Low dimensional dynamics in birdsong production

The way in which information about behavior is represented at different levels of the motor pathway, remains among the fundamental unresolved problems of motor coding and sensorimotor integration. Insight into this matter is essential for understanding complex learned behaviors such as speech or birdsong. A major challenge in motor coding has been to identify an appropriate framework for characterizing behavior. In this work we discuss a novel approach linking biomechanics and neurophysiology to explore motor control of songbirds. We present a model of song production based on gestures that can be related to physiological parameters that the birds can control. This physical model for the vocal structures allows a reduction in the dimensionality of the behavior, being a powerful approach for studying sensorimotor integration. Our results also show how dynamical systems models can provide insight into neurophysiological analysis of vocal motor control. In particular, our work challenges the actual understanding of how the motor pathway of the songbird systems works and proposes a novel perspective to study neural coding for song production