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.
The ability to properly categorize sounds into meaningful groupings is a core precursor to spoken and written language acquisition that is often impaired in auditory-based learning disorders (e.g., dyslexia). By recording neural signals via the human EEG, the proposed work will fill important knowledge gaps by addressing foundational questions of when, where, and how the brain converts acoustic signals into discrete categorical groupings exploited by our perceptual system and factors which modulate this ability (e.g., context, learning). Knowledge gained by the proposed studies will provide a detailed account of the neural mechanisms that support auditory categorization abilities in speech perception, and in turn, may guide future efforts to determine where/when these perceptual skills breakdown in communication disorders.
| Mankel, Kelsey; Bidelman, Gavin M (2018) Inherent auditory skills rather than formal music training shape the neural encoding of speech. Proc Natl Acad Sci U S A 115:13129-13134 |
| Bidelman, Gavin M; Davis, Mary Katherine; Pridgen, Megan H (2018) Brainstem-cortical functional connectivity for speech is differentially challenged by noise and reverberation. Hear Res 367:149-160 |
