Birdsong to study neural control in a learned sensorimotor task

ANA AMADOR

Oaxaca

Conferencia; Third Pacific Rim Mathematical Association (PRIMA) Congress; 2017

Birdsong is a complex motor activity that emerges from the interaction between the peripheral system (PS), the central nervous system (CNS) 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 talk I will present a low dimensional dynamical system as a model of the avian vocal apparatus. Inputs can be related to physiological variables, being the output a synthetic song (SYN) that is a copy of the recorded birdsong (BOS). To go beyond sound comparison, we measured neural activity highly tuned to BOS and found that the patterns of neural response to BOS and SYN were remarkable similar. This work allowed to relate motor gestures and neural activity, making specific predictions on the timing of the neural activity. To study the dynamical emergence of these features, 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 can reproduce the measured respiratory patterns and the timing of the neural activity. In this talk, I will present experimental data in accordance with the dynamical model. This interdisciplinary work shows how low dimensional models for the PS and CNS can be a valuable tool for studying the neuroscience of generation and control of complex motor tasks.