifests in nearly all aspects of human cognition and learning including the perception of faces, colors, and
music. Skilled categorization is particularly important in the context of spoken and written language as evident
by its integral role in reading acquisition and auditory-based learning disorders (e.g., dyslexia, specific
language impairment). Despite a wealth of behavioral studies and its importance to understanding receptive
human communication, the neural mechanisms underlying the core ability of CP remain poorly understood. In
a series of studies, the proposed work will address foundational questions of when, where, and how the brain
converts continuous acoustic signals into discrete, meaningful categories exploited by the perceptual system.
High-density neuroelectric brain recordings (EEG/ERP) will be obtained from human listeners during tasks
designed to tap different attributes of categorical processing and modulate its neurobiology. Our central
hypothesis is that auditory categorization skills recruit a common, parsimonious frontotemporal neural network
that is both dynamically and differentially engaged depending on attention, familiarity of stimulus
context/complexity, learning, and prior listening experience. Novel multivariate analytic techniques will be used
to derive “neurometric functions” from listeners’ ERPs to “decode” listeners’ speech perception behaviors from
their underlying brain activity. This common neurocomputational approach will be used to investigate several
factors that modulate auditory categorization skills through five research aims: (Aim 1) the spatiotemporal
emergence of CP in the brain; (Aim 2) linear vs. nonlinear signal dynamics; (Aim 3) identifying sounds from
different domains (e.g., speech vs. music); (Aim 4) prior listening experience and novel learning. Aim 5 will
measure functional connectivity from EEG recordings to determine how the directed flow of information within
the CP brain network changes with the manipulations of prior aims (e.g., learning vs. processing mature
categories). Providing a more complete biological description of the acoustic-to-phonetic mapping problem of
CP will ultimately offer a window into not only normal speech perception but may reveal important neural
mechanisms to target in disorders that impair the formation of auditory categories.

## Key facts

- **NIH application ID:** 10129937
- **Project number:** 5R01DC016267-04
- **Recipient organization:** UNIVERSITY OF MEMPHIS
- **Principal Investigator:** Gavin M. Bidelman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $353,516
- **Award type:** 5
- **Project period:** 2018-05-16 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10129937

## Citation

> US National Institutes of Health, RePORTER application 10129937, Neural Dynamics Underlying the Emergence of Auditory Categorization and Learning (5R01DC016267-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10129937. Licensed CC0.

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