The brain uses sensory feedback to calibrate the performance of complex behaviors. However, the neural and computational bases of sensorimotor learning remain mysterious. Our lab uses behavioral, physiological, biomechanical, and computational techniques to investigate the biological underpinnings 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 demonstrate that songbirds use vocal variability to constrain the speed and extent of vocal learning, and that the dynamics of learning across a number of experimental conditions can be understood as the result of an iterative process of Bayesian inference. Second, recent neuroanatomical and lesion studies demonstrate a crucial role for dopaminergic inputs to a basal ganglia nucleus in mediating vocal reinforcement learning. Third, neurophysiological recordings and computational analyses suggest that cortical motor neurons employ a millisecond-resolution spike timing code to regulate vocal behavior. Recent single-unit recordings from muscle tissue in behaving animals and in vitro measures of vocal biomechanics further suggest that millisecond-scale spike timing is an essential component of motor control, suggesting that reorganization of fine temporal spiking patterns might underlie vocal plasticity.