Director of Graduate Studies
Emory Neuroscience Graduate Program
The brain leans motor skills by using sensory feedback to shape complex patterns of muscle activation. However, despite the apparently effortless agility of skilled behaviors, the biological and computational bases of sensorimotor control remain mysterious. Our group combines behavioral, neurophysiological, biomechanical, and computational techniques to investigate motor control and vocal learning in songbirds. My talk will cover three ongoing lines of investigation into how songbirds correct vocal errors and precisely coordinate the acoustics of vocal production. First, our behavioral studies reveal how songbirds use vocal variability to constrain the speed and extent of vocal learning and show that a simple but powerful computational framework (iterative Bayesian inference) can account for the dynamics of learning across a number of experimental conditions. Second, neurophysiological recordings and computational analyses show that neurons in the motor system employ a millisecond-resolution spike timing code to regulate vocal behavior. Third, single-unit recordings from muscle tissue in behaving animals and in vitro measures of muscle function demonstrate how the nervous system uses precise spike timing patterns to exploit the biomechanics of the motor periphery. Finally, I will present a survey of ongoing and future research projects, emphasizing how combining experimental, analytical, and neuroengineering approaches to complex natural behaviors can yield important general insights into neural function.