Millisecond-scale, single-neuron credit assignment in a songbird

Learning an adaptive behavior requires identifying which actions, in which contexts, lead to particular outcomes. This problem of credit assignment is fundamental to both biological and artificial learners1-3. Songbird vocal learning presents a particularly demanding credit assignment problem: singing is controlled by millisecond-precise activity of thousands of motor neurons4-7, but song quality is encoded by a diffuse, delayed dopamine signal with more than an order of magnitude less temporal precision8-12. It is unknown how precisely the songbird brain can drive changes in specific premotor neurons at precise times to improve song performance. Here we show that the cortico-basal ganglia circuit thought to underlie songbird vocal learning can learn with millisecond-scale temporal precision and single-neuron spatial precision. We find that playing disruptive auditory feedback contingent on the activity of a targeted neuron in a vocal variability-generating premotor nucleus at one time in the song causes adaptive changes in the activity of the targeted neuron with 3.2 ms temporal precision. Learned changes in firing rate are not observed in uncorrelated neighboring neurons, thus revealing single-neuron spatial precision. These findings challenge the prevailing view of dopamine-mediated reinforcement as slow and imprecise13-15, and redefine our understanding of the limits of credit assignment in the brain.