The study of the neural mechanisms underlying the acquisition of complex behaviors is a new and intriguing area of neuroscience for which the songbird has emerged as an important model system. We have recently shown that the temporal structure of bird song may be controlled by an extremely sparse sequence of bursts in the avian premotor nucleus HVC. Preliminary recordings of antidromically identified premotor HVC neurons in the singing zebra finch show that these neurons are activated sequentially, each generating a burst of action potentials at a single precise moment of the song. Our proposal builds on these initial findings and aims to answer the following questions: What is the relation between vocal output and the sparse sequences of bursts in HVC? What is the organization and representation of motor control signals in higher premotor areas that project to HVC, such as NIf and Uva? We will use our new motorized microdrive to address the following Specific Aims:
Aim 1) To characterize the firing patterns of antidromically-identified HVC projection neurons and interneurons in the singing bird. We wish to examine the relationship between vocal output and HVC firing patterns.
Aim 2) To determine the extent to which firing patterns of HVC neurons are influenced by auditory feedback during singing.
Aim 3) To characterize the firing patterns of antidromically identified NIf neurons in singing birds.
Aim 4) Using a new head-fixed sleeping bird preparation, we will test the hypothesis that burst sequences in HVC are driven directly from higher premotor area NIf, but not Uva. The song control system represents a specialized motor circuit, evolved to produce a precisely controlled and learned motor behavior that, in many ways, is similar to human speech. An understanding of the neural circuit mechanisms underlying vocal production in the songbird should therefore have broad implications for our understanding of the dynamics and disorders of brain circuits, particularly those related to the detection, production, and learning of complex sensory and motor sequences.
Showing the most recent 10 out of 16 publications
