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Superfast Vocal Muscles Control Song Production in Songbirds

Overview of attention for article published in PLOS ONE, July 2008
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Title
Superfast Vocal Muscles Control Song Production in Songbirds
Published in
PLOS ONE, July 2008
DOI 10.1371/journal.pone.0002581
Pubmed ID
Authors

Coen P. H. Elemans, Andrew F. Mead, Lawrence C. Rome, Franz Goller

Abstract

Birdsong is a widely used model for vocal learning and human speech, which exhibits high temporal and acoustic diversity. Rapid acoustic modulations are thought to arise from the vocal organ, the syrinx, by passive interactions between the two independent sound generators or intrinsic nonlinear dynamics of sound generating structures. Additionally, direct neuromuscular control could produce such rapid and precisely timed acoustic features if syringeal muscles exhibit rare superfast muscle contractile kinetics. However, no direct evidence exists that avian vocal muscles can produce modulations at such high rates. Here, we show that 1) syringeal muscles are active in phase with sound modulations during song over 200 Hz, 2) direct stimulation of the muscles in situ produces sound modulations at the frequency observed during singing, and that 3) syringeal muscles produce mechanical work at the required frequencies and up to 250 Hz in vitro. The twitch kinematics of these so-called superfast muscles are the fastest measured in any vertebrate muscle. Superfast vocal muscles enable birds to directly control the generation of many observed rapid acoustic changes and to actuate the millisecond precision of neural activity into precise temporal vocal control. Furthermore, birds now join the list of vertebrate classes in which superfast muscle kinetics evolved independently for acoustic communication.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
United Kingdom 1 <1%
Denmark 1 <1%
Italy 1 <1%
Unknown 108 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 30%
Researcher 20 18%
Student > Bachelor 12 11%
Student > Master 10 9%
Professor 9 8%
Other 20 18%
Unknown 9 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 50%
Neuroscience 15 13%
Engineering 6 5%
Earth and Planetary Sciences 6 5%
Psychology 4 4%
Other 13 11%
Unknown 13 11%