Automatic reconstruction of physiological gestures used in a model of birdsong production

A. AMADOR

San Rafael, Mendoza

Conferencia; XIII Congreso Regional de Física Estadística y Aplicaciones a la Materia Condensada: TREFEMAC; 2015

<!-- /* Font Definitions */@font-face{font-family:Cambria;panose-1:2 4 5 3 5 4 6 3 2 4;mso-font-charset:0;mso-generic-font-family:auto;mso-font-pitch:variable;mso-font-signature:3 0 0 0 1 0;} /* Style Definitions */p.MsoNormal, li.MsoNormal, div.MsoNormal{mso-style-parent:"";margin:0in;margin-bottom:.0001pt;mso-pagination:widow-orphan;font-size:12.0pt;font-family:"Times New Roman";mso-ascii-font-family:Cambria;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:"Times New Roman";mso-fareast-theme-font:minor-fareast;mso-hansi-font-family:Cambria;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:"Times New Roman";mso-bidi-theme-font:minor-bidi;mso-fareast-language:ES;}@page Section1{size:8.5in 11.0in;margin:1.0in 1.25in 1.0in 1.25in;mso-header-margin:.5in;mso-footer-margin:.5in;mso-paper-source:0;}div.Section1{page:Section1;}-->Birdsong production is a widelystudied example of a highly coordinated learned behavior in which numerousmuscles have to be coordinated in precise sequences to generate the elaboratevocalizations that characterize an individual?s song. We have proposed thatgiven the complexity involved, understanding the neural code for suchsophisticated motor control benefits from abandoning traditional spectrographicanalysis in favor of a recently developed low-dimensional framework for codingthe motor act. Prior studies used manual procedures to model singing behavior.In the present work, we present an automatic procedure to extract lowdimensional motor gestures that could predict vocal behavior. In particular, werecorded zebra finch songs and generated synthetic copies using a biomechanicalmodel for the vocal apparatus and vocal tract. This dynamical model describedsong as a sequence of physiological parameters the birds control duringsinging. In order to validate this procedure, we developed an experimentalsetup for performing neural recordings during the presentation of auditorystimuli. We recorded electrophysiological activity of the telencephalic nucleusHVC. HVC neurons were highly selective to the auditory presentation of thebird?s own song, and gave similar selective responses to the automaticallygenerated synthetic model of song. In this way, we showed a meaningful dimensionalityreduction in terms of physiological parameters the individual could actuallycontrol. Furthermore, this methodology can be extended to other vocal systemsto study fine motor control.