Control of Singing in Birds
The challenge of systems neurobiology is to explain behavior in terms of wiring diagrams, neuronal morphologies, synaptic weights, and other properties of the nervous system. The strength of the neuroethological approach lies in an appreciation of behavior and the profound interaction between behavioral specialization and physiological mechanism. We study birdsong learning and song recognition from this perspective.
Our main goals are to describe song learning in quantitative behavioral terms, to understand how sensory and motor aspects of the nervous system are modified during this process, and to cast this knowledge in terms of testable models. For example, at the behavioral level a syllable is a unit of song. Within the brain, how are different syllables represented? By small groups of highly specialized neurons and/or by larger groups of less specialized neurons? How do such structures develop and under what external and innate influences? What are the neural mappings of sounds onto movement and then unto muscles? Once such structures are established, what limits or facilitates their further modification? Can we use detailed quantitative descriptions of song learning to rigorously test any neuronal models of the song system we may develop?
To address these and related questions, we use a variety of approaches, including single-cell auditory neurophysiology, chronic recordings from freely-moving singing birds, neuroanatomical techniques, sophisticated computer-based systems for behavioral observation and data reduction, and (connectionist) neural network modeling
Zebra finch used in studies of singing-related neuronal activity in the nuclei HVc and robustus archistriatalis (RA).