Resumo: Birdsong is a complex motor activity that emerges from the interaction between the central and peripheral nervous systems, with the body and the environment. The similarities with human speech, both in production and learning, have positioned songbirds as highly useful animal models to study this learned motor skill.
In this talk I will show an interdisciplinary approach to study the emergence of behavior. Specifically I will discuss a biomechanical model for song production and its validation through neural experiments. I will show how this model can be used to make predictions regarding motor control and how it can suggest a hierarchy of importance of the physiological parameters.
I will also show neuronal recordings in a telencephalic region where a sensori-motor integration occurs, showing the presence of well-defined oscillations in local field potentials, which are synchronized to the rhythm of the canary (Serinus canaria) song. I will also show that there is a correspondence between local field potentials, multiunit activity, and single unit activity within the same brain region. A low- dimensional mathematical model for a neural network will be presented that can reproduce the neural dynamics observed in the experiments.
This interdisciplinary work shows how low-dimensional models can be a valuable tool to study the neuroscience of perception, generation and control of complex motor tasks.
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