Learning the microstructure of successful behavior

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Abstract
Reinforcement signals indicating success or failure are known to alter the probability of selecting between distinct actions. Here the authors examine the structure of learning at a millisecond timescale, suggesting that reinforcement can also guide learning of continuous action trajectories. Reinforcement signals indicating success or failure are known to alter the probability of selecting between distinct actions. However, successful performance of many motor skills, such as speech articulation, also requires learning behavioral trajectories that vary continuously over time. Here, we investigated how temporally discrete reinforcement signals shape a continuous behavioral trajectory, the fundamental frequency of adult Bengalese finch song. We provided reinforcement contingent on fundamental frequency performance only at one point in the song. Learned changes to fundamental frequency were maximal at this point, but also extended both earlier and later in the fundamental frequency trajectory. A simple principle predicted the detailed structure of learning: birds learned to produce the average of the behavioral trajectories associated with successful outcomes. This learning rule accurately predicted the structure of learning at a millisecond timescale, demonstrating that the nervous system records fine-grained details of successful behavior and uses this information to guide learning.

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