Integrating motor and neural control in songbirds

A. AMADOR

Puebla

Conferencia; IV Conference Dynamics Days LAC; 2016

Birdsong is a complex motor activity that emerges from the interaction between the peripheral system, the central nervous system and the environment. The similarities to human speech, both in production and learning, have positioned songbirds as unique animal models for studying this learned motor skill.In this work, we developed a low dimensional dynamical system model of the vocal apparatus in which inputs could be related to physiological variables, being the output a synthetic song (SYN) that could be compared with the recorded birdsong (BOS). To go beyond sound comparison, we measured neural activity highly tuned to BOS and found that the patterns of response to BOS and SYN were remarkable similar. This work allowed to relate motor gestures and neural activity, making specific predictions on the timing. To study the dynamical emergence of this feature, we developed a neural model in which the variables were the average activities of different neural populations within the nuclei of the song system. This model was capable of reproducing the measured respiratory patterns and matched the specific predictions on the timing of the neural activity during their production. These results suggest that vocal production is controlled by a distributed recurrent network rather than by a top-down architecture.