INVITED TALK: Low dimensional models and electrophysiological experiments to study neural dynamics in songbirds

A. AMADOR

Webinar

Conferencia; Advanced computational and experimental techniques in nonlinear dynamics; 2020

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 the production and perception of this learned motor skill.In this work, I will present a low dimensional dynamical system as a model of the avian neural network for song production. We developed a neural model in which the variables were the average activities of different neural populations within the nuclei of the song system. We performed electrophysiological experiments to record neural activity from one of these nuclei during song production in canaries (Serinus canaria) and found that the low dimensional model could reproduce the neural dynamics observed. Also, this model could reproduce the respiratory motor patterns used to generate song. We showed that sparse activity in one of the neural nuclei could drive a more complex activity downstream in the network. This interdisciplinary work shows how low dimensional models can be a valuable tool for studying the emergence of complex motor tasks.