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Song Feature Specific Analysis of Isolate Song Reveals Interspecific Variation in Learned Components.

Jay LoveAmanda HoepfnerFranz Goller
Published in: Developmental neurobiology (2019)
Studies of avian vocal development without exposure to conspecific song have been conducted in many passerine species, and the resultant isolate song is often interpreted to represent an expression of the genetic code for conspecific song. There is wide recognition that vocal learning exists in oscine songbirds, but vocal learning has only been thoroughly investigated in a few model species, resulting in a narrow view of birdsong learning. By extracting acoustic signals from published spectrograms, we have reexamined the findings of isolate studies with a universally applicable semi-automated quantitative analysis regimen. When song features were analyzed in light of three different production aspects (respiratory, syringeal, and central programming of sequence), all three show marked interspecific variability in how close isolate song features are to normal. This implies that song learning mechanisms are more variable than is commonly recognized. Our results suggest that the interspecific variation shows no readily observable pattern reflecting phylogeny, which has implications for understanding the mechanisms behind the evolution of avian vocal communication. We emphasize that song learning in passerines provides an excellent opportunity to investigate the evolution of a complex, plastic trait from a phylogenetic perspective.
Keyphrases
  • machine learning
  • deep learning
  • poor prognosis
  • randomized controlled trial
  • genome wide
  • gene expression
  • high resolution
  • high throughput
  • copy number
  • case control
  • respiratory tract