Rhythmic Neural Oscillations Underlying Birdsong

Abstract

Birdsong is a complex motor activity that arises from the interaction between the central and peripheral nervous systems, the body, and the environment. Its striking similarities to human speech, both in production and learning, make songbirds powerful animal models for studying learned motor skills. In this talk, I will present an interdisciplinary approach to understanding the emergence of behavior. Specifically, I will show neuronal recordings from a telencephalic region involved in sensorimotor integration, revealing well-defined oscillations in local field potentials synchronized with the rhythmic structure of canary (Serinus canaria) song. I will introduce a low-dimensional mathematical model of a neural network that replicates the neural dynamics observed in the experiments. This work highlights the value of low-dimensional models as tools for exploring the neuroscience of perception and generation of complex motor behaviors.