Cortical processing of temporal modulations

Xiaoqin Wang, Thomas Lu, Li Liang

Research output: Contribution to journalArticlepeer-review


Temporal modulations are fundamental components of human speech and animal communication sounds. Understanding their representations in the auditory cortex is a crucial step towards our understanding of brain mechanisms underlying speech processing. While modulated signals have long been used as experimental stimuli, their cortical representations are not completely understood, particularly for rapid modulations. Known physiological data do not adequately explain psychophysical observations on the perception of rapid modulations, largely due to slow stimulus-synchronized temporal discharge patterns of cortical neurons. In this article, we summarize recent findings from our laboratory on temporal processing mechanisms in the auditory cortex. These findings show that the auditory cortex represents slow modulations explicitly using a temporal code and fast modulations implicitly by a discharge rate code. Rapidly modulated signals within a short-time window (∼ 20-30 ms) are integrated and transformed into a discharge rate-based representation. The findings also indicate that there is a shared representation of temporal modulations by cortical neurons that encodes the temporal profile embedded in complex sounds of various spectral contents. Our results suggest that cortical processing of sound streams operates on a "segment-by-segment" basis with a temporal integration window on the order of ∼ 20-30 ms.

Original languageEnglish (US)
Pages (from-to)107-121
Number of pages15
JournalSpeech Communication
Issue number1
StatePublished - Aug 2003


  • Amplitude modulation
  • Auditory cortex
  • Frequency modulation
  • Species-specific vocalization
  • Temporal asymmetry
  • Temporal integration
  • Temporal processing

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Communication
  • Language and Linguistics
  • Linguistics and Language
  • Computer Vision and Pattern Recognition
  • Computer Science Applications


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