Discrimination of Voiced Stop Consonants Based on Auditory Nerve Discharges

Sharba Bandyopadhyay, Eric D. Young

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Previous studies of the neural representation of speech assumed some form of neural code, usually discharge rate or phase locking, for the representation. In the present study, responses to five synthesized CVC_CV (e.g., /dad_da/) utterances have been examined using information-theoretic distance measures [or Kullback-Leibler (KL) distance] that are independent of a priori assumptions about the neural code. The consonants in the stimuli fall along a continuum from /b/ to /d/ and include both formant-frequency (F1, F2, and F3) transitions and onset (release) bursts. Differences in responses to pairs of stimuli, based on single-fiber auditory nerve responses at 70 and 50 dB sound pressure level, have been quantified, based on KL and KL-like distances, to show how each portion of the response contributes to information coding and the fidelity of the encoding. Distances were large at best frequencies, in which the formants differ but were largest for fibers encoding the high-frequency release bursts. Distances computed at differing time resolutions show significant information in the temporal pattern of spiking, beyond that encoded by rate, at time resolutions from 1-40 msec. Single-fiber just noticeable differences (JNDs) for F2 and F3 were computed from the data. These results show that F2 is coded with greater fidelity than F3, even among fibers tuned to F3, and that JNDs are larger in the syllable final consonant than in the releases.

Original languageEnglish (US)
Pages (from-to)531-541
Number of pages11
JournalJournal of Neuroscience
Volume24
Issue number2
DOIs
StatePublished - Jan 14 2004
Externally publishedYes

Keywords

  • Auditory nerve
  • Formant transitions
  • Information theory
  • JND
  • Kullback-Leibler distance
  • Neural discrimination
  • Release burst
  • Stop consonant

ASJC Scopus subject areas

  • General Neuroscience

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