title: Neural dynamics of variable-rate speech categorization.
abstract: What is the neural representation of a speech code as it evolves in time? A neural model simulates data concerning segregation and integration of phonetic percepts. Hearing two phonetically related stops in a VC-CV pair (V = vowel; C = consonant) requires 150 ms more closure time than hearing two phonetically different stops in a VC1-C2V pair. Closure time also varies with long-term stimulus rate. The model simulates rate-dependent category boundaries that emerge from feedback interactions between a working memory for short-term storage of phonetic items and a list categorization network for grouping sequences of items. The conscious speech code is a resonant wave. It emerges after bottom-up signals from the working memory select list chunks which read out top-down expectations that amplify and focus attention on consistent working memory items. In VC1-C2V pairs, resonance is reset by mismatch of C2 with the C1 expectation. In VC-CV pairs, resonance prolongs a repeated C.
authors.affiliation: Department of Cognitive and Neural Systems, Boston University, Massachusetts 02215, USA. steve@cns.bu.edu
authors.forename: S
authors.initials: S
authors.lastname: Grossberg
authors.forename: I
authors.initials: I
authors.lastname: Boardman
authors.forename: M
authors.initials: M
authors.lastname: Cohen
mesh_terms: D003198:Computer Simulation; D006801:Humans; D008568:Memory / Q000502:physiology*; D008960:Models, Psychological; D010700:Phonetics; D013060:Speech / Q000502:physiology*