Human cortical encoding of pitch in tonal and non-tonal languages.

Journal: Nature communications
Published Date: Feb 19, 2021

Abstract

Languages can use a common repertoire of vocal sounds to signify distinct meanings. In tonal languages, such as Mandarin Chinese, pitch contours of syllables distinguish one word from another, whereas in non-tonal languages, such as English, pitch is used to convey intonation. The neural computations underlying language specialization in speech perception are unknown. Here, we use a cross-linguistic approach to address this. Native Mandarin- and English- speaking participants each listened to both Mandarin and English speech, while neural activity was directly recorded from the non-primary auditory cortex. Both groups show language-general coding of speaker-invariant pitch at the single electrode level. At the electrode population level, we find language-specific distribution of cortical tuning parameters in Mandarin speakers only, with enhanced sensitivity to Mandarin tone categories. Our results show that speech perception relies upon a shared cortical auditory feature processing mechanism, which may be tuned to the statistics of a given language.

Authors

  • Yuanning Li
    Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, USA; Program in Neural Computation, Carnegie Mellon University and University of Pittsburgh, USA; Department of Neurological Surgery, University of Pittsburgh, USA. Electronic address: ynli@cmu.edu.
  • Claire Tang
    Department of Neurological Surgery, University of California, San Francisco, CA, USA.
  • Junfeng Lu
    Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.
  • Jinsong Wu
    Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.
  • Edward F Chang
    Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA. Electronic address: edward.chang@ucsf.edu.

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