A Hierarchy of Autonomous Systems for Vocal Production

Yisi S. Zhang, Asif A. Ghazanfar

Research output: Contribution to journalReview articlepeer-review

31 Scopus citations


Vocal production is hierarchical in the time domain. These hierarchies build upon biomechanical and neural dynamics across various timescales. We review studies in marmoset monkeys, songbirds, and other vertebrates. To organize these data in an accessible and across-species framework, we interpret the different timescales of vocal production as belonging to different levels of an autonomous systems hierarchy. The first level accounts for vocal acoustics produced on short timescales; subsequent levels account for longer timescales of vocal output. The hierarchy of autonomous systems that we put forth accounts for vocal patterning, sequence generation, dyadic interactions, and context dependence by sequentially incorporating central pattern generators, intrinsic drives, and sensory signals from the environment. We then show the framework's utility by providing an integrative explanation of infant vocal production learning in which social feedback modulates infant vocal acoustics through the tuning of a drive signal.

Original languageEnglish (US)
Pages (from-to)115-126
Number of pages12
JournalTrends in Neurosciences
Issue number2
StatePublished - Feb 2020

All Science Journal Classification (ASJC) codes

  • General Neuroscience


  • Mayer wave
  • biomechanics
  • birdsong
  • dynamical system
  • marmoset monkey
  • parental feedback
  • slow oscillations
  • social reinforcement
  • timescales
  • vocalizations


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