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In situ vocal fold properties and pitch prediction by dynamic actuation of the songbird syrinx

The biomechanics of sound production forms an integral part of the neuromechanical control loop of avian vocal motor control. However, we critically lack quantification of basic biomechanical parameters describing the vocal organ, the syrinx, such as material properties of syringeal elements, forces...

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Detalles Bibliográficos
Autores principales: Düring, Daniel N., Knörlein, Benjamin J., Elemans, Coen P. H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5595934/
https://www.ncbi.nlm.nih.gov/pubmed/28900151
http://dx.doi.org/10.1038/s41598-017-11258-1
Descripción
Sumario:The biomechanics of sound production forms an integral part of the neuromechanical control loop of avian vocal motor control. However, we critically lack quantification of basic biomechanical parameters describing the vocal organ, the syrinx, such as material properties of syringeal elements, forces and torques exerted on, and motion of the syringeal skeleton during song. Here, we present a novel marker-based 3D stereoscopic imaging technique to reconstruct 3D motion of servo-controlled actuation of syringeal muscle insertions sites in vitro and focus on two muscles controlling sound pitch. We furthermore combine kinematic analysis with force measurements to quantify elastic properties of sound producing medial labia (ML). The elastic modulus of the zebra finch ML is 18 kPa at 5% strain, which is comparable to elastic moduli of mammalian vocal folds. Additionally ML lengthening due to musculus syringealis ventralis (VS) shortening is intrinsically constraint at maximally 12% strain. Using these values we predict sound pitch to range from 350–800 Hz by VS modulation, corresponding well to previous observations. The presented methodology allows for quantification of syringeal skeleton motion and forces, acoustic effects of muscle recruitment, and calibration of computational birdsong models, enabling experimental access to the entire neuromechanical control loop of vocal motor control.