Modeling variability in cortical representations of human complex sound perception

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


This study investigated methodological (task, stimulus) and intersubject variability in the cortical representation of auditory processing of complex sounds, including speech. Subjects were adult seizure patients undergoing left hemisphere electrocortical mapping (ECM). We tested auditory discrimination of complex sounds, including frequency-modulated tones and speech syllables (digitized, synthesized) contrasted by phonetic features and lexical status. To measure task effects, auditory comprehension was also tested. Within- and across-patient differences in the distribution of deficits induced by ECM were modeled statistically using the recently developed method of Template Mixture Modeling. Cortical representations of auditory discrimination were smaller, more localized, and less variable across subjects than auditory comprehension. Stimulus effects were observed only for speech-tone contrasts. When tasks and stimuli were held constant, two auditory discrimination centers were identified in the posterior temporal lobe. There was also an interaction between task and intersubject effects, with more intersubject variability in cortical maps of auditory comprehension than auditory discrimination. These results demonstrate the utility of using the statistical modeling approach of Template Mixture Modeling to quantify sources of variability in cortical functional organization.

Original languageEnglish (US)
Pages (from-to)382-387
Number of pages6
JournalExperimental Brain Research
Issue number3
StatePublished - Dec 2003
Externally publishedYes


  • Brain mapping
  • Electrocortical mapping
  • Speech perception
  • Statistical modeling
  • Template mixture modeling

ASJC Scopus subject areas

  • Neuroscience(all)


Dive into the research topics of 'Modeling variability in cortical representations of human complex sound perception'. Together they form a unique fingerprint.

Cite this