A circular model for song motor control in Serinus canaria

ALONSO R; M. A. TREVISAN; M TREVISAN; A. AMADOR; F. GOLLER; BERNARDO GABRIEL MINDLIN

frontiers in computational neuroscience

Frontiers

Lugar: Lausanne; Año: 2015 vol. 9 p. 1 - 9

Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsongproduction, whose variables are the average activities of different neural populations within these nuclei of thesong system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a modelin which 1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and 2) a higher forebrain neural population, HVC, is sparsely active,simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve 19  these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after 20  being processed by other areas of the song system. The model is capable of reproducing the measured 21  respiratory patterns and makes specific predictions on the timing of HVC activity during their production. 22  These results suggest that vocal production is controlled by a circular network rather than by a simple top- 23  down architecture.