Sequences of actions are fundamental to many animal and human behaviors, including locomotion, playing piano, language, and logical reasoning. Sequential behaviors often follow some action syntax, which defines how elementary actions can be strung together to form complex sequences, similar to following grammatical rules in the construction of sentences. How action syntax is generated and controlled in the nervous system is poorly understood. The Bengalese finch is an ideal animal model for studying this problem, because the songs of the Bengalese finch consist of several syllables arranged into sequences with complex syntactical structures. This project will test the hypothesis that the premotor brain area HVC encodes the syntactic structure of the Bengalese finch's song. It is hypothesized that the propagation of spiking neural activity along a chain-like network structure in the HVC is driving the song of the bird and generating the song syntax. The approach combines computational modeling and single unit recordings of neural activity in the song control system of Bengalese finches. Neural recordings will be combined with altering acoustic feedback and transient electrical stimulations of the song control system to elucidate the role of the HVC in song syntax. The results of this research will have a significant impact on understanding the neural mechanisms underlying the generation of sequences of motor actions, and may also shed light on the neural mechanisms of human speech synthesis. The research brings together interdisciplinary expertise drawn from physics, computational neuroscience, and electrophysiology, and involves a wide range of modern experimental and computational techniques. Consequently, it will provide ample opportunity for postdoctoral researchers, graduate and undergraduate students, and summer high school interns to gain expertise in electrophysiology, neural data analysis and modern methods in computational neuroscience.
